秸秆焚烧对中国东部气溶胶时空格局的影响

大气与环境光学学报 ›› 2013, Vol. 8 ›› Issue (4): 241-252.

• 大气光学 • 下一篇

秸秆焚烧对中国东部气溶胶时空格局的影响

杨元建1,2,3, 傅云飞1,2,3*, 吴必文3, 石春娥3, 邓学良3, 张浩3, 张颖2

(1 中国科学院安徽光学精密机械研究所中国科学院大气成分与光学重点实验室, 安徽合肥 230031;
2 中国科学技术大学地球和空间科学学院大气探测与水循环实验室, 安徽合肥 230026;
3 安徽省气象科学研究所安徽省大气科学与卫星遥感重点实验室, 安徽合肥 230031)

收稿日期:2013-04-12 修回日期:2013-05-18 出版日期:2013-07-28 发布日期:2013-07-16
通讯作者: 傅云飞（1961-），男，安徽安庆人，博士，教授，主要从事卫星遥感资料的分析处理、反演及其在天气和气候方面的应用研究. E-mail:fyf@ustc.edu.cn
作者简介:杨元建（1985-），男，安徽寿县人，博士研究生，主要从事卫星遥感与气候环境变化研究。
基金资助:
国家重点基础研究发展计划(2010CB428601)、国家公益性行业支撑项目( GYHY201306077，GYHY201206011)、中国科学院战略性先导科技专项（XDA05100303）、国家自然科学基金(41230419, 41075041，41205126)、安徽省自然科学基金项目(1308085MD55)、中国科学院大气成分与光学重点实验室开放课题（JJ1102）资助

Impacts of Agricultural Fire on Aerosol Distribution over East China During Summer Harvest Time

YANG Yuan-jian1,2,3, FU Yun-fei1,2,3*, WU Bi-wen3, SHI Chun-e3, DENG Xue-Liang3, ZHANG Hao3, ZHANG Ying2

(1 Key Laboratory of Atmospheric Composition and Optical Radiation, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China;
2 Laboratory of Atmosphere Observation and Water Cycle, School of Earth and Space Sciences, University of Science and Technology of China, Hefei, 230026, China;
3 Key Laboratory of Atmospheric Sciences and Satellite Remote Sensing of Anhui Province, Anhui Institute of Meteorological Sciences, Hefei 230031, China )

Received:2013-04-12 Revised:2013-05-18 Published:2013-07-28 Online:2013-07-16

摘要/Abstract

摘要：

利用2001-2009年期间的MODIS遥感数据，结合地面能见度资料和近地面风场资料，通过个例和统计分析了我国东部地区6月份的气溶胶时空格局及其成因。结果表明： 1）MODIS监测的火点主要分布在32°N -35°N东西向带状区域内，气溶胶光学厚度（AOD）的高值区和监测到的火点高发区有着较好的空间对应关系。6月受到秸秆焚烧的影响，整个东部地区的AOD达到全年最高。此外，地形和人类活动共同决定了东部地区气溶胶的分布格局。2）安徽地区的能见度、霾日数以及AOD的逐月变化关系表明，6月份夏收季节大量焚烧秸秆，造成空气中颗粒物浓度升高，配合相应的气象条件使得整个东部地区的AOD均有所上升。这进一步加重了东部地区的空气污染，形成了严重灰霾天气，从而导致能见度下降。3）我国东部地区6月份AOD的时空变化（特别是年际变化）与近地面风场时空变化密切相关：风速大值区，污染物容易扩散，AOD相对较低；风速小值区，即气流停滞区，水平扩散条件不好，污染物浓度容易升高，AOD相对较高。

关键词: 气溶胶, MODIS, 中国东部, 秸秆燃烧, 霾

Abstract:

The Moderate Resolution Imaging Spectroradiometer (MODIS) level 2 aerosol products (2001–2009) were used to study aerosol spatial and temporal distributions in Jun, as well as their variations with surface wind over East China. The results of case and statistical studies indicate that fire pixels almost dominate the whole northern Anhui and Jiangsu Provinces (32°N -35°N) in Jun. It is found that fire pixel count is quite large in June and clearly matches the high aerosol optical depth (AOD) loads during the burning month. These suggest that agricultural biomass burning occurs seriously in June, which leads to appearance of AOD peak values over East China. Moreover, the distribution feature of aerosol over East China has been proved mainly depending on topography and anthropogenic activities. The variabilities of visibility, days of haze and AOD in Anhui Province demonstrated that the agricultural biomass burning aerosols can also be transported into East China from the surrounding rural area in June. The spatial-temporal variabilities of AOD in Jun over East China are closely related to those of surface wind. On one hand, strong wind is favor for the diffusion of the pollutants, which leads to the relatively lower AOD loads. On the other hand, still wind process by which formation of airflow stagnation area can induce that the pollutants accumulate much easily, which leads to the relatively higher AOD loads.

Key words: aerosol, MODIS, East China, agricultural fire, haze

中图分类号:

P401

杨元建傅云飞吴必文石春娥邓学良张浩张颖. 秸秆焚烧对中国东部气溶胶时空格局的影响[J]. 大气与环境光学学报, 2013, 8(4): 241-252.

YANG Yuan-Jian, FU Yun-Fei, WU Bi-Wen, SHI Chun-E, DENG Xue-Liang, ZHANG Hao, ZHANG Ying. Impacts of Agricultural Fire on Aerosol Distribution over East China During Summer Harvest Time[J]. Journal of Atmospheric and Environmental Optics, 2013, 8(4): 241-252.

参考文献

[1] Albrecht B A. Aerosols, cloud microphysics, and fractional cloudiness [J]. Science, 1989, 245(4923): 1227-1230.
[2] Ferek R J, Hegg D A, Hobbs P V, et al. Measurements of ship-induced tracks in clouds off the Washington coast [J]. J. Geophys. Res., 1998, 103(D18): 23199-23206.
[3] Rosenfeld D, Dai J, Yu X, et al. Inverse relations between amounts of air pollution and orographic precipitation [J]. Science, 2007, 315(5817): 1396-1398
[4] Duan Jing, Mao Jietai. Influence of aerosol on regional precipitation in North China [J]. Chinese Science Bulletin, 2009, 54 (3): 474-483(in Chinese).
段婧, 毛节泰. 华北地区气溶胶对区域降水的影响 [J]. 科学通报, 2008, 53(23): 2947-2955.
[5] Song Yao, Ma Jinji. Estimation of aerosol direct radiative forcing in Beijing area using MODIS data [J]. Journal of Atmospheric and Environmental Optics, 2012, 7(6): 445-451(in Chinese).
宋姚, 麻金继. 利用MODIS数据计算北京地区的气溶胶直接辐射强迫 [J]. 大气与环境光学学报, 2012, 7(6): 445-451.
[6] Wang Yi. The development of atmospheric aerosol investigation by earth observation system [J]. Remote Sensing Technology and Application, 2006, 21(6): 584-592(in Chinese).
王毅. 国际新一代对地观测系统在气溶胶遥感方面的应用 [J]. 遥感技术与应用, 2006, 21(6): 584-592.
[7] Shao Pei, Ma Jinji, Hong Chao. Spatial-temporal features of aerosol optical thickness on polarization information in Beijing area [J]. Journal of Atmospheric and Environmental Optics, 2012, 7(2): 108-115(in Chinese).
邵培, 麻金继, 洪超. 基于偏振数据反演北京市的气溶胶光学厚度及其时空特征的研究 [J]. 大气与环境光学学报, 2012, 7(2): 108-115.
[8] Liu Zhaoliang, Ma Jinji. Retrieval of aerosol optical thickness over bright surface areas using MODIS data [J]. Journal of Atmospheric and Environmental Optics, 2012, 7(5): 358-363(in Chinese).
刘兆亮, 麻金继. 基于MODIS数据反演高反射率地区气溶胶光学厚度的方法研究 [J].大气与环境光学学报, 2012, 7(5): 358-363.
[9] Liu Guiqing, Mao Jietai, Li Chengcai. Optical depth research of atmospheric aerosol in the Yangtze River Delta Region [J]. Shanghai Environmental Sciences, 2003, (S2): 58-63(in Chinese).
刘桂青, 毛节泰, 李成才. 长江三角洲地区大气气溶胶光学厚度研究 [J]. 上海环境科学, 2003, (S2): 58-63.
[10] Li Chengcai, Mao Jietai, Liu Qihan. Characteristics of the spatial distribution and seasonal variation of aerosol optical depth over China using MODIS data [J]. Chinese Science Bulletin, 2003, 48(19): 2094-2100(in Chinese).
李成才, 毛节泰, 刘启汉，等. 利用MODIS研究中国东部地区气溶胶光学厚度的分布和季节变化特征 [J]. 科学通报, 2003, 48(19): 2094-2100.
[11] Sun Juan, Shu Jiong, Lu Xiaoqin, et al. Application of aerosol optical depth data from MODIS to retrieval visibility [J]. Environmental Science and Management, 2006, 31(5): 96-101(in Chinese).
孙娟, 束炯, 鲁小琴, 等. MODIS 遥感气溶胶光学厚度产品在地面能见距中的应用 [J]. 环境科学与管理, 2006, 31(5): 96-101.
[12] Wang Yu, Fu Yunfei. Comparison on aerosol properties between central and East China and Indian Subcontinent by using MODIS products [J]. Climatic and Environmental Research, 2007, 12(2): 137-146(in Chinese).
王雨, 傅云飞. 利用MODIS卫星资料对中国中东部和印度次大陆地区气溶胶特性的分析 [J]. 气候与环境研究, 2007, 12(2): 137-146.
[13] Deng Xueliang, Deng Weitao, He Dongyan. Spatial-temporal features of atmospheric aerosol in East China in recent years [J]. Transactions of Atmospheric Sciences, 2010, 33(3): 347-354(in Chinese).
邓学良, 邓伟涛, 何冬燕. 近年来华东地区大气气溶胶的时空特征 [J]. 大气科学学报, 2010, 33(3) : 347-354.
[14] Cai Hongke, Zhou Renjun, Fu Yunfei, et al. Aerosol lidar with orthogonal polarization detection of aerosol optical properties after a crop burning case [J]. Climatic and Environmental Research, 2011, 16(4): 469-478(in Chinese),.
蔡宏珂, 周任君, 傅云飞, 等. CALIOP对一次秸秆焚烧后气溶胶光学特征的探测分析 [J]. 气候与环境研究, 2011, 16(4): 469-478.
[15] He Q S, Li C C, Geng F H, et al. Study on long-term aerosol distribution over the land of East China using MODIS data [J]. Aerosol Air Qual. Res., 2012, 12: 304-319.
[16] Li H Y, Han Z W, Cheng T T, et al. Agricultural fire impacts on the air quality of Shanghai during summer harvest time [J]. Aerosol Air Qual. Res., 2010, 10(2): 95-101.
[17] Wu Dui, Liao Guolian, Deng Xue jiao, et al. Transport condition of surface layer under haze weather over the Pearl River Delta [J]. Journal of Applied Meterological Science, 2008, 19(1): 1-9(in Chinese).
吴兑, 廖国莲, 邓雪娇, 等. 珠江三角洲霾天气的近地层输送条件研究 [J]. 应用气象学报, 2008, 19(1): 1-9.

秸秆焚烧对中国东部气溶胶时空格局的影响

Impacts of Agricultural Fire on Aerosol Distribution over East China During Summer Harvest Time

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	董鉴韬, 李正强, 谢一凇, 樊程, 洪津, 戴刘新, 顾浩然, 郑杨 . 基于GF-5(02) 卫星DPC数据的2022年春季陆表细粒子气溶胶光学厚度空间分布[J]. 大气与环境光学学报, 2023, 18(4): 323-338.
[2]	翟颖超, 王涵, 赵梅如, 陈科, 李林森 . 山区气溶胶多角度偏振遥感地气解耦方法评估[J]. 大气与环境光学学报, 2023, 18(4): 339-356.
[3]	顾浩然, 李正强, 侯伟真, 裘桢炜, 刘振海, 朱军, 伽丽丽, 罗杰, 洪津, 麻金继 . 紫外多角度偏振探测气溶胶层高的信息量分析初步研究[J]. 大气与环境光学学报, 2023, 18(4): 357-370.
[4]	孙二昌, 麻金继, 吴文涵, 杨光, 郭金雨, . Himawari-8气溶胶变分同化对PM2.5污染模拟的改进[J]. 大气与环境光学学报, 2023, 18(1): 59-72.
[5]	汪惜今, 徐青山, 范传宇, 程晨, 戚鹏, 徐赤东 . 激光雷达探测整层大气昼夜气溶胶光学厚度[J]. 大气与环境光学学报, 2023, 18(1): 14-24.
[6]	黄冬, 李新, 张艳娜, 张允祥 . 全自动太阳光度计温控系统设计及测试[J]. 大气与环境光学学报, 2023, 18(1): 73-81.
[7]	许健, 饶兰兰, DOICU Adrian, 胡斯勒图∗, 秦凯∗. 基于氧气A 带的高光谱卫星气溶胶层高优化反演[J]. 大气与环境光学学报, 2022, 17(6): 630-639.
[8]	王雪林, 陈文忠∗. 亚北极太平洋气溶胶光学厚度与净初级生产力的变化特征及其相关性研究[J]. 大气与环境光学学报, 2022, 17(5): 558-569.
[9]	陈玉宽, 王朔, 徐学哲, 赵卫雄, 盖艳波, 方波, 张为俊, ∗. 安徽省寿县气溶胶消光系数变化特征分析[J]. 大气与环境光学学报, 2022, 17(5): 533-541.
[10]	蔡振锋, 李丁∗, 黄海虹. 2021 年春季沙尘传输对徐州地区气溶胶演变影响分析[J]. 大气与环境光学学报, 2022, 17(4): 409-419.
[11]	程璐璐, 施文杰, 夏果∗, 王江涛, 陈巧芹, 金施群. 偏振氧A 带光谱气溶胶垂直剖面反演的信息量分析和灵敏度研究[J]. 大气与环境光学学报, 2022, 17(3): 360-368.
[12]	陈标, 吴东, ∗. 基于CALIOP 和MODIS 的北极地区海雾检测研究[J]. 大气与环境光学学报, 2022, 17(2): 267-278.
[13]	赵锋, 冯亚娟∗. 2-甲基甘油酸-硫酸/甲磺酸团簇的大气物化特性研究[J]. 大气与环境光学学报, 2022, 17(2): 213-219.
[14]	姜晓彤, 杜林∗. 环境因素影响二次有机气溶胶生成的研究进展[J]. 大气与环境光学学报, 2022, 17(1): 3-15.
[15]	项往, 王炜罡, ∗, 张文玉, 葛茂发, ∗, 李坤. 二次有机气溶胶光学特性研究进展[J]. 大气与环境光学学报, 2022, 17(1): 16-28.