利用河北省2017~2018年逐日PM_(2.5)浓度地面观测数据和CUACE空气质量模式的PM_(2.5)气象条件评估指数(EMI,evaluation on meteorological condition index of PM_(2.5) pollution),定量评估了2018年相比2017年河北省冬季气象条件对PM_(...利用河北省2017~2018年逐日PM_(2.5)浓度地面观测数据和CUACE空气质量模式的PM_(2.5)气象条件评估指数(EMI,evaluation on meteorological condition index of PM_(2.5) pollution),定量评估了2018年相比2017年河北省冬季气象条件对PM_(2.5)浓度的贡献,并分析了石家庄市气象条件和PM_(2.5)浓度的同期月变化。结果表明:与2017年相比,2018年冬季河北省气象条件不利于PM_(2.5)浓度的下降,其中,北部、西北部地区气象条件极为不利,使PM_(2.5)浓度同比上升28%~45%,不同城市的气象条件变化存在显著差异;2018年石家庄市PM_(2.5)年均浓度同比下降12.7%,其中气象条件使PM_(2.5)浓度同比下降3.1%,说明石家庄市大气污染防治减排措施对PM_(2.5)浓度下降贡献显著。可见,EMI指数可定量诊断和评估污染期间气象条件对PM_(2.5)浓度的影响。展开更多
In this paper, five national meteorological stations in Anhui province are taken as typical examples to explore the effects of local urbanization on their thermal environment by using Landsat data from 1990 to 2010. S...In this paper, five national meteorological stations in Anhui province are taken as typical examples to explore the effects of local urbanization on their thermal environment by using Landsat data from 1990 to 2010. Satellite-based land use/land cover(LULC), land surface temperature(LST), normalized difference vegetation index(NDVI) are used to investigate the effects. The study shows that LULC around meteorological stations changed significantly due to urban expansion. Fast urbanization is the main factor that affects the spatial-temporal distribution of thermal environment around meteorological stations. Moreover, the normalized LST and NDVI exhibit strong inverse correlations around meteorological stations, so the variability of LST can be monitored through evaluating the variability of NDVI. In addition, station-relocation plays an important role in improving representativeness of thermal environment. Notably, the environment representativeness was improved, but when using the data from the station to study climate change, the relocation-induced inhomogeneous data should be considered and adjusted. Consequently,controlling the scale and layout of the urban buildings and constructions around meteorological stations is an effective method to ameliorate observational thermal environment and to improve regional representativeness of station observation. The present work provides observational evidences that high resolution Landsat images can be used to evaluate the thermal environment of meteorological stations.展开更多
文摘利用河北省2017~2018年逐日PM_(2.5)浓度地面观测数据和CUACE空气质量模式的PM_(2.5)气象条件评估指数(EMI,evaluation on meteorological condition index of PM_(2.5) pollution),定量评估了2018年相比2017年河北省冬季气象条件对PM_(2.5)浓度的贡献,并分析了石家庄市气象条件和PM_(2.5)浓度的同期月变化。结果表明:与2017年相比,2018年冬季河北省气象条件不利于PM_(2.5)浓度的下降,其中,北部、西北部地区气象条件极为不利,使PM_(2.5)浓度同比上升28%~45%,不同城市的气象条件变化存在显著差异;2018年石家庄市PM_(2.5)年均浓度同比下降12.7%,其中气象条件使PM_(2.5)浓度同比下降3.1%,说明石家庄市大气污染防治减排措施对PM_(2.5)浓度下降贡献显著。可见,EMI指数可定量诊断和评估污染期间气象条件对PM_(2.5)浓度的影响。
基金supported by the National Natural Science Foundation of China(41205126 and 41475085)Anhui Provincial Natural Science Foundation(1408085MKL60 and1508085MD64)Meteorological Research Fund of Anhui Meteorological Bureau(KM201520)
文摘In this paper, five national meteorological stations in Anhui province are taken as typical examples to explore the effects of local urbanization on their thermal environment by using Landsat data from 1990 to 2010. Satellite-based land use/land cover(LULC), land surface temperature(LST), normalized difference vegetation index(NDVI) are used to investigate the effects. The study shows that LULC around meteorological stations changed significantly due to urban expansion. Fast urbanization is the main factor that affects the spatial-temporal distribution of thermal environment around meteorological stations. Moreover, the normalized LST and NDVI exhibit strong inverse correlations around meteorological stations, so the variability of LST can be monitored through evaluating the variability of NDVI. In addition, station-relocation plays an important role in improving representativeness of thermal environment. Notably, the environment representativeness was improved, but when using the data from the station to study climate change, the relocation-induced inhomogeneous data should be considered and adjusted. Consequently,controlling the scale and layout of the urban buildings and constructions around meteorological stations is an effective method to ameliorate observational thermal environment and to improve regional representativeness of station observation. The present work provides observational evidences that high resolution Landsat images can be used to evaluate the thermal environment of meteorological stations.
