RESOURCES AND ENVIRONMENT IN THE YANGTZE BASIN >> 2016, Vol. 25 >> Issue (05): 813-821.doi: 10.11870/cjlyzyyhj201605015

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SPATIAL-TEMPORAL CHARACTERISTICS OF PM 2.5 IN YANGTZE RIVER DELTA (YRD) REGION BASED ON THE GROUND MONITORING DATA FROM 2013-2015

DAI Zhao-xin1,2, ZHANG Yun-zhi1,3, HU Yun-feng1, DONG Yu1,2   

  1. 1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China;
    3. Inner Mongolia Normal University, Hohehot Municipality 010022, China
  • Received:2015-09-10 Revised:2015-12-29 Online:2016-05-20
  • Supported by:
    National Science and Technology Major Project of the Ministry of Science and Technology of China;The Monitor and Evaluation Application System of the National PrincipalFunction Region Based on High Resolution Remote Sensing(a)(00-Y30B14-9001-14/16)

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Abstract: As one of the three economic hubs in China, the Yangtze River Delta (YRD) experiences serious air pollution due to the huge energy consumption in recent years. The air pollution in this region became more and more serious with increasingly frequent haze. The main pollution source is respirable particulate matters (PM2.5). Based on this, data of PM2.5 from 214 automatic air quality monitoring stations of YRD and surrounding buffer regions from January 2013 to May 2015 were analyzed to examine the temporal and spatial characteristics of PM2.5 at year, season, month scales. Using Ordinary Kriging interpolation method, we found that (1) The distribution of PM2.5 concentration was obvious in the YRD region and displayed high values in the north and low values in the south. The annual average concentrations of PM2.5 was 57.08 μg·m-3 in the YRD region. From a regional perspective, the annual average concentrations of PM2.5 in different sub-regions decreased in the order of Jiangsu province, Shanghai Municipality and Zhejiang province, which were 65.84μg·m-3, 47.31μg·m-3 and 51.53 μg·m-3, respectively. The average concentrations of PM2.5 in this three regions all exceeded the national ambient air quality standard of 35 μg·m-3. The main reason may be related with the regional industrial structure, regional agricultural pollution, meteorological characteristics and etc. (2) The average concentration of PM2.5 in different seasons decreased in the order of winter, spring, autumn and summer, which were 82.73 μg/m-3,54.02 μg/m-3, 49.71 μg/m-3 and 41.72 μg/m-3, respectively. The main reasons caused the obvious differences in seasons were the atmosphere conditions (air mass source, precipitation, etc.), human activities and the condition of natural ecosystems. For example, in winter more stable atmosphere, high frequency and intensity temperature inversion were not conducive to pollution dilution. But in summer more plants grow and flourish, this was conducive to the adsorption of particulate matter in the atmosphere; secondly, the precipitation increase in summer can also conducive to the wet deposition and dilution of atmospheric pollutants; therefore, the concentration of PM2.5 was the lowest in summer relatively.(3) Monthly average concentrations of PM2.5 showed a U-shaped curve; the peaks of which appeared in December; after March, the average concentration of PM2.5 showed a gradual decline; In 5-9 months, the average concentration of PM2.5 in the bottom of U-shaped curve and reached to the minimum in September; but in June, the average concentration of PM2.5 concentrations increased slightly because of the straw burning; in October the average concentrations of PM2.5 rose rapidly and continued to rise in November and December. In this study, the result based on the method of GIS spatial interpolation may cause a few errors; the achievements based on the space statistical method may not represent the real phenomenon completely. But overall, the spatial interpolation method based on GIS provided the way to understand the spatial distribution characteristics of regional PM2.5; the spatial statistical method based on GIS provided the basic data and material science for the discrimination of regional PM2.5 concentration level. This paper has important practical significance for the remote sensing of atmospheric pollutants, product validation and local governments to carry out environment management decision-making and so on.

Key words: the concentrations of PM2.5, ground monitoring, spacedistribution, temporal dynamics, Yangtze River Delta region

CLC Number: 

  • X513
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