In order to assess the effect of meteorological conditions on air pollution quantitatively and predict the air pollution potential, the Atmospheric Self-cleaning ability Index (ASI) was defined based on the prediction principle of city air pollution prediction system (CAPPS). Both computational methods of ASI using observational data of meteorological stations and the meso-scale modelling result were introduced. The analysis of ASI in China showed that the lowest ASI was located in Sichuan Basin and Talimu Basin in Xinjiang, and the highest ASI was located in Plateau, island and peninsula areas. The decrease of ASI and the increase of the low ASI days of a year were found in regions of Jing-Jin-Ji, Yangtze River Delta and Pearl River Delta from 1961 to 2017. The effect evaluation of air pollution prevention and control during the Beijing APEC conference using ASI showed that the AQI in Beijing decreased by 77% and the mean AQI of 11cities in Jing-Jin-Ji Plain decreased by 37% because of the emission reduction while the worst air pollution meteorological condition happened in 8th~10th Nov. 2014. An air pollution potential prediction system on extended and monthly scales, which can predict nationwide daily ASI of 40 days in advance, was set up based on the combination of the production of the extended and monthly dynamical climate model (DERF2.0) and the downscaling of WRF model. The historical simulation experiment showed that the system could forecast the process of heavy air pollution events 15days in advance in most cases, and the forecast accuracy depended on the extended and monthly dynamical climate model (DERF2.0) to a considerable extent.
朱蓉, 张存杰, 梅梅. 大气自净能力指数的气候特征与应用研究[J]. 中国环境科学, 2018, 38(10): 3601-3610.
ZHU Rong, ZHANG Cun-jie, MEI Mei. The climate characteristics of atmospheric self-cleaning ability index and its application in China. CHINA ENVIRONMENTAL SCIENCECE, 2018, 38(10): 3601-3610.
He J, Gong S, Yu Y, et al. Air pollution characteristics and their relation to meteorological conditions during 2014~2015 in major Chinese cities[J]. Environmental Pollution, 2017,223:484-496.
[2]
Li L, Qian J, Ou C Q, et al. Spatial and temporal analysis of Air Pollution Index and its timescale-dependent relationship with meteorological factors in Guangzhou, China, 2001~2011[J]. Environmental Pollution, 2014,190:75-81.
[3]
Zhang H, Wang Y, Hu J, et al. Relationships between meteorological parameters and criteria air pollutants in three megacities in China[J]. Environmental Research, 2015,140:242-254.
Pearce J L, Beringer J, Nicholls N, et al. Investigating the influence of synoptic-scale meteorology on air quality using self-organizing maps and generalized additive modelling[J]. Atmospheric Environment, 2011,45:128-136.
[7]
Chen D L. A monthly circulation climatology for Sweden and its application to a winter temperature case study[J]. International Journal of Climatology, 2000,20:1067-1076.
[8]
Grundstrom M, Tang L, Hallquist M, et al. Influence of atmospheric circulation patterns on urban air quality during the winter[J]. Atmospheric Pollution Research, 2015,6:278-285.
[9]
Grundstrom M, Hak C, Chen D, et al. Variation and co-variation of PM10, particle number concentration, NOx and NO2 in the urban air-relationships with wind speed, vertical temperature gradient and weather type[J]. Atmospheric Environment, 2015,120:317-327.
[10]
Tang L, Chen D., Karlsson P E, et al. Synoptic circulation and its influence on spring and summer surface ozone concentrations in southern Sweden[J]. Boreal Environ. Res., 2009,14:889-902.
Ashrafi K, Shafie-Pour, M, Kamalan H. Estimating Temporal and Seasinal Variation of Ventilation Coefficients[J]. Int. J. Environ Res., 2009,3(4):637-644.
[16]
Maria I G, Nicolás A M. Air Pollution Potential:Regional Study in Argentina[J]. Environmental Management, 2000,25(4):375-382.
[17]
Praveena K, Kunhikrishnan P K. Temporal variations of ventilation coefficient at a tropical Indian station using UHF wind profiler[J]. Current Science, 2004,86(3):447-451.
Wang J Z, Gong S L, Zhang X Y, et al. A Parameterized Method for Air-Quality Diagnosis and Its Applications[J]. Advances in Meteorology. 2012, doi:10.1155/2012/238589.
