New Delhi: air-quality warning system cuts peak pollution

Effectiveness of respiratory face masks in reducing acute PM2.5 pollution exposure during peak pollution period in Delhi

The cities of North India, such as Delhi, face a significant public health threat from severe air pollution. Between October 2021 and January 2022, 79 % of Delhi's daily average PM2.5 (Particulate matter with an aerodynamic diameter ≤ 2.5 μm) values exceeded 100 μg/m3 (the permissible level being 60 μg/m3 as per Indian standards). In response to this acute exposure, using Respiratory Face Masks (RFMs) is a cost-effective solution to reduce immediate health risks while policymakers develop long-term emission control plans. Our research focuses on the health and economic benefits of using RFMs to prevent acute exposure to PM2.5 pollution in Delhi for different age groups. Our findings indicate that, among the fifty chosen RFMs, M50 has greatest potential to prevent short-term excess mortality (908 in age ranges 5-44), followed by M49 (745) and M48 (568). These RFMs resulted in estimated economic benefits of 500.6 (46 %), 411.1 (37 %), and 313.4 (29 %) million Indian Rupee (INR), respectively during October-January 2021-22. By wearing RFMs such as M50, M49, and M48 during episodes of bad air quality, it is estimated that 13 % of short-term excess mortality and associated costs could be saved if at least 30 % of Delhi residents followed an alert issued by an operational Air Quality Early Warning System (AQEWS) developed by the Ministry of Earth Sciences. Our research suggests that RFMs can notably decrease health and economic burdens amid peak PM2.5 pollution in post-monsoon and winter seasons until long-term emission reduction strategies are adopted. It is suggested that an advisory may be crafted in collaboration with statutory bodies and should be disseminated to assist the vulnerable population in using RFMs during winter. The analysis presented in this research is purely science based and outcomes of study are in no way to be construed as endorsement of product.

HONO chemistry and its impact on the atmospheric oxidizing capacity over the Indo-Gangetic Plain

Chemical processes involving nitrous acid (HONO) play a pivotal role as it is a notable source of hydroxyl (∙OH) radicals, influencing the oxidation capacity of the atmosphere. We conduct a comprehensive investigation into the temporal dynamics of HONO, other gases (nitrogen oxides (NOx), ozone (O3), ammonia (NH3), sulphur dioxide (SO2), and nitric acid (HNO3)), particulate matter (PM2.5), and meteorological parameters using measurements that took place during the Winter Fog Experiment (WiFEx) campaign in Delhi, India, during the winter of 2017-2018. Remarkable day-to-day variations in HONO concentrations are observed, with the peak value reaching 54.5 μg m-3 during a fog event. This coincides with elevated levels of sulfate and nitrate in aerosols, underscoring the significant role of heterogeneous fog chemistry in HONO production. We investigated HONO sources and sinks during fog periods by using a photochemical box model. The model shows that the gas-phased chemistry of HONO predicts concentrations lower by an order of magnitude compared to observations (peaking at 0.60 μg m-3 compared to the average observed value of 7.00 μg m-3). The calculated production rates of HONO from observations for daytime to nighttime peaks are 3.10 μg m-3 h-1 (1.1 × 107 molecules cm3 s-1) and 2.00 μg m-3 h-1 (7.1 × 106 molecules cm3 s-1), respectively. This shows the existence of an undefined heterogeneous reaction pathway for HONO production. At the peak of HONO concentration, we estimated an ∙OH formation rate of 9.4 × 107 molecules cm3 s-1 due to the photolysis of HONO, which is much higher than the production of HONO from the reaction of O1D with H2O. This underscores the predominant role of HONO photolysis as the primary source of ∙OH radicals compared to other pathways and highlights the significant role of HONO chemistry in influencing atmospheric oxidation capacity.

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 PM_2.5 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 PM_2.5 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.

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 PM_2.5 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 PM_2.5 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 PM_2.5 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 PM_2.5 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 PM_2.5 by a chemical transport model.