| 引用本文: | 张艳阁,熊维彬,赵付荣,饶欢欢,汪俊峰.2025.甘肃省2015—2021年大气污染时空变化特征研究[J].地球环境学报,16(3):368-378 |
| ZHANG Yange,XIONG Weibin,ZHAO Furong,RAO Huanhuan,WANG Junfeng.2025.Study on the temporal and spatial variation of air pollutants in Gansu Province during 2015—2021[J].Journal of Earth Environment,16(3):368-378 |
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| 甘肃省2015—2021年大气污染时空变化特征研究 |
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张艳阁1, 3，熊维彬1，赵付荣1, 3，饶欢欢1, 3，汪俊峰2, 4*
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1. 闽江学院 地理与海洋学院，福建省海洋生物多样性保护与永续利用重点实验室，福州 350108
2. 南京信息工程大学 环境与科学与工程学院，江苏省大气环境监测与污染控制高技术研究重点实验室，江苏省大气环境与装备技术协同创新中心，南京 210044
3. 福州海洋研究院，福州 350108
4. 上海市环境科学研究院，国家环境保护城市大气复合污染成因与防治重点实验室，上海 200233
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| 摘要: |
| 大气污染物既会对大气环境和人体健康产生负面效应，也可通过干湿沉降迁移至地表，影响地表生态系统。甘肃省临近沙尘源区，自然源沙尘、快速的城市化和工业化以及不利气象因素的耦合，在甘肃省引发了一系列大气污染事件。利用2015—2021年中国环境监测总站国控站点空气污染物浓度数据，研究甘肃省大气污染物时空分布特征及其影响因素。结果表明：（1）相较2015年，2021年甘肃省PM2.5、SO2、NO2和CO的年均浓度均呈下降趋势，降幅分别为31.9%、60.0%、23.4%和45.5%；而PM10波动则受沙尘事件影响。（2）除O3外，主要大气污染物的季节变化趋势一致，均呈冬季高、夏季低的特征；除O3日变化呈“单峰”型特征外，其他大气污染物日变化均呈“双峰”分布特征。（3）从区域上看，河西走廊和陇中地区为大气污染物浓度高值区，陇南地区则为浓度低值区。 |
| 关键词: 甘肃省 大气污染 时空分布 |
| DOI：10.7515/JEE232042 |
| CSTR：32259.14.JEE232042 |
| 分类号: |
| 基金项目:国家环境保护城市大气复合污染成因与防治重点实验室开放课题（2021080544）；福建省教育厅中青年教师科研项目（JAT190632）；江苏省大气环境监测与污染控制高技术研究重点实验室开放基金（KHK2006） |
| 英文基金项目:State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex (2021080544); Educational and Scientific Research (on Science and Technology) Projects for Young and Middle-aged Teachers in Fujian (JAT190632); Open Fund by Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control (KHK2006) |
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| Study on the temporal and spatial variation of air pollutants in Gansu Province during 2015—2021 |
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ZHANG Yange1, 3, XIONG Weibin1, ZHAO Furong1, 3, RAO Huanhuan1, 3, WANG Junfeng2, 4*
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1. Fujian Key Laboratory on Conservation and Sustainable Utilization of Marine Biodiversity, College of Geography and Oceanography, Minjiang University, Fuzhou 350108, China
2. Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
3. Fuzhou Institute of Oceanography, Fuzhou 350108, China
4. State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environment Sciences, Shanghai 200233, China
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| Abstract: |
| Background, aim, and scope Atmospheric pollutants not only have negative effects on the atmospheric environment and human health but can also be deposited on the ground through dry and wet deposition, thereby affecting soil quality and terrestrial ecosystems. Gansu Province is located in the Hexi Corridor and is close to the dust-source regions. The combination of dust-raising processes, rapid urbanisation and industrialisation and adverse meteorological factors has triggered a series of atmospheric pollution events in Gansu Province. To better understand the status of air pollution and provide supporting data for air treatment, the concentration of air pollutants recorded by the national monitoring sites of the China National Environmental Monitoring Centre from 2015 to 2021 were used to study the spatiotemporal distribution characteristics of atmospheric pollutants in Gansu Province and their influencing factors. Materials and methods Hourly pollutant data (PM2.5, PM10, SO2, NO2, CO, O3) from 2015 to 2021 were acquired from the national monitoring sites of China National Environmental Monitoring Centre. Data processing and air quality evaluation were following “GB 3095—2012, ambient air quality standards” and “HJ 663—2013, technical regulation on ambient air quality index (on trial)”. Results (1) Compared with 2015, the annual average concentrations of PM2.5, SO2, NO2 and CO in Gansu Province showed a decreasing trend, with a decline of 31.9%, 60.0%, 23.4% and 45.5%, respectively. Unlike the trend of PM2.5, the annual average concentration of PM10 in Gansu Province remained stable from 2015 to 2018 (ranging from 92.3 to 99.0 μg·m−3), however it dropped sharply in 2019 and 2020, decreasing by approximately 30% compared with that in 2015. In 2021, the concentration of PM10 increased to 87.1 μg·m−3. Except for O3 and PM10, the seasonal variation of the major air pollutants followed similar trends, having a high concentration in winter and a low concentration in summer. PM10 and O3 were detected at high concentrations in spring and summer, respectively. The diurnal variation of the atmospheric pollutants (except for O3) followed a ‘bimodal’ distribution. The O3 variation had a unimodal profile, and the concentration of O3 also showed unimodal characteristics. From a regional point of view, the Hexi Corridor and Longzhong area are regions with high concentrations of atmospheric pollutants, whereas the Longnan areas have low concentrations. Discussion Overall, the annual average concentration of PM2.5 met the national secondary standard (35 μg·m−3) since 2019; however, it is above the national primary annual standard (15 μg·m−3). According to data from the China Statistical Yearbook: 2015—2020, the total emissions of SO2 and NO2 in Gansu Province decreased by 85.0% and 49.3%, respectively. NO2 and SO2 are crucial precursors of atmospheric PM2.5, where a decrease in the concentrations of these precursors may be a significant factor influencing the reduction in atmospheric PM2.5 concentration. Fluctuations in the concentration of respirable PM10 are influenced by dust events. The increase in O3 from 2015 to 2017 may be related to the reduction of NO2 emissions, whereas the decrease of O3 concentration after 2018 may be caused by an emission reduction of volatile organic compounds. Except for PM10 and O3, the seasonal variation of the major air pollutants followed similar trends, characterised by a high concentration in winter and low concentration in summer. Heating emission and lower convective mixing layer (or inversion layers) in winter may contribute to the high pollutant concentration in winter. In contrast, the favourable meteorological conditions in summer facilitate the upwards diffusion and transport of near-surface pollutants, resulting in lower pollutant concentrations. The bimodal diurnal distribution of PM2.5, SO2, NO2 and CO may arise from the complex influence of human activity, the inversion layer and the height of the planetary boundary layer. O3 shows a unimodal diurnal variation and peaked at 16: 00, which is primarily influenced by photochemical reaction. Spatially, the Hexi Corridor and the Longzhong area have high concentrations of atmospheric particulate matter (PM2.5 and PM10) concentrations, whereas the Longnan area is the region with the lowest pollutant concentrations. The decreasing trend of PM10 from west to east suggests dust transport is the crucial process in this region. Conclusions The concentrations of atmospheric pollutants in Gansu Province (with the exception of PM10 and O3) show a general downward trend, indicating that the pollution reduction efforts in Gansu Province have effectively improved air quality. However, the mass concentration of O3, remains at a relatively high level. The concentration of PM10 may be affected by dust events; thus, the concentration trend has significant uncertainty. Recommendations and perspectives The mass concentration of O3 follows a different trend from the declining annual average concentrations of other pollutants and remains at a relatively high level. Therefore, future research should focus on strengthening the monitoring of concentration and sources of ozone. Dust events may add further uncertainty to air pollution control. |
| Key words: Gansu Province air pollution temporal and spatial distribution |
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