Sensitivity of WRF/Chem simulated PM2.5 to initial/boundary conditions and planetary boundary layer parameterization schemes over the Indo-Gangetic Plain.

The ability of a chemical transport model to simulate accurate meteorological and chemical processes depends upon the physical parametrizations and quality of meteorological input data such as initial/boundary conditions. In this study, weather research and forecasting model coupled with chemistry (WRF-Chem) is used to test the sensitivity of PM2.5 predictions to planetary boundary layer (PBL) parameterization schemes (YSU, MYJ, MYNN, ACM2, and Boulac) and meteorological initial/boundary conditions (FNL, ERA-Interim, GDAS, and NCMRWF) over Indo-Gangetic Plain (Delhi, Punjab, Haryana, Uttar Pradesh, and Rajasthan) during the winter period (December 2017 to January 2018). The aim is to select the model configuration for simulating PM2.5 which shows the lowest errors and best agreement with the observed data. The best results were achieved with initial/boundary conditions from ERA and GDAS datasets and local PBL parameterization (MYJ and MYNN). It was also found that PM2.5 concentrations are relatively less sensitive to changes in initial/boundary conditions but in contrast show a stronger sensitivity to changes in the PBL scheme. Moreover, the sensitivity of the simulated PM2.5 to the choice of PBL scheme is more during the polluted hours of the day (evening to early morning), while that to the choice of the meteorological input data is more uniform and subdued over the day. This work indicates the optimal model setup in terms of choice of initial/boundary conditions datasets and PBL parameterization schemes for future air quality simulations. It also highlights the importance of the choice of PBL scheme over the choice of meteorological data set to the simulated PM2.5 by a chemical transport model.

How Much Does Large-Scale Crop Residue Burning Affect the Air Quality in Delhi?

Elevated PM2.5 concentrations frequently cause severe air pollution events in Delhi. Till recently, the effect of crop residue burning on the air quality in Delhi has not been fully quantified and the approaches to control the impact of fire emissions have not been effective. In this study, for the first time, we quantified the statewise contribution of post-monsoon crop residue burning in the northwestern states of India to surface PM2.5 concentrations in Delhi using several sensitivity experiments with the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) and FINNv1.5 fire emission inventory. Results were evaluated with ground-based observations in Delhi (21 stations), Punjab, and Haryana (14 stations). On average, ∼20% of PM2.5 concentration in Delhi during the post-monsoon season (October-November) was found to be contributed by nonlocal fire emissions. However, on typical air pollution events, fire emissions contributed as high as 50-75% (80-120 µg/m3) to PM2.5 in Delhi, highlighting the importance of both external transport and local emissions to PM2.5 pollution in Delhi.

Stubble-burning activities in north-western India in 2021: Contribution to air pollution in Delhi.

Stubble-burning in northern India is an important source of atmospheric particulate matter (PM) and trace gases, which significantly impact local and regional climate, in addition to causing severe health risks. Scientific research on assessing the impact of these burnings on the air quality over Delhi is still relatively sparse. The present study analyzes the satellite-retrieved stubble-burning activities in the year 2021, using the MODIS active fire count data for Punjab and Haryana, and assesses the contribution of CO and PM2.5 from such biomass-burning activities to the pollution load in Delhi. The analysis suggests that the satellite-retrieved fire counts in Punjab and Haryana were the highest among the last five years (2016-2021). Further, we note that the stubble-burning fires in the year 2021 are delayed by ∼1 week compared to that in the year 2016. To quantify the contribution of the fires to the air pollution in Delhi, we use tagged tracers for CO and PM2.5 emissions from fire emissions in the regional air quality forecasting system. The modeling framework suggests a maximum daily mean contribution of the stubble-burning fires to the air pollution in Delhi in the months of October-November 2021 to be around 30-35%. We find that the contribution from stubble burning activities to the air quality in Delhi is maximum (minimum) during the turbulent hours of late morning to afternoon (calmer hours of evening to early morning). The quantification of this contribution is critical from the crop-residue and air-quality management perspective for policymakers in the source and the receptors regions, respectively.