Variability of ambient black carbon concentration in the Central Himalaya and its assessment over the Hindu Kush Himalayan region

Spatiotemporal distribution, light absorption characteristics, and source apportionments of black and brown carbon in China

Black carbon (BC) and brown carbon (BrC) are aerosols that absorb light and thereby contribute to climate change. In this study, the light absorption properties and spatiotemporal distributions of equivalent BC (eBC) and BrC aerosols were determined based on continuous measurements of aerosol light absorption from January to August 2017, using a seven-channel aethalometer at 49 sampling sites in China. The source apportionments of BC and BrC were identified using the BC/PM2.5, absorption Ångström exponent, the concentration-weighted trajectory method, and the random forest model. Based on the results, BC was the dominant light absorber, whereas BrC was responsible for a higher proportion of the light absorption in northern compared to southern China. The light absorption of BrC was highest in winter (34.3 Mm-1), followed by spring (19.0 Mm-1) and summer (3.6 Mm-1). The combustion of liquid fuels accounted for over 50 % of the light absorption coefficient of BC in most cities and the importance of carbon monoxide (CO) and nitrogen dioxide (NO2) was over 10 % for BC emitted by liquid fuel combustion, based on the random forest model. The contribution of solid fuel combustion to BC in the north was larger than that in the southern regions as coal combustion and crop residue burning are important emission sources of BC in most northern cities. The contribution of primary BrC to light absorption was high in some northern cities, whereas that of secondary BrC was prevalent in some southern cities. The diurnal variations in secondary BrC were affected by changes in odd oxygen and relative humidity, which promoted the photobleaching of the chromophores and aqueous-phase reactions of secondary BrC.

Modeling the dispersion of traffic-derived black carbon emissions into hilly terrain

This study examines hilly terrain's effect on black carbon (BC) dispersion. The apportionment of distinct sources obtained by a two-component mixing model (Aethalometer: AE-33) using improved radiative transfer equations showed the dominance of traffic-derived black carbon (BCFF) emissions in the study region. The AERMOD was used to model BC emissions from moving traffic as a line source and parking lot as area source using observational and WRF-processed meteorology for the winter (January to March 2020). The model results showed that the BC levels substantially vary with local meteorological conditions, traffic volume, and composition. The hilly terrain obstructs the winds and develops a negative pressure loading to a vacuum on the other side of the hills, which promotes the accumulation of emissions, causing high BC concentrations. The pockets of higher concentration were seen at the locations where steep slopes were associated with low winds (<1 m s-1) and hill fogs. The AERMOD model, after statistical evaluation against the observational datasets, has been applied to study the reduction in BCFF concentrations due to the implementation of Indian emission norms as mitigation measures, i.e., BS-IV (equivalent to Euro 4) and BS-VI (equivalent to Euro 6). It was found that the BCFF concentrations for BS-IV and BS-VI reduced by 35% and 75%, respectively. The model was also used to study the contribution of the different vehicular categories to BC concentration.

The COVID-19 lockdown: a unique perspective into heterogeneous impacts of transboundary pollution on snow and ice darkening across the Himalayas

The Tibetan Plateau holds the largest mass of snow and ice outside of the polar regions. The deposition of light-absorbing particles (LAPs) including mineral dust, black carbon and organic carbon and the resulting positive radiative forcing on snow (RFSLAPs) substantially contributes to glacier retreat. Yet how anthropogenic pollutant emissions affect Himalayan RFSLAPs through transboundary transport is currently not well known. The COVID-19 lockdown, resulting in a dramatic decline in human activities, offers a unique test to understand the transboundary mechanisms of RFSLAPs. This study employs multiple satellite data from the moderate resolution imaging spectroradiometer and ozone monitoring instrument, as well as a coupled atmosphere-chemistry-snow model, to reveal the high spatial heterogeneities in anthropogenic emissions-induced RFSLAPs across the Himalaya during the Indian lockdown in 2020. Our results show that the reduced anthropogenic pollutant emissions during the Indian lockdown were responsible for 71.6% of the reduction in RFSLAPs on the Himalaya in April 2020 compared to the same period in 2019. The contributions of the Indian lockdown-induced human emission reduction to the RFSLAPs decrease in the western, central, and eastern Himalayas were 46.8%, 81.1%, and 110.5%, respectively. The reduced RFSLAPs might have led to 27 Mt reduction in ice and snow melt over the Himalaya in April 2020. Our findings allude to the potential for mitigating rapid glacial threats by reducing anthropogenic pollutant emissions from economic activities.