北京市2012-2013年秋冬季大气颗粒物污染特征分析

大气颗粒物一直是影响我国城市空气质量的重要污染物,2013年1月北京市的严重灰霾污染更是带来了重大的健康危害和经济损失。为了摸清北京市颗粒物污染的特征,本文利用北京市实时发布的颗粒物污染监测数据,选取污染最为严重的2012-2013年秋冬季时段,对颗粒物的达标情况、变化趋势及其与气象因子相关性等方面进行研究。研究结果表明：1）2012年,北京市年均ρ（PM10）为109.0μg.m-3,超过了新国标二级标准限值,日均ρ（PM10）的超标天数为84天,全年超标天数比例为23.0%。2）2012年10月至2013年2月,ρ（PM10）达标天数比例为77.9%,ρ（PM2.5）的达标天数比例为51.9%。各月ρ（PM2.5）的达标天数比例均低于ρ（PM10）,某些月份二者达标天数比例差异很大。3）ρ（PM2.5）与ρ（PM10）的逐小时连续变化趋势基本相同,变化特征为＂快速积累,迅速消散,持续时间不定＂。ρ（PM2.5）与ρ（PM10）平均值24 h的变化呈双峰双谷曲线,颗粒物质量浓度夜间高于白天。4）研究期日均ρ（PM10）和ρ（PM2.5）与日均相对湿度呈显著正相关关系,与平均风速和最大风速呈显著负相关关系,ρ（PM2.5）比ρ（PM10）更易受气象条件变化影响。5）ρ（PM10）和ρ（PM2.5）日均值有着非常显著的线性相关关系。本研究得出的ρ（PM2.5）/ρ（PM10）的均值高于之前北京市及我国其他城市研究得出的数值,严重污染现象是由特殊的气象背景条件与污染物高排放共同导致的。

Analysis of characteristics of atmospheric particulate matter pollution in Beijing during the fall and winter of 2012 to 2013

Atmospheric particulate matter is an important constituent of atmosphere pollution in China. Serious ash haze pollution has brought significant health risks and economic losses in Beijing. This paper investigates the characteristics of particulate matter pollution in Beijing by utilizing real-time data obtained during the fall and winter of 2012 to 2013, and by studying the levels of particulate matter, its trends of variation, and its correlation with meteorological factors. The research has highlighted some significant results. 1） In 2012, the annual average ρ（PM10） reached 109.0μg.m-3and failed to meet new Grade II national air quality standards. There were 84 days when the levels of ρ（PM10） failed to meet new Grade II standards, accounting for 23% of the year. 2）From October 2012 to February 2013, the percentage of days during which the levels of ρ（PM10） and ρ（PM2.5） met new Grade II standards were 77.9% and 51.9%, respectively. The percentage of days during which the levels of ρ（PM2.5） met new Grade II standards for each month of the research period was lower than that for ρ（PM10）, and in some months it exhibited large differences. 3）The hourly trends of change of ρ（PM2.5） and ρ（PM10） were similar and could be described as accumulating fast and dissipating faster with an uncertain duration. The 24-hour mean values of the trends of change of ρ（PM2.5） and ρ（PM10） levels showed double peaks and double valleys, and that the concentration of particulate matter at nighttime was higher than that during the day. 4） The daily average values of ρ（PM2.5） and ρ（PM10） had significant positive correlation with relative humidity and significant negative correlation with both the daily average and the maximum wind speed. The level of ρ（PM2.5） was more likely to be affected by changes in weather conditions than was the level of ρ（PM10）. 5） There was very significant linear correlation between the daily average levels of ρ（PM2.5） and ρ（PM10）. The ρ（PM2.5）/ρ（PM10） value in our study is higher than that recorded in previous studies for Beijing and other cities in China. This serious phenomenon of particulate pollution is caused by specific background meteorological conditions and high emissions of pollutants.