Based on the data of six automatic air monitoring stations in Bengbu City,the pollution characteristics and temporal distribution of fine particulate matter PM 2.5 in the air in Bengbu City from 2015 to 2019 were stud...Based on the data of six automatic air monitoring stations in Bengbu City,the pollution characteristics and temporal distribution of fine particulate matter PM 2.5 in the air in Bengbu City from 2015 to 2019 were studied,and the correlation between meteorological factors and PM 2.5 concentration was analyzed.The results showed that from 2015 to 2019,PM 2.5 pollution in Bengbu City was relatively heavy in winter and spring and relatively light in summer and autumn,and PM 2.5 concentration had two peaks during the day and night.Precipitation,relative humidity,wind direction and wind speed had certain effects on PM 2.5 concentration in Bengbu City.The research provides reference for the monitoring,early warning and prevention of PM 2.5 pollution in the city.展开更多
In this paper, the spatial, temporal distribution, transformation and source simulation of NO3- were analyzed systematically based on the monitoring data, literature review and numerical simulation （ CMAQ4.7.1 ）. An...In this paper, the spatial, temporal distribution, transformation and source simulation of NO3- were analyzed systematically based on the monitoring data, literature review and numerical simulation （ CMAQ4.7.1 ）. Analysis results showed that annual average concentration of NO3- in Beijing was between 6.69 and 12.48 μg/m3 with an increasing trend in recent years; concentration of NO3- in Beijing in 2013 was higher in winter and autumn than that in spring and summer and diurnal variation of NO3- showed bimedal distribution and spatial distribution of NO3- showed significant north-south gradient distribution; annual average NOR in Beijing was between 0.12 and 0.17 while it was between 0.17 and 0.20 during heavy air pollution days in 2013; the average ratio of NO3-/SO42- was between 0.97 and 1.06 while it was between 1.00 and 1.07 during heavy air pollution days in 2013; the emission sources of Beijing was being changed from fixed source to both fixed and moving sources in feature development; simulated local, external transportation, background and boundary condition were 40%, 44% and 16% respectively to the annual average concentration of NO3- in Beijing in 2013 while they were 31%, 57% and 12% respectively in heavy air pollution days, which indicated that extemal source played an important role to the concentration of NO3- in Beijing. Key words NO3- ; Spatial and temporal distribution; Source; PM2.5; Beijing; CAMx展开更多
With the rapid development of China's economy,people's demand for a healthy living environment is increasing,and air quality has gradually been widely concerned by all sectors of society.Using the big data of ...With the rapid development of China's economy,people's demand for a healthy living environment is increasing,and air quality has gradually been widely concerned by all sectors of society.Using the big data of air quality monitoring from 1998 to 2016,based on the exploratory spatio-temporal analysis method,this paper explored the spatio-temporal evolution of PM_(2.5) at the national scale,and drew the following conclusions:①PM_(2.5) heavy pollution is mainly in central and eastern China,north and south China,and the pollution degree is relatively light in northwest and northeast China.Meanwhile,PM_(2.5) concentration in heavily polluted areas increased significantly over time,while PM_(2.5) concentration in low-polluted areas showed a long-term stable trend.②The number and area of cities with moderate and high PM_(2.5) pollution levels showed an inverted U-shaped curve from 1998 to 2016,and 2007 was the inflection point.③The spatial autocorrelation coefficient of PM_(2.5) is high over the years,and the spatial neighbor effect of PM_(2.5) is significant.The high-pollution clusters are mainly concentrated in the Beijing-Tianjin-Hebei region,the Yangtze River Delta and the Pearl River Delta,and the pollution concentration in these three regions has increased rapidly in recent years.It is necessary to focus on joint prevention and control.展开更多
文摘Based on the data of six automatic air monitoring stations in Bengbu City,the pollution characteristics and temporal distribution of fine particulate matter PM 2.5 in the air in Bengbu City from 2015 to 2019 were studied,and the correlation between meteorological factors and PM 2.5 concentration was analyzed.The results showed that from 2015 to 2019,PM 2.5 pollution in Bengbu City was relatively heavy in winter and spring and relatively light in summer and autumn,and PM 2.5 concentration had two peaks during the day and night.Precipitation,relative humidity,wind direction and wind speed had certain effects on PM 2.5 concentration in Bengbu City.The research provides reference for the monitoring,early warning and prevention of PM 2.5 pollution in the city.
文摘In this paper, the spatial, temporal distribution, transformation and source simulation of NO3- were analyzed systematically based on the monitoring data, literature review and numerical simulation （ CMAQ4.7.1 ）. Analysis results showed that annual average concentration of NO3- in Beijing was between 6.69 and 12.48 μg/m3 with an increasing trend in recent years; concentration of NO3- in Beijing in 2013 was higher in winter and autumn than that in spring and summer and diurnal variation of NO3- showed bimedal distribution and spatial distribution of NO3- showed significant north-south gradient distribution; annual average NOR in Beijing was between 0.12 and 0.17 while it was between 0.17 and 0.20 during heavy air pollution days in 2013; the average ratio of NO3-/SO42- was between 0.97 and 1.06 while it was between 1.00 and 1.07 during heavy air pollution days in 2013; the emission sources of Beijing was being changed from fixed source to both fixed and moving sources in feature development; simulated local, external transportation, background and boundary condition were 40%, 44% and 16% respectively to the annual average concentration of NO3- in Beijing in 2013 while they were 31%, 57% and 12% respectively in heavy air pollution days, which indicated that extemal source played an important role to the concentration of NO3- in Beijing. Key words NO3- ; Spatial and temporal distribution; Source; PM2.5; Beijing; CAMx
基金Supported by the National Natural Science Foundation of China(51808413)General Project of Hubei Social Science Fund(Later Funded Project)(2020158)Innovation and Entrepreneurship Training Program for College Students in Hubei Province(S202010490027)。
文摘With the rapid development of China's economy,people's demand for a healthy living environment is increasing,and air quality has gradually been widely concerned by all sectors of society.Using the big data of air quality monitoring from 1998 to 2016,based on the exploratory spatio-temporal analysis method,this paper explored the spatio-temporal evolution of PM_(2.5) at the national scale,and drew the following conclusions:①PM_(2.5) heavy pollution is mainly in central and eastern China,north and south China,and the pollution degree is relatively light in northwest and northeast China.Meanwhile,PM_(2.5) concentration in heavily polluted areas increased significantly over time,while PM_(2.5) concentration in low-polluted areas showed a long-term stable trend.②The number and area of cities with moderate and high PM_(2.5) pollution levels showed an inverted U-shaped curve from 1998 to 2016,and 2007 was the inflection point.③The spatial autocorrelation coefficient of PM_(2.5) is high over the years,and the spatial neighbor effect of PM_(2.5) is significant.The high-pollution clusters are mainly concentrated in the Beijing-Tianjin-Hebei region,the Yangtze River Delta and the Pearl River Delta,and the pollution concentration in these three regions has increased rapidly in recent years.It is necessary to focus on joint prevention and control.
