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Purpose of Review: Fine particulate matter (PM2.5) and ground-level ozone (O3) pose a significant risk to human health. The World Health Organization (WHO) has recently revised healthy thresholds for both pollutants. The formation and evolution of PM2.5 and O3 are however governed by complex physical and multiphase chemical processes, and therefore, it is extremely challenging to mitigate both pollutants simultaneously. Here, we review mechanisms and discuss the science-informed pathways for effective and simultaneous mitigation of PM2.5 and O3. Recent Findings: Global warming has led to a general increase in biogenic emissions, which can enhance the formation of O3 and secondary organic aerosols. Reductions in anthropogenic emissions during the COVID-19 lockdown reduced PM2.5; however, O3 was enhanced in several polluted regions. This was attributed to more intense sunlight due to low aerosol loading and non-linear response of O3 to NOx. Such contrasting physical and chemical interactions hinder the formulation of a clear roadmap for clean air over such regions. Summary: Atmospheric chemistry including the role of biogenic emissions, aerosol-radiation interactions, boundary layer, and regional-scale transport are the key aspects that need to be carefully considered in the formulation of mitigation pathways. Therefore, a thorough understanding of the chemical effects of the emission reductions, changes in photolytic rates and boundary layer due to perturbation of solar radiation, and the effect of meteorological/seasonal changes are needed on a regional basis. Statistical emulators and machine learning approaches can aid the cumbersome process of multi-sector multi-species source attribution.

The Arctic climate has changed significantly over the past two to three decades. Aerosols play various roles in the radiative forcing in the Arctic, both directly and indirectly, depending on the changes in loading and composition. However, their observation from the ground or with airborne instruments is challenging and thus measurements are sparse. In this study, total Aerosol Optical Depth (AOD) is determined from top-of-atmosphere reflectance measurements by the Advanced Along-Track Scanning Radiometer (AATSR) aboard ENVISAT over snow and ice in the Arctic using a retrieval called AEROSNOW for the period 2003 to 2011. We use the dual-viewing capability of the AATSR instrument to reduce the impact of surface reflectance on the accuracy of AOD. The AOD is retrieved assuming that the surface reflectance observed by the satellite can be well-parametrized by a bidirectional snow reflectance distribution function, BRDF. The spatial distribution of AODs shows that high values in spring (March, April, May) and lower AOD values in summer (June, July, August) are well captured. Spaceborne AOD values are consistent with colocated AERONET measurements, with no systematic bias as a function of time. The AEROSNOW AOD in the high Arctic ( ≥ 72° N) was validated by comparison with ground-based measurements at the PEARL, OPAL, Hornsund, and Thule stations. The AEROSNOW AOD value is less than 0.15 on average and the regression to AERONET yields a slope of 0.98, a Pearson correlation coefficient of R = 0.86, and an RMSE = 0.01 at a monthly scale, both in spring and summer. These AOD results provide, for the first time, observational insights into the central Arctic with significant spatial and temporal coverage.

Aerosol-cloud-precipitation interaction represents the largest uncertainty in climate change’s current and future understanding. Therefore, aerosol properties affecting the cloud and precipitation formation and their accurate estimation is a first step in developing improved parameterizations for the prognostic climate models. Over the last couple of decades, a commercially available Cloud Condensation Nuclei Counter (CCNC) has been deployed in the field and laboratory for characterizing CCN properties of ambient or atmospherically relevant laboratory-generated aerosols. However, most of the CCN measurements performed in the field are often compounded with the erroneous estimation of CCN concentration and other parameters due to a lack of robust and accurate CCNC calibration. CCNC is not a plug-and-play instrument and requires prudent calibration and operation, to avoid erroneous data and added parameterization uncertainties. In this work, we propose and demonstrate the usability of a global calibration equation derived from CCNC calibration experiments from 8 contrasting global environments. Significant correlationwas observed between the global calibration and each of the 16 individual experiments. A significant improvement in the correlation was observed when the calibration experiments were separated for high altitude measurements. Using these equations, we further derived the effective hygroscopicity parameter and found lower relative uncertainty in the hygroscopicity parameter at higher effective supersaturation. Our results signify that altitude-based pressure change could be of importance for accurate calibration at high altitude locations. Our results are consistent with previous studies emphasizing the criticality of the accurate CCN calibration for the lower supersaturations.

The COVID lockdown presented a unique opportunity to study the anthropogenic emissions from different sectors under relatively cleaner conditions in India. The complex interplays of power production, industry, and transport could be dissected due to the significantly reduced influence of the latter two emission sources. Here, based on measurements of cloud condensation nuclei (CCN) activity and chemical composition of atmospheric aerosols during the lockdown, we report an episodic event showing rapid growth and high hygroscopicity of new aerosol particles formed in the SO2 plume from a large coal-fired power plant. These sulfate-rich particles had high CCN activity and number concentration, indicating high cloud-forming potential. Examining the sensitivity of CCN properties under relatively clean conditions over India provides important new clues to delineate contributions of different anthropogenic emission sectors and further to understand their perturbations of past and future climate forcing.

Tropospheric chlorine chemistry can strongly impact the atmospheric oxidation capacity and composition, especially in urban environments. To account for these reactions, the gas- and aqueous-phase Cl chemistry of the community atmospheric chemistry box model CAABA/MECCA has been extended. In particular, an explicit mechanism for ClNO2 formation following N2O5 uptake to aerosols has been developed. The updated model has been applied to two urban environments with different concentrations of NOx (NO and NO2): New Delhi (India) and Leicester (United Kingdom). The model shows a sharp build-up of Cl at sunrise through Cl2 photolysis in both environments. Besides Cl2 photolysis, ClO+NO reaction, and photolysis of ClNO2 and ClONO are prominent sources of Cl in Leicester. High-NOx conditions in Delhi tend to suppress the night-time build-up of N2O5 due to titration of O3 and thus lead to lower ClNO2, in contrast to Leicester. Major loss of ClNO2 is through its uptake on chloride, producing Cl2 , which consequently leads to the formation of Cl through photolysis. The reactivities of Cl and OH are much higher in Delhi, however, the Cl/OH ratio is up to ≈7 times greater in Leicester. The contribution of Cl to the atmospheric oxidation capacity is significant and even exceeds (by ≈2.9 times) that of OH during the morning hours in Leicester. Sensitivity simulations suggest that the additional consumption of VOCs due to active gas and aqueous-phase chlorine chemistry enhances OH, HO2, RO2 near the sunrise. The simulation results of the updated model have important implications for future studies on atmospheric chemistry and urban air quality.

Machine learning (ML) has emerged as a powerful technique in the Earth system science, nevertheless, its potential to model complex atmospheric chemistry remains largely unexplored. Here, we applied ML to simulate the variability in urban ozone (O3) over Doon valley of the Himalaya. The ML model, trained with past variations in O3 and meteorological conditions, successfully reproduced the independent O3 data (r2 ~ 0.7). Model performance is found to be similar when the variation in major precursors (CO and NOx) were included in the model, instead of the meteorology. Further the inclusion of both precursors and meteorology improved the performance significantly (r2 = 0.86) and the model could also capture the outliers, which are crucial for air quality assessments. We suggest that in absence of high-resolution measurements, ML modeling has profound implications for unraveling the feedback between pollution and meteorology in the fragile Himalayan ecosystem.

Covid lockdown presented an important opportunity to study relatively cleaner conditions in India. The complex factors of power production, industry, and transportation could be more carefully dissected because of the extreme reduction in the influence of the latter two emission sources. Measurements of cloud condensation nuclei (CCN) activity and other chemical properties of atmospheric aerosols showed that newly formed aerosol particles were produced in the SO2 plume from a large coal-fired power plant, contrary to normal conditions of heavy pollution. The sulfate-rich particles had high CCN activity and number concentration, indicating high cloud-forming potential. Examining the sensitivity of CCN properties under relatively clean conditions over India provides important new constraints on the perturbations of past and future climate forcing by anthropogenic emissions. Because most sensitive regime of aerosol climate forcing on cloud development is the midpoint of relatively clean conditions afforded by the Covid lockdown between background and polluted conditions.

Black Carbon (BC) aerosols critically impact the climate and hydrological cycle. The impact of anthropogenic emissions and coastal meteorology on BC dynamics, however, remain unclear over tropical India, a globally identified hotspot. In this regard, we have performed in situ measurements of BC over a megacity (Chennai, 12°59'26.5"N, 80°13'51.8"E) on the eastern coast of India during January­–June 2020, comprising the period of COVID-19 induced strict lockdown. Our measurements revealed an unprecedented reduction in BC concentration by an order of magnitude as reported by other studies for various other pollutants. This was despite having stronger precipitation during pre-lockdown and lesser precipitation washout during the lockdown. Our analyses, taking mesoscale dynamics into account, unravels stronger BC depletion in the continental air than marine air. Additionally, the BC source regime also shifted from a fossil-fuel dominance to a biomass burning dominance as a result of lockdown, indicating relative reduction in fossil fuel combustion. Considering the rarity of such a low concentration of BC in a tropical megacity environment, our observations and findings under near-natural or background levels of BC may be invaluable to validate model simulations dealing with BC dynamics and its climatic impacts in the Anthropocene.

The human microbiome plays a crucial role in health and disease conditions. These microbiomes constitute a structured, coordinated microbial network throughout the human body. The oral cavity harbors one of the extensively diverse bacteria in the human system. Although many studies emphasize bacteriome and its interaction with the host system, very little attention is given to candidate phyla radiation (CPR), fungal components, and its interkingdom interaction in the oral microecology even with advanced techniques. The interkingdom interactions among caries causing microbes trigger the pathogenesis of bacterial diseases and cause ecological shifts and affect the host system. Studying the complex relations among the diverse oral microbiome and its host, especially CPR phyla and fungi, would give a holistic view of the caries etiology. This review provides evidence on the interkingdom interaction that establishes a complex community that could help predict future oral and systemic diseases.

The sensitive ecosystem of the central Himalayan (CH) region, which is experiencing enhanced stress from anthropogenic forcing, requires adequate atmospheric observations and an improved representation of the Himalaya in the models. However, the accuracy of atmospheric models remains limited in this region due to highly complex mountainous topography. This article delineates the effects of spatial resolution on the modeled meteorology and dynamics over the CH by utilizing the Weather Research and Forecasting (WRF) model extensively evaluated against the Ganges Valley Aerosol Experiment (GVAX) observations during the summer monsoon. The WRF simulation is performed over a domain (d01) encompassing northern India at 15 km × 15 km resolution and two nests (d02 at 5 km × 5 km and d03 at 1 km × 1 km) centered over the CH, with boundary conditions from the respective parent domains. WRF simulations reveal higher variability in meteorology, e.g., relative humidity (RH = 70.3 %–96.1 %) and wind speed (WS = 1.1–4.2 m s−1), compared to the ERA-Interim reanalysis (RH = 80.0 %–85.0 %, WS = 1.2–2.3 m s−1) over northern India owing to the higher resolution. WRF-simulated temporal evolution of meteorological variables is found to agree with balloon-borne measurements, with stronger correlations aloft (r = 0.44–0.92) than those in the lower troposphere (r = 0.18–0.48). The model overestimates temperature (warm bias by 2.8 ∘C) and underestimates RH (dry bias by 6.4 %) at the surface in d01. Model results show a significant improvement in d03 (P = 827.6 hPa, T = 19.8 ∘C, RH = 92.3 %), closer to the GVAX observations (P = 801.4 hPa, T = 19.5 ∘C, RH = 94.7 %). Interpolating the output from the coarser domains (d01, d02) to the altitude of the station reduces the biases in pressure and temperature; however, it suppresses the diurnal variations, highlighting the importance of well-resolved terrain (d03). Temporal variations in near-surface P, T, and RH are also reproduced by WRF in d03 to an extent (r>0.5). A sensitivity simulation incorporating the feedback from the nested domain demonstrates the improvement in simulated P, T, and RH over the CH. Our study shows that the WRF model setup at finer spatial resolution can significantly reduce the biases in simulated meteorology, and such an improved representation of the CH can be adopted through domain feedback into regional-scale simulations. Interestingly, WRF simulates a dominant easterly wind component at 1 km × 1 km resolution (d03), which is missing in the coarse simulations; however, the frequency of southeasterlies remains underestimated. The model simulation implementing a high-resolution (3 s) topography input (SRTM) improved the prediction of wind directions; nevertheless, further improvements are required to better reproduce the observed local-scale dynamics over the CH.

Tropical cyclones (TCs) that make landfall over India’s east coast are responsible for significant loss of life along affected coastlines. TCs forming over the Bay of Bengal (BoB) region in October, November, and December have, in the past, intensified significantly at the time of landfall. The effects of climate change on TCs of different strengths and their characteristics such as track, intensity, precipitation, and convective available potential energy over the BoB region have not been well studied. This study explores the effects of climate change on two TCs of very severe cyclonic storm (VSCS) category (TC Vardah and TC Madi), and two other TCs of extremely severe cyclonic storm (ESCS) category (TC Hudhud and TC Phailin) formed over BoB, both in the short term (2035) and long term (2075). The high-resolution Weather Research and Forecasting (WRF) model is used to simulate the TCs under current and future climate conditions. The simulated TC track and intensity in the current climate agree well with the observations. To explore the impacts of climate change on TCs, the mean climate change signal, computed from future projections of the Community Climate System Model (CCSM4) in different representative concentration pathway (RCP) scenarios, is added to current climate conditions by using the pseudo global warming method. Results show a climate change-related reduction in TC translation speed, deepening of TC core, increased maximum surface wind, and increased precipitation over land in future RCP (4.5, 6.0, and 8.5) scenarios. The TCs in future RCP scenarios are seen to be more intensified compared to current climate simulations. Results demonstrate that all VSCS and ESCS category TCs considered in this study are likely to further intensify to the next higher category level with respect to their current classification, particularly in the far future RCP 6.0 and in the far future RCP 8.5 scenarios. The cyclone damage potential index of TC Vardah, TC Hudhud, and TC Phailin is projected to increase in a future warming climate.

Many cities in India experience severe deterioration of air quality in winter. Particulate matter is a key atmospheric pollutant that impacts millions of people. In particular, the high mass concentration of particulate matter reduces visibility, which has severely damaged the economy and endangered human lives. But the underlying chemical mechanisms and physical processes responsible for initiating haze and fog formation remain poorly understood. Here we present the measurement results of chemical composition of particulate matter in Delhi and Chennai. We find persistently high chloride in Delhi and episodically high chloride in Chennai. These measurements, combined with thermodynamic modelling, suggest that in the presence of excess ammonia in Delhi, high local emission of hydrochloric acid partitions into aerosol water. The highly water-absorbing and soluble chloride in the aqueous phase substantially enhances aerosol water uptake through co-condensation, which sustains particle growth, leading to haze and fog formation. We therefore suggest that the high local concentration of gas-phase hydrochloric acid, possibly emitted from plastic-contained waste burning and industry, causes some 50% of the reduced visibility. Our work implies that identifying and regulating gaseous hydrochloric acid emissions could be critical to improve visibility and human health in India. Half of the reduced visibility due to haze formation in cities in India is attributed to local emission of gas-phase hydrochloric acid from waste-burning and industry, according to measurements of particulate matter and thermodynamic modelling.

The interaction between water vapor and atmospheric aerosol leads to enhancement in aerosol water content, which facilitates haze development, but its concentrations, sources, and impacts remain largely unknown in polluted urban environments. Here, we show that the Indian capital, Delhi, which tops the list of polluted capital cities, also experiences the highest aerosol water yet reported worldwide. This high aerosol water promotes secondary formation of aerosols and worsens air pollution. We report that severe pollution events are commonly associated with high aerosol water which enhances light scattering and reduces visibility by 70%. Strong light scattering also suppresses the boundary layer height on winter mornings in Delhi, inhibiting dispersal of pollutants and further exacerbating morning pollution peaks. We provide evidence that ammonium chloride is the largest contributor to aerosol water in Delhi, making up 40% on average, and we highlight that regulation of chlorine-containing precursors should be considered in mitigation strategies.

Gaseous and particulate chlorine species play an important role in modulating tropospheric oxidation capacity, aerosol water uptake, visibility degradation, and human health. The lack of recent global continental chlorine emissions has hindered modeling studies of the role of chlorine in the atmosphere. Here, we develop a comprehensive global emission inventory of gaseous HCl and particulate Cl-(pCl), including 35 sources categorized in six source sectors based on published up-to-date activity data and emission factors. These emissions are gridded at a spatial resolution of 0.1° × 0.1° for the years 1960 to 2014. The estimated emissions of HCl and pCl in 2014 are 2354 (1661-3201) and 2321 (930-3264) Gg Cl a-1, respectively. Emissions of HCl are mostly from open waste burning (38%), open biomass burning (19%), energy (19%), and residential (13%) sectors, and the major sources classified by fuel type are combustion of waste (43%), biomass (32%), and coal (25%). Emissions of pCl are mostly from biofuel (29%) and open biomass burning processes (44%). The sectoral and spatial distributions of HCl and pCl emissions are very heterogeneous along the study period, and the temporal trends are mainly driven by the changes in emission factors, energy intensity, economy, and population.

Fine particulate matter (PM2.5, aerodynamic diameter ≤2.5 µm) impacts the climate, reduces visibility and severely influences human health. The Indo-Gangetic Plain (IGP), home to about one-seventh of the world’s total population and a hotspot of aerosol loading, observes strong enhancements in the PM2.5 concentrations towards winter. We performed high-resolution (12 km × 12 km) atmospheric chemical transport modeling (WRF-Chem) for the post-monsoon to winter transition to unravel the underlying dynamics and influences of regional emissions over the region. Model, capturing the observed variations to an extent, reveals that the spatial distribution of PM2.5 having patches of enhanced concentrations (≥100 µgm−3) during post-monsoon, evolves dramatically into a widespread enhancement across the IGP region during winter. A sensitivity simulation, supported by satellite observations of fires, shows that biomass-burning emissions over the northwest IGP play a crucial role during post-monsoon. Whereas, in contrast, towards winter, a large-scale decline in the air temperature, significantly shallower atmospheric boundary layer, and weaker winds lead to stagnant conditions (ventilation coefficient lower by a factor of ~4) thereby confining the anthropogenic influences closer to the surface. Such changes in the controlling processes from post-monsoon to winter transition profoundly affect the composition of the fine aerosols over the IGP region. The study highlights the need to critically consider the distinct meteorological processes of west-to-east IGP and changes in dominant sources from post-monsoon to winter in the formulation of future pollution mitigation policies.

Dry deposition is a major sink for tropospheric ozone; nevertheless, studies on its effects on ozone distribution are very limited over the rapidly developing South Asian region. We performed numer...

The Indo-Gangetic Plain (IGP) is one of the dominant sources of air pollution worldwide. During winter, the variations in planetary boundary layer (PBL) height, driven by a strong radiative thermal inversion, affect the regional air pollution dispersion. To date, measurements of aerosol-water vapor interactions, especially cloud condensation nuclei (CCN) activity, are limited in the Indian subcontinent, causing large uncertainties in radiative forcing estimates of aerosol-cloud interactions. We present the results of a one-month field campaign (February-March 2018) in the megacity, Delhi, a significant polluter in the IGP. We measured the composition of fine particulate matter (PM1) and size-resolved CCN properties over a wide range of water vapor supersaturations. The analysis includes PBL modeling, backward trajectories, receptor models and fire spots to elucidate the influence of PBL and air mass origins on aerosols. The aerosol properties depended strongly on PBL height and a simple power-law fit could parameterize the observed correlations of PM1 mass, aerosol particle number and CCN number with PBL height, indicating PBL induced changes in aerosol accumulation. The low inorganic mass fractions, low aerosol hygroscopicity and high externally mixed weakly CCN-active particles under low PBL height ((Formula presented.) 100 m) indicated the influence of PBL on aerosol aging processes. In contrast, aerosol properties did not depend strongly on air mass origins or wind direction, implying that the observed aerosol and CCN are from local emissions. An error function could parameterize the relationship between CCN number and supersaturation throughout the campaign.

Ambient PM10 (particulate matter with aerodynamic diameter ≤ 10 µm) samples were collected and characterized from July 2012 to August 2013 with the objective to evaluate the variation in elemental concentration and use the same as markers for source apportionment and health risk assessment for the first time over Bhubaneswar, India. The yearly average mass of PM10 was 82.28 µg/m3, which was ~ 37% higher than the national ambient air quality (NAAQ) standards. Maximum PM10 concentration was observed during winter season followed by post-monsoon, pre-monsoon, and monsoon months. Acid soluble components in the PM10 samples were analyzed using ICP-OES (inductive coupled plasma optical emission spectroscopy), and 19 different elements including heavy metals were determined. Enrichment factor analysis attributed the source to either crustal or non-crustal origin. Principal component analysis (PCA) revealed that crustal sources, industrial activities, and vehicular emissions were significant contributors to PM mass. The contribution of total average elemental concentration showed a seasonal variation with the lowest (11.96 µg/m3) and highest (17.77 µg/m3) during monsoon and winter, respectively, which is relatively less significant than the variation in total PM10 mass that ranged between 48.43 µg/m3 in monsoon and 138.24 µg/m3 during the winter season. This observation evidences the predominant contribution of local/regional emission sources to the metallic components in coarse PM10 mass, which is corroborated by the wind pattern studies carried out using polar plots and a Lagrangian Particle Dispersion Model (LPDM) FLEXPART. Further, carcinogenic and non-carcinogenic health risk assessments of the measured elements that find their way into the human body through different exposure pathways have been calculated using United State Environmental Protection Agency (USEPA) standards. The carcinogenic risk of most of the elements was insignificant. The potential risk assessment study revealed that regular exposure to heavy metals through the ingestion pathway caused detrimental health effects. These effects were observed to be more severe in children in comparison to adults.

Coronaviruses are single stranded RNA viruses usually present in bats (reservoir hosts), and are generally lethal, highly transmissible, and pathogenic viruses causing sever morbidity and mortality rates in human. Several animals including civets, camels, etc. have been identified as intermediate hosts enabling effective recombination of these viruses to emerge as new virulent and pathogenic strains. Among the seven known human coronaviruses SARS-CoV, MERS-CoV, and SARS-CoV-2 (2019-nCoV) have evolved as severe pathogenic forms infecting the human respiratory tract. About 8096 cases and 774 deaths were reported worldwide with the SARS-CoV infection during year 2002; 2229 cases and 791 deaths were reported for the MERS-CoV that emerged during 2012. Recently ~ 33,849,737 cases and 1,012,742 deaths (data as on 30 Sep 2020) were reported from the recent evolver SARS-CoV-2 infection. Studies on epidemiology and pathogenicity have shown that the viral spread was potentially caused by the contact route especially through the droplets, aerosols, and contaminated fomites. Genomic studies have confirmed the role of the viral spike protein in virulence and pathogenicity. They target the respiratory tract of the human causing severe progressive pneumonia affecting other organs like central nervous system in case of SARS-CoV, severe renal failure in MERS-CoV, and multi-organ failure in SARS-CoV-2. Herein, with respect to current awareness and role of coronaviruses in global public health, we review the various factors involving the origin, evolution, and transmission including the genetic variations observed, epidemiology, and pathogenicity of the three potential coronaviruses variants SARS-CoV, MERS-CoV, and 2019-nCoV. Electronic supplementary material The online version of this article (10.1007/s13337-020-00632-9) contains supplementary material, which is available to authorized users.

Air pollution in urban environments has been shown to have a negative impact on air quality and human health, particularly in megacities. Over recent decades, Delhi, India has suffered high atmospheric pollution, with significant particulate matter (PM) concentrations as result of anthropogenic activities. Organic aerosols (OA) are composed of thousands of different chemical species and are one of the main constituents of submicron particles. However, quantitative knowledge of OA composition, their sources and processes in urban environments is still limited. This is important particularly in India, as Delhi is a massive, inhomogeneous conurbation, which we would expect that the apportionment and concentrations will vary depending on where in Delhi the measurements/source apportionment is performed, indicating the need of multi-site measurements. This study presents the first multisite analysis carried out in India over different seasons, with a focus on identifying OA sources. The measurements were taken during 2018 at two sites in Delhi, India. One site was located at the India Meteorological Department, New Delhi (ND). The other site was located at the Indira Gandhi Delhi Technical University for Women, Old Delhi (OD). Non-refractory submicron aerosol (NR-PM1) concentrations (ammonium, nitrate, sulphate, chloride and organic aerosols) of four aerosol mass spectrometers were analysed. Collocated measurements of VOC, black carbon, NOx and CO were performed. Positive matrix factorization (PMF) analysis was performed to separate the organic fraction, identifying a number of conventional factors: hydrocarbon-like OA (HOA) related to traffic emissions, biomass burning OA (BBOA), cooking OA (COA) and secondary OA (SOA). A composition-based estimate of PM1 is defined by combining BC and NR-PM1 (C-PM1 = BC + NR-PM1). No significant difference was observed on C-PM1 concentrations between sites; OD (142 ± 117 µg m−3) compared to ND (123 ± 71 µg m−3), from post-monsoon measurements. A wider variability was observed between seasons, where pre-monsoon and monsoon showed C-PM1 concentrations lower than 60 µg m−3. A seasonal variation in C-PM1 composition was observed; SO42− showed a high contribution over pre-monsoon and monsoon seasons while NO3− and Cl− had a higher contribution in winter and post-monsoon. The main primary aerosol source was from traffic, which is consistent with the PMF analysis and aethalometer model analysis. Thus, in order to reduce PM1 concentrations in Delhi through local emission controls traffic emissions control offers the greatest opportunity. PMF-AMS mass spectra will help to improve future aerosol source apportionment studies. The information generated in this study increases our understanding of PM1 composition and OA sources in Delhi, India. Furthermore, the scientific findings provide significant information to strengthen legislation that aims to improve air quality in India.

Ambient air consists of bioaerosols that constitute many microbes from biosphere due to natural and anthropogenic activities. Size-dependent ambient measurements of bioaerosols at two seminatural and three anthropogenic coastal sites in southern tropical India were taken during the summer 2017. All the five sites considered in this study considerably contributed to the bioaerosol burden with larger contribution from the dumping yard site followed by the marshland site, wastewater treatment plant, composting site, and Indian Institute of Technology Madras. The colony-forming units concentration for all the sites ranged from 17 to 2750 m−3 for bacteria and 42–2673 m−3 for fungi. Firmicutes and Actinomycetes were the dominant phyla observed in 698 bacterial OTUs obtained, and Ascomycota and Zygomycota were the dominant phyla observed in 159 fungal OTUs obtained in the study. Further, the study revealed the presence of pathogenic and ice-nucleating bacteria and fungi in the bioaerosols that can largely affect the well-being of the human population and vegetation in this region. Moreover, the statistical analysis revealed high bacterial abundance and diversity at the grit chamber of wastewater treatment plant and high fungal abundance and diversity at the dumping yard. Further, principal coordinate analysis of the sites studied inferred that the marshland, wastewater treatment plant, and the dumping yard sites shared similar microbial community composition indicating the existence of similar source materials and activities at the sites. Further, this study evidently brings out the fact that urban locations may play an important role in anthropogenic contribution of both pathogenic and ice-nucleating microorganisms.

Ambient PM

Particle number size distributions in the diameter range of 5 nm–34 µm were measured in tropical southern India during the transition season from May (pre-monsoon) to June–July (monsoon). Averaged over the entire measurement period, the particle number size distributions were bimodal with a total particle number concentration of NTot = (4.5 ± 2.7) × 103 cm−3 (arithmetic mean ± standard deviation). The ratio of Aitken to accumulation mode particle number concentrations (NAit/NAcc) ranged from 1.06 to 2.07, increasing from May to June–July due to a pronounced decrease in the accumulation mode particles with the onset of the monsoon. Cloud condensation nuclei concentrations at 0.4% supersaturation (CCN0.4) were calculated under the assumption of an average continental hygroscopicity parameter of κ = 0.3. The calculated CCN0.4 concentrations are mostly sensitive to variations in NAcc and vary accordingly between the May and June–July. Using a cloud parcel model, we investigated the formation of cloud droplets using the measured average particle number size distributions, updraft velocities up to 20 m s−1, and initial aerosol particle number concentrations up to 25,000 cm−3. We found different regimes of CCN activation and cloud formation for the month of May (shifting from aerosol-limited regime to transitional regime) and for June–July (transitional regime), which was primarily due to the variability of particle number concentrations in the accumulation mode.

The novel coronavirus, since its first outbreak in December, has, up till now, affected approximately 114,542 people across 115 countries. Many international agencies are devoting efforts to enhance the understanding of the evolving COVID-19 outbreak on an international level, its influences, and preparedness. At present, COVID-19 appears to affect individuals through person-to-person means, like other commonly found cold or influenza viruses. It is widely known and acknowledged that viruses causing influenza peak during cold temperatures and gradually subside in the warmer temperature, owing to their seasonality. Thus, COVID-19, due to its regular flu-like symptoms, is also expected to show similar seasonality and subside as the global temperatures rise in the northern hemisphere with the onset of spring. Despite these speculations, however, the systematic analysis in the global perspective of the relation between COVID-19 spread and meteorological parameters is unavailable. Here, by analyzing the region- and city-specific affected global data and corresponding meteorological parameters, we show that there is an optimum range of temperature and UV index strongly affecting the spread and survival of the virus, whereas precipitation, relative humidity, cloud cover, etc. have no effect on the virus. Unavailability of pharmaceutical interventions would require greater preparedness and alert for the effective control of COVID-19. Under these conditions, the information provided here could be very helpful for the global community struggling to fight this global crisis. It is, however, important to note that the information presented here clearly lacks any physiological evidences, which may merit further investigation. Thus, any attempt for management, implementation, and evaluation strategies responding to the crisis arising due to the COVID-19 outbreak must not consider the evaluation presented here as the foremost factor.

Cloud Condensation Nuclei (CCN) and other aerosol properties were investigated in Delhi, India, from Feb. to Mar. 2018. The high anthropogenic influence on aerosol was studied with size-resolved CCN measurements (supersaturation (S) between 0.13 to 0.66% and selected diameters from 10 to 300 nm). Furthermore the chemical composition (Aerosol Chemical Speciation Monitor and Aethalometer AE33) of the particles was measured. The aerosol number size distribution was derived by size data inversion of Differential Mobility Particle Sizer (DMPS) from size-resolved CCN measurements. Based on multi-year back trajectory (BT) data, a spatial clustering analysis was done for the actual campaign period and two distinct clusters were identified: northwest- west northwest-long range transport (NW-LRT) and south-southeast-east southeast (SE).There was preponderant organic mass fraction (forg) in the aerosols throughout the campaign, with prominent diurnal variation except during the SE period. Pronounced diurnal variation was observed also in black carbon (BC) with an average concentration of 16 µg/m3 during NW-LRT, in contrast to a weak diurnal cycle with lower average concentration of 8 µg/m3 during SE. During the NW-LRT cluster the air masses traversed over agriculture fields with biomass burning (BB) activities identified using the fire radiative power (FRP) observations of Copernicus Atmosphere Monitoring Service (CAMS) Global Fire Assimilation System (GFAS). So it can be speculated that the BB emissions from the fields have contributed to enhanced BC concentrations during this period over Delhi. The remaining period, showing a mixture of local and long-range transported emissions also had a BC concentration higher than SE period when only local/regional emissions were observed. This is an important insight into the air pollution apocalypse in Delhi.The overall average values of critical dry diameter (Dc) for CCN activation varied from 54 ± 8 nm at S = 0.66% to 139 ± 12 nm at S = 0.13%.The hygroscopicity parameter derived from CCN data (кCCN) was in the range from 0.1 to 0.9 with an arithmetic mean of 0.27 ± 0.10, which is close to that of Beijing, another polluted continental region (0.31 ± 0.08, Gunthe et al., 2011). кCCN also shows good agreement with the hygroscopicity parameter derived from the chemical composition measurements. A linear fit (Gunthe et al., 2009) applied to the relationship between refractory/non-refractory organic mass fraction and кCCN at S = 0.13%, gives an effective hygroscopicity parameter кorg = 0.17 ± 0.09 and кinorg = 0.80 ± 0.09, when extrapolated to forg = 1 and forg = 0, respectively. The presence of externally mixed inactive CCN particles is indicated by an average maximum activated fraction (MAF) of 0.82 ± 0.17 at S = 0.13%. The overall average Dc, кCCN, and MAF did not vary much between NW-LRT and SE periods, although the particle number concentration was higher during NW-LRT. Moreover, high CCN efficiency was observed during NW-LRT, in spite of its enhanced BC concentration, indicating the presence of aged internally mixed aerosols. Further details will be presented.

Atmospheric aerosol particles, known for their direct interaction with incoming solar radiations (direct effect) and for perturbation of the cloud properties (indirect effect) by acting as cloud condensation nuclei (CCN), represents largest uncertainty in the current and future understanding of the climate change. In part, this uncertainty is attributed to the lack of accurate measurements of aerosol physical and chemical properties for the improvement of various schemes in prognostic modelling useful for the effective prediction of cloud and precipitation formation. The Indian tropical region, constitutes ~18% of the world’s total population spread heterogeneously over diverse land cover, experiences a distinctive meteorological phenomenon by means of Indian Summer Monsoon (ISM). Thus, the sources, chemical properties and characteristics of aerosols are also expected to have significant variations over the Indian subcontinent depending upon the location and seasons. Online continuous measurements of NR-PM1 (Non refractory particulate matter ≤1 µm) have been carried out in near real-time using ACSM (Aerosol Chemical Speciation Monitor) at a marine urban location of Chennai, from 4th January to 2nd February, 2019, complimented by simultaneous measurements of meteorological parameters. Average NR-PM1 mass concentration for the duration of the measurements was 30.37±28.31 µg/m3 with organics constituting major fraction of ~47.43% followed by sulphate (~33.34%), ammonium (~11.89%), nitrate (~4.57%) and chloride (~2.74%). Back trajectory analysis using HYSPLIT model enabled the classification of air samples measured in to three periods: “Continental polluted”, “Marine polluted” and “Clean marine”. The polluted periods were distinguished by the potential biomass burning event, which occurs during the regional festival Bhogi, celebrated on 14th of January in this part of the country. During this period the organics had a peak concentration of 211 µg/m3 followed by chloride ~ 42 µg/m3. During the clean marine period, low mass concentration of PM1 is attributed to change in meteorological conditions accompanied by airmass originating from the Bay of Bengal. The average mass concentration of NR-PM1 during this period was observed to be 7.14±2.78 µg/m3, which is ~5 times lesser than the polluted period. A comprehensive source apportionment study was carried out using Positive Matrix Factorization (PMF) model implemented through the multilinear engine tool (ME-2) in Source Finder (SoFi) graphical user interface, to understand the contribution of primary and secondary sources to the organic aerosols. Primary anthropogenic emissions contributed on average ~45% (~19% from traffic, ~16.7% from cooking, ~10% from biomass burning) to the total organic mass for entire measurement period, while the major contribution was associated with secondary formation ~55%. On the other hand, for clean marine period, the fractional contribution of secondary formation to PM1 increased to ~75% to 85%, while that of primary emissions decreased to less than ~15%.In brief, these findings indicate the influence of oceanic air masses on aerosol mass concentration and composition. Further details will be presented.

Dental caries is the most prevalent oral disease affecting nearly 70% of children in India and elsewhere. Micro-ecological niche based acidification due to dysbiosis in oral microbiome are crucial for caries onset and progression. Here we report the tooth bacteriome diversity compared in Indian children with caries free (CF), severe early childhood caries (SC) and recurrent caries (RC). High quality V3–V4 amplicon sequencing revealed that SC exhibited high bacterial diversity with unique combination and interrelationship. Gracillibacteria_GN02 and TM7 were unique in CF and SC respectively, while Bacteroidetes, Fusobacteria were significantly high in RC. Interestingly, we found Streptococcus oralis subsp. tigurinus clade 071 in all groups with significant abundance in SC and RC. Positive correlation between low and high abundant bacteria as well as with TCS, PTS and ABC transporters were seen from co-occurrence network analysis. This could lead to persistence of SC niche resulting in RC. Comparative in vitro assessment of biofilm formation showed that the standard culture of S. oralis and its phylogenetically similar clinical isolates showed profound biofilm formation and augmented the growth and enhanced biofilm formation in S. mutans in both dual and multispecies cultures.

Bioaerosols abundantly found in the atmosphere can potentially influence the climate by acting as ice nuclei and thus profoundly influencing the hydrological cycle. As the first attempt over India, we report the diversity, abundance, and ice nucleating ability of bacteria present in the rainwater collected at Chennai, during summer and two contrasting monsoon seasons. Diverse bacterial communities were present in all the twenty rainwater samples and predominantly belonged to Actinobacteria (6%), Alpha proteobacter (9%), Bacilli (29%), Betaproterobacteria (14%), Flavobacteria (3%), and Gammaproteobacteria (39%). The most efficient ice nucleating bacteria such as Pseudomonas sp. and Pantoea sp. were present in our precipitation samples and they contributed to 8.4% and 9.4% of the total cultivable bacterial species obtained. The relative abundance of Pseudomonas was highest during the south-west monsoon (75%) whereas Pantoea was abundant in the north-east monsoon (51.8%). The dominant bacteria belonging to the known ice nucleating genera Pseudomonas, Pantoea, and Bacillus were chosen for the determination of their freezing temperatures using tube freeze assay technique. The onset freezing temperature of species belonging to Pseudomonas and Pantoea was recorded as −12 °C and for those species belonging to Bacillus it was found to be −14 °C. Further, the number of bacterial cells making up an ice nucleus was estimated at the temperatures ranging from −18 °C to −12 °C for all the ice nucleating bacteria and it was found to vary from 106 to 109 (cells/nucleus).

Persistent organic pollutants that have accumulated in soils can be remobilised by volatilisation in response to chemical equilibrium with the atmosphere. Clean air masses from the Indian Ocean, advected with the onset of the summer monsoon, are found to reduce concentrations of hexachlorocyclohexane (HCH), dichlorodiphenyltrichloroethane (DDT) and its derivatives, endosulfan and polychlorinated biphenyls (PCBs) in air at a mountain site (all in the range 5–20 pg m−3) by 77 %, 70 %, 82 % and 45 %, respectively. The analysis of fugacities in soil and air suggest that the arrival of summer monsoon triggers net volatilisation or enhances ongoing revolatilisation of the now-banned chemicals HCH and PCBs from background soils in southern India. The response of the air–soil exchange was modelled using a regional air pollution model, WRF-Chem PAH/POP. The results suggest that the air is increasingly polluted during transport by the south-westerly monsoon winds across the subcontinent. Using a multidecadal multimedia mass balance model, it is found that air–surface exchange of HCH and DDT have declined since the ban of these substances from agriculture, but remobilisation of higher chlorinated PCBs may have reached a historical high, 40 years after peak emission.

The rapidly increasing industrialization and urbanization, in combination with under representation of in-situ measurements, especially Volatile Organic Compounds (VOCs), has posed serious challenges in understanding air quality and atmospheric chemistry over India. Here we present yearlong measurements of VOCs, carried out during March 2014–February 2015 using a Proton Transfer Reaction Mass Spectrometer (PTR-MS) from an urban site Pune (18.58oN, 73.91°E, 559 m amsl) in western tropical India. The averaged diurnal variation in VOCs at Pune exhibited a characteristic bimodal pattern, with highly pronounced peak during morning hours and secondary enhancement during late evening/night, except for Isoprene. Isoprene mixing ratios were observed to be higher (1.30 ± 0.69 ppbv) during the daytime (0900–1800 h) and lower (0.89 ± 0.65 ppbv) during the nighttime (after 1900 h and before 0900 h). While, Methanol, Acetonitrile, and Acetaldehyde are observed to be the highest (14.3 ± 5.9, 0.9 ± 0.4, and 6.1 ± 2.6 ppbv respectively) during spring, Benzene and Toluene were highest (1.6 ± 1.1, 2.6 ± 2.2 ppbv respectively) during winter. Isoprene mixing ratios showed broader maxima during autumn and winter (1.3 ppbv). Nominally, all the VOCs were observed to be lowest during the monsoon season. The two peaks in the seasonal cycle of acetonitrile along with VIIRS retrieved fire counts indicated impact of the regional biomass burning during spring and winter. Analysis of air-mass residence time further revealed potential influences from the highly polluted Indo-Gangetic Plain during the autumn and winter, whereas local pollution supplemented with regional biomass burning found to be the dominant process during spring. These yearlong measurements are a step forward in filling a major gap of observational data of VOCs over the tropical Indian region, which would be invaluable for evaluation of chemistry transport models and understanding of regional tropospheric chemistry.

Quantitative estimations of fungal aerosols are important to understand their role in causing respiratory diseases to humans especially in the developing and highly populated countries. In this study we sampled and quantified the three most dominantly found allergenic airborne fungi, Aspergillus fumigatus, Cladosporium cladosporioides, and Alternaria alternata from ambient PM10 samples using the quantitative PCR (qPCR) technique in a southern tropical Indian region, for one full year. Highest concentrations of A. fumigatus and C. cladosporioides were observed during monsoon whereas A. alternata displayed an elevated concentration in winter. The meteorological parameters such as temperature, relative humidity, wind speed, and precipitation exhibited a substantial influence on the atmospheric concentrations of allergenic fungal aerosols. The morphological features of various allergenic fungal spores present in the PM10 were investigated and the spores were found to possess distinct structural features. In a maiden attempt over this region we correlate the ambient fungal concentrations with the epidemiological allergy occurrence to obtain firsthand and preliminary information about the causative fungal allergen to the inhabitants exposed to bioaerosols. Our findings may serve as an important reference to atmospheric scientists, aero-biologists, doctors, and general public.

Atmospheric bioaerosols, which contain a diverse group of various biological materials, also include pathogenic microorganisms such as viruses, bacteria, and fungal spores. The dispersal of various pathogens negatively impacts the human and ecosystem health. While the impact of pathogenic bacteria and viruses on human and ecosystem health is well documented, the impact of fungal spores on crop, however, is poorly characterized. An unprecedented increase in number of fungal and fungal-like diseases (emerging fungal diseases (EFDs)) in plants is threatening the food security and endangering the biodiversity. In present communication, we show an increasing trend in the fungal bioaerosol attacks on crops over India outstripping bacteria and viruses. We further argue about the complex interactions between the fungal species, and crop impact over India is unique and highly interconnected with the topography, meteorological variables, and season of the year. Under constantly warming scenario, the fungal attacks on plants are expected to rise and, in all likelihood, extend to the sensitive and fragile ecosystems like the Himalayan region and the Western Ghats. An increasing trend in EFDs calls for immediate coordinated efforts towards understanding the type and diversity of pathogenic fungal bioaerosols. There is, however, a lack over Indian region about biogeography of pathogenic fungi. The detailed biogeography would help in improving public and political awareness to formulate the effective policy decisions. Any further disregard and delay in recognizing the importance of EFDs to crop and sensitive ecosystems can have severe societal and ecological repercussions over Indian region.

Aerosols of biological origin play a vital role in the Earth system, particularly in the interactions between atmosphere, biosphere, climate, and public health. Airborne bacteria, fungal spores, pollen, and other bioparticles are essential for the reproduction and spread of organisms across various ecosystems, and they can cause or enhance human, animal, and plant diseases. Moreover, they can serve as nuclei for cloud droplets, ice crystals, and precipitation, thus influencing the hydrological cycle and climate. The sources, abundance, composition, and effects of biological aerosols and the atmospheric microbiome are, however, not yet well characterized and constitute a large gap in the scientific understanding of the interaction and co-evolution of life and climate in the Earth system. This review presents an overview of the state of bioaerosol research, highlights recent advances, and outlines future perspectives in terms of bioaerosol identification, characterization, transport, and transformation processes, as well as their interactions with climate, health, and ecosystems, focusing on the role bioaerosols play in the Earth system.

This study is based on the analysis of the measurement of ozone and water vapor by airbus in-service aircraft (MOZAIC) data of vertical ozone (O3) and carbon monoxide (CO) over Hyderabad during November 2005–March 2009. Measurements in the upper troposphere show highest values of O3 (53–75 ppbv) and CO (80–110 ppbv) during the pre-monsoon and post-monsoon seasons, respectively. The episodes of strong wind shears (>20 ms−1) were frequent during the monsoon/post-monsoon months, while weak shear conditions (