A 1-D model to retrieve the vertical profiles of minor atmospheric constituents for cloud microphysical modeling: II. Simulation of diurnal cycle.

The accurate forecast of the diurnal cycle of the number concentration of trace gases is vital due to their influence on precipitation processes by controlling the number concentration of cloud condensation nuclei (CCN). 1-D hybrid Monte Carlo-Gear solver developed to retrieve vertical profiles of the number concentration of CCNs for microphysics modeling has been tested for representation of the diurnal cycle in the present paper. The retrieved profiles of CH4 and SO2 have been tested with the Copernicus Atmosphere Monitoring Service (CAMS) model at 3-hour time intervals for four megacities: Delhi, Kolkata, Chennai, and Mumbai for rainy and non-rainy days. The retrieved profiles have shown diurnal variation up to 18 UTC at all pressure levels with lead or lag with that of the CAMS model. After 18 UTC there was a furious increase in the number concentrations. During non-rainy days, the 1-D model slightly overestimated (underestimated) the maximum (minimum) number concentrations of CH4 over Delhi whereas concentrations are overestimated over Kolkata, Chennai, and Mumbai. Forecasted CH4 has a good (weak) correlation over Chennai (Mumbai) respectively. The 1-D model overestimated (overestimated) the maximum (minimum) number concentrations of SO2 over Delhi but the maximum (minimum) concentrations are underestimated (overestimated) over Kolkata, Chennai, and Mumbai. The number concentrations of SO2 have shown a good correlation for all megacities except Delhi. CH4 number concentration is overestimated during rainy days. Delhi and Kolkata show a good correlation of CH4 during rainy days. SO2 during rainy days is underestimated except over Chennai and both models show a good correlation except over Mumbai. Overall, it can be stated that the 1-D hybrid solver is successful in simulating the monthly mean diurnal variation of vertical profiles of CH4 and SO2, and its implementation in the global model may estimate the number concentrations with better accuracies.

A 1-D model to retrieve the vertical profiles of minor atmospheric constituents for cloud microphysical modeling: I. Formulation and validation.

Determining the number concentration of minor constituents in the atmosphere is very important as it determines the whole tropospheric chemistry process. These constituents may act as cloud condensation nuclei (CCN) and ice nuclei (IN), impacting heterogeneous nucleation inside the cloud. However, the estimations of the number concentration of CCN/IN in cloud microphysical parameters are associated with uncertainties. In the present work, a hybrid Monte Carlo Gear solver has been developed to retrieve profiles of CH4, N2O, and SO2. The idealized experiments have been carried out using this solver for retrieving vertical profiles of these constituents over four megacities, viz., Delhi, Mumbai, Chennai, and Kolkata. Community Long-term Infrared Microwave Coupled Atmospheric Product System (CLIMCAPS) dataset around 0800 UTC (2000UTC) has been used for initializing the number concentration of CH4, N2O, and SO2 for daytime (nighttime). The daytime (nighttime) retrieved profiles have been validated using 2000 UTC (next day 0800 UTC) CLIMCAPS products. ERA5 temperature dataset has been used to estimate the kinematic rate of reactions with 1000 perturbations determined using Maximum Likelihood Estimation (MLE). The retrieved profiles and CLIMCAPS products are in very good agreement, as evidenced by the percentage difference between them within the range of 1.3 × 10-5-60.8 % and the coefficient of determination mainly within the range between 81 and 97 %. However, during the passage of tropical cyclone and western disturbance, its value became as low as 27 and 65 % over Chennai and Kolkata, respectively. The enactment of synoptic scale systems such as western disturbances, tropical cyclone Amphan, and easterly waves caused disturbed weather over these megacities-the retrieved profiles during disturbed weather cause large deviations of vertical profiles of N2O. However, the profiles of CH4 and SO2 have less deviation. It is inferred that incorporating this methodology in the dynamical model will be useful to simulate the realistic vertical profiles of the minor constituents in the atmosphere.

Diurnal and temporal changes in air pollution during COVID-19 strict lockdown over different regions of India.

Lockdown measures to contain COVID-19 pandemic has resulted in a considerable change in air pollution worldwide. We estimate the temporal and diurnal changes of the six criteria air pollutants, including particulate matter (PM2.5 and PM10) and gaseous pollutants (NO2, O3, CO, and SO2) during lockdown (25th March - 3rd May 2020) across regions of India using the observations from 134 real-time monitoring sites of Central Pollution Control Board (CPCB). Significant reduction in PM2.5, PM10, NO2, and CO has been found in all the regions during the lockdown. SO2 showed mixed behavior, with a slight increase at some sites but a comparatively significant decrease at other locations. O3 also showed a mixed variation with a mild increase in IGP and a decrease in the South. The absolute decrease in PM2.5, PM10, and NO2 was observed during peak morning traffic hours (08-10 Hrs) and late evening (20-24 Hrs), but the percentage reduction is almost constant throughout the day. A significant decrease in day-time O3 has been found over Indo Gangetic plain (IGP) and central India, whereas night-time O3 has increased over IGP due to less O3 loss. The most significant reduction (∼40-60%) was found in PM2.5 and PM10. The highest decrease in PM was found for the north-west and IGP followed by South and central regions. A considerable reduction (∼30-70%) in NO2 was found except for a few sites in the central region. A similar pattern was observed for CO having a ∼20-40% reduction. The reduction observed for PM2.5, PM10, NO2, and enhancement in O3 was proportional to the population density. Delhi's air quality has improved with a significant reduction in primary pollutants, however, an increase in O3 was observed. The changes reported during the lockdown are combined effect of changes in the emissions, meteorology, and atmospheric chemistry that requires detailed investigations.

High resolution vehicular PM10 emissions over megacity Delhi: Relative contributions of exhaust and non-exhaust sources.

Exposure to particulate matter (PM) from traffic can cause adverse health risks. Recent studies project an increase in non-exhaust emissions in the future despite a reduction in exhaust emissions. While there is a lot of research on exhaust emissions, the challenges remain to quantify non-exhaust emissions, especially in developing countries. In this work, an approach has been developed, and on-road vehicular non-exhaust PM emissions are estimated due to brake wear, tyre wear, road wear and resuspension, at very high resolution (100 m2) over an Indian megacity Delhi. Further, the relative contribution of non-exhaust emissions to the total vehicular emission was also calculated. The total PM10 emissions in megacity Delhi were 31.5 Gg/year, which is mainly dominated by the non-exhaust sources. The non-exhaust emissions were found to be six times (86%) of the exhaust emission (14%). The highest contribution to the total vehicular PM emission comes from the cars (34%) followed by buses (23%) and heavy commercial vehicles (HCVs, 17%), which is dominated by resuspension of dust. Cars and buses contribute less to exhaust emissions and more to non-exhaust emissions. Majors roads are the largest contributors to the total emissions in Delhi. The emissions from HCVs, diesel cars along with the other diesel vehicles result in diesel vehicles contributing more than the petrol vehicles to both exhaust and non-exhaust emissions. As India target to reduce PM pollution under the national clean air program, the current study will be useful to plan a suitable intervention to mitigate air pollution and associated health impacts.

Ionic and heavy metal composition of respirable particulate in Madurai, India.

Airborne particulate matter (PM(10)) was collected for a period of 1 year at six locations in Madurai city, India. The chemical analyses on PM(10) samples were carried out for the estimation of heavy metals and ions using atomic absorption spectroscopy and ion chromatography respectively. The average PM(10) concentrations varied from 97.2 to 152.5 microg/m(3), which were found to be below the Indian air quality standards. While industrial areas had the highest concentrations of heavy metals such as Fe, Zn and Cr and also the SO(4)(2-) ions, traffic areas with relatively higher traffic densities in the city endured highest concentrations of Cd and the NO(3)(-) ion. As gaseous pollutants serve as precursors of ionic particles in the atmospheric environment, gaseous pollution control is necessitated along with particulate with special reference to heavy metal and ion pollution abatement for the sustainable development of Madurai city.