The urban population is subjected to multiple exposures of air pollution and heat stress and bear severe impacts on their health and well-being in terms of premature deaths and morbidity. India tops ...the list of countries with the highest air pollution exposure and hosts some of the most polluted cities in the world. Similarly, Indian cities are highly vulnerable to extreme heat with the frequency of heatwaves expected to increase several-fold in urban areas in India. It is reported that mitigating air pollution could reduce the rural-urban difference of the incoming radiation thus resulting in mitigation of the urban heat island effect. Since the interaction between urban heat and air pollution is dynamic and complex, both these factors should be considered by the urban authorities in designing mitigation strategies. Given the multi-functional nature and cost-effectiveness of Nature-Based Solutions (NbS), they appear to be the most appropriate remedy for environmental issues of urban areas, particularly in developing countries. In addition to improving public health (through the reduction in air pollution and urban heat), NbS also provides a wide range of co-benefits such as reducing energy cost and health costs as well as conservation of biodiversity. This review is an attempt to understand the potentials of NbS in co-mitigating air pollution and urban heat in Indian cities. A framework for the planning and design of NbS in Indian cities is also proposed based on the review that could help city planners and decision-makers in addressing these two issues in an integrated manner.
In the present study, personal exposure to fine particulate matter (particulate matter with an aerodynamic diameter <2.5 μm PM
) concentrations in an urban hotspot (central business district CBD) was ...investigated. The PM monitoring campaigns were carried out at an urban hotspot from June to October 2015. The personal exposure monitoring was performed during three different time periods, i.e., morning (8 a.m.-9 a.m.), afternoon (12.30 p.m.-1.30 p.m.), and evening (4 p.m.-5 p.m.), to cover both the peak and lean hour activities of the CBD. The median PM
concentrations were 38.1, 34.9, and 40.4 µg/m
during the morning, afternoon, and evening hours on the weekends. During weekdays, the median PM
concentrations were 59.5, 29.6, and 36.6 µg/m
in the morning, afternoon, and evening hours, respectively. It was observed that the combined effect of traffic emissions, complex land use, and micrometeorological conditions created localized air pollution hotspots. Furthermore, the total PM
lung dose levels for an exposure duration of 1 hr were 8.7 ± 5.7 and 12.3 ± 5.2 µg at CBD during weekends and weekdays, respectively, as compared with 2.5 ± 0.8 µg at the urban background (UB). This study emphasizes the need for mobile measurement for short-term personal exposure assessment complementing the fixed air quality monitoring.
Personal exposure monitoring at an urban hotspot indicated space and time variation in PM concentrations that is not captured by the fixed air quality monitoring networks. The short-term exposure to higher concentrations can have a significant impact on health that need to be considered for the health risk-based air quality management. The study emphasizes the need of hotspot-based monitoring complementing the already existing fixed air quality monitoring in urban areas. The personal exposure patterns at hotspots can provide additional insight into sustainable urban planning.
Abstract Background: The development of standard protocol to improve the efficiency of a metal-based ayurvedic drug (Bhasma) requires understanding on the scientific basis and correlation between the ...preparation method and surface properties of the drug. Objective: With an objective to investigate the change in physico-chemical properties of a bhasma associated with preparation method, an extensive study was conducted on the synthesis and material characterization of ayurvedic drug Praval bhasma. Materials and Methods: Calcium-based ayurvedic traditional drug Praval bhasma was synthesized using red coral calyx which is a natural rich source of calcium. The surface properties and chemical aspects of the synthesised drug were studied using different characterization techniques. Results: The change in chemical composition due to the presence of phytoconstituents was evident from Fourier Transform Infrared Spectroscopy analysis. The addition of Calotropis gigantea latex plays a major role in maintaining pH which further reduces the toxicity of metals. The addition of lime juice converts insoluble calcium salt to soluble salt. The results of characterization studies confirmed the reduction in particle size and increase in surface area of the drug which enhances the rate of absorption of calcium. The current study will provide useful insights to tune the physicochemical properties of drugs that are capable to develop a standard protocol which further helps to enhance the efficiency of the drug.
Chemical characterization and source apportionment of PM
10
and PM
2.5
were carried out for two different elevations (lower elevation (LE) ~ 5–10 m and higher elevation (HE) ~ 30–45 m) at four ...different locations representing urban background, city center, upwind, and downwind of the Delhi city during January 2017–March 2017. The 24-h average PM
10
and PM
2.5
concentrations were varied between 135.2–258.7 and 79.3–120.9 µg/m
3
, respectively. The average PM
10
and PM
2.5
concentrations were found significantly higher at LE than HE. The PM samples were analyzed for ions, elements and carbonaceous matter (EC/OC), and their concentrations (except S, V, As, Ni, Sb, Sr, Ga, elements associated with industrial combustion activities, and NO
3
−
, attributed to high nitrate formation potential at HE) were observed higher in LE than HE at all the study locations. The chemical mass balance model was applied to quantify the source contributions to PM
10
and PM
2.5
mass at two different elevations. Model identified vehicular emission (diesel, PM
10
~ 8.8–21.7% and PM
2.5
~ 10.5–24.4% and gasoline, PM
10
~ 4.8–15.6% and PM
2.5
~ 6.7–14.8%), industrial residual oil combustion (PM
10
~ 8.8–23.5% and PM
2.5
~ 3.2–10.4%), road dust (PM
10
~ 13.6–22.3% and PM
2.5
~ 8.8–17.8%), soil dust (PM
10
~ 33.8–41.1% and PM
2.5
~ 5.8–8.3%), secondary nitrate (PM
10
~ 6.1–16.2% and PM
2.5
~ 13.4–20.2%), secondary sulfate (PM
10
~ 7.1–12.3% and PM
2.5
~ 10.6–16.7%), and biomass burning (PM
10
~ 6.8–21.8% and PM
2.5
~ 4.9–38.7%) as the main sources of PM
10
and PM
2.5
mass at both the elevations at all the study sites. The contribution of industrial residual oil combustion, vehicular emission, and secondary nitrate to PM
10
and PM
2.5
mass was found relatively higher in HE than LE. Results also revealed that biomass burning contributed significantly to PM pollution in the outskirts of Delhi than inside the city. Further, potential source contribution function analysis revealed that there may not be a long-range transport of PM emitted from biomass burning in the upwind region of Delhi during the study period. Shifting to Indian BS VI vehicles and fuel, switching to cleaner fuel in slum households, strict compliance on industries, and regular vacuum cleaning of roads will reduce the severe air quality problem in Delhi.
Background: Exposure to ambient PM 2.5 is known to affect lipid metabolism through systemic inflammation and oxidative stress. Evidence from developing countries, such as India with high levels of ...ambient PM 2.5 and distinct lipid profiles, is sparse. Methods: Longitudinal nonlinear mixed-effects analysis was conducted on >10,000 participants of Centre for cArdiometabolic Risk Reduction in South Asia (CARRS) cohort in Chennai and Delhi, India. We examined associations between 1-month and 1-year average ambient PM 2.5 exposure derived from the spatiotemporal model and lipid levels (total cholesterol TC, triglycerides TRIG, high-density lipoprotein cholesterol HDL-C, and low-density lipoprotein cholesterol LDL-C) measured longitudinally, adjusting for residential and neighborhood-level confounders. Results: The mean annual exposure in Chennai and Delhi was 40 and 102 μg/m 3 respectively. Elevated ambient PM 2.5 levels were associated with an increase in LDL-C and TC at levels up to 100 µg/m 3 in both cities and beyond 125 µg/m 3 in Delhi. TRIG levels in Chennai increased until 40 µg/m 3 for both short- and long-term exposures, then stabilized or declined, while in Delhi, there was a consistent rise with increasing annual exposures. HDL-C showed an increase in both cities against monthly average exposure. HDL-C decreased slightly in Chennai with an increase in long-term exposure, whereas it decreased beyond 130 µg/m 3 in Delhi. Conclusion: These findings demonstrate diverse associations between a wide range of ambient PM 2.5 and lipid levels in an understudied South Asian population. Further research is needed to establish causality and develop targeted interventions to mitigate the impact of air pollution on lipid metabolism and cardiovascular health.
Abstract High-resolution assessment of historical levels is essential for assessing the health effects of ambient air pollution in the large Indian population. The diversity of geography, weather ...patterns, and progressive urbanization, combined with a sparse ground monitoring network makes it challenging to accurately capture the spatiotemporal patterns of ambient fine particulate matter (PM2.5) pollution in India. We developed a model for daily average ambient PM2.5 between 2008 and 2020 based on monitoring data, meteorology, land use, satellite observations, and emissions inventories. Daily average predictions at each 1 km × 1 km grid from each learner were ensembled using a Gaussian process regression with anisotropic smoothing over spatial coordinates, and regression calibration was used to account for exposure error. Cross-validating by leaving monitors out, the ensemble model had an R2 of 0.86 at the daily level in the validation data and outperformed each component learner (by 5–18%). Annual average levels in different zones ranged between 39.7 μg/m3 (interquartile range: 29.8–46.8) in 2008 and 30.4 μg/m3 (interquartile range: 22.7–37.2) in 2020, with a cross-validated (CV)-R2 of 0.94 at the annual level. Overall mean absolute daily errors (MAE) across the 13 years were between 14.4 and 25.4 μg/m3. We obtained high spatial accuracy with spatial R2 greater than 90% and spatial MAE ranging between 7.3–16.5 μg/m3 with relatively better performance in urban areas at low and moderate elevation. We have developed an important validated resource for studying PM2.5 at a very fine spatiotemporal resolution, which allows us to study the health effects of PM2.5 across India and to identify areas with exceedingly high levels.
•Spatial variation of PM10, SO2 and NO2 concentrations at an industrial area.•Particulate chemical composition at near field and far field regions of national highway.•Dispersion of pollutants at ...near field and far field regions of national highway.•Secondary pollutant formation at far field region of the highway.
This paper presents the characterization of air quality monitored at near field region (NFR) and far field region (FFR) of a national highway located at an industrial complex. The pollutants such as PM10, SO2 and NO2 were monitored in two campaigns (11th September to 18th October 2012 and 18th January to 17th February 2013). The 24h average PM10 concentration at NFR and FFR were found to be 86.69±18.56μg/m3; 73.16±16.21μg/m3 and 89.44±18.69μg/m3; 81.91±16.42μg/m3, respectively during first and second campaign. In both the campaigns PM10, SO2 and NO2 concentration at NFR was higher than FFR. The chemical characterization of PM10 at NFR and FFR indicated the abundance of major elements such as Na (NFR=30% and FFR=32%), Ca (NFR=12% and FFR=14%) and ions namely NO3− (NFR=71% and FFR=68%) and NH3+ (NFR=15% and FFR=19%). Further, at FFR, SO42− and NO3− were found to be 18% and 35% higher than NFR indicating the conversions of SO2 and NO2 concentration into secondary particles. The measured SO2 and NO2 concentrations were 23 and 21% lower at FFR when compared to NFR confirms the secondary formation.
The CALPUFF, EPA regulatory model was set up to understand the dynamics of air pollutants at the industrial complex. The predicted PM10, SO2 and NO2 concentrations at NFR and FFR were found to be 32.31±1.56μg/m3 and 31.35±1.27μg/m3; 0.37±0.21μg/m3 and 0.06±0.04μg/m3; 12.83±6.55μg/m3 and 4.67±2.77μg/m3, respectively. The model showed moderate predictions for PM10 (R2=0.44–0.52), SO2 (R2=0.41–0.51) and NO2 (R2=0.45–0.61) concentrations.
The PM10 and PM2.5 source apportionment and health risk assessment were performed for two different elevations (lower elevation (LE) ∼5–10 m and higher elevation (HE) ∼30–45 m) at four different ...locations of Delhi city during January 2017–March 2017. The measured 24-h average PM10 and PM2.5 concentrations at different locations were found between 134.7 and 257.7 μg/m3 and 78.7–121.1 μg/m3, respectively. The 24-h average PM10 and PM2.5 concentrations at the study sites were exceeding the national (NAAQS) and WHO limits by more than 1.3 and 3 times, respectively. The PM mass was enriched with carbonaceous matter, ions, crustal and trace elements and their concentrations (except, Sr, Ni, S, As, V, Sb, Ga- the trace elements associated with coal and heavy oil combustion & NO3− - due to high nitrate formation ability at greater heights) were found higher in LE. The source apportionment study was performed with positive matrix factorisation (PMF). PMF analysis identified vehicular emission (PM10, 9.6–24.3% & PM2.5, 12.1–25.3%), secondary inorganics (PM10, 6.4–22.5% & PM2.5, 11–23%), crustal source (PM10, 9–52% & PM2.5, 3.8–10.7%), fuel oil combustion (PM10, 3–21% & PM2.5, 9–23%), biomass burning (PM10, 7.4–28.6% & PM2.5, 6–50.5%), and coal combustion (PM10, 13–17% & PM2.5, 14–19.1%) as the main sources of PM10 and PM2.5 at the study sites. A significant difference in source contribution between the elevations was observed for coal combustion, fuel oil combustion, biomass burning, and crustal sources. The contribution of vehicular emission and secondary inorganics estimates were broadly similar at both elevations. Coal and fuel oil combustion contribution was found relatively higher at HE. Further, health risk due to exposure to toxic heavy metals in PM2.5 was assessed. Non-carcinogenic and carcinogenic risks (averaged of four sites) for both children and adults were exceeding the acceptable limit by more than 1.13 times. Results also showed that the public residing at HE is more susceptible to have greater health risks than LE at Delhi city. Sources contribution to carcinogenic risk was assessed and the results indicated that coal combustion (41%) contribution was highest followed by crustal sources (22%), fuel oil combustion (17%), vehicular emission (12%), biomass burning (4%) and secondary inorganics (4%).
•The sampling of PM was performed at two different elevations.•Shares of ambient sources of PM and its associated health risk were estimated for Delhi city.•Vehicular emission, secondary inorganics, fuel oil combustion, coal combustion, and crustal sources were the dominant sources in Delhi city.•The public residing at higher levels is more susceptible to have high health risks in Delhi city.•Coal combustion contribution to the carcinogenic risk was highest at Delhi city.
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