An early South Asian dust storm during March 2012 and its impacts on Indian Himalayan foothills: a case study

Aerosol-CCN characteristics and dynamics associated with a pre-monsoon dust storm over a high-altitude site in Western Ghats, India

Aerosol-CCN characteristics and dynamics during a pre-monsoon dust storm (April 6-11, 2015) over a high-altitude site ((17.92°N, 73.66°E, and 1348 m above mean sea level (MSL)) in Western Ghats, India, has been studied using ground-based observations, satellite, and reanalysis datasets. Spatial distribution of dust surface mass concentration along with the back trajectory analysis showed the Arabian Desert area (Rub-Al-khali desert) as the source region and strong westerly winds transported the dust particles toward the Indian subcontinent. High values noticed in the surface PM10 (PM2.5), i.e., ~ 450 (~ 130) µg m-3, MODIS AOD550nm (0.6), and MERRA 2 dust surface mass concentration (5 × 10-7 kg m-3) along MODIS true color images confirmed the dust storm event on April 6, 2015 over the observational site. Size-segregated aerosol number concentration measured from ground-based observations showed the dominance of Aitken, accumulation, and coarse mode particles during dust period. CCN concentrations at 0.1, 0.3, 0.5, 0.7, and 0.9% SS were analyzed. A low value of CCN concentration and activation fraction (~ 0.3) near surface was noticed during dust storm day, suggesting insoluble mineral dust particle being transported. Analyzed vertical velocity during pre-dust period showed downdraft between 900 and 750 hPa, suggesting dust transport from upper altitudes toward the observational site. WRF-Chem model simulation also captured the dust storm event, and the results are in good agreement with the observation with a significance of 95% confidence level.

Temporal and Spatial Variations of Satellite-Based Aerosol Optical Depths, Angstrom Exponent, Single Scattering Albedo, and Ultraviolet-Aerosol Index over Five Polluted and Less-Polluted Cities of Northern India: Impact of Urbanization and Climate Change

It is widely acknowledged that factors such as population growth, urbanization's quick speed, economic growth, and industrialization all have a role in the atmosphere's rising aerosol concentration. In the current work, we assessed and discussed the findings of a thorough analysis of the temporal and spatial variations of satellite-based aerosol optical parameters such as Aerosol Optical Depth (AOD), Angstrom Exponent (AE), Single Scattering Albedo (SSA), and Ultraviolet-Aerosol Index (UV-AI), and their concentration have been investigated in this study over five polluted and less-polluted cities of northern India during the last decade 2011–2020. The temporal variation of aerosol optical parameters for AOD ranging from 0.2 to 1.8 with decadal mean 0.86 ± 0.36 for Patna region shows high value with a decadal increasing trend over the study area due to rise in aerosols combustion of fossil fuels, huge vehicles traffic, and biomass over the past ten years. The temporal variation of AE ranging from 0.3 to 1.8 with decadal mean 1.72 ± 0.11 for Agra region shows high value as compared to other study areas, which indicates a comparatively higher level of fine-mode aerosols at Agra. The temporal variation of SSA ranging from 0.8 to 0.9 with decadal mean 0.92 ± 0.02 for SSA shows no discernible decadal pattern at any of the locations. The temporal variation of UV-AI ranging from -1.01 to 2.36 with decadal mean 0.59 ± 0.06 for UV-AI demonstrates a rising tendency, with a noticeable rise in Ludhiana, which suggests relative dominance of absorbing dust aerosols over Ludhiana. Further, to understand the impact of emerging activities, analyses were done in seasonality. For this aerosol climatology was derived for different seasons, i.e., Winter, Pre-Monsoon, Monsoon, and Post-Monsoon. High aerosol was observed in Winter for the study areas Patna, Delhi, and Agra which indicated the particles major dominance of burning aerosol from biomass; and the worst in Monsoon and Post-Monsoon for the Tehri Garhwal and Ludhiana study areas which indicated most of the aerosol concentration is removed by rainfall. After that, we analyzed the correlation among all the parameters to better understand the temporal and spatial distribution characteristics of aerosols over the selected region. The value of r for AOD (550 nm) for regions 2 and 1(0.80) shows a strong positive correlation and moderately positive for the regions 3 and 1 (0.64), mostly as a result of mineral dust carried from arid western regions. The value of r for AE (412/470 nm) for region 3 and (0.40) shows a moderately positive correlation, which is the resultant of the dominance of fine-mode aerosol and negative for the regions 5 and 1 (− 0.06). The value of r for SSA (500 nm) for regions 2 and 1 (0.63) shows a moderately positive correlation, which explains the rise in big aerosol particles, which scatters sun energy more efficiently, and the value of r for UV-AI for regions 1 and 2 shows a strong positive correlation (0.77) and moderately positive for the regions 3 and 1 (0.46) which indicates the absorbing aerosols present over the study region.

Climatology and model prediction of aerosol optical properties over the Indo-Gangetic Basin in north India

The current research focuses on the use of different simulation techniques in the future prediction of the crucial aerosol optical properties over the highly polluted Indo-Gangetic Basin in the northern part of India. The time series model was used to make an accurate forecast of aerosol optical depth (AOD) and angstrom exponent (AE), and the statistical variability of both cases was compared in order to evaluate the effectiveness of the model (training and validation). For this, different models were used to simulate the monthly average AOD and AE over Jaipur, Kanpur and Ballia during the period from 2003 to 2018. Further, the study was aimed to construct a comparative model that will be used for time series statistical analysis of MODIS-derived AOD₅₅₀ and AE_412-470. This will provide a more comprehensive information about the levels of AOD and AE that will exist in the future. To test the validity and applicability of the developed models, root-mean-square error (RMSE), mean absolute error (MAE), mean absolute percent error (MAPE), fractional bias (FB), and Pearson coefficient (r) were used to show adequate accuracy in model performance. From the observation, the monthly mean values of AOD and AE were found to be nearly similar at Kanpur and Ballia (0.62 and 1.26) and different at Jaipur (0.25 and 1.14). Jaipur indicates that during the pre-monsoon season, the AOD mean value was found to be highest (0.32 ± 0.15), while Kanpur and Ballia display higher AOD mean values during the winter season (0.72 ± 0.26 and 0.83 ± 0.32, respectively). Among the different methods, the autoregressive integrated moving average (ARIMA) model was found to be the best-suited model for AOD prediction at Ballia based on fitted error (RMSE (0.22), MAE (0.15), MAPE (24.55), FB (0.05)) and Pearson coefficient r (0.83). However, for AE, best prediction was found at Kanpur based on RMSE (0.24), MAE (0.21), MAPE (22.54), FB (-0.09) and Pearson coefficient r (0.82).

Identification of key aerosol types and mixing states in the central Indian Himalayas during the GVAX campaign: the role of particle size in aerosol classification

Studies in aerosol properties, types and sources in the Himalayas are important for atmospheric and climatic issues due to high aerosol loading in the neighboring plains. This study uses in situ measurements of aerosol optical and microphysical properties obtained during the Ganges Valley Aerosol eXperiment (GVAX) at Nainital, India over the period June 2011-March 2012, aiming to identify key aerosol types and mixing states for two particle sizes (PM₁ and PM₁₀). Using a classification matrix based on SAE vs. AAE thresholds (scattering vs. absorption Ångström exponents, respectively), seven aerosol types are identified, which are highly dependent on particle size. An aerosol type named "large/BC mix" dominates in both PM₁ (45.4%) and PM₁₀ (46.9%) mass, characterized by aged BC mixed with other aerosols, indicating a wide range of particle sizes and mixing states. Small particles with low spectral dependence of the absorption (AAE < 1) account for 31.6% and BC-dominated aerosols for 14.8% in PM₁, while in PM₁₀, a large fraction (39%) corresponds to "large/low-absorbing" aerosols and only 3.9% is characterized as "BC-dominated". The remaining types consist of mixtures of dust and local emissions from biofuel burning and display very small fractions. The main optical properties e.g. spectral scattering, absorption, single scattering albedo, activation ratio, as well as seasonality and dependence on wind speed and direction of identified types are examined, revealing a large influence of air masses originating from the Indo-Gangetic Plains. This indicates that aerosols over the central Himalayas are mostly composed by mixtures of processed and transported polluted plumes from the plains. This is the first study that identifies key aerosol populations in the central Indian Himalayas based on in situ measurements and the results are highly important for aerosol-type inventories, chemical transport models and reducing the uncertainty in aerosol radiative forcing over the third pole.

Improved air quality during COVID-19 at an urban megacity over the Indo-Gangetic Basin: From stringent to relaxed lockdown phases

The enforced lockdown amid COVID-19 pandemic eased anthropogenic activities across India. The satellite-derived aerosol optical depth (AOD) and absorption AOD showed a significant reduction of ~30% over the Indo-Gangetic Basin (IGB) in north India during the lockdown period in 2020 with respect to the previous year 2019, when no such lockdown was in effect. Further, near-surface air pollutants were investigated at an urban megacity Delhi during 01 March to 31 May 2020. Except O₃, a drastic reduction in PM₁₀, PM_2.5, NO, NO₂ and CO concentrations were observed by ~58%, 47%, 76%, 68% and 58%, respectively during the lockdown period of 2020 as compared to 2019. While, O₃ was low in the initial phase and gradually increased with progression of lockdown phases, the mean O₃ during the entire lockdown period was nearly similar in both the years. Though, all the measured pollutants showed significant reduction during the entire lockdown, a phase-wise enhancement, associated with the conditional relaxations was observed in their concentrations. Thus, the present results may help, not only to assess the impact of outbreak on air quality, but also in designing the mitigation policies in urban megacities in more efficient ways to combat the air pollution problems.

Identifying sources of dust aerosol using a new framework based on remote sensing and modelling

Dust particles are transported globally. Dust storms can adversely impact both human health and the environment, but they also impact transportation infrastructure, agriculture, and industry, occasionally severely. The identification of the locations that are the primary sources of dust, especially in arid and semi-arid environments, remains a challenge as these sites are often in remote or data-scarce regions. In this study, a new method using state-of-the-art machine-learning algorithms - random forest (RF), support vector machines (SVM), and multivariate adaptive regression splines (MARS) - was evaluated for its ability to spatially model the distribution of dust-source potential in eastern Iran. To accomplish this, empirically identified dust-source locations were determined with the ozone monitoring instrument aerosol index and the Moderate-Resolution Imaging Spectroradiometer (MODIS) Deep Blue aerosol optical thickness methods. The identified areas were divided into training (70%) and validation (30%) sets. Measurements of the conditioning factors (lithology, wind speed, maximum air temperature, land use, slope angle, soil, rainfall, and land cover) were compiled for the study area and predictive models were developed. The area-under-the-receiver operating characteristics curve (AUC) and true-skill statistics (TSS) were used to validate the maps of the models' predictions. The results show that the RF algorithm performed best (AUC = 89.4% and TSS = 0.751), followed by the SVM (AUC = 87.5%, TSS = 0.73) and the MARS algorithm (AUC = 81%, TSS = 0.69). The results of the RF indicated that wind speed and land cover are the most important factors affecting dust generation. The region of highest dust-source potential that was identified by the RF is in the eastern parts of the study region. This model can be applied to other arid and semi-arid environments that experience dust storms to promote management that prevents desertification and reduces dust production.

Impact of dust storm on phytoplankton bloom over the Arabian Sea: a case study during March 2012

Dust storms affect the primary productivity of the ocean by providing necessary micronutrients to the surface layer. One such dust storm during March 2012 led to a substantial reduction in visibility and enhancement in aerosol optical depth (AOD) up to ~ 0.8 (AOD increased from 0.1 to 0.9) over the Arabian Sea. We explored the possible effects and mechanisms through which this particular dust storm could impact the ocean's primary productivity (phytoplankton concentration), using satellite-borne remote sensors and reanalysis model data (2003-2016). The climatological analyses revealed anomalous March 2012 in terms of dust deposition and enhancement in phytoplankton concentration in the month of March during 2003-2016 over this region. The studied dust storm accounts for increase in the daily average surface dust deposition rate from ~ 3 to ~53 mg m^-2 day^-1, which is followed by a significant enhancement in the chlorophyll-a (Chl_a) concentration (~ 2 to ~9 mg m^-3). We show strong association between a dust storm and an event of anomalously high biological production (with a 4-day forward lag) in the Arabian Sea. We suggest that the increase in biological production results from the superposition of two complementary processes (deposition of atmospheric nutrients and deepening of the mixed layer due to dust-induced sea surface temperature cooling) that enhance nutrient availability in the euphotic layer.

Characterization of aerosol optical properties using multiple clustering techniques over Zanjan, Iran, during 2010-2013

Discrimination of aerosol types is very important, because different aerosols are created from diverse sources having different chemical, physical, and optical properties. In the present study, we have analyzed the seasonal classification of aerosol types by multiple clustering techniques, using AERosol Robotic NETwork (AERONET) data during 2010-2013 over Zanjan, Iran. We found that aerosol optical depth (AOD) showed pronounced seasonal variations of a summer high and winter low. Conversely, the values of the Angstrom exponent (AE) in winter and fall were higher than in spring and summer, which confirmed the presence of fine particles, while the low value of AE in the summer and spring represented the existence of coarse particles. Single Scattering Albedo (SSA) variations revealed the presence of scattering aerosols like dust in spring, summer, and fall while the dominance of absorbing-type aerosols in winter were also observed. The influence of local anthropogenic activities has caused a higher concentration of fine aerosols, and a higher fine mode fraction (FMF) of AOD in winter was recorded. Classification of aerosol types was carried out by analyzing different aerosol properties such as AOD versus AE, extinction Angstrom exponent (EAE) versus SSA, EAE versus absorption Angstrom exponent (AAE), FMF AOD versus EAE, and SSA versus FMF AOD. The analysis revealed the presence of dust and polluted dust in spring, summer, and fall in the atmosphere of Zanjan. Urban/industrial aerosols were available in all seasons, especially in fall and winter. The mixed aerosols existed in all seasons over the study location; however, no biomass burning aerosols were found. The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) aerosol subtype profiles showed the dominance of dust and polluted dust in spring and summer. However, the presence of polluted dust and industrial smoke during fall and winter were also noted over the study site.

Chemical characterization of rainwater at a high-altitude site "Nainital" in the central Himalayas, India

The present study investigates the chemical composition of rainwater (RW) from a high-altitude site "Nainital" (1958 m above msl) in the central Himalaya region, to understand the influence of local, regional, and long-range transport of pollutants. A total of 55 (2 in pre-monsoon and 53 in monsoon) RW samples were collected during the study period (June-September 2012) and were analyzed for major anions and cations using an ion chromatograph. The pH of precipitation events ranged from 4.95 to 6.50 (average 5.6 ± 0.3) was observed during the monsoon period (near to the acidic), whereas during the pre-monsoon, the pH was 6.25 ± 0.49 (alkaline) over the study region; it is due the mixture of anthropogenic as well as the natural chemical constituents. The average ionic concentration (sum of measured chemical constituents) was ∼3 times higher during the pre-monsoon (986 ± 101 μeq/1) compared to that in the monsoon season (373 ± 37 μeq/1). This is mainly due to the presence of more natural aerosols in the pre-monsoon season which is also reflected in the pH of rainwater (average 6.25 ± 0.50) as well as ionic concentration. The chemical composition suggests that Ca²⁺ was the major contributor (34%) among cations, followed by Na⁺ (10%), K⁺ (8%), and Mg²⁺ (9%), whereas Cl^-, NO₃^-, and SO₄^2- contributed ∼13, 11, and 9%, respectively, among anions. The average ratio of acidic species (SO₄^2-/NO₃^-) is 1.56, suggesting 61 and 39% contribution of SO₄^2- and NO₃^-, respectively, which is very close to the estimated contribution of H₂SO₄ (60-70%) and HNO₃ (30-40%) in the precipitation samples. Neutralization factors for Ca²⁺, Mg²⁺, and NH₄⁺ in RW at Nainital are 4.94, 1.21, and 0.37, respectively, indicating their crucial role in neutralization of acidic species. The non-sea-salt (NSS) contribution to total Ca²⁺, K⁺, and Mg²⁺ is estimated to be ∼98, 97, and 74%, respectively, suggesting the dominance of crustal sources for cations. In contrast, the NSS contribution to the total Cl^- and SO₄^2- is 16 and 69% indicating their anthropogenic origin, respectively. Principle component analysis also suggests that the first factor (i.e., natural sources, mainly dust, and sea-salts) accounts for ∼33% variance, whereas the second factor (i.e., fossil fuel and biomass burning) accounts for ∼18% variance of the measured ionic composition. The remaining contributions are attributed to the mixed emission sources and transport of pollutants from Indo-Gangetic Plain (IGP) and western parts of India. The results of the present study reveal a significant contribution of crustal and anthropogenic sources in the RW and neutralization processes in the central Himalaya.

Optical and radiative properties of aerosols over Desalpar, a remote site in western India: Source identification, modification processes and aerosol type discrimination

Aerosol optical properties are analyzed for the first time over Desalpar (23.74°N, 70.69°E, 30m above mean sea level) a remote site in western India during October 2014 to August 2015. Spectral aerosol optical depth (AOD) measurements were performed using the CIMEL CE-318 automatic Sun/sky radiometer. The annual-averaged AOD₅₀₀ and Ångström exponent (α_440-870) values are found to be 0.43±0.26 and 0.69±0.39, respectively. On the seasonal basis, high AOD₅₀₀ of 0.45±0.30 and 0.61±0.34 along with low α_440-870 of 0.41±0.27 and 0.41±0.35 during spring (March-May) and summer (June-August), respectively, suggest the dominance of coarse-mode aerosols, while significant contribution from anthropogenic sources is observed in autumn (AOD₅₀₀=0.47±0.26, α_440-870=1.02±0.27). The volume size distribution and the spectral single-scattering albedo also confirm the presence of coarse-mode aerosols during March-August. An overall dominance of a mixed type of aerosols (~56%) mostly from October to February is found via the AOD₅₀₀ vs α_440-870 relationship, while marine aerosols contribute to ~18%. Spectral dependence of α and its second derivative (α') are also used for studying the aerosol modification processes. The average direct aerosol radiative forcing (DARF) computed via the SBDART model is estimated to range from -27.08Wm^-2 to -10.74Wm^-2 at the top of the atmosphere, from -52.21Wm^-2 to -21.71Wm^-2 at the surface and from 10.97Wm^-2 to 26.54Wm^-2 within the atmosphere. This atmospheric forcing translates into heating rates of 0.31-0.75Kday^-1. The aerosol properties and DARF are also examined for different trajectory clusters in order to identify the sources and to assess the influence of long-range transported aerosols over Desalpar.

Aerosol optical properties and radiative effects over Manora Peak in the Himalayan foothills: seasonal variability and role of transported aerosols

The higher altitude regions of Himalayas and Tibetan Plateau are influenced by the dust and black carbon (BC) aerosols from the emissions and long-range transport from the adjoining areas. In this study, we present impacts of advection of polluted air masses of natural and anthropogenic emissions, on aerosol optical and radiative properties at Manora Peak (~2000 m amsl) in central Himalaya over a period of more than two years (February 2006-May 2008). We used the most updated and comprehensive data of chemical and optical properties available in one of the most climatically sensitive region, the Himalaya, to estimate atmospheric radiative forcing and heating rate. Aerosol optical depth (AOD) was found to vary from 0.04 to 0.45 with significantly higher values in summer mainly due to an increase in mineral dust and biomass burning aerosols due to transport. In contrast, single scattering albedo (SSA) varied from 0.74 to 0.88 with relatively lower values during summer, suggesting an increase in absorbing BC and mineral dust aerosols. As a result, a large positive atmospheric radiative forcing (about 28 ± 5 Wm(-2)) and high values of corresponding heating rate (0.80 ± 0.14 Kday(-1)) has been found during summer. During the entire observation period, radiative forcing at the top of the atmosphere varied from -2 to +14 Wm(-2) and from -3 to -50 Wm(-2) at the surface whereas atmospheric forcing was in the range of 3 to 65 Wm(-2) resulting in a heating rate of 0.1-1.8 Kday(-1).