Usman Mazhar

Dr. Usman Mazhar

Department of Geography, University of the Punjab, Lahore, Punjab, Pakistan
orcid

Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 October 2021 in Remote Sensing of Environment
Verified
Journal Article
Closed access
Muhammad BilalMuhammad Bilal
Muhammad Bilal
AMAlaa Mhawish
Alaa Mhawish
Janet NicholJanet Nichol
Janet Nichol
ZQZhongfeng Qiu
Zhongfeng Qiu
Majid NazeerMajid Nazeer
Majid Nazeer
SKSong Ke
Song Ke

1 November 2020 in Atmospheric Environment
Verified
Journal Article
Closed access
Md. Arfan AliMd. Arfan Ali
Md. Arfan Ali
JNJanet E. Nichol
Janet E. Nichol
Muhammad BilalMuhammad Bilal
Muhammad Bilal
ZQZhongfeng Qiu
Zhongfeng Qiu
Usman MazharUsman Mazhar
Usman Mazhar
MIM. Nazrul Islam
M. Nazrul Islam

1 March 2022 in Geoscience Frontiers
Verified
Journal Article
Open access
Md. Arfan AliMd. Arfan Ali
Md. Arfan Ali
Muhammad BilalMuhammad Bilal
Muhammad Bilal
YWYu Wang
Yu Wang
ZQZhongfeng Qiu
Zhongfeng Qiu
JNJanet E. Nichol
Janet E. Nichol
MIM. Nazrul Islam
M. Nazrul Islam

26 February 2021 in Remote Sensing
Verified
Journal Article
Open access
PDF file
ZQZhongfeng Qiu
Zhongfeng Qiu
Md. Arfan AliMd. Arfan Ali
Md. Arfan Ali
Janet NicholJanet Nichol
Janet Nichol
Muhammad BilalMuhammad Bilal
Muhammad Bilal
Pravash TiwariPravash Tiwari
Pravash Tiwari
MRMuhammad Ashfaqur Rahman
Muhammad Ashfaqur Rahman
This study investigates spatiotemporal changes in air pollution (particulate as well as gases) during the COVID-19 lockdown period over major cities of Bangladesh. The study investigated the aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra and Aqua satellites, PM2.5 and PM10 from Copernicus Atmosphere Monitoring Service (CAMS), and NO2 and O3 from TROPOMI-5P, from March to June 2019–2020. Additionally, aerosol subtypes from the Cloud-Aerosol Lidar and Infrared Pathfinder (CALIPSO) were used to explore the aerosol types. The strict lockdown (26 March–30 May 2020) led to a significant reduction in AOD (up to 47%) in all major cities, while the partial lockdown (June 2020) led to increased and decreased AOD over the study area. Significant reductions in PM2.5 (37–77%) and PM10 (33–70%) were also observed throughout the country during the strict lockdown and partial lockdown. The NO2 levels decreased by 3–25% in March 2020 in the cities of Rajshahi, Chattogram, Sylhet, Khulna, Barisal, and Mymensingh, in April by 3–43% in Dhaka, Chattogram, Khulna, Barisal, Bhola, and Mymensingh, and May by 12–42% in Rajshahi, Sylhet, Mymensingh, and Rangpur. During the partial lockdown in June, NO2 decreased (9–35%) in Dhaka, Chattogram, Sylhet, Khulna, Barisal, and Rangpur compared to 2019. On the other hand, increases were observed in ozone (O3) levels, with an average increase of 3–12% throughout the country during the strict lockdown and only a slight reduction of 1–3% in O3 during the partial lockdown. In terms of aerosol types, CALIPSO observed high levels of polluted dust followed by dust, smoke, polluted continental, and clean marine-type aerosols over the country in 2019, but all types were decreased during the lockdown. The study concludes that the strict lockdown measures were able to significantly improve air quality conditions over Bangladesh due to the shutdown of industries, vehicles, and movement of people.

27 August 2019 in Atmosphere
Verified
Journal Article
Open access
PDF file
Muhammad BilalMuhammad Bilal
Muhammad Bilal
Janet NicholJanet Nichol
Janet Nichol
Majid NazeerMajid Nazeer
Majid Nazeer
Yuan ShiYuan Shi
Yuan Shi
Lunche WangLunche Wang
Lunche Wang
Simone LolliSimone Lolli
Simone Lolli
In urban areas, fine particulate matter (PM2.5) associated with local vehicle emissions can cause respiratory and cardiorespiratory disease and increased mortality rates, but less so in rural areas. However, Hong Kong may be a special case, since the whole territory often suffers from regional haze from nearby mainland China, as well as local sources. Therefore, to understand which areas of Hong Kong may be affected by damaging levels of fine particulates, PM2.5 data were obtained from March 2005 to February 2009 for urban, suburban, and rural air quality monitoring stations; namely Central (city area, commercial area, and urban populated area), Tsuen Wan (city area, commercial area, urban populated, and residential area), Tung Chung (suburban and residential area), Yuen Long (urban and residential area), and Tap Mun (remote rural area). To evaluate the relative contributions of regional and local pollution sources, the study aimed to test the influence of weather conditions on PM2.5 concentrations. Thus, meteorological parameters including temperature, relative humidity, wind speed, and wind directions were obtained from the Hong Kong Observatory. The results showed that Hong Kong’s air quality is mainly affected by regional aerosol emissions, either transported from the land or ocean, as similar patterns of variations in PM2.5 concentrations were observed over urban, suburban, and rural areas of Hong Kong. Only slightly higher PM2.5 concentrations were observed over urban sites, such as Central, compared to suburban and rural sites, which could be attributed to local automobile emissions. Results showed that meteorological parameters have the potential to explain 80% of the variability in daily mean PM2.5 concentrations—at Yuen Long, 77% at Tung Chung, 72% at Central, 71% at Tsuen Wan, and 67% at Tap Mun, during the spring to summer part of the year. The results provide not only a better understanding of the impact of regional long-distance transport of air pollutants on Hong Kong’s air quality but also a reference for future regional-scale collaboration on air quality management.

13 January 2021 in Remote Sensing
Verified
Journal Article
Open access
PDF file
Usman MazharUsman Mazhar
Usman Mazhar
Shuanggen JinShuanggen Jin
Shuanggen Jin
WDWentao Duan
Wentao Duan
Muhammad BilalMuhammad Bilal
Muhammad Bilal
Md. Arfan AliMd. Arfan Ali
Md. Arfan Ali
HFHusnain Farooq
Husnain Farooq
Being the highest and largest land mass of the earth, the Tibetan Plateau has a strong impact on the Asian climate especially on the Asian monsoon. With high downward solar radiation, the Tibetan Plateau is a climate sensitive region and the main water source for many rivers in South and East Asia. Although many studies have analyzed energy fluxes in the Tibetan Plateau, a long-term detailed spatio-temporal variability of all energy budget parameters is not clear for understanding the dynamics of the regional climate change. In this paper, satellite remote sensing and reanalysis data are used to quantify spatio-temporal trends of energy budget parameters, net radiation, latent heat flux, and sensible heat flux over the Tibetan Plateau from 2001 to 2019. The validity of both data sources is analyzed from in situ ground measurements of the FluxNet micrometeorological tower network, which verifies that both datasets are valid and reliable. It is found that the trend of net radiation shows a slight increase. The latent heat flux increases continuously, while the sensible heat flux decreases continuously throughout the study period over the Tibetan Plateau. Varying energy fluxes in the Tibetan plateau will affect the regional hydrological cycle. Satellite LE product observation is limited to certain land covers. Thus, for larger spatial areas, reanalysis data is a more appropriate choice. Normalized difference vegetation index proves a useful indicator to explain the latent heat flux trend. Despite the reduction of sensible heat, the atmospheric temperature increases continuously resulting in the warming of the Tibetan Plateau. The opposite trend of sensible heat flux and air temperature is an interesting and explainable phenomenon. It is also concluded that the surface evaporative cooling is not the indicator of atmospheric cooling/warming. In the future, more work shall be done to explain the mechanism which involves the complete heat cycle in the Tibetan Plateau.