Source Apportionment of PM2.5 Using a CMB Model for a Centrally Located Indian City

Fine particulate matters (PM 2.5 ) have been identified as one of the major air pollutants in urban areas, which are responsible for the deterioration of the atmospheric air quality as well as adverse effects on public health. In this study, the mass concentration, water-soluble ionic component, trace metal component, carbon component and modeling the contribution source for PM 2.5 was characterized for Chiayi City, which has high population density and surrounded by agricultural area. The lowest PM 2.5 mass concentrations were registered in the summer (9-22 µg m -3 ), while for the spring, autumn, and winter were well above the healthy level suggested by World Health Organization (WHO). For all seasons, the dominants were the sulfate (SO 4 2-), nitrate (NO 3 -) and followed closely by ammonium (NH 4 + ). Those secondary aerosols were transformed from SO 2 and NO 2 into particulate NO 3 -and SO 4 2-during spring, autumn and winter. Lower carbon mass concentrations were observed for summer (2.03-2.49 µg m -3 ) corresponding to the highest carbon content in PM 2.5 mass concentrations in terms of percentages (average 18.1%). Using the Chemical Mass Balance receptor model, the secondary nitrate (NO 3 -), primary traffic source, secondary sulfate (SO 4 2-), re-suspending soil particle, and petrochemical industry were identified as the major sources of PM 2.5 in Chiayi City. Consequently, the PM 2.5 contributions were complicated in a small but various seasons and geological distributing area. The air quality control strategies were thus seasonal and periodical dependent.

“…Additionally, Ni, Fe, Cu and Zn are reported basically from anthropogenic activities, while Cr, Mg and Mn maybe from crustal sources (Pipalatkar et al, 2014).…”

Section: Trace Metal Elementsmentioning

confidence: 99%

Characteristics of Atmospheric PM2.5 in a Densely Populated City with Multi-Emission Sources

Tseng

Lin

Mwangi

et al. 2016

“…In the CMB calculation, the source fingerprints and ambient measurements are needed for the input data (Watson et al, 1984). The contributions of sources can then be estimated by determining the best-fit combination of the chemical profiles of emission sources and chemical composition of the ambient samples (Pipalatkar et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Distribution and Sources of Atmospheric Polycyclic Aromatic Hydrocarbons at an Industrial Region in Kaohsiung, Taiwan

Lai

Tsai

Chen

et al. 2017

The chemical mass balance model was applied to estimate the major sources of atmospheric polycyclic aromatic hydrocarbons (PAHs) at an Industrial Region in Kaohsiung, Taiwan. The gaseous and particulate phases of 16 individual compounds were analyzed between March 2012 and August 2012. The mean total concentrations and total BaP eq were higher during the cold season and lower during the warm summer, with gaseous PAHs predominant at all sites. Low weight-PAHs and median weight-PAHs were found predominantly in the gaseous phase, while high weight-PAHs were predominant in the particle phase. Results from the receptor model revealed that the average contributions were 38.2%, 27.2%, 20.7%, 6.8%, 5.2%, and 2.0% from vehicles, heavy oil combustion, natural gas combustion, incinerator, tetrabromobisphenol A production, and diesel combustion at the seven receptors, respectively. Vehicle emissions appear to be the significant source of PAHs in the investigated area, although other industrial sources, as described above, also have an impact on the total PAHs.

“…Sever metal elements in PM 2.5 were considered as the characteristic components of the emission sources, such as industrial exhaust, open burning, sea salt suspension, fuel combustion, and soil dust particle (Pipalatkar et al, 2014;Tseng et al, 2016). There were 22 of them analyzed in this study and illustrated in other order of their contributions (%) of total metal components as Figs.…”

Section: Metal Elementsmentioning

confidence: 99%

“…The dominant species within PM 2.5 before and after restriction were explained as some natural phenomenon. Previous studies mentioned element Ca and K are included of alkaline earth metal and alkali metal which usually presents in soil/ mineral dust dispersal or biomass burning (Mkoma et al, 2014), also trace metal element for Na is possible from sea salt spray (Pipalatkar et al, 2014;Tseng et al, 2016).…”

Section: Metal Elementsmentioning

confidence: 99%

Reduction of Atmospheric PM2.5 Level by Restricting the Idling Operation of Buses in a Busy Station

Lee

Lin

Aniza

et al. 2017

Fine particulate matter (PM 2.5 ) has been found to be harmful when inhaled by people, which has caused enormous health problems. It is found at high levels at public bus stations, where many passengers and workers may be exposed to PM 2.5 emissions from idling diesel engines. This study evaluated the restriction on idling vehicles as a strategy to control PM 2.5 levels at bus stations by measuring the PM 2.5 and the chemical properties at both upwind and exposure sites for comparable data. The sampling took place on weekends and weekdays and before and after the idling restriction was applied. Originally, the exposure site showed a PM 2.5 level that was 7% higher, non-neutralized nitrate content, anthropogenic metal elements, and higher mobile source contributions, as evaluated by a chemical mass balance model (CMB8.2). After the prohibition on idling heavy-duty diesel vehicles, the PM 2.5 mass concentrations at the exposure site were reduced to levels comparable to those at the upwind site. Additionally, the nitrate content was reduced in the background. Moreover, the contributions of several anthropogenic metals (Zn, Pb, Mn, Cu, Cr, V, Ni, and Ti) in PM 2.5 were reduced while those of crustal elements (Na, Mg, Al, K, and Ca) significantly increased after the restriction. Finally, the mobile contribution decreased to only 33.7-34.5%. Consequently, these findings verify that the prohibition policy on idling vehicles works well as a control strategy to manage the PM 2.5 emissions at local hotspots such as bus stations.