2010-2021年四川盆地氮氧化物的时空分布特征

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  • 1. 成都信息工程大学大气科学学院,成都平原城市气象与环境四川省野外科学观测研究站,四川 成都 610041
    2. 兰州大学,甘肃 兰州 730000
    3. 中国气象科学研究院,大气成分与环境气象研究所,北京 100081

网络出版日期: 2025-06-26

基金资助

国家自然科学基金项目(42175174);国家重点研发计划课题(2023YFC3709301);成都信息工程大学本科教学工程项目
JYJG2022006

Spatial Distribution Characteristics of Nitrogen Oxides in the Sichuan Basin from 2010 to 2021 

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  • 1. School of Atmospheric SciencesChengdu University of Information TechnologySichuan Province Field Scientific Observation and Research Station for Urban Meteorology and Environment in Chengdu PlainChengdu 610225SichuanChina
    2. Lanzhou UniversityLanzhou 730000GansuChina
    3. Chinese Academy of Meteorological SciencesInstitute of Atmospheric Composition and Environmental MeteorologyBeijing 100081China

Online published: 2025-06-26

摘要

氮氧化物(NOx)排放水平是衡量人为源大气污染物排放的关键指标。研究NOx排放的长期变化趋势并识别热点排放区域,对大气污染治理具有重要意义。本研究利用 OMITROPOMI数据分析了川渝地区 2010-2021年不同区域对流层 NO2柱浓度长期变化趋势以及空间分布特征,并结合地面环境监测站NO2浓度数据和MEIC清单NOx排放量数据,评估了卫星观测的NOx排放的长期变化趋势。结果表明:(1)川渝地区NO2柱浓度的空间分布存在两个热点区域,分别为成都市和重庆市主城区。与OMI相比,TROPOMI因其高信噪比和高分辨率的特点,能够识别更精细的空间分布特征;(2)对流层NO2柱浓度总体呈现下降趋势,在成都平原、重庆以及川渝地区的下降趋势分别为-0. 115×1015-0. 096×1015-0. 053×1015 molec·cm2·a-1;(32010-2012年随着工业源和交通源的 NOx排放量增加,NO2柱浓度逐渐上升。2012-2015NO2柱浓度大幅下降,川渝地区下降幅度为 19. 91%,主要归因于电力部门和工业部门的大幅减排。2015-2017年川渝地区NO2柱浓度上升10. 76%,随后再次逐渐下降;(4)卫星观测的NO2柱浓度变化趋势能够较好地反映地面监测NO2浓度的变化趋势;(5NO2柱浓度季节变化明显:四川盆地各地区冬季NO2柱浓度显著高于其他季节,春秋两季次之,夏季最低;而川西高原地区受自然源影响,夏季NO2柱浓度高于冬季。

本文引用格式

胡 芩, 杨显玉, 王文雷, 李豆旺, 贲秉政, 杨 周, 张小玲 . 2010-2021年四川盆地氮氧化物的时空分布特征[J]. 高原气象, 0 : 1 . DOI: 10.7522/j.issn.1000-0534.2024.00107

Abstract

The level of nitrogen oxidesNOxemission is a key indicator for assessing anthropogenic atmospheric pollutant emissions. Understanding the long-term trends of NOx emissions and identifying emission hotspots are of significant importance for air pollution control. This study utilized OMI and TROPOMI data to analyze the long-term trends and spatial distribution characteristics of tropospheric NO2 column density across various regions of Sichuan and Chongqing from 2010 to 2021. Additionallyground-based NO2 concentration data from environmental monitoring stations and NOx emission data from the MEIC inventory were integrated to evaluate the long-term trends of NOx emissions observed by satellite. Ground-based NO2 concentration measurements and ME‐ IC NO x emission inventory data are incorporated to assess the accuracy of satellite observations. The results show that:(1The spatial distribution of NO2 column density in the Sichuan-Chongqing region reveals two hotspot areasincluding Chengdu and the central urban area of Chongqing. Compared to OMI satelliteTROPOMIwith its higher signal-to-noise ratio and resolutioncaptures more detailed spatial distribution features;(2tropo‐ spheric NO2 column density exhibits a declining trendwith rates of -0. 115×1015-0. 096×1015 and -0. 053×1015 molec·cm2·a-1 in the Chengdu PlainChongqingand the Sichuan-Chongqing regionrespectively;(3NO2 column density increased with rising NOx emissions from industrial and transportation sources during 2010 -2012. For the period of 2012 -2015NO2 column density decreased by 19. 91% across the SichuanChongqing regionwhich is mainly attributed to substantial emission reductions in power and industrial sectors. From 2015 to 2017NO2 concentrations increased by 10. 76%followed by a gradual decline;(4The trends in satellite-observed NO 2 column density closely align with ground-level ambient NO2 measurements;(5NO2 column density exhibits distinct seasonal variationsin the Sichuan Basinwinter NO2 concentrations are significantly higher than in other seasonsfollowed by spring and autumnwith summer concentrations being the low‐ est. In contrastin the western Sichuan PlateauNO2 concentrations are higher in summer than in winter due to natural sources.

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