Aerosol Optical Depth Over India

A review of quantification methods for light absorption enhancement of black carbon aerosol

Black carbon (BC) is a distinct type of carbonaceous aerosol that has a significant impact on the environment, human health, and climate. A non-BC material coating on BC can alter the mixing state of the BC particles, which considerably enhances the mass absorption efficiency of BC by directing more energy toward the BC cores (lensing effect). A lot of methods have been reported for quantifying the enhancement factor (Eabs), with diverse results. However, to the best of our knowledge, a comprehensive review specific to the quantification methods for Eabs has not been systematically performed, which is unfavorable for the evaluation of obtained results and subsequent radiative forcing. In this review, quantification methods are divided into two broad categories, direct and indirect, depending on whether experimental removal of the coating layer from an aged carbonaceous particle is required. The direct methods described include thermal peeling, solvent dissolution, and optical virtual exfoliation, while the indirect methods include intercept-linear regression fitting, minimum R squared, numerical simulation, and empirical value. We summarized the principles, procedures, virtues, and limitations of the major Eabs quantification methods and analyzed the current problems in the determination of Eabs. We pointed out what breakthroughs are needed to improve or innovate Eabs quantification methods, particularly regarding the need to avoid the influence of brown carbon, develop a broadband Eabs quantification scheme, quantify the Eabs values for the emissions of low-efficiency combustions, measure the Eabs of particles in a high-humidity environment, design a real-time monitor of Eabs by a proper combination of mature techniques, and make more use of artificial intelligence for better Eabs quantification. This review deepens the understanding of Eabs quantification methods and benefits the estimation of the contribution of BC to radiative forcing using climate models.

Investigating changes in atmospheric aerosols properties over the Indo-Gangetic Plain during different phases of COVID-19-induced lockdowns

Impact of COrona VIrus Diseases 2019 (COVID-19) restrictive measures on aerosol optical depth (AOD) and black carbon (BC) concentration is investigated for the western, central, and eastern Indo-Gangetic Plain (IGP) using satellite-based observations. Due to COVID-19-induced lockdown measures, a noticeable decline in AOD and BC concentrations was observed across the IGP when compared to pre-lockdown period of 2020 and the lockdown concurrent period of 2015-2019. During the total lockdown period, a maximum drop in AOD and BC was observed in the central IGP (26.5 % and 10.1 %), followed by western IGP (24.9% and 5.2%) and eastern IGP (23.2 % and 4.9 %) with respect to the same period of 2015-2019. We have removed seasonal influences on aerosol properties during the COVID-19 lockdown, by taking average seasonal variations during the period of 2015-2019 as reference and projecting the hypothetical AOD and BC for the lockdown period under normal scenario. The difference between the hypothetical AOD and BC (under normal scenario) and the retrieved AOD and BC for the lockdown period is the absolute percentage change in AOD and BC concentration due to the lockdown alone. This elimination of seasonal influence is a novel approach. Central IGP showed an absolute decrease in AOD and BC of 38.5% and 18.2% during the lockdown period followed by western IGP (34.6% and 7.7%) and eastern IGP (25.9% and 11.5%). The observed absolute reduction in AOD, 26-39 %, is significantly higher than the global average reduction in AOD of 2-5%. CALIPSO-derived aerosol sub-types over major location of the western, central, and eastern IGP suggests prevalence of anthropogenic activities during pre- and post-lockdown periods. During the lockdown, IGP was influenced by aerosols from natural sources, with mineral dust and polluted dust in the western and central IGP, and aerosols from marine regions in the eastern IGP. Replenishment of aerosols within the boundary layer were far quicker when compared to total column during post-lockdown. Overall, the study reveals a reduction in anthropogenic emissions during the COVID-19-induced lockdowns, leading to temporary improvements in air quality over the IGP. Our study presents a comprehensive analysis of COVID-19 lockdown impact on aerosols properties over the IGP and highlights unprecedented reductions in AOD (~ 40 %) and BC (~ 20 %), due to imposition of lockdown and subsequent cessation of aerosol sources, by removing seasonal influences.

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

Fine particulate matter (PM_2.5) 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 PM_2.5 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 PM_2.5, 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 PM_2.5 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 PM_2.5-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 PM_2.5 (>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 PM_2.5 mass and improve population health by reducing emissions from traditional energy sources across multiple sectors in South Asia.

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.

Air quality trends in rural India: analysis of NO2 pollution using satellite measurements

India is a country with more than 67% of its population (947 million) residing in rural areas and 33% in urban areas (472 million) as of 2020. Therefore, health of the people living in rural India is very important for its future development plans, economy and growth. Here, we analyse the rural air quality using satellite measurements of NO₂ in India, as the sources of NO₂ are well connected to the industrial and economic uplift of a nation. Our analyses for the rural regions show distinct seasonal changes with the highest value (2.0 × 10¹⁵ molecules per cm²) in winter and the lowest in monsoon (1.5 × 10¹⁵ molecules per cm²) seasons. About 41% of the total NO₂ pollution in India is from its rural sources, but 59% of the urban sources were focused in the past studies. In addition, around 45% of the rural NO₂ pollution is due to road transport, whereas more than 90% of it in urban India comes from the power sector. Our assessment shows that the NO₂ exposure in rural regions is as serious as that in urban areas, indicating the need for more effective reduction of population exposure and protection of public health. Henceforth, this study reveals that rural India is gradually getting polluted from its nearby regions as well as from the new sources within. This is a big concern for the public health of the large rural population of India.

Analysis and Variation of the Maiac Aerosol Optical Depth in Underexplored Urbanized Area of National Capital Region, India

Aerosol monitoring is the emerging application field of satellite remote sensing. As a satellite-based indicator of aerosol concentration, aerosol optical depth (AOD) can aid in assessing the crucial effects of aerosols on the global environment. Among various satellite-based aerosol product, Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 (C6), Multiangle Implementation of Atmospheric Correction (MAIAC) aerosol product (1 km resolution) has still untapped potential in Indian regions. Considering the importance of regional validation of such high-resolution aerosol product, the present study attempts to fill this gap by validating MAIAC aerosol estimates (AODMAIAC) in highly polluted districts (Faridabad, Ghaziabad, Gautam Budh Nagar, Gurugram) of National Capital Region (NCR) with heavy aerosol loading using limited AErosol RObotic NETwork (AERONET) observations obtained from AERONET sites at Amity University (AU) and Gual Pahari (GP). Such evaluation of satellite-retrieved aerosol product with ground data confirms its practicality based on retrieval errors (Expected Error (EE) values (EE = 0.05 + 15 %*AOD) (EE: 78.85 % at AU, 73.58 % at GP), root mean square error (RMSE) values (RMSE: 0.15 at AU, 0.24 at GP), and correlation coefficient (R) values (R: 0.86 at AU, 0.73 at GP). The seasonal variation in AOD over the study area from 2010-2019 reveals increasing trend of AOD in the monsoon and post-monsoon season due to natural and anthropogenic factors. In addition to contributing to a holistic assessment of MAIAC aerosol estimates as a recent, high-resolution aerosol product, present results provide a basis for further research into NCR aerosols.

Limited influence of irrigation on pre-monsoon heat stress in the Indo-Gangetic Plain

Hot extremes are anticipated to be more frequent and more intense under climate change, making the Indo-Gangetic Plain of India, with a 400 million population, vulnerable to heat stress. Recent studies suggest that irrigation has significant cooling and moistening effects over this region. While large-scale irrigation is prevalent in the Indo-Gangetic Plain during the two major cropping seasons, Kharif (Jun-Sep) and Rabi (Nov-Feb), hot extremes are reported in the pre-monsoon months (Apr-May) when irrigation activities are minimal. Here, using observed irrigation data and regional climate model simulations, we show that irrigation effects on heat stress during pre-monsoon are 4.9 times overestimated with model-simulated irrigation as prescribed in previous studies. We find that irrigation increases relative humidity by only 2.5%, indicating that irrigation is a non-crucial factor enhancing the moist heat stress. On the other hand, we detect causal effects of aerosol abundance on the daytime land surface temperature. Our study highlights the need to consider actual irrigation data in testing model-driven hypotheses related to the land-atmosphere feedback driven by human water management.

Pre-monsoon irrigation over the Indo-Gangetic Plain is often misrepresented in model-driven hypothesis. Using actual census-based data and realistic model simulations, the authors show that irrigation has limited role in enhancing heat stress in the region.

Long-term spatiotemporal trends in aerosol optical depth and its relationship with enhanced vegetation index and meteorological parameters over South Asia

Satellite-based aerosol optical depth (AOD) is columnar light extinction by aerosol absorption and scattering and has become the most important variable for the assessment of the spatiotemporal distribution of aerosols at a regional and global level. In this paper, we have used AOD observations of multiangle imaging spectroradiometer (MISR) from September 2002 to May 2017, moderate resolution imaging spectroradiometer (MODIS) from September 2002 to December 2020, and sea-viewing wide field-of-view sensor (SeaWiFS) from September 2002 to December 2010 over South Asia. We have observed the association of AOD with enhanced vegetation index (EVI) and meteorological variables (temperature (TEMP), wind speed (WS), and relative humidity (RH)) acquired from Giovanni during the period September 2002-December 2020. The satellite observations of Terra-, MISR-, and SeaWiFS-AOD were also compared with Aqua-AOD. The findings show that AOD in eastern Pakistan is higher than in the western Pakistan due to increase in population density and biomass burning. Mean annual peak AOD (˃ 0.7) has been observed over the IGB region because of the significant increase in economical, industrial, and agricultural activities while AOD of ˃ 0.6 is observed over Bangladesh. The lowest mean annual AOD of ˂ 0.3 is observed over northeastern Afghanistan, western Nepal, and Bhutan whereas the AOD of 0.3 is seen over Sri Lanka. The highest seasonal mean AOD of 0.8 has been seen over Bihar, India, and AOD of ~ 0.7 is observed over Bangladesh while the lowest AOD is observed over Afghanistan, Sri Lanka, Nepal, and Bhutan during the winter season. However, the mean AOD over eastern Pakistan is maximum in both monsoon and post-monsoon season but relatively low in pre-monsoon and winter. The highest positive seasonal AOD anomalies were observed over South Asia in winter season followed by post-monsoon, pre-monsoon, and least being monsoon. The higher mean AOD anomaly value is found to be 0.2 over eastern Pakistan and western India. In northeastern Pakistan and central India, AOD and RH are positively correlated (r ˃ 0.54) while negatively correlated over Afghanistan, southwestern region of Pakistan, eastern India, Nepal, Bhutan, and Bangladesh. AOD is negatively correlated (r =  ~  - 0.3) with EVI over eastern Pakistan and western India. The highest correlation coefficient (r) obtained among Terra and Aqua is 0.97, MISR and Aqua is 0.93, and SeaWiFS and Aqua is 0.58 over South Asia.

Retrieval of Black Carbon Absorption Aerosol Optical Depth from AERONET Observations over the World during 2000–2018

Black carbon (BC) absorption aerosol optical depth (AAODBC) defines the contribution of BC in light absorption and is retrievable using sun/sky radiometer measurements provided by Aerosol Robotic Network (AERONET) inversion products. In this study, we utilized AERONET-retrieved depolarization ratio (DPR, δp), single scattering albedo (SSA, ω), and Ångström Exponent (AE, å) of version 3 level 2.0 products as indicators to estimate the contribution of BC to the absorbing fractions of AOD. We applied our methodology to the AERONET sites, including North and South America, Europe, East Asia, Africa, India, and the Middle East, during 2000–2018. The long-term AAODBC showed a downward tendency over Sao Paulo (−0.001 year−1), Thessaloniki (−0.0004 year−1), Beijing (−0.001 year−1), Seoul (−0.0015 year−1), and Cape Verde (−0.0009 year−1) with the highest values over the populous sites. This declining tendency in AAODBC can be attributable to the successful emission control policies over these sites, particularly in Europe, America, and China. The AAODBC at the Beijing, Sao Paulo, Mexico City, and the Indian sites showed a clear seasonality indicating the notable role of residential heating in BC emissions over these sites during winter. We found a higher correlation between AAODBC and fine mode AOD at 440 nm at all sites except for Beijing. High pollution episodes, BC emission from different sources, and aggregation properties seem to be the main drivers of higher AAODBC correlation with coarse particles over Beijing.

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

Chronic exposure to fine particulate matter (PM_2.5) poses a major global health risk, commonly assessed by assuming equivalent toxicity for different PM_2.5 constituents. We used a data-informed global atmospheric model and recent exposure-response functions to calculate the health burden of ambient PM_2.5 from ten source categories. We estimate 4.23 (95% confidence interval 3.0-6.14) million excess deaths annually from the exposure to ambient PM_2.5. 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 PM_2.5 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 PM_2.5 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 PM_2.5, 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 PM_2.5, 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.

Rapid increase in mortality attributable to PM2.5 exposure in India over 1998-2015

PM_2.5-attributable deaths and years of life lost (YLL) due to specific causes during 1998-2015 in India were estimated using the integrated exposure-response (IER) model. The estimated PM_2.5-mortality in India revealed an annual increasing rate of 2.7% during the study period. Spatially, deaths due to the exposure to ambient PM_2.5 concentrated mostly in populated North India, and four northern states contributed 43% to the national PM_2.5-attributable deaths in 2015. PM_2.5-attributable deaths in India increased by 21% during 1998-2015 due to the changes of PM_2.5 only, and deaths due to lung cancer (LC) revealed the largest sensitivity to increasing ambient PM_2.5. The findings of this study suggest that aggressive air pollution control strategies should be implemented in North India due to their dominant contributions to the current health risks. Moreover, the rapid growth of LC related deaths with increasing ambient PM_2.5 should not be neglected.

Spatio-temporal variability of near-surface air pollutants at four distinct geographical locations in Andhra Pradesh State of India

India is highly vulnerable to air pollution in the recent decade, especially urban areas with rapidly growing urbanisation and industrialisation. Here, we present spatio-temporal variability of air pollutants at four distinct locations in Andhra Pradesh State of India. The mean concentrations of air pollutants were generally higher at Visakhapatnam site than Amaravati, Rajahmundry, and Tirumala sites. The mean concentration of particulate matter of diameter less than 2.5 μm (PM_2.5) was higher at Visakhapatnam site (48.5 ± 27.3 μg/m³) by a factor of about 1.6 as compared to Tirumala site (29.5 ± 17 μg/m³). On the contrary, the mean concentrations of oxides of nitrogen (NO_x, 70.3 ± 28.1 μg/m³) and ammonia (NH₃, 20.5 ± 9.2 μg/m³) were higher at Tirumala by a factor of about 1.4 and 1.9, respectively, as compared to Visakhapatnam (49 ± 5 μg/m³ and 10.7 ± 5 μg/m³). This was mainly attributed to higher vehicular emissions at Tirumala site. PM_2.5, carbon monoxide (CO), NOx, and sulfur dioxide (SO₂) showed distinct seasonal variation, with higher concentrations in winter followed by post-monsoon, pre-monsoon and monsoon. The Concentration Weighted Trajectory analysis of PM_2.5 based on 5-days backward air mass trajectories showed that all sites experienced northeast air mass flow indicative of the outflow from Indo-Gangetic Plain, particularly in the post-monsoon and winter seasons. The Continuous Wavelet Transform analysis further showed that higher variations in PM_2.5 concentrations occurring at a regular interval from a week to 16 days at both Tirumala and Visakhapatnam sites, while weekly periods are dominant over Amaravati and Rajahmundry sites with 95% significance during post-monsoon and winter seasons. Overall, our results underline heterogeneity in air pollution emission sources and influx of pollutants from distant sources, which would be useful when formulating the policies and mitigation procedures for this region.

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.

Recent Increase in Winter Hazy Days over Central India and the Arabian Sea

Indian subcontinent is greatly vulnerable to air pollution, especially during the winter season. Here, we use 15 years (2003-2017) of satellite and model reanalysis datasets over India and adjoining Seas to estimate the trend in hazy days (i.e. days with high aerosol loading) during the dry winter season (November to February). The number of hazy days is increasing at the rate of ~2.6 days per year over Central India. Interestingly, this is higher than over the Indo-Gangetic Plain (~1.7 days/year), a well known global hotspot of particulate pollution. Consistent increasing trends in absorbing aerosols are also visible in the recent years. As a result, the estimated atmospheric warming trends over Central India are two-fold higher than that over Indo-Gangetic Plain. This anomalous increment in hazy days over Central India is associated with the relatively higher increase in biomass burning over the region. Moreover, the trend in aerosol loading over the Arabian Sea, which is located downwind to Central India, is also higher than that over the Bay of Bengal during the dry winter season. Our findings not only draw attention to the rapid deteriorating air quality over Central India, but also underline the significance of increasing biomass burning under the recent climate change.

Vulnerability of Indian wheat against rising temperature and aerosols

Potential impacts of change in climate on Indian agriculture may be significantly adverse, if not disastrous. There are projections of potential loss in wheat yield due to the rise in daily minimum (Tmin) and maximum (Tmax) temperature, but only few researchers have considered the extent of such loss on a spatial scale. We therefore, systematically studied the effect of change in Tmax, Tmean (daily average temperature) and Tmin, solar radiation (Srad) and precipitation (RAIN) during wheat growing seasons (from 1986 to 2015) on wheat crop yield over five wheat growing zones across India, taking into account the effect modification by aerosol loading (in terms of aerosol optical depth, 2001-2015). We note that for the entire India, 1 °C rise in Tmean resulted a 7% decrease in wheat yield which varied disproportionately across the crop growing zones by a range of -9% (peninsular zone, PZ) to 4% (northern hills zone, NHZ). The effect of Tmean on wheat yield was identical to the marginal effect of Tmax and Tmin, while 1% increase in Srad enhance wheat yield by 4% for all India with small geographical variations (2-5%), except for the northern hill region (-4%). Rise in 1 °C Tmean exclusively during grain filling duration was noted positive for all the wheat growing regions (0-2%) except over central plain zone (-3%). When estimates of weather variables on wheat yield was combined with the estimated impact of aerosols on weather, the most significant impact was noted over the NHZ (-23%), which otherwise varied from -7% to -4%. Overall, the study brings out the conclusive evidence of negative impact of rising temperature on wheat yield across India, which we found spatially inconsistent and highly uncertain when integrated with the compounding effect of aerosols loading.

Constraining Emissions of Volatile Organic Compounds Over the Indian Subcontinent Using Space-Based Formaldehyde Measurements

India is an air pollution mortality hot spot, but regional emissions are poorly understood. We present a high-resolution nested chemical transport model (GEOS-Chem) simulation for the Indian subcontinent and use it to interpret formaldehyde (HCHO) observations from two satellite sensors (OMI and GOME-2A) in terms of constraints on regional volatile organic compound (VOC) emissions. We find modeled biogenic VOC emissions to be overestimated by ~30-60% for most locations and seasons, and derive a best estimate biogenic flux of 16 Tg C/year subcontinent-wide for year 2009. Terrestrial vegetation provides approximately half the total VOC flux in our base-case inversions (full uncertainty range: 44-65%). This differs from prior understanding, in which biogenic emissions represent >70% of the total. Our derived anthropogenic VOC emissions increase slightly (13-16% in the base case, for a subcontinent total of 15 Tg C/year in 2009) over RETRO year 2000 values, with some larger regional discrepancies. The optimized anthropogenic emissions agree well with the more recent CEDS inventory, both subcontinent-wide (within 2%) and regionally. An exception is the Indo-Gangetic Plain, where we find an underestimate for both RETRO and CEDS. Anthropogenic emissions thus constitute 37-50% of the annual regional VOC source in our base-case inversions and exceed biogenic emissions over the Indo-Gangetic Plain, West India, and South India, and over the entire subcontinent during winter and post-monsoon. Fires are a minor fraction (<7%) of the total regional VOC source in the prior and optimized model. However, evidence suggests that VOC emissions in the fire inventory used here (GFEDv4) are too low over the Indian subcontinent.

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.

How Long should the MISR Record Be when Evaluating Aerosol Optical Depth Climatology in Climate Models?

This study used the nearly continuous 17-year observation record from the Multi- angle Imaging SpectroRadiometer (MISR) instrument on the National Aeronautics and Space Administration (NASA) Terra Earth Observing System satellite to determine which temporal subsets are long enough to define statistically stable speciated aerosol optical depth (AOD) climatologies (i.e., AOD by particle types) for purposes of climate model evaluation. A random subsampling of seasonally averaged total and speciated AOD retrievals was performed to quantitatively assess the statistical stability in the climatology, represented by the minimum record length required for the standard deviation of the subsampled mean AODs to be less than a certain threshold. Our results indicate that the multi-year mean speciated AOD from MISR is stable on a global scale; however, there is substantial regional variability in the assessed stability. This implies that in some regions, even 17 years may not provide a long enough sample to define regional mean total and speciated AOD climatologies. We further investigated the agreement between the statistical stability of total AOD retrievals from MISR and the Moderate Resolution Imaging Spectroradiometer (MODIS), also on the NASA Terra satellite. The difference in the minimum record lengths between MISR and MODIS climatologies of total AOD is less than three years for most of the globe, with the exception of certain regions. Finally, we compared the seasonal cycles in the MISR total and speciated AODs with those simulated by three global chemistry transport models in the regions of climatologically stable speciated AODs. We found that only one model reproduced the observed seasonal cycles of the total and non-absorbing AODs over East China, but the seasonal cycles in total and dust AODs in all models are similar to those from MISR in Western Africa. This work provides a new method for considering the statistical stability of satellite-derived climatologies and illustrates the value of MISR’s speciated AOD data record for evaluating aerosols in global models.