Two-decade surface ozone (O3) pollution in China: Enhanced fine-scale estimations and environmental health implications

IF 11.1 1区地球科学 Q1 ENVIRONMENTAL SCIENCES

Remote Sensing of Environment Pub Date : 2024-11-21 DOI:10.1016/j.rse.2024.114459

Zeyu Yang, Zhanqing Li, Fan Cheng, Qiancheng Lv, Ke Li, Tao Zhang, Yuyu Zhou, Bin Zhao, Wenhao Xue, Jing Wei

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引用次数: 0

Abstract

Surface ozone (O₃) has become a primary pollutant affecting urban air quality and public health in mainland China. To address this concern, we developed a nation-wide surface maximum daily average 8-h (MDA8) O₃ concentration dataset for mainland China (ChinaHighO₃) at a 10-km resolution with a start year of 2013, which has been widely employed in a wide range of studies. To meet the increasing demand for its usage, we have made important enhancements, including the development of a more advanced deep-learning model and the incorporation of major source updates, such as 1-km surface downward shortwave radiation and temperature directly from satellite retrievals, as well as a 1-km emission inventory. Additionally, we have extended the temporal coverage dating back to 2000, increased the spatial resolution to 1 km, and most importantly, notably improved the data quality (e.g., sample-based cross-validation coefficient of determination = 0.89, and root-mean-square error = 15.77 μg/m³). Using the substantially improved new product, we have found dynamic and diverse patterns in national surface O₃ levels over the past two decades. Peak-season levels have been relatively stable from 2000 to 2015, followed by a sharp increase, reaching peak values in 2019 and subsequently declining. Additionally, we observed a large relative difference of 12 % in peak-season surface O₃ concentrations between urban and rural regions in mainland China. This disparity has greatly increased since 2015, particularly in the Beijing-Tianjin-Hebei and Pearl River Delta regions. Notably, since 2000, nearly all of the population across mainland China (> 99.7 %) has resided in areas exposed to surface O₃ pollution exceeding the World Health Organization (WHO) recommended long-term air quality guideline (AQG) level (peak-season MDA8 O₃ = 60 μg/m³). Moreover, the short-term population-risk exposure to daily surface O₃ pollution has shown a significant increasing trend of 1.2 % (p < 0.001) of the days exceeding the WHO's recommended short-term AQG level (daily MDA8 O₃ = 100 μg/m³) per year during the 22-year period. The overall upward trend (0.73 μg/m³/yr, p < 0.001) in peak-season surface O₃ pollution has led to an exceptionally large rate of increase of 953 (95 % confidence interval: 486, 1288) premature deaths per year from 2000 to 2021 in mainland China. Urgent action is required to develop comprehensive strategies aimed at mitigating surface O₃ pollution to enhance air quality in the future.

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中国二十年的地表臭氧（O3）污染：强化的精细尺度估算和对环境健康的影响

地表臭氧（O3）已成为影响中国大陆城市空气质量和公众健康的主要污染物。为解决这一问题，我们开发了中国大陆地表臭氧最大日平均 8 小时（MDA8）浓度数据集（ChinaHighO3），分辨率为 10 千米，起始年为 2013 年。为满足日益增长的使用需求，我们对该数据集进行了重要改进，包括开发了更先进的深度学习模型，并纳入了主要来源更新，如直接从卫星获取的 1 千米地表向下短波辐射和温度，以及 1 千米排放清单。此外，我们还将时间覆盖范围扩展到了 2000 年，将空间分辨率提高到了 1 公里，最重要的是，我们显著提高了数据质量（例如，基于样本的交叉验证确定系数 = 0.89，均方根误差 = 15.77 μg/m3）。利用大幅改进后的新产品，我们发现了过去二十年中全国地表臭氧浓度的动态和多样化模式。从 2000 年到 2015 年，高峰季节的水平相对稳定，随后急剧上升，在 2019 年达到峰值，随后下降。此外，我们还观察到中国大陆城市和农村地区的地表臭氧浓度峰季相对差异较大，达到 12%。自 2015 年以来，这一差距大幅扩大，尤其是在京津冀和珠江三角洲地区。值得注意的是，自 2000 年以来，中国大陆几乎所有人口（99.7%）所居住地区的地表臭氧污染均超过了世界卫生组织（WHO）建议的长期空气质量准则（AQG）水平（峰季 MDA8 O3 = 60 μg/m3）。此外，在这 22 年间，短期人口暴露于每日地表 O3 污染的风险呈显著上升趋势，每年超过世界卫生组织建议的短期空气质量准则水平（每日 MDA8 O3 = 100 μg/m3）的天数占 1.2%（p < 0.001）。从 2000 年到 2021 年，旺季地表 O3 污染的总体上升趋势（0.73 μg/m3/年，p < 0.001）导致中国大陆每年过早死亡人数增加 953 人（95 % 置信区间：486，1288），增幅非常大。为改善未来的空气质量，我们需要采取紧急行动，制定旨在减轻地表 O3 污染的综合战略。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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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.