Effects of road dust on the airborne particle concentrations in Taipei

Abstract. We have numerically evaluated how effective selected potential measures would be for reducing the impact of road dust on ambient air particulate matter (PM10). The selected measures included a reduction of the use of studded tyres on light-duty vehicles and a reduction of the use of salt or sand for traction control. We have evaluated these measures for a street canyon located in central Helsinki for four years (2007–2009 and 2014). Air quality measurements were conducted in the street canyon for two years, 2009 and 2014. Two road dust emission models, NORTRIP (NOn-exhaust Road TRaffic Induced Particle emissions) and FORE (Forecasting Of Road dust Emissions), were applied in combination with the Operational Street Pollution Model (OSPM), a street canyon dispersion model, to compute the street increments of PM10 (i.e. the fraction of PM10 concentration originating from traffic emissions at the street level) within the street canyon. The predicted concentrations were compared with the air quality measurements. Both road dust emission models reproduced the seasonal variability of the PM10 concentrations fairly well but under-predicted the annual mean values. It was found that the largest reductions of concentrations could potentially be achieved by reducing the fraction of vehicles that use studded tyres. For instance, a 30 % decrease in the number of vehicles using studded tyres would result in an average decrease in the non-exhaust street increment of PM10 from 10 % to 22 %, depending on the model used and the year considered. Modelled contributions of traction sand and salt to the annual mean non-exhaust street increment of PM10 ranged from 4 % to 20 % for the traction sand and from 0.1 % to 4 % for the traction salt. The results presented here can be used to support the development of optimal strategies for reducing high springtime particulate matter concentrations originating from road dust.

Download Full-text

Characterization, identification of ambient air and road dust polycyclic aromatic hydrocarbons in central Taiwan, Taichung

The Science of The Total Environment ◽

10.1016/j.scitotenv.2003.10.016 ◽

2004 ◽

Vol 327 (1-3) ◽

pp. 135-146 ◽

Cited By ~ 138

Author(s):

Guor-Cheng Fang ◽

Cheng-Nan Chang ◽

Yuh-Shen Wu ◽

Peter Pi-Cheng Fu ◽

I-Lin Yang ◽

...

Keyword(s):

Polycyclic Aromatic Hydrocarbons ◽

Aromatic Hydrocarbons ◽

Road Dust ◽

Ambient Air ◽

Polycyclic Aromatic ◽

Central Taiwan

Download Full-text

Geochemical Mapping, Risk Assessment, and Source Identification of Heavy Metals in Road Dust Using Positive Matrix Factorization (PMF)

Atmosphere ◽

10.3390/atmos12050614 ◽

2021 ◽

Vol 12 (5) ◽

pp. 614

Author(s):

Muhammad Faisal ◽

Zening Wu ◽

Huiliang Wang ◽

Zafar Hussain ◽

Chenyang Shen

Keyword(s):

Heavy Metals ◽

Risk Assessment ◽

Matrix Factorization ◽

Anthropogenic Activities ◽

Contamination Factor ◽

Road Dust ◽

Positive Matrix Factorization ◽

Prevention Measures ◽

Positive Matrix ◽

The City

Heavy metals in road dust pose a significant threat to human health. This study investigated the concentrations, patterns, and sources of eight hazardous heavy metals (Cr, Ni, Cu, Zn, As, Cd, Pb, and Hg) in the street dust of Zhengzhou city of PR China. Fifty-eight samples of road dust were analyzed based on three methods of risk assessment, i.e., Geo-Accumulation Index (Igeo), Potential Ecological Risk Assessment (RI), and Nemerow Synthetic Pollution Index (PIN). The results exhibited higher concentrations of Hg and Cd 14 and 7 times higher than their background values, respectively. Igeo showed the risks of contamination in a range of unpolluted (Cr, Ni) to strongly polluted (Hg and Cd) categories. RI came up with the contamination ranges from low (Cr, Ni, Cu, Zn, As, and Pb) to extreme (Cd and Hg) risk of contamination. The risk of contamination based on PIN was from safe (Cu, As, and Pb) to seriously high (Cd and Hg). The results yielded by PIN indicated the extreme risk of Cd and Hg in the city. Positive Matrix Factorization was used to identify the sources of contamination. Factor 1 (vehicular exhaust), Factor 2 (coal combustion), Factor 3 (metal industry), and Factor 4 (anthropogenic activities), respectively, contributed 14.63%, 35.34%, 36.14%, and 13.87% of total heavy metal pollution. Metal’s presence in the dust is a direct health risk for humans and warrants immediate and effective pollution control and prevention measures in the city.

Download Full-text