Latha R, Mukherjee A, Dahiya K, Bano S, Pawar P, Kalbande R, Maji S, Beig G, Murthy B S
Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, India.
Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, India.
J Environ Manage. 2022 Jun 1;311:114834. doi: 10.1016/j.jenvman.2022.114834. Epub 2022 Mar 11.
Source apportionment study of PM using positive matrix factorization was performed to identify the emission characteristic from different sectors (sub-urban residential, industrial and rapidly urbanizing) of Delhi during winter. Chemical characterization of PM included metals (Ca, Cd, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb and Zn), water soluble ionic compounds (WSICs) (Cl, NO, SO and NH) and Carbon partitions (OC, EC). Particulates (PM) were collected on filter twice daily for stable and unstable atmospheric conditions, at the locations with specific characteristics, viz. Ayanagar, Noida and Okhla. Ions solely occupied 50% of the total PM concentration. Irrespective of location, high correlation between OC and EC (0.871-0.891) at p ≤ 0.1 is observed. Relatively lower ratio of NO/SO at Ayanagar (0.696) and Okhla (0.84) denotes predominance of emission from stationary sources rather than mobile sources like that observed at Noida (1.038). Using EPA PMF5.0, optimum factors for each location are fixed based on error estimation (EE). Crustal dust, vehicular emission, biomass burning and secondary aerosol are the major contributing sources in all the three locations. Incineration contributes about 19% at Ayanagar and 18% at Okhla. Metal industries in Okhla contribute about 19% to PM. These specific local emissions with considerable potency are to be targeted for long-term policymaking. Considerable secondary aerosol contribution (15%-24%) indicates that gaseous emissions also need to be reduced to improve air quality.
利用正定矩阵因子分解法对细颗粒物进行源解析研究,以确定德里冬季不同区域(城郊居民区、工业区和快速城市化区域)的排放特征。细颗粒物的化学特征包括金属(钙、镉、铬、铜、铁、钾、镁、锰、钠、镍、铅和锌)、水溶性离子化合物(氯离子、硝酸根离子、硫酸根离子和铵根离子)以及碳组分(有机碳、元素碳)。在阿亚纳加尔、诺伊达和奥克拉等具有特定特征的地点,每天两次在过滤器上采集颗粒物,以适应稳定和不稳定的大气条件。离子仅占细颗粒物总浓度的50%。无论在哪个地点,均观察到有机碳和元素碳之间在p≤0.1时有较高的相关性(0.871 - 0.891)。阿亚纳加尔(0.696)和奥克拉(0.84)的硝酸根离子/硫酸根离子比值相对较低,表明固定源排放占主导地位,而非诺伊达(1.038)所观察到的移动源排放。使用美国环保署的PMF5.0模型,根据误差估计确定每个地点的最佳因子。地壳尘埃、车辆排放、生物质燃烧和二次气溶胶是所有三个地点的主要贡献源。焚烧在阿亚纳加尔的贡献率约为19%,在奥克拉为18%。奥克拉的金属工业对细颗粒物的贡献率约为19%。这些具有相当影响力的特定本地排放是长期政策制定的目标。相当大的二次气溶胶贡献(15% - 24%)表明,为了改善空气质量,也需要减少气体排放。