Chemical characteristics and source apportionment of PM2.5 using PCA/APCS, UNMIX, and PMF at an urban site of Delhi, India

Jain, Srishti; Sharma, S.K.; Choudhary, Nikki; Masiwal, Renu; Saxena, Mohit; Sharma, Ashima; Mandal, T. K.; Gupta, Anil; Gupta, N. C.; Sharma, C.

doi:10.1007/s11356-017-8925-5

Cited by 118 publications

(54 citation statements)

References 143 publications

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“…The PCA/APCS receptor model can quantitatively determine not only the load of each pollutant attributed to each source, but also the average contribution of each source to each pollutant and to the pollution in each sample. Currently, the model is mainly used in research on air pollution and water pollution [24][25][26][27]. In this study, PCA was performed on the spatial distributions of heavy metal accumulation in soils for source identification using factor extraction with eigenvalues > 1 after varimax rotation.…”

Section: Methods For the Assessment Of Pollution And Potential Ecologmentioning

confidence: 99%

Spatial Distributions, Pollution Assessment, and Qualified Source Apportionment of Soil Heavy Metals in a Typical Mineral Mining City in China

Yang

Liu

et al. 2018

Sustainability

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Daye is a city in China known for its rich mineral resources, with a history of metal mining and smelting that dates back more than 3000 years. To analyze the spatial distribution patterns, ecological risk, and sources of heavy metals (Cd, Co, Cr, Cu, Mn, Ni, Pb, and Zn) in soils, 213 topsoil samples were collected in the main urban area of Daye in September 2016. The mean concentrations of Cd, Cu, Pb, and Zn were higher than the corresponding background values, with the mean concentration of Cd being almost seven times its background value. Spatially, the high concentrations of Cd, Mn, Pb, and Zn were mainly concentrated in the southeastern part of the region due to nonferrous metal mining and smelting. However, the high concentrations of Co and Cu were concentrated in the central part of the study area, resulted from copper mining and smelting. The data of the geoaccumulation index showed that the contamination levels ranged from no pollution (Co, Cr, Mn, and Ni) to heavy contamination (Cd, Cu, and Pb). Ecological risk assessment showed that Cd posed a high, serious, and even severe ecological risk in 53.78% of the area of Daye. According to the results of the principal component analysis, mineral exploitation and smelting involving a variety of minerals (ES_M), mining exploitation, and smelting of copper ore (ES_C), and natural sources are the three main sources of heavy metals in these soils. Furthermore, the absolute principal component scores showed that 69.21% and 23.17% of the heavy metal concentrations were ascribed to ES_M and ES_C, respectively.

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Section: Methods For the Assessment Of Pollution And Potential Ecologmentioning

confidence: 99%

Spatial Distributions, Pollution Assessment, and Qualified Source Apportionment of Soil Heavy Metals in a Typical Mineral Mining City in China

Yang

Liu

et al. 2018

Sustainability

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“…HI = HQ (6) where, ADD-ingestion, inhalation or dermal dose; RfD-reference dose that is given in the Integrated Information Risk System (IRIS) [49,50] (Table 2). Exposure indicators have not been calculated for two elements: Rb and Al, because there is no data in the literature on the RfD value that is key to calculating the health risk hazard quotient.…”

Section: Non-cancerogenic Health Riskmentioning

confidence: 99%

Selected Metals in Urban Road Dust: Upper and Lower Silesia Case Study

et al. 2020

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In this study, urban road dust (URD) samples were collected in two populated agglomerations of Wrocław and Katowice (Lower and Upper Silesia) in Poland. Both the total concentrations of URD-bound Mn, Ni, Cu, Zn, As, Rb, Ba, Cr, Mg, and Al and concentrations of their water-soluble fraction were determined. The contamination characteristics and health risk related to these elements were assessed. Contamination level assessment was done by Pollution Load Index (PLI), which indicated much higher pollution of Katowice agglomeration than Wrocław. The enrichment factor values (EF) showed that the most elements in both Katowice and Wrocław orginated from anthropogenic sources. The calculations of geo-accumulation index (Igeo) showed that Zn and As are the key pollutants in Katowice; and in the Wrocław region, Cu, Zn, Cr, and Ni are. The principle component analysis (PCA) and correlation analysis provide information about the potential sources of metals. Additionally, a positive matrix factorization (PMF) was performed and four factors in PMF analysis were found and then interpreted by comparing to the source profiles. Three contamination sources were revealed: fossil fuel combustion, road traffic and industrial emissions. Although the main source of studied metals in Lower Silesia is road traffic, in Upper Silesia, domestic heating with the use of hard and brawn coal and industrial activity predominates. Human exposure to individual toxic metals through road dust was assessed for both children and adults. By calculating the average daily dose (ADD) via ingestion, inhalation, and dermal contact, it was found that ingestion and then dermal contact were the greatest exposure pathways for humans in Katowice and Wrocław. Children had greater health risks than adults. According to the health risk assessment, the overall non-carcinogenic risks in both urban areas was rather low. The only exception was As bound to urban road dust in Katowice agglomeration, which indicates risk for children when ingested. The total excess cancer risk (ECR) was also lower than the acceptable level (10−6–10−4) for both adults and children, although ECR for Katowice was closer to this limit.

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“…Pb can be a part of vehicular emission. Though leaded fuel was banned in India in the year 2000 [55], traces of Pb are still found in road dust, as observed by Hsu et al [56] and Pandey et al [57]. Zn and Al may have originated from tire and brake pad wear of vehicles [60].…”

Section: Enrichment Factor (Ef) and Principal Component Analysis (Pca)mentioning

confidence: 99%

“…Further, the Kurtosis test conducted on the elements revealed mixed results: Some elements such as Cd, Pb, Mg, Al, Ca, and Zn showed negative values, whereas elements such as Co, Ni, K, Cr, Mn, Fe, and Cu showed positive values. Negative values denote a flat distribution of the data, while positive values [49], b [50], c [51], d [52], e [53], f [12], g [54], h [2], i [55], j [56], k [57] denote sporadic high emissions [47,48]. Figure S4 shows a box and whisker plot of the estimated trace elements.…”

Section: Chemical Species Comprising Rspmmentioning

confidence: 99%

Sources and health risks of atmospheric particulate matter at Bhagwanpur, an industrial site along the Himalayan foothills

et al. 2020

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Temporal variations in atmospheric particulate matter (PM) were studied in Bhagwanpur-a data-deficient area located along the foothills of the Himalayas. The concentrations of respirable suspended particulate matter (RSPM) and PM 0.4-10 µm (categorized into eight size fractions) were measured during winter and summer of 2014-2015. The RSPM concentration over a 24-h period was found to be 259.6 ± 52.6 µg/m 3 , which is 2.6 times greater than the permissible limit set by the Indian National Ambient Air Quality Standards. A significant difference (p < 0.05, t test) in RSPM with seasons was observed with winter maximum (284.6 ± 48.6 µg/m 3) and summer minimum (234.5 ± 44.8 µg/m 3). Size fractionated PM measurements revealed maximum concentration (36.4 ± 5.2 µg/m 3) in PM 9.0-10.0 µm, while least concentration was observed in PM 2.1-3.3 µm (16.8 ± 2.3 µg/m 3). Further, on quantification of 13 chemical species associated with RSPM, it was observed that mass concentration followed the trend of Ca > K > Mg > Al > Zn > Fe > Mn > Cr > Co > Ni > Cu > Pb > C d. Source apportionment through principal component analysis revealed the sources such as industrial, vehicular, and crustal. The excess cancer risk for Cr was about 2.7 times higher than the tolerance level (10 −4), while only Pb was below the safe limit (10 −6). However, total ECR for Cr, Cd, Pb, and Ni was about 3 times higher than the tolerance level. Three-day air mass back trajectory analysis reveals that emissions from biomass burning over the neighbouring regions adversely affect the air quality at the study site. The results of this study can be utilized toward the effective implementation of environmental regulations at the study site.

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Chemical characteristics and source apportionment of PM2.5 using PCA/APCS, UNMIX, and PMF at an urban site of Delhi, India

Cited by 118 publications

References 143 publications

Spatial Distributions, Pollution Assessment, and Qualified Source Apportionment of Soil Heavy Metals in a Typical Mineral Mining City in China

Spatial Distributions, Pollution Assessment, and Qualified Source Apportionment of Soil Heavy Metals in a Typical Mineral Mining City in China

Selected Metals in Urban Road Dust: Upper and Lower Silesia Case Study

Sources and health risks of atmospheric particulate matter at Bhagwanpur, an industrial site along the Himalayan foothills

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