基于典型城市气象参数的建筑通风用新风所含污染物统计分析*
Statistical analysis of pollutants in outdoor air system for building ventilation based on typical urban meteorological parameters
摘要：
选取我国5个气候分区的12个典型城市，用SPSS软件统计分析了2012—2017年PM2.5，PM10，SO2，NO2及温度和相对湿度的分布特征，以及各气象要素之间的关联性。结果表明：PM2.5，PM10，SO2，NO2日均浓度的变化趋势呈现冬高夏低，年内单峰型、年间双峰型正弦分布的规律，且温湿度变化趋势与空气污染物质量浓度相似；雾霾综合污染指数F存在地区差异性，季节性特征明显且冬季峰值最大；空气污染物的主成分为PM2.5和PM10（累计贡献率大于90%），PM2.5和PM10与温度和相对湿度的线性相关性明显（相关系数大于0.5），SO2和NO2与温度和相对湿度的线性相关性不明显（相关系数小于0.3）；用考虑温湿度的优化后的雾霾综合污染指数分析空气污染因素时，方差数值小，数值离散程度小，分析结果更精确。
Abstract：
Selects twelve typical cities in China’s five climate zones, and statistically analyses the distribution characteristics of PM2.5, PM10, SO2, NO2, temperature and relative humidity and the correlation among meteorological elements from 2012 to 2017 using SPSS software. The results show the variation trend of daily average concentration of PM2.5, PM10, SO2, NO2 higher in winter and lower in summer, single peak within a year and double peaks with sinusoidal distribution law in the period of years. The variation trend of temperature and relative humidity is similar to that of mass concentration of air pollutants. The fog and haze index (F) has regional differences, obvious seasonal characteristics and the highest peak in winter. The principal components of air pollutants are PM2.5 and PM10 (cumulative contribution rate is more than 90%). PM2.5 and PM10 have obvious linear correlations with temperature and relative humidity (correlation coefficient is greater than 0.5), while SO2 and NO2 have no obvious linear correlations with temperature and relative humidity (correlation coefficient is less than 0.3). When the optimal F considering temperature and humidity is introduced to analyse air pollution factors, the variance value and the numerical dispersion degree are smaller, the degree of numerical dispersion is small, and the analysis result is more accurate.
Keywords:urban meteorological parameter, air pollutant, distribution characteristic, fog and haze index, principal component analysis