{"title":"空间模拟:一种估算工业排放对大气二氧化碳影响的方法","authors":"Muhammad Salaha Uddin, Neil Reid","doi":"10.1007/s12061-023-09532-z","DOIUrl":null,"url":null,"abstract":"<div><p>Sectoral emissions of carbon dioxide and their spatial distribution are explored in carbon monitoring and reporting. However, emissions are not observed and are usually estimated from repurposed data. Due to the uncertainties in the estimated emissions and predicted atmospheric concentrations, scientific doubts are rarely avoidable. Therefore, it is vital to know the effects of emissions on the observable atmospheric phenomenon. Methodologically, this paper presents the spatial modeling approach to estimate and spatially represent the annual industrial emissions’ effects on the observed atmospheric phenomenon of column-averaged carbon dioxide (XCO<sub>2</sub>). This study explores the spatial variation of XCO<sub>2</sub> with the annual industrial emissions at the county level across the contiguous USA (CONUS) by processing the Orbiting Carbon Observatory-2 (OCO-2) satellite-based observed database of XCO<sub>2</sub>. The study finds that in 2017, on average, the level of XCO<sub>2</sub> increased by 0.067 ppm due to the 2634.92 Million Tonnes (MTonnes) of industrial emissions (industrial process and electricity generation) in the CONUS. On average, the direct effect of industrial emissions was 0.026 ppm. Finally, the paper presents the effect map of industrial emissions at the county level of the CONUS. This effect estimation approach ensures industrial emissions’ geographic visualization regarding the observed atmospheric phenomenon rather than unobserved emission amounts. The sectoral emission’s effect analysis with the atmospheric phenomenon of XCO<sub>2</sub> at the subnational level helps to explore the required sectoral emission reduction amounts with the globally referenced atmospheric concentration target.</p></div>","PeriodicalId":46392,"journal":{"name":"Applied Spatial Analysis and Policy","volume":"16 4","pages":"1729 - 1754"},"PeriodicalIF":2.0000,"publicationDate":"2023-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Spatial Modeling: an Approach for Estimating the Effect of Industrial Emissions on the Atmospheric Carbon Dioxide\",\"authors\":\"Muhammad Salaha Uddin, Neil Reid\",\"doi\":\"10.1007/s12061-023-09532-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Sectoral emissions of carbon dioxide and their spatial distribution are explored in carbon monitoring and reporting. However, emissions are not observed and are usually estimated from repurposed data. Due to the uncertainties in the estimated emissions and predicted atmospheric concentrations, scientific doubts are rarely avoidable. Therefore, it is vital to know the effects of emissions on the observable atmospheric phenomenon. Methodologically, this paper presents the spatial modeling approach to estimate and spatially represent the annual industrial emissions’ effects on the observed atmospheric phenomenon of column-averaged carbon dioxide (XCO<sub>2</sub>). This study explores the spatial variation of XCO<sub>2</sub> with the annual industrial emissions at the county level across the contiguous USA (CONUS) by processing the Orbiting Carbon Observatory-2 (OCO-2) satellite-based observed database of XCO<sub>2</sub>. The study finds that in 2017, on average, the level of XCO<sub>2</sub> increased by 0.067 ppm due to the 2634.92 Million Tonnes (MTonnes) of industrial emissions (industrial process and electricity generation) in the CONUS. On average, the direct effect of industrial emissions was 0.026 ppm. Finally, the paper presents the effect map of industrial emissions at the county level of the CONUS. This effect estimation approach ensures industrial emissions’ geographic visualization regarding the observed atmospheric phenomenon rather than unobserved emission amounts. The sectoral emission’s effect analysis with the atmospheric phenomenon of XCO<sub>2</sub> at the subnational level helps to explore the required sectoral emission reduction amounts with the globally referenced atmospheric concentration target.</p></div>\",\"PeriodicalId\":46392,\"journal\":{\"name\":\"Applied Spatial Analysis and Policy\",\"volume\":\"16 4\",\"pages\":\"1729 - 1754\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2023-07-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Spatial Analysis and Policy\",\"FirstCategoryId\":\"90\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s12061-023-09532-z\",\"RegionNum\":4,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENVIRONMENTAL STUDIES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Spatial Analysis and Policy","FirstCategoryId":"90","ListUrlMain":"https://link.springer.com/article/10.1007/s12061-023-09532-z","RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL STUDIES","Score":null,"Total":0}
Spatial Modeling: an Approach for Estimating the Effect of Industrial Emissions on the Atmospheric Carbon Dioxide
Sectoral emissions of carbon dioxide and their spatial distribution are explored in carbon monitoring and reporting. However, emissions are not observed and are usually estimated from repurposed data. Due to the uncertainties in the estimated emissions and predicted atmospheric concentrations, scientific doubts are rarely avoidable. Therefore, it is vital to know the effects of emissions on the observable atmospheric phenomenon. Methodologically, this paper presents the spatial modeling approach to estimate and spatially represent the annual industrial emissions’ effects on the observed atmospheric phenomenon of column-averaged carbon dioxide (XCO2). This study explores the spatial variation of XCO2 with the annual industrial emissions at the county level across the contiguous USA (CONUS) by processing the Orbiting Carbon Observatory-2 (OCO-2) satellite-based observed database of XCO2. The study finds that in 2017, on average, the level of XCO2 increased by 0.067 ppm due to the 2634.92 Million Tonnes (MTonnes) of industrial emissions (industrial process and electricity generation) in the CONUS. On average, the direct effect of industrial emissions was 0.026 ppm. Finally, the paper presents the effect map of industrial emissions at the county level of the CONUS. This effect estimation approach ensures industrial emissions’ geographic visualization regarding the observed atmospheric phenomenon rather than unobserved emission amounts. The sectoral emission’s effect analysis with the atmospheric phenomenon of XCO2 at the subnational level helps to explore the required sectoral emission reduction amounts with the globally referenced atmospheric concentration target.
期刊介绍：
Description
The journal has an applied focus: it actively promotes the importance of geographical research in real world settings
It is policy-relevant: it seeks both a readership and contributions from practitioners as well as academics
The substantive foundation is spatial analysis: the use of quantitative techniques to identify patterns and processes within geographic environments
The combination of these points, which are fully reflected in the naming of the journal, establishes a unique position in the marketplace.
RationaleA geographical perspective has always been crucial to the understanding of the social and physical organisation of the world around us. The techniques of spatial analysis provide a powerful means for the assembly and interpretation of evidence, and thus to address critical questions about issues such as crime and deprivation, immigration and demographic restructuring, retailing activity and employment change, resource management and environmental improvement. Many of these issues are equally important to academic research as they are to policy makers and Applied Spatial Analysis and Policy aims to close the gap between these two perspectives by providing a forum for discussion of applied research in a range of different contexts
Topical and interdisciplinaryIncreasingly government organisations, administrative agencies and private businesses are requiring research to support their ‘evidence-based’ strategies or policies. Geographical location is critical in much of this work which extends across a wide range of disciplines including demography, actuarial sciences, statistics, public sector planning, business planning, economics, epidemiology, sociology, social policy, health research, environmental management.
FocusApplied Spatial Analysis and Policy will draw on applied research from diverse problem domains, such as transport, policing, education, health, environment and leisure, in different international contexts. The journal will therefore provide insights into the variations in phenomena that exist across space, it will provide evidence for comparative policy analysis between domains and between locations, and stimulate ideas about the translation of spatial analysis methods and techniques across varied policy contexts. It is essential to know how to measure, monitor and understand spatial distributions, many of which have implications for those with responsibility to plan and enhance the society and the environment in which we all exist.
Readership and Editorial BoardAs a journal focused on applications of methods of spatial analysis, Applied Spatial Analysis and Policy will be of interest to scholars and students in a wide range of academic fields, to practitioners in government and administrative agencies and to consultants in private sector organisations. The Editorial Board reflects the international and multidisciplinary nature of the journal.
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