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2005-2016 年中国西南某特大城市 NO 污染与城市化时空关系制图。

Spatiotemporally mapping of the relationship between NO pollution and urbanization for a megacity in Southwest China during 2005-2016.

机构信息

Department of Environmental Science and Engineering, Sichuan University, Chengdu, Sichuan, 610065, China.

Department of Environmental Science and Engineering, Sichuan University, Chengdu, Sichuan, 610065, China.

出版信息

Chemosphere. 2019 Apr;220:155-162. doi: 10.1016/j.chemosphere.2018.12.095. Epub 2018 Dec 12.

Abstract

Nitrogen dioxide (NO) significantly contributes to air pollution. Long-term NO exposure is harmful to human health. The NO pollution in China has surpassed developed countries and attracts international attention. To understand the spatial and temporal distributions of NO across Chengdu in Southwest China, a random forest (RF) model was developed based on NO environmental monitoring data, the Ozone Monitoring Instrument (OMI) satellite retrievals, and geographic covariates. The RF model showed good performance with a cross validation R of 0.77, and a root mean square error (RMSE) of 11.0 μg/m. The ground-level NO concentrations of Chengdu for 2005-2016 were predicted using the developed model with the multiyear population weighted NO concentration being 41.7 ± 11.7 μg/m. The predicted NO concentrations exhibited a clear seasonal variation trend with winter being the highest and summer being the lowest. Furthermore, higher NO concentrations in the downtown areas were observed than that in the rural areas indicating the former being attributed to more anthropogenic sources. The population weighted NO concentrations with deseasonlization were relatively high during 2011-2013. The NO concentration increased at a rate of 0.81 μg/m/year before 2011 (43.4 ± 11.2 μg/m) and decreased at a rate of -1.03 μg/m/year after 2013 (44.8 ± 12.8 μg/m).

摘要

二氧化氮(NO)对空气污染有重大影响。长期接触 NO 对人类健康有害。中国的 NO 污染已经超过了发达国家,引起了国际关注。为了了解中国西南城市成都的 NO 时空分布情况,本研究基于 NO 环境监测数据、臭氧监测仪(OMI)卫星反演数据和地理协变量,建立了随机森林(RF)模型。RF 模型表现出良好的性能,交叉验证 R 为 0.77,均方根误差(RMSE)为 11.0μg/m。利用该模型预测了 2005-2016 年成都的地面 NO 浓度,多年人口加权的 NO 浓度为 41.7±11.7μg/m。预测的 NO 浓度呈现明显的季节性变化趋势,冬季最高,夏季最低。此外,市中心的 NO 浓度高于农村地区,表明前者受到更多人为源的影响。去季节化后的人口加权 NO 浓度在 2011-2013 年相对较高。2011 年之前,NO 浓度以每年 0.81μg/m 的速度增加(43.4±11.2μg/m),2013 年之后,NO 浓度以每年-1.03μg/m 的速度减少(44.8±12.8μg/m)。

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