Source apportionment of PM2.5 episodes in the Taichung metropolitan area, Taiwan

IF 4.5 2区 地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES Atmospheric Research Pub Date : 2024-09-03 DOI:10.1016/j.atmosres.2024.107666
Ming-Tung Chuang, Charles C.-K. Chou, Chuan-Yao Lin, Wei-Che Lin, Ja-Huai Lee, Meng-Hsuan Li, Wei-Nai Chen, Chih-Chung Chang, Chian-Yi Liu, Yi-Chun Chen
{"title":"Source apportionment of PM2.5 episodes in the Taichung metropolitan area, Taiwan","authors":"Ming-Tung Chuang,&nbsp;Charles C.-K. Chou,&nbsp;Chuan-Yao Lin,&nbsp;Wei-Che Lin,&nbsp;Ja-Huai Lee,&nbsp;Meng-Hsuan Li,&nbsp;Wei-Nai Chen,&nbsp;Chih-Chung Chang,&nbsp;Chian-Yi Liu,&nbsp;Yi-Chun Chen","doi":"10.1016/j.atmosres.2024.107666","DOIUrl":null,"url":null,"abstract":"<div><p>To analyze the physicochemical mechanisms affecting the variation in fine suspended particulate matter (PM<sub>2.5</sub>) concentrations in Taichung City, the largest city in central Taiwan (the second largest city in Taiwan), during a high-pollution event from November 3 to 6, 2021, we applied the sulfur tracking method (STM) and integrated source apportionment method (ISAM) of the WRF/CMAQ model to simulate the impacts of various emission sources. The sources of pollution in Taichung City are very similar, which shows that the impacts of point, line, and area sources should not be neglected in addition to the boundary conditions. SO<sub>4</sub><sup>2−</sup> is mainly generated from point emissions and the production of H<sub>2</sub>O<sub>2</sub>, Fe, Mn, and O<sub>3</sub>. NO<sub>3</sub><sup>−</sup> is also mainly generated from point sources in Taichung City, with HNO<sub>3</sub> being the main source at noon and ANO<sub>3</sub> at other times of the day. NH<sub>4</sub><sup>+</sup> is mainly generated from area sources in Taichung City. OM is more complex, mainly originating from line sources in Taichung City and other sources, such as point/area emissions in Taichung City and other emissions from Changhua County. The most important mechanism is low-volatility/semivolatile oxidized combustion of OC at noon, followed by low-volatility/semivolatile POA, which is produced in the morning or evening. EC mainly originates from line sources in Taichung City and Changhua County. In other nearby counties, EC is dominated by local emission sources. In addition, when the concentration of PM<sub>2.5</sub> is high, the Neutralization Ratio (NR) is high and PM<sub>2.5</sub> is relatively neutral or slightly alkaline. On the contrary, when the concentration of PM<sub>2.5</sub> is low, the NR is lower than 1 and the aerosol is acidic. Besides, this study used positive matrix factorization (PMF), which indicates that the PM<sub>2.5</sub> at the UAPRS originated from eight kinds of pollution, namely, windblown dust, oil cracking, iron and steel industry, sea salt, transport, Cl<sup>−</sup> containing exhaust, biomass burning, fossil combustion containing abundant SO<sub>4</sub><sup>2−</sup> and the heavy oil refining and coal combustion industry. The direction of the source of pollution can be traced by a conditional bivariate probability function (CBPF). Overall, fossil fuel combustion, mainly involving sulfate, is the largest source of pollution, with the heavy oil refining and coal combustion industry contributing less, and the remaining factors contribute relatively evenly.</p></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"311 ","pages":"Article 107666"},"PeriodicalIF":4.5000,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Atmospheric Research","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0169809524004484","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

To analyze the physicochemical mechanisms affecting the variation in fine suspended particulate matter (PM2.5) concentrations in Taichung City, the largest city in central Taiwan (the second largest city in Taiwan), during a high-pollution event from November 3 to 6, 2021, we applied the sulfur tracking method (STM) and integrated source apportionment method (ISAM) of the WRF/CMAQ model to simulate the impacts of various emission sources. The sources of pollution in Taichung City are very similar, which shows that the impacts of point, line, and area sources should not be neglected in addition to the boundary conditions. SO42− is mainly generated from point emissions and the production of H2O2, Fe, Mn, and O3. NO3 is also mainly generated from point sources in Taichung City, with HNO3 being the main source at noon and ANO3 at other times of the day. NH4+ is mainly generated from area sources in Taichung City. OM is more complex, mainly originating from line sources in Taichung City and other sources, such as point/area emissions in Taichung City and other emissions from Changhua County. The most important mechanism is low-volatility/semivolatile oxidized combustion of OC at noon, followed by low-volatility/semivolatile POA, which is produced in the morning or evening. EC mainly originates from line sources in Taichung City and Changhua County. In other nearby counties, EC is dominated by local emission sources. In addition, when the concentration of PM2.5 is high, the Neutralization Ratio (NR) is high and PM2.5 is relatively neutral or slightly alkaline. On the contrary, when the concentration of PM2.5 is low, the NR is lower than 1 and the aerosol is acidic. Besides, this study used positive matrix factorization (PMF), which indicates that the PM2.5 at the UAPRS originated from eight kinds of pollution, namely, windblown dust, oil cracking, iron and steel industry, sea salt, transport, Cl containing exhaust, biomass burning, fossil combustion containing abundant SO42− and the heavy oil refining and coal combustion industry. The direction of the source of pollution can be traced by a conditional bivariate probability function (CBPF). Overall, fossil fuel combustion, mainly involving sulfate, is the largest source of pollution, with the heavy oil refining and coal combustion industry contributing less, and the remaining factors contribute relatively evenly.

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
台湾台中都会区 PM2.5 事件的来源分配
为分析2021年11月3日至6日台湾中部第一大城市(台湾第二大城市)台中市高污染事件期间细悬浮微粒(PM2.5)浓度变化的物理化学影响机制,我们应用WRF/CMAQ模型的硫跟踪法(STM)和综合源分摊法(ISAM)模拟了各种排放源的影响。台中市的污染源非常相似,这说明除了边界条件外,点源、线源和面源的影响也不容忽视。SO42- 主要产生于点状排放以及 H2O2、Fe、Mn 和 O3 的产生。台中市的 NO3- 也主要来自点源,其中 HNO3 是中午的主要来源,而 ANO3 则是一天中其他时间的主要来源。台中市的 NH4+ 主要来自区域源。OM 则较为复杂,主要来源于台中市的线源和其他来源,如台中市的点/区域排放和彰化县的其他排放。最重要的机理是中午低挥发性/半挥发性的 OC 氧化燃烧,其次是早晨或傍晚产生的低挥发性/半挥发性 POA。氨基甲酸乙酯主要來自台中市和彰化縣的管線污染源。在其他鄰近縣市,EC 主要來自當地的排放源。此外,当 PM2.5 浓度较高时,中和比(NR)较高,PM2.5 呈相对中性或微碱性。相反,当 PM2.5 浓度较低时,中和比(NR)低于 1,气溶胶呈酸性。此外,本研究采用正矩阵因式分解法(PMF),结果表明,UAPRS 的 PM2.5 来源于八种污染,即风吹扬尘、石油裂解、钢铁工业、海盐、运输、含 Cl- 废气、生物质燃烧、含大量 SO42- 的化石燃烧以及重油炼制和燃煤工业。污染源的方向可以通过条件双变量概率函数(CBPF)进行追踪。总体而言,以硫酸盐为主的化石燃料燃烧是最大的污染源,重油炼制和燃煤工业的贡献较小,其余因素的贡献相对均衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Atmospheric Research
Atmospheric Research 地学-气象与大气科学
CiteScore
9.40
自引率
10.90%
发文量
460
审稿时长
47 days
期刊介绍: The journal publishes scientific papers (research papers, review articles, letters and notes) dealing with the part of the atmosphere where meteorological events occur. Attention is given to all processes extending from the earth surface to the tropopause, but special emphasis continues to be devoted to the physics of clouds, mesoscale meteorology and air pollution, i.e. atmospheric aerosols; microphysical processes; cloud dynamics and thermodynamics; numerical simulation, climatology, climate change and weather modification.
期刊最新文献
Editorial Board Improving long-term prediction of terrestrial water storage through integration with CMIP6 decadal prediction Relative Impact of Assimilation of Multi-Source Observations using 3D-Var on Simulation of Extreme Rainfall Events over Karnataka, India Recent impact of reduced arctic sea-ice on the winter North Atlantic jet stream and its quantitative contributions compared to pre-industrial level Investigating secondary ice production in a deep convective cloud with a 3D bin microphysics model: Part I - Sensitivity study of microphysical processes representations
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1