A modeling framework to assess fenceline monitoring and self-reported upset emissions of benzene from multiple oil refineries in Texas

IF 3.8 Q2 ENVIRONMENTAL SCIENCES Atmospheric Environment: X Pub Date : 2024-08-01 DOI:10.1016/j.aeaoa.2024.100281
Qi Li , Lauren Padilla , Tammy Thompson , Shuolin Xiao , Elizabeth J. Mohr , Xiaohe Zhou , Nino Kacharava , Yuanfeng Cui , Chenghao Wang
{"title":"A modeling framework to assess fenceline monitoring and self-reported upset emissions of benzene from multiple oil refineries in Texas","authors":"Qi Li ,&nbsp;Lauren Padilla ,&nbsp;Tammy Thompson ,&nbsp;Shuolin Xiao ,&nbsp;Elizabeth J. Mohr ,&nbsp;Xiaohe Zhou ,&nbsp;Nino Kacharava ,&nbsp;Yuanfeng Cui ,&nbsp;Chenghao Wang","doi":"10.1016/j.aeaoa.2024.100281","DOIUrl":null,"url":null,"abstract":"<div><p>Benzene as one type of hazardous air pollutants (HAPs) is produced by industrial production processes and/or emitted during upset events caused by man-made or natural accidents. Although upset emissions of benzene can be a significant contributor to the total emission, it is still challenging to quantify. This study first develops a fast modeling framework using obstacle-resolving computational fluid dynamics modeling to compare the modeled within-facility-scale passive pollutant dispersion with the observed levels based on self-reported emissions for fourteen facilities in Texas, United States. Results of numerical simulations demonstrate that neglecting the obstacle effect can underpredict (overpredict) the near-(far-)field concentrations for a low source. For a source located above obstacles, underprediction occurs at all distances. The diagnostic framework is applied to 107 self-reported upset emission events for fourteen petroleum refineries in Texas from year 2019–2022. Considering different metrics across all events, it can be concluded that the modeled concentrations based on self-reported emissions likely underpredict the observed concentration increments. Depending on the possible source height, the median factor of underprediction ranges from 3 to 95 based on the average-plume metric. The agreement between model and observation is better for events characterized by high emission amounts and rates, which also correspond to high observed concentration increments. Overall, the research highlights the importance of considering obstacles and demonstrates the potential application of the current approach as an efficient diagnostic method for self-reported upset emissions using fenceline observations of HAPs.</p></div>","PeriodicalId":37150,"journal":{"name":"Atmospheric Environment: X","volume":null,"pages":null},"PeriodicalIF":3.8000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2590162124000480/pdfft?md5=a7d167d3de9fbabdda699cc5b021fe0f&pid=1-s2.0-S2590162124000480-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Atmospheric Environment: X","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2590162124000480","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

Benzene as one type of hazardous air pollutants (HAPs) is produced by industrial production processes and/or emitted during upset events caused by man-made or natural accidents. Although upset emissions of benzene can be a significant contributor to the total emission, it is still challenging to quantify. This study first develops a fast modeling framework using obstacle-resolving computational fluid dynamics modeling to compare the modeled within-facility-scale passive pollutant dispersion with the observed levels based on self-reported emissions for fourteen facilities in Texas, United States. Results of numerical simulations demonstrate that neglecting the obstacle effect can underpredict (overpredict) the near-(far-)field concentrations for a low source. For a source located above obstacles, underprediction occurs at all distances. The diagnostic framework is applied to 107 self-reported upset emission events for fourteen petroleum refineries in Texas from year 2019–2022. Considering different metrics across all events, it can be concluded that the modeled concentrations based on self-reported emissions likely underpredict the observed concentration increments. Depending on the possible source height, the median factor of underprediction ranges from 3 to 95 based on the average-plume metric. The agreement between model and observation is better for events characterized by high emission amounts and rates, which also correspond to high observed concentration increments. Overall, the research highlights the importance of considering obstacles and demonstrates the potential application of the current approach as an efficient diagnostic method for self-reported upset emissions using fenceline observations of HAPs.

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
评估得克萨斯州多家炼油厂苯的围栏监测和自报扰动排放的建模框架
苯是有害空气污染物(HAPs)的一种,由工业生产过程产生和/或在人为或自然事故造成的扰动事件中排放。尽管苯的扰动排放在总排放量中占很大比例,但对其进行量化仍然具有挑战性。本研究首先利用障碍物解析计算流体动力学建模技术开发了一个快速建模框架,将建模的设施范围内被动污染物扩散与根据美国得克萨斯州 14 家设施的自我报告排放量观测到的水平进行比较。数值模拟结果表明,忽略障碍物效应会低估(高估)低排放源的近场(远场)浓度。对于位于障碍物上方的污染源,在所有距离上都会出现预测不足的情况。诊断框架适用于德克萨斯州 14 家炼油厂在 2019-2022 年发生的 107 起自报扰动排放事件。考虑到所有事件的不同指标,可以得出结论:基于自报告排放的模型浓度很可能无法预测观测到的浓度增量。根据可能的污染源高度,基于平均烟羽指标,预测不足的中位系数从 3 到 95 不等。对于高排放量和高排放率的事件,模型和观测之间的一致性更好,这也与观测到的高浓度增量相对应。总之,该研究强调了考虑障碍物的重要性,并证明了当前方法作为一种利用 HAPs 边线观测数据对自报的扰动排放进行有效诊断的方法的潜在应用价值。
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 Environment: X
Atmospheric Environment: X Environmental Science-Environmental Science (all)
CiteScore
8.00
自引率
0.00%
发文量
47
审稿时长
12 weeks
期刊最新文献
Detection and analysis of ship emissions using single-particle mass spectrometry: A land-based field study in the port of rostock, Germany Comparison of global air pollution impacts across horizontal resolutions Manifesting the hidden pollutants: Quantifying emissions and environmental impact of petroleum refinery on PM2.5 Quantifying particulate matter emission rates from naturally ventilated dairy buildings by considering roof opening contributions Regional and seasonal impact of hydrogen propulsion systems on potential contrail cirrus cover
×
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