Show that you understand the current state of research on your topic.
The length of a research proposal can vary quite a bit. A bachelor’s or master’s thesis proposal can be just a few pages, while proposals for PhD dissertations or research funding are usually much longer and more detailed. Your supervisor can help you determine the best length for your work.
One trick to get started is to think of your proposal’s structure as a shorter version of your thesis or dissertation , only without the results , conclusion and discussion sections.
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Writing a research proposal can be quite challenging, but a good starting point could be to look at some examples. We’ve included a few for you below.
Like your dissertation or thesis, the proposal will usually have a title page that includes:
The first part of your proposal is the initial pitch for your project. Make sure it succinctly explains what you want to do and why.
Your introduction should:
To guide your introduction , include information about:
As you get started, it’s important to demonstrate that you’re familiar with the most important research on your topic. A strong literature review shows your reader that your project has a solid foundation in existing knowledge or theory. It also shows that you’re not simply repeating what other people have already done or said, but rather using existing research as a jumping-off point for your own.
In this section, share exactly how your project will contribute to ongoing conversations in the field by:
Following the literature review, restate your main objectives . This brings the focus back to your own project. Next, your research design or methodology section will describe your overall approach, and the practical steps you will take to answer your research questions.
? or ? , , or research design? | |
, )? ? | |
, , , )? | |
? |
To finish your proposal on a strong note, explore the potential implications of your research for your field. Emphasize again what you aim to contribute and why it matters.
For example, your results might have implications for:
Last but not least, your research proposal must include correct citations for every source you have used, compiled in a reference list . To create citations quickly and easily, you can use our free APA citation generator .
Some institutions or funders require a detailed timeline of the project, asking you to forecast what you will do at each stage and how long it may take. While not always required, be sure to check the requirements of your project.
Here’s an example schedule to help you get started. You can also download a template at the button below.
Download our research schedule template
Research phase | Objectives | Deadline |
---|---|---|
1. Background research and literature review | 20th January | |
2. Research design planning | and data analysis methods | 13th February |
3. Data collection and preparation | with selected participants and code interviews | 24th March |
4. Data analysis | of interview transcripts | 22nd April |
5. Writing | 17th June | |
6. Revision | final work | 28th July |
If you are applying for research funding, chances are you will have to include a detailed budget. This shows your estimates of how much each part of your project will cost.
Make sure to check what type of costs the funding body will agree to cover. For each item, include:
To determine your budget, think about:
If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.
Methodology
Statistics
Research bias
Once you’ve decided on your research objectives , you need to explain them in your paper, at the end of your problem statement .
Keep your research objectives clear and concise, and use appropriate verbs to accurately convey the work that you will carry out for each one.
I will compare …
A research aim is a broad statement indicating the general purpose of your research project. It should appear in your introduction at the end of your problem statement , before your research objectives.
Research objectives are more specific than your research aim. They indicate the specific ways you’ll address the overarching aim.
A PhD, which is short for philosophiae doctor (doctor of philosophy in Latin), is the highest university degree that can be obtained. In a PhD, students spend 3–5 years writing a dissertation , which aims to make a significant, original contribution to current knowledge.
A PhD is intended to prepare students for a career as a researcher, whether that be in academia, the public sector, or the private sector.
A master’s is a 1- or 2-year graduate degree that can prepare you for a variety of careers.
All master’s involve graduate-level coursework. Some are research-intensive and intend to prepare students for further study in a PhD; these usually require their students to write a master’s thesis . Others focus on professional training for a specific career.
Critical thinking refers to the ability to evaluate information and to be aware of biases or assumptions, including your own.
Like information literacy , it involves evaluating arguments, identifying and solving problems in an objective and systematic way, and clearly communicating your ideas.
The best way to remember the difference between a research plan and a research proposal is that they have fundamentally different audiences. A research plan helps you, the researcher, organize your thoughts. On the other hand, a dissertation proposal or research proposal aims to convince others (e.g., a supervisor, a funding body, or a dissertation committee) that your research topic is relevant and worthy of being conducted.
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McCombes, S. & George, T. (2023, November 21). How to Write a Research Proposal | Examples & Templates. Scribbr. Retrieved July 27, 2024, from https://www.scribbr.com/research-process/research-proposal/
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Find employment opportunities with legislatures, states and public policy organizations.
Posted July 24, 2024
Washington Joint Legislative Audit and Review Committee
Hybrid/Olympia, Wash.
Range: $6,832 to $8,400 per month, depending on experience and qualifications.
Posted July 23, 2024
Legislative Budget Office
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Range: $91,996 to $166,048 p/year
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Maryland General Assembly, Department of Legislative Services
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Full Time (On-site)
Aug. 14, 2024
The Legislative Budget Office (LBO) is seeking to fill an Economist position as part of their tax expenditure evaluation team. This is a full-time benefits eligible position. The economist enjoys rewarding work applying statistical and econometric research methods to support the Minnesota Legislature in evaluating tax expenditure policies including, tax credits, tax exemptions, and preferential rates, among other tax incentives. The Legislative Budget Office will determine the starting salary based on the successful applicant’s qualifications and experience. The full salary range for the position is $91,996 to $166,048. The starting salary offered will be based upon an assessment of the candidate’s qualifications and experience. A complete position description is available on the legislative coordinating commission's employment opportunities webpage or call 651-284-6436 to request a copy. For more information regarding the LBO, visit the LBO website.
The Economist position supports the Minnesota Legislature by contributing as an essential member of the LBO team through:
The LBO is committed to building a staff complement that includes diverse perspectives and backgrounds. The LBO plays a meaningful role in the legislative process and provides elected officials with objective and nonpartisan analysis needed to make informed decisions. The Minnesota Legislature offers a comprehensive benefits package.
Comprehensive Benefit Package
The State of Minnesota offers exceptional benefits including low cost medical and dental insurance, employer paid life insurance, other optional insurance, optional pre-tax spending accounts, retirement plan, optional tax-deferred compensation, vacation and sick leave and paid holidays each year. The LBO recognizes there are key elements that make life and work meaningful: health and wellness, financial well-being, professional development, and work/life balance. These benefits, in addition to your salary, make up your total compensation.
During peak periods, LBO staff may experience long work hours and deadlines requiring the ability to stay composed under pressure. The LBO values the unique contributions that candidates with diverse experiences, knowledge, and backgrounds can bring to our work. The State of Minnesota is an equal opportunity employer. We are committed to embedding diversity, equity, inclusion, and accessibility at our workplace.
To ensure consideration, applications should be received by Wednesday, August 14, 2024. Interested applicants must submit a cover letter with their resume to the LBO Economist Search Committee at [email protected] or mail to LBO Economist Search Committee, Legislative Budget Office, 658 Cedar St., Centennial Building, 1st Floor, St. Paul, MN 55155.
If you have specific questions, please contact Christian Larson at [email protected] .
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This project reviewed eel passes in England and considers how to improve them.
SC150001 Eel passes - improving design and performance
This project reviewed how different designs of eel passes in England are working. The aim was to identify any problems with installed passes and consider how to improve the design and performance of existing and future passes.
In response to the severe decline in numbers of European eels in England, eel passes were installed at more than 500 Environment Agency river structures such as dams, weirs, and tide gates. These passes aim to make it easier for juvenile eels to migrate upstream to help restore eel populations in freshwater habitats. As some passes were installed several years ago, this gave us the opportunity to learn lessons to improve eel passage.
This project had 2 phases. The first was a literature review on eel pass performance and seasonal eel migration patterns. The second part was a detailed case studies of 2 facilities that have been operating and monitored for more than 10 years: Judas Gap Weir (Essex) and Greylake Sluice (Somerset).
The final report draws together the phase 1 literature review findings with the phase 2 data on how eel passes have worked. It can be used as a resource to:
The report’s design considerations for eel passes are for the Environment Agency and other structure owners, such as water companies and private individuals. They use lessons learnt from existing passes to help make sure future ones are designed to protect and secure the survival of the nation’s eel population.
The design considerations cover all aspects of pass installation and design, such as:
The report also includes a summary of the characteristics of upstream eel migration that are important when designing and operating passage facilities, for example:
The project identified areas for future research to further improve eel pass design and performance. These are based on a better understanding of the behaviour and requirements of different life stages of eel and lessons learned. This report was written in 2019 and the future research is underway.
Project managers: Juliet de Little, Zora van Leeuwen and Sarah Twohig (FCERM research), Ros Wright (National Monitoring, Fisheries and Ecology)
This project was commissioned by the Environment Agency’s FCRM Directorate, as part of the joint Flood and Coastal Erosion Risk Management Research and Development Programme.
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Title: a survey of prompt engineering methods in large language models for different nlp tasks.
Abstract: Large language models (LLMs) have shown remarkable performance on many different Natural Language Processing (NLP) tasks. Prompt engineering plays a key role in adding more to the already existing abilities of LLMs to achieve significant performance gains on various NLP tasks. Prompt engineering requires composing natural language instructions called prompts to elicit knowledge from LLMs in a structured way. Unlike previous state-of-the-art (SoTA) models, prompt engineering does not require extensive parameter re-training or fine-tuning based on the given NLP task and thus solely operates on the embedded knowledge of LLMs. Additionally, LLM enthusiasts can intelligently extract LLMs' knowledge through a basic natural language conversational exchange or prompt engineering, allowing more and more people even without deep mathematical machine learning background to experiment with LLMs. With prompt engineering gaining popularity in the last two years, researchers have come up with numerous engineering techniques around designing prompts to improve accuracy of information extraction from the LLMs. In this paper, we summarize different prompting techniques and club them together based on different NLP tasks that they have been used for. We further granularly highlight the performance of these prompting strategies on various datasets belonging to that NLP task, talk about the corresponding LLMs used, present a taxonomy diagram and discuss the possible SoTA for specific datasets. In total, we read and present a survey of 44 research papers which talk about 39 different prompting methods on 29 different NLP tasks of which most of them have been published in the last two years.
Subjects: | Computation and Language (cs.CL); Artificial Intelligence (cs.AI) |
Cite as: | [cs.CL] |
(or [cs.CL] for this version) | |
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Apply now Job no: 532410 Work type: Staff Full-Time Location: Main Campus (Gainesville, FL) Categories: Computer Science, Information Technology, Artificial Intelligence, Engineering, Physical/Mathematical Sciences Department: 29240101 - MD-HOBI-GENERAL
Classification Title: | Data Management Analyst III |
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Job Description: | |
Expected Salary: | $85,000; Commensurate with education and experience. |
Minimum Requirements: | Master’s degree in an appropriate area and two years of relevant experience; or a bachelor’s degree in an appropriate area and four years of relevant experience. |
Preferred Qualifications: | Doctorate or master’s degree in outcomes research, statistics, information systems, biomedical informatics or related field and two years of relevant experience. In-depth knowledge of health outcomes study design. Experience with general statistical software (e.g. R, SAS). Experience with machine learning frameworks (R, Python, Weka, RapidMiner, etc). Excellent technical writing and communication skills. Knowledge of basic principles of clinical and data science research. Ability to plan, organize and coordinate work assignments. Ability to work effectively and independently. Ability to communicate effectively verbally and in writing. Ability to establish and maintain effective working relationships with others. |
Special Instructions to Applicants: | In order to be considered, you must upload your cover letter and resume. Application must be submitted by 11:55 p.m. (ET) of the posting end date. This is a time limited position. The University of Florida is committed to non-discrimination with respect to race, creed, color, religion, age, disability, sex, sexual orientation, gender identity and expression, marital status, national origin, political opinions or affiliations, genetic information and veteran status in all aspects of employment including recruitment, hiring, promotions, transfers, discipline, terminations, wage and salary administration, benefits, and training. |
Health Assessment Required: | No |
Advertised: 22 Jul 2024 Eastern Daylight Time Applications close: 04 Aug 2024 Eastern Daylight Time
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We are recruiting a Data Management Analyst III in the Department of Health Outcomes and Biomedical Informatics (HOBI) at the University of Florida. The Data Management Analyst will participate in data driven research activities in the UF Health Cancer Center Cancer Informatics Shared Resource. This position will work with large real-world clinical datasets such as electronic health records in the OneFlorida+ Clinical Research Consortium and UF Health IDR. Responsibilities include: 1) Designing and managing data analysis projects using the above databases. 2) Participation in the design and implementation of research and evaluation studies. 3) Developing data queries and processing scripts to prepare raw data for analysis. 4) Conducting statistical data analyses and interpreting results. 5) Assisting with data collection, reporting and contributing to scientific reports, conference papers, and journal articles. |
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BMC Emergency Medicine volume 24 , Article number: 127 ( 2024 ) Cite this article
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Emergency medical services preparedness in mass casualty incidents is one of the most important concerns in emergency systems. A mass casualty incident is a sudden event with several injured individuals that overwhelms the local health care system. This study aimed to identify and validate the components of emergency medical services readiness in mass casualty incidents which ultimately led to designing a conceptual model.
This research was an explanatory mixed-method study conducted in five consecutive stages in Iran between November 2021 and September 2023. First, a systematic review was carried out to extract the components of emergency medical services preparedness in mass casualty incidents based on the PRISMA guideline. Second, a qualitative study was designed to explore the preparedness components through in-depth semi-structured interviews and analyzed using the content analysis approach. Third, the integration of the components extracted from the two stages of the systematic review and qualitative study was done by an expert panel. Fourth, the obtained components were validated using the Delphi technique. Two rounds were done in the Delphi phase. Finally, the conceptual model of emergency medical services preparedness in mass casualty incidents was designed by a panel of experts.
10 articles were included in the systematic review stage and sixteen main components were extracted and classified into four categories. In the second stage, thirteen components were extracted from the qualitative study and classified into five categories. Then, the components of the previous two phases were integrated into the panel of experts and 23 components were identified. After validation with the Delphi technique, 22 components were extracted. Lastly, the final components were examined by the panel of experts, and the conceptual schematic of the model was drawn.
It is necessary to have an integrated framework and model of emergency medical service readiness in the planning and management of mass casualty incidents. The components and the final model of this research were obtained after the systematic scientific steps, which can be used as a scheme to improve emergency medical service preparedness in response to mass casualty incidents.
Peer Review reports
Mass casualty incidents (MCIs) are among the critical issues that affect the healthcare system including emergency medical service (EMS). The World Health Organization (WHO) defines MCIs as disasters characterized by quantity, severity, and variety of patients that can immediately overwhelm the capability of local medical resources to deliver comprehensive medical care. MCIs occur when the demand for medical services brought on by a sudden event exceeds the capacity of a healthcare system to supply them [ 1 , 2 ]. MCIs span multiple causes including natural disasters, transport incidents, terrorism, armed conflicts, etc. MCIs are often devastating to societies and have profound mortality and long-term consequences [ 3 ]. EMS is a part of the health system that is assigned to emergency response. The WHO considers EMS systems as an integral part of any operational healthcare system. EMS provides care to people in a variety of medical emergencies. One of the most important responsibilities of EMS is to respond to MCIs. When an EMS response involves large casualties, responsible organizations such as the police and fire and rescue teams must utilize resources to expand operations. In large MCIs, there may be more victims than regional EMS can manage, and additional assistance may be required. When the resources are limited or the EMS is involved in the number of casualties, the disaster happens. In most MCIs, routine operations may be developed to manage increased capacity. In the United States, MCIs are managed using the National Incident Management System (NIMS) and the Incident Command System (ICS). All rescue providers and disaster management workforce should be familiar with and competent in using NIMS and ICS [ 4 , 5 ].
EMS plays a major role in managing all phases of MCIs, including prevention, preparedness, response, and recovery [ 6 ]. These systems require an organized and planned approach with adequate resources so that they can effectively manage MCIs. Such important tasks of this system are life-saving measures, triage, and transfer of the injured to medical centers. The EMS system should increase its level of preparedness in response to such disasters. This requires planning, training, coordinating, and sensitizing managers to pay more attention to this area [ 7 ]. Therefore, EMS systems must design a framework based on standard indices. To this end, this study was conducted to identify the components of EMS readiness in MCIs and design a model that can depict the dimensions of EMS preparedness in response to MCIs.
The conceptual framework of this research in line with the study objectives includes three components: emergency medical service (EMS), preparedness, and mass casualty incidents (MCIs).
An Emergency Medical Service can be defined as "a comprehensive system which provides the organization of staff, facilities, and equipment for the effective, coordinated, and timely delivery of care and emergency services to victims of sudden illness or injury." The ambition of EMS focuses on providing timely care to the victims of sudden and life-threatening injuries or emergencies to prevent undesired mortality or long-term morbidity. The function of EMS can be simplified into four main components: accessing emergency care, care in the community, care en route, and care upon arrival to receiving care at the healthcare facility [ 8 , 9 ]. In addition to the routine responsibility of EMS, one of the important tasks of this system is disaster management [ 2 ].
Preparedness is the knowledge and capacities developed by governments, professional response and relief organizations, communities, and individuals to effectively anticipate, respond to, and recover from the impacts of likely, imminent, or current hazards, events, or situations [ 10 ]. Preparedness is a continuous cycle of planning, organizing, training, equipping, exercising, evaluating, and taking corrective action to ensure effective coordination during the incident response [ 11 ]. Preparedness within the field of emergency management can best be defined as a state of readiness to respond to a disaster, crisis, or any other type of emergency [ 12 , 13 ]
A Mass Casualty Incident (MCI) can be defined as "an overwhelming event, which generates more victims at a time than locally available resources can manage using routine procedures. It requires exceptional emergency arrangements and additional or extraordinary assistance." MCIs can occur as a consequence of a wide variety of events: disasters (both natural and man-made), terrorist attacks, motor vehicle collisions, etc. Whatever the cause of the event is, the characterizing feature of an MCI is the number of victims large enough to disrupt the normal functioning of healthcare services. MCIs can be classified into different levels according to either the number of potential victims or the entity of the response [ 14 ] .
This research was an explanatory mixed method suggested by Creswell [ 15 ] which was conducted in five consecutive stages in Iran between November 2021 and September 2023. The purpose of this mixed-method study was to identify the main components of EMS preparedness in MCIs in several systematic stages and then design a conceptual model that can represent the essential elements of EMS readiness in MCIs in the form of a framework. The questions of this research were as follows:
What are the main and effective components of EMS preparedness in response to MCIs?
What will be the final model of EMS readiness in response to MCIs?
The research implementation diagram is shown in Fig. 1 .
Research implementation diagram
Eligibility criteria and search strategies.
This study was conducted based on the Preferred Reporting Item for Systematic Reviews and Meta-analyses (PRISMA-ScR) instruction. The systematic review instruction included the background data, review questions, inclusion and exclusion criteria, search strategies, selection of studies, criteria to review the studies, literature review, data extraction, and reporting. A systematic search was performed from January 1970 to February 2022 in peer-reviewed English texts related to the research question—i.e., what the components of EMS preparedness for MCIs are. First, a rapid and general search was conducted in the Cochrane Library database to ensure the lack of duplicate studies. The results indicated that there were no duplicate articles. The electronic databases searched included PubMed, Cochrane Library, Scopus, Science Direct, and ProQuest. The gray literature, such as books, theses, conference articles, and websites, was also searched. The “AND” operator was used to search among the groups of words considered as separate concepts. For synonym words, the “OR” operator was used. The search was conducted on the titles, abstracts, and keywords of the articles. Medical Subject Headings (MeSH) terms were used to find articles in the PubMed database. The search strategy is presented in Table 1 .
The keywords were selected using MeSH and investigating the studies based on the objectives. In the next step, a full list of references for all the articles was prepared, and the titles of the articles were investigated by the researchers to omit the irrelevant ones. The END NOTE software, version X8, was used to manage the resources.
The main keywords were used to explore the studies related to EMS preparedness in MCIs. First, the titles of the articles were evaluated by two independent reviewers. We determined whether titles, keywords, or abstracts were included in the study subject. In the case of disagreement, they were verified by one external reviewer using the consensus method, and any disagreement was resolved. Then, the abstracts were assessed; finally, the full texts of the articles were evaluated based on the validated checklists. The STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) and the COREQ (Consolidated criteria for reporting qualitative research) checklists were used for the quality evaluation of the studies. The included articles were written in the English language. Unpublished articles (gray literature), protocols, conference papers, guidelines, and reports from creditable organizations were reviewed as well. To analyze the risk of bias, two researchers independently performed all quality assessment processes based on the Cochrane Collaboration tools.
The articles in the field of hospital emergency department, those irrelevant to the research questions, guidelines outside the scope of the study, and the articles that did not meet the expected quality according to the validated checklists were excluded from this study.
First, the titles of all the articles extracted from the databases were checked by two independent reviewers. The articles that met the inclusion criteria and were relevant to the research question were selected. In the next step, the author studied the abstracts of the selected articles. Then, those abstracts that were completely in line with the study objectives and the inclusion criteria were extracted, and their full texts were assessed by the authors. Finally, the articles relevant to EMS preparedness in MCIs were selected.
The essential information was extracted after reading the articles carefully based on the summaries and collection forms. This form included the title, corresponding author, research objective, research population, samples, country, time of research, research design, instruments, method, results, and conclusion sections. The summary forms were filled out for each article. These forms were evaluated by two independent researchers after reviewing all the articles; the data were then presented in a table. If there were disagreements in data extraction, an external researcher commented on the conflicting issues, and any disagreement was resolved [ 16 ].
This qualitative study was conducted using a content analysis approach. Inductive coding was adopted in this approach. Recently, three approaches have been presented in content analysis, including conventional, summative, and directed, which differ in coding and trustworthiness. In the conventional approach, classification codes are extracted directly from the data [ 17 ]. The study adopted the conventional content analysis as well. This study was conducted using the consolidated criteria for reporting qualitative research (COREQ).
Sampling was done from five provinces (Tehran, Fars, Hormozgan, Hamadan, and Kerman) in Iran from April 2022 to mid-March 2023. The participants were managers and members of the EMS incident command team, EMS field experts, technicians, paramedics, and EMS telecommunicators with rich information who were selected using the purposive sampling method. Sampling continued until data saturation. The inclusion criteria were as follows: (1) having at least a bachelor's degree; (2) having experiences in MCIs context and being motivated to participate in the study; and (4) signing an informed consent form.
Data were collected through semi-structured interviews by the researcher (VS), using a pilot-tested interview guide. The interviews were conducted face-to-face, and their follow-up was mostly done using a telephone. The study outline was approved by three members of the research team. Some of the main interview questions were as follows:
In what ways is EMS more vulnerable during MCIs?
What measures are needed to be taken in EMS before MCIs?
What features should EMS systems have to respond to MCIs?
What elements affect EMS readiness in MCIs?
All the interviews were completed and recorded by the main researcher (VS). The interviews lasted about 30–90 min, and the participants responded to all the questions according to the research outline. Before the interview, the necessary arrangements were made with the participants. The interviews were conducted in a quiet and uninterrupted atmosphere. The researcher refrained from using negative, judgmental, and forgiving statements and attitudes. Data collection continued until saturation, and the researcher stopped sampling when he realized that no new data was obtained and that there were a lot of duplicated data.
A qualitative method was used for data analysis. After each interview, the recordings were transcribed, and the main researcher (VS) used the content analysis method to analyze and summarize the data. The steps were: (1) familiarization: the text was read repeatedly to familiarize the subjects with the qualitative data; (2) coding: the open coding method was used to analyze the data line by line, and essential words and phrases (unit meaning) were recorded in the margins of the content; and (3) integration: each important meaning unit was described in a descriptive code, and codes with the same meaning were integrated [ 18 ]. MAXQDA was used for data organization and coding. After the analysis, two other researchers, who were familiar with the telephone records, performed a peer review to ensure the validity of the analysis results.
Long-term engagement with participants, member and peer checking, presentation of rich descriptions of data, and data analysis were used for rigor [ 19 ]. Besides long-term communication with the participants, the research team spent enough time on data collection and follow-up with the interviewees. Transcriptions along with coding and categories were shown to two qualitative researchers for peer check. Their confirmation was obtained after applying their comments. A brief report of the interviews and the extracted codes was given to the interviewees, who approved it to examine the members. There was also an attempt to consider the maximum diversity in sampling for transferability [ 20 ].
The integration of the results was done using joint display technique in the expert panel [ 21 ]. The members present in the panel consisted of 10 experts in the field of EMS and MCIs area who were selected purposefully. To integrate the findings of two qualitative stages and systematic review, we first entered a table with three columns into Word software. On the left side, the findings of the systematic review were entered, and on the right column, those of the qualitative study were entered. A column in the middle was considered empty to enter the integrated findings. Before entering the findings into the table, the research team did a content analysis on the findings of the systematic review, and new concepts were obtained from the data extracted from this stage. Two expert researchers in the field of EMS independently reviewed the results of this content analysis, and any disagreement was resolved. This content analysis was done because, firstly, the components of the systematic review were unique in terms of content and did not overlap with each other. Secondly, the components of the two stages should have a closer affinity for integration. It is worth mentioning that two researchers in the field of EMS and the people present in the panel were very familiar with the setting of EMS and this selection of people was done purposefully. After entering the final results of each step into the table, the panel members reviewed all the findings of both studies separately. Then, the components were read one by one from the left side by the researcher and the members were asked to determine the similarity of this finding with that of the right column by drawing a line through critical thinking. To reach a consensus at this stage, voting by raising hands was used. This process was done for all the findings in two consecutive panel sessions until the completion of the integration stage. Table 2 shows integration of components using the display joint method.
The Delphi technique was used to validate the integrated components. It is a systematic approach to elicit opinions from a group of experts on a specific topic [ 22 ]. Targeted sampling was used to select the experts who were working in EMS systems at this stage. The research population consisted of experts in the field of health in disasters and emergencies, emergency medicine specialists, and managers of the EMS system of Iran (Fars, Hormozgan, Tehran, Hamedan, and Kerman provinces). A questionnaire containing extracted components was created by the research team and sent to 29 participants who were selected purposefully. This questionnaire included 23 questions scored using a five-point Likert scale, and the scored ranged from completely agree (score 5); I agree (score 4); I have no opinion (score 3); I disagree (score 2), and completely disagree (score 1). In the questionnaire form, the purpose of this step was explained, and the consent form was signed by the participants. Out of 29 people, 22 completed the questionnaire. SPSS version 16 software was used for data analysis. Descriptive statistics were used to interpret the data. Mean and standard deviation indicators were used to describe the percentage of the participants' agreement on each component. In the first round, the components whose average score was less than 50% were eliminated. A percentage of agreement greater than 75% for each component means that it is accepted. The components whose percentage of agreement was between 50 and 75% were included in the second round, and if more than 75% agreement was obtained, they were approved [ 23 ].
A panel of experts was used to design the model. This panel was held with the presence of 7 disaster context specialists and EMS experts who selected purposefully. For this purpose, the objectives of the research were first described to the experts. Then, the components obtained from the previous steps were explained to them so that they could express their opinions and ideas about the role and placement of the variables, and schematic of the model. Since in this model the cause-effect relationship of the variables was not considered, an attempt was made to design a simple and expressive model by considering the international standards. Therefore, to examine the models, we searched internationally recognized EMS agencies and systems such as the Federal Emergency Management Agency (FEMA), Pan American Health Organization (PAHO), and other related databases. After reviewing and discussing, a model that was close to our goals was selected finally. However, minor changes were made to this model to make it easier to understand. This model was introduced by Adam Tager. Adam Tager serves as the disaster preparedness program manager in the FEMA mission support executive office. In this role, he leads preparedness and response attempts on behalf of the associate administrator for mission support. Before this, he served as a field operations analyst and a consultant supporting FEMA and the Department of Defense. He has worked with national and state emergency management programs and has had roles in all-hazards event response and recovery, development and conduct of training exercises, and development and writing after-action reports [ 24 ]. Therefore, this model was selected, and after some changes was made in it, the schematic of the model was drawn.
After searching the databases, 20,499 articles were identified; of them, 201 were in Direct Science, 1417 in PubMed, 16,192 in Scopus, 2677 in ProQuest, and 12 in the Cochrane Library. After screening and evaluating the quality of the articles, finally, 10 articles were included in the study. The components of the EMS preparedness in MCIs were identified after reviewing the articles. The 16 main components including education and training, skills and experience, relationships and psychological factors, management planning, constant improvement, coordination, manpower, equipment and ambulance, support processes, command and control, incident scene, triage, evacuation and gathering, treatment, communication, distribution, transport, and follow-up of the injured were extracted. These were extracted by the research team through summarizing the findings of the articles. The components were classified into four categories, including individual improvement, group improvement, resources, and operations through thematic analysis [ 16 ].
Thirty-six participants (24 men and 12 women) were included in the study. Thirteen components were extracted from the study and classified into five categories including strengthening management and organization, individual and group empowerment, capacity expansion, technology and infrastructure development, and operational response measures [ 20 ], as shown in Fig. 2 .
Findings of the qualitative stage (this printed table is the result of our article published in reference 20)
23 components were extracted from combining the results of the two stages of systematic review and qualitative study in the panel of experts. The integrated components are presented in Table 3 .
In the first round of Delphi, 22 out of 28 participants completed the questionnaire. In the second round of Delphi, out of 28 subjects who had received the questionnaires again, 22 experts filled out the questionnaires sent. Descriptive statistics showed that 22 subjects entered the Delphi stage, of whom 16 were men and 6 were women in the age range of 32–55 years and with a work experience of 5–25 years. The results of the statistical analysis showed that out of 23 components, only "Establishment of EMS decontamination teams in CBRNE" scored less than 2.5 (with an average score of 2.27, which means less than 50% of the acceptable score), so it was eliminated during the first round.
According to the results, the average of most of the components was more than 3.75 (more than 75% agreement), and only two components, "Common triage and treatment" and "Unified emergency contact number", had an average score of more than 2.5 and less than 3.75 (i.e. agreement between 50 and 75 percent) and were sent to the second round of Delphi. In the second round of Delphi, the two components mentioned were again given to 22 participants and the scores were analyzed. The results showed that the average agreement score of these components was more than 3.75 (i.e. more than 75% agreement).
After the completion of the Delphi phase, it was found that 22 out of the 23 components finally got the necessary points; thus, they were approved for review in the next phase which was related to the panel of experts. All the Delphi rounds and the final scores are shown in Table 4 .
The design of the schematic was based on the model proposed by Adam Tager. According to the acceptability and validation of this model in the panel of experts, with some modifications in line with the study objectives, this model was selected and finally the schematic form of the model was designed. This pattern consists of classes that are placed in a cycle, while the main subject of the model is in the center, and the subclasses are placed outside the cycle in their partitions. After content analysis in the panel, all components were placed in 5 main categories including "Command", "Operations", "Resources", "Communications and Information", and "Group and Individual Empowerment". The final model of EMS preparedness in response to MCIs is designed in Fig. 3 .
The model of EMS preparedness in MCIs
After several consecutive steps in this research, the components of EMS preparedness in MCIs which were the main objectives of the study were finally determined. One of the reasons why the research team decided to do a mixed-method work was the importance of the area. Maybe, if we had a single study approach to achieve the main goal, we could not confidently trust the obtained result. Therefore, the mixed method was adopted. Systematic review studies contain rich results, and we have made comprehensive findings in this phase. The findings of the systematic review included the experiences of EMS systems around the world in response to MCIs. Most of the results of this phase, according to the selected articles, were taken from the real experiences of EMS systems, and this was a turning point in the findings obtained in this research. Considering that this study was in a special context (the field of emergencies and disasters), it would be better to consider complementary methods to achieve the goals. Therefore, we decided to look for unwritten experiences in disaster context, in addition to the published documents. For this reason, we chose a qualitative approach to obtain the experiences of people who spend their lives in EMS systems. The purpose of conducting a qualitative study was to enrich the results in this mixed method. A qualitative study was conducted with in-depth semi-structured interviews in Iran, and the results obtained were mostly consistent with those of the systematic review phase. After passing through these two steps, we integrated the findings in a systematic way to obtain more comprehensive results. After several consecutive stages, 22 main components were finalized, which were drawn in a conceptual model in 5 main levels including command, operation, resources, communication and information, and group and individual empowerment for better understanding and implementation. Although the known components in this research have many similarities with the studies done, the differences mostly originate from regional and national structures and policies. One of the highlights of this study was the removal of the component of "EMS decontamination teams in CBRNE" in the first round of Delphi. Although this component was extracted from the systematic review [ 16 ], it was not accepted in the remaining stages, including the qualitative study [ 20 ], Delphi stage, and panel of experts. One of the reasons this issue arose in the qualitative study and expert panel was that EMS has complex tasks in triage, treatment, transfer, and other incident management processes [ 25 ], and decontamination is a sensitive operation that requires specialized logistics and equipment that is beyond the scope of most EMS systems. In most emergency systems, the duty of decontamination (according to the type of the risk) is the responsibility of the fire department, army, safety units of refineries and factories, and so on. However, this component must be accepted in some EMS systems due to the existence of resources, equipment, integration of rescue teams, and regional policies [ 26 ]. Due to the complexity of CBRNE incidents, regional policies are essential, and this component may not be accepted globally in an EMS setting. However, this issue depends on national and regional policies.
In addition, components such as a common emergency contact number, common triage and treatment system, and tactical teams that are used in many emergency systems still have pros and cons in some countries. However, the rest of the components, including the unified command, strengthening of communication, education and training, physical and psychological factors, and so on, are present in most EMS systems as the main indicators of readiness although there may be differences in how they are implemented. Nonetheless, in this research, the components of EMS preparedness in MCIs were explored in several stages so that a model with reliable indicators for planning and policymaking can be developed.
Various methods have been used in developing EMS preparedness and response models in MCIs. Among these, dynamic modeling methods, computer modeling, conceptual modeling, and modeling with cause-effect relationships can be mentioned.
A study by Lee aimed to simulate the distribution of emergency relief equipment for disaster response operations. In this study, the concern was that in the event of disasters such as storms, earthquakes, and terrorism, there is a need to distribute emergency relief equipment to the victims to protect their health and lives. The research team developed a modeling framework for disaster response in which the supply chain of relief supplies and distribution operations were simulated and analyzed to test the optimal transportation of relief supplies to various distribution points. The disaster response simulation model included the modeling of the relief resource supply chain and operations at the distribution point. The results showed that the model could evaluate a wide range of disaster scenarios, evaluate disaster response plans and policies, and identify better approaches for government agencies and first responders [ 27 ].
In another study, a simulated model of EMS services in MCIs was designed by Su in Taiwan. In this study, object-oriented simulation software was used to improve EMS care. In this research, a computer virtual simulated model was designed. The results showed that the most efficient part of this model in caring for the injured is when the integrated deployment of EMS is launched along with the increase of emergency networks and specialized life-saving protocols [ 28 ].
Another research was conducted by Pasupathy in Belgium to design a simulated model of casualty management in disasters and emergencies. In this study, a profile of the real injured was drawn by the elites of the pre-hospital field. These profiles were drawn in a medical emergency model where a single response was given by the system to real casualties. The medical emergency response model focused on emergency services operations including triage, evacuation, and medical procedures. Medical decisions such as whether to evacuate or treat at the scene were based on the victim’s breathing, heart rate, and motor response. Finally, a simulated model was designed that was related to road accidents and showed how much resources could affect the prognosis in these incidents [ 29 ].
In China, a model entitled EMS response dynamic model was designed in response to MCIs. This study was conducted to find out the EMS-MCI modeling in Shanghai, improving rescue efficiency in MCIs and providing a possible method for quick decision making in these incidents. This model was designed using the Vensim DSS program and intervention scenarios by adjusting the scales of accidents, ambulance allocation, emergency medical staff allocation and the efficiency of organization and command. The results showed that by increasing the number of ambulances and improving the efficiency of the organization and command, the mortality rate decreased significantly [ 30 ].
Tseng in China designed a theoretical model of EMS response in tunnel-related traffic incidents as a scenario-based computer simulation model. In this study, based on a theory, data related to the general characteristics and components of MCIs were collected in order to create a simulation model based on the method of emergency response plans. In this method, a disaster response simulation model was presented using realistic accidents taken from previous experiences. In this study, the main variables included EMS response components in MCIs, pre-hospital time indicators, the ability to save and preserve hospital life, and the level of organizational and command efficiency. This model is called causal curve diagram and included 5 main parameters with 102 variables, which were connected in the form of curvilinear flows and based on one-way or two-way relation. In addition, the subsystems of this model include 5 items: MCIs, hospital rescue and life preservation operations, organization and control, emergency center, and finally prognosis of the injured which were connected through input and output variables [ 31 ].
The results of this mixed method indicate that EMS systems need to strengthen specific components to increase their readiness in response to MCIs. The components extracted from this study were identified in depth with several approaches which were finally drawn in the form of a simple model. Due to the deep and scientific view in the methodology of this research and the extraction of validated findings, these results can be theoretically used in EMS planning and policies in the field of disasters. In addition, EMS systems and Partner organizations can use the results of this research in practice and personnel training. Due to the importance of the mixed method in achieving rich results in the field of disasters, the method of this study can be used more than single approaches. Also, the methodology and techniques of this research can be used as a pattern in the design of future studies in important areas such as disasters where it is necessary to achieve valid and vital results.
Due to the complexity of management and operational planning in most MCIs, it would be better to draw the preparedness plans in a simple and comprehensible way so that a quick and effective response can be delivered. In this research, the goal was to create a simple conceptual model that represents the main components of EMS preparedness in MCIs. The most important distinguishing feature of the model designed in this study was that simulation, computer and special software methods were not used as in the above-mentioned studies and the main attempt was to design a model to cover the important readiness indicators of EMS systems in response to MCIs so that they can be used easily. Although most of the components were identified and validated in this study, there may be other components that can be unique to states and regional policies. For example, some specific indicators were related to the regions with specific climatic and geographical conditions that overshadow the EMS response. However, in this research the components of EMS preparedness in MCIs were only introduced and presented in the form of a model, and the effectiveness of this model was not measured practically. Therefore, it is recommended that the effectiveness of this model in the management of MCIs in practical exercises, simulations and real incidents should be measured.
In the systematic review phase, one of the limitations was the lack of access to some electronic databases such as Web of science (WOS), for searching articles. Unfortunately, due to economic and political sanctions in Iran, some databases were not available at the time of the search and we had to ignore them. This issue worried us because we might have missed some studies. However, we tried to use other reliable electronic databases such as PubMed, Scopus, Science direct, ProQuest, and Cochrane.
MCIs are complex conditions that can seriously overwhelm the EMS function. Improving EMS readiness in MCIs is multifactorial and influenced by regional and national conditions. Designing a model with different methods in improving EMS readiness in MCIs can have a significant impact on better understanding of the plans and policies in simulated environments and real incidents. The designed model can be used as a framework for implementing EMS management strategies in MCIs.
The data are not publicly available due to privacy or ethical restrictions, but the data that support the findings of this study are available on reasonable request from the corresponding author.
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The research team would like to thank the participants for their valuable time and the research deputy of Shiraz University of Medical Sciences.
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Department of Medical Emergencies, School of Paramedicine, Faculty of Jahrom University of Medical Science, Jahrom, Iran
Vahid Saadatmand
Department of Health in Disasters and Emergencies, School of Health Management and Medical Information Sciences, Faculty of Shiraz University of Medical Sciences, Shiraz, Iran
Milad Ahmadi Marzaleh
English Department, Faculty of Paramedical Sciences, Shiraz, Iran
Nasrin Shokrpour
Department of Surgery, School of Medicine, Faculty of Shiraz University of Medical Sciences, Shiraz, Iran
Hamid Reza Abbasi
Department of Health in Disasters and Emergencies, School of Health Management and Medical Information Sciences, Faculty of Shiraz University of Medical Sciences, Alley 29, Qasrodasht Ave, Shiraz, 71336-54361, Iran
Mahmoud Reza Peyravi
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Conceptualization, VS, M AM, MR P; methodology, VS, MR P; Investigation and formal analysis, VS, HR A, MR P; writing—original draft preparation, VS, N SH, M AM; writing—review and editing, VS, N SH. All authors have read and approved the final version of the manuscript. The corresponding author had full access to all of the data in this study and takes complete responsibility for the integrity of the data and the accuracy of the data analysis.
Correspondence to Mahmoud Reza Peyravi .
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The study was approved by the ethics committee of Shiraz University of Medical Sciences with the code of IR.SUMS.NUMIMG.REG.1401.020, and consent was obtained from all participants and experts. The subjects were volunteers and were assured that the data would be strictly confidential, and the principle of anonymity would be adhered to. Additionally, the participants and experts could withdraw from the study any time they wished.
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Saadatmand, V., Ahmadi Marzaleh, M., Shokrpour, N. et al. Designing a model of emergency medical services preparedness in response to mass casualty incidents: a mixed-method study. BMC Emerg Med 24 , 127 (2024). https://doi.org/10.1186/s12873-024-01055-1
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It is of great significance for the engineering popularization of CO 2 -ECBM technology to evaluate the potential of CCUS source and sink and study the matching of pipeline network of deep unworkable seam. In this study, the deep unworkable seam was taken as the research object. Firstly, the evaluation method of CO 2 storage potential in deep unworkable seam was discussed. Secondly, the CO 2 storage potential was analyzed. Then, the matching research of CO 2 source and sink was carried out, and the pipe network design was optimized. Finally, suggestions for the design of pipe network are put forward from the perspective of time and space scale. The results show that the average annual CO 2 emissions of coal-fired power plants vary greatly, and the total emissions are 58.76 million tons. The CO 2 storage potential in deep unworkable seam is huge with a total amount of 762 million tons, which can store CO 2 for 12.97 years. During the 10-year period, the deep unworkable seam can store 587.6 million tons of CO 2 , and the cumulative length of pipeline is 251.61 km with requiring a cumulative capital of $ 4.26 × 10 10 . In the process of CO 2 source-sink matching, the cumulative saving mileage of carbon sink is 98.75 km, and the cumulative saving cost is $ 25.669 billion with accounting for 39.25% and 60.26% of the total mileage and cost, respectively. Based on the three-step approach, the whole line of CO 2 source and sink in Huainan coalfield can be completed by stages and regions, and all CO 2 transportation and storage can be realized. CO 2 pipelines include gas collection and distribution branch lines, intra-regional trunk lines, and interregional trunk lines. Based on the reasonable layout of CO 2 pipelines, a variety of CCS applications can be simultaneously carried out, intra-regional and inter-regional CO 2 transport network demonstrations can be built, and integrated business models of CO 2 transport and storage can be simultaneously built on land and sea. The research results can provide reference for the evaluation of CO 2 sequestration potential of China's coal bases, and lay a foundation for the deployment of CCUS clusters.
Introduction.
CCUS stands for CO 2 Capture, Utilization and Storage 1 . On the one hand, CCUS technology can reduce CO 2 emissions in the atmosphere and reduce the concentration of greenhouse gases 2 , 3 . On the other hand, it can help industries with CO 2 high-emission achieve low-carbon development and promote economic transformation 4 , 5 . Therefore, CCUS technology has broad application prospects in the field of global energy and environment. CO 2 emissions from coal are the largest source of carbon emissions in China, and it will take a long time for China to transform its energy situation 6 , 7 . Therefore, based on CCUS technology, it is of profound significance to reduce CO 2 emissions from coal, and can promote the realization of China's dual-carbon strategy.
CO 2 geological sequestration, a core component of CCUS, is an effective way to achieve large-scale de-carbonization 8 , 9 . Scientific evaluation of CO 2 storage potential in sedimentary basin and realization of source-sink matching are the basis of CCUS cluster deployment 10 , 11 . Major sedimentary basin in China have great potential for CO 2 storage, and the storage forms are diverse 12 . However, due to the lack of unified methods for CO 2 storage potential in sedimentary basin in China, the assessment of CO 2 storage potential greatly varies 13 . The CO 2 sequestration potential of geological body in China, such as oil and gas fields, deep unrecoverable seam, production and closed mines and goaf areas, is unclear and needs to be evaluated in detail.
Carbon emission sources in China's coal base are concentrated, and CO 2 emission sources and CO 2 storage sinks are highly overlapping 14 , which provides favorable conditions for CCUS cluster deployment. CCUS technology is the only way for coal base to achieve near zero for CO 2 emission in the future, and the deployment of “Coal base + CCUS” cluster has scale and agglomeration effects 15 . The geographical proximity of CO 2 sources and sinks can save more costs for CO 2 transportation, and the geographical concentration of a large number of CO 2 sources and sinks is also conducive to large-scale and clustered layout engineering practices. Geological body, such as deep unrecoverable seam, is the most typical forms of CO 2 storage in coal bases 16 , 17 . However, its CO 2 geological storage is still in the exploration stage, and there are few studies on its CO 2 storage potential 18 . Therefore, it is necessary to establish potential assessment methods suitable for the characteristics of China’s coal bases.
The CO 2 sequestration process can be simplified as the reverse process of the CBM extraction process, and its core mechanism is the dynamic process of CO 2 adsorption and displacement of CBM 19 , 20 . Therefore, the mechanism of CO 2 geological storage in unworkable seam is mainly about the mechanism of CO 2 adsorption and desorption in coal seam 21 . The coal resource in Huainan and Huaibei coalfields account for 97.7% of the total resources in the province, and the distribution is concentrated 22 , 23 , 24 . Therefore, the Huainan coalfield is determined as the estimation coalfield for CO 2 storage in this study. Due to the limitation of technical and geological conditions, the buried depth of coal mining in Anhui province is limited to less than 1000 m at present stage, and the coal seam with 1000–2000 m is the resource amount, which will be exploited in the next stage, and belongs to the deep unworkable seam at the present stage 16 , that is, the geological reserves with burial depth of 1000–2000 m are used to estimate the CO 2 storage potential in Anhui province.
In this study, the deep unworkable seam in Huainan coalfield was taken as the research object. Firstly, the evaluation method of CO 2 storage potential in deep unworkable seam was discussed. Secondly, the CO 2 geological storage potential was analyzed. Then, based on the lowest cost objective function and improved mileage saving method, the matching research of CO 2 source and sink for CO 2 geological storage was carried out, and the pipe network design was optimized. Finally, from the perspective of time and space scale, suggestions on the design of network planning of CCS source and sink are put forward in Huainan coalfield. The research innovations are described as follows: (1) Evaluation method of CO 2 storage potential in deep unworkable seam is discussed; (2) Matching problem of CO 2 source and sink is studied, and its pipe network design is optimized; (3) Design idea of network planning of CCS source and sink is systematically proposed. The results can provide reference for the evaluation of CO 2 sequestration potential of coal bases in China, and lay a foundation for CCUS cluster deployment.
Geological background of the study area.
Based on regional structural analysis, the Huainan coalfield is located at the southern margin of North China Plate. In the west–east direction, the coal field boundary lies between the Kouziji-Nanzhaoji faults and the Xinchengkou-Changfeng faults. From north to south, the coalfield boundary lies between the Shangtangming-Longshan faults and Yingshang-Dingyuan faults (Fig. 1 ) 25 , 26 . The coalfield is a near east–west hedge tectonic basin with imbricate fan composed of nappe structures on both sides of the basin and simple synclinic structure in the interior (Fig. 1 ).
Geological background of Huainan coalfield and distribution of CO 2 source-sink geological points in deep unrecoverable coal seams.
The coal-bearing strata are Taiyuan formation of upper Carboniferous series, Shanxi formation and Xiashihezi formation of lower Permian series, and Shangshihezi formation of upper Permian series, with a total thickness of about 900 m and about 40 layers of coal seams 27 , 28 . In the coal-bearing strata, there are 9–18 coal layers with a single layer thickness greater than 0.7 m on average, the maximum thickness is 12 m, and the total thickness is 23–36 m, which are distributed in Shanxi formation, Xiashihezi formation and lower part of Shangshihezi formation. In this study, the CO 2 emission sources were 10 coal-fired power plants in the coalfield with numbered D1-D10, respectively. Deep unworkable seams are CO 2 storage sinks, which are bounded by faults and numbered B1-B15, respectively (Fig. 1 ).
In deep unworkable seam, CO 2 geological storage is mainly in adsorbed, dissolved and free states 29 , and adsorption storage is the main storage form of coal seam 30 . Considering the storage differences of different phase of CO 2 , the following potential assessment model of CO 2 storage can be adopted 16 , 31 :
where \(M_{{{\text{CO}}_{2} }}\) is CO 2 storage capacity, t; ρ CO2 is the CO 2 density, kg/m 3 ; M coal is proved coal reserves, t; m ab , m d and m f are the stored quantity of CO 2 adsorbed, dissolved and free states in coal per unit mass, m 3 /t.
In the unit mass coal, the storage potential of CO 2 adsorbed state in deep unworkable seam can be characterized by the following formula 16 , 31 :
where P is the reservoir pressure, which is also CO 2 adsorption pressure, MPa; T c is CO 2 critical temperature, K; Z is the CO 2 compression coefficient; p c is CO 2 critical pressure, MPa; T is the reservoir temperature, which also CO 2 adsorption temperature, K; and m ex is the CO 2 excess adsorption amount per unit mass of coal, m 3 /t, which can be calculated using the following D-R adsorption model 16 , 31 :
where m 0 is the maximum CO 2 adsorption capacity of coal per unit mass tested by adsorption experiment, m 3 /t; ρ f and ρ a are the densities of free and adsorbed CO 2 under the real temperature and pressure conditions, kg/m 3 ; D is the adsorption constant, and k is the constant associated with Henry's Law.
In coal reservoir, CO 2 density is a function of pressure and temperature, which can be expressed as ρ f = f(p, T) , and can be further characterized as follows 16 , 31 , 32 :
where δ = ρ c /ρ f is the CO 2 reduced density; ρ c is the CO 2 critical density, kg/m 3 ; τ = T c /T is the reduced temperature; and ϕ(δ,τ) is the Helmholtz free energy, which can be controlled by temperature and density 16 , 31 , 32 :
where ϕ o (δ, τ) is the Helmholtz free energy of ideal fluid, and ϕ r (δ, τ) is the Helmholtz free energy of the residual fluid.
In deep unworkable seam, the storage potential of dissolved CO 2 per unit mass of coal is a function of coal porosity, water saturation, coal density and CO 2 solubility, which can be characterized as follows 16 , 31 :
where φ is the coal porosity, %; S w is the water saturation, %; \(S_{{{\text{CO}}_{2} }}\) is the CO 2 solubility, and ρ coal is the coal density, kg/m 3 .
According to Boyle-Mariotte law, the free CO 2 storage potential per unit mass of coal in deep unworkable seam can be characterized as follows 16 , 31 :
where S g is the gas saturation, %; P 0 is the standard atmospheric pressure, MPa; T 0 is the temperature under the standard condition, K; and ρ visual is the coal apparent density, kg/m 3 .
Co 2 source and sink matching.
CO 2 source-sink matching is the basis of CCUS cluster deployment and its pipe network design and construction, with the goal of minimizing CO 2 transportation cost and maximizing carbon removal. Its essence is the optimization planning of CCUS cluster system 33 , 34 . Based on CO 2 emission source, storage sink, storage geological process, transport network connecting source and sink and corresponding parameter data, the dynamic optimal matching between CO 2 source and sink can be achieved in terms of target quantity, continuity and economic efficiency (Fig. 2 ).
Schematic diagram of connotation of CO 2 source and sink matching.
The matching of CO 2 source and sink is mainly based on the characteristics of large number, different types and scattered locations of CO 2 emission sources (i.e., thermal power, steel, cement, chemical industry, etc.) and storage sinks (i.e., saltwater layer, CO 2 -ECBM, CO 2 -EOR, MCO 2 -ILU, CO 2 -SDR, etc.). Based on the discussion of constraint conditions and determination of objective function, the influence of regional geographical conditions, traffic, population density, transportation cost and transportation mode on CO 2 transport between emission sources and storage sinks is fully considered in the CCUS system. The optimal matching of CO 2 emission sources, storage sinks and transportation parameters was realized, so as to determine scientific and reasonable CO 2 source and sink matching schemes (Fig. 2 ).
Based on the theory of network analysis in operations research, theoretical models of CO 2 source-sink matching within CCUS technology can be constructed in Huainan coalfield by using the minimum support tree method. The construction of theoretical models should meet the following basic assumptions: (1) Source and sink with the lowest cost should be firstly matched; (2) Allow the matching of one source with multi sinks or one sink with multi sources; (3) Sequestration sink must meet the requirement of CCUS planning period.
In this study, the lowest total cost of matching of CO 2 source-sink in CCS technology is taken as the objective function, namely:
where i refers to the i th CO 2 source; j means the j th CO 2 sink; m indicates the number of CO 2 sources and the value is 10, and n indicates the number of CO 2 sinks with the value of 15.
CO 2 capture cost (i.e., C C )
Based on the analysis of the industrial sources report published by the National Energy Technology Laboratory of the United States, the average capture cost of CO 2 source in coal-fired power plants is $ 64.35 /t 30 , 35 . Therefore, the capture cost of CO 2 source in Huainan coalfield can be characterized as follows:
where \(\omega_{ij}\) represents the CO 2 capture cost in the i coal-fired power plant, $/t; and X ij represents CO 2 transport amount from the i coal-fired power plant to the j sequestration sink, t.
CO 2 transportation cost (i.e., C T )
CO 2 transport is most common by pipeline, ship and tanker, and pipeline transportation is suitable for directional transportation with large capacity, long distance and stable load, which mainly includes construction cost and operation and maintenance cost. The operation and maintenance cost accounts for about 1.5% of the construction cost 35 , which can be calculated according to formula 10 and 11 , respectively.
where L is the distance of pipeline transportation, km.
where N represents the transportation cycle of the pipeline, year.
Therefore, CO 2 transport cost can be characterized as follows:
CO 2 sequestration cost (i.e., C S )
The cost of CO 2 geological storage is closely related to the amount of CO 2 storage and the type of storage site, and the average storage cost coefficient is $ 5.59 /t 30 , 35 . Therefore, the cost of CO 2 geological storage in coal reservoir can be characterized as follows:
where \(\varepsilon_{ij}\) is the sequestration cost factor of transporting CO 2 from coal-fired power plant i to sequestration sink j , $/t.
In summary, by substituting formulas ( 9 ), ( 12 ) and ( 13 ) into formula ( 8 ), the minimum objective function of total cost of CO 2 source-sink matching in CCS technology can be obtained:
Based on the basic assumptions of theoretical model, in the planning process of matching pipe network of CO 2 source-sink with CCS technology, the constraint conditions of the lowest total cost objective function are as follows:
The total amount of CO 2 captured from all CO 2 emission sources is equal to the total amount of pipeline transport, that is:
where a i is the CO 2 capture amount of the i th coal-fired power plant.
The CO 2 content transported by the pipeline to the storage site shall not exceed the storage capacity of the storage sink, that is:
where b j is the storage capacity of the j th storage sink.
The amount of CO 2 captured in all coal-fired power plants must not exceed the total capacity of all potential sequestration sinks, that is:
Non-negative constraint: the pipeline of CO 2 transport content is non-negative, that is:
The core idea of the mileage saving algorithm is to merge two transportation loops into one loop to reduce the transportation distance in the merging process, and keep cycling until the limit condition is reached, thus reducing the transportation cost. Specifically, three points, A, B and C, transport goods from A to B and C, where the distance from A to B is L AB (unit: km), the distance from A to C is L AC (unit: km), and the distance from B to C is L BC (unit: km), if the transportation from A to B and A to C is separately completed, the transportation distance is 2 × (L AB + L AC ) with including the round trip process (Fig. 3 a). If from A to B, then from B to C, and finally from C back to A, then the transport distance is L AB + L AC + L BC (Fig. 3 a), then the distance saved is 2 × (L AB + L AC ) − (L AB + L AC + L BC ) = L AB + L AC − L BC > 0.
Optimization of CCUS source-sink matching pipe network. ( a ) Traditional mileage saving methods; ( b ) Improvement of the mileage saving method.
In CO 2 source-sink matching, each sink is taken as the distribution center and distributed with the connected source points. The basic principle is similar to the mileage saving method, except that there is only a transportation network from the source to the sink, and there is no return pipeline. Based on this, the idea of mileage saving method is introduced in this study, and it is improved to meet the needs of CO 2 source-sink matching and transportation network optimization. As shown in Fig. 3 b, the CO 2 emitted from points B and C is transported to the storage sink A for storage. The most direct way is from B to A, and then from C to A, with a transport distance of L AB + L AC (Fig. 3 b). If it is transported from B to C and then from C to A or from C to B and then from B to A (Fig. 3 b), the transport distance is L AC + L BC or L AB + L BC . L AB and L AC need to be compared to choose a route with a smaller distance for connection. If L BC < L AB /L AC , then L AB (L AC ) − L BC is the savings; if L BC > L AB /L AC , then L AB /L AC − L BC is negative, which means no savings (Fig. 3 b).
Characteristics of co 2 sources.
In Huainan coalfield, CO 2 emission sources are 10 coal-fired power plants within the coalfield, of which 9 have been put into operation, 1 has finished commissioning and plans to put into operation. According to the “Greenhouse Gas Emission Accounting Methods and Reporting Guidelines for Chinese Power Generation Enterprises (Trial)” and related methods, the carbon emission intensity of the coal-fired power plants was calculated, and on this basis, the average annual CO 2 emissions of each coal-fired power plant were estimated. The installed capacity of China's coal-fired power plants is mainly 300 WM, 600 WM and 1000 WM, and the CO 2 emission intensity of which is 0.845 t/MW/h, 0.807 t/MW/h and 0.768 t/MW/h, respectively, and in this study, the mean value is taken as the basis for estimation 36 , 37 . Based on the average annual power generation statistics of each power plant, the average annual CO 2 emissions of each coal-fired power plant can be analyzed (Table 1 ).
As can be seen from Table 1 , the average annual CO 2 emissions of coal-fired power plants vary greatly with ranging from 0.36 million tons to 17.12 million tons. Among them, the average annual CO 2 emissions of D7 power plant reach 17.12 million tons, accounting for about 30% of the total annual CO 2 emissions. The total annual CO 2 emissions of all coal-fired power plants are 58.76 million tons, which includes 5.28 million tons of emissions from the proposed D6 power plant (Table 1 ).
The core parameters of potential assessment of CO 2 geological storage are mainly derived from engineering data, test data, experimental data and scientific research papers (Table 2 ) 16 , 31 , 38 , 39 . In this study, for deep unworkable seam in Huainan coalfield, the proved reserves with burial depth ≤ 1500 m are obtained from coal exploration, and the proved reserves with burial depth > 1500 m are predicted reserves by the resource management department. The geothermal gradient is 3.10 °C/100 m. When the depth of coal seam is less than 1000 m, the pressure gradient is 0.95 MPa/100 m. When the depth of coal seam is more than 1000 m, the pressure gradient is 1.08 MPa/100 m 16 , 31 . The core parameters of CO 2 geological storage potential assessment can be detailed in Table 2 16 , 31 , 38 , 39 .
The CO 2 geological storage potential of deep unworkable seam in Huainan coalfield is huge, and the total amount is 762 million tons. The adsorbed, free and dissolved CO 2 can be stored 685 million tons, 53 million tons and 24 million tons, respectively. The CO 2 geological storage with adsorbed state in deep unworkable seam is the most dominant, accounting for 89.895% of the total storage. When the buried depth of coal seam is ≤ 1500 m and > 1500 m, the total CO 2 geological storage is 253 million tons and 510 million tons, with accounting for 33.17% and 66.83% of the total storage, respectively. Regardless of the state in which CO 2 is stored, the total amount of CO 2 stored when the buried depth is greater than 1500 m is greater than that under the same state when the buried depth is less than 1500 m (Table 3 ).
When the buried depth of coal seam is > 1500 m and ≤ 1500 m, the proved coal reserves are 4.03 billion tons and 1.99 billion tons, respectively, with a ratio of 2.025. For the total amount of CO 2 geologic storage and its adsorption, free and dissolved state, the ratio of coal seam buried depth > 1500 m and ≤ 1500 m is 2.016, 1.996, 2.312 and 2.000, respectively. The main reason why the ratio of total CO 2 geological storage and total adsorption state is lower than 2.025 is that although the CO 2 geological storage potential of deep unworkable seam is positively correlated with the proved coal reserves, the maximum CO 2 adsorption capacity at the depth ≤ 1500 m is much higher than that at the depth > 1500 m. With the increase of burial depth, the reservoir pressure gradually increases, and the CO 2 storage potential in free state in pore structure gradually increases, which will make the free CO 2 ratio far greater than 2.025.
Plane distribution characteristics of co 2 sinks.
The total CO 2 storage potential of deep unworkable seam in Huainan coalfield is 762 million tons (Table 3 ). For the average annual CO 2 emissions of the 10 coal-fired power plants, it can be stored for 12.97 years. The deep unworkable seam is the most potential body for CO 2 storage in Huainan coalfield. The unrecoverable coal seam with buried depth ≤ 1500 m can meet the CO 2 geological storage requirements of coal-fired power plants for 4.31 years. Considering the technical challenges and implementation costs of CO 2 storage in coal seam with different burial depths, the unworkable coal seam with burial depths ≤ 1500 m should be the main target reservoir for the implementation of CO 2 -ECBM technology in the next five years.
With fault structure as the boundary, the deep unworkable seam can be divided into 15 CO 2 storage blocks, and the comparative analysis of the plane distribution of CO 2 storage sinks can be carried out according to the plane area size (Fig. 4 ). The main blocks of CO 2 geological storage are B9, B12, B8 and B5, and their sealable stocks are 124 million tons, 114 million tons, 97 million tons and 85 million tons, respectively, among which the largest two blocks, B9 and B12, can store the CO 2 emissions of 10 coal-fired power plants for nearly four years. The four blocks with larger area are also the main blocks of the CO 2 source-sink matching.
Plane distribution of CO 2 storage sink in unrecoverable coal seams of Huainan coalfield.
According to the preliminary potential assessment analysis, for the average annual CO 2 emissions of the 10 coal-fired power plants in Huainan coalfield, the deep unworkable seam can be stored for 12.97 years. Therefore, in this study, the matching study of CO 2 source-sink was conducted based on the cumulative CO 2 emissions of 10 coal-fired power plants in Huainan coalfield in 10 years for deep unworkable seam (Fig. 5 ).
CCS source and sink matching of cumulative CO 2 emissions from 10 coal-fired power plants in Huainan coalfield during the 10-year cycle.
Based on the matching results of CO 2 source and sink during the 10-year cycle in Huainan coalfield, it can be seen that the coal-fired power plant of D1 can be mainly stored in blocks of B2, B3, B4 and B7, with the stored stocks of 20.2 million tons, 19.7 million tons, 30.9 million tons and 10.8 million tons, respectively. Coal-power plant of D2 is mainly stored in block of B5, and the stored stock is 3.6 million tons. The coal-power plant of D3 is mainly stored in blocks of B7 and B10, with a stored stock of 25.8 million tons and 51 million tons, respectively. Coal-fired power plant of D4 is mainly stored in blocks of B8 and B9, with a storage capacity of 10.9 million tons and 12.3 million tons, respectively. Coal-fired power plant of D5 is mainly stored in block of B9, with a stored stock of 58.9 million tons. Coal-fired power plant of D6 is mainly stored in block of B9, and the stored stock is 52.8 million tons. Coal-fired power plant of D7 is mainly stored in blocks of B8, B12 and B14, with stored stocks of 61.1 million tons, 58.3 million tons and 51.8 million tons, respectively. Coal-fired power plant of D8 is mainly stored in block B8, with a stored stock of 15.5 million tons. Coal-fired power plant of D9 is mainly stored in block of B13, and the stored stock is 48.2 million tons. The coal-fired power plant of D10 is mainly stored in block of B12, with a stored stock of 56.0 million tons (Fig. 5 ). During the 10-year cycle, the CO 2 in deep unworkable seam can be stored up to 587.6 million tons, and the cumulative planned pipeline is 251.61 km, which will require a cumulative capital of $ 4.26 × 10 10 .
Analysis of matching pipe network of co 2 source-sink.
Based on the analysis of matching pipe network of CO 2 source-sink in deep unworkable seam, it can be seen that the transportation routes of pipelines of 9, 4, 16, 5 and 8 are relatively long, which accounts for 53.65% of the total transportation route length (Fig. 6 ). Because the transportation cost is proportional to the route, it is important to optimize the line length of pipelines of 9, 4, 16, 5 and 8 to reduce the total cost.
Analysis of the number, length and proportion of CO 2 source-sink matching pipe network in deep unrecoverable coal seams.
Based on the analysis of CO 2 storage and transport costs and their proportion in deep unworkable seam, it can be seen that the transport costs of blocks of 8, 7, 12 and 13 are the highest, which accounts for 36.96%, 14.01%, 11.60% and 11.86% of the total CO 2 storage and transport costs, respectively. The transportation cost of four CO 2 storage sinks accounted for 74.43% of the total cost. Therefore, blocks of 8, 7, 12 and 13 of deep unworkable seam will be the focus of optimization of matching pipe network of CO 2 source-sink. Blocks of 1, 6, 11 and 15 do not need to bear CO 2 geological storage for the time being, which can be used as alternative blocks for CO 2 storage (Figs. 5 and 7 ).
Transportation cost and proportion of CO 2 storage sinks matched by CO 2 source and sink in deep unrecoverable coal seams.
Based on the improved mileage saving method, the optimization results of matching pipe network of CO 2 source-sink in deep unworkable seam can be obtained (Fig. 8 ).The unchanged pipe network paths are D1–B4, D1–B7, D3–B10, D4–B8, D4–B9 and D7–B13 (Fig. 8 ), and the routes among other source-sink take the minimum total transportation cost as the objective function, and the pipe network optimization is carried out according to the constraints of the emission source and the storage capacity (Fig. 8 ).
Optimization results of CO 2 source-sink matching pipe network in Huainan coalfield.
Based on the optimization results of matching pipe network of CO 2 source-sink in Huainan coalfield, it can be seen that the accumulated mileage saved is 98.75 km, and the accumulated cost saved is $ 25.669 billion, which accounts for 39.25% and 60.26% of the total mileage and cost of pipeline, respectively (Table 4 ). Among them, the mileage and cost savings of 13 and 14 blocks in deep unworkable seam are more obvious, which accounts for 10.43% and 10.10% of the total mileage and 16.20% and 16.01% of the total cost, respectively (Table 4 ).
Pipeline network planning on a time scale.
By analyzing the optimization results of matching pipe network of CO 2 source-sink in Huainan coalfield and the amount of CO 2 transported by each pipe network line, it can be seen that the entire pipe network is centrally distributed in the east and west regions, and it is obvious that the transport amount of the eastern pipe network is significantly greater than that of the western one (Fig. 9 ). The thicker the lines of the route, the greater the traffic amount (Fig. 9 ). The planning and design of matching pipe network of CO 2 source-sink should refer to the thickness of the transportation line, that is, the amount of CO 2 transported (Figs. 10 , 11 , 12 ). The planning and design of matching pipe network of CO 2 source-sink in Huainan coalfield is proposed in accordance with three steps:
CO 2 transport statistics of CCS source-sink matching pipe networks in Huainan coalfield.
Three-step planning and design of CO 2 source-sink matching pipe network in Huainan coalfield (First step).
First step: It is recommended to preferentially plan the pipeline route of D9–D8–D7–B12–D6–D4–B8 in the eastern region, and the D3–B10 and D1–B4 in the western region. This planned pipeline can effectively connect the coal-fired power plants of D9, D8, D7, D6 and D4, and unworkable blocks of B12, B8, B10 and B4 of Huainan coalfield (Fig. 10 ). At this step, the total amount of CO 2 that can be transported by the pipeline network is 6.65 billion tons, and the total amount of CO 2 that can be stored is 2.27 billion tons, which accounts for 56.99% and 38.74% of the total transportation and storage stock of CO 2 , respectively.
Second step: It is recommended to further plan the pipeline lines of D10–D9, D7–B13, D7–B14, D4–B9, D5–B9, B10–B7, and B4–B3–B2, which can further effectively connect the deep unworkable seam in the east, middle and west areas (Fig. 11 ). After the pipeline network planning at this step, the total amount of CO 2 transported can be 10.345 billion tons, and the total amount of CO 2 stored can be 5.84 billion tons, which accounts for 88.66% and 99.39% of the total CO 2 transport and storage, respectively.
Three-step planning and design of CO 2 source-sink matching pipe network in Huainan coalfield (Second step).
Third step: Complete the design of all remaining pipelines to connect the deep unworkable seam in the east and west of the study area. It is suggested to add the design of B3 and B4 pipelines, so as to run through all CO 2 emission sources and CO 2 storage sinks in Huainan coalfield, so as to realize all CO 2 transportation and geological storage (Fig. 12 ).
Three-step planning and design of CO 2 source-sink matching pipe network in Huainan coalfield (Third step).
In this study, the location of each point in deep unworkable seam is determined by taking the center location of each region (Fig. 1 ), but in the actual well location layout, the regional center location is often not the only consideration. Therefore, the analysis of the type of CCS pipeline within each region and the planning of CCS pipeline network between each region are very important (Fig. 13 ).
Schematic diagram of four types of CO 2 pipelines connecting carbon sources and carbon sinks.
According to the location and use of CO 2 pipelines in the pipe network, CO 2 pipelines can be defined as the following four types (Fig. 13 ): (1) Gas collection branch, that is, the pipeline that communicates CO 2 source and transfer point, and the transport phase is determined according to its economy; (2) Distribution branch, that is, the pipeline from the end of the communication pipeline to the carbon sequestration point; (3) Intra-regional trunk lines, that is, trunk pipelines from the transfer point to the carbon sequestration point in the region; (4) Interregional trunk lines, that is, shared pipelines connecting regions. As far as Huainan coalfield is concerned, in terms of spatial scale, priority should be given to planning intra-regional pipe networks in various regions within unworkable seam bounded by faults, that is, the pipe networks in various regions within B1–B15 (Fig. 13 ).
Whether it is a small area of Huainan coalfield or the whole large area of China, the CCS pipe network layout should follow the following ideas. First of all, small-scale carbon sources in the region should be transferred to main pipelines through gas collection branch lines, and commercial CO 2 pipeline demonstration projects can be built. Secondly, the collection and distribution pipelines of regional carbon sources can be planned within the basin to form a backbone sharing pipeline, and a variety of CCS carbon sequestration applications can be simultaneously carried out to build an interregional transport network demonstration. Then, for areas that do not have the conditions for storage, inter-regional trunk pipelines should be built to gradually form a cross-regional carbon network on land to fully meet the matching transport of source and sink. Offshore CO 2 storage resources should be developed, suitable coastal injection points should be selected, marine transport pipelines and ship transport should be simultaneously carried out, and integrated business models of transport and storage based on land and sea should be built (Fig. 13 ).
In this study, the deep unworkable seam in Huainan coalfield was taken as the research object. Firstly, the evaluation method of CO 2 storage potential in deep unworkable seam was discussed. Secondly, the CO 2 geological storage potential was analyzed. Then, the matching research of CO 2 source and sink for CO 2 geological storage was carried out, and the pipe network design was optimized. Finally, suggestions on the design of network planning of CCS source and sink are put forward in Huainan coalfield. The main conclusions are as follows:
The total annual CO 2 emissions of each coal-fired power plant are 58.76 million tons, and the average annual CO 2 emissions of each coal-fired power plant vary greatly with ranging from 0.356 million tons to 17.12 million tons. The CO 2 geological storage potential of deep unworkable seam is huge, and the total amount is 762 million tons. It can store 685 million tons, 53 million tons and 24 million tons of CO 2 in adsorbed, free and dissolved states, respectively. For the average annual CO 2 emissions of coal-fired power plants, deep unworkable seam can be stored for 12.97 years. During the 10-year period, the deep unworkable coal seam can store 587.6 million tons, and the cumulative planning pipeline is 251.61 km, requiring a cumulative capital of $ 4.26 × 10 10 .
The main blocks of CO 2 geological storage are B9, B12, B8 and B5, with stored stocks of 124 million tons, 114 million tons, 97 million tons and 85 million tons, respectively. The matching of CO 2 source and sink saved 98.75 km, and saved $ 25.67 billion, accounting for 39.25% and 60.26% of the total mileage and cost, respectively. The mileage and cost savings in 13 and 14 blocks are more obvious, which accounts for 10.43%, 10.10% and 16.20% and 16.01% of the total mileage and cost, respectively.
Based on the three-step approach, the whole line of CO 2 emission sources and CO 2 storage sinks in Huainan coalfield can be completed by stages and regions, and all CO 2 transportation and storage can be realized. CO 2 pipelines include gas collection branch lines, gas distribution branch lines, intra-regional trunk lines, and interregional trunk lines. Based on the reasonable layout of various types of CO 2 pipelines, a variety of CCS carbon sequestration applications can be simultaneously carried out, the intra-regional and inter-regional network demonstration for CO 2 transport can be built, and integrated business models of CO 2 transport and storage can be built simultaneously on land and sea.
All data generated or analysed during this study are included in this published article (Please refer to the manuscript that has been uploaded).
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We would like to express our gratitude to the anonymous reviewers for offering their constructive suggestions and comments which improved this manuscript in many aspects. This work was financially supported by the Natural Science Research Project of Anhui Educational Committee (2023AH040154), the Anhui Provincial Natural Science Foundation (2308085Y30), the Anhui Provincial Key Research and Development Project (2023z04020001), the National Natural Science Foundation of China (No. 42102217; 42277483), and the University Synergy Innovation Program of Anhui Province (No. GXXT-2021-018).
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School of Earth and Environment, Anhui University of Science and Technology, Huainan, 232001, Anhui, China
Huihuang Fang, Yujie Wang, Shua Yu, Huihu Liu, Jinran Guo & Zhangfei Wang
Institute of Energy, Hefei Comprehensive National Science Center, Hefei, 230000, China
Department of Geological Sciences, University of Saskatchewan, Saskatoon, SK, S7N 5E2, Canada
Huihuang Fang
Carbon Neutrality Institute, China University of Mining and Technology, Xuzhou, 221008, China
Shuxun Sang
School of Resources and Geosciences, China University of Mining and Technology, Xuzhou, 221116, China
Jiangsu Key Laboratory of Coal-based Greenhouse Gas Control and Utilization, China University of Mining and Technology, Xuzhou, 221008, China
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H.F. and S.S.: The conception and design of the study, revising it critically for important intellectual content, final approval of the version to be submitted. H.F. and Y.W.: Drafting the article. J.G. and H.L.: Drawing of all figures. H.F. and Z.W.: Collection and analysis of the field data. S.Y.: Derivation of mathematical models.
Correspondence to Huihuang Fang .
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Fang, H., Wang, Y., Sang, S. et al. Potential assessment of CO 2 source/sink and its matching research during CCS process of deep unworkable seam. Sci Rep 14 , 17206 (2024). https://doi.org/10.1038/s41598-024-67968-w
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11 min read
Climate change is a wicked problem architects can and should play a significant role in addressing. Buildings are responsible for nearly 40% of carbon emissions globally. Opportunities abound through design, education, development and support of policy, research, and more.
With the need to draw down carbon emissions sooner rather than later and the current and forthcoming policies worldwide, the ethical and business case for design firms focusing on carbon is easy to make.
“We have to draw the carbon back down as fast as we can, and buildings have a huge role to play in that effort,” writes Chris Magwood and Bruce King in their book Build Beyond Zero.
Furthermore, as the late Lance Hosey eloquently expressed in his book The Shape of Green , design—or aesthetics—and sustainability do not have to be mutually exclusive. This idea is celebrated by the AIA’s Committee on the Environment (COTE) Top Ten awards recognizing beautiful buildings that have implemented many of the measures defined in the AIA Framework for Design Excellence.
We are not all starting from the same place in the journey to mitigate climate change. If any of this is new to you, the AIA and Carbon Leadership Forum (CLF) have developed an Embodied Carbon Toolkit for Architects which is a great place to start. Another great “getting started” resource is the Lake|Flato white paper on embodied carbon, discussed later in this article.
As we are all in this together, we believe that sharing methods and practices can be a good way to solve the climate change problem. In this article, I am going to tell you a bit about Lake|Flato’s story.
“Design can save the world…” wrote Corey Squire, architect, author, and sustainability expert, next to his name when signing my copy of his new book People Planet Design . Understanding the opportunities, policies, and tools goes a long way in making meaningful impacts on carbon pollution reductions through design.
I recently worked with a small team of about six people to update the Architects Are Environmentally Responsible section of the AIA Public Policies and Position Statements . There are three sections related to carbon: Operational, Reuse, and Embodied. Architects, especially AIA members, should read this and understand the obligation to “consider with their clients the environmental effects of their project decisions” per the AIA Code of Ethics and Professional Conduct .
More pointedly, governments are implementing policies that can leave design firms empty-handed when it comes to being awarded commissions if they are not prepared to design and deliver low-carbon projects, specifications, and required reports and documentation. Current examples abound, from the Embodied Carbon Guidelines in Vancouver, Canada, to the LCA requirements in Minnesota’s B3 Guidelines, to policies in unexpected places, such as the deconstruction ordinance in San Antonio, Texas.
As design firms become more invested in operation and embodied carbon, a good next step is making a firm-wide tracking commitment. The AIA 2030 Commitment supports a firm culture of high-performance design because, like municipal policy, the firm has obligated itself (although, not legally) to portfolio-wide tracking of operational carbon with optional embodied carbon and light power density (LPD) metrics.
“There is no better resource to track your impact on climate change through measurement of the project performance than the AIA 2030 Commitment and the corresponding Design Data Exchange (DDx). Now is the time to make the commitment, measure to improve, and help solve climate change.” – Ashley Mulhall, AIA, LEED AP, BD+C, Orcutt|Winslow Architects
Every year, the AIA publishes a report, 2030 By the Numbers , to show how the collective group of reporting firms is tracking towards the net zero carbon goal by 2030. Lake|Flato has been a 2030 Commitment signatory since the program’s inception 14 years ago.
Architecture firm Mahlum recently presented at the 2024 AIA Conference on Architecture in Washington D.C. on a Tableau dashboard they created to better visualize their downloaded AIA 2030 Design Data Exchange (DDx) data. They have made this dashboard freely available via this link: Tableau 2030 Dashboard by Mahlum Architects .
A key component of becoming a 2030 commitment signatory is creating a firmwide Sustainability Action Plan (SAP). An SAP creates actionable goals and strategies that help firms progress even when projects, business, and life compete for valuable time and resources.
If your firm does not have an SAP and needs inspiration, the AIA maintains a Dropbox repository of firm SAPs you can download, compare, and be inspired by. We would love to inspire you— so if you are interested, Lake|Flato recently updated its SAP, which is easy to find in the AIA Dropbox folder. Our document is divided into Practice, People, and Planet. The base and reach goals for operational and embodied carbon are shown below. At the very least, we strive to consider each base goal on every project.
Well-defined strategies and tested tools are critical in verifying assumptions and validating results. For example, the Path to Zero graphic below is often presented internally, to clients, and at conferences to reinforce the importance of timing and decision-making within the design process. We also highlight the tools our firm uses during new hire orientations, studio huddles, design charettes, with clients, and at conferences.
Another tool, Autodesk Forma is a powerful analysis tool designers can use to understand microclimate conditions, daylight, wind, and noise for one or more design solutions. A newer feature is the ability to develop a carbon budget or benchmark/baseline – more on the backstory for this later in this article. You can check out my YouTube playlist, sponsored by Autodesk, on Forma: Autodesk Forma Series by Daniel John Stine .
An embodied carbon benchmark/baseline has traditionally been much more challenging to understand than operational carbon, given the years of development and post-occupancy evaluations not to mention robust codes such as ASHRAE 90.1, which list EUIs by building type and climate zone. Great work is being done on the embodied carbon front by the Carbon Leadership Forum, Rocky Mountain Institute, and others.
Due to the limited benchmark data for embodied carbon and the fact that the number and size of columns and beams are not 1:1 between a steel/concrete structure and mass timber, on one project Lake|Flato paid the structural engineer to do a basic structural design for the baseline design for a more accurate comparison. You can also see an example of Lake|Flato’s use of Forma in this Autodesk customer story and video: Architecture firm Lake|Flato’s adaptive-reuse project embodies sustainability
The image below shows the embodied carbon results of three options in Forma. Using AI, simple massing, and a handful of inputs about the project, we can arrive at some helpful early metrics to use as a guidepost (or budget) throughout the project. Fun fact: For the concrete structure option, Forma uses carbon data that is accurate to the zip code level in the US.
A popular Life Cycle Analysis (LCA) tool for architects is TallyLCA. This is an add-in for Revit, which allows Tally material definitions to be assigned to objects and materials within Revit. In addition to Tally, Lake|Flato also uses OneClick LCA .
The image below features an LCA I performed on a boutique hotel in Austin, Texas – Hotel Magdalena . The building has a mass timber structure, which is primarily a Dowel Laminated Timber (DLT) system. Notably, the DLT system does not have glue in it like CLT so the global warming potential was even lower! The result from a Tally LCA is a spreadsheet (shown in the image below) that itemizes and tallies the global warming potential as well as biogenic carbon, eutrophication, and acidification.
Autodesk also offers two robust tools for understanding the predictive energy use intensity (pEUI) of a project: Insight and Systems Analysis. The first primarily works in the cloud, and the latter works locally using OpenStudio (NREL) and EnergyPlus (US DOE). In addition to being able to develop a highly accurate envelope, the image below shows the internal loads being specified at the room level, including set points, LPD, schedules, and more. Notice the OpenStudio/EnergyPlus results are even seen within Revit.
A new tool Autodesk has been working on, and one I have been attending customer-facing sprint reviews for, is the cloud-based Total Carbon. Using the same Revit model preparation for operation carbon/energy the model can be studied for embodied carbon impacts. Not to reinvent the wheel and for more transparency and credibility, Autodesk uses the open source EPD data by EC3 from Building Transparency.
Once configured in the cloud, a project dashboard with custom factors can be created as shown in the image below.
Another example of Autodesk Total Carbon in action can be seen in the image below. This is a healthcare project in Australia by Warren and Mahoney . Sustainability Lead and Low Carbon Design and Research Specialist, Emily Newmarch gave a compelling presentation at Autodesk University 2023 titled The Carbon Legacy of Building Portfolios: Time Bombs for Future Generations . In this session, she shares her firm’s staunch commitment to historic preservation, circular economy, and minimizing embodied carbon throughout the lifecycle of a building.
The embodied carbon engine added to Forma was created by EHDD Architects . This is a wonderful example of practice and software working together to address this wicked problem of solving climate change! EHDD has a free standalone tool called EPIC that uses an AI/ML engine (they also created) under the hood called C.Scale. EHDD used their own tool in the interview and during the design of the national AIA Headquarters project in Washington D.C.
While working on the Autodesk Forma series I created, I had the opportunity to sit down with Jack Rusk, Climate Strategist at EHDD, and talk about their tool and its integration into Forma. You can see that video here: Talking Climate Strategy with Jack Rusk from EHDD .
Whether embedded in a project, a partnership with academia, or an independent effort, research can significantly impact a firm’s understanding of carbon, especially as it relates to its specific project types and location in the world. Engaging in research also enhances staff/firm knowledge, efficiency, and can start to develop a thought leadership position within the industry.
I lead the research program at Lake|Flato called Investigations. It is a self-funded program that allows designers to submit proposals for projects that, if selected, offer dedicated billable time to focus on the topic they are interested in. The deliverable is a whitepaper and an officewide presentation. They also often result in presentations, recent examples include the national AIA conference, AIA/ACSA Intersections, and Environmental Design and Research Association (EDRA) conferences.
You can learn more about the Lake|Flato research program . In recent months, we have also submitted for grants with academic institutions to further some of our research on carbon and circularity and design for deconstruction.
You can learn more about the research on embodied carbon by Kate Sector, Design Performance Manager at Lake|Flato in “ Embodied Carbon: Exploring Global Warming Potential Using Life Cycle Assessments .” The featured case studies include Hotel Magdalena and a project currently under construction at the University of Pennsylvania (UPenn).
Let me conclude by saying architects are crucial in combating climate change. Architects can significantly reduce carbon pollution by integrating innovative design, education, supportive policies, and research. The ethical and business incentives for focusing on carbon reduction are clear, especially with emerging global policies.
Aesthetic and sustainable design can coexist, as evidenced by the AIA COTE Top Ten awards. Resources like the AIA’s Embodied Carbon Toolkit, and Lake|Flato’s white paper provide essential guidance. Policy advancements will continue to demand low-carbon projects, and the AIA 2030 Commitment supports firms in tracking and improving their carbon footprint. Tools like Autodesk Forma and Tally help analyze and reduce carbon impacts.
Research initiatives, such as Lake|Flato’s Investigations program, enhance personal, firm, and industry knowledge and efficiency. By embracing sustainable design, adhering to policies, making commitments, and engaging in research, architects can take charge of reducing carbon emissions, benefiting both the environment and their businesses.
Dan Stine, AIA, IES, CSI, CDT, Well AP. Dan is the Director of Design Technology and leads the internal research program, Investigations, at the top-ranked architecture firm Lake|Flato, in San Antonio, Texas. He is a registered architect (WI), educator, author, blogger, and international speaker.
In addition to teaching graduate architecture students at NDSU, he has written 19 textbooks, including the #1 Revit book in North America, which is used extensively in the academic market. Committed to climate action, Dan was on a six-person team commissioned by the American Institute of Architects (AIA) to write the AIA Climate Action Business Playbook. He also serves on the national AIA Committee on the Environment (COTE) Leadership Group. He chairs a national Illuminating Engineering Society (IES) committee.
Dedicated to furthering the design profession, Dan has given presentations on building performance and design technology in North America, Europe, Singapore, and Australia. He has also presented at AIA conferences (National, TX, MN), AIA-COTE working groups (Philly, New Orleans, San Antonio, LA), universities (Penn State, Pratt, University of MN, UTSA, and more), lightfair, NVIDIA GTC, Autodesk University, and more.
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A research design is a strategy for answering your research question using empirical data. Creating a research design means making decisions about: Your overall research objectives and approach. Whether you'll rely on primary research or secondary research. Your sampling methods or criteria for selecting subjects. Your data collection methods.
The purpose of research design is to plan and structure a research study in a way that enables the researcher to achieve the desired research goals with accuracy, validity, and reliability. Research design is the blueprint or the framework for conducting a study that outlines the methods, procedures, techniques, and tools for data collection ...
Step 2: Choose a type of research design. Step 3: Identify your population and sampling method. Step 4: Choose your data collection methods. Step 5: Plan your data collection procedures. Step 6: Decide on your data analysis strategies. Frequently asked questions. Introduction. Step 1. Step 2.
Research design refers to the overall plan, structure or strategy that guides a research project, from its conception to the final analysis of data. Research designs for quantitative studies include descriptive, correlational, experimental and quasi-experimenta l designs. Research designs for qualitative studies include phenomenological ...
Types of Research Designs Compared | Guide & Examples. Published on June 20, 2019 by Shona McCombes.Revised on June 22, 2023. When you start planning a research project, developing research questions and creating a research design, you will have to make various decisions about the type of research you want to do.. There are many ways to categorize different types of research.
Research design methods refer to the systematic approaches and techniques used to plan, structure, and conduct a research study. The choice of research design method depends on the research questions, objectives, and the nature of the study. Here are some key research design methods commonly used in various fields: 1.
Research methods are specific procedures for collecting and analyzing data. Developing your research methods is an integral part of your research design. When planning your methods, there are two key decisions you will make. First, decide how you will collect data. Your methods depend on what type of data you need to answer your research question:
Research design is a plan to answer your research question. A research method is a strategy used to implement that plan. Research design and methods are different but closely related, because good research design ensures that the data you obtain will help you answer your research question more effectively. Which research method should I choose?
It should be written prior to data collection and analysis, as it provides a clear roadmap for the research project. The research methodology is an important section of any research paper or thesis, as it describes the methods and procedures that will be used to conduct the research. It should include details about the research design, data ...
Design research is the process of gathering, analyzing and interpreting data and insights to inspire, guide and provide context for designs. It's a research discipline that applies both quantitative and qualitative research methods to help make well-informed design decisions. Not to be confused with user experience research - focused on the ...
Research Design and Research Methods 47 research design link your purposes to the broader, more theoretical aspects of procedures for conducting Qualitative, Quantitative, and Mixed Methods ... when you set up your procedures in a survey project or an intervention, you want to be sure that other researchers who use similar procedures will reach
This Sage Research Methods tool is designed for the first time researcher to guide you through your research project. Each concept has a specif meaning in terms of research projects. Skip to Main Content. Library; ... you will also see the term "research design" used in other types of research. Below is a list of possible research designs ...
Generative or exploratory research. Generative research, also known as exploratory research, focuses on a deeper understanding of user needs and desires. It is usually conducted at the beginning of the design project when you need to answer basic questions like, "What problem are we solving for our customers?".
The five main types of research design are: 1. Descriptive - describes a situation or scenario statistically. 2. Experimental - allows for cause-and-effect conclusions. 3. Correlational - shows ...
The research design underpins a study or a project that a researcher pursues (Kamau, 2014). This research design was the most suitable in this study because it highlighted developmental ...
In Design Methods and Practices for Research of Project Management, Beverly Pasian and Rodney Turner have brought together 27 original chapters from many of the leading international thinkers in project management research. The collection looks at each step in the research stages, including research strategy, management, methodology ...
A research design also called a research strategy, is a plan to answer a set of questions (McCombes, 2019). It is a framework that includes the methods and procedures to collect, analyze, and interpret data. In other words, the research design describes how the researcher will investigate the central problem of the research and is, thus part of ...
Here's a complete guide to UX research methods. ® Top 3%. Hire Talent ... Here is a diagram listing recommended options that can be done as a project moves through the design stages. The process will vary, and may only include a few things on the list during each phase. The most frequently used methods are shown in bold.
Definition: Research Project is a planned and systematic investigation into a specific area of interest or problem, with the goal of generating new knowledge, insights, or solutions. It typically involves identifying a research question or hypothesis, designing a study to test it, collecting and analyzing data, and drawing conclusions based on ...
Over the last decade, we have seen design thinking gain popularity across industries. Nielsen Norman Group conducted a long-term research project to understand design thinking in practice. The research project included 3 studies involving more than 1000 participants and took place from 2018 to 2020: Intercepts and interviews with 87 participants.
A research methodology encompasses the way in which you intend to carry out your research. This includes how you plan to tackle things like collection methods, statistical analysis, participant observations, and more. You can think of your research methodology as being a formula. One part will be how you plan on putting your research into ...
Research design and methods. Following the literature review, restate your main objectives. This brings the focus back to your own project. Next, your research design or methodology section will describe your overall approach, and the practical steps you will take to answer your research questions.
IT Project Manager. Hybrid/Lansing, Mich. Range: $75,931 - $137,140 annually Posted July 18, 2024 ... The economist enjoys rewarding work applying statistical and econometric research methods to support the Minnesota Legislature in evaluating tax expenditure policies including, tax credits, tax exemptions, and preferential rates, among other ...
Method. This project had 2 phases. The first was a literature review on eel pass performance and seasonal eel migration patterns. ... develop a research programme to improve design and performance ...
Large language models (LLMs) have shown remarkable performance on many different Natural Language Processing (NLP) tasks. Prompt engineering plays a key role in adding more to the already existing abilities of LLMs to achieve significant performance gains on various NLP tasks. Prompt engineering requires composing natural language instructions called prompts to elicit knowledge from LLMs in a ...
OneFlorida+ Clinical Research Consortium and UF Health IDR. Responsibilities include: 1) Designing and managing data analysis projects using the above databases. 2) Participation in the design and implementation of research and evaluation studies. 3) Developing data queries and processing scripts to prepare raw data for analysis.
This research was an explanatory mixed method suggested by Creswell [] which was conducted in five consecutive stages in Iran between November 2021 and September 2023.The purpose of this mixed-method study was to identify the main components of EMS preparedness in MCIs in several systematic stages and then design a conceptual model that can represent the essential elements of EMS readiness in ...
The NIH Data Management & Sharing Policy (DMS Policy) has some significant impacts for NIH proposals submitted for due dates on or after Jan. 25, 2023.. Does this Policy Apply to My Research Project? Determine if the proposed research is subject to the DMS policy.. This DMS Policy applies to all NIH funded research which results in the generation of scientific data.
The research innovations are described as follows: (1) Evaluation method of CO 2 storage potential in deep unworkable seam is discussed; (2) Matching problem of CO 2 source and sink is studied ...
This is a healthcare project in Australia by Warren and Mahoney. Sustainability Lead and Low Carbon Design and Research Specialist, Emily Newmarch gave a compelling presentation at Autodesk University 2023 titled The Carbon Legacy of Building Portfolios: Time Bombs for Future Generations. In this session, she shares her firm's staunch ...