Bomi Kim , Hyejung Hu , Youjung Jang , Junhee Park , Minwoo Park , Jinseok Kim , Younha Kim , Seung Jick Yoo , Jung-Hun Woo
{"title":"改进空气质量政策中减排量的计算方法","authors":"Bomi Kim , Hyejung Hu , Youjung Jang , Junhee Park , Minwoo Park , Jinseok Kim , Younha Kim , Seung Jick Yoo , Jung-Hun Woo","doi":"10.1016/j.apr.2024.102271","DOIUrl":null,"url":null,"abstract":"<div><div>This study improves the calculation methods for emission reduction of individual policies and policy sets and validates the enhanced methodologies through scenario analysis experiments. First, to ensure that the policy's rule penetration does not exceed 100%, emission sources with excessive policy applications are classified and their reductions are adjusted accordingly. Second, each policy is applied sequentially and adjusts target emissions to reflect prior policy reductions. This prevents overestimation of the total reduction amount, and the reduction for each policy is calculated based on the adjusted value and then summed to obtain the total reduction for the policy set. We selected air pollutants, NO<sub>x</sub>, SO<sub>x</sub>, PM<sub>2.5</sub>, and VOCs to calculate reductions and analyzed the improvement effects through experimental scenarios in Korea's Seoul Metropolitan Area (SMA). According to the comparison between the Clean Air Policy Support System (CAPSS) inventory and the results of this study for 2019, NO<sub>x</sub> exhibited a difference of 6.8% in the non-improvement scenario, which was reduced to 0.1% after the improvement. The differences in SO<sub>x</sub>, PM<sub>2.5</sub>, and VOC decreased from 5.0% to 2.4%, 14.1%–7.9%, and 55.8%–30.6%, respectively. When comparing the NO<sub>x</sub> emission change rates from 2015 to 2018 with Globemission and CAPSS-KU inventories, the differences in the non-improvement scenario were 8.9%p and 9.6%p, respectively, but decreased to 4.4%p and 5.2%p after the improvement. Thus, existing policy research methodologies overestimate policy effects. This study is expected to contribute to a more accurate analysis of policy effects and provide useful data for establishing air quality policies.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"15 12","pages":"Article 102271"},"PeriodicalIF":3.9000,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1309104224002368/pdfft?md5=c2b037756e28ee850f6777addcbf8c67&pid=1-s2.0-S1309104224002368-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Enhancing the methodology for calculating emission reductions in air quality policies\",\"authors\":\"Bomi Kim , Hyejung Hu , Youjung Jang , Junhee Park , Minwoo Park , Jinseok Kim , Younha Kim , Seung Jick Yoo , Jung-Hun Woo\",\"doi\":\"10.1016/j.apr.2024.102271\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This study improves the calculation methods for emission reduction of individual policies and policy sets and validates the enhanced methodologies through scenario analysis experiments. First, to ensure that the policy's rule penetration does not exceed 100%, emission sources with excessive policy applications are classified and their reductions are adjusted accordingly. Second, each policy is applied sequentially and adjusts target emissions to reflect prior policy reductions. This prevents overestimation of the total reduction amount, and the reduction for each policy is calculated based on the adjusted value and then summed to obtain the total reduction for the policy set. We selected air pollutants, NO<sub>x</sub>, SO<sub>x</sub>, PM<sub>2.5</sub>, and VOCs to calculate reductions and analyzed the improvement effects through experimental scenarios in Korea's Seoul Metropolitan Area (SMA). According to the comparison between the Clean Air Policy Support System (CAPSS) inventory and the results of this study for 2019, NO<sub>x</sub> exhibited a difference of 6.8% in the non-improvement scenario, which was reduced to 0.1% after the improvement. The differences in SO<sub>x</sub>, PM<sub>2.5</sub>, and VOC decreased from 5.0% to 2.4%, 14.1%–7.9%, and 55.8%–30.6%, respectively. When comparing the NO<sub>x</sub> emission change rates from 2015 to 2018 with Globemission and CAPSS-KU inventories, the differences in the non-improvement scenario were 8.9%p and 9.6%p, respectively, but decreased to 4.4%p and 5.2%p after the improvement. Thus, existing policy research methodologies overestimate policy effects. This study is expected to contribute to a more accurate analysis of policy effects and provide useful data for establishing air quality policies.</div></div>\",\"PeriodicalId\":8604,\"journal\":{\"name\":\"Atmospheric Pollution Research\",\"volume\":\"15 12\",\"pages\":\"Article 102271\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2024-08-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S1309104224002368/pdfft?md5=c2b037756e28ee850f6777addcbf8c67&pid=1-s2.0-S1309104224002368-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Atmospheric Pollution Research\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1309104224002368\",\"RegionNum\":3,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Atmospheric Pollution Research","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1309104224002368","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Enhancing the methodology for calculating emission reductions in air quality policies
This study improves the calculation methods for emission reduction of individual policies and policy sets and validates the enhanced methodologies through scenario analysis experiments. First, to ensure that the policy's rule penetration does not exceed 100%, emission sources with excessive policy applications are classified and their reductions are adjusted accordingly. Second, each policy is applied sequentially and adjusts target emissions to reflect prior policy reductions. This prevents overestimation of the total reduction amount, and the reduction for each policy is calculated based on the adjusted value and then summed to obtain the total reduction for the policy set. We selected air pollutants, NOx, SOx, PM2.5, and VOCs to calculate reductions and analyzed the improvement effects through experimental scenarios in Korea's Seoul Metropolitan Area (SMA). According to the comparison between the Clean Air Policy Support System (CAPSS) inventory and the results of this study for 2019, NOx exhibited a difference of 6.8% in the non-improvement scenario, which was reduced to 0.1% after the improvement. The differences in SOx, PM2.5, and VOC decreased from 5.0% to 2.4%, 14.1%–7.9%, and 55.8%–30.6%, respectively. When comparing the NOx emission change rates from 2015 to 2018 with Globemission and CAPSS-KU inventories, the differences in the non-improvement scenario were 8.9%p and 9.6%p, respectively, but decreased to 4.4%p and 5.2%p after the improvement. Thus, existing policy research methodologies overestimate policy effects. This study is expected to contribute to a more accurate analysis of policy effects and provide useful data for establishing air quality policies.
期刊介绍:
Atmospheric Pollution Research (APR) is an international journal designed for the publication of articles on air pollution. Papers should present novel experimental results, theory and modeling of air pollution on local, regional, or global scales. Areas covered are research on inorganic, organic, and persistent organic air pollutants, air quality monitoring, air quality management, atmospheric dispersion and transport, air-surface (soil, water, and vegetation) exchange of pollutants, dry and wet deposition, indoor air quality, exposure assessment, health effects, satellite measurements, natural emissions, atmospheric chemistry, greenhouse gases, and effects on climate change.