A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Spatio-temporal distribution of localized aerosol loading in China: A satellite view
https://orcid.org/0000-0002-8718-0045
AbstractIn recent years, haze pollution and high concentrations of particulate matter frequently occur in many mega cities of China, which has seriously impacted the regional air quality, and further caused harm to human health. Although satellite observation provides a convenient way to evaluate air quality in space and time, satellite measurements do not separate between natural and anthropogenic aerosols. To discriminate anthropogenic aerosol contribution from satellite observations, we proposed the concept of Local Aerosol Optical Depth (LAOD) to describe the localized aerosol loading. A comparative analysis was performed between seasonal/monthly Mean AOD (MAOD), LAOD and ground measured PM2.5/PM10. The comparison results show that LAOD has better linear relationship with PM2.5/PM10 than MAOD in central and eastern China with persistent localized aerosol emissions. Based on the MODIS Deep Blue AOD dataset from 2001 to 2015, we analyzed the spatio-temporal distribution of LAOD over China. Spatially, high LAODs are mainly distributed in Sichuan basin, North China Plain, and central China; temporally, LAOD over China presents an upward trend (+0.003 year−1) during 2001–2007 and a weak downward (−0.002 year−1) trend from 2008 to 2015. LAOD was also found to be highly correlated with haze frequency over most areas of central and eastern China, especially in North China Plain with a correlation coefficient of 0.87 (P < 0.01). It demonstrates the significant impact of local anthropogenic aerosol emission on regional haze pollution in China.
HighlightsLocal Aerosol Optical Depth (LAOD) is proposed to evaluate the anthropogenic aerosol emissions over urban areas in China.LAOD shows a better relationship with ground PM2.5 measurements than mean AOD.Local aerosol emissions have significant impact on regional haze pollution in China.
Spatio-temporal distribution of localized aerosol loading in China: A satellite view
https://orcid.org/0000-0002-8718-0045
AbstractIn recent years, haze pollution and high concentrations of particulate matter frequently occur in many mega cities of China, which has seriously impacted the regional air quality, and further caused harm to human health. Although satellite observation provides a convenient way to evaluate air quality in space and time, satellite measurements do not separate between natural and anthropogenic aerosols. To discriminate anthropogenic aerosol contribution from satellite observations, we proposed the concept of Local Aerosol Optical Depth (LAOD) to describe the localized aerosol loading. A comparative analysis was performed between seasonal/monthly Mean AOD (MAOD), LAOD and ground measured PM2.5/PM10. The comparison results show that LAOD has better linear relationship with PM2.5/PM10 than MAOD in central and eastern China with persistent localized aerosol emissions. Based on the MODIS Deep Blue AOD dataset from 2001 to 2015, we analyzed the spatio-temporal distribution of LAOD over China. Spatially, high LAODs are mainly distributed in Sichuan basin, North China Plain, and central China; temporally, LAOD over China presents an upward trend (+0.003 year−1) during 2001–2007 and a weak downward (−0.002 year−1) trend from 2008 to 2015. LAOD was also found to be highly correlated with haze frequency over most areas of central and eastern China, especially in North China Plain with a correlation coefficient of 0.87 (P < 0.01). It demonstrates the significant impact of local anthropogenic aerosol emission on regional haze pollution in China.
HighlightsLocal Aerosol Optical Depth (LAOD) is proposed to evaluate the anthropogenic aerosol emissions over urban areas in China.LAOD shows a better relationship with ground PM2.5 measurements than mean AOD.Local aerosol emissions have significant impact on regional haze pollution in China.
Spatio-temporal distribution of localized aerosol loading in China: A satellite view
https://orcid.org/0000-0002-8718-0045
AbstractIn recent years, haze pollution and high concentrations of particulate matter frequently occur in many mega cities of China, which has seriously impacted the regional air quality, and further caused harm to human health. Although satellite observation provides a convenient way to evaluate air quality in space and time, satellite measurements do not separate between natural and anthropogenic aerosols. To discriminate anthropogenic aerosol contribution from satellite observations, we proposed the concept of Local Aerosol Optical Depth (LAOD) to describe the localized aerosol loading. A comparative analysis was performed between seasonal/monthly Mean AOD (MAOD), LAOD and ground measured PM2.5/PM10. The comparison results show that LAOD has better linear relationship with PM2.5/PM10 than MAOD in central and eastern China with persistent localized aerosol emissions. Based on the MODIS Deep Blue AOD dataset from 2001 to 2015, we analyzed the spatio-temporal distribution of LAOD over China. Spatially, high LAODs are mainly distributed in Sichuan basin, North China Plain, and central China; temporally, LAOD over China presents an upward trend (+0.003 year−1) during 2001–2007 and a weak downward (−0.002 year−1) trend from 2008 to 2015. LAOD was also found to be highly correlated with haze frequency over most areas of central and eastern China, especially in North China Plain with a correlation coefficient of 0.87 (P < 0.01). It demonstrates the significant impact of local anthropogenic aerosol emission on regional haze pollution in China.
HighlightsLocal Aerosol Optical Depth (LAOD) is proposed to evaluate the anthropogenic aerosol emissions over urban areas in China.LAOD shows a better relationship with ground PM2.5 measurements than mean AOD.Local aerosol emissions have significant impact on regional haze pollution in China.
Spatio-temporal distribution of localized aerosol loading in China: A satellite view
Sun, Kun (author) / Chen, Xiaoling (author)
Atmospheric Environment ; 163 ; 35-43
2017-05-16
9 pages
Article (Journal)
Electronic Resource
English