Gupta A K, Nag Subhankar, Mukhopadhyay U K
Department of Civil Engineering, Indian Institute of Technology, Kharagpur, India.
Environ Monit Assess. 2006 Apr;115(1-3):205-22. doi: 10.1007/s10661-006-6550-8. Epub 2006 Apr 16.
In this study, the relationship between inhalable particulate (PM(10)), fine particulate (PM(2.5)), coarse particles (PM(2.5 - 10)) and meteorological parameters such as temperature, relative humidity, solar radiation, wind speed were statistically analyzed and modelled for urban area of Kolkata during winter months of 2003-2004. Ambient air quality was monitored with a sampling frequency of twenty-four hours at three monitoring sites located near traffic intersections and in an industrial area. The monitoring sites were located 3-5 m above ground near highly trafficked and congested areas. The 24 h average PM(10) and PM(2.5) samples were collected using Thermo-Andersen high volume samplers and exposed filter papers were extracted and analysed for benzene soluble organic fraction. The ratios between PM(2.5) and PM(10) were found to be in the range of 0.6 to 0.92 and the highest ratio was found in the most polluted urban site. Statistical analysis has shown a strong positive correlation between PM(10) and PM(2.5) and inverse correlation was observed between particulate matter (PM(10) and PM(2.5)) and wind speed. Statistical analysis of air quality data shows that PM(10) and PM(2.5) are showing poor correlation with temperature, relative humidity and solar radiation. Regression equations for PM(10) and PM(2.5) and meteorological parameters were developed. The organic fraction of particulate matter soluble in benzene is an indication of poly aromatic hydrocarbon (PAH) concentration present in particulate matter. The relationship between the benzene soluble organic fraction (BSOF) of inhalable particulate (PM(10)) and fine particulate (PM(2.5)) were analysed for urban area of Kolkata. Significant positive correlation was observed between benzene soluble organic fraction of PM(10) (BSM10) and benzene soluble organic fraction of PM(2.5) (BSM2.5). Regression equations for BSM10 and BSM2.5 were developed.
在本研究中，对2003 - 2004年冬季加尔各答市区的可吸入颗粒物（PM₁₀）、细颗粒物（PM₂.₅）、粗颗粒物（PM₂.₅₋₁₀）与温度、相对湿度、太阳辐射、风速等气象参数之间的关系进行了统计分析和建模。在位于交通路口附近和工业区的三个监测点，以24小时的采样频率对环境空气质量进行监测。监测点位于交通繁忙和拥堵区域附近地面上方3 - 5米处。使用Thermo-Andersen大容量采样器收集24小时平均PM₁₀和PM₂.₅样本，对暴露的滤纸进行萃取，并分析苯溶性有机成分。发现PM₂.₅与PM₁₀的比值在0.6至0.92范围内，且在污染最严重的城市监测点发现了最高比值。统计分析表明PM₁₀与PM₂.₅之间存在强正相关，而颗粒物（PM₁₀和PM₂.₅）与风速之间存在负相关。空气质量数据的统计分析表明，PM₁₀和PM₂.₅与温度、相对湿度和太阳辐射的相关性较差。建立了PM₁₀和PM₂.₅与气象参数的回归方程。颗粒物中可溶于苯的有机成分是颗粒物中多环芳烃（PAH）浓度的一个指标。对加尔各答市区可吸入颗粒物（PM₁₀）和细颗粒物（PM₂.₅）的苯溶性有机成分（BSOF）之间的关系进行了分析。观察到PM₁₀的苯溶性有机成分（BSM₁₀）与PM₂.₅的苯溶性有机成分（BSM₂.₅）之间存在显著正相关。建立了BSM₁₀和BSM₂.₅的回归方程。
