Seasonal dynamics of particulate matter pollution and its dispersion in the city of Delhi, India

Sharma, Priyanka; Peshin, S. K.; Soni, V. K.; Singh, Siddhartha; Beig, Gufran; Ghosh, Chaitali

doi:10.1007/s00703-021-00852-8

Cited by 16 publications

(5 citation statements)

References 50 publications

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“…The pre-dominant wind speed falls within the range of 1.9 to 2.4 m/s. Similar results have been document in earlier studies, where the predominant wind direction was northwest, west–northwest directions during pre-monsoon season (Deshmukh et al, 2012 ; Garg & Gupta, 2020 ; Mandal et al, 2016 ; Sharma et al, 2022 ; Srivastava et al, 2008 ). In the beginning of March, a change in wind direction from north-western to south-western delivers heat waves known as Loo’ from the desolate region of Rajasthan (Kumar et al, 2021 ).…”

Section: Resultssupporting

confidence: 90%

“…During the summer, high wind speed events accompanied with dust are common over Delhi and its surrounding regions, causing enormous suspensions of dry and loose soil dust (Trivedi et al, 2014 ). Higher temperatures result in more turbulence, which aggravates surface dust re-suspension and increases particulate matter concentration (Sharma et al, 2022 ). Additionally, local emission sources majorly vehicular and industrial emissions along with road dust resuspension add-up to PM 10 concentration (CPCB report, 2010 ; Sharma et al, 2014 ; Jain et al, 2018 ).…”

Section: Resultsmentioning

confidence: 99%

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An analysis of particulate pollution using urban aerosol pollution island intensity over Delhi, India

Singh

Payra

Mishra

et al. 2022

Environ Monit Assess

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The accent of the present study is determination of Urban Aerosol Pollution Island (UAPI) intensity and spatial variability in particulate matter concentration (PM 10 and PM 2.5 ) over Delhi. For analysis, the hourly concentration dataset of PM 2.5 and PM 10 from January 2019 to December 2020 was obtained from ten air quality monitoring stations of Delhi. Additionally, UAPI Index has been calculated to assess the intensity of particulate pollution. The daily, monthly, and annual variations in the trends of PM 10 , PM 2.5 , and UAPI index along with related meteorological parameters have been analyzed. Particulate pollution peaked majorly during two seasons, i.e., summer and winter. The highest concentration of PM 10 was observed to be 426.77 µg/m 3 while that of PM 2.5 was observed to be 301.91 µg/m 3 in January 2019 for traffic-affected regions. During winters, higher PM 2.5 concentration was observed which can be ascribed to increased local emissions and enhanced secondary particle formations. While the increase in PM 10 concentrations led to an increment in pollution episodes during summers over most of the sites in Delhi. The UAPI index was found to be declining in 2020 over traffic affected regions (77.92 and 27.22 for 2019 and 2020, respectively) as well as in the background regions (64.91 and 19.80 for 2019 and 2020, respectively) of Delhi. Low traffic intensity and reduced pollutant emission could have been responsible for the reduction of UAPI intensity in the year 2020. The result indicates that lockdown implemented to control the COVID-19 outbreak led to an unexpected decrease in the PM 10 pollution over Delhi.

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Section: Resultssupporting

confidence: 90%

Section: Resultsmentioning

confidence: 99%

An analysis of particulate pollution using urban aerosol pollution island intensity over Delhi, India

Singh

Payra

Mishra

et al. 2022

Environ Monit Assess

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“…A similar pattern was also observed for PM 2.5 , PM 10 , and NO 2 in the province of Tehran, Iran (Yousefian et al 2020 ). The major reasons of increased air pollution levels during winters are low ventilation and stable atmospheric and precipitation conditions that confine the air pollutants to the lower boundary surface (Deep et al 2019 ; Ojha et al 2020 ; Sharma et al 2022 ). In the present study, the average concentrations of SO 2 and NO 2 were found below the recommended level by CPCB while the average concentration of PM 2.5 and PM 10 were above the limit.…”

Section: Resultsmentioning

confidence: 99%

“…However, in response to environmental stress, plants incorporate some biochemical, morphological, and physiological modifications to continue functioning (Singh et al 2017 ; Anand et al 2022 ; Banerjee et al 2022 ; Enitan et al 2022 ). Impacts of air pollution on vegetation depend on the meteorological (He et al 2017 ), climatic and seasonal phenomenon (Xie et al 2015 ; Sharma et al 2022 ), along with the source of pollutants, their physicochemical characteristics, and residence time in the atmosphere (Deep et al 2019 ; Rai 2019 ; Bodor et al 2020 ). Studying the impacts of biochemical components on the leaves of roadside plants in urban areas shows that ascorbic acid (AA), total chlorophyll (T.…”

Section: Introductionmentioning

confidence: 99%

A biochemical and morphological study with multiple linear regression modeling–based impact prediction of ambient air pollutants on some native tree species of Haldwani City of Kumaun Himalaya, Uttarakhand, India

Goswami

Kumar

Singh

et al. 2023

Environ Sci Pollut Res

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The current study was conducted around the province of Haldwani City, Uttarakhand, India, to understand the seasonal variation of ambient air pollutants (PM 2.5, PM 10 , SO 2 , and NO 2 ) and their impact on four tree species, i.e., neem ( Azadirachta indica ), mountain cedar ( Toona ciliate ), bottlebrush ( Callistemon citrinus ), and guava ( Psidium guajava ) during 2020–2021. Multiple linear regression (MLR)-based prediction analysis showed that the selected air quality variables (PM 2.5 , PM 10 , SO 2 , and NO 2 ) had a significant impact on the biochemical responses of selected tree spp. including, pH, ascorbic acid (AA), total chlorophyll content (T. Chl.), relative water content (RWC), and dust deposition potential. In this, the coefficient of variance ( R 2 ) of the developed models was in the range of 0.70–0.98. The ambient air pollutants showed significant seasonal variations as depicted by using the air pollution tolerance index (APTI) and anticipated performance index (API). The tree species from polluted sites observed more pollution tolerance than the tree species from the control site. Regression analysis showed a significant positive association between the biochemical characteristics and APTI, with the highest influence by AA ( R 2 = 0.961) followed by T. Chl., RWC, and pH. The APTI and API score was observed as maximum for A. indica and minimum for C. citrinus . The impact of air pollutants on the morphology of foliar surface was investigated by the scanning electron microscopy (SEM) and recorded various dust deposition patterns, stomatal blockages, and damage of guard cells in the trees growing along the polluted site (S2). The present study can assist environmental managers to examine the pollution-induced variables and develop an effective green belt for combating air pollution in polluted areas. Supplementary Information The online version contains supplementary material available at 10.1007/s11356-023-27563-4.

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“…PM10 and PM2.5 concentration in ambient air is affected by wind speed, wind direction, relative humidity and rainfall (Sirithian, et al 2022). Temperature and wind direction also influences the pollutant load (Sharma, 2022). Negative correlations were found between PM2.5 and PM10, and wind speed in the winter months, because wind speed could affect the dispersal of airborne particulates (Table 3).…”

Section: Quantification Of Atmospheric Pm10 and Pm25mentioning

confidence: 99%

Risk Assessment of Particulate Matter (PM 2.5 and PM 10 ) During Winter Crop at the Agricultural Site of Delhi, India

Chaudhary¹,

Prakash²,

Sharma

et al. 2023

Preprint

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In Indian cities, airborne particulate matter, PM2.5, is related with regional or across border problem and that of PM 10 with local-land urban problem. The present study was carried out for risk assessment of PM10 and PM2.5 and its associated carbonaceous component and heavy metals of an experimental agriculture farm site of Delhi, India. In our studies, at the agricultural site which is surrounded by heavy traffic and industries related sites, concentrations of both PM10 and PM2.5 varied significantly from 136.34 to 176.66 µg/m3 and 56 to 162 µ/m3 respectively. However, the concentrations of NOx were relatively higher during the months of February and March. The concentrations of O3 in the present study, were observed to be the highest in February. In general, the Hazard index for both adults and children population was reported to be < 1, which indicated the probability of non-carcinogenic risks to both populations as negative.

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Seasonal dynamics of particulate matter pollution and its dispersion in the city of Delhi, India

Cited by 16 publications

References 50 publications

An analysis of particulate pollution using urban aerosol pollution island intensity over Delhi, India

An analysis of particulate pollution using urban aerosol pollution island intensity over Delhi, India

A biochemical and morphological study with multiple linear regression modeling–based impact prediction of ambient air pollutants on some native tree species of Haldwani City of Kumaun Himalaya, Uttarakhand, India

Risk Assessment of Particulate Matter (PM 2.5 and PM 10 ) During Winter Crop at the Agricultural Site of Delhi, India

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