Trend analysis of atmospheric aerosols enhances confidence in the evaluation of both direct and indirect effects of aerosols on regional climate change. To comprehensively achieve this over East Africa, it’s importan...Trend analysis of atmospheric aerosols enhances confidence in the evaluation of both direct and indirect effects of aerosols on regional climate change. To comprehensively achieve this over East Africa, it’s important to understand aerosols temporal characteristics over well selected sites namely Nairobi (1°S, 36°E), Mbita (0°S, 34°E), Mau Forest (0.0°S - 0.6°S;35.1°E - 35.7°E), Malindi (2°S, 40°E), Mount Kilimanjaro (3°S, 37°E) and Kampala (0°N, 32.1°E). In this context, trend analysis (annual (in Aerosol Optical Depth (AOD) at 550 nm and Ångström Exponent Anomaly (ÅEA) at 470 - 660 nm) and seasonal (AOD)) from Moderate Resolution Imaging Spectroradiometer (MODIS) were performed following the weighted least squares (WLS) fitting method for the period 2000 to 2013. The MODIS AOD annual trends were ground-truthed by AErosol RObotic NETwork (AERONET) data. Tropical Rainfall Measurement Mission (TRMM) was utilized to derive rainfall rates (RR) in order to assess its influence on the observed aerosol temporal characteristics. The derived annual AOD trends utilizing MODIS and AERONET data were consistent with each other. However, monthly AOD and RR were found to be negatively correlated over Nairobi, Mbita, Mau forest complex and Malindi. There was no clear relationship between the two trends over Kampala and Mount Kilimanjaro, which may imply the role of aerosols in cloud modulation and hence RR received. Seasonality is evident between AOD and ÅEA annual trends as these quantities were observed to be modulated by RR. AOD was observed to decrease over East Africa except Nairobi during the study period as a result of RR during the study period. Unlike the other study sites, Nairobi shows positive trends in AOD that may be attributed to increasing populace and fossil fuel, vehicular-industrial emission and biomass and refuse burning during the study period. Negative trends over the rest of the study sites were associated to rain washout. The AOD and ÅEA derived annual trends were found to meet the statistical significance of 95% confidence level over each study site.展开更多
Lidar ratios and AngstrOm exponents of continental,maritime,and desert aerosols were calculated to evaluate the effects of aerosol composition on these parameters.Their correlation was assessed using correlation analy...Lidar ratios and AngstrOm exponents of continental,maritime,and desert aerosols were calculated to evaluate the effects of aerosol composition on these parameters.Their correlation was assessed using correlation analysis and curve fitting.The Pearson correlation coefficient between the lidar ratio and the AngstrOm exponent was larger than 0.95 in all cases.We verified the reliability of the Pearson correlation coefficient using the significance test.The relationship between the lidar ratio and the Angstrom expo- nent of continental aerosol can be described by a cubic polynomial model;thus,the function relation between the change in lidar ratios at different laser wavelengths depends on the fitting coefficients and the AngstrOm exponent.The relationship between the lidar ratio and the AngstrOm exponent of both maritime and desert aerosols can be described by a linear model.In these aerosols,the linear change in lidar ratios at different laser wavelengths remains unaffected by the AngstrOm exponent.The changes in the lidar ratio in maritime aerosol at 355nm and 532nm are -0.7times and -0.18times that at 1064nm, respectively.For desert aerosol,the changes in the lidar ratio at 355nm and 532nm are 0.37 times and 1.88times that at 1064nm,respectively.展开更多
为研究徐州冬季雾-霾天气形成过程中颗粒物粒径及气溶胶光学特性的变化特征,分析了2014年12月1日-2015年2月28日徐州大气颗粒物质量浓度（PM（10）、PM（2.5）、PM1）、数浓度（0-1μm、1-2.5μm、2.5-10μm）和气溶胶光学特性等数据....为研究徐州冬季雾-霾天气形成过程中颗粒物粒径及气溶胶光学特性的变化特征,分析了2014年12月1日-2015年2月28日徐州大气颗粒物质量浓度（PM（10）、PM（2.5）、PM1）、数浓度（0-1μm、1-2.5μm、2.5-10μm）和气溶胶光学特性等数据.结果表明：0-1μm粒径范围细颗粒物的大量增多是引发徐州冬季雾-霾天气的主要因素,徐州冬季地面风速小（静风或轻风天气）,较高的大气相对湿度对雾-霾的形成和维持起着重要影响作用.持续时间较长的雾霾天气,因颗粒物吸湿增长和水汽附着,1-10μm粒径范围大气颗粒物在雾霾时段易发生沉降而减少,后随相对湿度降低雾霾转为短时间的霾天气,1-10μm颗粒物数浓度大幅上升.徐州冬季500nm波段AOD total和AOD fine mode具有相同的变化趋势,雾-霾日AOD total和AOD fine mode显著高于非霾日.AOD fine mode与AOD coarse mode的比值雾-霾日亦明显高于非霾日,而且在雾-霾日Angstrom波长指数主要集中在1-1.6,表明徐州冬季雾-霾时段大气中细颗粒物为主控粒子.展开更多
文摘Trend analysis of atmospheric aerosols enhances confidence in the evaluation of both direct and indirect effects of aerosols on regional climate change. To comprehensively achieve this over East Africa, it’s important to understand aerosols temporal characteristics over well selected sites namely Nairobi (1°S, 36°E), Mbita (0°S, 34°E), Mau Forest (0.0°S - 0.6°S;35.1°E - 35.7°E), Malindi (2°S, 40°E), Mount Kilimanjaro (3°S, 37°E) and Kampala (0°N, 32.1°E). In this context, trend analysis (annual (in Aerosol Optical Depth (AOD) at 550 nm and Ångström Exponent Anomaly (ÅEA) at 470 - 660 nm) and seasonal (AOD)) from Moderate Resolution Imaging Spectroradiometer (MODIS) were performed following the weighted least squares (WLS) fitting method for the period 2000 to 2013. The MODIS AOD annual trends were ground-truthed by AErosol RObotic NETwork (AERONET) data. Tropical Rainfall Measurement Mission (TRMM) was utilized to derive rainfall rates (RR) in order to assess its influence on the observed aerosol temporal characteristics. The derived annual AOD trends utilizing MODIS and AERONET data were consistent with each other. However, monthly AOD and RR were found to be negatively correlated over Nairobi, Mbita, Mau forest complex and Malindi. There was no clear relationship between the two trends over Kampala and Mount Kilimanjaro, which may imply the role of aerosols in cloud modulation and hence RR received. Seasonality is evident between AOD and ÅEA annual trends as these quantities were observed to be modulated by RR. AOD was observed to decrease over East Africa except Nairobi during the study period as a result of RR during the study period. Unlike the other study sites, Nairobi shows positive trends in AOD that may be attributed to increasing populace and fossil fuel, vehicular-industrial emission and biomass and refuse burning during the study period. Negative trends over the rest of the study sites were associated to rain washout. The AOD and ÅEA derived annual trends were found to meet the statistical significance of 95% confidence level over each study site.
基金National Natural Science Foundation of China grants:No.61405158and No.41627807.
文摘Lidar ratios and AngstrOm exponents of continental,maritime,and desert aerosols were calculated to evaluate the effects of aerosol composition on these parameters.Their correlation was assessed using correlation analysis and curve fitting.The Pearson correlation coefficient between the lidar ratio and the AngstrOm exponent was larger than 0.95 in all cases.We verified the reliability of the Pearson correlation coefficient using the significance test.The relationship between the lidar ratio and the Angstrom expo- nent of continental aerosol can be described by a cubic polynomial model;thus,the function relation between the change in lidar ratios at different laser wavelengths depends on the fitting coefficients and the AngstrOm exponent.The relationship between the lidar ratio and the AngstrOm exponent of both maritime and desert aerosols can be described by a linear model.In these aerosols,the linear change in lidar ratios at different laser wavelengths remains unaffected by the AngstrOm exponent.The changes in the lidar ratio in maritime aerosol at 355nm and 532nm are -0.7times and -0.18times that at 1064nm, respectively.For desert aerosol,the changes in the lidar ratio at 355nm and 532nm are 0.37 times and 1.88times that at 1064nm,respectively.
文摘为研究徐州冬季雾-霾天气形成过程中颗粒物粒径及气溶胶光学特性的变化特征,分析了2014年12月1日-2015年2月28日徐州大气颗粒物质量浓度（PM（10）、PM（2.5）、PM1）、数浓度（0-1μm、1-2.5μm、2.5-10μm）和气溶胶光学特性等数据.结果表明：0-1μm粒径范围细颗粒物的大量增多是引发徐州冬季雾-霾天气的主要因素,徐州冬季地面风速小（静风或轻风天气）,较高的大气相对湿度对雾-霾的形成和维持起着重要影响作用.持续时间较长的雾霾天气,因颗粒物吸湿增长和水汽附着,1-10μm粒径范围大气颗粒物在雾霾时段易发生沉降而减少,后随相对湿度降低雾霾转为短时间的霾天气,1-10μm颗粒物数浓度大幅上升.徐州冬季500nm波段AOD total和AOD fine mode具有相同的变化趋势,雾-霾日AOD total和AOD fine mode显著高于非霾日.AOD fine mode与AOD coarse mode的比值雾-霾日亦明显高于非霾日,而且在雾-霾日Angstrom波长指数主要集中在1-1.6,表明徐州冬季雾-霾时段大气中细颗粒物为主控粒子.
