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• What Is a Case Study? | Definition, Examples & Methods

What Is a Case Study? | Definition, Examples & Methods

Published on May 8, 2019 by Shona McCombes . Revised on November 20, 2023.

A case study is a detailed study of a specific subject, such as a person, group, place, event, organization, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research.

A case study research design usually involves qualitative methods , but quantitative methods are sometimes also used. Case studies are good for describing , comparing, evaluating and understanding different aspects of a research problem .

Table of contents

When to do a case study, step 1: select a case, step 2: build a theoretical framework, step 3: collect your data, step 4: describe and analyze the case, other interesting articles.

A case study is an appropriate research design when you want to gain concrete, contextual, in-depth knowledge about a specific real-world subject. It allows you to explore the key characteristics, meanings, and implications of the case.

Case studies are often a good choice in a thesis or dissertation . They keep your project focused and manageable when you don’t have the time or resources to do large-scale research.

You might use just one complex case study where you explore a single subject in depth, or conduct multiple case studies to compare and illuminate different aspects of your research problem.

Prevent plagiarism. Run a free check.

Once you have developed your problem statement and research questions , you should be ready to choose the specific case that you want to focus on. A good case study should have the potential to:

• Provide new or unexpected insights into the subject
• Challenge or complicate existing assumptions and theories
• Propose practical courses of action to resolve a problem
• Open up new directions for future research

TipIf your research is more practical in nature and aims to simultaneously investigate an issue as you solve it, consider conducting action research instead.

Unlike quantitative or experimental research , a strong case study does not require a random or representative sample. In fact, case studies often deliberately focus on unusual, neglected, or outlying cases which may shed new light on the research problem.

Example of an outlying case studyIn the 1960s the town of Roseto, Pennsylvania was discovered to have extremely low rates of heart disease compared to the US average. It became an important case study for understanding previously neglected causes of heart disease.

However, you can also choose a more common or representative case to exemplify a particular category, experience or phenomenon.

Example of a representative case studyIn the 1920s, two sociologists used Muncie, Indiana as a case study of a typical American city that supposedly exemplified the changing culture of the US at the time.

While case studies focus more on concrete details than general theories, they should usually have some connection with theory in the field. This way the case study is not just an isolated description, but is integrated into existing knowledge about the topic. It might aim to:

• Exemplify a theory by showing how it explains the case under investigation
• Expand on a theory by uncovering new concepts and ideas that need to be incorporated
• Challenge a theory by exploring an outlier case that doesn’t fit with established assumptions

To ensure that your analysis of the case has a solid academic grounding, you should conduct a literature review of sources related to the topic and develop a theoretical framework . This means identifying key concepts and theories to guide your analysis and interpretation.

There are many different research methods you can use to collect data on your subject. Case studies tend to focus on qualitative data using methods such as interviews , observations , and analysis of primary and secondary sources (e.g., newspaper articles, photographs, official records). Sometimes a case study will also collect quantitative data.

Example of a mixed methods case studyFor a case study of a wind farm development in a rural area, you could collect quantitative data on employment rates and business revenue, collect qualitative data on local people’s perceptions and experiences, and analyze local and national media coverage of the development.

The aim is to gain as thorough an understanding as possible of the case and its context.

In writing up the case study, you need to bring together all the relevant aspects to give as complete a picture as possible of the subject.

How you report your findings depends on the type of research you are doing. Some case studies are structured like a standard scientific paper or thesis , with separate sections or chapters for the methods , results and discussion .

Others are written in a more narrative style, aiming to explore the case from various angles and analyze its meanings and implications (for example, by using textual analysis or discourse analysis ).

In all cases, though, make sure to give contextual details about the case, connect it back to the literature and theory, and discuss how it fits into wider patterns or debates.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Normal distribution
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Ecological validity

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

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McCombes, S. (2023, November 20). What Is a Case Study? | Definition, Examples & Methods. Scribbr. Retrieved September 4, 2024, from https://www.scribbr.com/methodology/case-study/

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Case Study – Methods, Examples and Guide

Table of Contents

A case study is a research method that involves an in-depth examination and analysis of a particular phenomenon or case, such as an individual, organization, community, event, or situation.

It is a qualitative research approach that aims to provide a detailed and comprehensive understanding of the case being studied. Case studies typically involve multiple sources of data, including interviews, observations, documents, and artifacts, which are analyzed using various techniques, such as content analysis, thematic analysis, and grounded theory. The findings of a case study are often used to develop theories, inform policy or practice, or generate new research questions.

Types of Case Study

Types and Methods of Case Study are as follows:

Single-Case Study

A single-case study is an in-depth analysis of a single case. This type of case study is useful when the researcher wants to understand a specific phenomenon in detail.

For Example , A researcher might conduct a single-case study on a particular individual to understand their experiences with a particular health condition or a specific organization to explore their management practices. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of a single-case study are often used to generate new research questions, develop theories, or inform policy or practice.

Multiple-Case Study

A multiple-case study involves the analysis of several cases that are similar in nature. This type of case study is useful when the researcher wants to identify similarities and differences between the cases.

For Example, a researcher might conduct a multiple-case study on several companies to explore the factors that contribute to their success or failure. The researcher collects data from each case, compares and contrasts the findings, and uses various techniques to analyze the data, such as comparative analysis or pattern-matching. The findings of a multiple-case study can be used to develop theories, inform policy or practice, or generate new research questions.

Exploratory Case Study

An exploratory case study is used to explore a new or understudied phenomenon. This type of case study is useful when the researcher wants to generate hypotheses or theories about the phenomenon.

For Example, a researcher might conduct an exploratory case study on a new technology to understand its potential impact on society. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as grounded theory or content analysis. The findings of an exploratory case study can be used to generate new research questions, develop theories, or inform policy or practice.

Descriptive Case Study

A descriptive case study is used to describe a particular phenomenon in detail. This type of case study is useful when the researcher wants to provide a comprehensive account of the phenomenon.

For Example, a researcher might conduct a descriptive case study on a particular community to understand its social and economic characteristics. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of a descriptive case study can be used to inform policy or practice or generate new research questions.

Instrumental Case Study

An instrumental case study is used to understand a particular phenomenon that is instrumental in achieving a particular goal. This type of case study is useful when the researcher wants to understand the role of the phenomenon in achieving the goal.

For Example, a researcher might conduct an instrumental case study on a particular policy to understand its impact on achieving a particular goal, such as reducing poverty. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of an instrumental case study can be used to inform policy or practice or generate new research questions.

Case Study Data Collection Methods

Here are some common data collection methods for case studies:

Interviews involve asking questions to individuals who have knowledge or experience relevant to the case study. Interviews can be structured (where the same questions are asked to all participants) or unstructured (where the interviewer follows up on the responses with further questions). Interviews can be conducted in person, over the phone, or through video conferencing.

Observations

Observations involve watching and recording the behavior and activities of individuals or groups relevant to the case study. Observations can be participant (where the researcher actively participates in the activities) or non-participant (where the researcher observes from a distance). Observations can be recorded using notes, audio or video recordings, or photographs.

Documents can be used as a source of information for case studies. Documents can include reports, memos, emails, letters, and other written materials related to the case study. Documents can be collected from the case study participants or from public sources.

Surveys involve asking a set of questions to a sample of individuals relevant to the case study. Surveys can be administered in person, over the phone, through mail or email, or online. Surveys can be used to gather information on attitudes, opinions, or behaviors related to the case study.

Artifacts are physical objects relevant to the case study. Artifacts can include tools, equipment, products, or other objects that provide insights into the case study phenomenon.

How to conduct Case Study Research

Conducting a case study research involves several steps that need to be followed to ensure the quality and rigor of the study. Here are the steps to conduct case study research:

• Define the research questions: The first step in conducting a case study research is to define the research questions. The research questions should be specific, measurable, and relevant to the case study phenomenon under investigation.
• Select the case: The next step is to select the case or cases to be studied. The case should be relevant to the research questions and should provide rich and diverse data that can be used to answer the research questions.
• Collect data: Data can be collected using various methods, such as interviews, observations, documents, surveys, and artifacts. The data collection method should be selected based on the research questions and the nature of the case study phenomenon.
• Analyze the data: The data collected from the case study should be analyzed using various techniques, such as content analysis, thematic analysis, or grounded theory. The analysis should be guided by the research questions and should aim to provide insights and conclusions relevant to the research questions.
• Draw conclusions: The conclusions drawn from the case study should be based on the data analysis and should be relevant to the research questions. The conclusions should be supported by evidence and should be clearly stated.
• Validate the findings: The findings of the case study should be validated by reviewing the data and the analysis with participants or other experts in the field. This helps to ensure the validity and reliability of the findings.
• Write the report: The final step is to write the report of the case study research. The report should provide a clear description of the case study phenomenon, the research questions, the data collection methods, the data analysis, the findings, and the conclusions. The report should be written in a clear and concise manner and should follow the guidelines for academic writing.

Examples of Case Study

Here are some examples of case study research:

• The Hawthorne Studies : Conducted between 1924 and 1932, the Hawthorne Studies were a series of case studies conducted by Elton Mayo and his colleagues to examine the impact of work environment on employee productivity. The studies were conducted at the Hawthorne Works plant of the Western Electric Company in Chicago and included interviews, observations, and experiments.
• The Stanford Prison Experiment: Conducted in 1971, the Stanford Prison Experiment was a case study conducted by Philip Zimbardo to examine the psychological effects of power and authority. The study involved simulating a prison environment and assigning participants to the role of guards or prisoners. The study was controversial due to the ethical issues it raised.
• The Challenger Disaster: The Challenger Disaster was a case study conducted to examine the causes of the Space Shuttle Challenger explosion in 1986. The study included interviews, observations, and analysis of data to identify the technical, organizational, and cultural factors that contributed to the disaster.
• The Enron Scandal: The Enron Scandal was a case study conducted to examine the causes of the Enron Corporation’s bankruptcy in 2001. The study included interviews, analysis of financial data, and review of documents to identify the accounting practices, corporate culture, and ethical issues that led to the company’s downfall.
• The Fukushima Nuclear Disaster : The Fukushima Nuclear Disaster was a case study conducted to examine the causes of the nuclear accident that occurred at the Fukushima Daiichi Nuclear Power Plant in Japan in 2011. The study included interviews, analysis of data, and review of documents to identify the technical, organizational, and cultural factors that contributed to the disaster.

Application of Case Study

Case studies have a wide range of applications across various fields and industries. Here are some examples:

Business and Management

Case studies are widely used in business and management to examine real-life situations and develop problem-solving skills. Case studies can help students and professionals to develop a deep understanding of business concepts, theories, and best practices.

Case studies are used in healthcare to examine patient care, treatment options, and outcomes. Case studies can help healthcare professionals to develop critical thinking skills, diagnose complex medical conditions, and develop effective treatment plans.

Case studies are used in education to examine teaching and learning practices. Case studies can help educators to develop effective teaching strategies, evaluate student progress, and identify areas for improvement.

Social Sciences

Case studies are widely used in social sciences to examine human behavior, social phenomena, and cultural practices. Case studies can help researchers to develop theories, test hypotheses, and gain insights into complex social issues.

Law and Ethics

Case studies are used in law and ethics to examine legal and ethical dilemmas. Case studies can help lawyers, policymakers, and ethical professionals to develop critical thinking skills, analyze complex cases, and make informed decisions.

Purpose of Case Study

The purpose of a case study is to provide a detailed analysis of a specific phenomenon, issue, or problem in its real-life context. A case study is a qualitative research method that involves the in-depth exploration and analysis of a particular case, which can be an individual, group, organization, event, or community.

The primary purpose of a case study is to generate a comprehensive and nuanced understanding of the case, including its history, context, and dynamics. Case studies can help researchers to identify and examine the underlying factors, processes, and mechanisms that contribute to the case and its outcomes. This can help to develop a more accurate and detailed understanding of the case, which can inform future research, practice, or policy.

Case studies can also serve other purposes, including:

• Illustrating a theory or concept: Case studies can be used to illustrate and explain theoretical concepts and frameworks, providing concrete examples of how they can be applied in real-life situations.
• Developing hypotheses: Case studies can help to generate hypotheses about the causal relationships between different factors and outcomes, which can be tested through further research.
• Providing insight into complex issues: Case studies can provide insights into complex and multifaceted issues, which may be difficult to understand through other research methods.
• Informing practice or policy: Case studies can be used to inform practice or policy by identifying best practices, lessons learned, or areas for improvement.

Advantages of Case Study Research

There are several advantages of case study research, including:

• In-depth exploration: Case study research allows for a detailed exploration and analysis of a specific phenomenon, issue, or problem in its real-life context. This can provide a comprehensive understanding of the case and its dynamics, which may not be possible through other research methods.
• Rich data: Case study research can generate rich and detailed data, including qualitative data such as interviews, observations, and documents. This can provide a nuanced understanding of the case and its complexity.
• Holistic perspective: Case study research allows for a holistic perspective of the case, taking into account the various factors, processes, and mechanisms that contribute to the case and its outcomes. This can help to develop a more accurate and comprehensive understanding of the case.
• Theory development: Case study research can help to develop and refine theories and concepts by providing empirical evidence and concrete examples of how they can be applied in real-life situations.
• Practical application: Case study research can inform practice or policy by identifying best practices, lessons learned, or areas for improvement.
• Contextualization: Case study research takes into account the specific context in which the case is situated, which can help to understand how the case is influenced by the social, cultural, and historical factors of its environment.

Limitations of Case Study Research

There are several limitations of case study research, including:

• Limited generalizability : Case studies are typically focused on a single case or a small number of cases, which limits the generalizability of the findings. The unique characteristics of the case may not be applicable to other contexts or populations, which may limit the external validity of the research.
• Biased sampling: Case studies may rely on purposive or convenience sampling, which can introduce bias into the sample selection process. This may limit the representativeness of the sample and the generalizability of the findings.
• Subjectivity: Case studies rely on the interpretation of the researcher, which can introduce subjectivity into the analysis. The researcher’s own biases, assumptions, and perspectives may influence the findings, which may limit the objectivity of the research.
• Limited control: Case studies are typically conducted in naturalistic settings, which limits the control that the researcher has over the environment and the variables being studied. This may limit the ability to establish causal relationships between variables.
• Time-consuming: Case studies can be time-consuming to conduct, as they typically involve a detailed exploration and analysis of a specific case. This may limit the feasibility of conducting multiple case studies or conducting case studies in a timely manner.
• Resource-intensive: Case studies may require significant resources, including time, funding, and expertise. This may limit the ability of researchers to conduct case studies in resource-constrained settings.

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• Knowledge Base
• Methodology
• Case Study | Definition, Examples & Methods

Case Study | Definition, Examples & Methods

Published on 5 May 2022 by Shona McCombes . Revised on 30 January 2023.

A case study is a detailed study of a specific subject, such as a person, group, place, event, organisation, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research.

A case study research design usually involves qualitative methods , but quantitative methods are sometimes also used. Case studies are good for describing , comparing, evaluating, and understanding different aspects of a research problem .

Table of contents

When to do a case study, step 1: select a case, step 2: build a theoretical framework, step 3: collect your data, step 4: describe and analyse the case.

A case study is an appropriate research design when you want to gain concrete, contextual, in-depth knowledge about a specific real-world subject. It allows you to explore the key characteristics, meanings, and implications of the case.

Case studies are often a good choice in a thesis or dissertation . They keep your project focused and manageable when you don’t have the time or resources to do large-scale research.

You might use just one complex case study where you explore a single subject in depth, or conduct multiple case studies to compare and illuminate different aspects of your research problem.

Prevent plagiarism, run a free check.

Once you have developed your problem statement and research questions , you should be ready to choose the specific case that you want to focus on. A good case study should have the potential to:

• Provide new or unexpected insights into the subject
• Challenge or complicate existing assumptions and theories
• Propose practical courses of action to resolve a problem
• Open up new directions for future research

Unlike quantitative or experimental research, a strong case study does not require a random or representative sample. In fact, case studies often deliberately focus on unusual, neglected, or outlying cases which may shed new light on the research problem.

If you find yourself aiming to simultaneously investigate and solve an issue, consider conducting action research . As its name suggests, action research conducts research and takes action at the same time, and is highly iterative and flexible. 

However, you can also choose a more common or representative case to exemplify a particular category, experience, or phenomenon.

While case studies focus more on concrete details than general theories, they should usually have some connection with theory in the field. This way the case study is not just an isolated description, but is integrated into existing knowledge about the topic. It might aim to:

• Exemplify a theory by showing how it explains the case under investigation
• Expand on a theory by uncovering new concepts and ideas that need to be incorporated
• Challenge a theory by exploring an outlier case that doesn’t fit with established assumptions

To ensure that your analysis of the case has a solid academic grounding, you should conduct a literature review of sources related to the topic and develop a theoretical framework . This means identifying key concepts and theories to guide your analysis and interpretation.

There are many different research methods you can use to collect data on your subject. Case studies tend to focus on qualitative data using methods such as interviews, observations, and analysis of primary and secondary sources (e.g., newspaper articles, photographs, official records). Sometimes a case study will also collect quantitative data .

The aim is to gain as thorough an understanding as possible of the case and its context.

In writing up the case study, you need to bring together all the relevant aspects to give as complete a picture as possible of the subject.

How you report your findings depends on the type of research you are doing. Some case studies are structured like a standard scientific paper or thesis, with separate sections or chapters for the methods , results , and discussion .

Others are written in a more narrative style, aiming to explore the case from various angles and analyse its meanings and implications (for example, by using textual analysis or discourse analysis ).

In all cases, though, make sure to give contextual details about the case, connect it back to the literature and theory, and discuss how it fits into wider patterns or debates.

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McCombes, S. (2023, January 30). Case Study | Definition, Examples & Methods. Scribbr. Retrieved 3 September 2024, from https://www.scribbr.co.uk/research-methods/case-studies/

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A case study research paper examines a person, place, event, condition, phenomenon, or other type of subject of analysis in order to extrapolate  key themes and results that help predict future trends, illuminate previously hidden issues that can be applied to practice, and/or provide a means for understanding an important research problem with greater clarity. A case study research paper usually examines a single subject of analysis, but case study papers can also be designed as a comparative investigation that shows relationships between two or more subjects. The methods used to study a case can rest within a quantitative, qualitative, or mixed-method investigative paradigm.

Case Studies. Writing@CSU. Colorado State University; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010 ; “What is a Case Study?” In Swanborn, Peter G. Case Study Research: What, Why and How? London: SAGE, 2010.

How to Approach Writing a Case Study Research Paper

General information about how to choose a topic to investigate can be found under the " Choosing a Research Problem " tab in the Organizing Your Social Sciences Research Paper writing guide. Review this page because it may help you identify a subject of analysis that can be investigated using a case study design.

However, identifying a case to investigate involves more than choosing the research problem . A case study encompasses a problem contextualized around the application of in-depth analysis, interpretation, and discussion, often resulting in specific recommendations for action or for improving existing conditions. As Seawright and Gerring note, practical considerations such as time and access to information can influence case selection, but these issues should not be the sole factors used in describing the methodological justification for identifying a particular case to study. Given this, selecting a case includes considering the following:

• The case represents an unusual or atypical example of a research problem that requires more in-depth analysis? Cases often represent a topic that rests on the fringes of prior investigations because the case may provide new ways of understanding the research problem. For example, if the research problem is to identify strategies to improve policies that support girl's access to secondary education in predominantly Muslim nations, you could consider using Azerbaijan as a case study rather than selecting a more obvious nation in the Middle East. Doing so may reveal important new insights into recommending how governments in other predominantly Muslim nations can formulate policies that support improved access to education for girls.
• The case provides important insight or illuminate a previously hidden problem? In-depth analysis of a case can be based on the hypothesis that the case study will reveal trends or issues that have not been exposed in prior research or will reveal new and important implications for practice. For example, anecdotal evidence may suggest drug use among homeless veterans is related to their patterns of travel throughout the day. Assuming prior studies have not looked at individual travel choices as a way to study access to illicit drug use, a case study that observes a homeless veteran could reveal how issues of personal mobility choices facilitate regular access to illicit drugs. Note that it is important to conduct a thorough literature review to ensure that your assumption about the need to reveal new insights or previously hidden problems is valid and evidence-based.
• The case challenges and offers a counter-point to prevailing assumptions? Over time, research on any given topic can fall into a trap of developing assumptions based on outdated studies that are still applied to new or changing conditions or the idea that something should simply be accepted as "common sense," even though the issue has not been thoroughly tested in current practice. A case study analysis may offer an opportunity to gather evidence that challenges prevailing assumptions about a research problem and provide a new set of recommendations applied to practice that have not been tested previously. For example, perhaps there has been a long practice among scholars to apply a particular theory in explaining the relationship between two subjects of analysis. Your case could challenge this assumption by applying an innovative theoretical framework [perhaps borrowed from another discipline] to explore whether this approach offers new ways of understanding the research problem. Taking a contrarian stance is one of the most important ways that new knowledge and understanding develops from existing literature.
• The case provides an opportunity to pursue action leading to the resolution of a problem? Another way to think about choosing a case to study is to consider how the results from investigating a particular case may result in findings that reveal ways in which to resolve an existing or emerging problem. For example, studying the case of an unforeseen incident, such as a fatal accident at a railroad crossing, can reveal hidden issues that could be applied to preventative measures that contribute to reducing the chance of accidents in the future. In this example, a case study investigating the accident could lead to a better understanding of where to strategically locate additional signals at other railroad crossings so as to better warn drivers of an approaching train, particularly when visibility is hindered by heavy rain, fog, or at night.
• The case offers a new direction in future research? A case study can be used as a tool for an exploratory investigation that highlights the need for further research about the problem. A case can be used when there are few studies that help predict an outcome or that establish a clear understanding about how best to proceed in addressing a problem. For example, after conducting a thorough literature review [very important!], you discover that little research exists showing the ways in which women contribute to promoting water conservation in rural communities of east central Africa. A case study of how women contribute to saving water in a rural village of Uganda can lay the foundation for understanding the need for more thorough research that documents how women in their roles as cooks and family caregivers think about water as a valuable resource within their community. This example of a case study could also point to the need for scholars to build new theoretical frameworks around the topic [e.g., applying feminist theories of work and family to the issue of water conservation].

Eisenhardt, Kathleen M. “Building Theories from Case Study Research.” Academy of Management Review 14 (October 1989): 532-550; Emmel, Nick. Sampling and Choosing Cases in Qualitative Research: A Realist Approach . Thousand Oaks, CA: SAGE Publications, 2013; Gerring, John. “What Is a Case Study and What Is It Good for?” American Political Science Review 98 (May 2004): 341-354; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Seawright, Jason and John Gerring. "Case Selection Techniques in Case Study Research." Political Research Quarterly 61 (June 2008): 294-308.

Structure and Writing Style

The purpose of a paper in the social sciences designed around a case study is to thoroughly investigate a subject of analysis in order to reveal a new understanding about the research problem and, in so doing, contributing new knowledge to what is already known from previous studies. In applied social sciences disciplines [e.g., education, social work, public administration, etc.], case studies may also be used to reveal best practices, highlight key programs, or investigate interesting aspects of professional work.

In general, the structure of a case study research paper is not all that different from a standard college-level research paper. However, there are subtle differences you should be aware of. Here are the key elements to organizing and writing a case study research paper.

I.  Introduction

As with any research paper, your introduction should serve as a roadmap for your readers to ascertain the scope and purpose of your study . The introduction to a case study research paper, however, should not only describe the research problem and its significance, but you should also succinctly describe why the case is being used and how it relates to addressing the problem. The two elements should be linked. With this in mind, a good introduction answers these four questions:

• What is being studied? Describe the research problem and describe the subject of analysis [the case] you have chosen to address the problem. Explain how they are linked and what elements of the case will help to expand knowledge and understanding about the problem.
• Why is this topic important to investigate? Describe the significance of the research problem and state why a case study design and the subject of analysis that the paper is designed around is appropriate in addressing the problem.
• What did we know about this topic before I did this study? Provide background that helps lead the reader into the more in-depth literature review to follow. If applicable, summarize prior case study research applied to the research problem and why it fails to adequately address the problem. Describe why your case will be useful. If no prior case studies have been used to address the research problem, explain why you have selected this subject of analysis.
• How will this study advance new knowledge or new ways of understanding? Explain why your case study will be suitable in helping to expand knowledge and understanding about the research problem.

Each of these questions should be addressed in no more than a few paragraphs. Exceptions to this can be when you are addressing a complex research problem or subject of analysis that requires more in-depth background information.

II.  Literature Review

The literature review for a case study research paper is generally structured the same as it is for any college-level research paper. The difference, however, is that the literature review is focused on providing background information and  enabling historical interpretation of the subject of analysis in relation to the research problem the case is intended to address . This includes synthesizing studies that help to:

• Place relevant works in the context of their contribution to understanding the case study being investigated . This would involve summarizing studies that have used a similar subject of analysis to investigate the research problem. If there is literature using the same or a very similar case to study, you need to explain why duplicating past research is important [e.g., conditions have changed; prior studies were conducted long ago, etc.].
• Describe the relationship each work has to the others under consideration that informs the reader why this case is applicable . Your literature review should include a description of any works that support using the case to investigate the research problem and the underlying research questions.
• Identify new ways to interpret prior research using the case study . If applicable, review any research that has examined the research problem using a different research design. Explain how your use of a case study design may reveal new knowledge or a new perspective or that can redirect research in an important new direction.
• Resolve conflicts amongst seemingly contradictory previous studies . This refers to synthesizing any literature that points to unresolved issues of concern about the research problem and describing how the subject of analysis that forms the case study can help resolve these existing contradictions.
• Point the way in fulfilling a need for additional research . Your review should examine any literature that lays a foundation for understanding why your case study design and the subject of analysis around which you have designed your study may reveal a new way of approaching the research problem or offer a perspective that points to the need for additional research.
• Expose any gaps that exist in the literature that the case study could help to fill . Summarize any literature that not only shows how your subject of analysis contributes to understanding the research problem, but how your case contributes to a new way of understanding the problem that prior research has failed to do.
• Locate your own research within the context of existing literature [very important!] . Collectively, your literature review should always place your case study within the larger domain of prior research about the problem. The overarching purpose of reviewing pertinent literature in a case study paper is to demonstrate that you have thoroughly identified and synthesized prior studies in relation to explaining the relevance of the case in addressing the research problem.

III.  Method

In this section, you explain why you selected a particular case [i.e., subject of analysis] and the strategy you used to identify and ultimately decide that your case was appropriate in addressing the research problem. The way you describe the methods used varies depending on the type of subject of analysis that constitutes your case study.

If your subject of analysis is an incident or event . In the social and behavioral sciences, the event or incident that represents the case to be studied is usually bounded by time and place, with a clear beginning and end and with an identifiable location or position relative to its surroundings. The subject of analysis can be a rare or critical event or it can focus on a typical or regular event. The purpose of studying a rare event is to illuminate new ways of thinking about the broader research problem or to test a hypothesis. Critical incident case studies must describe the method by which you identified the event and explain the process by which you determined the validity of this case to inform broader perspectives about the research problem or to reveal new findings. However, the event does not have to be a rare or uniquely significant to support new thinking about the research problem or to challenge an existing hypothesis. For example, Walo, Bull, and Breen conducted a case study to identify and evaluate the direct and indirect economic benefits and costs of a local sports event in the City of Lismore, New South Wales, Australia. The purpose of their study was to provide new insights from measuring the impact of a typical local sports event that prior studies could not measure well because they focused on large "mega-events." Whether the event is rare or not, the methods section should include an explanation of the following characteristics of the event: a) when did it take place; b) what were the underlying circumstances leading to the event; and, c) what were the consequences of the event in relation to the research problem.

If your subject of analysis is a person. Explain why you selected this particular individual to be studied and describe what experiences they have had that provide an opportunity to advance new understandings about the research problem. Mention any background about this person which might help the reader understand the significance of their experiences that make them worthy of study. This includes describing the relationships this person has had with other people, institutions, and/or events that support using them as the subject for a case study research paper. It is particularly important to differentiate the person as the subject of analysis from others and to succinctly explain how the person relates to examining the research problem [e.g., why is one politician in a particular local election used to show an increase in voter turnout from any other candidate running in the election]. Note that these issues apply to a specific group of people used as a case study unit of analysis [e.g., a classroom of students].

If your subject of analysis is a place. In general, a case study that investigates a place suggests a subject of analysis that is unique or special in some way and that this uniqueness can be used to build new understanding or knowledge about the research problem. A case study of a place must not only describe its various attributes relevant to the research problem [e.g., physical, social, historical, cultural, economic, political], but you must state the method by which you determined that this place will illuminate new understandings about the research problem. It is also important to articulate why a particular place as the case for study is being used if similar places also exist [i.e., if you are studying patterns of homeless encampments of veterans in open spaces, explain why you are studying Echo Park in Los Angeles rather than Griffith Park?]. If applicable, describe what type of human activity involving this place makes it a good choice to study [e.g., prior research suggests Echo Park has more homeless veterans].

If your subject of analysis is a phenomenon. A phenomenon refers to a fact, occurrence, or circumstance that can be studied or observed but with the cause or explanation to be in question. In this sense, a phenomenon that forms your subject of analysis can encompass anything that can be observed or presumed to exist but is not fully understood. In the social and behavioral sciences, the case usually focuses on human interaction within a complex physical, social, economic, cultural, or political system. For example, the phenomenon could be the observation that many vehicles used by ISIS fighters are small trucks with English language advertisements on them. The research problem could be that ISIS fighters are difficult to combat because they are highly mobile. The research questions could be how and by what means are these vehicles used by ISIS being supplied to the militants and how might supply lines to these vehicles be cut off? How might knowing the suppliers of these trucks reveal larger networks of collaborators and financial support? A case study of a phenomenon most often encompasses an in-depth analysis of a cause and effect that is grounded in an interactive relationship between people and their environment in some way.

NOTE:   The choice of the case or set of cases to study cannot appear random. Evidence that supports the method by which you identified and chose your subject of analysis should clearly support investigation of the research problem and linked to key findings from your literature review. Be sure to cite any studies that helped you determine that the case you chose was appropriate for examining the problem.

IV.  Discussion

The main elements of your discussion section are generally the same as any research paper, but centered around interpreting and drawing conclusions about the key findings from your analysis of the case study. Note that a general social sciences research paper may contain a separate section to report findings. However, in a paper designed around a case study, it is common to combine a description of the results with the discussion about their implications. The objectives of your discussion section should include the following:

Reiterate the Research Problem/State the Major Findings Briefly reiterate the research problem you are investigating and explain why the subject of analysis around which you designed the case study were used. You should then describe the findings revealed from your study of the case using direct, declarative, and succinct proclamation of the study results. Highlight any findings that were unexpected or especially profound.

Explain the Meaning of the Findings and Why They are Important Systematically explain the meaning of your case study findings and why you believe they are important. Begin this part of the section by repeating what you consider to be your most important or surprising finding first, then systematically review each finding. Be sure to thoroughly extrapolate what your analysis of the case can tell the reader about situations or conditions beyond the actual case that was studied while, at the same time, being careful not to misconstrue or conflate a finding that undermines the external validity of your conclusions.

Relate the Findings to Similar Studies No study in the social sciences is so novel or possesses such a restricted focus that it has absolutely no relation to previously published research. The discussion section should relate your case study results to those found in other studies, particularly if questions raised from prior studies served as the motivation for choosing your subject of analysis. This is important because comparing and contrasting the findings of other studies helps support the overall importance of your results and it highlights how and in what ways your case study design and the subject of analysis differs from prior research about the topic.

Consider Alternative Explanations of the Findings Remember that the purpose of social science research is to discover and not to prove. When writing the discussion section, you should carefully consider all possible explanations revealed by the case study results, rather than just those that fit your hypothesis or prior assumptions and biases. Be alert to what the in-depth analysis of the case may reveal about the research problem, including offering a contrarian perspective to what scholars have stated in prior research if that is how the findings can be interpreted from your case.

Acknowledge the Study's Limitations You can state the study's limitations in the conclusion section of your paper but describing the limitations of your subject of analysis in the discussion section provides an opportunity to identify the limitations and explain why they are not significant. This part of the discussion section should also note any unanswered questions or issues your case study could not address. More detailed information about how to document any limitations to your research can be found here .

Suggest Areas for Further Research Although your case study may offer important insights about the research problem, there are likely additional questions related to the problem that remain unanswered or findings that unexpectedly revealed themselves as a result of your in-depth analysis of the case. Be sure that the recommendations for further research are linked to the research problem and that you explain why your recommendations are valid in other contexts and based on the original assumptions of your study.

V.  Conclusion

As with any research paper, you should summarize your conclusion in clear, simple language; emphasize how the findings from your case study differs from or supports prior research and why. Do not simply reiterate the discussion section. Provide a synthesis of key findings presented in the paper to show how these converge to address the research problem. If you haven't already done so in the discussion section, be sure to document the limitations of your case study and any need for further research.

The function of your paper's conclusion is to: 1) reiterate the main argument supported by the findings from your case study; 2) state clearly the context, background, and necessity of pursuing the research problem using a case study design in relation to an issue, controversy, or a gap found from reviewing the literature; and, 3) provide a place to persuasively and succinctly restate the significance of your research problem, given that the reader has now been presented with in-depth information about the topic.

Consider the following points to help ensure your conclusion is appropriate:

• If the argument or purpose of your paper is complex, you may need to summarize these points for your reader.
• If prior to your conclusion, you have not yet explained the significance of your findings or if you are proceeding inductively, use the conclusion of your paper to describe your main points and explain their significance.
• Move from a detailed to a general level of consideration of the case study's findings that returns the topic to the context provided by the introduction or within a new context that emerges from your case study findings.

Note that, depending on the discipline you are writing in or the preferences of your professor, the concluding paragraph may contain your final reflections on the evidence presented as it applies to practice or on the essay's central research problem. However, the nature of being introspective about the subject of analysis you have investigated will depend on whether you are explicitly asked to express your observations in this way.

Problems to Avoid

Overgeneralization One of the goals of a case study is to lay a foundation for understanding broader trends and issues applied to similar circumstances. However, be careful when drawing conclusions from your case study. They must be evidence-based and grounded in the results of the study; otherwise, it is merely speculation. Looking at a prior example, it would be incorrect to state that a factor in improving girls access to education in Azerbaijan and the policy implications this may have for improving access in other Muslim nations is due to girls access to social media if there is no documentary evidence from your case study to indicate this. There may be anecdotal evidence that retention rates were better for girls who were engaged with social media, but this observation would only point to the need for further research and would not be a definitive finding if this was not a part of your original research agenda.

Failure to Document Limitations No case is going to reveal all that needs to be understood about a research problem. Therefore, just as you have to clearly state the limitations of a general research study , you must describe the specific limitations inherent in the subject of analysis. For example, the case of studying how women conceptualize the need for water conservation in a village in Uganda could have limited application in other cultural contexts or in areas where fresh water from rivers or lakes is plentiful and, therefore, conservation is understood more in terms of managing access rather than preserving access to a scarce resource.

Failure to Extrapolate All Possible Implications Just as you don't want to over-generalize from your case study findings, you also have to be thorough in the consideration of all possible outcomes or recommendations derived from your findings. If you do not, your reader may question the validity of your analysis, particularly if you failed to document an obvious outcome from your case study research. For example, in the case of studying the accident at the railroad crossing to evaluate where and what types of warning signals should be located, you failed to take into consideration speed limit signage as well as warning signals. When designing your case study, be sure you have thoroughly addressed all aspects of the problem and do not leave gaps in your analysis that leave the reader questioning the results.

Case Studies. Writing@CSU. Colorado State University; Gerring, John. Case Study Research: Principles and Practices . New York: Cambridge University Press, 2007; Merriam, Sharan B. Qualitative Research and Case Study Applications in Education . Rev. ed. San Francisco, CA: Jossey-Bass, 1998; Miller, Lisa L. “The Use of Case Studies in Law and Social Science Research.” Annual Review of Law and Social Science 14 (2018): TBD; Mills, Albert J., Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Putney, LeAnn Grogan. "Case Study." In Encyclopedia of Research Design , Neil J. Salkind, editor. (Thousand Oaks, CA: SAGE Publications, 2010), pp. 116-120; Simons, Helen. Case Study Research in Practice . London: SAGE Publications, 2009;  Kratochwill,  Thomas R. and Joel R. Levin, editors. Single-Case Research Design and Analysis: New Development for Psychology and Education .  Hilldsale, NJ: Lawrence Erlbaum Associates, 1992; Swanborn, Peter G. Case Study Research: What, Why and How? London : SAGE, 2010; Yin, Robert K. Case Study Research: Design and Methods . 6th edition. Los Angeles, CA, SAGE Publications, 2014; Walo, Maree, Adrian Bull, and Helen Breen. “Achieving Economic Benefits at Local Events: A Case Study of a Local Sports Event.” Festival Management and Event Tourism 4 (1996): 95-106.

Writing Tip

At Least Five Misconceptions about Case Study Research

Social science case studies are often perceived as limited in their ability to create new knowledge because they are not randomly selected and findings cannot be generalized to larger populations. Flyvbjerg examines five misunderstandings about case study research and systematically "corrects" each one. To quote, these are:

Misunderstanding 1 :  General, theoretical [context-independent] knowledge is more valuable than concrete, practical [context-dependent] knowledge. Misunderstanding 2 :  One cannot generalize on the basis of an individual case; therefore, the case study cannot contribute to scientific development. Misunderstanding 3 :  The case study is most useful for generating hypotheses; that is, in the first stage of a total research process, whereas other methods are more suitable for hypotheses testing and theory building. Misunderstanding 4 :  The case study contains a bias toward verification, that is, a tendency to confirm the researcher’s preconceived notions. Misunderstanding 5 :  It is often difficult to summarize and develop general propositions and theories on the basis of specific case studies [p. 221].

While writing your paper, think introspectively about how you addressed these misconceptions because to do so can help you strengthen the validity and reliability of your research by clarifying issues of case selection, the testing and challenging of existing assumptions, the interpretation of key findings, and the summation of case outcomes. Think of a case study research paper as a complete, in-depth narrative about the specific properties and key characteristics of your subject of analysis applied to the research problem.

Flyvbjerg, Bent. “Five Misunderstandings About Case-Study Research.” Qualitative Inquiry 12 (April 2006): 219-245.

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Qualitative Research Designs

Case study design, using case study design in the applied doctoral experience (ade), applicability of case study design to applied problem of practice, case study design references.

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The field of qualitative research there are a number of research designs (also referred to as “traditions” or “genres”), including case study, phenomenology, narrative inquiry, action research, ethnography, grounded theory, as well as a number of critical genres including Feminist theory, indigenous research, critical race theory and cultural studies. The choice of research design is directly tied to and must be aligned with your research problem and purpose. As Bloomberg & Volpe (2019) explain:

Choice of research design is directly tied to research problem and purpose. As the researcher, you actively create the link among problem, purpose, and design through a process of reflecting on problem and purpose, focusing on researchable questions, and considering how to best address these questions. Thinking along these lines affords a research study methodological congruence (p. 38).

Case study is an in-depth exploration from multiple perspectives of a bounded social phenomenon, be this a social system such as a program, event, institution, organization, or community (Stake, 1995, 2005; Yin, 2018). Case study is employed across disciplines, including education, health care, social work, sociology, and organizational studies. The purpose is to generate understanding and deep insights to inform professional practice, policy development, and community or social action (Bloomberg 2018).

Yin (2018) and Stake (1995, 2005), two of the key proponents of case study methodology, use different terms to describe case studies. Yin categorizes case studies as exploratory or descriptive . The former is used to explore those situations in which the intervention being evaluated has no clear single set of outcomes. The latter is used to describe an intervention or phenomenon and the real-life context in which it occurred. Stake identifies case studies as intrinsic or instrumental , and he proposes that a primary distinction in designing case studies is between single and multiple (or collective) case study designs. A single case study may be an instrumental case study (research focuses on an issue or concern in one bounded case) or an intrinsic case study (the focus is on the case itself because the case presents a unique situation). A longitudinal case study design is chosen when the researcher seeks to examine the same single case at two or more different points in time or to capture trends over time. A multiple case study design is used when a researcher seeks to determine the prevalence or frequency of a particular phenomenon. This approach is useful when cases are used for purposes of a cross-case analysis in order to compare, contrast, and synthesize perspectives regarding the same issue. The focus is on the analysis of diverse cases to determine how these confirm the findings within or between cases, or call the findings into question.

Case study affords significant interaction with research participants, providing an in-depth picture of the phenomenon (Bloomberg & Volpe, 2019). Research is extensive, drawing on multiple methods of data collection, and involves multiple data sources. Triangulation is critical in attempting to obtain an in-depth understanding of the phenomenon under study and adds rigor, breadth, and depth to the study and provides corroborative evidence of the data obtained. Analysis of data can be holistic or embedded—that is, dealing with the whole or parts of the case (Yin, 2018). With multiple cases the typical analytic strategy is to provide detailed description of themes within each case (within-case analysis), followed by thematic analysis across cases (cross-case analysis), providing insights regarding how individual cases are comparable along important dimensions. Research culminates in the production of a detailed description of a setting and its participants, accompanied by an analysis of the data for themes or patterns (Stake, 1995, 2005; Yin, 2018). In addition to thick, rich description, the researcher’s interpretations, conclusions, and recommendations contribute to the reader’s overall understanding of the case study.

Analysis of findings should show that the researcher has attended to all the data, should address the most significant aspects of the case, and should demonstrate familiarity with the prevailing thinking and discourse about the topic. The goal of case study design (as with all qualitative designs) is not generalizability but rather transferability —that is, how (if at all) and in what ways understanding and knowledge can be applied in similar contexts and settings. The qualitative researcher attempts to address the issue of transferability by way of thick, rich description that will provide the basis for a case or cases to have relevance and potential application across a broader context.

Qualitative research methods ask the questions of "what" and "how" a phenomenon is understood in a real-life context (Bloomberg & Volpe, 2019). In the education field, qualitative research methods uncover educational experiences and practices because qualitative research allows the researcher to reveal new knowledge and understanding. Moreover, qualitative descriptive case studies describe, analyze and interpret events that explain the reasoning behind specific phenomena (Bloomberg, 2018). As such, case study design can be the foundation for a rigorous study within the Applied Doctoral Experience (ADE).

Case study design is an appropriate research design to consider when conceptualizing and conducting a dissertation research study that is based on an applied problem of practice with inherent real-life educational implications. Case study researchers study current, real-life cases that are in progress so that they can gather accurate information that is current. This fits well with the ADE program, as students are typically exploring a problem of practice. Because of the flexibility of the methods used, a descriptive design provides the researcher with the opportunity to choose data collection methods that are best suited to a practice-based research purpose, and can include individual interviews, focus groups, observation, surveys, and critical incident questionnaires. Methods are triangulated to contribute to the study’s trustworthiness. In selecting the set of data collection methods, it is important that the researcher carefully consider the alignment between research questions and the type of data that is needed to address these. Each data source is one piece of the “puzzle,” that contributes to the researcher’s holistic understanding of a phenomenon. The various strands of data are woven together holistically to promote a deeper understanding of the case and its application to an educationally-based problem of practice.

Research studies within the Applied Doctoral Experience (ADE) will be practical in nature and focus on problems and issues that inform educational practice.  Many of the types of studies that fall within the ADE framework are exploratory, and align with case study design. Case study design fits very well with applied problems related to educational practice, as the following set of examples illustrate:

Elementary Bilingual Education Teachers’ Self-Efficacy in Teaching English Language Learners: A Qualitative Case Study

The problem to be addressed in the proposed study is that some elementary bilingual education teachers’ beliefs about their lack of preparedness to teach the English language may negatively impact the language proficiency skills of Hispanic ELLs (Ernst-Slavit & Wenger, 2016; Fuchs et al., 2018; Hoque, 2016). The purpose of the proposed qualitative descriptive case study was to explore the perspectives and experiences of elementary bilingual education teachers regarding their perceived lack of preparedness to teach the English language and how this may impact the language proficiency of Hispanic ELLs.

Exploring Minority Teachers Experiences Pertaining to their Value in Education: A Single Case Study of Teachers in New York City

The problem is that minority K-12 teachers are underrepresented in the United States, with research indicating that school leaders and teachers in schools that are populated mainly by black students, staffed mostly by white teachers who may be unprepared to deal with biases and stereotypes that are ingrained in schools (Egalite, Kisida, & Winters, 2015; Milligan & Howley, 2015). The purpose of this qualitative exploratory single case study was to develop a clearer understanding of minority teachers’ experiences concerning the under-representation of minority K-12 teachers in urban school districts in the United States since there are so few of them.

Exploring the Impact of an Urban Teacher Residency Program on Teachers’ Cultural Intelligence: A Qualitative Case Study

The problem to be addressed by this case study is that teacher candidates often report being unprepared and ill-equipped to effectively educate culturally diverse students (Skepple, 2015; Beutel, 2018). The purpose of this study was to explore and gain an in-depth understanding of the perceived impact of an urban teacher residency program in urban Iowa on teachers’ cultural competence using the cultural intelligence (CQ) framework (Earley & Ang, 2003).

Qualitative Case Study that Explores Self-Efficacy and Mentorship on Women in Academic Administrative Leadership Roles

The problem was that female school-level administrators might be less likely to experience mentorship, thereby potentially decreasing their self-efficacy (Bing & Smith, 2019; Brown, 2020; Grant, 2021). The purpose of this case study was to determine to what extent female school-level administrators in the United States who had a mentor have a sense of self-efficacy and to examine the relationship between mentorship and self-efficacy.

Suburban Teacher and Administrator Perceptions of Culturally Responsive Teaching to Promote Connectedness in Students of Color: A Qualitative Case Study

The problem to be addressed in this study is the racial discrimination experienced by students of color in suburban schools and the resulting negative school experience (Jara & Bloomsbury, 2020; Jones, 2019; Kohli et al., 2017; Wandix-White, 2020). The purpose of this case study is to explore how culturally responsive practices can counteract systemic racism and discrimination in suburban schools thereby meeting the needs of students of color by creating positive learning experiences. 

As you can see, all of these studies were well suited to qualitative case study design. In each of these studies, the applied research problem and research purpose were clearly grounded in educational practice as well as directly aligned with qualitative case study methodology. In the Applied Doctoral Experience (ADE), you will be focused on addressing or resolving an educationally relevant research problem of practice. As such, your case study, with clear boundaries, will be one that centers on a real-life authentic problem in your field of practice that you believe is in need of resolution or improvement, and that the outcome thereof will be educationally valuable.

Bloomberg, L. D. (2018). Case study method. In B. B. Frey (Ed.), The SAGE Encyclopedia of educational research, measurement, and evaluation (pp. 237–239). SAGE. https://go.openathens.net/redirector/nu.edu?url=https%3A%2F%2Fmethods.sagepub.com%2FReference%2Fthe-sage-encyclopedia-of-educational-research-measurement-and-evaluation%2Fi4294.xml

Bloomberg, L. D. & Volpe, M. (2019). Completing your qualitative dissertation: A road map from beginning to end . (4th Ed.). SAGE.

Stake, R. E. (1995). The art of case study research. SAGE.

Stake, R. E. (2005). Qualitative case studies. In N. K. Denzin and Y. S. Lincoln (Eds.), The SAGE handbook of qualitative research (3rd ed., pp. 443–466). SAGE.

Yin, R. (2018). Case study research and applications: Designs and methods. SAGE.

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COMMUNITY CASE STUDY article

Frameworks for community impact - community case study.

• Northeastern Vermont Regional Hospital, St. Johnbury, VT, United States

The Affordable Care Act of 2008 placed specific community health needs assessment and community benefit reporting requirements on US not-for-profit hospitals. The requirements are straightforward, but come with no expectation for synergy between the needs assessment and the community benefit spending, no direction on how to design systems to improve community health, and with surprisingly little accountability for improving health outcomes. With the help of diverse community partners, one Critical Access hospital in rural Vermont has successfully linked the needs assessment with community benefit dollars to address upstream contributors of health. In 2014, Northeastern Vermont Regional Hospital lead the creation of NEK Prosper: Caledonia and Southern Essex Accountable Health Community with a mission to tackle poverty as the ultimate root cause of poor health in the region. This article outlines how a hospital community health needs assessment ignited a change in how community partners worked together, aligned organizational strategies, and overcame industry jargon barriers to create regional system change to improve health. And how that same hospital has used community benefit dollars to accelerate action at the community level.

Introduction

This article outlines how Northeastern Vermont Regional Hospital (NVRH) is able to use its community health needs assessment as both a catalyst to change how community partners work together, and to inform how best to spend the hospital community benefit dollars to impact community health.

NVRH is a 25 bed Critical Access Hospital in northern Vermont. The 2012 NVRH Community Health Needs Assessment (CHNA) identified poverty as one of the top health priority areas. Poverty, and the symptoms of poverty like inadequate access to healthcare, healthy food, transportation, and education, is a well-documented root cause of poor health ( 1 , 2 ). Low income adults are more likely to suffer difficulties in their daily lives due to chronic illness, while children living in poverty are often left with risk factors that can affect their health throughout their lives ( 3 ) Consequently, tackling poverty in the hospital service area became a priority issue for NVRH and its leaders, particularly the CEO. As part of the 2012 CHNA implementation plan, NVRH committed to convene community leaders to address the issue of poverty as the upstream, systemic driver of poor health and health inequity.

Convened by invitation of NVRH, the leaders of the regional Federally Qualified Health Center (FQHC) and home health agency, designated mental health agency, community action agency, council on aging, and designated regional housing organization began meeting regularly at the hospital. As they talked about what they each could do to address poverty and researched how they could work better together in a strategic and collaborative way, two models emerged: The Accountable Health Community (AHC) and collective impact (CI) models.

AHC is an emerging model gaining popularity across the US. An AHC is responsible for the health and well-being of everyone who lives in a geographic region. The AHC model recognizes that the health of a population is determined by multiple factors: healthcare, environment, socio-economic status, and individual behaviors. ( 4 ) The Center for Medicare and Medicaid Services (CMS) says the AHC model “addresses a critical gap between clinical care and community services in the current health care delivery system” ( 5 ).

The Prevention Institute has embraced the AHC model as a “promising vehicle toward reaching the full potential of the Triple Aim.” The Prevention Institute has identified nine core elements of the AHC model: multi-sectoral partnership; integrator organization; governance; data; strategy and implementation; community engagement; communications; and sustainable financing ( 6 ).

The AHC model outlines one structure to foster collaboration ( 7 ). True collaboration requires multi-sector partners work well-together ( 8 ). This is where the collective impact model can help.

CI has been articulated as a method for solving large scale social problems by “a systemic approach to social impact that focuses on the relationships between organizations and the progress toward shared objectives.” Successful CI initiatives have five conditions that together produce true alignment and lead to powerful results: a common agenda, shared measurement systems, mutually reinforcing activities, continuous communication, and backbone support organizations ( 9 ).

NVRH is located in Vermont's Northeast Kingdom, a region known for its rugged rural landscape and independent and spirited people. The primary service area for NVRH is Caledonia and southern Essex counties, with just under 30,000 people. Population density in Caledonia County is 48.1 persons per square mile and 9.5 persons per square mile in Essex County ( 10 ). Both counties are bordered by the Connecticut River and New Hampshire to the east.

The 25 bed hospital is the largest employer in the region, with over 600 employees. The hospital operates four rural health clinics and six specialty medical offices. A different entity operates three FQHC's and home health and hospice for the region. All the primary care offices in the region are recognized NCQA Patient Centered Medical Homes. Mental health services are provided by a regional designated mental health agency and many independent providers in private practice. There are several independent long-term care facilities in the area. Comprehensive cancer care services are located on the NVRH campus, but provided by the nearest (70 miles to the south) tertiary center. A private for-profit dialysis center provides services in a building owned by NVRH. Medically Assisted Treatment (MAT) for opioid addiction is provided by a private for-profit organization located down the road from NVRH. The mental health agency and several primary care offices operated by the hospital and the FQHC also provide MAT services.

NVRH has a long history and reputation for working collaboratively and embracing the idea that health happens outside the walls of the hospital. Over the decades, NVRH leadership has spearheaded the formation of prevention coalitions to address obesity and substance use, providing staff resources, meeting space, and funding for coalition initiatives. Both NVRH leadership and staff routinely works with local and state public health staff though the Vermont Department of Health on prevention and public health initiatives driven by the Vermont State Health Improvement Plan, and data like the Behavioral Risk Factor Surveillance Survey and the Youth Behavior Risk Survey collected by the Health Department, as well as local Department of Health priorities.

The NVRH service area was the first of two pilot communities funded by the Vermont Blueprint for Health in 2005, and the first Integrated Medical Home and Community Health Team pilot community created under Act 71 ( 11 ). The robust and active Blueprint for Health Community Health Team continues to provide a forum for coordinated care between direct service providers from healthcare, human services, and community-based organizations.

NEK Prosper!

In 2014, NVRH lead the creation of NEK Prosper: Caledonia and Southern Essex Accountable Health Community with a mission to tackle poverty as the ultimate root cause of poor health in the region.

That initial informal group of community leaders convened by NVRH in 2014 has since added the state-wide foodbank and the regional United Way and become the leadership team. NEK Prosper has provided the forum for the leadership team decision makers come together to strategically align their organizations, something that did not happen prior to the formation of the AHC.

The leadership team embraced the frameworks provided by the AHC and CI models. There is a formal governance and decision-making structure, shared measures for success, and intentional methods for community engagement. Basic meeting etiquette and equitable participation is ensured by reviewing standard norms of behavior, such as “listening with intent” and “address issues directly and succinctly” at each meeting. Leadership team members have adopted norms of behavior for meetings. They have all signed a memorandum of understanding (MOU) that outlines the mission and purpose of the AHC, specific roles and responsibilities of the leadership team members, and a process for decision-making. Stewardship has been an important guiding principle for all members; the advice to “wear two hats – those of your organization and this partnership” is included in the norms of behavior.

Today, the AHC includes members from healthcare, human services, housing, transportation, mental health, community action, charitable food, funders, school districts, domestic violence agency, youth services, economic development and regional planning, banks/financial organizations, town government, restorative justice, and State agencies including Vermont Department of Health and Vermont Department of Human Services ( Figure 1 ). All NEK Prosper members sign a culture statement that encourages innovative thinking, sharing of resources, and working relationships based on trust and respect. Rather than creating another needs assessment, NEK Prosper officially adopted the hospital community health needs assessment (CHNA) as the official community needs assessment of the AHC in 2016.

Figure 1 . Member Organizations for NEK Prosper.

The name NEK Prosper: Caledonia and Southern Essex Accountable Health Community was officially adopted in 2018. NVRH serves as the backbone organization for NEK Prosper.

Workgroups called Collaborative Action Networks (CANs) include community member participation and focus on each of NEK Prosper's five outcome areas: our community will be well–nourished, well-housed, physically healthy, mentally healthy, and financially secure. NEK Prosper and the CANs use Results Based Accountability™ to measure impact on health.

Programmatic Elements

The purpose of the NVRH community health needs assessment is to identify initiatives at the individual, community, environmental, and policy level, as well as programs and services that meet the hospital's mission to improve the health of people in the communities it serves. When it came time for NVRH to complete the 2018 CHNA, the leading criterion for setting community health priorities was the ability to work within the NEK Prosper framework to best capitalize on existing community resources and assets.

The 2018 CHNA built on the foundation of the previous assessments. New for 2018, the CHNA used the framework of NEK Prosper. Additionally, the CHNA was advised by the data compiled and the community engagement work already done by NEK Prosper, and adopted the mission of the NEK Prosper to reduce poverty in the region.

The CHNA data collection identified low-income families, and older adults as the most vulnerable population. The CHNA validated the objectives of NEK Prosper that communities will be financially secure, physically healthy, mentally healthy, well-nourished, and well-housed. Consequently, the NVRH 2018 CHNA proposed that over the next three years, NVRH will implement initiatives, and programs and services that work to meet these five objectives to improve health in the community, while intentionally addressing the underlying causes of health disparities .

Like NEK Prosper, the 2018 NVRH CHNA Implementation Plan and Evaluation use Results Based Accountability™ (RBA) to measure impact, evaluate initiatives, and drive action and change. RBA provides a step by step process to get results. RBA defines both population level (whether we have achieved goals for a defined population) and performance level (how well a program or service is working) measures. ( 12 ).

In fiscal year 2019, with an intentional effort to use community benefit dollars to accelerate action, the hospital budgeted $93,000 from operations to fund initiatives of the five CANs of NEK Prosper. The initiatives and dollar amounts are outlined in the CHNA Implementation Plan. For that first year, not all the CANs had initiatives ready for funding. The same amounts were budgeted for fiscal year 2020.

The CANs are data driven and use a common template and tools to decide which community strategies to implement. The Well-Nourished CAN launched the Food Hero Social Marketing Campaign in May 2019. Food Hero is a program from Oregon State University Extension Service with funding from SNAP-ED. The goal of the program is to increase fruit and vegetable consumption by creating and disseminating low cost, easy to prepare, and healthy recipes ( 13 ).

NVRH Community Benefit dollars purchased re-useable grocery bags with the Food Hero and NVRH logo. The bags are distributed at events sponsored by NVRH and the partner organizations of the Well-Nourished CAN. Large Food Hero banners attract attention at local events. Food Hero themed placemats are used at the hospital and senior meal sites.

Using Results Based Accountability™ (RBA) principles, the Well-Nourished CAN tracks the number of sites using Food Hero materials, social media engagements, and the number of Food Hero recipes distributed to measure performance level results. The CAN will use a Food Hero qualitative evaluation tool to measure behavior change in spring 2020. The CAN uses population level indicators collected by the Vermont Department of Health (fruit and vegetable consumption and the prevalence of hypertension) to measure long term impact.

Other CAN initiatives funded by NVRH community benefit dollars are the popular smoothie bikes for use at school and community events as part of the Physically Healthy CAN's community-based campaign to increase physical activity, and stipends for fitness providers to offer free pop up fitness classes in local parks. NVRH has funded a small pilot project that pays for complimentary therapies like acupuncture for people coping with mental health issues under the direction of the Mentally Healthy CAN. Every CAN initiative is evaluated for impact by using RBA performance measures of “how much, how well, and is anyone better off.” Each CAN measures community wide impact by using population level indicators such as percentage of people getting the recommended amount of physical activity or regional rates of suicide. Impact dashboard for some of the CANs can found at the NEK Prosper website.

The partners in NEK Prosper are not stopping with community-based interventions of the CANs. Two wellness funds were created thanks to the strong culture of stewardship, and leaders focused on action to improve health by tackling poverty.

Working with local economic development and financial partners NEK Prosper members are ready to launch the NEK Prosperity Fund using a capital stacking approach to raise funds to free up almost a million dollars currently held by the regional Community Development Financial Institution (CDFI) to invest in small and emerging local businesses. The purpose of the fund is to act as an investment vehicle aimed at promoting economic development by offering loans to local businesses, as well as supporting the overall well-being of the employees and customers of the business. Loans will be given to businesses that might not qualify for traditional bank loans or other loans offered by the CDFI. These more “at risk” businesses will need a high level of technical assistance to be successful. An Advisory Committee of NEK Prosper will assist the CDFI in developing general policies for mission driven funding.

The NEK Prosper leadership team has committed to raising $200,000 for a loan loss reserve fund to protect the original capital loan fund assets, and to pay for additional business support services by the experienced CDFI staff. It is expected the money will be raised quickly with investments from the hospital, other leadership team organizations, and local businesses.

In spring 2020, NEK Prosper launched the Healthy Cents Fund. The Healthy Cents Fund is available for local organizations for innovative upstream interventions or investments that will create healthy and thriving communities and positive social, economic, or environmental impact. The fund aims to accelerate the work of NEK Prosper and move the AHC closer to the five outcome areas. The value-based payment environment was key to the creation of this fund. Funding for the Healthy Cents Fund comes from Medicaid capitated payments to NVRH paid through the Vermont All Payer Model and the state-wide Accountable Care Organization. Rather than wait for potential shared savings, NVRH takes 1% off the top of the per member per month capitated payments to finance the Healthy Cents Fund, or about $58,000 annually.

Both funds require community engagement activities, and must tie directly to the five outcomes areas of NEK Prosper and the health priorities of the CHNA. Social return on investment is measured using a modified logic model table linking funded activities to short and long term social outcomes.

In a value-based payment environment, hospitals have the financial incentives to keep people well and out of the hospital and the flexibility to use hospital resources to address the social determinants of health. It is time for hospitals to put resources into prevention and the social and environmental factors that make people sick ( 1 ). Nationally, researchers and policy makers are looking for ways for hospitals and partners to combine resources in a more systemic way ( 14 , 15 ).

Hospitals already have a tool in place to identify the community needs and priorities: the CHNA. The data and community input gathered during the CHNA process provides the roadmap for where hospitals can best invest resources to make the most impact on health. The community benefit requirements of the Affordable Care Act make it possible for hospitals to get credit for their investments. Yet, few hospitals are investing in “community building” projects that address social determinants ( 2 ). Additionally, there is clear consensus that a comprehensive approach to improving health requires multisector partners working in sync. However, we are falling short of all we can do to truly improve health and well-being ( 8 ).

NVRH and the partner organizations in the region have used the promising models of collaboration of Accountable Health Community (AHC) and collective impact (CI) to align their strategies, organization resources, and funding. The models provide the structure to work collaboratively, while holding people accountable for their contributions to the goals of NEK Prosper. AHC and CI have helped create an atmosphere of trust and a process for measuring results.

Leadership from the hospital CEO and the executive directors of other community agencies was a critical component to initiating and continuing the collaboration. Stewardship and trust are two additional elements that are essential. The CI model provides a model for identifying and incorporating these elements into concrete activities.

The role of the hospital was critical to the success of NEK Prosper. Despite its small size, NVRH is a leading force in the community. Additionally, the financial contribution provided through the community benefit funds enabled concrete actions that the community might otherwise have struggled to achieve.

Lessons Learned and Tips for Success:

• Don't reinvent the wheel. Use existing models and frameworks to create a community collaborative structure the works in your community.

• Be strategic in making your list of who needs to be at the table. Include traditional health and human service partners, community-based organizations focused on social determinants, local and state government, funders, and less traditional partners like for-profit business and economic development agencies.

• Finding common ground with less traditional partners may take some time; expect communication barriers. NVRH and NEK Prosper found that banks and economic development agencies wanted the same thing – a healthy prosperous community; however, industry specific jargon made it difficult to identify common goals. Engage these partners in your work by asking for their expertise in finding financial resources for projects and measuring financial return on investment. In exchange, health and human services can offer expertise in social return on investment measures, and provide specific services and programs to improve the health and well-being for employees of these partners and for the employers and customers they work with every day.

We inherently know that we are better together, stronger together, and can accomplish more together. Using current partnership frameworks like Accountable Health Community and collective impact, hospitals can provide the data - CHNA, the funding - community benefits, and the leadership to foster a culture of stewardship to truly create and maintain healthy communities.

Conclusions

As hospitals work to improve health in their communities, they must be intentional about improving the systems and structures within their organizations and regions to support health, well-being, and equal opportunities for all.

The recipe for success includes a strong foundation built on three models: Accountable Health Community, Collective Impact, and Results Based Accountability™ to guide operations, keep community partners heading in the same strategic direction, and quantify and measure results. Adding three key ingredients: leadership, stewardship, and action to the foundational structure drives NEK Prosper toward high impact and a healthier, and potentially more prosperous, region.

Data Availability Statement

The datasets generated for this study are available on request to the corresponding author.

Author's Note

This is a community case study as described by one author. The author has a unique perspective because of her involvement in the initial and ongoing operations of NEK Prosper. She is also the staff person at NVRH in charge of both the CHNA process and the community benefit reporting.

Author Contributions

The author confirms being the sole contributor of this work and has approved it for publication.

Conflict of Interest

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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9. Kania J, Kramer M. Collective Impact . Stanford social innovation review (2011) 36.

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Keywords: community benefit, accountable health community, community health needs assessment, non-profit hospital, social determinansts of health

Citation: Ruggles L (2020) Frameworks for Community Impact - Community Case Study. Front. Public Health 8:197. doi: 10.3389/fpubh.2020.00197

Received: 02 March 2020; Accepted: 30 April 2020; Published: 02 June 2020.

Reviewed by:

Copyright © 2020 Ruggles. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Laural Ruggles, l.ruggles@nvrh.org

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

• Resources and Development Class 10 Case Study Social Science Geography Chapter 1

Last Updated on September 3, 2024 by XAM CONTENT

Hello students, we are providing case study questions for class 10 social science. Case study questions are the new question format that is introduced in CBSE board. The resources for case study questions are very less. So, to help students we have created chapterwise case study questions for class 10 social science. In this article, you will find case study for CBSE Class 10 Social Science Geography Chapter 1 Resources and Development. It is a part of Case Study Questions for CBSE Class 10 Social Science Series.

Table of Contents

Case Study Questions on Resources and Development Class 10

Read the following passage and answer the questions:

We have shared our land with the past generations and will have to do so with the future generations too. Ninety five per cent of our basic needs for food, shelter and clothing are obtained from land.

Human activities have not only brought about degradation of land but have also aggravated the pace of natural forces to cause damage to land. Some human activities such as deforestation, overgrazing, mining and quarrying too have contributed significantly in land degradation. Mining sites are abandoned, after excavation work is complete, leaving deep scars and traces of over burdening. In states like Jharkhand, Chhattisgarh, Madhya Pradesh and Odisha, deforestation due to mining have caused severe land degradation. In states like Gujarat, Rajasthan, Madhya Pradesh and Maharashtra, over-grazing is one of the main reasons for land degradation. In the states like Punjab, Haryana, Western Uttar Pradesh, over irrigation is responsible for land degradation due to water logging leading to increase in salinity and alkalinity in the soil.

Q 1. How does human activities have brought about land degradation? Ans. Human activities have brought about land degradation through the factors like deforestation, over-grazing, mining and quarrying.

Q 2. How is over irrigation responsible for land degradation? Ans. Over irrigation is responsible for land degradation due to water logging leading to increase in salinity in soil.

Q 3. Why is human considered as the main culprit for land degradation? Ans. Human is considered as the main culprit for land degradation due to the following reasons: (i) His excavation work at mining sites. (ii) His significant contribution to deforestation. (iii) He has aggravated the pace of natural forces causing damage to land. (Any two)

Planning is the widely accepted strategy for judicious use of resources. It has importance in a country like India, which has enormous diversity in the availability of resources. There are regions which are rich in certain types of resources but are deficient in some other resources. There are some regions which can be considered self-sufficient in terms of the availability of resources and there are some regions which have acute shortage of some vital resources. For example, the states of Jharkhand, Chhattisgarh and Madhya Pradesh are rich in minerals and coal deposits. Arunachal Pradesh has abundance of water resources but lacks in infrastructural development. The state of Rajasthan is very well endowed with solar and wind energy but lacks in water resources. The cold desert of Ladakh is relatively isolated from the rest of the country. It has very rich cultural heritage, but it is deficient in water, infrastructure and some vital minerals. This calls for balanced resource planning at the national, state, regional and local levels.

Q. 1. Which of the following statements correctly describes about resource planning? a. Identification and quantification of available resources. b. Development of available resources. c. Both a. and b. d. Uneven distribution of resources.

Ans. Option (c) is correct.

Q. 2. Resource planning is important in a country like India due to: a. enormous diversity in availability of resources b. deficiency in certain types of resources c. abundance of water resources d. rich cultural heritage

Ans. Option (a) is correct.

Q. 3. The state(s) which is/are rich in minerals and coal deposits is/are: a. Jharkhand b. Chhattisgarh c. Madhya Pradesh d. All of these

Ans. Option (d) is correct.

Q. 4. The states like Jharkhand, Madhya Pradesh are rich in coal and minerals but have less development in resources as: a. they are economically less developed b. they have rich cultural heritage c. they lack water resources d. they lack technological and institutional support

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• Types – natural and human
• Need for resource planning
• Natural resources
• Land as a resource
• Soil types and distribution
• Changing land-use pattern
• Land degradation and conservation measures.

Everything available in our environment which can be used to satisfy our needs, provided it is technologically accessible, economically feasible and culturally acceptable, can be termed as ‘resource’.

The first International Earth Summit held in Rio de Janeiro in 1992 endorsed global Forest Principles and adopted Agenda 21 for achieving sustainable development.

Frequently Asked Questions (FAQs) on Resources and Development Class 10 Case Study

Q1: what are case study questions.

A1: Case study questions are a type of question that presents a detailed scenario or a real-life situation related to a specific topic. Students are required to analyze the situation, apply their knowledge, and provide answers or solutions based on the information given in the case study. These questions help students develop critical thinking and problem-solving skills.

Q2: How should I approach case study questions in exams?

A2: To approach case study questions effectively, follow these steps: Read the case study carefully: Understand the scenario and identify the key points. Analyze the information: Look for clues and relevant details that will help you answer the questions. Apply your knowledge: Use what you have learned in your course to interpret the case study and answer the questions. Structure your answers: Write clear and concise responses, making sure to address all parts of the question.

Q3: What are the benefits of practicing case study questions from your website?

A3: Practicing case study questions from our website offers several benefits: Enhanced understanding: Our case studies are designed to deepen your understanding of historical events and concepts. Exam preparation: Regular practice helps you become familiar with the format and types of questions you might encounter in exams. Critical thinking: Analyzing case studies improves your ability to think critically and make connections between different historical events and ideas. Confidence: Practicing with our materials can boost your confidence and improve your performance in exams.

Q4: What are the important keywords in this chapter “Resources and Development”?

A4: Important keywords for CBSE Class 10 Resources and Development are given below: Land Use Pattern: Use of land for different purposes like forests, cultivation, fallow land, etc. Ecological Balance: The balance in our physical and cultural environment. Man’s activities cause disturbances in this balance. For example, two important aspects are balance of gases in air and balance of constituents in soil. Land Degradation: Depletion of the resources of the land through soil erosion, mining, deforestation, etc. Khadar: The new alluvium. Kankar: Substance now containing calcium carbonates. Laterite: Soils from which silicates have been leached out and iron and aluminium predominate. Bangar: The old alluvium. Conservation: Preservation and protection of natural or man-made resources. Regur: Black soil of extremely fine clayey material. Basin: A wide depression or an area drained by a river. Sub-soil: Part of the soil below the top layer, normally used for cultivation to the depth to which most plant roots grow. Fallow Land: Agricultural land left uncultivated after two-three crops to restore its natural fertility. Marginal Land: Land which is difficult to cultivate and yields little profit. Net Sown Area: The total land under crop production excluding wasteland or land left fallow. Soil: Top layer of earth containing humus.

Q5: When and why was the Rio-de-Janeiro Earth summit held?

A5: Rio-de-Janeiro summit was held in 1992 in Brazil. Earth Summit: To achieve sustainable development in order to combat environment damage, poverty and disease, it laid emphasis on global cooperation, mutual needs and shared responsibilities.

Q6: What type of soil is found in the river deltas of the eastern coast? Write three main features of this type of soil.

A6: Alluvial Soil: Its main features are: (i) Mostly these soils contain adequate proportion of potash and lime which are ideal for the growth of sugarcane, paddy, wheat, etc. (ii) Such a soil is the result of deposits of river. (iii) Very fertile soil

Q7: What do you mean by land use pattern? Name the factors that determine the use of land.

A7: Utilisation of land for various purposes, such as cultivation, grazing of animals, mining, construction of roads, etc. Factors that determine land use pattern are: (i) Topography (ii) Climate (iii) Human Factor (iv) Accessibility

Q8: What does the term ‘sustainable economic development’ mean? How can we eradicate irrational consumption and over-utilisation of resources?

A8: Sustainable economic development means ‘development should take place without damaging the environment’ and development in the present should not compromise with the needs of the future generations. We can eradicate irrational consumption and over-utilisation of resources through conservation of resources. Irrational consumption and over-exploitation of resources lead to many socioeconomic and environmental problems. To overcome these problems and to preserve resources for our future generation as well, proper management and conservation of resources is essential

Q9: What is resource planning? Write three phases of resource planning.

A9: Resource planning is a proper and judicious planning of resources. Resources are put to use according to availability and needs for development of the economy. Three processes which are involved in resource planning are: (a) Identification and inventory of resources across various regions of the country. It involves surveying, mapping, qualitative and quantitative estimation and measurement of the resources. (b) Evolving a planning structure, endowed with appropriate technological skill and institutional set up for implementing resource development plans. (c) Synchronizing the resource development with overall national development plans.

Q10: Explain the role of human in resource development

A10: Human is at the centre of resource development. Actually all resources become resources only when they are put to use by humans. It is human who makes natural things usable with the help of technology. Had no technology been there, development would not have been possible. There are regions where natural resources are in abundance but the regions are not developed, e.g., Africa. But if humans are developed, they make the region developed with technology, e.g., Japan.

Q11: Are there any online resources or tools available for practicing “ Resources and Development” case study questions?

A11: We provide case study questions for CBSE Class 10 Social Science on our  website . Students can visit the website and practice sufficient case study questions and prepare for their exams.

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In times of political polarization and push back on inclusion work, it's important to measure the impact of that work. Measuring the impact of inclusion work can quiet the naysayers and connect people to the deeper purpose of the work.

In my interview with PwC’s chief people and inclusion officer, Yolanda Seals-Coffield, she shared how they measure inclusion work. “We have 12 inclusion networks that bring together allies and deal with issues of belonging. Forty percent of our employees are associated with at least one inclusion network. Allyship is about bringing intersectionality into the forefront—every[thing] from how decisions are made in the organization [to] how people’s careers are discussed when they are not in the room and how people feel about the value of their work.”

It's absolutely critical for inclusion networks or groups (think Employee Resource Groups) to be supported by senior leadership. “Inclusion networks are partner-led at the firm level, and each metro area has a partner lead that may identify as more of an ally. This shows the importance of allyship to the organization,” Seals-Coffield explained.

Inclusion groups must also be aligned to a bigger vision and purpose. Seals-Coffield adds, “Our goal is that every identity in the firm will be respected. That means everyone has to be committed to the culture of care and belonging. Inclusion is what it means to manage talent.”

For these inclusion groups to work, it is necessary to take a data-driven approach. That starts with how the organization designs programs and measures their impact to the business. It’s about the experience people are having at work and what people are self-reporting they feel. While it can be difficult to measure human feelings, to measure the impact of inclusion groups, consider these areas:

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• Feelings of connection and belonging at the organization
• Retention of members of diverse groups
• Investment in diversity, equity and inclusion (DEI) learning and development

Feelings of Connection and Belonging at the Organization

Measuring feelings of connection and belonging at work is crucial for assessing the impact of inclusion groups. One method is to conduct surveys that gauge employees' perceptions of their relationships with colleagues, managers and the organization as a whole. These surveys can include questions about how valued, respected and supported employees feel, as well as their sense of belonging and inclusion.

Additionally, focus groups and interviews can provide deeper insights into employees' experiences and perspectives, helping organizations understand the factors that contribute to or hinder feelings of connection and belonging. By collecting and analyzing this data, organizations can identify areas for improvement and develop strategies to foster a more inclusive and supportive work environment.

Organizations measure feelings of connection and belonging in different formats and frequencies. It often makes sense to measure more frequently at first to see what activities have the most impact and which do not create impact. Once leadership has piloted a few activities, and it is more intentional and consistent over time, it can be helpful to measure feelings on an annual basis (at a minimum) and conduct focus groups for listening sessions to learn more about what the results mean and gather ideas to continuously improve.

Retention of Diverse Group Members

Hiring more diverse talent (that often reflects the communities organizations hope to serve) is pointless if diverse talent is not retained. When the retention of diverse groups is measured over time compared to the dominant group (white, straight, male, etc.) there is usually a two-to-three times higher rate of turnover for employees belonging to diverse groups. This is a leading indicator of a lack of connection and, often, a lack of belonging.

For example, PwC conducted a connectivity partner pilot to see what impact partnering people early in their careers with senior leaders would have on retention. The hypothesis was that creating bridges to allies would help boost employees’ sense of connection. They found a link between partnership early in people’s careers and their career longevity.

Investment in DEI Learning and Development

Measurement of learning-and-development programs is crucial for organizations to assess the effectiveness of their initiatives and identify areas for improvement. In addition to measuring retention and attitudes, organizations can track the number of employees who participate in DEI learning programs and the level of engagement in these programs. By collecting and analyzing these data, organizations can gain valuable insights into the impact of their DEI learning-and-development programs.

“Allyship serves as a bridge that brings us together to create a stronger, more inclusive future. At PwC, we’re bringing this to life by creating spaces for our people to come together for cultural events and developmental opportunities that foster deeper connection and celebrate our diverse experiences. For example, in July, our Pan-Asian Community Inclusion Network (PACIN) launched the PACIN Connects series to further support our members. By cultivating allyship and providing spaces for open dialogue and learning, we can help challenge assumptions, increase our awareness of biases and continue to cultivate a world where everyone feels seen, heard and valued,” Nisha Sheth, PwC US Partner and PACIN Co-Partner Champion added in our interview.

However an organization decides to measure the impact of inclusion, the important part is the decision to measure it. Having an intentional set of consistent activities and measuring the impact to the business over time will ensure that the impact of inclusion work is undeniable .

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• Diabetes & Primary Care

Interactive case study: MODY – a strong family history of diabetes

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Nadia , 27 years old, has, amongst a set of otherwise normal routine blood investigations, a mildly elevated fasting blood glucose level, confirmed on repeat testing, and is diagnosed with diabetes. Her BMI is 23.2 kg/m 2 and her HbA 1c is 49 mmol/mol (6.6%). She has no relevant past medical history and her only medication is the combined contraceptive pill. Her father was diagnosed with type 2 diabetes at the age of 43, and this is controlled by diet. What type of diabetes might you suspect?

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Monitoring soil carbon in smallholder carbon projects: insights from Kenya

• Open access
• Published: 03 September 2024
• Volume 177 , article number  143 , ( 2024 )

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• Adaugo O. Okoli   ORCID: orcid.org/0009-0007-2141-8878 1 &
• Athena Birkenberg 1  

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Voluntary carbon market schemes facilitate funding for projects promoting sustainable land management practices to sequester carbon in natural sinks such as biomass and soil, while also supporting agricultural production. The effectiveness of VCM schemes relies on accurate measurement mechanisms that can directly attribute carbon accumulation to project activities. However, measuring carbon sequestration in soils has proven to be difficult and costly, especially in fragmented smallholdings predominant in global agriculture. The cost and accuracy limitations of current methods to monitor soil organic carbon (SOC) limit the participation of smallholder farmers in global carbon markets, where they could potentially be compensated for adopting sustainable farming practices that provide ecosystem benefits. This study evaluates nine different approaches for SOC accounting in smallholder agricultural projects. The approaches involve the use of proximal and remote sensing, along with process models. Our evaluation centres on stakeholder requirements for the Measurement, Reporting, and Verification system, using the criteria of accuracy, level of standardisation, costs, adoptability, and the advancement of community benefits. By analysing these criteria, we highlight opportunities and challenges associated with each approach, presenting suggestions to enhance their applicability for smallholder SOC accounting. The contextual foundation of the research is a case study on the Western Kenya Soil Carbon Project. Remote sensing shows promise in reducing costs for direct and modelling-based carbon measurement. While it is already being used in certain carbon market applications, transparency is vital for broader integration. This demands collaborative work and investment in infrastructure like spectral libraries and user-friendly tools. Balancing community benefits against the detached nature of remote techniques is essential. Enhancing information access aids farmers, boosting income through improved soil and crop productivity, even with remote monitoring. Handheld sensors can involve smallholders, given consistent protocols. Engaging the community in monitoring can cut project costs, enhance agricultural capabilities, and generate extra income.

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1 Introduction

Soil’s role as a carbon sink, when properly managed, is increasingly recognized as an important asset in climate change mitigation. Furthermore, sustainable agricultural land management can halt soil degradation, improve soil fertility, lower production input costs, and enhance ecosystem resilience against climate change impacts (Chenu et al. 2019 ; Liniger et al. 2011 ; Rumpel et al. 2020 ). However, most of the world's agriculture involves smallholder farmers with limited access to technical knowledge and financial resources for sustainable land management due to inadequate funding for public extension services worldwide (Wollenberg et al. 2022 ).

Voluntary carbon markets offer a solution to incentivize improved soil management, addressing issues of food security, climate adaptation and mitigation in developing countries through improved soil management. Carbon sequestered on-farm through sustainable practices can be traded as a commodity to offset corporate greenhouse gas emissions. Voluntary carbon projects involving soil carbon management are growing, with a tenfold increase in carbon credits issued from agricultural land management projects between 2020 and 2021 (Ecosystems Marketplace, 2022 ). However, effective scaling to benefit smallholders in the tropics is hampered by a lack of reliable, cost-effective soil analysis methods for quantifying the carbon sequestration benefits of land management practices (FAO et al. 2020 ; Olander et al. 2013 ; Berry & Ryan 2013 ). This obstacle has become even more significant following the deactivation of the most utilized method for agricultural carbon projects by the leading carbon standard, Verra. Footnote 1 Currently available methodologies therefore lack precedence in smallholder projects.

Smallholder carbon projects differ substantially from those involving commercial farms in high-income countries, which have been the focus of other studies (Paul et al. 2023 ). Smallholder farms are below two hectares on average, requiring aggregation of hundreds or thousands of landowners to achieve economies of scale and a tradeable amount of carbon credits. This increases the complexity, and costs of monitoring practices and comes with unique needs related to project governance and adoption incentives, which differ from farmers in Europe or North America who typically have larger plots, more access to information, and require less technical support. Therefore, integrating the multiple needs and requirements of stakeholders through participatory approaches is essential in such projects (Wollenberg et al. 2022 ).

Emerging technologies, including proximal and remote sensing, are promising for rapid, large-scale soil data collection and analysis. Many have investigated the use of such technologies for measuring soil organic carbon (SOC). However, within the scenario of carbon projects, technologies e.g., remote sensing, and tools like handheld soil scanners, are used for either data collection or analysis and are applied as part of a larger monitoring approach for SOC accounting. ‘Approach’ refers to the full set of procedures used for data collection and analysis of SOC stock change, including which tools are used, how often, and by whom. Such a monitoring approach is part of a larger project Measurement, Reporting, and Verification (MRV) system which comprises the monitoring approaches of all emission sources/sinks and non-carbon project impacts such as community livelihood benefits. Based on the nuances described above, it is more practical to evaluate SOC monitoring approaches for smallholder carbon projects than to assess single measurement tools. This paper takes a holistic systems perspective by addressing the following research questions:

What are the needs of different stakeholders in smallholder agricultural carbon projects in developing countries?

How well can existing and new SOC monitoring approaches contribute to the identified needs?

What are the challenges and benefits of available SOC monitoring approaches in the context of smallholder carbon projects in developing countries?

While others (Paul et al. 2023 ) have recently questioned the effectiveness of agricultural land management projects in reaching climate change mitigation targets, this paper does not attempt to weigh in on this subject. Instead, considering the growing number of such projects, and the predicted exponential growth of the Voluntary Carbon Market in coming years (BCG & Shell 2022 ), this study adopts a functional outlook to evaluate nine different SOC monitoring approaches (Table 1 ), and their potential for synergizing, rather than trading off on, multiple stakeholder objectives or requirements. The evaluation focuses on the level of accuracy, standardisation, cost reduction, adoptability, and their impact on community benefits. These criteria were identified as key factors influencing the choice of monitoring approaches for carbon projects. This evaluation is timely due to increasing public scrutiny of methodologies applied by carbon projects (Miltenberger et al. 2021 ) and consequently an evolution of smallholder methodologies within the standards.

The paper is organized as follows: after providing background information on the technical and operational requirements of carbon projects, we provide an overview of the existing research on soil carbon monitoring techniques. The methods section details the case study location in Kenya, describe the nine SOC monitoring approaches chosen for the evaluation and how the evaluation was conducted. Finally, we highlight the main results and discuss further implications of the findings to provide a comprehensive conclusion.

2 Conceptual background

2.1 important criteria for monitoring design.

When designing a carbon project monitoring approach, two categories of criteria must be considered.

Technical criteria are aligned with carbon certification standards and scientific best practices. The IPCC guidelines (IPCC 2006 ) identify completeness, transparency, accuracy, (time-series) consistency, and comparability as its foundational data quality principles. Completeness means that an inventory covers all sources and sinks of gases relevant to the project. Projects often include multiple carbon pools, which require different monitoring methods. A typical smallholder agricultural project might monitor above-ground biomass, SOC pools, emissions from inorganic fertilizers and biomass burning. Therefore, it is important to note that SOC accounting is only one aspect of a project’s MRV system. Transparency means that the assumptions and methodologies used for an inventory should be clearly explained to facilitate replication and assessment of the inventory. Accuracy is a relative measure of the exactness of emission or removal estimates, striving to avoid systematic over or underestimation and to reduce uncertainties as far as practicable. Most carbon standards set a minimum acceptable threshold for accuracy. For example, the VCS requires an R2 > 0.80 for correlations between predicted and observed stocks, and an uncertainty of < 20 percent based on a 95 percent confidence interval for predicted values. Where this is impossible to attain, deductions proportional to the uncertainty value are applied to the GHG removal estimates in line with the principle of conservativeness as described below. Consistency mandates internal coherence across all inventory elements and with inventories of other years. An inventory is consistent if it uses the same methodologies for the base and all subsequent years and relies on consistent datasets for estimations. Comparability ensures that emission and removal estimates are comparable across projects. Therefore, projects should use methodologies and formats agreed by standards. GHG Protocol and ISO 14062–2 introduce the additional principle of conservativeness, favouring an underestimation rather than overestimation of GHG reductions. Conservative values and assumptions should be applied in situations where data and assumptions are uncertain and where the cost of reducing uncertainty is not worth the increase in accuracy, ensuring that GHG reductions/removals are not overestimated. These principles are fundamental to providing investors and stakeholders with sufficient confidence in credits and allowing them to make decisions with reasonable assurance in the integrity of the reported information.

Operational (feasibility) criteria focus on practicality of projects for their proponents. Developers of carbon projects aim to cover expenses and ensure ongoing viability of their operations. The monitoring approach chosen should be within acceptable costs and suited to the level of available data and local expertise. Monitoring also typically accounts for the non-carbon objectives of stakeholders. For example, investors and government authorities are usually interested in a project’s socio-economic and/or agronomic impacts on smallholders, aligning with Sustainable Development Goals. Many carbon projects therefore integrate this into a monitoring framework—ideally, through a mechanism that can be effectively synchronized with the project’s larger MRV system.

2.2 SOC monitoring approaches

SOC monitoring approaches can be categorized into two ‘Domains’ (Fig. 1 ) in line with Paustian et al. ( 2019 ). Domain a involves directly measuring SOC through empirical observation of soil physical/chemical components. Domain b contains activity modelling approaches, which estimate carbon stock changes due to changes in land management using biogeochemical process models.

Alternative SOC monitoring approaches: Domain a direct measurement and Domain b activity modelling

Domain a (measurement) approaches have two main sources of inaccuracy:

Sampling error from biased or non-representative sampling design. This can be minimized by following best practice for soil sampling (See Annex 3 of FAO, 2020 ; World Bank 2021 ) and

Measurement errors from equipment or analytical procedures used to estimate SOC content of a sample. This is quite low when using conventional methods.

The accuracy of Domain b (modelling) approaches is limited by two broad challenges:

Leading soil models are calibrated and parameterized with weather and soil properties in temperate climes. Thus, applicability of model parameters in tropical regions is limited without local validation using localized datasets. The absence of such datasets means that significant uncertainty is propagated in the extrapolation of model parameters.

The uncertain nature of modelling itself, given that results are based on simulations of natural systems, which are subject to inexplicable random variation. Newer methods (e.g., VM0042 by VCS) now require intermittent model true ups to compare model predictions to reality and improve estimates of model prediction error.

The traditional Domain a method for SOC analysis used to be, and in most cases still is, wet oxidation in potassium dichromate (i.e. the Walkley & Black method). Due to observed difficulties of this method in recovering the total organic carbon content, dry combustion has been put forth as a more reliable benchmark for SOC measurements to enable comparability (Sparks et al., 1996 ). More recently, infrared spectroscopy has been demonstrated to have high accuracy and repeatability for soil analysis. It is increasingly suggested as a cost-effective alternative to other laboratory methods due to rapid and non-destructive sample processing (Viscarra-Rossel et al. 2006 , Jia et al. 2017 , Gomez et al. 2008 ). Still, many authors point out that laboratory methods remain cost-intensive and unsuitable for large processing volumes (Angelopoulou et al., 2020 ; Milori et al. 2011 ).

For this reason, smallholder projects in the carbon market prefer activity modeling approaches; the Roth-C model is used predominantly in most cropland projects to estimate soil carbon dynamics. Footnote 2 Modelling approaches are generally lower cost, as they rely on reported data about land management, soil, and climate to estimate SOC stock changes. They are however widely regarded as less accurate than Domain b approaches due to concerns about quality of model input data (Schober 2021 ) as well as the broad challenges stated above. In alignment with carbon market demand for more rigorous methodologies, Verra has recently inactivated its pioneer SOC activity modelling methodology VM0017. Schilling et al. ( 2023 ) speculate that direct measurement will become the new quality requirement, even for smallholder projects.

There is therefore a need to identify accurate SOC estimation techniques capable of reducing the cost of data collection, reducing analytical complexity (thus expertise requirements), and scaling SOC monitoring over larger areas (Olander et al. 2013 ; Saiz and Albrecht 2016 ; Climate Action Reserve 2019 ). In the literature, soil spectroscopy, remote sensing, and increased integration of digital tools have been identified as possible technologies to support such improvements.

Field-based proximal sensing tools reportedly show reasonable accuracy performance under laboratory and field conditions (Viscarra-Rossel et al. 2006 ; Stevens et al. 2008 ; Sorenson et al., 2017 ). However, authors have highlighted various challenges with in-situ application in the field. These include how to account for variability in field conditions (e.g. moisture, soil texture) given the lack of sample preparation which affects the repeatability of results. Vehicle-mounted proximal sensor devices have been proposed by some authors to reduce the labour-intensive data collection across large areas. This approach is however not considered in this study as we consider this more feasible for commercial fields where mechanization is routinely used.

Estimation of soil carbon stocks from satellite imagery as an alternative to field sampling has also been investigated by many studies, with varying reports of accuracy. The main technical limitations of this method have been discussed in depth in the literature. These include difficulties handling atmospheric cloud cover, the interruption of bare soil by vegetation and crop residue, and like proximal data collection, the effect of varying soil conditions (e.g., moisture, texture, surface roughness) in fields during satellite data recording (van Wesemael et al. 2021 ). Furthermore, as World Bank ( 2021 ) points out, most satellite sensors only measure surface (1 cm) soil reflectance (the same is also true for proximal sensors) while carbon storage is usually analysed to 30 cm depth.

Some of these challenges can be overcome with specialised processing methods. Good results have been demonstrated for normalizing the effect of in-field moisture/texture variations using statistical techniques such as External Parameter Orthogonalization (Nawar et al. 2020 ; Veum et al. 2018 ) and Direct Standardisation (Angelopoulou et al., 2020 ; Ji et al. 2015 ). Statistical techniques can also be applied to surface spectral measurements to correlate soil depth to carbon content (Kusumo 2018 ; Lu et al., 2019 ), and Zepp et al. ( 2021 ) discuss an ‘SCMap’ procedure to composite multi-temporal satellite imagery, allowing data to be obtained from different periods in the year where bare soil is visible.

Authors have reported the successful use of remote sensing for detecting farming practices such as cover cropping, crop-rotation, and no-tillage (Hagen et al., 2020 ; World Bank 2021 ; Zheng et al. 2014 ). Bégué et al. ( 2018 ) extensively review literature on this method which can support large-scale collection of input data as part of a modelling ( Domain b ) approach. However, this technique is limited in detecting a wider range of practices such as fertilizer use, composting or residue burning remotely. Moreover, greater variability in when and how farmers implement practices could also make remote monitoring more difficult, especially on smaller plots. Examples of current use in the carbon market include in detecting tree cover (agroforestry practices) e.g., Rabobank’s Acorn methodology approved under the Plan Vivo standard Footnote 3 and surveying livestock numbers e.g., Verra’s VM0032. More recent carbon initiatives pioneering this approach include the Carbon Plus Grasslands Methodology Footnote 4 developed by independent marketplace providers Regen Network Development Inc, and the CIBO Technologies program CIBO Initiative for Scaling Regenerative Agriculture . Footnote 5 The latter two programs are currently in the process of being developed under the VM0042 methodology of VCS Standard by Verra.

Numerous benefits and challenges of different SOC monitoring techniques have been discussed in the literature. However, to determine the most suitable monitoring approach for smallholder agricultural projects, evaluating individual techniques alone is insufficient. This paper aims to assess the overall performance of a comprehensive monitoring approach, which combines data collection and analysis methods, to best support the estimation of SOC stock changes in these projects.

3 Methods and context

3.1 study design.

This study employs an iterative process of literature reviews and key informant interviews, underpinned by a case-study conducted in the Western Kenya Soil Carbon Project (WKSCP). An initial review aimed at understanding the current SOC monitoring system in agricultural settings and developing a shortlist of potential monitoring approaches for analysis. Based on an analysis of peer-reviewed studies on soil carbon dynamics, monitoring and implementation reports of carbon projects, lessons learned reports, discussion papers from project investors and researchers, and methodology documents from official offsetting standards, three approaches were identified as the current state-of-the-art for SOC accounting: dry combustion (L1), Ex-situ MIR spectroscopy (L2), and activity modelling 1 (AM1). These are described in Table  1 . They were chosen based on their predominance and acceptance in the literature as commonly used methods for estimating SOC stock changes. Six alternative approaches (Table  1 ) integrating the use of remote sensing, proximal sensing and digital technologies were then conceptualized and proposed for comparison with the three mentioned above. Comparisons were based on the literature and data collected from interviews in the study area as described below.

a We assume services incur minimal or no cost compared to PS2 since farmers participate in the project with the expectation that the generated carbon credits will enable community benefits.

3.2 Study area and data collection

The Western Kenya Soil Carbon Project (WKSCP) was used as a case study on agricultural carbon projects in developing countries. This project is situated in the counties of Bungoma, Siaya and Kakamega in Western Kenya (see Fig. 2 ).

Source: Soil Carbon Certification Services ( 2023 )

Map of the study area

The project is expected to cover 32,000 ha at full-size and involve about 40,000 farm households. It has a predicted emission reduction impact of 1,873,798 tCO2 equivalent over its 20-year lifespan. Footnote 6 WKSCP is registered with the Verified Carbon Standard using the VM0017 methodology Footnote 7 “Sustainable Agricultural Land Management”, which represents a Domain b approach. The project is currently undergoing verification for the first round of credit issuance.

The project area is characterized by its tropical montane climate and clayey soils with high potential for storing organic matter. Small-scale (average 1 ha), rain-fed subsistence farming based on maize and beans is practiced without fallow periods. Increasing population has resulted in land fragmentation, overutilization, and nutrient depletion through the loss of topsoil and the misuse of inputs (Mburu and Kiragu-Wissler 2017 ; Sommer et al., 2018 ). The region is densely populated by poor rural, farming households (Tennigkeit et al. 2013 ), making it a carbon project hotspot.

Semi-structured interviews were conducted between April and May 2021 to elaborate the contextual information about the operational dynamics of a carbon project, soil monitoring in general, and the perceptions and experiences of project stakeholders regarding the short-listed SOC monitoring approaches. A total of 118 interviews were conducted with both project participants and non-participants from 6 stakeholder groups: smallholders, project developers, Implementing Organizations (IOs), enforcers of carbon certification standards, governmental/international research agencies, and technical (methodological) experts. In summary, across all three counties, we conducted 102 smallholder interviews in person, which were randomly selected, and stratified by geographical location (ward Footnote 8 ), complemented by another 16 expert interviews, out of which 8 were held virtually.

Interview questions, derived from themes in the literature, were tailored to respondents’ expertise. The questions addressed the objectives of stakeholders in joining the carbon project, their anticipation of monitoring outcomes, and their views on how soil monitoring tools and approaches could work in the project. The interviews were recorded, transcribed, and analyzed as described in Sect.  3.3 .

3.3 Data analysis

Figure  3 presents a conceptual framework developed to analyse the selected SOC monitoring approaches and to identify future development opportunities. At the centre of the framework are five evaluation criteria used to compare the proposed approaches, and to assess their potential benefits and shortcomings. The criteria reflect project MRV needs and challenges identified in the literature search and corroborated through key informant interviews.

Analytical framework for the evaluation of SOC monitoring approaches

Accuracy and standardisation reflect the “technical criteria” defined by the standards while cost reduction, adoptability and community benefits reflect “operational criteria” highlighted by various project stakeholders. Based on the criteria outlined, the identified approaches (Table  1 ) are evaluated to derive recommendations that address the multiple needs of stakeholders in smallholder soil-carbon projects in low- and middle-income countries.

To ensure objective comparison, suitable indicators (scoring mechanism) were identified (Table  2 ) and scores were assigned based on a deductive thematic analysis of the literature including project documents (for the indicators on accuracy, standardisation, cost reduction and community benefits) and interview data (for the indicators on adoptability, community benefits, standardisation and cost reduction).

Each point raised within the literature and/or interviews was categorized into thematic clusters aligning with the evaluation criteria. For example, after explaining the approaches, respondents were asked, “Which of these is better suited and why?”, or “How do you think this will affect you or the project?”. Responses related to adoptability, influence on community benefits, or standardisation were then labelled and grouped accordingly with some responses addressing more than one criterion. Responses were then further grouped by monitoring approach. Note that each unique response was counted only once, irrespective of how many times the same point was expressed in different interviews. Finally, each unique point (now grouped by approach and relevant criterion) was evaluated according to the defined indicator scoring mechanism detailed in Table  2 , to derive a final criterion score for each approach. In instances where interview responses provided conflicting answers to score a specific indicator, we prioritized either expert or farmer responses based on relevance for each criterion. Expert responses were prioritized over farmer responses to evaluate standardisation and adoptability, while the reverse was the case for community benefits. If this was insufficient to resolve the issue, findings from the literature were given precedence. The exceptions to this described process were the accuracy and cost reduction criteria. Bottom-up cost estimations were derived solely from data collected during expert interviews and from reviewing project documents. Accuracy of the approaches was evaluated using correlation coefficients (R 2 ), reported from literature comparing the underlying methods with standard laboratory techniques (L1 or L2). R 2 quantifies the strength of linear relationship between observed and predicted variables, serving as a measure of model prediction accuracy. In this analysis, the average R 2 value was taken from various papers as a benchmark for theoretical accuracy of a technology. However, practical accuracy may differ, explored further in the discussion. Footnote 9 It was noted that the concept of accuracy (the degree of a measurement representation of the true value) and precision (which concerns the repeatability of results) were sometimes used interchangeably in the project literature and expert interviews. In this evaluation, the concept of the repeatability of results is partly captured under the standardisation criteria.

3.3.1 Limitations and assumptions

Before describing the results, it is useful to highlight the methodological challenges faced during this study. First, we translated the interview responses into quantitative indicator scores without considering frequency. This was done to prevent bias from the larger number of farmer interviews, necessary to achieve suitable representation of diverse smallholders in the extensive study area. However, this method reduced some qualitative depth, as the indicator scores do not reflect whether they are based on the perceptions of multiple farmers or single experts. Table 3 offers an overview of key demands for each stakeholder group, though a deeper analysis of different stakeholder perspectives would be an interesting aspect to be addressed in future studies. Second, some monitoring approaches considered lacked sufficient data to develop cost estimates. Simplistic assumptions were therefore made as detailed in the Supplementary material. Another limitation waStakeholder requirements for an MRV systems a scarcity of validation studies on the use of remote sensing for detecting land management practices (Approach AM4/RS2). Therefore, the same R 2 value for activity modelling (AM-) was used, assuming similarities since both approaches share SOC analysis methods (modelling). The comparison of R 2 across different approaches also has inherent limitations, since R 2 is a measure of correlation, and high correlation values do not always mean higher prediction accuracy: R 2 neither accounts for model bias nor considers random unexplainable variation. Nonetheless, it was the most reported validation parameter across the literature reviewed and therefore chosen as the accuracy indicator. Another challenge was the multiplicity of model validation procedures across studies, especially across different fields and purposes: studies assess the accuracy of SOC predictions at differing depths; reporting different types of error statistics, which hinders comparability. Lastly, a wide range of R 2 values was reported for the technologies, creating high variance around the mean values considering low sample sizes of available papers.

4 Results and discussion

In this section, we first highlight the expectations of different project stakeholders on what the MRV system should deliver. Next, findings on how the stakeholder groups assessed the various monitoring approaches are shown, followed by an objective and systematic comparison of the approaches – given the criteria presented beforehand which integrates stakeholder perspectives and scientific literature.

4.1 Stakeholder requirements for an MRV system

Table 3 provides a summary of what different stakeholders expect from a project MRV system. The most common requirements across multiple stakeholders were low process costs and high data accuracy. Generation of soil, land, and household information to support farm- and landscape-level decision-making was also demanded. This corroborates with the existing literature (Schilling et al. 2023 ; Tennigkeit et al. 2013 ; Olander et al. 2013 ; Smith et al. 2020 ) and informed the criteria used in evaluating selected monitoring approaches. Accuracy is enforced by carbon standards and highly prioritized by project developers due to investor expectations regarding quality of carbon credits. Researchers and technical experts require standardisation of different approaches for objective comparison and time series research on project impacts. Governmental stakeholders require decision-making information calling for scalable data collection and standardisation, to enable integration of information from multiple projects.

Farmers and Implementing Organisations (IOs) who support on-the-ground activities hold the greatest influence on the execution of project monitoring. However, project monitoring plans are commonly designed without their input. IOs prefer low-effort monitoring approaches which align with their other non-SOC monitoring tasks due to limited staff and resources, acknowledged as challenges. We consider these as important operational demands, factored into cost and adoptability criteria. Many landowners emphasized their desire for informed land management and skill development, which could be built up through participatory monitoring approaches. Wehinger and Alphayo ( 2023 ) found in a recent ELD study of WKSCP that neighbouring farmers in the project area, on witnessing evidence of positive economic outcomes, have high interest in adopting the project’s sustainable land management practices, but are hindered by a limited availability of extension support. However, some landowners, especially older, illiterate, and those with multiple livelihoods, found this unfavourable due to time-consuming training and/or data-keeping efforts. Most farmers are unaccustomed to maintaining farm records, finding it time-consuming. This implies that approaches relying heavily on farm management data may impose an undesirable "data burden" on participating landowners, aligning with Schober's ( 2021 ) claims. This differs from the view of project developers and IOs who see potential benefits for smallholders in improved record keeping which aids farm business management. Project developers face increasing pressure as investors demand measurable community or biodiversity benefits to align with sustainable development goals and prevent reputational damage. Aligning these requirements with practical project needs is often challenging. Therefore, balancing the needs and requirements of different stakeholders regarding information and level of detail from project MRV was identified as a challenge in project design.

4.2 Stakeholder perceptions about the monitoring approaches

Considering the above needs and constraints, the perceptions of project stakeholder groups on the monitoring approaches were then analysed from the interview data. In this section we will present the reflections of different stakeholders on the various monitoring approaches and tools.

Most respondents found conventional laboratory soil measurement costly, due to sampling and equipment costs. L2 (MIR spectroscopy) was understood to be less expensive than L1 even though both share data collection and preparation procedures. Farmers had a limited understanding of the analytical procedures involved in estimating SOC and were generally indifferent to the approach used, if sufficient information would be offered, and analysis results could be accessible for their farm management decisions. The primary concern for this stakeholder group was the accessibility of the end results of the MRV process. Therefore, approaches with field-based data collection, and analytical methods yielding quick and easily interpretable results were favoured such as mobile soil scanners. When it was properly explained, landowners appreciated the potential cost- and effort-saving benefits of remote sensing, but expressed concern over the inaccessibility of the results since it involves off-farm data collection and analysis.

Implementing organizations rely on project developers to establish the project MRV system and provide necessary implementation resources including capacity-building. Therefore, they are unlikely to outright oppose any monitoring approach. IOs interviewed had limited technical understanding about carbon accounting requirements. Even though they collect the data for activity modelling, the job of parameterizing and running the carbon model is outsourced to external technical experts. Similarly, IOs possessed limited knowledge about remote sensing and other soil analytical methods. Due to their preference for labour saving, implementers favoured farmer-sourced data collection methods and/or those which group multiple plots together. For similar reasons, they favoured mobile soil scanners since farmers could potentially be trained to use them—however some expressed scepticism about the reliability of results. This sceptical sentiment was echoed by researchers and government representatives who questioned the lack of transparency around the proprietary calibration data used in such tools.

“The scanners you talk about…they use dry chemistry. Dry chemistry does not go into so many things in the soil and it's very easy to give you a photocopy of another soil test. I did one. I checked on some 54 soil tests one day using dry chemistry and I was surprised when I realized that 10 soil samples had the same [soil organic carbon] figures. These are different farms! Dry chemistry is cheaper, but [wet chemistry] provides more precise and dependable soil results”. Researcher

Technical experts and project developers, placing more value on the quality of collected data, described current modelling approaches as unsatisfactory.

‘The result of an activity-based approach are theoretical results and wrong and I think we shouldn't be satisfied with that. We should have higher aspirations than that’. Remote sensing expert

However, there was a lack of consensus among experts on which data collection or analytical methods fulfil these quality aspirations, or what an acceptable accuracy threshold should be. Researchers pointed out that even the conventional methods can be imprecise where quality control is lacking. Apart from perceived high costs, the biggest drawback of direct soil measurement approaches for project developers is that the temporal observation of significant SOC stock changes requires long measurement intervals (3–5 years) due to the slow magnitude of change relative to stock size. Developers prefer more frequent SOC quantification and credit issuance to generate carbon revenue and sustain project activities in the absence of alternative funding sources. Modelling allows more frequent monitoring intervals and is preferred by some for this reason despite acknowledged accuracy limitations.

The possible role of remote sensing in monitoring produced the highest split of responses among the key informants. Several technical experts opined that remote sensing is too early-stage for use in SOC accounting due to computing uncertainties, and a widespread lack of technical expertise. Therefore, it would be better suited for the collection of readily available auxiliary data (e.g., soil texture or land use classes for stratification). One remote-sensing expert believed that the collection of auxiliary data is a sub-optimal use of remote sensing potential, and that the technology’s use in temporal SOC change detection should be explored further:

“Yes, remote sensing can monitor whether a farmer has done tillage or no tillage, but that’s not what we want to focus on, because then you’re using something that can be very accurate to measure something whereby the result of that will be very inaccurate. If you want to use remote sensing to establish whether they have applied tillage or not, and then simply take a theoretical result of the application of tillage for the actual amount of carbon credits, we believe that’s the wrong way around.” Remote sensing expert.

4.3 Evaluation of monitoring approaches using selected criteria

We evaluated the different monitoring approaches based on the selected criteria by presenting their performance in spider diagrams (see Fig.  4 ). For reasons of visualization, we present the performances in three groups: conventional approaches, new monitoring approaches based on measurements ( Domain a ) and new approaches based on modelling ( Domain b ).

Comparison of the different monitoring approaches

4.3.1 Cost & accuracy

Except L1 and the AM- approaches, all approaches considered (L2, PS1, PS2, RS1, and RS2) are based on spectroscopic analysis, combined with different data collection methods. We found that these approaches generally maintain higher accuracy than activity-based modelling (AM-) approaches due to the latter’s indirect/theoretical nature. Therefore, we deduce that the choice of analytical procedure has a higher impact on potential accuracy of a monitoring approach than data collection methods. We emphasize here the accuracy potential, recognizing that data collection methods could influence the achieved accuracy to some extent. For example, laboratory analyses are often affected by sampling errors and AM approaches influenced by input data quality. However, if data collection best-practices are available and followed in all cases, the greatest influence on accuracy is the method via which the soil carbon stocks are estimated.

Conversely the choice of data collection method was found to have a greater impact on the cost of the approach. Consider the activity modelling (AM) approaches which have been the status quo for agricultural carbon projects so far: the AM1 approach, where data is collected from all participants on a yearly basis could cost up to 10 times more than AM3, where only a random sample is collected yearly and scaled up for the project area (Fig.  4 a, c). No significant difference in accuracy is estimated between the two approaches. This is because statistically, beyond a certain point, only a minimal increase in accuracy is gained from increasing sample size whereas the costs continue to increase. Laboratory measurements L1 and L2, requiring soil sample collection and laboratory processing, were the most expensive approaches while approaches based on in-situ or satellite data collection could drive down costs significantly.

Remote sensing-based monitoring (RS1, RS2) offers the best long-term cost performance (Fig.  4 b), but the level of reported accuracies varies greatly for different studies (see supplementary material) due to varying analytical techniques applied. The selection and use of appropriate analytical techniques to improve accuracy, however, requires high expertise which is lacking in many project countries.

In the case of proximal sensing, it was found that a farmer-led data collection approach (PS1) could offer significant cost savings and potential community benefits (due to its participatory nature) in comparison to commercial mobile testing services (PS2) with – in theory—similar accuracy levels (Fig.  4 b). This may only be true in theory, because the accuracy of results would depend on the capacity of smallholders to use these devices and on the existence of protocols and quality control procedures to ensure consistent data collection and outputs. While the modelling approaches are generally similar in potential accuracy, the achieved accuracy of AM1 (self-reported) approach may be lower in practice due to the poor quality of data often reported by farmers. Several factors contribute to this: (i.) smallholder farmers do not typically take measurements and if so, often use non-standard measurements, (ii.) they are also susceptible to social desirability bias when answering questions e.g., about production or fertilizer use and (iii.) secondary information to cross-check self-reported data is lacking. Because of these issues, a lot of time is spent on subsequent quality control and correction, which often outweighs the initial benefits (convenience and cost) of farmer self-reporting. The data collection process for AM4/RS2 (modelling based on remotely sensed activity data) was also found to potentially impact the estimated accuracy of input data. This approach is limited by difficulty in detecting a wider range of activities such as fertilizer use, composting or residue burning remotely. Moreover, greater variability in when and how farmers implement practices could also make remote activity monitoring more difficult, especially on smaller plots. However, the exact degree of impact was difficult to determine as this approach is not yet widely used and available literature on this topic is scarce. AM3 (modelling based on a sample of farms) is currently the least expensive of the AM approaches, although AM4/RS2 (modelling based on remotely sensed activity data) holds potential to further reduce costs and effort.

None of the newer approaches reach the accuracy of the conventional methods (Fig.  4 ), however there is potential to increase accuracy to meet the requirements of carbon standards, especially for remote and proximal sensing if protocols are standardized and followed. When cost and other limitations make improved accuracy difficult to achieve, detailed uncertainty estimation and adopting a conservative approach can help maintain the credibility of project GHG quantification.

4.3.2 Community benefits

PS (proximal sensing) approaches were found to provide the greatest contribution to non-carbon objectives (community benefits) by enabling community participation, direct feedback, and in-field advisory while saving costs, thus, potentially, allowing more carbon revenue flow to the communities. Although even more cost saving is possible with remote sensing, it scored lowest for other contributions to community benefits due to its detached, off-farm nature. For laboratory approaches, we theorize that the associated on-field benefits and greater measurement accuracy are outweighed by the high implementation costs which will take away from community benefits if implementation costs become higher than payment from credits, and the project is not able to fund or show benefits. The same applies to other higher-cost monitoring approaches such as AM1 (self-reported) and AM2 (yearly full census) which leave less carbon revenue available.

4.3.3 Standardisation and adoption

As emphasized by the IPCC GHG accounting principles, standard protocols and quality control measures play a key role in aiding comparability of results over time and across projects. The Standard Operating Procedures of the Soil–Plant Spectral Diagnostics Laboratory of World Agroforestry Centre (ICRAF) provides widely adopted protocols for spectral analysis in the lab (L2). Protocols also exist for proximal sensing (PS-) approaches e.g. Vis–NIR protocol in Annex B of Viscarra-Rossel et al. ( 2016 ), which is endorsed by carbon certification standard, VCS under the VM0042 methodology. However, such protocols are not yet widely adopted and are lacking for remote sensing (RS-) approaches. Literature on RS-based approaches features different combinations of steps and techniques to predict SOC from remotely sensed data (e.g. Vågen et al., 2018, Zepp et al 2021 ; see further sources in supplementary information). No common guidance exists for selecting modelling techniques, covariates, or data sources. Therefore, the quality of results from different sources varies. Error reporting is also not standardised, and many unaccounted sources of uncertainty are propagated into the results (Takoutsing et al. 2022 ). Moreover, these approaches are not yet endorsed by carbon standards and lack precedented use in carbon projects. This was found to play an important role influencing adoption; less standardised methods were perceived with scepticism by experts and project developers, which reduces the likelihood of adoption. It follows that adoption issues are more likely to be faced by less understood technologies, since trust and transparency of monitoring approaches were found to be important factors for national and local experts. In contrast, farmers and implementers had less significant power in the adoption decision since the monitoring design is usually done by the project developer. However, if capacities are lacking, or there is a lack of synergies with other non-SOC monitoring tasks, the monitoring approach will not be effectively adopted by those on the ground.

4.4 Outlook: proximal or remote sensing?

Figure  5 highlights the role of featured tools in the different monitoring approaches. Domain a (direct measurement) features conventional wet and dry laboratory methods (L1 and L2) as well as remote and proximal sensing of SOC content (RS1, PS1. PS2). Domain b (activity-based modelling) features paper-, mobile-, or satellite-based surveys of land practices as input to models. In the following we will discuss the outlook for the use of proximal and remote sensing approaches in soil organic carbon monitoring. These approaches, grounded in new technologies, offer the greatest potential to satisfy the diverse needs of stakeholders involved in smallholder carbon projects. We will discuss the opportunities and challenges associated with these approaches, as well as provide recommendations to support their future utility in smallholder crediting schemes.

Approaches and tools in the different SOC monitoring domains

4.4.1 Proximal sensing devices

As described in the results, in-situ spectroscopy produces potentially accurate soil analysis while keeping costs low and maintaining community benefits through field visits for data collection. For smallholder projects, devolving data collection to farmers (i.e. the PS1 approach) could further reduce logistical costs while offering additional community benefits via participation and skills development. As suggested in some interviews, a few farmers can volunteer to be trained in monitoring with this device and may even offer this service to other farmers in the area for additional income. A requirement for this is that soil scanners are easily operable by smallholder farmers and provide results that are translated for farmers into practicable advice. An example of such small-holder friendly device is the SoilPal ( https://ujuzikilimo.com/soil-pal ) scanner developed for rural farmers in Kenya which delivers SMS results in the absence of internet connectivity. Such tools could be programmed with additional features that allow the detailed soil data and GIS coordinates to be uploaded upon each scan to an external database for expert analysis – this would also rule out the possibility of biased reporting by farmers who may be incentivized to do so. To solve the problem of standardisation as described above, proximal sensing devices, as is the case for remote sensing, must find a way to control or account for in-field variations in soil conditions during data collection. Technical solutions for this are proposed in the literature as discussed in Sect.  2.2 . Finally, less complex Standard Operating Protocols must be developed for the use of these devices which consider both the quality requirements for measurements and the ease of use by farmers.

4.4.2 Remote sensing

The advancement of satellite imagery with high spectral resolution enables cost improvements on current data collection approaches while leveraging the accuracy potential of spectroscopic analysis. Collection and processing of plot-level soil or land management data via satellite is, however, still associated with several challenges.

A major limitation to the accurate processing of soil data from satellite imagery as surmised from the results is the highly specialised expertise requirement, which is lacking overall, hindering the use of this approach. Perhaps more important, is the fact that this approach lacks acceptance among carbon project experts as it is yet to be verified by any major certification standard. One reason for this is that many of the techniques used in existing peer reviewed sources are widely different, lacking a basis for comparison and standardisation. Despite this, some commercial organizations already market MRV solutions Footnote 10 promising accurate results with this technology. Because these organizations have proprietary business models, they do not disclose their methods transparently and have not yet published peer reviewed scientific information making them unsuitable for use on the carbon market. It is essential that carbon certification standards oversee these processes to align market needs. Lastly, the accuracy of the remote sensing model is dependent on the soil data used for its calibration. This often requires intensive field sampling cost at the initial stage of setting up the RS1 system. We recommend collaborative effort to establish open-source soil spectral libraries in different regions which can be designed for expansion over time through crowdsourcing and communal sampling. We also suggest the establishment of open-source geostatistical toolboxes containing pre-processing methods, covariates, SOC prediction models, and validation or error accounting techniques, along with guidelines to aid applicability by local experts. This might support the proliferation of RS- methods on the voluntary carbon market.

The AM4/RS2 (remotely sensed activity modelling) approach is limited in detecting a wider range of activities especially on smaller plots. Further studies on the accuracy of this approach are needed to enhance the limited body of knowledge. So far, pilot trials have been done on large commercial-size farms in North America, but they need to be conducted on smaller plots, covering a range of land use types typically occurring with smallholders in developing countries for the technology to be usable there. As a Domain b approach, one important advantage of RS2/AM4 for project developers is that it allows for more frequent MRV cycles, thereby making available cash-flow for project implementation. Activity monitoring is, moreover, essential in projects to monitor practice adoption over the project area even beyond its requirement for SOC modelling. RS2/AM4 could reduce not only the costs of activity data collection, but also the risk that the process poses a data burden to certain smallholders.

A new resulting challenge for community benefits, however, is the integration of feedback loops in such a remote system. Both literature and key informants agree that without ongoing advisory services, smallholders lack the technical knowledge and resources to sustain implementation of project activities and could easily revert to the baseline. Therefore, field visits remain important to sustaining implementation of smallholder carbon schemes and keep the project functioning. It is therefore worth rethinking the cost–benefit trade-off from reduced field monitoring visits since field visits are critical to foster adoption and optimize extension delivery. In fact, monitoring and extension are strongly intertwined in the implementation of current projects using the AM- approach (personal communication, project implementing organisation). Projects in the future using remote sensing-based approaches (RS1 and RS2/AM4) will need to carefully design feedback and advisory components which can sustain the community and environmental benefits of such projects. This may be easily addressed in regions with common smartphone access, since digital tools can be designed that recommend management practices to landowners based on remote sensing analysis. The adoption of such approaches should be tested where it is a possibility. However, in places like the case-study area, where smartphone access is rare and/or internet connectivity is a challenge, this becomes more complex.

Our results and the subsequent discussion indicate that while accuracy and cost are primary concerns in the literature, other factors also impact the usability of monitoring approaches in smallholder carbon projects, reflecting stakeholders' varied expectations for decision-support information. Effective monitoring systems must address these demands to enhance adoptability and ensure the successful implementation of sustainable land management practices. Technological advancements provide promising low-cost, accurate soil analysis methods, but challenges in standardization, expertise, and usability by non-experts remain. Collaborative efforts are crucial to achieve broader acceptance and implementation of these tools in carbon project monitoring. Moreover, integrating effective feedback mechanisms is essential to maintain the benefits and sustainability of these projects, particularly in regions with limited digital access..

5 Conclusion

This study aimed to evaluate approaches for monitoring soil carbon in smallholder agricultural projects, according to their accuracy, level of standardisation, cost, adoptability, and community benefits. Stakeholder interviews and a literature review identified these criteria as vital for the MRV system’s success. This research investigated remote sensing, soil spectroscopy, and soil models in tropical/subtropical developing countries, addressing the limited availability of methods for smallholder agricultural carbon projects in the voluntary market.

It was found that data collection is more associated with monitoring costs, while choice of data analysis methods has a greater impact on accuracy, emphasizing the need for a systems perspective, rather than focusing on individual technologies. Soil spectroscopy, coupled with low-cost data collection such as in-field scanners or remotely sensed spectral imagery, showed the best cost-accuracy performance for repeated soil measurements. However, our study reveals that while accuracy and cost are primary concerns in the literature, other factors also influence the usability of monitoring approaches in smallholder carbon projects, reflecting stakeholders' varied expectations for decision-support information. In this line, field-level data collection remains essential for monitoring adoption and supporting advisory services, which are both crucial for project continuity and community benefits. The use of smartphone technology was identified as a potential tool to integrate feedback loops and bridge this gap if accessible to farmers in a project area. Practice monitoring via remote sensing can replace farm surveys and should be explored further in this context.

Proximal sensing offers rapid data collection with high accuracy analysis and the ability to strengthen participation and capacity building of local actors e.g., via trained farmer representatives. However, standardisation through widely accepted quality control protocols is necessary. Similarly, remote sensing approaches lack common calibration protocols, hindering comparability within and among projects. Moreover, the use of satellite-based spectral measurements still lacks approval by major carbon certification standards. Hence, developing clear data collection protocols and performance benchmarks in collaboration with major carbon certification standards for the use of in-situ and remote technologies in soil carbon monitoring is essential.

To close initial cost/effort gaps associated with calibrating accurate spectral libraries (mainly soil sampling costs), there is a need to synergize efforts from different actors. One option could be a joint investment into open-source libraries of soil spectral and covariate data, which may be used for several purposes apart from soil carbon accounting. Bridging the technical skill gap in developing countries is crucial for the adoption of the newer SOC monitoring approaches to enable small-scale projects and their contribution to climate action. User-friendly decision-making tools such as automated dashboards and toolboxes Footnote 11 can bring long-term cost savings and increased adoption.

Emphasizing accuracy as the sole objective of GHG accounting might impede the adoption of effective SOC accounting approaches that fulfil various other requirements. Arguably, the principle of conservativeness if applied, balances out the requirement for accuracy Footnote 12 and provides project developers with flexibility in selecting an appropriate monitoring approach, enabling them to strike a better balance among other sets of requirements. For instance, monitoring approaches with lower accuracy may still be suitable, if all uncertainties are quantified and reported. The investment decision would then hinge on whether the net value of conservative estimates justifies the effort invested in the project. It is, in any case, crucial to fulfil the principle of transparency that all approaches apply appropriate error accounting techniques for uncertain data sources.

Effective monitoring systems must address the various demands of different stakeholders, leveraging technological advancements for low-cost, accurate soil analysis, while overcoming challenges in standardization, expertise, usability by non-experts, and integrating effective feedback mechanisms to ensure sustainable implementation.

Verra deactivates VM0017 methodology.

Based on a review of projects on the VERRA and Gold Standard registry.

More about Acorn here.

Carbon Plus Grasslands Methodology here.

See the project listing on Verra registry here.

Project description document available at https://registry.verra.org/

Although discontinued, projects registered under this methodology before March 2024 may continue to use it until the next baseline reassessment or crediting period renewal and must then select a different methodology.

In Kenya, there are 47 counties which are subdivided into 290 administrative units called sub-counties. Each sub-county is further stratified into wards which contain smaller villages.

For instance, both proximal sensing approaches PS1 and PS2 are based on the same data collection tool and underlying analysis methods but differ in who does the sampling/data collection. Although they have the same potential for accuracy, actual accuracy of the PS1 approach may be limited by the sampling protocol and the skill / training of the users when compared to PS2. Therefore, the approaches as considered in this paper give a deeper perspective to the whole system.

For example, Boomitra , Earthbanc .

Examples include the FAO Land Resource Planning Toolbox and the Climate Tool box by University of California, USA.

Verra in fact acknowledges that although accuracy should be pursued as far as possible, the high cost of monitoring of some types of GHG emissions and removals, and other limitations make accuracy difficult to attain in many cases. In these cases, conservativeness may serve as a moderator to accuracy to maintain the credibility of project and program GHG quantification. (Verra 2023. VCS Standard v4.4).

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Acknowledgements

We are grateful to the soil protection and rehabilitation for food security (ProSoil) Kenya program of the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) for funding and assisting in organizing the field research for this study. Special appreciation to the respondents, including farmers and experts, and to the Ministry of Agriculture and Livestock, Kenya Agricultural and Livestock Research Organization (KALRO), Prof. John Mburu, Dr. Abed Kiwia, Unique land use, World Agroforestry Center (ICRAF), and aEsti for their valuable collaboration and expertise. Many thanks to Regina Birner for her supervision.

Open Access funding enabled and organized by Projekt DEAL. This research was supported by funding from the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH under the framework of the soil protection and rehabilitation for food security (ProSoil) program, with financial support from the German Federal Ministry for Economic Cooperation and Development (BMZ).

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Adaugo O. Okoli & Athena Birkenberg

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Both authors contributed to the study’s conception and design. Funding acquisition for the study was done by Athena Birkenberg. Material preparation was performed by both authors while data collection and analysis were performed by Adaugo Okoli. The first draft of the manuscript was written by Adaugo Okoli, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Okoli, A.O., Birkenberg, A. Monitoring soil carbon in smallholder carbon projects: insights from Kenya. Climatic Change 177 , 143 (2024). https://doi.org/10.1007/s10584-024-03796-1

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DOI : https://doi.org/10.1007/s10584-024-03796-1

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The University of Chicago The Law School

Abrams environmental law clinic—significant achievements for 2023-24, protecting our great lakes, rivers, and shorelines.

The Abrams Clinic represents Friends of the Chicago River and the Sierra Club in their efforts to hold Trump Tower in downtown Chicago accountable for withdrawing water illegally from the Chicago River. To cool the building, Trump Tower draws water at high volumes, similar to industrial factories or power plants, but Trump Tower operated for more than a decade without ever conducting the legally required studies to determine the impact of those operations on aquatic life or without installing sufficient equipment to protect aquatic life consistent with federal regulations. After the Clinic sent a notice of intent to sue Trump Tower, the State of Illinois filed its own case in the summer of 2018, and the Clinic moved successfully to intervene in that case. In 2023-24, motions practice and discovery continued. Working with co-counsel at Northwestern University’s Pritzker Law School’s Environmental Advocacy Center, the Clinic moved to amend its complaint to include Trump Tower’s systematic underreporting each month of the volume of water that it intakes from and discharges to the Chicago River. The Clinic and co-counsel addressed Trump Tower’s motion to dismiss some of our clients’ claims, and we filed a motion for summary judgment on our claim that Trump Tower has committed a public nuisance. We also worked closely with our expert, Dr. Peter Henderson, on a supplemental disclosure and on defending an additional deposition of him. In summer 2024, the Clinic is defending its motion for summary judgment and challenging Trump Tower’s own motion for summary judgment. The Clinic is also preparing for trial, which could take place as early as fall 2024.

Since 2016, the Abrams Clinic has worked with the Chicago chapter of the Surfrider Foundation to protect water quality along the Lake Michigan shoreline in northwest Indiana, where its members surf. In April 2017, the U. S. Steel plant in Portage, Indiana, spilled approximately 300 pounds of hexavalent chromium into Lake Michigan. In January 2018, the Abrams Clinic filed a suit on behalf of Surfrider against U. S. Steel, alleging multiple violations of U. S. Steel’s discharge permits; the City of Chicago filed suit shortly after. When the US government and the State of Indiana filed their own, separate case, the Clinic filed extensive comments on the proposed consent decree. In August 2021, the court entered a revised consent decree which included provisions advocated for by Surfrider and the City of Chicago, namely a water sampling project that alerts beachgoers as to Lake Michigan’s water quality conditions, better notifications in case of future spills, and improvements to U. S. Steel’s operations and maintenance plans. In the 2023-24 academic year, the Clinic successfully litigated its claims for attorneys’ fees as a substantially prevailing party. Significantly, the court’s order adopted the “Fitzpatrick matrix,” used by the US Attorney’s Office for the District of Columbia to determine appropriate hourly rates for civil litigants, endorsed Chicago legal market rates as the appropriate rates for complex environmental litigation in Northwest Indiana, and allowed for partially reconstructed time records. The Clinic’s work, which has received significant media attention, helped to spawn other litigation to address pollution by other industrial facilities in Northwest Indiana and other enforcement against U. S. Steel by the State of Indiana.

In Winter Quarter 2024, Clinic students worked closely with Dr. John Ikerd, an agricultural economist and emeritus professor at the University of Missouri, to file an amicus brief in Food & Water Watch v. U.S. Environmental Protection Agency . In that case pending before the Ninth Circuit, Food & Water Watch argues that US EPA is illegally allowing Concentrated Animal Feeding Operations, more commonly known as factory farms, to pollute waterways significantly more than is allowable under the Clean Water Act. In the brief for Dr. Ikerd and co-amici Austin Frerick, Crawford Stewardship Project, Family Farm Defenders, Farm Aid, Missouri Rural Crisis Center, National Family Farm Coalition, National Sustainable Agriculture Coalition, and Western Organization of Resource Councils, we argued that EPA’s refusal to regulate CAFOs effectively is an unwarranted application of “agricultural exceptionalism” to industrial agriculture and that EPA effectively distorts the animal production market by allowing CAFOs to externalize their pollution costs and diminishing the ability of family farms to compete. Attorneys for the litigants will argue the case in September 2024.

Energy and Climate

Energy justice.

The Abrams Clinic supported grassroots organizations advocating for energy justice in low-income communities and Black, Indigenous, and People of Color (BIPOC) communities in Michigan. With the Clinic’s representation, these organizations intervened in cases before the Michigan Public Service Commission (MPSC), which regulates investor-owned utilities. Students conducted discovery, drafted written testimony, cross-examined utility executives, participated in settlement discussions, and filed briefs for these projects. The Clinic’s representation has elevated the concerns of these community organizations and forced both the utilities and regulators to consider issues of equity to an unprecedented degree. This year, on behalf of Soulardarity (Highland Park, MI), We Want Green, Too (Detroit, MI), and Urban Core Collective (Grand Rapids, MI), Clinic students engaged in eight contested cases before the MPSC against DTE Electric, DTE Gas, and Consumers Energy, as well as provided support for our clients’ advocacy in other non-contested MPSC proceedings.

The Clinic started this past fall with wins in three cases. First, the Clinic’s clients settled with DTE Electric in its Integrated Resource Plan case. The settlement included an agreement to close the second dirtiest coal power plant in Michigan three years early, $30 million from DTE’s shareholders to assist low-income customers in paying their bills, and $8 million from DTE’s shareholders toward a community fund that assists low-income customers with installing energy efficiency improvements, renewable energy, and battery technology. Second, in DTE Electric’s 2023 request for a rate hike (a “rate case”), the Commission required DTE Electric to develop a more robust environmental justice analysis and rejected the Company’s second attempt to waive consumer protections through a proposed electric utility prepayment program with a questionable history of success during its pilot run. The final Commission order and the administrative law judge’s proposal for final decision cited the Clinic’s testimony and briefs. Third, in Consumers Electric’s 2023 rate case, the Commission rejected the Company’s request for a higher ratepayer-funded return on its investments and required the Company to create a process that will enable intervenors to obtain accurate GIS data. The Clinic intends to use this data to map the disparate impact of infrastructure investment in low-income and BIPOC communities.

In the winter, the Clinic filed public comments regarding DTE Electric and Consumers Energy’s “distribution grid plans” (DGP) as well as supported interventions in two additional cases: Consumers Energy’s voluntary green pricing (VGP) case and the Clinic’s first case against the gas utility DTE Gas. Beginning with the DGP comments, the Clinic first addressed Consumers’s 2023 Electric Distribution Infrastructure Investment Plan (EDIIP), which detailed current distribution system health and the utility’s approximately $7 billion capital project planning ($2 billion of which went unaccounted for in the EDIIP) over 2023–2028. The Clinic then commented on DTE Electric’s 2023 DGP, which outlined the utility’s opaque project prioritization and planned more than $9 billion in capital investments and associated maintenance over 2024–2028. The comments targeted four areas of deficiencies in both the EDIIP and DGP: (1) inadequate consideration of distributed energy resources (DERs) as providing grid reliability, resiliency, and energy transition benefits; (2) flawed environmental justice analysis, particularly with respect to the collection of performance metrics and the narrow implementation of the Michigan Environmental Justice Screen Tool; (3) inequitable investment patterns across census tracts, with emphasis on DTE Electric’s skewed prioritization for retaining its old circuits rather than upgrading those circuits; and (4) failing to engage with community feedback.

For the VGP case against Consumers, the Clinic supported the filing of both an initial brief and reply brief requesting that the Commission reject the Company’s flawed proposal for a “community solar” program. In a prior case, the Clinic advocated for the development of a community solar program that would provide low-income, BIPOC communities with access to clean energy. As a result of our efforts, the Commission approved a settlement agreement requiring the Company “to evaluate and provide a strawman recommendation on community solar in its Voluntary Green Pricing Program.” However, the Company’s subsequent proposal in its VGP case violated the Commission’s order because it (1) was not consistent with the applicable law, MCL 460.1061; (2) was not a true community solar program; (3) lacked essential details; (4) failed to compensate subscribers sufficiently; (5) included overpriced and inflexible subscriptions; (6) excessively limited capacity; and (7) failed to provide a clear pathway for certain participants to transition into other VGP programs. For these reasons, the Clinic argued that the Commission should reject the Company’s proposal.

In DTE Gas’s current rate case, the Clinic worked with four witnesses to develop testimony that would rebut DTE Gas’s request for a rate hike on its customers. The testimony advocated for a pathway to a just energy transition that avoids dumping the costs of stranded gas assets on the low-income and BIPOC communities that are likely to be the last to electrify. Instead, the testimony proposed that the gas and electric utilities undertake integrated planning that would prioritize electric infrastructure over gas infrastructure investment to ensure that DTE Gas does not over-invest in gas infrastructure that will be rendered obsolete in the coming decades. The Clinic also worked with one expert witness to develop an analysis of DTE Gas’s unaffordable bills and inequitable shutoff, deposit, and collections practices. Lastly, the Clinic offered testimony on behalf of and from community members who would be directly impacted by the Company’s rate hike and lack of affordable and quality service. Clinic students have spent the summer drafting an approximately one-hundred-page brief making these arguments formally. We expect the Commission’s decision this fall.

Finally, both DTE Electric and Consumers Energy have filed additional requests for rate increases after the conclusion of their respective rate cases filed in 2023. On behalf of our Clients, the Clinic has intervened in these cases, and clinic students have already reviewed thousands of pages of documents and started to develop arguments and strategies to protect low-income and BIPOC communities from the utility’s ceaseless efforts to increase the cost of energy.

Corporate Climate Greenwashing

The Abrams Environmental Law Clinic worked with a leading international nonprofit dedicated to using the law to protect the environment to research corporate climate greenwashing, focusing on consumer protection, green financing, and securities liability. Clinic students spent the year examining an innovative state law, drafted a fifty-page guide to the statute and relevant cases, and examined how the law would apply to a variety of potential cases. Students then presented their findings in a case study and oral presentation to members of ClientEarth, including the organization’s North American head and members of its European team. The project helped identify the strengths and weaknesses of potential new strategies for increasing corporate accountability in the fight against climate change.

Land Contamination, Lead, and Hazardous Waste

The Abrams Clinic continues to represent East Chicago, Indiana, residents who live or lived on or adjacent to the USS Lead Superfund site. This year, the Clinic worked closely with the East Chicago/Calumet Coalition Community Advisory Group (CAG) to advance the CAG’s advocacy beyond the Superfund site and the adjacent Dupont RCRA site. Through multiple forms of advocacy, the clinics challenged the poor performance and permit modification and renewal attempts of Tradebe Treatment and Recycling, LLC (Tradebe), a hazardous waste storage and recycling facility in the community. Clinic students sent letters to US EPA and Indiana Department of Environmental Management officials about how IDEM has failed to assess meaningful penalties against Tradebe for repeated violations of the law and how IDEM has allowed Tradebe to continue to threaten public and worker health and safety by not improving its operations. Students also drafted substantial comments for the CAG on the US EPA’s Lead and Copper Rule improvements, the Suppliers’ Park proposed cleanup, and Sims Metal’s proposed air permit revisions. The Clinic has also continued working with the CAG, environmental experts, and regulators since US EPA awarded $200,000 to the CAG for community air monitoring. The Clinic and its clients also joined comments drafted by other environmental organizations about poor operations and loose regulatory oversight of several industrial facilities in the area.

Endangered Species

The Abrams Clinic represented the Center for Biological Diversity (CBD) and the Hoosier Environmental Council (HEC) in litigation regarding the US Fish and Wildlife Service’s (Service) failure to list the Kirtland’s snake as threatened or endangered under the Endangered Species Act. The Kirtland’s snake is a small, secretive, non-venomous snake historically located across the Midwest and the Ohio River Valley. Development and climate change have undermined large portions of the snake’s habitat, and populations are declining. Accordingly, the Clinic sued the Service in the US District Court for the District of Columbia last summer over the Service’s denial of CBD’s request to have the Kirtland’s snake protected. This spring, the Clinic was able to reach a settlement with the Service that requires the Service to reconsider its listing decision for the Kirtland’s snake and to pay attorney fees.

The Clinic also represented CBD in preparation for litigation regarding the Service’s failure to list another species as threatened or endangered. Threats from land development and climate change have devastated this species as well, and the species has already been extirpated from two of the sixteen US states in its range. As such, the Clinic worked this winter and spring to prepare a notice of intent (NOI) to sue the Service. The Team poured over hundreds of FOIA documents and dug into the Service’s supporting documentation to create strong arguments against the Service in the imminent litigation. The Clinic will send the NOI and file a complaint in the next few months.

Students and Faculty

Twenty-four law school students from the classes of 2024 and 2025 participated in the Clinic, performing complex legal research, reviewing documents obtained through discovery, drafting legal research memos and briefs, conferring with clients, conducting cross-examination, participating in settlement conferences, and arguing motions. Students secured nine clerkships, five were heading to private practice after graduation, and two are pursuing public interest work. Sam Heppell joined the Clinic from civil rights private practice, bringing the Clinic to its full complement of three attorneys.

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Title: flight delay prediction using hybrid machine learning approach: a case study of major airlines in the united states.

Abstract: The aviation industry has experienced constant growth in air traffic since the deregulation of the U.S. airline industry in 1978. As a result, flight delays have become a major concern for airlines and passengers, leading to significant research on factors affecting flight delays such as departure, arrival, and total delays. Flight delays result in increased consumption of limited resources such as fuel, labor, and capital, and are expected to increase in the coming decades. To address the flight delay problem, this research proposes a hybrid approach that combines the feature of deep learning and classic machine learning techniques. In addition, several machine learning algorithms are applied on flight data to validate the results of proposed model. To measure the performance of the model, accuracy, precision, recall, and F1-score are calculated, and ROC and AUC curves are generated. The study also includes an extensive analysis of the flight data and each model to obtain insightful results for U.S. airlines.

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