Air Contaminants and Atmospheric Black Carbon Association with White Sky Albedo at Hindukush Karakorum and Himalaya Glaciers

Abstract

Environmental contaminants are becoming a growing issue due to their effects on the cryosphere and their impact on the ecosystem. Mountain glaciers are receding in the HKH region and are anticipated to diminish further as black carbon (BC) concentrations rise along with other pollutants in the air, increasing global warming. Air contaminants and BC concentrations were estimated (June 2017–May 2018). An inventory of different pollutants at three glaciers in Karakoram, Hindukush, and the Himalayas has been recorded with Aeroqual 500 and TSI DRX 8533, which are as follows: ozone (28.14 ± 3.58 µg/m3), carbon dioxide (208.58 ± 31.40 µg/m3), sulfur dioxide (1.73 ± 0.33 µg/m3), nitrogen dioxide (2.84 ± 0.37 µg/m3), PM2.5 (15.90 ± 3.32 µg/m3), PM10 (28.05 ± 2.88 µg/m3), total suspended particles (76.05 ± 10.19 µg/m3), BC in river water (88.74 ± 19.16 µg/m3), glaciers (17.66 ± 0.82 µg/m3), snow/rain (57.43 ± 19.66 ng/g), and air (2.80 ± 1.20 µg/m3). BC was estimated by using DRI Model 2015, Multi-Wavelength Thermal/Optical Carbon Analyzer, in conjunction with satellite-based white-sky albedo (WSA). The average BC concentrations in the Karakoram, Himalaya, and Hindukush were 2.35 ± 0.94, 4.38 ± 1.35, and 3.32 ± 1.09 (µg/m3), whereas WSA was 0.053 ± 0.024, 0.045 ± 0.015, and 0.045 ± 0.019 (µg/m3), respectively. Regression analysis revealed the inverse relationship between WSA and BC. The resulting curves provide a better understanding of the non-empirical link between BC and WSA. Increased BC will inherit ecological consequences for the region, ultimately resulting in biodiversity loss.

Special Issue on Air Quality Prediction Based on Machine Learning Algorithms

“…Zainab et al [1] propose an innovative method using satellite-based white-sky albedo (WSA) to estimate the concentration of black carbon in the Himalaya region. Additionally, the second study makes use of satellite data and combines them with ground-based measurements for predicting air pollution.…”