TY - JOUR
T1 - Monitoring temporal–spatial variations of AOD over the Yangtze River Delta, China
AU - Wang, Xiyuan
AU - Guo, Zhongyang
AU - Wang, Yuanyuan
AU - Chen, Yihui
AU - Zheng, Xuman
AU - Xu, Xiaoning
N1 - Publisher Copyright:
© 2018, Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2018/9/1
Y1 - 2018/9/1
N2 - Aerosol can induce visibility reduction, affect radiation balance and modify cloud property on the environmental effect, and show the harmful effects on human health. Insight of aerosol becomes an integral task in the process of control measures for environmental pollution. The present study provided an analysis of temporal–spatial variations of aerosol optical depth (AOD) using the MOD04 level-2 in collection 6 (C6) with the deep blue retrieval algorithm from January 2005 to December 2015 over Yangtze River Delta (YRD) in China. The AOD validations between MODIS and Aerosol Robotic Network (AERONET) were estimated by the methods of regression, correlation. Then, the periodic features and trends of AOD and angstrom exponent (AE) were explored with the wavelet transformation (WT) procedure. Further, the variations of AOD and AE spatial distribution on multi-time scales (annual, monthly and season) were demonstrated. Meantime, the sources of AOD are discussed. It was found that the daily AOD from MODIS has a strong correlation relationship (slope = 0.9838, r = 0.84) with AERONET over YRD. The variations of both AOD and AE on time series have been distinct temporal periodic (12, 6 and 4 months) characteristics, and show the decreasing trends on annual and semi-annual periods. On annual, the AOD on spatial distribution is slowly declining from the northwest towards the southeast, and the AE on spatial distribution is gradually decreasing from the northwest to the southeast and from the land to the coast. The variations both inter-annual AOD and AE on spatial distribution show the inverse trends, respectively. On monthly, the means of AOD range from minimum 0.46 in January to maximum 0.90 in July, and the variations of spatial distribution mainly occur in the north parts of Yangtze River and some scattered areas with high terrain and south coast. The means of AE range from minimum 1.13 in October to maximum 1.58 in April, and the variations of spatial distribution are mainly found in the south of Henan, the north of Jiangsu, the coast belt and the riverside of Yangtze River and the high terrain regions. On seasonality, the means of AOD reaches its maximum 0.68 in summer and minimum 0.50 in winter, and the variations of spatial distribution mainly occur in the coast belt, the north parts of Hongze Lake and the south parts with high terrain. The means of AE reaches its maximum 1.48 in spring and minimum 1.25 in autumn, and the variations of spatial distribution were shown the similarity with that of monthly.
AB - Aerosol can induce visibility reduction, affect radiation balance and modify cloud property on the environmental effect, and show the harmful effects on human health. Insight of aerosol becomes an integral task in the process of control measures for environmental pollution. The present study provided an analysis of temporal–spatial variations of aerosol optical depth (AOD) using the MOD04 level-2 in collection 6 (C6) with the deep blue retrieval algorithm from January 2005 to December 2015 over Yangtze River Delta (YRD) in China. The AOD validations between MODIS and Aerosol Robotic Network (AERONET) were estimated by the methods of regression, correlation. Then, the periodic features and trends of AOD and angstrom exponent (AE) were explored with the wavelet transformation (WT) procedure. Further, the variations of AOD and AE spatial distribution on multi-time scales (annual, monthly and season) were demonstrated. Meantime, the sources of AOD are discussed. It was found that the daily AOD from MODIS has a strong correlation relationship (slope = 0.9838, r = 0.84) with AERONET over YRD. The variations of both AOD and AE on time series have been distinct temporal periodic (12, 6 and 4 months) characteristics, and show the decreasing trends on annual and semi-annual periods. On annual, the AOD on spatial distribution is slowly declining from the northwest towards the southeast, and the AE on spatial distribution is gradually decreasing from the northwest to the southeast and from the land to the coast. The variations both inter-annual AOD and AE on spatial distribution show the inverse trends, respectively. On monthly, the means of AOD range from minimum 0.46 in January to maximum 0.90 in July, and the variations of spatial distribution mainly occur in the north parts of Yangtze River and some scattered areas with high terrain and south coast. The means of AE range from minimum 1.13 in October to maximum 1.58 in April, and the variations of spatial distribution are mainly found in the south of Henan, the north of Jiangsu, the coast belt and the riverside of Yangtze River and the high terrain regions. On seasonality, the means of AOD reaches its maximum 0.68 in summer and minimum 0.50 in winter, and the variations of spatial distribution mainly occur in the coast belt, the north parts of Hongze Lake and the south parts with high terrain. The means of AE reaches its maximum 1.48 in spring and minimum 1.25 in autumn, and the variations of spatial distribution were shown the similarity with that of monthly.
KW - AE
KW - AOD
KW - Multi-time scale
KW - Trends
KW - Variations
UR - https://www.scopus.com/pages/publications/85049583392
U2 - 10.1007/s00477-018-1575-4
DO - 10.1007/s00477-018-1575-4
M3 - 文章
AN - SCOPUS:85049583392
SN - 1436-3240
VL - 32
SP - 2619
EP - 2632
JO - Stochastic Environmental Research and Risk Assessment
JF - Stochastic Environmental Research and Risk Assessment
IS - 9
ER -