印度北部五个污染严重和污染较轻城市上空基于卫星的气溶胶光学深度、安氏指数、单散射反照率和紫外线-气溶胶指数的时空变化:城市化和气候变化的影响

IF 1.6 4区 环境科学与生态学 Q4 ENVIRONMENTAL SCIENCES
Rolly Singh, Vikram Singh, Alok Sagar Gautam, Sneha Gautam, Manish Sharma, Pushpendra Singh Soni, Karan Singh, Alka Gautam
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引用次数: 6

摘要

人们普遍认为,人口增长、城市化的快速发展、经济增长和工业化等因素都对大气气溶胶浓度的上升起到了一定作用。在目前的工作中,我们评估并讨论了对基于卫星的气溶胶光学参数(如气溶胶光学深度(AOD)、埃氏指数(AE)、单散射反照率(SSA)和紫外线气溶胶指数(UV-AI))的时间和空间变化的彻底分析结果,在过去的2011-2020年中,本研究对印度北部五个污染和污染较轻的城市进行了浓度调查。AOD气溶胶光学参数的时间变化范围为0.2至1.8,十年平均值为0.86 ± 过去十年中,由于化石燃料的气溶胶燃烧、巨大的车辆交通和生物量的增加,巴特那地区的0.36显示出高值,研究区域呈十年增长趋势。AE的时间变化范围为0.3至1.8,十年平均值为1.72 ± 与其他研究地区相比,阿格拉地区的0.11显示出较高的值,这表明阿格拉的细模式气溶胶水平相对较高。SSA的时间变化范围为0.8至0.9,十年平均值为0.92 ± SSA的0.02在任何位置都没有显示出可辨别的十年模式。UV-AI的时间变化范围为-1.01-2.36,十年平均值为0.59 ± 0.06的UV-AI显示出上升趋势,卢迪亚纳的UV-AI显著上升,这表明吸收尘埃气溶胶在卢迪亚纳相对占主导地位。此外,为了了解新兴活动的影响,对季节性进行了分析。因此,气溶胶气候学是针对不同季节得出的,即冬季、季风前、季风和季风后。研究区域巴特那、德里和阿格拉在冬季观测到高气溶胶,这表明颗粒物在生物质燃烧气溶胶中占主要地位;Tehri Garhwal和Ludhiana研究区的季风和后季风最差,这表明大部分气溶胶浓度被降雨去除。之后,我们分析了所有参数之间的相关性,以更好地了解选定区域气溶胶的时间和空间分布特征。区域2和1的AOD(550nm)的r值(0.80)显示出强正相关,区域3和1的r值为中等正相关(0.64),主要是由于干旱西部地区携带的矿尘。区域3和(0.40)的AE(412/470nm)的r值显示出适度的正相关性,这是细模式气溶胶占主导地位的结果,而区域5和1的AE为负(− 0.06)。区域2和1的SSA(500nm)的r值(0.63)显示出适度的正相关性,这解释了更有效地散射太阳能量的大气溶胶颗粒的增加,区域1和2的UV-AI的r值显示出强正相关(0.77),区域3和1的r值为中等正相关(0.46),这表明研究区域上存在吸收气溶胶。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Temporal and Spatial Variations of Satellite-Based Aerosol Optical Depths, Angstrom Exponent, Single Scattering Albedo, and Ultraviolet-Aerosol Index over Five Polluted and Less-Polluted Cities of Northern India: Impact of Urbanization and Climate Change

It is widely acknowledged that factors such as population growth, urbanization's quick speed, economic growth, and industrialization all have a role in the atmosphere's rising aerosol concentration. In the current work, we assessed and discussed the findings of a thorough analysis of the temporal and spatial variations of satellite-based aerosol optical parameters such as Aerosol Optical Depth (AOD), Angstrom Exponent (AE), Single Scattering Albedo (SSA), and Ultraviolet-Aerosol Index (UV-AI), and their concentration have been investigated in this study over five polluted and less-polluted cities of northern India during the last decade 2011–2020. The temporal variation of aerosol optical parameters for AOD ranging from 0.2 to 1.8 with decadal mean 0.86 ± 0.36 for Patna region shows high value with a decadal increasing trend over the study area due to rise in aerosols combustion of fossil fuels, huge vehicles traffic, and biomass over the past ten years. The temporal variation of AE ranging from 0.3 to 1.8 with decadal mean 1.72 ± 0.11 for Agra region shows high value as compared to other study areas, which indicates a comparatively higher level of fine-mode aerosols at Agra. The temporal variation of SSA ranging from 0.8 to 0.9 with decadal mean 0.92 ± 0.02 for SSA shows no discernible decadal pattern at any of the locations. The temporal variation of UV-AI ranging from -1.01 to 2.36 with decadal mean 0.59 ± 0.06 for UV-AI demonstrates a rising tendency, with a noticeable rise in Ludhiana, which suggests relative dominance of absorbing dust aerosols over Ludhiana. Further, to understand the impact of emerging activities, analyses were done in seasonality. For this aerosol climatology was derived for different seasons, i.e., Winter, Pre-Monsoon, Monsoon, and Post-Monsoon. High aerosol was observed in Winter for the study areas Patna, Delhi, and Agra which indicated the particles major dominance of burning aerosol from biomass; and the worst in Monsoon and Post-Monsoon for the Tehri Garhwal and Ludhiana study areas which indicated most of the aerosol concentration is removed by rainfall. After that, we analyzed the correlation among all the parameters to better understand the temporal and spatial distribution characteristics of aerosols over the selected region. The value of r for AOD (550 nm) for regions 2 and 1(0.80) shows a strong positive correlation and moderately positive for the regions 3 and 1 (0.64), mostly as a result of mineral dust carried from arid western regions. The value of r for AE (412/470 nm) for region 3 and (0.40) shows a moderately positive correlation, which is the resultant of the dominance of fine-mode aerosol and negative for the regions 5 and 1 (− 0.06). The value of r for SSA (500 nm) for regions 2 and 1 (0.63) shows a moderately positive correlation, which explains the rise in big aerosol particles, which scatters sun energy more efficiently, and the value of r for UV-AI for regions 1 and 2 shows a strong positive correlation (0.77) and moderately positive for the regions 3 and 1 (0.46) which indicates the absorbing aerosols present over the study region.

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来源期刊
Aerosol Science and Engineering
Aerosol Science and Engineering Environmental Science-Pollution
CiteScore
3.00
自引率
7.10%
发文量
42
期刊介绍: ASE is an international journal that publishes high-quality papers, communications, and discussion that advance aerosol science and engineering. Acceptable article forms include original research papers, review articles, letters, commentaries, news and views, research highlights, editorials, correspondence, and new-direction columns. ASE emphasizes the application of aerosol technology to both environmental and technical issues, and it provides a platform not only for basic research but also for industrial interests. We encourage scientists and researchers to submit papers that will advance our knowledge of aerosols and highlight new approaches for aerosol studies and new technologies for pollution control. ASE promotes cutting-edge studies of aerosol science and state-of-art instrumentation, but it is not limited to academic topics and instead aims to bridge the gap between basic science and industrial applications.  ASE accepts papers covering a broad range of aerosol-related topics, including aerosol physical and chemical properties, composition, formation, transport and deposition, numerical simulation of air pollution incidents, chemical processes in the atmosphere, aerosol control technologies and industrial applications. In addition, ASE welcomes papers involving new and advanced methods and technologies that focus on aerosol pollution, sampling and analysis, including the invention and development of instrumentation, nanoparticle formation, nano technology, indoor and outdoor air quality monitoring, air pollution control, and air pollution remediation and feasibility assessments.
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