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2000 - 2022年北美卫星、模型和监测器所测细颗粒物化学成分:野火贡献的变化

North American Fine Particulate Matter Chemical Composition for 2000-2022 from Satellites, Models, and Monitors: The Changing Contribution of Wildfires.

作者信息

van Donkelaar Aaron, Martin Randall V, Ford Bonne, Li Chi, Pappin Amanda J, Shen Siyuan, Zhang Dandan

机构信息

McKelvey School of Engineering, Washington University in St. Louis, St. Louis, Missouri 63130-4899, United States.

Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, Colorado 80521, United States.

出版信息

ACS EST Air. 2024 Nov 11;1(12):1589-1600. doi: 10.1021/acsestair.4c00151. eCollection 2024 Dec 13.

DOI:10.1021/acsestair.4c00151
PMID:39698103
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11651298/
Abstract

Air quality management benefits from an in-depth understanding of the emissions associated with, and composition of, local PM concentrations. Here, we investigate the changing role of biomass burning emissions to North American PM exposure by combining multiple satellite-, ground-, and simulation-based data sets biweekly at a 0.01° × 0.01° resolution from 2000 to 2022. We also developed a Buffered Leave Cluster Out (BLeCO) method to address autocorrelation and computational cost in cross-validation. Biomass burning emissions contribute an increasingly large fraction to PM exposure in the United States and Canada, with national annual population-weighted mean contributions increasing from 0.4 μg/m (3-5%) in 2000-2004 to 0.8-0.9 μg/m (9-14%) by 2019-2022, led by western North American 2019-2022 annual contributions of 1.4-1.9 μg/m (15-27%) and maximum seasonal contributions of 3.3-5.5 μg/m (29-49%). Other components such as nonbiomass burning Organic Matter (OM) and nitrate can be regionally as (or more) important, albeit with distinct seasonal variability. The contribution of total OM to PM exposure in the United States in 2016-2022 is 42.2%, comparable to all other anthropogenically sourced components combined. Comparison of BLeCO and random 10-fold cross-validation suggests that random 10-fold cross-validation may significantly underrepresent true uncertainty for total PM concentrations due to the clustered nature of PM ground-based monitoring.

摘要

深入了解与当地细颗粒物(PM)浓度相关的排放及其组成,有助于空气质量的管理。在此,我们通过结合2000年至2022年每两周一次、分辨率为0.01°×0.01°的多个基于卫星、地面和模拟的数据集,研究生物质燃烧排放对北美PM暴露影响的变化作用。我们还开发了一种缓冲留簇法(BLeCO),以解决交叉验证中的自相关和计算成本问题。生物质燃烧排放对美国和加拿大的PM暴露贡献比例越来越大,全国年度人口加权平均贡献从2000 - 2004年的0.4μg/m³(3 - 5%)增加到2019 - 2022年的0.8 - 0.9μg/m³(9 - 14%),以2019 - 2022年北美西部年度贡献1.4 - 1.9μg/m³(15 - 27%)和最大季节性贡献3.3 - 5.5μg/m³(29 - 49%)为引领。其他成分,如非生物质燃烧的有机物(OM)和硝酸盐,在区域上可能同样(或更)重要,尽管具有明显的季节变化。2016 - 2022年美国总OM对PM暴露的贡献为42.2%,与所有其他人为来源成分的总和相当。BLeCO与随机10折交叉验证的比较表明,由于PM地面监测的聚集性质,随机10折交叉验证可能会显著低估总PM浓度的真实不确定性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36f6/11651298/8e83439dcf76/ea4c00151_0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36f6/11651298/88c8df2c15a4/ea4c00151_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36f6/11651298/804d4d4fe91b/ea4c00151_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36f6/11651298/7edbd85eaa9a/ea4c00151_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36f6/11651298/3e231974fa3a/ea4c00151_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36f6/11651298/a48fac4caa2a/ea4c00151_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36f6/11651298/8e83439dcf76/ea4c00151_0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36f6/11651298/88c8df2c15a4/ea4c00151_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36f6/11651298/804d4d4fe91b/ea4c00151_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36f6/11651298/7edbd85eaa9a/ea4c00151_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36f6/11651298/3e231974fa3a/ea4c00151_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36f6/11651298/a48fac4caa2a/ea4c00151_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36f6/11651298/8e83439dcf76/ea4c00151_0006.jpg

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本文引用的文献

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Long-term mortality burden trends attributed to black carbon and PM from wildfire emissions across the continental USA from 2000 to 2020: a deep learning modelling study.
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