| Inhalable particulate matter was the primary pollutant of China's air quality.In recent years,with the rapid growth of motor vehicle ownership in the city,particulate emissions caused by traffic activity had become a city of air pollution.It was one of the important sources of particulate pollution in traffic microenvironment.Based on the data of 8 environmental monitoring stations of Putian,this paper used GIS to interpolate the data of 8 monitoring stations,and analyze the spatial distribution of particulate matter concentration.Taking the typical road sections of different road greening models as the research object,the particulate matter,meteorological parameters and traffic volume in these roadside environment were monitored.On the basis of this,the paper compared the road environmental pollution under different traffic patterns and different traffic conditions to find the law of road environmental pollution under different traffic conditions,and provided a scientific basis for exploring a better road greening model The The main findings are as follows:(1)The annual concentration of PM10 and PM2.5 in spring and winter were significantly higher than those in summer and autumn.The pollution of the granules in the monitoring area of Licheng District was the most serious.The concentration of particulate matter in the monitoring area of Dongcheng Reservoir was the lowest.The areas where away from urban areas,greening and vegetation coverage,and adjacent areas of the waters shoued low concentration of particulate matter.There was a strong negative correlation between wind speed and PM10 concentration,and there was a negative correlation with PM2.5 concentration.There was a significant negative correlation between temperature and PM10?PM2.5 concentration.The relative was negatively correlated between humidity and PM10?PM2.5 correlation.(2)This paper attempted to use the different models of particulate matter emission factors,reversed the calculation of the proportion of traffic flow calculation,found that the emission factor based on the standardized traffic flow and particle concentration of the better correlation;Traffic flow showed better correlation with PM2.5 concentration,and poor correlation with the concentration of PM1,PM10 and TSP.The time distribution of vehicle flow and particle concentration was analyzed and It was found that the change of the concentration of the particles had a certain delay relative to the traffic volume due to the time required for the diffusion of the particles;According to the traffic volume and the prosperity degree of the monitoring station,the eight air automatic monitoring sub-stations were divided into three categories,The main features of the more serious areas were where traffic developed and human activities are frequent;The PM10 and TSP concentrations showed:main road>secondary road>branch;and PM,and PM2.5 concentration showed a secondary trunk of road>main,road>slip road;There were significant differences between the urban holidays and the daily changes in the concentration of particulate matter in Putian,while the traffic flow decreased significantly on the holidays,with an average decrease of 13.44%.The concentration of particulate matter was also significantly reduced,especially PM10 and TSP,respectively,reaching 35.36%and 39.09%,showing a significant "holiday effect".(3)The road-side greening zone of the "Tree-Irrigation-Grass"arrangement pattern had the highest reducing effect on the each particle size particle;PM,and PM2.5 were from similar pollution source,while PM10 and TSP came from another similar one;The reduction rate of the different size particle was different:TSP>PM10>PM2.5>PM1.The reduction rate of PM10 and TSP reached 44.9%and 43.7%in the "Tree-Irrigation-Grass" model,and the greening zone on the road side had better blocking and adsorption effect on the larger particle size.While the the purification effect of small particle was poor. |
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