Morphology of single inhalable particle inside public transit biodiesel fueled bus

Possible sources of ambient PM10 inside Jadavpur University Campus, Kolkata

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.

Bus commuter exposure and the impact of switching from diesel to biodiesel for routes of complex urban geometry

We report on commuters' exposure to black carbon (BC), PM_2.5 and particle number (PN, with aerodynamic diameter, d_a, in the range 0.01 <d_a< 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 PM_2.5 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.

Contamination, health risk, mineralogical and morphological status of street dusts- case study: Erbil metropolis, Kurdistan Region-Iraq

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 (E_jⁱ) 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).

Physical characterization of fine particulate matter inside the public transit buses fueled by biodiesel in Toledo, Ohio

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.

A new approach to simulate characterization of particulate matter employing support vector machines

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.