Zhang Xuguo, Stocker Jenny, Johnson Kate, Fung Yik Him, Yao Teng, Hood Christina, Carruthers David, Fung Jimmy C H
Department of Mathematics The Hong Kong University of Science and Technology Hong Kong China.
Division of Environment and Sustainability The Hong Kong University of Science and Technology Hong Kong China.
Geohealth. 2022 Mar 11;6(3):e2021GH000506. doi: 10.1029/2021GH000506. eCollection 2022 Mar.
Ultrahigh-resolution air quality models that resolve sharp gradients of pollutant concentrations benefit the assessment of human health impacts. Mitigating fine particulate matter (PM) concentrations over the past decade has triggered ozone (O) deterioration in China. Effective control of both pollutants remains poorly understood from an ultrahigh-resolution perspective. We propose a regional-to-local model suitable for quantitatively mitigating pollution pathways at various resolutions. Sensitivity scenarios for controlling nitrogen oxide (NO) and volatile organic compound (VOC) emissions are explored, focusing on traffic and industrial sectors. The results show that concurrent controls on both sectors lead to reductions of 17%, 5%, and 47% in NO, PM, and VOC emissions, respectively. The reduced traffic scenario leads to reduced NO and PM but increased O concentrations in urban areas. Guangzhou is located in a VOC-limited O formation regime, and traffic is a key factor in controlling NO and O. The reduced industrial VOC scenario leads to reduced O concentrations throughout the mitigation domain. The maximum decrease in median hourly NO is >11 μg/m³, and the maximum increase in the median daily maximum 8-hr rolling O is >10 μg/m³ for the reduced traffic scenario. When controls on both sectors are applied, the O increase reduces to <7 μg/m³. The daily averaged PM decreases by <2 μg/m³ for the reduced traffic scenario and varies little for the reduced industrial VOC scenario. An O episode analysis of the dual-control scenario leads to O decreases of up to 15 μg/m³ (8-hr metric) and 25 μg/m³ (1-hr metric) in rural areas.
能够解析污染物浓度急剧梯度变化的超高分辨率空气质量模型，有助于评估对人类健康的影响。在过去十年中，中国降低细颗粒物（PM）浓度引发了臭氧（O）浓度恶化。从超高分辨率的角度来看，对这两种污染物的有效控制仍知之甚少。我们提出了一种适用于在各种分辨率下定量减轻污染路径的区域到局部模型。探索了控制氮氧化物（NO）和挥发性有机化合物（VOC）排放的敏感性情景，重点关注交通和工业部门。结果表明，对这两个部门同时进行控制可分别使NO、PM和VOC排放量减少17%、5%和47%。交通情景减少导致城市地区NO和PM浓度降低，但O浓度升高。广州处于VOC限制的O生成区域，交通是控制NO和O的关键因素。工业VOC情景减少导致整个减排区域O浓度降低。在交通情景减少的情况下，每小时中位数NO的最大降幅>11μg/m³，每日最大8小时滚动O中位数的最大增幅>10μg/m³。当对两个部门都进行控制时，O的增幅降至<7μg/m³。在交通情景减少的情况下，日均PM降低<2μg/m³，在工业VOC情景减少的情况下变化不大。对双重控制情景进行的O事件分析表明，农村地区O浓度最多可降低15μg/m³（8小时指标）和25μg/m³（1小时指标）。
