Assessment of seasonal variability of PM, BC and UFP levels at a highway toll stations and their associated health risks.

As a part of their occupation, workers at toll stations are exposed to traffic emissions during the working shift, which sometimes stretches to 12 h. To assess the exposure and subsequent health risk of these workers, a study was performed on a highway toll station in India. PM1, PM2.5, PM10, BC and UFP concentration were determined inside a toll collectors' cabin and outside in a free-flowing traffic section (125 m from the toll cabin). The concentrations varied in the following range: PM1 (40.69-226.13 µg m-3), PM2.5 (49.71-247.36 µg m-3), PM10 (83.15-458.14 µg m-3) and BC (2.1-87.5 µg m-3) and UFP: 101-53705 pt cm-3. The mean concentration inside the cabin was 1.34 (PM1), 1.35 (PM2.5), 1.16 (PM10) and 2.91 (BC) times the concentration outside for the summer season. The corresponding levels in the winter season were 1.14 (PM1), 1.11 (PM2.5), 1.11 (PM10), 2.50 (BC) and 1.82 (UFP). In addition to the exhaust emission, the non-exhaust emissions such as resuspension of crustal particles, fly ash and bioaerosols were identified. Using the Multiple Path Particle Dosimetry model for two groups - adults (18-21 years) and adults (21+ years), it was estimated that the pulmonary deposition of in-cabin workers were 50% (PM2.5) -75% (PM1) higher than the workers outside the cabin. Particle mass deposition was found to be higher for adults (21+ years) than adults (18-21 years) for both the seasons. The study quantitatively assessed the health risk faced by the workers in terms of exposure concentration and deposition in respiratory tract. More such studies at different traffic mix and climate can provide better estimates of health risk of toll workers that can be used to devise appropriate strategies for control of it.

Did unprecedented air pollution levels cause spike in Delhi's COVID cases during second wave?

The onset of the second wave of COVID-19 devastated many countries worldwide. Compared with the first wave, the second wave was more aggressive regarding infections and deaths. Numerous studies were conducted on the association of air pollutants and meteorological parameters during the first wave of COVID-19. However, little is known about their associations during the severe second wave of COVID-19. The present study is based on the air quality in Delhi during the second wave. Pollutant concentrations decreased during the lockdown period compared to pre-lockdown period (PM2.5: 67 µg m-3 (lockdown) versus 81 µg m-3 (pre-lockdown); PM10: 171 µg m-3 versus 235 µg m-3; CO: 0.9 mg m-3 versus 1.1 mg m-3) except ozone which increased during the lockdown period (57 µg m-3 versus 39 µg m-3). The variation in pollutant concentrations revealed that PM2.5, PM10 and CO were higher during the pre-COVID-19 period, followed by the second wave lockdown and the lowest in the first wave lockdown. These variations are corroborated by the spatiotemporal variability of the pollutants mapped using ArcGIS. During the lockdown period, the pollutants and meteorological variables explained 85% and 52% variability in COVID-19 confirmed cases and deaths (determined by General Linear Model). The results suggests that air pollution combined with meteorology acted as a driving force for the phenomenal growth of COVID-19 during the second wave. In addition to developing new drugs and vaccines, governments should focus on prediction models to better understand the effect of air pollution levels on COVID-19 cases. Policy and decision-makers can use the results from this study to implement the necessary guidelines for reducing air pollution. Also, the information presented here can help the public make informed decisions to improve the environment and human health significantly.

Association of air pollution and meteorological variables with COVID-19 incidence: Evidence from five megacities in India.

Although lockdown of the industrial and transport sector and stay at home advisories to counter the COVID-19 pandemic have shown that the air quality has improved during this time, very little is known about the role of ambient air pollutants and meteorology in facilitating its transmission. This paper presents the findings from a study that was conducted to evaluate whether air quality index (AQI), three primary pollutants (PM2.5, PM10 and CO), Ground level ozone (O3) and three meteorological variables (temperature, relative humidity, wind speed) have promoted the COVID-19 transmission in five megacities of India. The results show significant correlation of PM2.5, PM10, CO, O3 concentrations, AQI and meteorological parameters with the confirmed cases and deaths during the lockdown period. Among the meteorological variables considered, temperature strongly correlated with the COVID-19 cases and deaths during the lockdown (r=0.54;0.25) and unlock period (r=0.66;0.25). Among the pollutants, ozone, and among the meteorological variables, temperature, explained the highest variability, up to 34% and 30% respectively, for COVID-19 confirmed cases and deaths. AQI was not a significant parameter for explaining the variations in confirmed and death cases. WS and RH could explain 10-11% and 4-6% variations of COVID-19 cases. A GLM model could explain 74% and 35% variability for confirmed cases and deaths during the lockdown and 66% and 19% variability during the unlock period. The results suggest that meteorological parameters may have promoted the COVID-19 incidences, especially the confirmed cases. Our findings may encourage future studies to explore more about the role of ambient air pollutants and meteorology on transmission of COVID-19 and similar infectious diseases.

In-vehicle PM2.5 personal concentrations in winter during long distance road travel in India.

During travel, passengers are exposed to high concentrations of PM which constitute a significant fraction of daily personal exposures. We carried out comprehensive mobile monitoring for a distance of 400km on an Indian National Highway during the winter season to evaluate the PM2.5 Personal Concentrations (PC) and mass exposure in three traffic microenvironments (public bus, car with AC (Car CW) and car without AC (Car OW)) and to quantify the key factors that influence it. The mean concentrations were highest inside Car OW (175.3±142.7µgm-3) followed by bus (134.0±113.9µgm-3) and lowest in Car CW (78.8±37.1µgm-3). PC during in-city highway sections were greater than out-city highway sections during Bus and Car OW journeys. PC were higher during morning than evening journeys in Bus and Car OW. Mean PC in different seating positions in Bus followed the trend: middle>rear>front. Results of the Linear Mixed-Effects Models (LMM) indicated that journey timings were the significant predictors of PC for Bus and Car OW. The exposures per unit time followed trend: Car OW>Bus>Car CW. Total mass of inhaled exposures however followed a different trend: Bus>Car OW>Car CW, because Bus needed longer duration to cover the entire distance. Car CW users experienced both the least PC and mass exposures. We estimated that the road repairing works contributed ~22% in Bus and Car OW, and ~12% in Car CW increment in mass exposures. These findings indicate that management of exposures needs to consider mass exposures in addition to PC, for curtailing the adverse health effects relating to long distance journeys. Highway authorities should focus on early completion of construction and repairing activities to reduce exposures to passengers.

A comparison of personal exposure to air pollutants in different travel modes on national highways in India.

People often travel a long distance on highways to the nearest city for professional/business activities. However, relatively few publications on passenger exposure to pollutants on highways in India or elsewhere are available. The aim of this study was to examine the contribution of different travel modes to passengers' pollutant exposure for a long distance travel on a national highway in India. We measured PM2.5 and CO exposure levels of the passengers over 200km on a national highway using two portable air monitors, EVM-7 and EPAM-5000. Personal concentration exposures and per min-, per hour-, per trip- and round trip mass exposures for three travel modes were calculated for 9 trips. Association between pollutants and weather variables were evaluated using levels Spearman correlation. ANOVA was carried out to evaluate the influence of travel mode, the timing of trips, temperature and RH on personal exposures. On an average, PM2.5 personal concentration exposure levels were highest in the car (85.41±61.85µgm-3), followed by the bus (75.08±55.39µgm-3) and lowest in the car (ac) (54.43±34.09µgm-3). In contrast, CO personal exposure was highest in the car (ac) (1.81±1.3ppm). Travel mode explained the highest variability for CO (18.1%), CO2 (9.9%), PM2.5 (1.2%) exposures. In-city mass exposures were higher than trip averages; PM2.5:1.21-1.22, 1.13-1.19 and 1.03-1.28 times; CO: 1.20-1.57, 1.37-2.10 and 1.76-2.22 times for bus, car and car (ac) respectively. Traveling by car (ac) results in the lowest PM2.5 exposures, although it exposes the passenger to high CO level. Avoiding national highways passing through cities can reduce up to 25% PM2.5 and 50% CO mass exposures. This information can be useful for increasing environmental awareness among the passengers and for framing better pollution control strategies on highways.