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2005—2014年中三角城市群大气污染特征及变化趋势 被引量:20

Air pollution characteristic and variation trend of Central Triangle urban agglomeration from 2005 to 2014
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摘要 通过对中三角2005—2014年的可吸入颗粒物(PM_(10))逐日浓度数据进行分析,从空间尺度和时间尺度2个角度出发,以武汉、长沙、南昌等6个城市为代表研究了中三角城市群近10年大气污染特征及变化趋势。结果表明:各城市10年中均有75%以上天数达到国家空气质量二级标准,武汉、长沙、常德为中3角城市群污染较重的3个城市。PM_(10)浓度最高的月份为1月、12月,7月最低,10月有一个小高峰;季节分布上冬季最大,春秋次之,夏季最小;年际变化上,2005—2012年,总体上有显著的变小趋势,2013年PM_(10)浓度异常升高,各城市较2012年均有较大的上升幅度,2014年PM_(10)回落。国内4大城市群大气污染程度排序为京津冀>中三角>长三角>珠三角,中三角大气污染问题要比长三角和珠三角突出,应加强对中三角大气污染成因及控制措施的研究。 To investigate the air pollution characteristics and variation trends of the Central Triangle urban ag- glomeration, PM10 concentrations from 2005 to 2014 for seven typical cities were analyzed. The data were derived from the data set of Wuhan et al. The results showed that at least 75% of the days in each city reached the sec- ondary standard detailed in GB 3095-2012. Wuhan, Changsha, and Changde were the top three polluted cities. The highest levels of PM10 occurred in January and February, whereas the lowest levels occurred in July. A small peak in concentrations was detected in October. On a seasonal basis, winter was found to be the most polluted season followed by spring and autumn, and summer was found to be the least polluted season. The PM10 concen- trations decreased from 2005 to 2012, but sudden increases were apparent in 2013. Afterward, the levels de- creased again in 2014. The order of ambient air pollution in terms of degree for the four large city groups was as follows: Beijing-Tianjin-Hebei (more serious) 〉 Central Triangle urban agglomeration 〉 Yangtze River Delta 〉 Pearl River Delta (less serious). Clearly, additional research on air pollution causative factors and control strategies in the Central Triangle urban agglomeration is of great importance.
出处 《环境工程学报》 CAS CSCD 北大核心 2017年第5期2977-2984,共8页 Chinese Journal of Environmental Engineering
基金 中国环境科学研究院院所科研专项(2013YSKY-05)
关键词 中三角城市群 可吸入颗粒物(PM10) 统计分析 Daniel趋势分析 Central Triangle urban agglomeration PM10 statistical analysis Daniel trend analysis
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