[论文解读] The relationships between PM2.5 and AOD in China: About and behind spatiotemporal variations

Qianqian Yang, Qiangqiang Yuan+4 more|arXiv (Cornell University)|Aug 17, 2018

Air Quality and Health Impacts参考文献 40被引用 7

一句话总结

本研究利用相关性分析和地理加权回归（GWR）方法，对中国368座城市2013至2017年期间PM2.5与气溶胶光学厚度（AOD）之间的时空关系进行了调查。研究发现，PM2.5-AOD关系在不同地区和季节间存在显著差异，且随时间推移相关性与反演精度持续下降，表明AOD在未来空气质量监测中可能逐渐失去作为PM2.5可靠代理指标的能力。

ABSTRACT

Satellite aerosol products have been widely used to retrieve ground PM2.5 concentration because of its wide coverage and continuously spatial distribution. While more and more studies focus on the retrieval algorithm, we find that the relationship between PM2.5 concentration and satellite AOD has not been fully discussed in China. Is satellite AOD always a good indicator for PM2.5 in different regions and can AOD still be employed to retrieve PM2.5 with pollution conditions changing in these years remain unclear. In this study, the relationships between PM2.5 and AOD were investigated in 368 cities in China for a continuous period from February 2013 to December 2017, at different time and regional scales. Pearson correlation coefficients and PM2.5/AOD ratio were used as the indicator. Firstly, we concluded the relationship of PM2.5 and AOD in terms of spatiotemporal variations. Then the impact of meteorological factors, aerosol size and topography were discussed. Finally, a GWR retrieval experiment was conducted to find out how was the retrieval accuracy changing with the varying of PM2.5-AOD relationship. We found that spatially the correlation is higher in Beijing-Tianjin-Hebei and Chengyu region and weaker in coastal areas such as Yangtze River Delta and Pearl River Delta. The PM2.5/AOD ratio has obvious North-South difference with a high ratio in north China and a lower ratio in south China. Temporally, PM2.5/AOD ratio is higher in winter and lower in summer, the correlation coefficient tends to be higher in May and September. As for interannual variations from 2013 to 2017, we detected a declining tendency on PM2.5/AOD ratio. The accuracy of GWR retrievals were decreasing too, which may imply that AOD may not be a good indicator for PM2.5 in the future.

研究动机与目标

• 评估中国范围内PM2.5与AOD关系的时空变异特征。
• 识别PM2.5-AOD相关性及PM2.5/AOD比值在不同区域和季节中的模式。
• 评估气象条件、气溶胶粒径分布及地形对PM2.5-AOD关系的影响。
• 考察PM2.5-AOD关系变化对GWR方法反演PM2.5精度随时间的影响。

提出的方法

• 计算了中国368座城市每日PM2.5与AOD之间的皮尔逊相关系数，以量化其线性关系。
• 计算PM2.5/AOD比值，作为区域范围内细颗粒物对气溶胶负荷相对贡献的指标。
• 分析了不同区域（如京津冀、长江三角洲）及季节间相关性与比值的空间与时间变异。
• 分析了气象因素（如相对湿度、风速）、气溶胶粒径分布及地形特征作为PM2.5-AOD变异潜在驱动因素的影响。
• 应用地理加权回归（GWR）方法从AOD反演PM2.5，并评估模型随时间的精度。
• 分析了PM2.5/AOD比值与GWR反演误差的年际趋势，以评估AOD作为PM2.5代理指标的长期可靠性。

实验结果

研究问题

• RQ1 PM2.5与AOD的相关性在中国不同区域的空间分布如何变化？
• RQ2 北方与南方中国PM2.5/AOD比值有何差异，其差异的驱动因素是什么？
• RQ3 季节性变化如何影响PM2.5-AOD关系，特别是在冬季与夏季之间？
• RQ4 2013至2017年间，PM2.5-AOD关系的年际变化在多大程度上影响了基于AOD的PM2.5反演精度？
• RQ5 气象条件、气溶胶粒径及地形在调节PM2.5-AOD关系中发挥何种作用？

主要发现

• PM2.5-AOD相关性在京津冀和成渝地区最强，而沿海地区（如长江三角洲和珠江三角洲）的相关性较低。
• 北方中国PM2.5/AOD比值显著高于南方中国，表明北方地区细颗粒物对AOD的贡献更大。
• PM2.5/AOD比值在冬季达到峰值，夏季则下降，且相关系数在5月和9月最高。
• 2013至2017年间检测到PM2.5/AOD比值呈下降趋势，表明AOD与PM2.5之间的关系随时间减弱。
• GWR反演精度在研究期间呈下降趋势，表明随着PM2.5-AOD关系的演变，AOD正逐渐失去作为PM2.5可靠指示物的能力。