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Rahman MH, Rahman MA, Bhattacharya S, Thakur B, Datta A. Possible sources of ambient PM 10 inside Jadavpur University Campus, Kolkata. ENVIRONMENTAL MONITORING AND ASSESSMENT 2021; 193:764. [PMID: 34729663 DOI: 10.1007/s10661-021-09490-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Accepted: 09/22/2021] [Indexed: 06/13/2023]
Abstract
High concentration of particulates in the university and research institutional campus can affect cognitive performance of students and researchers. However, studies on ambient particulate concentration in the campus of universities or research institutes are scarce. The ambient concentration of PM10 was measured in the campus of Jadavpur University, Kolkata, during two different seasons (S1: Post-monsoon; S2: Winter) to identify major sources of pollutant here. Significant seasonal variation of ambient PM10 was recorded in the campus. The average ambient PM10 concentration was recorded higher in S2 compared to S1 of the study period. Morphological characteristics of PM10 during the study period suggest that the roundness of particles was in the range of 0.66 to 0.68, whilst the mean spherical diameter suggests most of the PM10 particles were < 2.5 μ diameter. Based on factorial analysis, three factors were generated which includes factor 1: soil, building material and coal burning particles (53.76% of the variance); factor 2: particles from coal combustion (29.89% of the variance) and factor 3: particles from transport emission (16.33% of the variance). The study suggests that it is important to stop burning coal, reduce vehicular emission and reduce road dust resuspension around the campus to maintain the ambient PM10 concentration within the university campus during the post-monsoon and winter months.
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Affiliation(s)
- Md Hafizur Rahman
- Earth Science and Climate Change Division, The Energy and Resources Institute, New Delhi, 110 003, India
- School of Environmental Studies, Jadavpur University, Kolkata, India
| | - Md Azizur Rahman
- Department of Biotechnology Engineering and Food Technology, University Institute of Engineering, Chandigarh University, Punjab, India
| | | | - Biswajit Thakur
- Department of Civil Engineering, Megnad Saha Institute of Technology, Kolkata, India
| | - Arindam Datta
- Earth Science and Climate Change Division, The Energy and Resources Institute, New Delhi, 110 003, India.
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Targino AC, Krecl P, Cipoli YA, Oukawa GY, Monroy DA. Bus commuter exposure and the impact of switching from diesel to biodiesel for routes of complex urban geometry. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2020; 263:114601. [PMID: 33618461 DOI: 10.1016/j.envpol.2020.114601] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2020] [Revised: 04/05/2020] [Accepted: 04/13/2020] [Indexed: 06/12/2023]
Abstract
We report on commuters' exposure to black carbon (BC), PM2.5 and particle number (PN, with aerodynamic diameter, da, in the range 0.01 <da< 1.0 μm) collected on-board diesel- and biodiesel-fuelled buses of the Bus Rapid Transit (BRT) system of the city of Curitiba, Brazil. Particulate concentrations measured at high sampling rates allowed the capture of fine gradients along the route and the comparison of in-cabin air pollution on buses of different technologies. Of all metrics, BC showed the largest discrepancies, with mean concentrations of 20.1 ± 20.0 μg m-3 and 3.9 ± 26.0 μg m-3 on diesel- and biodiesel-fuelled buses, respectively. Mean PM2.5 concentrations were similar (31.6 ± 28.5 μg m-3 and 29.0 ± 17.8 μg m-3), whilst mean PN concentrations were larger on the biodiesel buses (56,697 ± 26,800 # cm-3vs. 43,322 ± 32,243 # cm-3). The results are in line with studies on biodiesel emission factors that reported lower BC mass but more particles with smaller diameters. Our hypothesis is that different emission factors of diesel and biodiesel engines reflected in differences of in-cabin particulate concentrations. We found that the passenger exposure during the bus commutes was affected not only by the fuel used but also by the street geometry along the route, with segments with canyon configurations resulting in peak exposure to particulates. The results suggest that i) switching from diesel to biodiesel may help abate commuters' exposure to BC particles on-board buses of the BRT system, whilst it would need to be complemented with after-treatment technologies to reduce emissions; ii) further reductions in exposure (to peaks in particular) could be achieved by changing bus routes to ones that avoid passing through narrow urban street canyons.
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Affiliation(s)
- Admir Créso Targino
- Graduate Program in Environmental Engineering, Federal University of Technology, Av. Pioneiros 3131, 86036-370, Londrina, PR, Brazil.
| | - Patricia Krecl
- Graduate Program in Environmental Engineering, Federal University of Technology, Av. Pioneiros 3131, 86036-370, Londrina, PR, Brazil
| | - Yago Alonso Cipoli
- Department of Environmental Engineering, Federal University of Technology, Av. Pioneiros 3131, 86036-370, Londrina, PR, Brazil
| | - Gabriel Yoshikazu Oukawa
- Department of Environmental Engineering, Federal University of Technology, Av. Pioneiros 3131, 86036-370, Londrina, PR, Brazil
| | - David Andrés Monroy
- Graduate Program in Environmental Engineering, Federal University of Technology, Av. Pioneiros 3131, 86036-370, Londrina, PR, Brazil
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Amjadian K, Pirouei M, Rastegari Mehr M, Shakeri A, Khurshid Rasool S, Ibrahim Haji D. Contamination, health risk, mineralogical and morphological status of street dusts- case study: Erbil metropolis, Kurdistan Region-Iraq. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2018; 243:1568-1578. [PMID: 30293039 DOI: 10.1016/j.envpol.2018.09.116] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2018] [Revised: 09/15/2018] [Accepted: 09/22/2018] [Indexed: 06/08/2023]
Abstract
Street dusts contamination by heavy metals (HMs) and polycyclic aromatic hydrocarbons (PAHs), their mineralogical and morphological properties were investigated in Erbil metropolis. A total of 43 soil and street dust samples were collected and analyzed, and SPSS, ImageJ, X-powder and positive matrix factorization (PMF) software were used for data analyzing. Results showed the role of geology in mineralogical status of dusts. Based on ImageJ software processing, dust particles with diameters below 10 μm and low circularity and roundness were dominant. The enrichments for Hg, Cu, Pb and Zn contents were observed in compare with their calculated local geochemical baselines and geoaccumulation index, while, Ni, Co and Cr were categorized as particularly unpolluted. However, Hg, Cu and Pb showed the highest ecological risk (Eji) values among the studied elements, and 25.80%, 25.80% and 12.90% of the samples were classified as very high, moderate and considerable potential ecological risks, respectively. Hazard index (HI) followed the decreasing order of Pb > Cr > Cu > Ni > Hg > Zn > Co, and ingestion was the main exposure route particularly for children. The concentrations of individual PAHs ranged from 1.06 to 1000 ng/g, with the dominance of 3 and 4-ring compounds. Also, non-carcinogenic PAHs concentrations were higher than carcinogenic compounds and toxic equivalents (TEQs) ranged from 22.30 to 246.92 ng/g, with a max value in Northern industrial zone. Finally, source identification using multivariate statistics and PMF introduced three main PAHs and HMs sources in the study area including geogenic, traffic and industries, and incinerators (mainly for medical wastes).
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Affiliation(s)
- Keyvan Amjadian
- Department of Petroleum Geosciences, Faculty of Science, Soran University, Soran, Erbil Governorate, Kurdistan Region, Iraq; Scientific Research Centre, Soran University, Soran, Erbil Governorate, Kurdistan Region, Iraq
| | - Mohammad Pirouei
- Department of Petroleum Geosciences, Faculty of Science, Soran University, Soran, Erbil Governorate, Kurdistan Region, Iraq; Scientific Research Centre, Soran University, Soran, Erbil Governorate, Kurdistan Region, Iraq
| | - Meisam Rastegari Mehr
- Department of Applied Geology, Faculty of Earth Science, Kharazmi University, Tehran, 15614, Iran.
| | - Ata Shakeri
- Department of Applied Geology, Faculty of Earth Science, Kharazmi University, Tehran, 15614, Iran
| | - Shakhawan Khurshid Rasool
- Department of Petroleum Geosciences, Faculty of Science, Soran University, Soran, Erbil Governorate, Kurdistan Region, Iraq
| | - Dlband Ibrahim Haji
- Department of Petroleum Geosciences, Faculty of Science, Soran University, Soran, Erbil Governorate, Kurdistan Region, Iraq
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Particle Bound Metals at Major Intersections in an Urban Location and Source Identification Through Use of Metal Markers. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES INDIA SECTION A-PHYSICAL SCIENCES 2016. [DOI: 10.1007/s40010-016-0268-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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Shandilya KK, Kumar A. Physical characterization of fine particulate matter inside the public transit buses fueled by biodiesel in Toledo, Ohio. JOURNAL OF HAZARDOUS MATERIALS 2011; 190:508-514. [PMID: 21497439 DOI: 10.1016/j.jhazmat.2011.03.078] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2011] [Revised: 03/09/2011] [Accepted: 03/21/2011] [Indexed: 05/30/2023]
Abstract
This study presents the physical characteristics of fine particulate matter (PM) collected inside the urban-public transit buses in Toledo, OH. These buses run on 20% biodiesel blended with ultra-low sulfur diesel (ULSD) (B20). For risk analysis, it is crucial to know the modality of the size distribution and the shape factor of PM collected inside the bus. The number-size distribution, microstructure, and aspect ratio of fine PM filter samples collected in the urban-public transit buses were measured for three years (2007-2009), using an environmental scanning electron microscope (ESEM) coupled with energy dispersive X-ray spectrometry (EDX). Only the reproducible results from repeated experiments on ESEM and size distribution obtained by the GRIMM dust monitor were used in this study. The size distribution was found bi-modal in the winter and fall months and was primarily uni-modal during spring and summer. The aspect ratio for different filter samples collected inside the bus range from 2.4 to 3.6 in average value, with standard deviation ranging from 0.9 to 7.4. The square-shaped and oblong-shaped particles represent the single inhalable particle's morphology characteristics in the air of the Toledo transit buses.
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Affiliation(s)
- Kaushik K Shandilya
- Department of Civil Engineering, The University of Toledo, 2801 W. Bancroft Street, Toledo, OH 43606-3390, USA.
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Mogireddy K, Devabhaktuni V, Kumar A, Aggarwal P, Bhattacharya P. A new approach to simulate characterization of particulate matter employing support vector machines. JOURNAL OF HAZARDOUS MATERIALS 2011; 186:1254-1262. [PMID: 21185646 DOI: 10.1016/j.jhazmat.2010.11.129] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2010] [Revised: 11/22/2010] [Accepted: 11/30/2010] [Indexed: 05/30/2023]
Abstract
This paper, for the first time, applies the support vector machines (SVMs) paradigm to identify the optimal segmentation algorithm for physical characterization of particulate matter. Size of the particles is an essential component of physical characterization as larger particles get filtered through nose and throat while smaller particles have detrimental effect on human health. Typical particulate characterization processes involve image reading, preprocessing, segmentation, feature extraction, and representation. Of these various steps, knowledge based selection of optimal image segmentation algorithm (from existing segmentation algorithms) is the key for accurately analyzing the captured images of fine particulate matter. Motivated by the emerging machine-learning concepts, we present a new framework for automating the selection of optimal image segmentation algorithm employing SVMs trained and validated with image feature data. Results show that the SVM method accurately predicts the best segmentation algorithm. As well, an image processing algorithm based on Sobel edge detection is developed and illustrated.
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Affiliation(s)
- K Mogireddy
- EECS Department, University of Toledo, MS 308, 2801W. Bancroft Street, Toledo, OH 43606, USA.
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