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评估贝叶斯最大熵数据融合方法以估算美国海湾地区的苯乙烯、苯、甲苯、乙苯和二甲苯,并为流行病学分析提供信息。

Evaluation of Bayesian Maximum Entropy Data Fusion Approaches to Estimate Styrene, Benzene, Toluene, Ethylbenzene, and Xylenes and to Inform Epidemiological Analyses in the US Gulf States.

作者信息

Abbott Nora A, Semone Lucie, Strott Richard, Dodda Praful, Wang Chi-Tsan, Green Jaime, Baek Bok Haeng, Engel Lawrence S, Vizuete William, Serre Marc L

机构信息

Department of Environmental Sciences & Engineering, University of North Carolina, Chapel Hill, North Carolina 27599, United States.

Center for Spatial Information Science and Systems (CSISS), George Mason University, Fairfax, Virginia 22030, United States.

出版信息

Environ Sci Technol. 2025 Jan 14;59(1):45-55. doi: 10.1021/acs.est.4c05094. Epub 2025 Jan 3.

DOI:10.1021/acs.est.4c05094
PMID:39754299
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11789024/
Abstract

The Gulf States are home to industries emitting styrene, benzene, toluene, ethylbenzene, and xylenes (SBTEX). Presently, adverse health effects of ambient SBTEX exposure in highly polluted regions, such as the Gulf States, must be evaluated. Epidemiologists, however, are limited by inadequate estimates of ambient SBTEX. Using Bayesian Maximum Entropy, SBTEX estimation methods of varying resource intensity were evaluated, including simple kriging (least intense), incorporation of observational and emissions data trends (moderately intense), and data fusion of observed and Comprehensive Air quality Model with extensions (CAMx) data (most intense). Generally, as resource intensity increased, so did SBTEX estimation performance, where SBTEX Spearman values increased by 0.48 on average from the least to most intense methods. Data fusion of observed and CAMx data was identified as the best ambient SBTEX estimation method in the Gulf States. Exposure estimates revealed that Gulf States residences within commuting distance of high industrial activity experienced 1.64 times higher 97.5th percentile daily exposures to SBTEX on average than those living in less industrialized areas, which could contribute to total occupational and ambient exposure disparities. Furthermore, ambient benzene exposure was greater than the acceptable one-in-a-million excess cancer risk threshold for 75% of estimated residence locations in the Gulf States.

摘要

海湾国家是苯乙烯、苯、甲苯、乙苯和二甲苯(SBTEX)排放行业的所在地。目前,必须评估在海湾国家等高污染地区,环境中SBTEX暴露对健康的不利影响。然而,流行病学家受到环境中SBTEX估计不足的限制。使用贝叶斯最大熵方法,评估了不同资源强度的SBTEX估计方法,包括简单克里金法(资源强度最低)、纳入观测和排放数据趋势(资源强度中等)以及观测数据与扩展综合空气质量模型(CAMx)数据的融合(资源强度最高)。一般来说,随着资源强度的增加,SBTEX估计性能也会提高,从资源强度最低到最高的方法,SBTEX斯皮尔曼值平均增加0.48。观测数据与CAMx数据的融合被确定为海湾国家环境中SBTEX的最佳估计方法。暴露估计显示,在高工业活动通勤距离内的海湾国家居民,平均每天接触SBTEX的第97.5百分位数比生活在工业化程度较低地区的居民高1.64倍,这可能导致职业和环境总暴露差异。此外,在海湾国家,估计有75%的居住地点的环境苯暴露超过了可接受的百万分之一额外癌症风险阈值。

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本文引用的文献

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Ethylene Oxide in Southeastern Louisiana's Petrochemical Corridor: High Spatial Resolution Mobile Monitoring during HAP-MAP.路易斯安那州东南部石化走廊中的环氧乙烷:HAP-MAP 期间的高空间分辨率移动监测。
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A hyperlocal hybrid data fusion near-road PM2.5 and NO2 annual risk and environmental justice assessment across the United States.美国的局地混合数据融合近路 PM2.5 和 NO2 年风险与环境正义评估。
PLoS One. 2023 Jun 1;18(6):e0286406. doi: 10.1371/journal.pone.0286406. eCollection 2023.
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Microbial Find, Inform, and Test Model for Identifying Spatially Distributed Contamination Sources: Framework Foundation and Demonstration of Ruminant Abundance in River Sediments.微生物发现、信息和测试模型,用于识别空间分布的污染来源:框架基础以及河流沉积物中反刍动物丰度的论证。
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PM polluters disproportionately and systemically affect people of color in the United States.颗粒物污染者对美国有色人种造成了不成比例且系统性的影响。
Sci Adv. 2021 Apr 28;7(18). doi: 10.1126/sciadv.abf4491. Print 2021 Apr.
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Estimating Wildfire Smoke Concentrations during the October 2017 California Fires through BME Space/Time Data Fusion of Observed, Modeled, and Satellite-Derived PM.通过对观测、模型和卫星衍生的 PM 进行 BME 时空数据融合估算 2017 年 10 月加州大火期间的野火烟雾浓度
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Kriging-Based Land-Use Regression Models That Use Machine Learning Algorithms to Estimate the Monthly BTEX Concentration.基于克里金的土地利用回归模型,利用机器学习算法估计每月 BTEX 浓度。
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