Long-term variations of major atmospheric compositions observed at the background stations in three key areas of China
Long-term variations of major atmospheric compositions observed at the background stations in three key areas of China
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我国三个重点地区背景站观测到的主要大气成分的长期变化
DOI：
10.1016/j.accre.2020.11.005
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发表时间：
2020-12
影响因子：
7.4
通讯作者：
J.Jin
中科院分区：
文献类型：
--
作者：
Y. Zhang;J.Jin
大气成分和酸雨与大气环境、天气和气候变化密切相关。在这项研究中，CO2，CH 4，O3，PM2.5，PM10和酸雨的浓度水平和长期趋势。根据截至2018年的观测数据，青海瓦里关全球基线站、华北平原（NCP）和中国长江三角洲地区（YRD）的上店子和临安区域本底站。在所有这些站点中发现了CO2的显著增加趋势。在Mt.在Waliguan，浓度水平和增长率与北方半球的平均值和在夏威夷的莫纳罗亚气象站观测到的值一致。CH 4也表现出类似的NH中观察到的上升趋势。与Mt.在瓦里关全球基准站，上店子和临安区域背景站的CO2和CH 4摩尔分数较高，说明人类活动对区域背景CO2和CH 4的贡献很大。年平均地面臭氧在Mt。而临安站则无明显变化趋势。根据PM2.5和PM10的观测结果，上店子和临安的气溶胶浓度变化规律相似。总体而言，自观测以来，两个站的气溶胶浓度呈下降趋势。然而，2006-2007年和2013-2014年出现了两个高颗粒浓度时期。自2013-2014年以来，年均气溶胶浓度持续下降，显示了三峡库区和长江三峡库区污染控制的有效性，特别是自2013年9月实施《大气污染防治行动计划》以来。气溶胶与酸雨的对比分析表明，气溶胶浓度高的前期与酸雨严重污染的前期相一致，说明中国的气溶胶污染和酸雨严重污染都与燃煤排放密切相关。由于控制了燃煤排放的酸和SO2，由于汽车拥有量的迅速增长，NOx排放对气溶胶的贡献更大。通过比较上店子站和临安站气溶胶与地面臭氧最大8小时平均值（MDA 8）的变化趋势，揭示了气溶胶减少与臭氧产生之间的复杂关系，即：随着三峡库区和长江三峡库区颗粒物污染状况的持续改善，两站的MDA 8均呈现先下降后上升的趋势，但气溶胶仍保持下降趋势。MDA 8与PM2.5（或PM10）的这种不同变化模式表明，中国气溶胶和臭氧污染的协同控制面临着很大的挑战。
Atmospheric compositions and acid rain are closely related to atmospheric environment, weather, and climate change. In this study, the concentration levels and long-term trends of CO2, CH4, O3, PM2.5, PM10, and acid rain were presented at the Mt. Waliguan global baseline station in Qinghai, Shangdianzi and Lin'an regional background stations in the North China Plain (NCP) and the Yangtze River Delta region (YRD) of China based on the data observed until 2018. Significant increasing trends of CO2were found at all of these stations. At Mt. Waliguan, the concentration levels and growth rate were consistent with the average values in the Northern Hemisphere (NH) and those observed at the Mauna Loa station in Hawaii. The CH4also showed a upward tendency similar to that observed in NH. Compared with the observations at Mt. Waliguan global baseline station, the CO2and CH4mole fractions were higher at Shangdianzi and Lin'an regional background stations, indicating the important contributions of anthropogenic activities to the regional background level of CO2and CH4. The annual averaged surface ozone showed increasing trends at Mt. Waliguan and Shangdianzi stations, whereas no clear trend was found at Lin'an station. Similar variations in the patterns of aerosol concentrations at Shangdianzi and Lin'an were found according to the PM2.5or PM10observations. Overall, the aerosol concentrations at both stations shown declining trends since the observations. However, two periods of high particle concentrations occurred in 2006–2007 and 2013–2014. The annual mean aerosol concentrations have continuously decreased after 2013–2014, indicating the effectiveness of pollution control in the NCP and YRD, especially since the implementation of the ‘Action Plan for Prevention and Control of Air Pollution’ in September 2013. Comparative analysis of aerosol with acid rain showed that the period with high concentrations of aerosols in the early years was consistent with that of severe acid rain pollution, suggesting that both aerosol pollution and severe acid rain are closely related to coal combustion emissions in China. As a result of the control of coal combustion emissions for acid and SO2, NOxemissions have contributed more substantially to aerosols due to the rapid growth of vehicle ownership. A comparison of the trends of aerosols with the maximum daily 8-h average of surface ozone (MDA8) at Shangdianzi and Lin'an stations revealed the complicated relationship between aerosol reduction and ozone production, i.e., together with the continuous improvement of particulate pollution in the NCP and YRD, the MDA8 at both stations showed a decreasing trend at first but subsequently increased after 2014 with aerosols remaining reduced. Such different variation patterns of the MDA8 with PM2.5(or PM10) indicated the high challenge of synergic control of aerosol and ozone pollution in China.
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影响因子：
10.4
作者：
van Donkelaar A;Martin RV;Brauer M;Kahn R;Levy R;Verduzco C;Villeneuve PJ
通讯作者：
Villeneuve PJ
影响因子：
5.2
作者：
Wang, Tao;Dai, Jianing;Brasseur, Guy P.
通讯作者：
Brasseur, Guy P.
影响因子：
3.1
作者：
Wei‐Chyung Wang;J. Pinto;Y. Yung
通讯作者：
Wei‐Chyung Wang;J. Pinto;Y. Yung
影响因子：
5.5
作者：
Jianan Zou;Zirui Liu;B. Hu;Xiaojuan Huang;T. Wen;D. Ji;Jing-Yuan Liu;Yang Yang-Yang;Q. Yao
通讯作者：
Jianan Zou;Zirui Liu;B. Hu;Xiaojuan Huang;T. Wen;D. Ji;Jing-Yuan Liu;Yang Yang-Yang;Q. Yao
DOI：
10.1016/j.scitotenv.2020.138905
发表时间：
2020-05
期刊：
The Science of the total environment
影响因子：
--
作者：
Lina Gao;Lijuan Cao;Yong Zhang;P. Yan;Junshan Jing;Qing Zhou;Yimeng Wang;Shanshan Lv;
通讯作者：
Lina Gao;Lijuan Cao;Yong Zhang;P. Yan;Junshan Jing;Qing Zhou;Yimeng Wang;Shanshan Lv;