2010—2019年粤港澳地区气溶胶光学厚度时空分布特征

何沐全; 肖建军; 石艳军; 吴永琪

doi:10.16032/j.issn.1004-4965.2021.061

2010—2019年粤港澳地区气溶胶光学厚度时空分布特征

doi: 10.16032/j.issn.1004-4965.2021.061

1.
广东省气象卫星遥感中心，广东广州 510641
2.
河源市气象局，广东河源 517000

基金项目:

广东省气象局科学技术研究项目 GRMC2018M08

广州气象卫星地面站2019年科研课题 1911

详细信息

通讯作者:
何沐全, 男, 广东省人, 工程师, 从事大气环境遥感研究。E-mail: wxzhmq@outlook.com

中图分类号: X16
计量
- 文章访问数: 7
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- 被引次数: 0
出版历程
- 收稿日期: 2020-11-06
- 修回日期: 2021-06-28
- 网络出版日期: 2021-12-15
- 刊出日期: 2021-08-20

SPATIO-TEMPORAL DISTRIBUTION CHARACTERISTICS OF AEROSOL OPTICAL DEPTH IN GUANGDONG, HONG KONG AND MACAO FROM 2010 TO 2019

1.
Guangdong Meteorological Satellite Remote Sensing Center, Guangzhou 510641, China
2.
Heyuan Meteorological Bureau, Heyuan 517000, China

摘要

摘要: 为了解粤港澳地区气溶胶光学厚度分布和时序变化规律, 深入认识大气气溶胶的光学特性及其气候效应, 利用2010—2019年的MODIS C61 AOD 3 km逐日产品, 分析了粤港澳地区的AOD空间分布及年、季、月变化特征。(1) MODIS AOD与AERONET CE318 AOD最优拟合系数为0.96, 与SolarSIM-D2 AOD拟合系数为0.62, 与PM < sub > 2.5 < /sub > 、PM < sub > 10 < /sub > 的最优拟合系数为0.58、0.56。(2)空间上表现为珠三角AOD值高, 粤西次之, 粤北及粤东北较低。(3)年变化特征整体上呈明显的下降趋势, 2010—2014年AOD波动上升, 至2014年达到峰值, 2015年后AOD显著减小, 于2016年达到最低值。(4)季节上表现为春季 > 夏季 > 秋季 > 冬季。(5)月变化特征表现为3月最大(AOD值: 0.73), 4月次之, 5—8月AOD维持在高值且波动平稳, 9—12月显著下降。研究显示, 粤港澳地区颗粒物污染防治应以佛山、广州等珠江三角洲城市及粤西为主, 重点控制春夏季高污染企业生产强度及颗粒物排放。
- 粤港澳地区 /
- MODIS /
- 气溶胶光学厚度 /
- 时空分布 /
- 太阳光度计
Abstract: To understand the optical depth distribution and temporal variation characteristics of aerosol in Guangdong, Hong Kong and Macao, and to explore the optical properties of atmospheric aerosols and their effects on climate, the present study used the daily products of MODIS C61 AOD 3 km from 2010 to 2019 to analyze the spatial distribution of aerosol optical depth(AOD) in Guangdong, Hong Kong and Macao and the characteristics of its annual, seasonal and monthly variation. The results showed that: (1) The optimal fitting coefficient of MODIS AOD and AERONET CE318 AOD was 0.96, that of Solarsim-D2 AOD was 0.62, and that of PM_2.5 and PM₁₀ mass concentrations were 0.58 and 0.56, respectively.(2)Spatially, the AOD value of the Pearl River Delta was the highest, followed by that of western Guangdong, and the values of northern Guangdong and northeastern Guangdong were the lowest.(3)Annual variation showed a clear downward trend. The fluctuation of AOD increased from 2010 to 2014 and reached its peak in 2014. After 2015, AOD decreased significantly and bottomed out in 2016.(4) The seasonal pattern was as follows: spring(AOD: 0.66) > summer(AOD: 0.53) > autumn(AOD: 0.44) > winter(AOD: 0.41).(5) The characteristics of monthly variation were that the AOD value in March was the largest(AOD: 0.73), followed by that in April. It remained high and fluctuated steadily from May to August, and decreased significantly from September to December. The results showed that Foshan, Guangzhou, other Pearl River Delta cities and western Guangdong are the key areas for the prevention and control of particulate matter pollution in Guangdong, Hong Kong and Macao, and the emphasis should be the control of production intensity and particulate matter emissions of high pollution enterprises in spring and summer.
- Guangdong /
- Hong Kong and Macao /
- MODIS /
- aerosol optical depth /
- spatio-temporal distribution

HTML全文

图 1 太阳光度计与国控环境监测站分布图

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图 2 MODIS AOD与太阳光度计AOD线性拟合关系图

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图 3 MODIS AOD与PM_2.5、PM₁₀质量浓度间的关系

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图 4 粤港澳地区MODIS AOD分布图

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图 5 粤港澳地区MODIS AOD年均值变化趋势图

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图 6 2010—2019年粤港澳地区MODIS AOD年均值分布图

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图 7 粤港澳地区MODIS AOD季均值变化图

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图 8 粤港澳地区MODIS AOD月均值变化图

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参考文献(39)

[1]	王娜, 张镭, 邓涛, 等. 一次浮尘过程气溶胶光学特性及其辐射效应的研究[J]. 热带气象学报, 2013, 29(3): 458-464. doi: 10.3969/j.issn.1004-4965.2013.03.012
[2]	宿兴涛, 王汉杰, 周林. 中国有机碳气溶胶时空分布与辐射强迫的模拟研究[J]. 热带气象学报, 2010, 26(6): 765-772. doi: 10.3969/j.issn.1004-4965.2010.06.016
[3]	LIU Z, YIM S H L, WANG C, et al. The impact of the aerosol direct radiative forcing on deep convection and air quality in the Pearl River delta region[J]. Geophy Res Lett, 2018, 45(9): 4 410-4 418. doi: 10.1029/2018GL077517
[4]	沈新勇, 黄文彦, 陈宏波. 气溶胶对东亚夏季风指数和爆发的影响及其机理分析[J]. 热带气象学报, 2015, 31(6): 733-743. https://rdqxxb.itmm.org.cn/article/id/20150602
[5]	邓洁淳, 徐海明, 马红云, 等. 中国东部地区人为气溶胶对东亚冬、夏季风的影响——一个高分辨率大气环流模式的模拟研究[J]. 热带气象学报, 2014, 30(3): 567-576. doi: 10.3969/j.issn.1004-4965.2014.03.018
[6]	王勇, 吉振明, 沈新勇, 等. 人为气溶胶对东亚夏季风直接气候效应的成因分析[J]. 热带气象学报, 2013, 29(3): 441-448. doi: 10.3969/j.issn.1004-4965.2013.03.010
[7]	陈思宇, 黄建平, 付强, 等. 气溶胶对我国中东部地区秋季降水的影响[J]. 热带气象学报, 2012, 28(3): 339-347. doi: 10.3969/j.issn.1004-4965.2012.03.006
[8]	SCOTT C E, ARNOLD S R, MONKS S A, et al. Substantial large-scale feedbacks between natural aerosols and climate[J]. Nature Geoscience. 2018, 11(1): 44-48. doi: 10.1038/s41561-017-0020-5
[9]	PÖSCHL U. Atmospheric aerosols: composition, transformation, climate and health effects[J]. Angewandte Chemie International Edition. 2006, 44(46): 7 520-7 540. http://www.onacademic.com/detail/journal_1000033757832210_1232.html
[10]	罗栩羽, 夏冬, 高斯, 等. 云凝结核浓度对不同强度南海热带气旋强度影响的个例模拟研究[J]. 热带气象学报, 2020, 36(4): 518-527. doi: 10.16032/j.issn.1004-4965.2020.048
[11]	尚晶晶, 廖宏, 符瑜, 等. 夏季硫酸盐和黑碳气溶胶对中国云特性的影响[J]. 热带气象学报, 2017, 33(4): 451-466. doi: 10.16032/j.issn.1004-4965.2017.04.003
[12]	CHRISTOPHER S A. Satellite remote sensing methods for estimating clear Sky shortwave Top of atmosphere fluxes used for aerosol studies over the global oceans[J]. Remote Sensing of Environment, 2011, 115(12): 3 002-3 006. doi: 10.1016/j.rse.2011.06.003
[13]	STEVENS B. Rethinking the lower bound on aerosol radiative forcing[J]. J Climate. 2015, 28(12): 4 794-4 819. doi: 10.1175/JCLI-D-14-00656.1
[14]	SEINFELD J H, BRETHERTON C, CARSLAW K S, et al. Improving our fundamental understanding of the role of aerosol-cloud interactions in the climate system[J]. Proceedings of the National Academy of ences of the United States of America. 2016, 113(21): 5 781-5 790. http://escholarship.org/uc/item/9zh399j3.pdf
[15]	SHINDELL D, KUYLENSTIERNA J C I, VIGNATI E, et al. Simultaneously Mitigating Near-Term Climate Change and Improving Human Health and Food Security[J]. Science, 2012, 335(6 065): 183-189.
[16]	DI Q, KLOOG I, KOUTRAKIS P, et al. Assessing PM_2.5exposures with high spatiotemporal resolution across the continental United States[J]. Environmental Science & amp; Technology, 2016, 50(9): 4 712-4 721.
[17]	SAM H, JENNIFER B, ERAN B, et al. Robust relationship between air quality and infant mortality in Africa[J]. Nature, 2018, 559(7713): 254-258. doi: 10.1038/s41586-018-0263-3
[18]	孟清, 白红英, 赵婷, 等. 秦岭地区气溶胶光学厚度的时空演变特征及其影响因子[J]. 生态环境学报, 2019, 28(8): 1 596-1 603. https://www.cnki.com.cn/Article/CJFDTOTAL-TRYJ201908012.htm
[19]	张颖蕾, 崔希民. 基于MODIS C061的长三角地区AOD与Angstrom指数时空变化分析[J]. 环境科学, 2020, 41(6): 2 617-2 624. https://www.cnki.com.cn/Article/CJFDTOTAL-HJKZ202006014.htm
[20]	牛林芝, 王旭红, 韩海青, 等. 中亚五国气溶胶光学厚度时空分布特征研究[J]. 环境科学学报, 2020, 40(12): 1-13. https://www.cnki.com.cn/Article/CJFDTOTAL-HJXX202102002.htm
[21]	张亮林, 潘竟虎, 张大弘. 基于MODIS数据的中国气溶胶光学厚度时空分布特征[J]. 环境科学学报, 2018, 38(11): 4 431-4 439. https://www.cnki.com.cn/Article/CJFDTOTAL-HJXX201811025.htm
[22]	郭婉臻, 张飞, 夏楠, 等. 近十年中国陆地AOD时空分布及与城市化的关系研究[J]. 环境科学学报, 2019, 39(7): 2 339-2 352. https://www.cnki.com.cn/Article/CJFDTOTAL-HJXX201907029.htm
[23]	刘海知, 郭海燕, 马振峰, 等. 2001-2017年全国气溶胶光学厚度时空分布及变化趋势[J]. 环境科学, 2019, 40(9): 3 886-3 897. https://www.cnki.com.cn/Article/CJFDTOTAL-HJKZ201909005.htm
[24]	王银牌, 喻鑫, 谢广奇. 中国近15年气溶胶光学厚度时空分布特征[J]. 中国环境科学. 2018, 38(2): 426-434. doi: 10.3969/j.issn.1000-6923.2018.02.004
[25]	HE Q, ZHANG M, HUANG B, et al. MODIS 3 km and 10 km aerosol optical depth for China: Evaluation and comparison[J]. Atmos Envir, 2017, 153(1): 150-162.
[26]	张颖蕾, 崔希民. 京津冀地区MODIS 3 km气溶胶光学厚度产品与10 km产品的对比分析[J]. 环境科学学报, 2020, 40(2): 429-437. https://www.cnki.com.cn/Article/CJFDTOTAL-HJXX202002007.htm
[27]	REMER L A, MATTOO S, LEVY R C, et al. MODIS 3 km aerosol product: algorithm and global perspective[J]. Atmospheric Measurement Techniques. 2013, 6(7): 1 829-1 844. doi: 10.5194/amt-6-1829-2013
[28]	何沐全, 刘志红, 张颖, 等. 川南城市群大气灰霾时空分布特征及成因分析[J]. 中国环境科学, 2017, 37(2): 432-442. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGHJ201702005.htm
[29]	林楚勇, 邓玉娇, 徐剑波, 等. 基于MODIS的广东省气溶胶光学厚度时空分布特征分析[J]. 热带气象学报, 2015, 31(6): 821-826. https://rdqxxb.itmm.org.cn/article/id/20150610
[30]	游积平, 高建秋, 黄梦宇, 等. 珠江三角洲地区大气气溶胶特征的飞机观测分析[J]. 热带气象学报, 2015, 31(1): 71-77. https://rdqxxb.itmm.org.cn/article/id/20150108
[31]	刘艳群, 张骥, 庞古乾, 等. 2001―2018年广东省气溶胶参数的时空变化特征[J]. 广东海洋大学学报, 2020, 40(6): 1-12. doi: 10.3969/j.issn.1673-9159.2020.06.001
[32]	KONG L, HU M, TAN Q, et al. Aerosol optical properties under different pollution levels in the Pearl River Delta(PRD)region of China[J]. J Envir Sci, 2020, 87(1): 49-59. http://www.cnki.com.cn/Article/CJFDTotal-HJKB202001005.htm
[33]	KUANG Q, WANG Y P. Spatial-temporal characteristics of the aerosol optical depth(aod)derived from longterm(1980-2018)MERRA-2 over Guangdong[J]. ISPAr, 2019, XLII-3/W9(42): 103-108.
[34]	黄健, 李菲, 邓雪娇, 等. 珠江三角洲城市地区MODIS气溶胶光学厚度产品的检验分析[J]. 热带气象学报, 2010, 26(5): 526-531. doi: 10.3969/j.issn.1004-4965.2010.05.003
[35]	王捷纯, 邓玉娇. 利用MODIS C6产品分析广东省气溶胶光学厚度时空特征[J]. 气象科技, 2018, 46(4): 809-813. https://www.cnki.com.cn/Article/CJFDTOTAL-QXKJ201804025.htm
[36]	张磊, 江洪, 陈诚, 等. 广东省MODIS气溶胶光学厚度时空分布及其影响因素[J]. 地理空间信息, 2017, 15(1): 46-49. doi: 10.3969/j.issn.1672-4623.2017.01.014
[37]	邓玉娇, 胡猛, 林楚勇, 等. 基于FY3A/MERSI资料分析广东省气溶胶光学厚度分布[J]. 气象, 2016, 42(1): 61-66. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXX201601007.htm
[38]	范萌, 张胜敏, 陈良富, 等. 珠三角地区长时间序列气溶胶时空变化特征分析[J]. 遥感学报, 2016, 20(6): 1413-1423. https://www.cnki.com.cn/Article/CJFDTOTAL-YGXB201606011.htm
[39]	REMER L A, KAUFMAN Y J, TANRÉD, et al. The MODIS aerosol algorithm, products, and validation[J]. J Atmos Sci, 2005, 62(4): 947-973. doi: 10.1175/JAS3385.1