Bengaluru, once known as the “Garden City,” has transitioned into one of India’s major IT hubs, marked by rapid population growth. This has driven a significant increase in fuel combustion across its transportation, domestic, and industrial sectors, resulting in a severe deterioration of its ambient air quality. Despite this, systematic studies examining the effects of urbanization on temporal variations of carbon monoxide (CO) and black carbon (BC) across different time scales are limited. This study examines the temporal variations of BC and CO levels in Bengaluru over a four-year period from January 2015 to December 2018. The analysis examines diurnal, seasonal, and annual patterns of CO and BC and their relationship with key meteorological factors, namely temperature, wind speed, relative humidity and boundary layer height. The daily mean CO concentrations ranged from 0.22 to 4.07 ppmv (mean 0.84 ± 0.3 ppmv), while BC concentrations ranged from 1.13 to 9.5 µg/m³ (mean 3.28 µg/m³). Higher concentrations of both pollutants were observed in winter, summer, and post-monsoon seasons, with lower levels in the monsoon. Correlation analysis reveals that meteorological factors govern pollutant dispersion and accumulation, with diurnal variations exhibiting bimodal peaks that consistently align with morning and evening traffic and are further modulated by the dynamics of the planetary boundary layer. Further, Principal Component Analysis (PCA) identified local traffic emissions as the primary source of CO and BC, with meteorology further influencing the observed concentrations. The study concludes with a health risk assessment that links BC exposure to ischemic heart disease, highlighting the threat that emissions combined with meteorology pose to air quality and public health in rapidly urbanizing regions.

The growth properties of submicron aerosols were investigated on the basis of particle number size distributions measured in field experiments. An analysis of condensation sink, growth rate, concentration of condensable vapors and their source rate, and real and apparent nucleation rates as a function of particle sizes and their number concentrations in the submicron range are presented to quantify their effects during nucleation events. Higher number concentrations of newly formed particles of 0.013, 0.024, 0.075, and 0.133 µm around 0900 h indicate that photochemistry plays an important role in their formation, and that they grow principally by gas-to-particle conversion. The magnitudes of nucleation parameter η are indicative of the number concentration of newly formed particles by nucleation and their subsequent growth. The estimated value of η is around 10 nm for Aitken mode particles (0.013 and 0.024 µm) and 6 nm for accumulation mode particles (Dp > 0.1 µm). The formation rate of 0.013 and 0.024 µm particles is 2.33 cm−3 s−1 and of intermediate particles (0.075 and 0.133 µm) is 1.33 cm−3 s−1. The growth rate of 0.013 and 0.024 um particles is 0.3 and 1 nm h−1 and the rate for 0.075 and 0.133 µm particles is 8 and 21 nm h−1 , indicating that high formation rate and rapid growth are generally found in semi-urban and urban areas. These results may be of interest for future study of nucleation processes in different environments.

Routine observations of surface ozone (O3) and its precursors (NO, NO2, NOx) were taken over Bengaluru, a southern megacity, India, for 4 years period between January 2015 and December 2018. The seasonal variations of O3, NO, NO2, and NOx have been analysed to understand the short-term variability of the pollutants at this site. The magnitude of O3 varied significantly by season, with maximum concentration during winter (13.07 ppbv) and minimum concentration during monsoon (9.52 ppbv). The highest concentration was observed in the post-monsoon season (17.38 ppbv) for NO, while NO2 and NOx showed the highest (41.75, 50.42 ppbv) in the winter season. The lowest concentrations of NO (5.70 ppbv), NO2 (30.43 ppbv) and NOx(36.28 ppbv) were observed in summer. An estimate was performed to determine the site's VOC-NOx sensitivity, using the TNMHC/NOX ratio as a photochemical measure. This ratio indicates that the study region is NOX responsive in all seasons. Analysis was done on the effects of meteorological factors such as temperature, water vapour, and ventilation coefficient on pollutants. Higher correlation of O3 with temperature showed the role of photochemical reactions in the formation of ozone and water vapour content leads to the removal of ozone concentration. The influence of meteorological variables on NO2 and TNMHC did not appear to be very significant. An analysis of CAMS data with real-time measurements of ozone and oxides of nitrogen showed that ozone is significantly correlated, while nitrogen oxides are not significantly correlated with CAMS data.

PM10, PM2.5 and PM1 mass concentrations have been measured at Delhi (28°35′N; 77°12′E) during the August to December 2007. The running mean of PM10, PM2.5 and PM1 data shows large variations. The PM10, PM2.5 and PM1 were ranged from 20 to 180 μg/m3 during the monsoon and from 100 to 500 μg/m3 during the winter (up to 1200 μg/m3 in November due to Deepavali fireworks). For the same running mean cycles, higher mass concentrations in the PM10, PM2.5 and PM1 were corresponded with peaks in the relative humidity and lower levels linked to peaks in the ambient temperature. The evolutions of PM10, PM2.5 and PM1 concentrations after the elapsed times are simulated with mean mass scavenging coefficients. These evolution patterns clearly show the difference in washout of PM10 with impaction scavenging relative to those for PM2.5 and PM1 particles over different rainfall durations. Air-mass pathways traced with HYSPLIT model over the study area illustrates the nature of PM10, PM2.5 and PM1 levels with monsoon and winter air-mass circulations over Delhi.

This study investigated the concentration of heavy metals in rainwater (RW) at a semi-arid region of the Indo-Gangetic basin to understand the influence of local, regional, or long-range transport of air pollutants during the monsoon and non-monsoonal rain. The concentration of heavy metals in RW was determined using Atomic Absorption Spectrophotometer with Graphite Furnace, the scavenging ratio was estimated, and source interpretation was carried out using Principle Component Analysis (PCA) and HYSPLIT model. Ca was the highest contributor in RW followed by Na, Fe, Mg, and Al whereas Ba, Cr, Cu, Mn, Ni, Pb, and Zn were found in trace quantity. During the non-monsoon period, the crustal component (Ca) was the highest; however, during the monsoon, sea salt components (Na and Fe) were found higher. The scavenging ratio for metals was estimated and was found many times higher than those reported over European sites. The moderate concentration of heavy metal in RW was found with higher wind from South (S), South-West (SW), and North-West (NW) directions. Air mass back trajectory shows a significant contribution of metals from the Arabian Sea (South-Westerly wind) during active monsoon, whereas, in the non-monsoon season, the air masses mainly originated from the north-west indicating a contribution from wind-blown dust. The correlation analysis has shown the positive correlations between Ca and Mg, Mg and Na, Na and Cu, Al and Zn, Zn and Ba, Ba and Cr, and Cr and Zn. Principal Component Analysis (PCA) indicated loading of Ca, Na, Mg, Cu, Mn, and Ni in the first factor suggesting their crustal origin, whereas the second factor showed high loading of Al, Ba, Zn, Cr, and Ni indicating vehicular exhaust and industrial emission as their major sources, and loading for Ba and Mg in the third factor indicates the mixed contribution from both natural and anthropogenic sources in rainwater during the monsoon and non-monsoon periods. The data of this study can be used in the air pollution transport model. This study will help in source interpretation over the Indo-Gangetic basin and will help in planning for National Clean Air Program (NCAP) and deriving critical load.

To improve ambient air quality, India has laid out strict action plans to reduce the increment in emissions over regional to urban scale by the year 2030. This study evaluates policy-induced improvement in air quality and associated health benefits achievable due to reduction in PM2.5 exposure under the adoption of promulgated (S2) and ambitious prospective regulations (S3) with respect to the scenario for Business As Usual (BAU) in 2030. The Weather Research and Forecasting model coupled with online chemistry (WRF-Chem) has been used to simulate ambient PM2.5 exposure to the population under BAU, S2 and S3 emission scenarios. Results show 15

PM2.5, PM10 mass levels at six and BC levels at one station were monitored at the tropical megacity, Bengaluru, India, for the year 2019. The annual average levels of PM2.5, PM10 and BC were 31, 73 and 2.72 µg/m3 respectively. PM2.5 levels were within the Indian National Ambient Air Quality Standard (INAAQS) value of 40 µg/m3 whereas that of PM10 exceeded INAAQS level of 60 µg/m3 for the year 2019 for all six stations. The season-wise diurnal variability of PM and BC shows bimodal peaks, first one in the morning and the second one in the late evening hours in all the stations. These peaks correspond to rush traffic hours and lower PBL height. The correlation analysis of PM and BC with meteorological parameters is presented. The data are also analysed for the Deepavali festival. The PM2.5 levels in festival have doubled, PM10 levels increased by more than 50 %, while BC showed marginal increase. Further, the night-time levels of PM and BC were higher than the daytime during the festival. The health risk assessment using Air Q+ for the city of Bengaluru for 2019 shows highest PM exposure risk to ischemic heart disease.

The presence of persistent heavy fog in northern India during winter creates hazardous situations for transportation systems and disrupts the lives of about 400 million people. The meteorological factors responsible for its genesis and predictability are not yet completely understood in this region. Given its high potential for socioeconomic impact, there is a pressing need for extensive research that understands the inherently complex nature of the phenomena through field observations and modeling exercises. WiFEX is a first-of-its-kind multi-institutional initiative dealing with intensive ground-based measurement campaigns for developing a suitable fog forecasting capability under the aegis of the smart cities mission of India. Measuring campaigns were conducted during the 2015-20 winters at the Indira Gandhi International Airport, New Delhi, covering more than 90 dense fog events. The field experiments involved extensive suites of in situ instruments and gathered simultaneous observations of micrometeorological conditions, radiative fluxes, turbulence, droplet/aerosol microphysics, aerosol optical properties, fog water chemistry, and vertical thermodynamical structure to describe the environmental stability in which fog develops. An operational modeling framework, the WRF Model, was set up to provide fog predictions during the measurement campaign. These field observations helped to interpret the strengths and deficiencies in the numerical modeling framework. Four scientific objectives were pursued: (i) the life cycle of optically thin and thick fog, (ii) microphysical properties in the polluted boundary layer, (iii) fog water chemistry, gas-aerosol partitioning during the fog life cycle, and (iv) numerical prediction of fog. This paper presents an overview of WiFEX and a synthesis of selected observational and modeling analyses/findings related to the abovementioned scientific topics.

Original article available at https://doi.org/10.4209/aaqr.220112 The original version of this article contained an error in Affiliation 2, which was incorrectly given as ‘Development of Atmospheric and Space Sciences, Savitribai Phule Pune University, Pune, India’. The correct affiliation is listed below: Department of Atmospheric and Space Sciences, Savitribai Phule Pune University, Pune, India The original article has been corrected.

Increasing concentrations of air pollutant are directly affecting human health and crop production and shown to have negative impact on economic sector of India. Similarly, wintertime fog in India severely hinders the flight operations and causes significant financial losses to the aviation industry. It is therefore important to undertake a quantitative to the estimated losses to the economy due to both air pollution and fog in India. This chapter provides overview of the estimated losses due to air pollution impact on health and crop production in India and estimates for the economic loss to the aviation sector due to interruption to flight operation due to dense fog at Delhi International Airport. The present-day premature mortalities due to PM2.5 and O3 exposure caused economic cost of approximately 640 billion USD, which is a factor of 10 higher than total expenditure on health by public and private expenditures in India. Similarly, the damage to crop due to O3 exposure caused economic cost of approximately 1.29 ± 0.47 billion USD2005 annually which is sufficient to feed approximately 94 million poor people living below poverty line in India under the provision of the National Food Security Ordinance. On the other hand, the wintertime fog in northern India hinders the flight operations led to a total economic cost of approximately 3.9 million USD (248 million Indian rupees) due to flights affected by heavy fog spells at Delhi International Airport over 5 years.

The present study analyses the continuous in-situ observations of surface ozone (O3), carbon monoxide (CO), and nitrogen oxides (NOX) conducted in an urban location, Bengaluru, India, during the year 2019 (January to December). The seasonal concentration of O3 fluctuated with the highest concentrations in the summer (39.6 ppbv) and winter (40.4 ppbv) and the lowest concentrations during the monsoon (16.8 ppbv). The seasonal mixing ratio of CO showed the highest value in post-monsoon (1.71 ppmv) and lowest during monsoon (0.79 ppmv). The seasonal trend of NOX showed highest in winter (56.8 ppbv) and lowest in monsoon (22.5 ppbv). The monthly mixing ratios of O3, CO, and NOX showed distinct variability, which may be attributed to changing anthropogenic activities, planetary boundary layer processes, and local meteorology. O3 was significantly related to temperature but inversely associated with relative humidity and wind speed. The association between CO, NOX with relative humidity, temperature, wind speed showed discrete results. The (dO3/dt) in the morning and evening duration were about 5.0 ppbv/h and -4.1 ppbv/h respectively.

This paper presents the analysis of the frequency of lightning strikes associated with thunderstorm and precipitation distributions over smooth oceanic surface relative to that over solid earth surface in the tropical region. Long-term (1998–2014) data retrieved from the Lightning Imaging Sensors (LIS) of the Tropical Rainfall Measuring Mission (TRMM) satellite shows lightning flash counts over Indian landmass found to be 9.1 times more than those over the smooth oceanic surface of the Arabian Sea and the Bay of Bengal. On the other hand, the annual variation of rainfall-to-lightning ratio (RLR) is found to be 0.8 over Indian landmass, whereas it is 10 over the oceanic surfaces. We discuss the convective strength of thunderstorm distributions over land and oceanic regions by examining the relationships of RLR to the Bowen ratio, sea surface temperature (SST), and maximum air temperature over land, maximum updraft speed, and Aerosol Optical Depth (AOD) and cloud ice water content. The RLR shows high positive Pearson’s correlations with the Bowen ratio, maximum updraft speed, AOD, and cloud ice water content over land region relative to those measured over the oceanic region. The RLR also shows negative correlations with SST, maximum updraft speed, AOD over the oceanic region. The results are applicable in understanding of the convective characteristics of thunderstorm distributions and lightning flashes over the tropical regions of the world.

This paper presents the lightning activity, aerosol optical depth (AOD) and climatic parameters (Bowen ratio, relative humidity, rainfall, maximum surface temperature and maximum updraft speed) over wet (Northeast India—NEI) and dry (Northwest India—NWI) land surfaces in a comparative analysis. The analyses are performed on flash counts and weather data of 17 years (1998–2014) retrieved from the Tropical Rainfall Measuring Mission (TRMM) lightning imaging sensors (LIS) and the Moderate Resolution Imaging Spectroradiometer (MODIS), respectively. The first higher peak for flash counts during pre-monsoon (April–May) and second lower peak during September over wet NEI and dry NWI regions indicate the development of strong electrified storms during pre-monsoon and weakly electrified clouds during the withdrawal phase of the southwest summer monsoon. The monthly means of flash counts, Bowen ratio, maximum surface temperature, AOD and maximum updraft speed are higher by 27, 81, 16, 50 and 16%, respectively, for NWI than those of NEI. The relative humidity and rainfall are higher by 12% and 73% for NEI than those of NWI, respectively. The Pearson’s correlation coefficients of lightning activity with climatic parameters and AOD demonstrate the distinctive orographic lifting, moisture content and vertical wind shear in the upper troposphere in the regional climatic zone of dry NWI in comparison to that of wet NEI.

Bengaluru, also considered India’s Silicon Valley, has seen steady growth in population over the years. Bengaluru’s rapid development has resulted in dwindling reservoirs, increased traffic congestion, high levels of air pollution, and, to some measure, a rise in summer temperatures. As a result of these changes in urban form over the last decade, anthropogenic heat fluxes for ozone production have increased. However, an observational study on the effects of growing urbanisation on trace gases in Bengaluru for various seasons and periods of the day is missing. Hence, in situ measurements of O3, NO, NO2, and NOX concentrations were carried out at Bengaluru, India, from January 2015 to December 2018. The data were examined for diurnal and interannual variations in trace gas mixing concentrations. The diurnal trend in O3 exhibits unimodal behaviour. Changes in photochemistry, local meteorology, and the planetary boundary layer’s distinctive features cause a rise in the value of concentrations and lead to a peak. In contrast, the diurnal trend in NO, NO2, and NOX displayed a bimodal peak due to the combined effect of vehicular emissions and the planetary boundary layer. The link involving the oxidant OX (O3 + NO2) and NOx levels were investigated to determine the NOx-independent regional and NOx-dependent local contributions to OX in the atmosphere. Daytime contributions are higher than night-time contributions, according to the present study. The observed anomalies could be the consequence of photochemical processes that produce OX.

This paper presents a relationship of lightning activity with maximum air temperature, Bowen ratio, rainfall, cloud ice contents and Aerosol Optical Depth (AOD) over India during transition period from dry to wet seasons. Lightning flash count data and weather parameters are retrieved from the Tropical Rainfall Measuring Mission (Lightning Imaging Sensor - LIS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) satellites for the period of 17 years (1998-2014). The Pearson correlation between lightning flash count and Bowen ratio is found to be coefficient of R = 0.95 for both dry and wet seasons. For dry season, the Pearson correlation of lightning flash count with surface maximum air temperature is found to be coefficient of R = 0.97 whereas, that for wet season negative coefficient of R = -0.89. The comparative analysis of Pearson correlations of lightning flash counts with AOD, rainfall and cloud ice content are found to be coefficients higher by 20%, 28% and 34% for dry season than those of during wet season, respectively. The results of lightning activity and weather parameters in comparative analyses over the Indian region may be useful for better understanding the differential convection characteristics during transition period of dry to wet season. The results are also important for estimations of impact associated with lightning strikes to ground during dry and wet seasons.

Air quality has become one of the most important environmental concerns for Delhi, India. In this perspective, we have developed a high-resolution air quality prediction system for Delhi based on chemical data assimilation in the chemical transport model Weather Research and Forecasting with Chemistry (WRF-Chem). The data assimilation system was applied to improve the PM2.5 forecast via assimilation of MODIS aerosol optical depth retrievals using three-dimensional variational data analysis scheme. Near real-time MODIS fire count data were applied simultaneously to adjust the fire-emission inputs of chemical species before the assimilation cycle. Carbon monoxide (CO) emissions from biomass burning, anthropogenic emissions, and CO inflow from the domain boundaries were tagged to understand the contribution of local and non-local emission sources. We achieved significant improvements for surface PM2.5 forecast with joint adjustment of initial conditions and fire emissions.

In this study, we used remotely sensed backscattered profiles from a ceilometer to characterize the vertical and horizontal mixing of aerosols in the polluted planetary boundary layer (PBL). These profiles revealed the structure of the boundary layer, which included the mixed layer, the nocturnal residual layer and the elevated aerosol layer far above the mixed layer over Delhi. The accumulation of aerosols near the surface during feeble turbulence and the mixing of aerosols from the residual layer into the surface layer during convection was captured very well by a ceilometer. The backscattered signal from a height of 45 m above the ground was strongly correlated (82

In this study, the sensitivity of the Weather Research and Forecasting (WRF) model to simulate the life cycle of a dense fog event that occurred on 23–24 January 2016 is evaluated using different model configurations. For the first time, intensive observational periods (IOPs) were made during the unique winter fog experiment (WIFEX) that took place over Delhi, India, where air quality is serious during the winter months. The multiple sensitivity experiments to evaluate the WRF model performance included parameters such as initial model and boundary conditions, vertical resolution in the lower boundary layer (BL), and the planetary BL (PBL) physical parameterizations. In addition, the model sensitivity was tested using various configurations that included domain size and grid resolution. Results showed that simulations with a high number of vertical levels within the lower PBL height (i.e., 10 levels below 300 m) simulated the accurate timing of fog formation, development, and dissipation. On the other hand, simulations with less vertical levels in the PBL captured only the mature physical characteristics of the fog cycle. A comparison of six local PBL schemes showed little variation in the onset of fog life cycle in comparison to observations of visibility. However, comparisons of observations with thermodynamical values such as 2-m temperature and longwave radiation showed poor relationships. Overall, quasi-normal scale elimination (QNSE) and MYNN 2.5 PBL schemes simulated the complete fog life cycle correctly with high liquid water content (LWC; 0.5/0.35 g m−3), while other schemes only responded during the mature phase.

Data on mass concentration of PM2.5 and its carbonaceous and water soluble inorganic chemical ions were compiled through sampling of PM2.5 at Indira Gandhi International Airport, Delhi during Dec. 16, 2015-Feb. 15, 2016 under Winter Fog Experiment (WIFEX) programof the Ministry of Earth Sciences (MoES) and analysing the samples. The data so generated were interpreted in terms of their variation on different time scales and apportioning their sources. It is found that mass concentration of PM2.5 averaged over the whole period of observation was 198.6 +/- 55.6. The concentration of organic carbon (OC) and elemental carbon (EC) was 24.7 +/- 9.4 and 11.7 +/- 4.7 mu g/m(3) respectively with no any trend of increase or decrease over the observational period. SO42-, Cl- and NO3- dominated over other anions with their overall average concentration 34.0 +/- 23.1, 32.7 +/- 16.1 and 13.3 +/- 8.7 mu g/m(3) respectively. Among cations, NH4+ showed highest concentration with an average value of 21.0 +/- 10.6 mu g/m(3). Variation of daily average mass concentration of these parameters over the period of observation matched well with the variation of PM2.5 mass concentration indicating thereby to be the major contributors to the PM2.5 mass. NH4+ mostly occurred as NH4Cl and NH4NO3 and poorly as (NH4)(2)SO4 or NH4HSO4. H+ ion mostly occurred as H2SO4 and occasionally as HNO3. Carbonaceous aerosols and NO3- were mainly generated from fossil-fuel combustion. NH4+ and anthropogenic Cl- were mostly generated by biomass burning. The source of SO42- was found to be industries and thermal power plants. Continental Ca2+ and Mg2+ originated from thermal power plants and soil dust. (C) 2019 Elsevier B.V. All rights reserved.