Full-coverage mapping and spatiotemporal variations of ground-level ozone (O3) pollution from 2013 to 2020 across China

IF 11.4 1区地球科学 Q1 ENVIRONMENTAL SCIENCES

Remote Sensing of Environment Pub Date : 2022-03-01 Epub Date: 2021-11-11 DOI:10.1016/j.rse.2021.112775

Jing Wei , Zhanqing Li , Ke Li , Russell R. Dickerson , Rachel T. Pinker , Jun Wang , Xiong Liu , Lin Sun , Wenhao Xue , Maureen Cribb

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引用次数: 0

Abstract

Ozone (O₃) is an important trace and greenhouse gas in the atmosphere, posing a threat to the ecological environment and human health at the ground level. Large-scale and long-term studies of O₃ pollution in China are few due to highly limited direct ground and satellite measurements. This study offers a new perspective to estimate ground-level O₃ from solar radiation intensity and surface temperature by employing an extended ensemble learning of the space-time extremely randomized trees (STET) model, together with ground-based observations, remote sensing products, atmospheric reanalysis, and an emission inventory. A full-coverage (100%), high-resolution (10 km) and high-quality daily maximum 8-h average (MDA8) ground-level O₃ dataset covering China (called ChinaHighO₃) from 2013 to 2020 was generated. Our MDA8 O₃ estimates (predictions) are reliable, with an average out-of-sample (out-of-station) coefficient of determination of 0.87 (0.80) and root-mean-square error of 17.10 (21.10) μg/m³ in China. The unique advantage of the full coverage of our dataset allowed us to accurately capture a short-term severe O₃ pollution exposure event that took place from 23 April to 8 May in 2020. Also, a rapid increase and recovery of O₃ concentrations associated with variations in anthropogenic emissions were seen during and after the COVID-19 lockdown, respectively. Trends in O₃ concentration showed an average growth rate of 2.49 μg/m³/yr (p < 0.001) from 2013 to 2020, along with the continuous expansion of polluted areas exceeding the daily O₃ standard (i.e., MDA8 O₃ = 160 μg/m³). Summertime O₃ concentrations and the probability of occurrence of daily O₃ pollution have significantly increased since 2015, especially in the North China Plain and the main air pollution transmission belt (i.e., the “2 + 26” cities). However, a decline in both was seen in 2020, mainly due to the coordinated control of air pollution and ongoing COVID-19 effects. This carefully vetted and smoothed dataset is valuable for studies on air pollution and environmental health in China.

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2013 - 2020年中国地面臭氧(O3)污染全覆盖制图及时空变化

臭氧(O3)是大气中重要的微量元素和温室气体，对地面生态环境和人类健康构成威胁。由于地面和卫星的直接测量非常有限，对中国臭氧污染的大规模和长期研究很少。本研究利用时空极端随机树(STET)模型的扩展集合学习，结合地面观测、遥感产品、大气再分析和排放清单，为从太阳辐射强度和地表温度估算地面O3提供了一个新的视角。生成了2013 - 2020年全覆盖(100%)、高分辨率(10 km)、高质量的中国地面臭氧日最大8小时平均值(MDA8)数据集(ChinaHighO3)。我们的MDA8 O3估计(预测)是可靠的，中国的平均样本外(站外)决定系数为0.87(0.80)，均方根误差为17.10 (21.10)μg/m3。我们的数据集完全覆盖的独特优势使我们能够准确捕捉到2020年4月23日至5月8日发生的短期严重臭氧污染暴露事件。此外，在COVID-19封锁期间和之后，分别观察到与人为排放变化相关的O3浓度的快速增加和恢复。O3浓度趋势显示平均增长率为2.49 μg/m3/yr (p <0.001)，同时O3日超标(即MDA8 O3 = 160 μg/m3)的污染区域不断扩大。2015年以来，夏季O3浓度和日O3污染发生概率显著增加，特别是在华北平原和主要大气污染输送带(即“2 + 26”城市)。然而，这两项指标在2020年都有所下降，主要原因是空气污染的协调控制和COVID-19的持续影响。这个经过仔细审查和平滑的数据集对中国空气污染和环境健康的研究有价值。

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来源期刊

Remote Sensing of Environment 环境科学-成像科学与照相技术

CiteScore

25.10

自引率

8.90%

发文量

455

审稿时长

53 days

期刊介绍： Remote Sensing of Environment (RSE) serves the Earth observation community by disseminating results on the theory, science, applications, and technology that contribute to advancing the field of remote sensing. With a thoroughly interdisciplinary approach, RSE encompasses terrestrial, oceanic, and atmospheric sensing. The journal emphasizes biophysical and quantitative approaches to remote sensing at local to global scales, covering a diverse range of applications and techniques. RSE serves as a vital platform for the exchange of knowledge and advancements in the dynamic field of remote sensing.