Suppr超能文献

印度奥里萨邦一个露天煤矿区周围颗粒物和气态污染物的季节和空间分布分析。

Analysis of seasonal and spatial distribution of particulate matters and gaseous pollutants around an open cast coal mining area of Odisha, India.

作者信息

Sharma Rajat, Kumar Ashutosh

机构信息

School of Energy & Environment, Thapar Institute of Engineering & Technology, Patiala, 147004, Punjab, India.

出版信息

Environ Sci Pollut Res Int. 2023 Mar;30(14):39842-39856. doi: 10.1007/s11356-022-25034-w. Epub 2023 Jan 5.

Abstract

Open cast mining - a predominant method of coal production in India (94.46% of total coal production) - has been found to be a major factor which is responsible for the emission of dust particles and gaseous pollutants, leading to the deterioration of air quality in the coal mining area. Considering the health concerns and environmental impacts of these pollutants, the inhabited villages of Ib valley coalfield area of Orisha, India, were selected for this study. In this regard, various researchers have performed the analysis of air quality data and modeling for the dispersion of pollutants. However, a long-term study on spatial and seasonal variations of air pollutants and their relationship with meteorological parameters were missing in the literature. Accordingly, the spatial and seasonal variations of air pollutants in the area were assessed for a period of six years (2014 - 2020), and concentrations of PM, PM, and SPM were found to be above the annual national ambient air quality standards (NAAQS) for all the three seasons. The overall mean concentrations of NO, PM, PM, SPM, and SO during this period were found to be 17.2 ± 9.28, 152.5 ± 99.7, 53.27 ± 37.70, 268.5 ± 158.2, and 12.58 ± 7.47 μg/m, respectively. The analysis of meteorological parameters showed a strong and significant negative correlation of relative humidity with PM (r =  - 0.30, p-value = 5.659 × 10), PM (r =  - 0.36, p-value = 1.97 × 10), and SPM (r =  - 0.45, p-value = 2.2 × 10). Furthermore, the spatial distribution of pollutants was performed using the geographic information system (GIS) and inverse distance weighting (IDW) method, wherein the seasonal distribution of pollutants was shown through the bivariate polar plots. Therefore, the analyses and recommendations provided in this study can help the policymakers in developing a long-term air quality improvement strategy around a coal mining area, including the spatial and seasonal variations of air pollutants and their relationship with meteorological parameters.

摘要

露天开采——印度煤炭生产的主要方式(占煤炭总产量的94.46%)——已被发现是导致粉尘颗粒和气态污染物排放的主要因素,进而导致煤矿区空气质量恶化。考虑到这些污染物对健康的影响和环境影响,印度奥里萨邦伊布河谷煤田地区有人居住的村庄被选作本研究对象。在这方面,众多研究人员已对空气质量数据进行了分析,并对污染物扩散进行了建模。然而,文献中缺少关于空气污染物的空间和季节变化及其与气象参数关系的长期研究。因此,对该地区六年(2014年至2020年)期间空气污染物的空间和季节变化进行了评估,发现所有三个季节的PM、PM和SPM浓度均高于国家年度环境空气质量标准(NAAQS)。在此期间,NO、PM、PM、SPM和SO的总体平均浓度分别为17.2±9.28、152.5±99.7、53.27±37.70、268.5±158.2和12.58±7.47μg/m。气象参数分析表明,相对湿度与PM(r = -0.30,p值 = 5.659×10)、PM(r = -0.36,p值 = 1.97×10)和SPM(r = -0.45,p值 = 2.2×10)之间存在强烈且显著的负相关。此外,使用地理信息系统(GIS)和反距离加权(IDW)方法对污染物的空间分布进行了分析,其中通过双变量极坐标图展示了污染物的季节分布。因此,本研究提供的分析和建议有助于政策制定者制定围绕煤矿区的长期空气质量改善策略,包括空气污染物的空间和季节变化及其与气象参数的关系。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验