Natural processes dominate the pollution levels during COVID-19 lockdown over India.

The lockdown measures that were taken to combat the COVID-19 pandemic minimized anthropogenic activities and created natural laboratory conditions for studying air quality. Both observations and WRF-Chem simulations show a 20-50% reduction (compared to pre-lockdown and same period of previous year) in the concentrations of most aerosols and trace gases over Northwest India, the Indo Gangetic Plain (IGP), and the Northeast Indian regions. It is shown that this was mainly due to a 70-80% increase in the height of the boundary layer and the low emissions during lockdown. However, a 60-70% increase in the pollutants levels was observed over Central and South India including the Arabian sea and Bay of Bengal during this period, which is attributed to natural processes. Elevated (dust) aerosol layers are transported from the Middle East and Africa via long-range transport, and a decrease in the wind speed (20-40%) caused these aerosols to stagnate, enhancing the aerosol levels over Central and Southern India. A 40-60% increase in relative humidity further amplified aerosol concentrations. The results of this study suggest that besides emissions, natural processes including background meteorology and dynamics, play a crucial role in the pollution concentrations over the Indian sub-continent.

Comparison of INSAT-3D retrieved total column ozone with ground-based and AIRS observations over India.

Ozone plays an important role in the thermal structure and chemical composition of the atmosphere. The present study compares the temporal and spatial distributions of Total Column Ozone (TCO) over the Indian sub-continent retrieved from a geostationary Indian National Satellite (INSAT-3D) and Atmospheric Infrared Sounder (AIRS). The INSAT-3D TCO values are also evaluated against the Dobson spectrophotometer observations at two locations. The inter-comparison results reveal a good correlation of 0.8, the bias of -5 DU, and Root Mean Square Error (RMSE) of 15 DU approximately between the TCO retrieved from INSAT-3D and AIRS. The lowest RMSE and highest correlation coefficient were found in the pre-monsoon season. The INSAT-3D and AIRS show reasonable agreement with the RMSE varying between 10 and 30 DU. On the other hand, evaluation of the INSAT-3D TCO with the ground-based observations from Dobson spectrophotometers located at New Delhi and Varanasi showed fair agreement with a maximum monthly mean correlation coefficient of 0.68 and 0.76, respectively, and RMSE varying from 11 to 16 DU for both the stations. The seasonal distribution of TCO and its variation over the Indian region has also been studied using INSAT-3D and AIRS data. The analysis exhibits strong seasonal variations, with higher values in pre-monsoon season and minimum values in winter season. The noticeable seasonal variability of TCO can be attributed to complex combination of photochemical and dynamical processes in the troposphere and stratosphere. The main objectives of the study are to compare the INSAT-3D TCO with two independent ground-based Dobson spectrophotometer observations and Atmospheric Infrared Sounder (AIRS) aboard NASA's Aqua satellite.

Analysis of Outdoor Thermal Discomfort Over the Kingdom of Saudi Arabia.

In this study, the variability and trends of the outdoor thermal discomfort index (DI) in the Kingdom of Saudi Arabia (KSA) were analyzed over the 39-year period of 1980-2018. The hourly DI was estimated based on air temperature and relative humidity data obtained from the next-generation global reanalysis from the European Center for Medium-Range Weather Forecasts and in-house high-resolution regional reanalysis generated using an assimilative Weather Research Forecast (WRF) model. The DI exceeds 28°C, that is, the threshold for human discomfort, in all summer months (June to September) over most parts of the KSA due to a combination of consistently high temperatures and relative humidity. The DI is greater than 28°C for 8-16 h over the western parts of KSA and north of the central Red Sea. A DI of >28°C persistes for 7-9 h over the Red Sea and western KSA for 90% of summer days. The spatial extent and number of days with DI > 30°C, that is, the threshold for severe human discomfort, are significantly lower than those with DI > 28°C. Long-term trends in the number of days with DI > 28°C indicate a reduced rate of increase or even a decrease over some parts of the southwestern KSA in recent decades (1999-2018). Areas with DI > 30°C, in particular the northwestern regions of the Arabian Gulf and its adjoining regions, also showed improved comfort levels during recent decades. Significant increases in population and urbanization have been reported throughout the KSA during the study period. Analysis of five-years clinical data suggests a positive correlation between higher temperatures and humidity with heat-related deaths during the Hajj pilgrimage. The information provided herein is expected to aid national authorities and policymakers in developing necessary strategies to mitigate the exposure of humans to high levels of thermal discomfort in the KSA.

An integrated WRF/HYSPLIT modeling approach for the assessment of PM(2.5) source regions over the Mississippi Gulf Coast region.

Fine particulate matter (PM(2.5)) is majorly formed by precursor gases, such as sulfur dioxide (SO(2)) and nitrogen oxides (NO(x)), which are emitted largely from intense industrial operations and transportation activities. PM(2.5) has been shown to affect respiratory health in humans. Evaluation of source regions and assessment of emission source contributions in the Gulf Coast region of the USA will be useful for the development of PM(2.5) regulatory and mitigation strategies. In the present study, the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model driven by the Weather Research & Forecasting (WRF) model is used to identify the emission source locations and transportation trends. Meteorological observations as well as PM(2.5) sulfate and nitric acid concentrations were collected at two sites during the Mississippi Coastal Atmospheric Dispersion Study, a summer 2009 field experiment along the Mississippi Gulf Coast. Meteorological fields during the campaign were simulated using WRF with three nested domains of 36, 12, and 4 km horizontal resolutions and 43 vertical levels and validated with North American Mesoscale Analysis. The HYSPLIT model was integrated with meteorological fields derived from the WRF model to identify the source locations using backward trajectory analysis. The backward trajectories for a 24-h period were plotted at 1-h intervals starting from two observation locations to identify probable sources. The back trajectories distinctly indicated the sources to be in the direction between south and west, thus to have origin from local Mississippi, neighboring Louisiana state, and Gulf of Mexico. Out of the eight power plants located within the radius of 300 km of the two monitoring sites examined as sources, only Watson, Cajun, and Morrow power plants fall in the path of the derived back trajectories. Forward dispersions patterns computed using HYSPLIT were plotted from each of these source locations using the hourly mean emission concentrations as computed from past annual emission strength data to assess extent of their contribution. An assessment of the relative contributions from the eight sources reveal that only Cajun and Morrow power plants contribute to the observations at the Wiggins Airport to a certain extent while none of the eight power plants contribute to the observations at Harrison Central High School. As these observations represent a moderate event with daily average values of 5-8 µg m(-3) for sulfate and 1-3 µg m(-3) for HNO(3) with differences between the two spatially varied sites, the local sources may also be significant contributors for the observed values of PM(2.5).

Simulation of atmospheric dispersion of elevated releases from point sources in Mississippi Gulf Coast with different meteorological data.

Atmospheric dispersion calculations are made using the HYSPLIT Particle Dispersion Model for studying the transport and dispersion of air-borne releases from point elevated sources in the Mississippi Gulf coastal region. Simulations are performed separately with three meteorological data sets having different spatial and temporal resolution for a typical summer period in 1-3 June 2006 representing a weak synoptic condition. The first two data are the NCEP global and regional analyses (FNL, EDAS) while the third is a meso-scale simulation generated using the Weather Research and Forecasting model with nested domains at a fine resolution of 4 km. The meso-scale model results show significant temporal and spatial variations in the meteorological fields as a result of the combined influences of the land-sea breeze circulation, the large scale flow field and diurnal alteration in the mixing depth across the coast. The model predicted SO(2) concentrations showed that the trajectory and the concentration distribution varied in the three cases of input data. While calculations with FNL data show an overall higher correlation, there is a significant positive bias during daytime and negative bias during night time. Calculations with EDAS fields are significantly below the observations during both daytime and night time though plume behavior follows the coastal circulation. The diurnal plume behavior and its distribution are better simulated using the mesoscale WRF meteorological fields in the coastal environment suggesting its suitability for pollution dispersion impact assessment in the local scale. Results of different cases of simulation, comparison with observations, correlation and bias in each case are presented.