Temperature projections and heatwave attribution scenarios over India: A systematic review.

The average global temperature is rising due to anthropogenic emissions. Hence, a systematic approach was used to examine the projected impacts of rising global temperatures on heatwaves in India and provide insights into mitigation and adaptation strategies. With over 24,000 deaths attributed to heatwaves from 1992 to 2015, there is an urgent need to understand India's vulnerabilities and prepare adaptive strategies under various emission scenarios.This situation is predicted to worsen as heatwaves become more frequent, intense, and long-lasting. Severe heatwaves can exacerbate chronic health conditions, vector-borne diseases, air pollution, droughts and other socio-economic pressures causing higher mortality and morbidity. Heatwaves with severe consequences have increased and are expected to become more frequent in Indian climatic and geographical conditions. As per the future projection studies, the temperature could rise ±1.2° C to ±3.5° C and will start reducing by the end of 2050. The study also provides data from the research that employs climatic models and statistical approaches for a more precise characterization of heat extremes and improved projections. Also, the study appraises the past, present and future heatwave trend projections. Most of these studies compute future projections using the Coupled Model Intercomparison Project (CMIP5) models and Representative Concentration Pathway (RCP). Limited systematic reports have been found using CMIP6, whereas the best-suited and widely used method was the RCP8.5. The study findings will aid in identifying the zones most susceptible to heatwave risk and provide actionable projections for policymakers to examine the existing evidence for developing proper planning and policy formulation, considering the future climate and temperature projections.

Nationwide estimation of daily ambient PM2.5 from 2008 to 2020 at 1 km2 in India using an ensemble approach.

High-resolution assessment of historical levels is essential for assessing the health effects of ambient air pollution in the large Indian population. The diversity of geography, weather patterns, and progressive urbanization, combined with a sparse ground monitoring network makes it challenging to accurately capture the spatiotemporal patterns of ambient fine particulate matter (PM2.5) pollution in India. We developed a model for daily average ambient PM2.5 between 2008 and 2020 based on monitoring data, meteorology, land use, satellite observations, and emissions inventories. Daily average predictions at each 1 km × 1 km grid from each learner were ensembled using a Gaussian process regression with anisotropic smoothing over spatial coordinates, and regression calibration was used to account for exposure error. Cross-validating by leaving monitors out, the ensemble model had an R2 of 0.86 at the daily level in the validation data and outperformed each component learner (by 5-18%). Annual average levels in different zones ranged between 39.7 µg/m3 (interquartile range: 29.8-46.8) in 2008 and 30.4 µg/m3 (interquartile range: 22.7-37.2) in 2020, with a cross-validated (CV)-R2 of 0.94 at the annual level. Overall mean absolute daily errors (MAE) across the 13 years were between 14.4 and 25.4 µg/m3. We obtained high spatial accuracy with spatial R2 greater than 90% and spatial MAE ranging between 7.3-16.5 µg/m3 with relatively better performance in urban areas at low and moderate elevation. We have developed an important validated resource for studying PM2.5 at a very fine spatiotemporal resolution, which allows us to study the health effects of PM2.5 across India and to identify areas with exceedingly high levels.

Characterization and apportionment of carbonaceous aerosol emission factors from light-duty and heavy-duty vehicle fleets in Maharashtra, India.

This study aims to investigate the characteristics of carbonaceous aerosols and estimate emission factor (EF) based on roadway tunnel measurements, from two distinct vehicular fleets: an all light-duty vehicle (LDV) fleet, and a mixed fleet of 80% LDV and 20% heavy-duty vehicle (HDV). Carbonaceous content (organic carbon: OC and elemental carbon: EC) in total fine particles (PM2.5) accounted for 41% ± 6.8% in LDV fleet and 48% ± 7.2% in mixed fleet. While higher volatile OC dominated in the LDV fleet emissions, in mixed fleet, lower volatile OC and EC emissions dominated due to the presence of higher HDV and super-emitter (SE) fractions which led to significantly higher optically active absorbing aerosols. Reconstructed HDV fleet EF was higher than LDV fleet by 36 times (PM2.5), 19 times (OC) and 51 times (EC). Our findings emphasize the significance of implementing vehicle inspection and maintenance programs, coupled with decarbonization of HDVs to mitigate on-road vehicular emissions in India.

Source Contributions to Fine Particulate Matter and Attributable Mortality in India and the Surrounding Region.

Fine particulate matter (PM2.5) exposure is a leading mortality risk factor in India and the surrounding region of South Asia. This study evaluates the contribution of emission sectors and fuels to PM2.5 mass for 29 states in India and 6 surrounding countries (Pakistan, Bangladesh, Nepal, Bhutan, Sri Lanka, and Myanmar) by combining source-specific emission estimates, stretched grid simulations from a chemical transport model, high resolution hybrid PM2.5, and disease-specific mortality estimates. We find that 1.02 (95% Confidence Interval (CI): 0.78-1.26) million deaths in South Asia attributable to ambient PM2.5 in 2019 were primarily from three leading sectors: residential combustion (28%), industry (15%), and power generation (12%). Solid biofuel is the leading combustible fuel contributing to the PM2.5-attributable mortality (31%), followed by coal (17%), and oil and gas (14%). State-level analyses reveal higher residential combustion contributions (35%-39%) in states (Delhi, Uttar-Pradesh, Haryana) with high ambient PM2.5 (>95 µg/m3). The combined mortality burden associated with residential combustion (ambient) and household air pollution (HAP) in India is 0.72 million (95% CI:0.54-0.89) (68% attributable to HAP, 32% attributable to residential combustion). Our results illustrate the potential to reduce PM2.5 mass and improve population health by reducing emissions from traditional energy sources across multiple sectors in South Asia.

Reassessing the availability of crop residue as a bioenergy resource in India: A field-survey based study.

Second-generation bioenergy, a carbon neutral or negative renewable resource, is crucial to achieving India's net-zero emission targets. Crop residues are being targeted as a bioenergy resource as they are otherwise burned on-field, leading to significant pollutant emissions. But estimating their bioenergy potential is problematic because of broad assumptions about their surplus fractions. Here, we use comprehensive surveys and multivariate regression models to estimate the bioenergy potential of surplus crop residues in India. These are with high sub-national and crop disaggregation that can facilitate the development of efficient supply chain mechanisms for its widespread usage. The estimated potential for 2019 of 1313 PJ can increase the present bioenergy installed capacity by 82% but is likely insufficient alone to meet India's bioenergy targets. The shortage of crop residue for bioenergy, combined with the sustainability concerns raised by previous studies, imply a need to reassess the strategy for the use of this resource.

Compositional Constraints are Vital for Atmospheric PM2.5 Source Attribution over India.

India experiences some of the highest levels of ambient PM2.5 aerosol pollution in the world. However, due to the historical dearth of in situ measurements, chemical transport models that are often used to estimate PM2.5 exposure over the region are rarely evaluated. Here, we conduct a novel model comparison with speciated airborne measurements of fine aerosol, revealing large biases in the ammonium and nitrate simulations. To address this, we incorporate process-level changes to the model and use satellite observations from the Cross-track Infrared Sounder (CrIS) and the TROPOspheric Monitoring Instrument (TROPOMI) to constrain ammonia and nitrogen oxide emissions. The resulting simulation demonstrates significantly lower bias (NMBModified: 0.19; NMBBase: 0.61) when validated against the airborne aerosol measurements, particularly for the nitrate (NMBModified: 0.08; NMBBase: 1.64) and ammonium simulation (NMBModified: 0.49; NMBBase: 0.90). We use this validated simulation to estimate a population-weighted annual PM2.5 exposure of 61.4 µg m-3, with the RCO (residential, commercial, and other) and energy sectors contributing 21% and 19%, respectively, resulting in an estimated 961,000 annual PM2.5-attributable deaths. Regional exposure and sectoral source contributions differ meaningfully in the improved simulation (compared to the baseline simulation). Our work highlights the critical role of speciated observational constraints in developing accurate model-based PM2.5 aerosol source attribution for health assessments and air quality management in India.

Evaluation of the simulated aerosol optical properties over India: COALESCE model inter-comparison of three GCMs with ground and satellite observations.

Within the framework of COALESCE project (Carbonaceous aerosol emissions, source apportionment, and climate impacts) initiative, spatio-temporal distribution of aerosol optical properties from three general circulation models are evaluated against aerosol data from satellite observations (MODIS and CALIPSO) and ground-based measurements (AERONET) for the period 2005-2014. The GCMs, NICAM-SPRINTARS (N-S), ECHAM6.3-HAM2.3 (E-H), CAM5.3 (CAM), input with identical emissions from the SMoG-India-v1 emission inventory over India nested in the CEDS global inventory, including all emission sectors except sea salt and soil dust. The annual mean total aerosol optical depth (AOD) averaged over the Indian land region is 0.38, 0.27, and 0.17 from the N-S, CAM, and E-H models respectively, while the annual mean value from the MODIS observational dataset is 0.43. Single scattering albedo predicted by E-H is lower compared to CAM and N-S while model predictions of Angstrom exponent are closer to MERRA2 dataset. However, the average total aerosol column burden over Indian landmass simulated by the models is very close and comparable to the reanalysis results. Statistical analysis of AOD between model and AERONET measurements at nine sites shows that the root mean square error varies from 0.1 to 0.4 and the index of agreement (average value) is ∼0.4. The aerosol emission and transport models, methodology for calculation of aerosol optical properties and their mixing states contributes to the diversity in the results from various models. The present study provides an analysis of limitations and uncertainties contributing to the differences between the simulations and observations, and the inter-model diversity.

Impact of Circular, Waste-Heat Reuse Pathways on PM2.5-Air Quality, CO2 Emissions, and Human Health in India: Comparison with Material Exchange Potential.

India is home to 1.3 billion people who are exposed to some of the highest levels of ambient air pollution in the world. In addition, India is one of the fastest-growing carbon-emitting countries. Here, we assess how two strategies to reuse waste-heat from coal-fired power plants and other large sources would impact PM2.5-air quality, human health, and CO2 emissions in 2015 and a future year, 2050, using varying levels of policy adoption (current regulations, proposed single-sector policies, and ambitious single-sector strategies). We find that power plant and industrial waste-heat reuse as input to district heating systems (DHSs), a novel, multisector strategy to reduce local biomass burning for heating emissions, can offset 71.3-85.2% of residential heating demand in communities near a power plant (9.3-12.4% of the nationwide heating demand) with the highest benefits observed during winter months in areas with collocated industrial activity and higher residential heating demands (e.g., New Delhi). Utilizing waste-heat to generate electricity via organic Rankine cycles (ORCs) can generate an additional 22 (11% of total coal-fired generating capacity), 41 (8%), 32 (13%), and 6 (5%) GW of electricity capacity in the 2015, 2050-current regulations, 2050-single-sector, and 2050-ambitious-single-sector scenarios, respectively. Emission estimates utilizing these strategies were input to the GEOS-Chem model, and population-weighted, simulated PM2.5 showed small improvements in the DHS (0.2-0.4%) and ORC (0.3-3.4%) scenarios, where the minimal DHS PM2.5-benefit is attributed to the small contribution of biomass burning for heating to nationwide PM2.5 emissions (much of the biomass burning activity is for cooking). The PM2.5 reductions lead to ∼130-36,000 mortalities per year avoided among the scenarios, with the largest health benefits observed in the ORC scenarios. Nationwide CO2 emissions reduced <0.04% by DHSs but showed larger reductions using ORCs (1.9-7.4%). Coal fly-ash as material exchange in cement and brick production was assessed, and capacity exists to completely reutilize unused fly-ash toward cement and brick production in each of the scenarios.

1H NMR structural signatures of source and atmospheric organic aerosols in India.

Organic aerosols (OA) play significant roles in several atmospheric processes and adversely impact human health. This study examines the key structural units present in water- and methanol-soluble organic carbon (WSOC, MSOC) fraction of OA from emission sources (traffic and biomass cooking) and an urban background location in India. Proton nuclear magnetic resonance (1H NMR) spectroscopy was employed to assess the distribution of non-exchangeable proton structural groups of the OAs. Organic carbon, elemental carbon, black carbon, and water-soluble organic carbon (WSOC) analyses were also conducted. The 1H NMR analysis corroborated that the WSOC and MSOC fractions hold similar 1H structural groups; however, they differ in their relative distribution and absolute concentrations across the ambient locations and source emissions. The relative contribution of the proton structural groups to OA was in the order C-H > H-C-C=> H-C-O > Ar-H. The aliphatic concentration was lower in the morning tunnel entry aerosols when compared to other tunnel aerosols, whereas the unsaturated structures (H-C-C= ) were present in all the tunnel aerosols within a range of 47.2-62.3 µmol/m3. The aromatic groups were the maximum in the firewood aerosols, about 1.4 and 3.7 times higher than the crop residue and the mixed fuel aerosols, respectively. The total functional groups, i.e., the sum of all the observed groups, significantly correlated with C-H (r = 0.96) and WSOC (r = 0.7), suggesting the higher contribution of aliphatic groups in the WSOC fraction. WSOC examined in this study fits well in the established 1H NMR source identification fingerprints of urban aerosols. However, biomass cooking aerosols do not fit the established biomass burning organic aerosols (BBOAs) boundaries, exhibiting a smaller relative contribution of carbon-oxygen double bonds and a less oxidised character than open-field burning. Our results provide essential insights into the nature of urban atmospheric, near-traffic and biomass cooking OAs in India.

Influence of aerosol radiative effects on surface temperature and snow melt in the Himalayan region.

Recent increases in surface temperature and snow melt acceleration in the Himalayan region are influenced by many factors. Here we investigate the influence of absorbing aerosols, including black carbon and dust, on surface temperature and snow melt in western, central, and eastern parts of the India-Nepal Himalayan region (INHR). We compare 40-y simulations (1971-2010) one with all evolving forcing agents representative of a present-day aerosol scenario, compared to a low aerosol forcing scenario. The difference between these scenarios shows a significant increase in surface air temperature, with higher warming in parts of Western and Central Himalaya (~0.2-2 °C) in the months of April and May. Higher absorbing aerosol (BC and dust abundance) both at the surface and in the atmospheric column, in the present-day aerosol simulations, led to increases in atmospheric radiative forcing and surface shortwave heating rate forcing (SWHRF), compared to the low aerosol forcing case. Therefore, the absorbing aerosols cause anomalous atmospheric heat energy transfer to land due to high surface SWHRF and changes in surface energy flux, leading to snow melt. The present model version did not parameterize snow albedo feedback, which would increase the magnitudes of the changes simulated here.

Global health burden of ambient PM2.5 and the contribution of anthropogenic black carbon and organic aerosols.

Chronic exposure to fine particulate matter (PM2.5) poses a major global health risk, commonly assessed by assuming equivalent toxicity for different PM2.5 constituents. We used a data-informed global atmospheric model and recent exposure-response functions to calculate the health burden of ambient PM2.5 from ten source categories. We estimate 4.23 (95% confidence interval 3.0-6.14) million excess deaths annually from the exposure to ambient PM2.5. We distinguished contributions and major sources of black carbon (BC), primary organic aerosols (POA) and anthropogenic secondary organic aerosols (aSOA). These components make up to ∼20% of the total PM2.5 in South and East Asia and East Africa. We find that domestic energy use by the burning of solid biofuels is the largest contributor to ambient BC, POA and aSOA globally. Epidemiological and toxicological studies indicate that these compounds may be relatively more hazardous than other PM2.5 compounds such as soluble salts, related to their high potential to inflict oxidative stress. We performed sensitivity analyses by considering these species to be more harmful compared to other compounds in PM2.5, as suggested by their oxidative potential using a range of potential relative risks. These analyses show that domestic energy use emerges as the leading cause of excess mortality attributable to ambient PM2.5, notably in Asia and Africa. We acknowledge the uncertainties inherent in our assumed enhanced toxicity of the anthropogenic organic and BC aerosol components, which suggest the need to better understand the mechanisms and magnitude of the associated health risks and the consequences for regulatory policies. However our assessment of the importance of emissions from domestic energy use as a cause of premature mortality is robust to a range of assumptions about the magnitude of the excess risk.

COVID-19 lockdown closures of emissions sources in India: Lessons for air quality and climate policy.

Reduced anthropogenic activities during the COVID-19 pandemic caused significant reductions in ambient fine particulate matter (PM2.5), SO2 and NOx concentrations across India. However, tropospheric O3 concentrations spiked over many urban regions. Moreover, reductions in SO2 and NOx (atmospheric cooling agents) emissions unmask heating exerted by warming forcers. Basing governmental guidelines, we model daily emissions reductions in CO2 and short-lived climate forcers (SLCFs) during different lockdown periods using bottom-up regional emission inventory. The transport sector, with maximum level of closure, followed by power plants and industry reduced nearly -50% to -75% emissions of CO2, primary PM2.5, SO2 and NOx, while warming SLCFs (black carbon, CH4, CO and non-methane VOCs) showed insignificant reduction from continuing activity in residential and agricultural sectors. Consequently, the analysis indicates that reduction in the emission ratio of NOx to NMVOC coincided spatially with observed increases in O3, consistent with reduced uptake of O3 from night-time NOx reactions. Also, similar reductions, occurring for longer timescales (say, a year), can potentially increase the annual warming rate over India from the positive regional temperature response, estimated using climate metric. Further, by linking ongoing policies to sectoral reductions during lockdown, this study shows that the relative pacing of implementation among policies is crucial to avoid counter-productive results. A key policy recommendation is introduction and improving efficacy of programs targeting reduction of NMVOC and warming SLCF emissions (shifts away from biomass cooking technologies, household electrification and curbing open burning of crop residues), must precede the strengthening of policies targeting NOx and SO2 dominated sectors.

Outdoor air pollution in India is not only an urban problem.

Urban outdoor air pollution in the developing world, mostly due to particulate matter with diameters smaller than 2.5 µm (PM2.5), has been highlighted in recent years. It leads to millions of premature deaths. Outdoor air pollution has also been viewed mostly as an urban problem. We use satellite-derived demarcations to parse India's population into urban and nonurban regions, which agrees with the census data. We also use the satellite-derived surface PM2.5 levels to calculate the health impacts in the urban and nonurban regions. We show that outdoor air pollution is just as severe in nonurban regions as in the urban regions of India, with implications to monitoring, regulations, health, and policy.

Origin and properties of soluble brown carbon in freshly emitted and aged ambient aerosols over an urban site in India.

This work investigates the absorption properties of soluble brown carbon (BrC), extracted in methanol and water, from ambient aerosol (PM10) samples, collected over an urban background site in Mumbai, India. The diurnal variability was investigated in samples collected in the morning (7-11 a.m.) and afternoon (12-4 p.m.) periods. Absorption properties of BrC (in the 300-600-nm wavelength range) were measured in filter extracts of water-soluble organic carbon (WSOC) and methanol-soluble organic carbon (MSOC). WSOC and MSOC accounted for on average 52% and 77%, respectively, of the measured OC, potentially indicating unextracted BrC and rendering these values the lower bound. Compared with afternoon samples, the morning samples of MSOC and WSOC had increased BrC concentrations and absorption coefficients (babs365; 40%-65%). The correlation between babs365 and EC, ns-K+, and NO3- in the morning samples indicated contributions from primary sources, including both biomass and vehicular sources. The decreased babs365 in the afternoon samples was partly explained by mixing layer dilution, accompanied by a reduction in the concentrations of primary aerosol constituents. Furthermore, in the afternoon samples, 1HNMR spectroscopy revealed the presence of more oxidized functional groups and significantly higher OC/EC and WSOC/OC ratios, indicating the greater aging of afternoon aerosol. The MAC365 (m2gC-1) for both WSOC and MSOC extracts decreased significantly by 20%-34% in the afternoon samples compared with the morning samples, indicating degradation in the absorption properties of the particles and potentially a change in the constituent BrC chromophores.

Premature Mortality Due to PM2.5 Over India: Effect of Atmospheric Transport and Anthropogenic Emissions.

The annual premature mortality in India attributed to exposure to ambient particulate matter (PM2.5) exceeds 1 million (Cohen et al., 2017, https://doi.org/10.1016/S0140-6736(17)30505-6). Studies have estimated sector-specific premature mortality from ambient PM2.5 exposure in India and shown residential energy use is the dominant contributing sector. In this study, we estimate the contribution of PM2.5 and premature mortality from six regions of India in 2012 using the global chemical-transport model. We calculate how premature mortality in India is determined by the transport of pollution from different regions. Of the estimated 1.1 million annual premature deaths from PM2.5 in India, about ~60% was from anthropogenic pollutants emitted from within the region in which premature mortality occurred, ~19% was from transport of anthropogenic pollutants between different regions within India, ~16% was due to anthropogenic pollutants emitted outside of India, and ~4% was associated with natural PM2.5 sources. The emissions from Indo Gangetic Plain contributed to ~46% of total premature mortality over India, followed by Southern India (13%). Indo Gangetic Plain also contributed (~8%) to the most premature mortalities in other regions of India through transport. More than 50% of the premature mortality in Northern, Eastern, Western, and Central India was due to transport of PM2.5 from regions outside of these individual regions. Our results indicate that reduction in anthropogenic emissions over India, as well as its neighboring regions, will be required to reduce the health impact of ambient PM2.5 in India.

Aerosol Optical Depth Over India.

Tropospheric aerosol optical depth (AOD) over India was simulated by Goddard Earth Observing System (GEOS)-Chem, a global 3-D chemical-transport model, using SMOG (Speciated Multi-pOllutant Generator from Indian Institute of Technology Bombay) and GEOS-Chem (GC) (current inventories used in the GEOS-Chem model) inventories for 2012. The simulated AODs were ~80% (SMOG) and 60% (GC) of those measured by the satellites (Moderate Resolution Imaging Spectroradiometer and Multi-angle Imaging SpectroRadiometer). There is no strong seasonal variation in AOD over India. The peak AOD values are observed/simulated during summer. The simulated AOD using SMOG inventory has particulate black and organic carbon AOD higher by a factor ~5 and 3, respectively, compared to GC inventory. The model underpredicted coarse-mode AOD but agreed for fine-mode AOD with Aerosol Robotic Network data. It captured dust only over Western India, which is a desert, and not elsewhere, probably due to inaccurate dust transport and/or noninclusion of other dust sources. The calculated AOD, after dust correction, showed the general features in its observed spatial variation. Highest AOD values were observed over the Indo-Gangetic Plain followed by Central and Southern India with lowest values in Northern India. Transport of aerosols from Indo-Gangetic Plain and Central India into Eastern India, where emissions are low, is significant. The major contributors to total AOD over India are inorganic aerosol (41-64%), organic carbon (14-26%), and dust (7-32%). AOD over most regions of India is a factor of 5 or higher than over the United States.

Source influence on emission pathways and ambient PM2.5 pollution over India (2015-2050).

India is currently experiencing degraded air quality, and future economic development will lead to challenges for air quality management. Scenarios of sectoral emissions of fine particulate matter and its precursors were developed and evaluated for 2015-2050, under specific pathways of diffusion of cleaner and more energy-efficient technologies. The impacts of individual source sectors on PM2.5 concentrations were assessed through systematic simulations of spatially and temporally resolved particulate matter concentrations, using the GEOS-Chem model, followed by population-weighted aggregation to national and state levels. We find that PM2.5 pollution is a pan-India problem, with a regional character, and is not limited to urban areas or megacities. Under present-day emissions, levels in most states exceeded the national PM2.5 annual standard (40 µg m-3). Sources related to human activities were responsible for the largest proportion of the present-day population exposure to PM2.5 in India. About 60 % of India's mean population-weighted PM2.5 concentrations come from anthropogenic source sectors, while the remainder are from "other" sources, windblown dust and extra-regional sources. Leading contributors are residential biomass combustion, power plant and industrial coal combustion and anthropogenic dust (including coal fly ash, fugitive road dust and waste burning). Transportation, brick production and distributed diesel were other contributors to PM2.5. Future evolution of emissions under regulations set at current levels and promulgated levels caused further deterioration of air quality in 2030 and 2050. Under an ambitious prospective policy scenario, promoting very large shifts away from traditional biomass technologies and coal-based electricity generation, significant reductions in PM2.5 levels are achievable in 2030 and 2050. Effective mitigation of future air pollution in India requires adoption of aggressive prospective regulation, currently not formulated, for a three-pronged switch away from (i) biomass-fuelled traditional technologies, (ii) industrial coal-burning and (iii) open burning of agricultural residue. Future air pollution is dominated by industrial process emissions, reflecting larger expansion in industrial, rather than residential energy demand. However, even under the most active reductions envisioned, the 2050 mean exposure, excluding any impact from windblown mineral dust, is estimated to be nearly 3 times higher than the WHO Air Quality Guideline.

Aerosols cause intraseasonal short-term suppression of Indian monsoon rainfall.

Aerosol abundance over South Asia during the summer monsoon season, includes dust and sea-salt, as well as, anthropogenic pollution particles. Using observations during 2000-2009, here we uncover repeated short-term rainfall suppression caused by coincident aerosols, acting through atmospheric stabilization, reduction in convection and increased moisture divergence, leading to the aggravation of monsoon break conditions. In high aerosol-low rainfall regions extending across India, both in deficient and normal monsoon years, enhancements in aerosols levels, estimated as aerosol optical depth and absorbing aerosol index, acted to suppress daily rainfall anomaly, several times in a season, with lags of a few days. A higher frequency of prolonged rainfall breaks, longer than seven days, occurred in these regions. Previous studies point to monsoon rainfall weakening linked to an asymmetric inter-hemispheric energy balance change attributed to aerosols, and short-term rainfall enhancement from radiative effects of aerosols. In contrast, this study uncovers intraseasonal short-term rainfall suppression, from coincident aerosol forcing over the monsoon region, leading to aggravation of monsoon break spells. Prolonged and intense breaks in the monsoon in India are associated with rainfall deficits, which have been linked to reduced food grain production in the latter half of the twentieth century.

Estimation of critical supersaturation solubility ratio for predicting diameters of dry particles prepared by air-jet atomization of solutions.

Air-jet atomization of solution into droplets followed by controlled drying is increasingly being used for producing nanoparticles for drug delivery applications. Nanoparticle size is an important parameter that influences the stability, bioavailability and efficacy of the drug. In air-jet atomization technique, dry particle diameters are generally predicted by using solute diffusion models involving the key concept of critical supersaturation solubility ratio (Sc) that dictates the point of crust formation within the droplet. As no reliable method exists to determine this quantity, the present study proposes an aerosol based method to determine Sc for a given solute-solvent system and process conditions. The feasibility has been demonstrated by conducting experiments for stearic acid in ethanol and chloroform as well as for anti-tubercular drug isoniazid in ethanol. Sc values were estimated by combining the experimentally observed particle and droplet diameters with simulations from a solute diffusion model. Important findings of the study were: (i) the measured droplet diameters systematically decreased with increasing precursor concentration (ii) estimated Sc values were 9.3±0.7, 13.3±2.4 and 18±0.8 for stearic acid in chloroform, stearic acid and isoniazid in ethanol respectively (iii) experimental results pointed at the correct interfacial tension pre-factor to be used in theoretical estimates of Sc and (iv) results showed a consistent evidence for the existence of induction time delay between the attainment of theoretical Sc and crust formation. The proposed approach has been validated by testing its predictive power for a challenge concentration against experimental data. The study not only advances spray-drying technique by establishing an aerosol based approach to determine Sc, but also throws considerable light on the interfacial processes responsible for solid-phase formation in a rapidly supersaturating system. Until satisfactory theoretical formulae for predicting CSS are developed, the present approach appears to offer the best option for engineering nanoparticle size through solute diffusion models.

Contrasting influences of aerosols on cloud properties during deficient and abundant monsoon years.

Direct aerosol radiative forcing facilitates the onset of Indian monsoon rainfall, based on synoptic scale fast responses acting over timescales of days to a month. Here, we examine relationships between aerosols and coincident clouds over the Indian subcontinent, using observational data from 2000 to 2009, from the core monsoon region. Season mean and daily timescales were considered. The correlation analyses of cloud properties with aerosol optical depth revealed that deficient monsoon years were characterized by more frequent and larger decreases in cloud drop size and ice water path, but increases in cloud top pressure, with increases in aerosol abundance. The opposite was observed during abundant monsoon years. The correlations of greater aerosol abundance, with smaller cloud drop size, lower evidence of ice processes and shallower cloud height, during deficient rainfall years, imply cloud inhibition; while those with larger cloud drop size, greater ice processes and a greater cloud vertical extent, during abundant rainfall years, suggest cloud invigoration. The study establishes that continental aerosols over India alter cloud properties in diametrically opposite ways during contrasting monsoon years. The mechanisms underlying these effects need further analysis.