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Khan M, Tariq S, Haq ZU. Variations in the aerosol index and its relationship with meteorological parameters over Pakistan using remote sensing. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:47913-47934. [PMID: 36749519 PMCID: PMC9904527 DOI: 10.1007/s11356-023-25613-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Accepted: 01/24/2023] [Indexed: 06/18/2023]
Abstract
Particulate pollution has become a major issue in developing countries including Pakistan. Aerosols are causing severe impacts on climate and human health. To understand the effects of aerosols on the environment and human health, we must first understand their optical and physical properties. In this paper, we used ozone monitoring instrument (OMI) retrieved ultraviolet aerosol index (UVAI) to analyze spatial and temporal distribution, annual and seasonal trends of absorbing aerosols, and their relationship with meteorological parameters (e.g., temperature, relative humidity, and wind speed) over Pakistan from October 2004 to December 2021. Significant spatiotemporal changes in UVAI values were found with high values in southern and central regions and low values in northern regions of Pakistan. The mean UVAI over Pakistan showed an increasing trend of 2.89% year-1. Seasonally, UVAI increases at the rate of 3.97% winter-1, 3.24% autumn-1, 0.81% summer-1, and 0.71% spring-1. A strong positive correlation of UVAI with precipitation and temperature (~ 0.6) is observed in the central and southern regions of Pakistan. A negative and positive correlation of -0.3223 and 0.4284 of UVAI with CO2 emissions and primary industry is observed in Pakistan, respectively. We also found potential sources of aerosols over major cities of Pakistan using the Hybrid Single Particle Langrangian Integrated Trajectory (HYSPLIT) model. It determines that the dominant aerosols over Karachi are natural aerosols like sea salt and dust particles and anthropogenic aerosols are dominant over Lahore. Moreover, the natural and anthropogenic factors influencing absorbing aerosols are also discussed herein. Considering the outcomes of this study different methods would be used to reduce the concentration of particulate pollution like afforestation, efficient fuel energy consumption, promotion of public transport networks, etc.
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Affiliation(s)
- Muhammad Khan
- Remote Sensing, GIS and Climatic Research Lab, National Center of GIS and Space Applications, Department of Space Science, University of the Punjab, New-Campus, Lahore, Pakistan.
| | - Salman Tariq
- Remote Sensing, GIS and Climatic Research Lab, National Center of GIS and Space Applications, Centre for Remote Sensing, University of the Punjab, New-Campus, Lahore, Pakistan
| | - Zia Ul Haq
- Remote Sensing, GIS and Climatic Research Lab, National Center of GIS and Space Applications, Centre for Remote Sensing, University of the Punjab, New-Campus, Lahore, Pakistan
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Mehmood U, Tariq S, Haq ZU, Agyekum EB, Uhunamure SE, Shale K, Nawaz H, Ali S, Hameed A. Financial Institutional and Market Deepening, and Environmental Quality Nexus: A Case Study in G-11 Economies Using CS-ARDL. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph191911984. [PMID: 36231285 PMCID: PMC9565658 DOI: 10.3390/ijerph191911984] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Revised: 09/15/2022] [Accepted: 09/16/2022] [Indexed: 05/05/2023]
Abstract
This study presents a new insight into the dynamic relationship between financial institutional deepening (FID), financial deepening, financial market deepening (FMD), foreign direct investment (FDI), economic growth (GDP), population, and carbon dioxide emissions (CO2e) in the G-11 economies by employing a cross-sectionally augmented autoregressive distributed lag (CS-ARDL) approach during 1990-2019. The outcomes from the CS-ARDL and dynamic common correlated effects mean group (DCCEMG) models shows that financial deepening, GDP, FDI, and population degraded environmental quality both in the short run and the long run. Contrary to this, FID and FMD improves environmental quality in these countries. The government should work to maximize financial institutions (access, depth, efficiency) and financial markets (access, depth, efficiency) to reduce the CO2e. A strong positive and in-phase correlation of CO2e with economic growth and population is observed for G-11 countries. These results suggest policy makers should further improve financial institutions by creating opportunities for their populations. Moreover, the governments of G-11 countries should revise their foreign direct investment policies and attention should be given to import efficient means of energy production.
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Affiliation(s)
- Usman Mehmood
- Remote Sensing, GIS and Climatic Research Lab, National Center of GIS and Space Applications, Centre for Remote Sensing, University of the Punjab, Lahore 54590, Pakistan
- Department of Political Science, University of Management and Technology, Lahore 54590, Pakistan
| | - Salman Tariq
- Remote Sensing, GIS and Climatic Research Lab, National Center of GIS and Space Applications, Department of Space Science, University of the Punjab, Lahore 54590, Pakistan
| | - Zia ul Haq
- Remote Sensing, GIS and Climatic Research Lab, National Center of GIS and Space Applications, Department of Space Science, University of the Punjab, Lahore 54590, Pakistan
| | - Ephraim Bonah Agyekum
- Department of Nuclear and Renewable Energy, Ural Federal University Named after the First President of Russia Boris Yeltsin, 19 Mira Street, Eka-Terinburg 620002, Russia
| | - Solomon Eghosa Uhunamure
- Faculty of Applied Sciences, Cape Peninsula University of Technology, P.O. Box 652, Cape Town 8000, South Africa
- Correspondence:
| | - Karabo Shale
- Faculty of Applied Sciences, Cape Peninsula University of Technology, P.O. Box 652, Cape Town 8000, South Africa
| | - Hasan Nawaz
- Remote Sensing, GIS and Climatic Research Lab, National Center of GIS and Space Applications, Centre for Remote Sensing, University of the Punjab, Lahore 54590, Pakistan
| | - Shafqat Ali
- Remote Sensing, GIS and Climatic Research Lab, National Center of GIS and Space Applications, Centre for Remote Sensing, University of the Punjab, Lahore 54590, Pakistan
| | - Ammar Hameed
- Remote Sensing, GIS and Climatic Research Lab, National Center of GIS and Space Applications, Centre for Remote Sensing, University of the Punjab, Lahore 54590, Pakistan
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