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模拟非常规天然气作业区的空气污染时空变异性。

Modelling spatial & temporal variability of air pollution in an area of unconventional natural gas operations.

机构信息

Civil and Mineral Engineering, University of Toronto, Canada.

Physical and Environmental Sciences, University of Toronto Scarborough, Canada.

出版信息

Environ Pollut. 2024 May 1;348:123773. doi: 10.1016/j.envpol.2024.123773. Epub 2024 Mar 16.

Abstract

Despite the growing unconventional natural gas production industry in northeastern British Columbia, Canada, few studies have explored the air quality implications on human health in nearby communities. Researchers who have worked with pregnant women in this area have found higher levels of volatile organic compounds (VOCs) in the indoor air of their homes associated with higher density and closer proximity to gas wells. To inform ongoing exposure assessments, this study develops land use regression (LUR) models to predict ambient air pollution at the homes of pregnant women by using natural gas production activities as predictor variables. Using the existing monitoring network, the models were developed for three temporal scales for 12 air pollutants. The models predicting monthly, bi-annual, and annual mean concentrations explained 23%-94%, 54%-94%, and 73%-91% of the variability in air pollutant concentrations, respectively. These models can be used to investigate associations between prenatal exposure to air pollutants associated with natural gas production and adverse health outcomes in northeastern British Columbia.

摘要

尽管加拿大不列颠哥伦比亚省东北部非常规天然气生产行业不断发展,但很少有研究探讨该地区附近社区的空气质量对人类健康的影响。在该地区与孕妇合作的研究人员发现,与气井密度更高和距离更近相关的室内空气中的挥发性有机化合物 (VOC) 水平更高。为了进行正在进行的暴露评估,本研究通过使用天然气生产活动作为预测变量,为孕妇的家庭开发了用于预测环境空气污染的土地利用回归 (LUR) 模型。利用现有的监测网络,针对 12 种空气污染物,为三个时间尺度开发了模型。预测月平均、双年平均和年平均浓度的模型分别解释了 23%-94%、54%-94%和 73%-91%的空气污染物浓度变化。这些模型可用于调查与天然气生产相关的产前暴露于空气污染物与不列颠哥伦比亚省东北部不良健康结果之间的关联。

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