In this study, regional persistent haze events(RPHEs) in the Beijing–Tianjin–Hebei(BTH) region were identified based on the Objective Identification Technique for Regional Extreme Events for the period 1980–201...In this study, regional persistent haze events(RPHEs) in the Beijing–Tianjin–Hebei(BTH) region were identified based on the Objective Identification Technique for Regional Extreme Events for the period 1980–2013. The formation mechanisms of the severe RPHEs were investigated with focus on the atmospheric circulation and dynamic mechanisms. Results indicated that:(1) 49 RPHEs occurred during the past 34 years.(2) The severe RPHEs could be categorized into two types according to the large-scale circulation, i.e. the zonal westerly airflow(ZWA) type and the high-pressure ridge(HPR) type. When the ZWA-type RPHEs occurred, the BTH region was controlled by near zonal westerly airflow in the mid–upper troposphere.Southwesterly winds prevailed in the lower troposphere, and near-surface wind speeds were only 1–2 ms^-1. Warm and humid air originating from the northwestern Pacific was transported into the region, where the relative humidity was 70% to 80%, creating favorable moisture conditions. When the HPR-type RPHEs appeared, northwesterly airflow in the mid–upper troposphere controlled the region. Westerly winds prevailed in the lower troposphere and the moisture conditions were relatively weak.(3) Descending motion in the mid-lower troposphere caused by the above two circulation types provided a crucial dynamic mechanism for the formation of the two types of RPHEs. The descending motion contributed to a reduction in the height of the planetary boundary layer(PBL), which generated an inversion in the lower troposphere. This inversion trapped the abundant pollution and moisture in the lower PBL, leading to high concentrations of pollutants.展开更多
[ Objective] The research aimed to analyze a local snowstorm weather process which happened in Beijing, Tianjin and Hebei during I - 4 January, 2010. [ Method] Based on routine meteorological observation data and NCEP...[ Objective] The research aimed to analyze a local snowstorm weather process which happened in Beijing, Tianjin and Hebei during I - 4 January, 2010. [ Method] Based on routine meteorological observation data and NCEP/NCAR 2.5° ×2.5° grid data (four times every day), a lo- cal snowstorm weather process which happened in Beijing, Tianjin and Hebei during 1 -4 January, 2010 was carried out diagnostic analysis by using composite analysis method. [Result] Circumfluence on the ground and strong cold advection in the rear of upper trough were the main weath- er system of the snowfall. The deep thick wet layer and strong water vapor convergence provided sufficient water vapor for snowfall. The divergence field of low-level convergence and high^level divergence, dynamic coupling effect of vorticity provided favorable dynamic condition upwardly for the occurrence of strong snowfall. The steep dense area of Oso, low temperature at the ground layer and inversion temperature at the high layer provided certain energy condition for the development of snowfall weather. [ Conclusion] The research provided theoretical basis for snowfall forecast in future.展开更多
Beijing–Tianjin–Hebei(BTH)and its surrounding areas are very important to air pollution control in China.To analyze the characteristics of BTH and its surrounding areas of China,we collected 5,641,440 air quality da...Beijing–Tianjin–Hebei(BTH)and its surrounding areas are very important to air pollution control in China.To analyze the characteristics of BTH and its surrounding areas of China,we collected 5,641,440 air quality data from 161 air monitoring stations and 37,123,000 continuous monitoring data from air polluting enterprises in BTH and surrounding cities to establish an indicator system for urban air quality portraits.The results showed that particulate matter with aerodynamic diameters of<2.5μm(PM2.5),particulate matter with aerodynamic diameters of<10μm(PM10)and SO2 improved significantly in 31 cities from2015 to 2018,but ozone deteriorated.Air quality in BTH and the surrounding areas showed obvious seasonal characteristics,among which PM2.5,PM10,SO2,and NO2 showed a"U"type distribution from January to December,while O3 had an"inverted U"distribution.The hourly changes in air quality revealed that peaks of PM2.5,PM10 and NO2 appeared from 8:00 to 10:00,while those for O3 appeared at 15:00–16:00.The exposure characteristics of the 31 cities showed that six districts in Beijing had the highest air quality population exposure,and that exposure levels in Zhengzhou,Puyang,Anyang,Jincheng were higher than the average of the 31 investigated cities.Additionally,multiple linear regression revealed a negative correlation between meteorological factors(especially wind and precipitation)and air quality,while a positive correlation existed between industrial pollution emissions and air quality in most of BTH and its surrounding cities.展开更多
In 2013,China issued "Air Pollution Prevention and Control Action Plan(Action Plan)" to improve air quality.To assess the benefits of this program in Beijing-Tianjin-Hebei(BTH)region,where the density of populat...In 2013,China issued "Air Pollution Prevention and Control Action Plan(Action Plan)" to improve air quality.To assess the benefits of this program in Beijing-Tianjin-Hebei(BTH)region,where the density of population and emissions vary greatly,we simulated the air quality benefit based on Ben MAP to satisfy the Action Plan.In this study,we estimate PM_(2.5) concentration using Voronoi spatial interpolation method on a grid with a spatial resolution of 1 × 1 km^2.Combined with the exposure-response function between PM_(2.5) concentration and health endpoints,health effects of PM_(2.5) exposure are analyzed.The economic loss is assessed by using the willingness to pay(WTP) method and human capital(HC) method.When the PM_(2.5) concentration falls by 25% in BTH and reached 60 μg/m^3 in Beijing,the avoiding deaths will be in the range of 3175 to 14051 based on different functions each year.Of the estimated mortality attributable to all causes,3117 annual deaths were due to lung cancer,1924 – 6318 annual deaths were due to cardiovascular,and343 – 1697 annual deaths were due to respiratory.Based on WTP,the estimated monetary values for the avoided cases of all cause mortality,cardiovascular mortality,respiratory mortality and lung cancer ranged from 1110 to 29632,673 to 13325,120 to 3579,1091 to 6574 million yuan,respectively.Based on HC,the corresponding values for the avoided cases of these four mortalities were 267 to 1178,161 to 529,29 to 143 and 261 million yuan,respectively.展开更多
Beijing–Tianjin–Hebei area is suffering from atmospheric pollution from a long time. The understanding of the air pollution mechanism is of great importance for officials to design strategies for the environmental g...Beijing–Tianjin–Hebei area is suffering from atmospheric pollution from a long time. The understanding of the air pollution mechanism is of great importance for officials to design strategies for the environmental governance. Mixing layer height(MLH) is a key factor influencing the diffusion of air pollutants. It plays an important role on the evolution of heavy pollution events. Light detection and ranging(lidar), is an effective remote-sensing tool, which can retrieve high spatial and temporal evolution process within mixing layer(ML), especially the variation of MLH. There are many methods to retrieve MLH, but each method has its own applicable limitations. The Mie-lidar data in Beijing was firstly used to compare three different algorithms which are widely used under different pollution levels.We find that the multi-layer structure near surface may cause errors in the detection of mixing layer. The MLH retrieved based on image edge detection was better than another two methods especially under heavy polluted episode. Then we applied this method to investigate the evolution of the mixing layer height during a pollution episode in December2016. MLH at Gucheng county showed the positive correlation with the concentration of particulate matters during the start of this pollution episode. The elevated pollution level in Gucheng was not associated with MLH's decrease, and the significantly increased particulate matters raised the boundary layer, which trapped the pollutants near the surface.展开更多
Environmental stress is used as an indicator of the overall pressure on regional environmental systems caused by the output of various pollutants as a result of human activities. Based on the pollutant emissions and s...Environmental stress is used as an indicator of the overall pressure on regional environmental systems caused by the output of various pollutants as a result of human activities. Based on the pollutant emissions and socioeconomic databases of the counties in Beijing–Tianjin–Hebei region, this paper comprehensively calculates the environmental stress index(ESI) for the urban agglomeration using the entropy weight method(EWM) at the county scale and analyzes the spatiotemporal patterns and the differences among the four types of major functional zones(MFZ) for the period 2012–2016. In addition, the socioeconomic driving forces of environmental stress are quantitatively estimated using the geographically weighted regression(GWR) method based on the STIRPAT model framework. The results show that:(1) The level of environmental stress in the Beijing–Tianjin–Hebei region was significantly alleviated during that time period, with a decrease in ESI of 54.68% by 2016. This decrease was most significant in Beijing, Tangshan, Tianjin, Shijiazhuang, and other central urban areas, as well as the Binhai New Area. The level of environmental stress in counties decreased gradually from the central urban areas to the suburban areas, and the high-level stress counties were eliminated by 2016.(2) The spatial spillover effect of environmental stress increased further at the county scale from 2012 to 2016, and spatial locking and path dependence emerged in the cities of Tangshan and Tianjin.(3) Urbanized zones(development-optimized and development-prioritized zones) were the major areas bearing environmental pollution in the Beijing–Tianjin–Hebei region in that time period. The ESI accounted for 65.98% of the whole region, where there was a need to focus on the prevention and control of environmental pollution.(4) The driving factors of environmental stress at the county scale included population size and the level of economic development. In addition, the technical capacity of environmental waste disposal, the intensity of agricultural production input, the intensity of territorial development, and the level of urbanization also had a certain degree of influence.(5) There was spatial heterogeneity in the effects of the various driving factors on the level of environmental stress. Thus, it was necessary to adopt differentiated environmental governance and reduction countermeasures in respect of emission sources, according to the intensity and spatiotemporal differences in the driving forces in order to improve the accuracy and adaptability of environmental collaborative control in the Beijing–Tianjin–Hebei region.展开更多
基金jointly sponsored by the National Basic Research Program of China(973 Program)(Grant No.2013CB430202)the National Natural Science Foundation of China(Grant No.41401056)+1 种基金the China Meteorological Administration Special Public Welfare Research Fund(Grant No.GYHY201406001)the Research Innovation Program for College Graduates of Jiangsu Province(Grant No.KYLX15 0858)
文摘In this study, regional persistent haze events(RPHEs) in the Beijing–Tianjin–Hebei(BTH) region were identified based on the Objective Identification Technique for Regional Extreme Events for the period 1980–2013. The formation mechanisms of the severe RPHEs were investigated with focus on the atmospheric circulation and dynamic mechanisms. Results indicated that:(1) 49 RPHEs occurred during the past 34 years.(2) The severe RPHEs could be categorized into two types according to the large-scale circulation, i.e. the zonal westerly airflow(ZWA) type and the high-pressure ridge(HPR) type. When the ZWA-type RPHEs occurred, the BTH region was controlled by near zonal westerly airflow in the mid–upper troposphere.Southwesterly winds prevailed in the lower troposphere, and near-surface wind speeds were only 1–2 ms^-1. Warm and humid air originating from the northwestern Pacific was transported into the region, where the relative humidity was 70% to 80%, creating favorable moisture conditions. When the HPR-type RPHEs appeared, northwesterly airflow in the mid–upper troposphere controlled the region. Westerly winds prevailed in the lower troposphere and the moisture conditions were relatively weak.(3) Descending motion in the mid-lower troposphere caused by the above two circulation types provided a crucial dynamic mechanism for the formation of the two types of RPHEs. The descending motion contributed to a reduction in the height of the planetary boundary layer(PBL), which generated an inversion in the lower troposphere. This inversion trapped the abundant pollution and moisture in the lower PBL, leading to high concentrations of pollutants.
文摘[ Objective] The research aimed to analyze a local snowstorm weather process which happened in Beijing, Tianjin and Hebei during I - 4 January, 2010. [ Method] Based on routine meteorological observation data and NCEP/NCAR 2.5° ×2.5° grid data (four times every day), a lo- cal snowstorm weather process which happened in Beijing, Tianjin and Hebei during 1 -4 January, 2010 was carried out diagnostic analysis by using composite analysis method. [Result] Circumfluence on the ground and strong cold advection in the rear of upper trough were the main weath- er system of the snowfall. The deep thick wet layer and strong water vapor convergence provided sufficient water vapor for snowfall. The divergence field of low-level convergence and high^level divergence, dynamic coupling effect of vorticity provided favorable dynamic condition upwardly for the occurrence of strong snowfall. The steep dense area of Oso, low temperature at the ground layer and inversion temperature at the high layer provided certain energy condition for the development of snowfall weather. [ Conclusion] The research provided theoretical basis for snowfall forecast in future.
基金supported by the Humanities and Social Sciences Project Youth Fund of Ministry of Education in China(No.18YJCZH196)the National Natural Science Foundation of China(No.71573149)
文摘Beijing–Tianjin–Hebei(BTH)and its surrounding areas are very important to air pollution control in China.To analyze the characteristics of BTH and its surrounding areas of China,we collected 5,641,440 air quality data from 161 air monitoring stations and 37,123,000 continuous monitoring data from air polluting enterprises in BTH and surrounding cities to establish an indicator system for urban air quality portraits.The results showed that particulate matter with aerodynamic diameters of<2.5μm(PM2.5),particulate matter with aerodynamic diameters of<10μm(PM10)and SO2 improved significantly in 31 cities from2015 to 2018,but ozone deteriorated.Air quality in BTH and the surrounding areas showed obvious seasonal characteristics,among which PM2.5,PM10,SO2,and NO2 showed a"U"type distribution from January to December,while O3 had an"inverted U"distribution.The hourly changes in air quality revealed that peaks of PM2.5,PM10 and NO2 appeared from 8:00 to 10:00,while those for O3 appeared at 15:00–16:00.The exposure characteristics of the 31 cities showed that six districts in Beijing had the highest air quality population exposure,and that exposure levels in Zhengzhou,Puyang,Anyang,Jincheng were higher than the average of the 31 investigated cities.Additionally,multiple linear regression revealed a negative correlation between meteorological factors(especially wind and precipitation)and air quality,while a positive correlation existed between industrial pollution emissions and air quality in most of BTH and its surrounding cities.
基金supported by the National Key Research and Development Program(No.2016YFC0201700)the Natural Science Fund of Tianjin(No.16JCQNJC08600)the Innovation Fund of Tianjin Normal University(No.52XC1501)
文摘In 2013,China issued "Air Pollution Prevention and Control Action Plan(Action Plan)" to improve air quality.To assess the benefits of this program in Beijing-Tianjin-Hebei(BTH)region,where the density of population and emissions vary greatly,we simulated the air quality benefit based on Ben MAP to satisfy the Action Plan.In this study,we estimate PM_(2.5) concentration using Voronoi spatial interpolation method on a grid with a spatial resolution of 1 × 1 km^2.Combined with the exposure-response function between PM_(2.5) concentration and health endpoints,health effects of PM_(2.5) exposure are analyzed.The economic loss is assessed by using the willingness to pay(WTP) method and human capital(HC) method.When the PM_(2.5) concentration falls by 25% in BTH and reached 60 μg/m^3 in Beijing,the avoiding deaths will be in the range of 3175 to 14051 based on different functions each year.Of the estimated mortality attributable to all causes,3117 annual deaths were due to lung cancer,1924 – 6318 annual deaths were due to cardiovascular,and343 – 1697 annual deaths were due to respiratory.Based on WTP,the estimated monetary values for the avoided cases of all cause mortality,cardiovascular mortality,respiratory mortality and lung cancer ranged from 1110 to 29632,673 to 13325,120 to 3579,1091 to 6574 million yuan,respectively.Based on HC,the corresponding values for the avoided cases of these four mortalities were 267 to 1178,161 to 529,29 to 143 and 261 million yuan,respectively.
基金supported by grants from National Key Research and Development Program of China (Nos. 2016YFC0203302, 2018YFC0213100, 2018YFC0213104)the National Natural Science Foundation of China (Nos. 41722501, 91544212, 51778596, 41575021)the National High-Resolution Earth Observation Project of China under grant of 05Y20A16-9001-15/17-2
文摘Beijing–Tianjin–Hebei area is suffering from atmospheric pollution from a long time. The understanding of the air pollution mechanism is of great importance for officials to design strategies for the environmental governance. Mixing layer height(MLH) is a key factor influencing the diffusion of air pollutants. It plays an important role on the evolution of heavy pollution events. Light detection and ranging(lidar), is an effective remote-sensing tool, which can retrieve high spatial and temporal evolution process within mixing layer(ML), especially the variation of MLH. There are many methods to retrieve MLH, but each method has its own applicable limitations. The Mie-lidar data in Beijing was firstly used to compare three different algorithms which are widely used under different pollution levels.We find that the multi-layer structure near surface may cause errors in the detection of mixing layer. The MLH retrieved based on image edge detection was better than another two methods especially under heavy polluted episode. Then we applied this method to investigate the evolution of the mixing layer height during a pollution episode in December2016. MLH at Gucheng county showed the positive correlation with the concentration of particulate matters during the start of this pollution episode. The elevated pollution level in Gucheng was not associated with MLH's decrease, and the significantly increased particulate matters raised the boundary layer, which trapped the pollutants near the surface.
基金National Natural Science Foundation of China,No.41971164, No.42071148Strategic Priority Research Program of the Chinese Academy of Sciences,Grant No.XDA23020101。
文摘Environmental stress is used as an indicator of the overall pressure on regional environmental systems caused by the output of various pollutants as a result of human activities. Based on the pollutant emissions and socioeconomic databases of the counties in Beijing–Tianjin–Hebei region, this paper comprehensively calculates the environmental stress index(ESI) for the urban agglomeration using the entropy weight method(EWM) at the county scale and analyzes the spatiotemporal patterns and the differences among the four types of major functional zones(MFZ) for the period 2012–2016. In addition, the socioeconomic driving forces of environmental stress are quantitatively estimated using the geographically weighted regression(GWR) method based on the STIRPAT model framework. The results show that:(1) The level of environmental stress in the Beijing–Tianjin–Hebei region was significantly alleviated during that time period, with a decrease in ESI of 54.68% by 2016. This decrease was most significant in Beijing, Tangshan, Tianjin, Shijiazhuang, and other central urban areas, as well as the Binhai New Area. The level of environmental stress in counties decreased gradually from the central urban areas to the suburban areas, and the high-level stress counties were eliminated by 2016.(2) The spatial spillover effect of environmental stress increased further at the county scale from 2012 to 2016, and spatial locking and path dependence emerged in the cities of Tangshan and Tianjin.(3) Urbanized zones(development-optimized and development-prioritized zones) were the major areas bearing environmental pollution in the Beijing–Tianjin–Hebei region in that time period. The ESI accounted for 65.98% of the whole region, where there was a need to focus on the prevention and control of environmental pollution.(4) The driving factors of environmental stress at the county scale included population size and the level of economic development. In addition, the technical capacity of environmental waste disposal, the intensity of agricultural production input, the intensity of territorial development, and the level of urbanization also had a certain degree of influence.(5) There was spatial heterogeneity in the effects of the various driving factors on the level of environmental stress. Thus, it was necessary to adopt differentiated environmental governance and reduction countermeasures in respect of emission sources, according to the intensity and spatiotemporal differences in the driving forces in order to improve the accuracy and adaptability of environmental collaborative control in the Beijing–Tianjin–Hebei region.