Air quality mapping using GIS and economic evaluation of health impact for Mumbai City, India

Kumar, Awkash; Gupta, Indrani; Brandt, Jørgen; Kumar, Rakesh; Dikshit, Anil Kumar; Patil, Rashmi S.

doi:10.1080/10962247.2016.1143887

Cited by 96 publications

(57 citation statements)

References 42 publications

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“…Hourly nine meteorological parameters such as wind speed, wind direction, rain fall, temperature, humidity, pressure, ceiling height, global horizontal radiation, and cloud cover were generated using Fig. 5 NO x concentration plot for morning and evening peak, off-peak and lean time Comparison of predicted vehicular pollution concentration with air quality standards for… WRF model at 25 km resolution. The generated temperature and wind were compared with observed values because they are more significant for air modeling (Kumar et al 2016b). The output meteorological data from WRF were incorporated in air quality model AERMOD.…”

Section: Resultsmentioning

confidence: 99%

Comparison of predicted vehicular pollution concentration with air quality standards for different time periods

Kumar

Patil

Dikshit

et al. 2016

Clean Techn Environ Policy

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Air pollution is caused by variety of sources such as industries, vehicles, cremation, bakeries, and open burning. These sources have variation in emission with different time scales. Industry and bakeries have variation in emission with day or week, rest of the sources like vehicles and domestic sector have variation with time in a day. In fact, vehicles have a large variation in emission with time period of the day. The average concentration of 24 h is much less than hourly concentration of peak time when there is heavy vehicular emissions. The hourly concentration of off-peak time or lean time is very low due to low emission for that period. The air quality standards of India are prescribed for 24-h average concentration with which the predicted average concentration from models is compared. However, the peak time concentration may be much higher than the standard. In the peak time, outdoor concentration is more and since a large proportion of the population is out the exposure is also very high and can cause severe health effect. In this paper, vehicular pollution modeling has been carried out using AERMOD with simulated meteorology by Weather Research and Forecasting model. NO x and PM concentrations were 3.6 and 1.45 times higher in peak time than off-peak and evening peak, respectively. Lean time has higher concentration for both NO x and PM than off-peak and evening peak. It shows the misleading concept of comparing average predicted concentration of 24 h with standards for vehicles.

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Section: Resultsmentioning

confidence: 99%

Comparison of predicted vehicular pollution concentration with air quality standards for different time periods

Kumar

Patil

Dikshit

et al. 2016

Clean Techn Environ Policy

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“…Kriging, a spatial interpolation GIS technique, was employed to assess the spatial spread of air pollutants over the cities for the selected periods. Kriging is a powerful statistical technique which assumes that distance or direction between sample points reflect a spatial correlation and hence represent variation in surface (Kumar et al, 2016;van Zoest et al, 2019). It uses a weighted average technique by considering spatial correlation to predict the values for an area from the available data samples as per the following equation:…”

Section: Spatiotemporal Analysis Of Air Pollution Over Covid-19 Epicementioning

confidence: 99%

Social and Travel Lockdown Impact Considering Coronavirus Disease (COVID-19) on Air Quality in Megacities of India: Present Benefits, Future Challenges and Way Forward

Jain

Sharma

2020

Aerosol Air Qual. Res.

234

230

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The coronavirus disease (COVID-19) created enormous pressure across the globe due to an increasing number of COVID-19 infected cases. All the governments' primary focus is to save humanity from this pandemic problem, and they have lockdown almost the entire nation to stop the spread of infection. This lockdown resulted in a considerable impact on the global as well as a local economy that will take a long time to perform with business as usual scenario. However, improvement in the air quality of the cities across the globe has emerged as a key benefit of this lockdown. Therefore, this study aims to assess the overall impact of social and travel lockdown in five megacities of India; Delhi, Mumbai, Chennai, Kolkata, and Bangalore. The study evaluated the spatiotemporal variations in five criteria pollutants over two time periods, i.e.

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“…The number of stations applied in the interpolation is represented by n , which is 16 in this study. Past works have used the IDW method for spatial topography of pollutants such as BTEX compounds in Shiraz, Iran (Dehghani et al, 2018), SO 2 and NO 2 in Mumbai (India) (Kumar et al, 2016), particulate matter in California and Pennsylvania (USA) (Li et al, 2016), and Beijing (China) (Li et al, 2014), and atmospheric wet-deposition in Oregon, Nevada, and Washington (USA) (Latysh and Wetherbee, 2012). …”

Section: Methodsmentioning

confidence: 99%

Characteristics and health effects of formaldehyde and acetaldehyde in an urban area in Iran

Delikhoon

Fazlzadeh

Sorooshian

et al. 2018

Environmental Pollution

109

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This study reports a spatiotemporal characterization of formaldehyde and acetaldehyde in the summer and winter of 2017 in the urban area of Shiraz, Iran. Sampling was fulfilled according to EPA Method TO-11 A. The inverse distance weighting (IDW) procedure was used for spatial mapping. Monte Carlo simulations were conducted to evaluate carcinogenic and non-cancer risk owing to formaldehyde and acetaldehyde exposure in 11 age groups. The average concentrations of formal-dehyde/acetaldehyde in the summer and winter were 15.07/8.40 μg m−3 and 8.57/3.52 μg m−3, respectively. The formaldehyde to acetaldehyde ratios in the summer and winter were 1.80 and 2.43, respectively. The main sources of formaldehyde and acetaldehyde were photochemical generation, vehicular traffic, and biogenic emissions (e.g., coniferous and deciduous trees). The mean inhalation lifetime cancer risk (LTCR) values according to the Integrated Risk Information System (IRIS) for formaldehyde and acetaldehyde in summer and winter ranged between 7.55 × 10−6 and 9.25 × 10−5, which exceed the recommended value by US EPA. The average LTCR according to the Office of Environmental Health Hazard Assessment (OEHHA) for formaldehyde and acetaldehyde in summer and winter were between 4.82 × 10−6 and 2.58 × 10−4, which exceeds recommended values for five different age groups (Birth to <1, 1 to <2, 2 to < 3, 3 to <6, and 6 to <11 years). Hazard quotients (HQs) of formaldehyde ranged between 0.04 and 4.18 for both seasons, while the HQs for acetaldehyde were limited between 0.42 and 0.97.

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Air quality mapping using GIS and economic evaluation of health impact for Mumbai City, India

Cited by 96 publications

References 42 publications

Comparison of predicted vehicular pollution concentration with air quality standards for different time periods

Comparison of predicted vehicular pollution concentration with air quality standards for different time periods

Social and Travel Lockdown Impact Considering Coronavirus Disease (COVID-19) on Air Quality in Megacities of India: Present Benefits, Future Challenges and Way Forward

Characteristics and health effects of formaldehyde and acetaldehyde in an urban area in Iran

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