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本底站和城区站CO浓度变化特征和源贡献
引用本文:程巳阳,安兴琴,周凌晞,程兴宏. 本底站和城区站CO浓度变化特征和源贡献[J]. 中国环境科学, 2016, 36(10): 2930-2937
作者姓名:程巳阳  安兴琴  周凌晞  程兴宏
作者单位:中国气象科学研究院, 灾害天气国家重点实验室和中国气象局大气化学重点开放实验室, 北京 100081
基金项目:国家自然科学基金项目(41505123);国家国际科技合作专项(2015DFG21960,2011DFA21090);中国气象科学研究院基本科研业务费专项(2015Y002);中国气象局气候变化专项(CCSF201431)
摘    要:
采用FLEXPART大气扩散模式结合清单的模拟方法,通过与2010年上甸子大气本底站和城区海淀宝联站的CO观测浓度的比较,研究了北京地区CO浓度变化特征,并统计分析了各类排放源的贡献差异.研究结果表明:上甸子站和宝联站CO模拟浓度与观测浓度的变化趋势基本一致,相关系数分别优于0.74和0.45;与观测值相比,两站模拟浓度值偏低,模式对观测浓度峰值模拟能力有限.利用不同源清单模拟获得的同一站点CO浓度值相近,但交通、工业、民用等分类排放源对CO模拟浓度的贡献差异明显.与INTEX-B2006清单相比,利用MEIC2010排放清单模拟的宝联站交通与工业排放贡献的占比小、民用排放占比大;而上甸子站交通排放贡献的占比小,民用与工业排放的贡献占比大.因此,利用FLEXPART模式结合清单的模拟方法对CO浓度具有较好的模拟能力,可以较为准确地反映区域大气本底站和城区站CO浓度的变化特征;各类排放源对模拟浓度的贡献不仅受到测站所在地的局地排放源影响,更与影响测站的印痕区域的排放源密切相关.

关 键 词:数值模拟  一氧化碳  排放清单  印痕  
收稿时间:2016-02-15

Variation characteristic and source contribution of CO concentration at the background and urban station
CHENG Si-yang,AN Xing-qin,ZHOU Ling-xi,CHENG Xing-hong. Variation characteristic and source contribution of CO concentration at the background and urban station[J]. China Environmental Science, 2016, 36(10): 2930-2937
Authors:CHENG Si-yang  AN Xing-qin  ZHOU Ling-xi  CHENG Xing-hong
Affiliation:State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of China Metevological Administration, Chinese Academy of Meteorological Sciences, Beijing 100081, China
Abstract:
The simulation method, combining FLEXPART atmospheric diffusion model with emission inventory, has been used to study variation characteristic of CO concentration in Beijing by comparing with CO observation concentrations at Shangdianzi (SDZ) atmospheric background station and Baolian (BL) urban station in 2010. Also, source emission contribution discrepancy of CO concentration was studied with statistical analysis. The variations of simulated CO concentrations were similar to observed values at SDZ and BL, where the correlation coefficients of concentrations were greater than 0.76 and 0.52 between simulation and observation respectively. Compared with observed CO concentrations, simulated values were lower. Observed CO peaks were limited by the capacity of simulation. Using different source emissions for the same site, the simulated CO concentrations were similar, but the contributions of specific classifications (transportation, industry, resident and power) were distinctly different. Using emission inventory MEIC2010compared with emission inventory INTEX-B2006, the contribution ratios of transportation and industry were less and the contribution ratio of resident was greater at BL, and the contribution ratio of transportation was less and the contribution ratios of resident and industry were greater at SDZ. Therefore, the simulated method, combining FLEXPART model with emission inventory, was effective to CO concentration simulation, and variation characteristics of CO concentrations could be obtained at regional atmospheric background station and urban station. The contributions of emission sources were not only affected by local emissions but also determined by source emissions in the footprint area of measurement station.
Keywords:numerical simulation  carbon monoxide  emission inventory  footprint  
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