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The study represents the seasonal characteristics (carbonaceous aerosols and elements) and the contribution of prominent sources of PM 2.5 and PM 10 in the high altitude of the eastern Himalaya (Darjeeling) during August 2018–July 2019. Carbonaceous aerosols [organic carbon (OC), elemental carbon (EC), and water soluble organic carbon (WSOC)] and elements (Al, Fe, Ti, Cu, Zn, Mn, Cr, Ni, Mo, Cl, P, S, K, Zr, Pb, Na, Mg, Ca, and B) in PM 2.5 and PM 10 were analyzed to estimate their possible sources. The annual concentrations of PM 2.5 and PM 10 were computed as 37±12 μg m −3 and 58±18 μg m −3 , respectively. In the present case, total carbonaceous species in PM 2.5 and PM 10 were accounted for 20.6% of PM 2.5 and 18.6% of PM 10 , respectively, whereas trace elements in PM 2.5 and PM 10 were estimated to be 15% of PM 2.5 and 12% of PM 10 , respectively. Monthly and seasonal variations in mass concentrations of carbonaceous aerosols and elements in PM 2.5 and PM 10 were also observed during the observational period. In PM 2.5 , the annual concentrations of POC and SOC were 2.35 ± 1.06 μg m −3 (66% of OC) and 1.19±0.57 μg m −3 (34% of OC), respectively, whereas annual average POC and SOC concentrations in PM 10 were 3.18 ± 1.13 μg m −3 (63% of OC) and 2.05±0.98 μg m −3 (37% of OC), respectively. The seasonal contribution of POC and SOC were ranging from 55 to 77% and 33 to 45% of OC in PM 2.5 , respectively, whereas in PM 10 , the seasonal contributions of POC and SOC were ranging from 51 to 73% and 37 to 49% of OC, respectively. The positive relationship between OC & EC and OC & WSOC of PM 2.5 and PM 10 during all the seasons (except monsoon in case of PM 10 ) indicates their common sources. The enrichment factors (EFs) and significant positive correlation of Al with othe crustal elements (Fe, Ca, Mg, and Ti) of fine and coarse mode aerosols indicate the influence of mineral dust at Darjeeling. Principal component analysis (PCA) resolved the four common sources (biomass burning + fossil fuel combustion (BB + FFC), crustal/soil dust, vehicular emissions (VE), and industrial emissions (IE)) of PM 2.5 and PM 10 in Darjeeling.

The present study represents the annual and seasonal concentration of PM 10 over different sites (Darjeeling, Nainital, Mohal-Kullu) across the Himalayan region of India from July 2018 to December 2019. The collected PM 10 samples were analyzed for carbonaceous aerosols [organic carbon (OC), elemental carbon (EC), water-soluble organic carbon (WSOC), primary organic carbon (POC), secondary organic carbon (SOC)] and major trace elements to inspect their possible sources. The annual average concentrations of PM 10 over Mohal-Kullu, Nainital, and Darjeeling were recorded as 57 ± 32 µg m –3 , 65 ± 41 µg m –3 , and 54 ± 17 µg m –3 , respectively. The high OC/EC ratio and significant correlation of OC with EC and WSOC with OC indicated a significant effect of biomass burning aerosols over the study sites. Principal component analysis/absolute principal component score (PCA/APCS) resolved four major sources: crustal/soil dust (26.6%), biomass burning/fossil fuel combustion (28%), vehicular emissions (28%), and industrial emissions/coal combustion (17%). Identification of the source region using the potential source contribution function (PSCF) and concentration weighted trajectories (CWT) showed that PM 10 was mainly transported from the northwestern part of India (Haryana, Punjab), the northeastern region of Pakistan, the Thar Desert, and Indo-Gangetic Plain (IGP), which contributed to dust-related aerosols over the Himalayan region of India.

Understanding the climate impact of residential emissions starts with determining the fuel consumption of various household activities. While cooking emissions have been widely studied, non-cooking energy-consumption activities in the residential sector such as heating and lighting, have been overlooked owing to the unavailability of data at national levels. The present study uses data from the Carbonaceous Aerosol Emissions, Source Apportionment and Climate Impacts (COALESCE) project, which consists of residential surveys over 6000 households across 49 districts of India, to understand the energy consumed by non-cooking residential activities. Regression models are developed to estimate information in non-surveyed districts using demographic, housing, and meteorological data as predictors. Energy demand is further quantified and distributed nationally at a 4 × 4 km resolution. Results show that the annual energy consumption from non-cooking activities is 1106 [201] PJ, which is equal to one-fourth of the cooking energy demand. Freely available biomass is widely used to heat water on traditional stoves, even in the warmer regions of western and southern India across all seasons. Space heating (51%) and water heating (42%) dominate non-cooking energy consumption. In comparison, nighttime heating for security personnel (5%), partly-residential personal heating by guards, dominant in urban centers and kerosene lighting (2%) utilize minimal energy. Biomass fuels account for over 90% of the non-cooking consumption, while charcoal and kerosene make up the rest. Half of the energy consumption occurs during winter months (DJF), while 10% of the consumption occurs during monsoon, when kerosene lighting is the highest. Firewood is the most heavily used fuel source in western India, charcoal in the northern hilly regions, agricultural residues and dung cake in the Indo-Gangetic plains, and kerosene in eastern India. The study shows that ∼20% of residential energy consumption is on account of biomass-based heating and kerosene lighting activities.

Light‐absorbing carbonaceous aerosols that dominate atmospheric aerosol warming over India remain poorly characterized. Here, we delve into UV‐visible‐IR spectral aerosol absorption properties at nine PAN‐India COALESCE network sites (Venkataraman et al., 2020, https://doi.org/10.1175/bams‐d‐19‐0030.1). Absorption properties were estimated from aerosol‐laden polytetrafluoroethylene filters using a well‐constrained technique incorporating filter‐to‐particle correction factors. The measurements revealed spatiotemporal heterogeneity in spectral intrinsic and extrinsic absorption properties. Absorption analysis at near‐UV wavelengths from carbonaceous aerosols at these regional sites revealed large near‐ultraviolet brown carbon absorption contributions from 21% to 68%—emphasizing the need to include these particles in climate models. Further, satellite‐retrieved column‐integrated absorption was dominated by surface absorption, which opens possibilities of using satellite measurements to model surface‐layer optical properties (limited to specific sites) at a higher spatial resolution. Both the satellite‐modeled and direct in‐situ absorption measurements can aid in validating and constraining climate modeling efforts that suffer from absorption underestimations and high uncertainties in radiative forcing estimates. Plain Language Summary Particulate pollution in the atmosphere scatter and absorb incoming solar energy, thus cooling or warming Earth's atmosphere. In developing countries and especially in India, one of the most polluted regions of the world, the extent to which particles can absorb solar energy and warm the atmosphere is not well understood. Here, for the first time, we measure particle absorption simultaneously at nine ground sites across India, in diverse geographical regions with different levels and types of particulate pollution. We find that organic carbon particles exert large absorption at near‐ultraviolet wavelengths, which contain significant solar energy. These light absorbing organic carbon particles, called brown carbon, are emitted in large quantities from biomass burning (e.g., burning crop residue and cooking on wood‐fired stoves). Comparing ground measurements of absorption with satellite‐retrieved measurements that are representative of the entire atmospheric column, we find that near‐surface atmospheric particles can exert significant warming. This study highlights the need to improve climate model simulations of particulate pollution's impact on the climate by incorporating spatiotemporal surface‐level absorption measurements, including absorption by brown carbon particles. Key Points Measurements at nine regional PAN‐India sites reveal several regions with large aerosol absorption strength Brown carbon contributes significantly (21%–68%) to near‐ultraviolet absorption, indicating its importance in shortwave light absorption Strong correlations observed between satellite data and surface absorption indicate future potential in modeling surface absorption

The study represents the seasonal characteristics (carbonaceous aerosols and elements) and the contribution of prominent sources of PM and PM in the high altitude of the eastern Himalaya (Darjeeling) during August 2018-July 2019. Carbonaceous aerosols [organic carbon (OC), elemental carbon (EC), and water soluble organic carbon (WSOC)] and elements (Al, Fe, Ti, Cu, Zn, Mn, Cr, Ni, Mo, Cl, P, S, K, Zr, Pb, Na, Mg, Ca, and B) in PM and PM were analyzed to estimate their possible sources. The annual concentrations of PM and PM were computed as 37±12 μg m and 58±18 μg m , respectively. In the present case, total carbonaceous species in PM and PM were accounted for 20.6% of PM and 18.6% of PM , respectively, whereas trace elements in PM and PM were estimated to be 15% of PM and 12% of PM , respectively. Monthly and seasonal variations in mass concentrations of carbonaceous aerosols and elements in PM and PM were also observed during the observational period. In PM , the annual concentrations of POC and SOC were 2.35 ± 1.06 μg m (66% of OC) and 1.19±0.57 μg m (34% of OC), respectively, whereas annual average POC and SOC concentrations in PM were 3.18 ± 1.13 μg m (63% of OC) and 2.05±0.98 μg m (37% of OC), respectively. The seasonal contribution of POC and SOC were ranging from 55 to 77% and 33 to 45% of OC in PM , respectively, whereas in PM , the seasonal contributions of POC and SOC were ranging from 51 to 73% and 37 to 49% of OC, respectively. The positive relationship between OC & EC and OC & WSOC of PM and PM during all the seasons (except monsoon in case of PM ) indicates their common sources. The enrichment factors (EFs) and significant positive correlation of Al with othe crustal elements (Fe, Ca, Mg, and Ti) of fine and coarse mode aerosols indicate the influence of mineral dust at Darjeeling. Principal component analysis (PCA) resolved the four common sources (biomass burning + fossil fuel combustion (BB + FFC), crustal/soil dust, vehicular emissions (VE), and industrial emissions (IE)) of PM and PM in Darjeeling.