Investigation of the spatiotemporal variation and influencing factors on fine particulate matter and carbon monoxide concentrations near a road intersection

Abstract

The minute-scale variations of fine particulate matter (PM_2.5) and carbon monoxide (CO) concentrations near a road intersection in Shanghai, China were investigated to identify the influencing factors at three traffic periods. Measurement results demonstrate a synchronous variation of pollutant concentrations at the roadside and setbacks, and the average concentration of PM_2.5 at the roadside is 7% (44% for CO) higher than that of setbacks within 500 m of the intersection. The pollution level at traffic peak periods is found to be higher than that of off-peak periods, and the morning peak period is found to be the most polluted due to a large amount of diesel vehicles and unfavorable dispersion conditions. Partial least square regressions were constructed for influencing factors and setback pollutant concentrations, and results indicate that meteorological factors are the most significant, followed by setback distance from the intersection and traffic factors. CO is found to be sensitive to distance from the traffic source and vehicle type, and highly dependent on local traffic conditions, whereas PM_2.5 originates more from other sources and background levels. These findings demonstrate the importance of localized factors in understanding spatiotemporal patterns of air pollution at intersections, and support decision makers in roadside pollution management and control.

Keywords

traffic-related pollutants / fine-scale variation / distance gradient / meteorology / road intersection

References

[1] Beckerman B, Jerrett M, Brook J R, Verma D K, Arain M A, Finkelstein M M (2008). Correlation of nitrogen dioxide with other traffic pollutants near a major expressway. Atmos Environ, 42(2): 275–290

[2] Brook R D, Brook J R, Urch B, Vincent R, Rajagopalan S, Silverman F (2002). Inhalation of fine particulate air pollution and ozone causes acute arterial vasoconstriction in healthy adults. Circulation, 105(13): 1534–1536

[3] Buonanno G, Fuoco F C, Stabile L (2011). Influential parameters on particle exposure of pedestrians in urban microenvironments. Atmos Environ, 45(7): 1434–1443

[4] Farrell W, Weichenthal S, Goldberg M, Hatzopoulou M (2014). A statistical model explaining air pollution exposures of cyclists in urban environments. Proceedings of the 93rd Annual Meeting of the Transportation Research Board, Washington, DC, January

[5] Galatioto F, Zito P (2009). Traffic parameters estimation to predict road side pollutant concentrations using neural networks. Environ Model Assess, 14(3): 365–374

[6] Grivas G, Chaloulakou A (2006). Artificial neural network models for prediction of PM10 hourly concentrations, in the Greater Area of Athens, Greece. Atmos Environ, 40(7): 1216–1229

[7] Hagler G S W, Thoma E D, Baldauf R W (2010). High-resolution mobile monitoring of carbon monoxide and ultrafine particle concentrations in a near-road environment. J Air Waste Manag Assoc, 60(3): 328–336

[8] He H D, Lu W Z (2012). Urban aerosol particulates on Hong Kong roadsides: size distribution and concentration levels with time. Stochastic Environ Res Risk Assess, 26(2): 177–187

[9] He H D, Lu W Z, Xue Y (2009). Prediction of PM10 concentrations at urban traffic intersections using semi-empirical box modelling with instantaneous velocity and acceleration. Atmos Environ, 43(40): 6336–6342

[10] HEI (2010). Traffic-related air pollution: a critical review of the literature on emissions, exposure, and health Effects. HEI Special Report 17, Health Effects Institute, Boston, MA

[11] Hollander M, Wolfe D A (1999). Nonparametric Statistical Methods. Hoboken, NJ: John Wiley & Sons, Inc

[12] Jamriska M, Morawska L, Mergersen K (2008). The effect of temperature and humidity on size segregated traffic exhaust particle emissions. Atmos Environ, 42(10): 2369–2382

[13] Jia L, Xu Y (2014). Effects of relative humidity on ozone and secondary organic aerosol formation from the photooxidation of benzene and ethylbenzene. Aerosol Sci Technol, 48(1): 1–12

[14] Jian L, Zhao Y, Zhu Y P, Zhang M B, Bertolatti D (2012). An application of ARIMA model to predict submicron particle concentrations from meteorological factors at a busy roadside in Hangzhou, China. Sci Total Environ, 426: 336–345

[15] Kaur S, Nieuwenhuijsen M J (2009). Determinants of personal exposure to PM_2.5, ultrafine particle counts, and CO in a transport microenvironment. Environ Sci Technol, 43(13): 4737–4743

[16] Kellnerova R, Janour Z (2011). Flow instabilities within an urban intersection. International Journal of Environment and Pollution, 47(1/2/3/4): 268–277

[17] Martin D, Nickless G, Price C S, Britter R E, Neophytou M K, Cheng H, Robins A G, Dobre A, Belcher S E, Barlow J F, Tomlin A S, Smalley R J, Tate J E, Colvile R N, Arnold S J, Shallcross D E (2010b). Urban tracer dispersion experiment in London (DAPPLE) 2003: field study and comparison with empirical prediction. Atmos Sci Lett, 11(4): 241–248

[18] Martin D, Price C S, White I R, Nickless G, Petersson K F, Britter R E, Robins A G, Belcher S E, Barlow J F, Neophytou M, Arnold S J, Tomlin A S, Smalley R J, Shallcross D E (2010a). Urban tracer dispersion experiments during the second DAPPLE field campaign in London 2004. Atmos Environ, 44(25): 3043–3052

[19] Mazzeo N A, Venegas L E (2012). Hourly NOX concentrations and wind direction in the vicinity of a street intersection. International Journal of Environment and Pollution, 48(1/2/3/4): 96–104

[20] McAdam K, Steer P, Perrotta K (2011). Using continuous sampling to examine the distribution of traffic related air pollution in proximity to a major road. Atmos Environ, 45(12): 2080–2086

[21] Pandian S, Gokhale S, Ghoshal A K (2009). Evaluating effects of traffic and vehicle characteristics on vehicular emissions near traffic intersections. Transp Res Part D Transp Environ, 14(3): 180–196

[22] Shallcross D E, Martin D, Price C S, Nickless G, White I R, Petersson F, Britter R E, Neophytou M K, Tate J E, Tomlin A S, Belcher S E, Barlow J F, Robins A (2009). Short-range urban dispersion experiments using fixed and moving sources. Atmos Sci Lett, 10(2): 59–65

[23] Slavin C, Figliozzi M A (2013). Impact of traffic signal timing on sidewalk-level particulate matter concentrations. Transportation Research Record, 2340: 29–37

[24] Soulhac L, Garbero V, Salizzoni P, Mejean P, Perkins R J (2009). Flow and dispersion in street intersections. Atmos Environ, 43(18): 2981–2996

[25] Tiwary A, Robins A, Namdeo A, Bell M (2011). Air flow and concentration fields at urban road intersections for improved understanding of personal exposure. Environ Int, 37(5): 1005–1018

[26] Tomlin A S, Smalley R J, Tate J E, Barlow J F, Belcher S E, Arnold S J, Dobre A, Robins A (2009). A field study of factors influencing the concentrations of a traffic-related pollutant in the vicinity of a complex urban junction. Atmos Environ, 43(32): 5027–5037

[27] Wang X, Westerdahl D, Wu Y, Pan X, Zhang K M (2011). On-road emission factor distributions of individual diesel vehicles in and around Beijing, China. Atmos Environ, 45(2): 503–513

[28] Wang Z, He H D, Lu F, Lu Q C, Peng Z R (2015b). Hybrid model for prediction of carbon monoxide and fine particulate matter concentrations near a road intersection. Transportation Research Record. Journal of the Transportation Research Board, 2503: 29–38

[29] Wang Z, Lu F, He H D, Lu Q C, Wang D, Peng Z R (2015a). Fine-scale estimation of carbon monoxide and fine particulate matter concentrations in proximity to a road intersection by using wavelet neural network with genetic algorithm. Atmos Environ, 104: 264–272

[30] Wold S, Sjostrom M, Eriksson L (2001). PLS-regression: a basic tool of chemometrics. Chemom Intell Lab Syst, 58(2): 109–130

[31] Yao X H, Lau N T, Fang M, Chan C K (2007). Correlations of ambient temperature and relative humidity with submicron particle number concentration size distributions in on-road vehicle plumes. Aerosol Sci Technol, 41(7): 692–700

[32] Yli-Tuomi T, Aarnio P, Pirjola L, Mäkelä T, Hillamo R, Jantunen M (2005). Emissions of fine particles, NO_x, and CO from on-road vehicles in Finland. Atmos Environ, 39(35): 6696–6706

[33] Zhang D Z, Yu Y, Peng Z R (2014). Near-road PM_2.5 concentration estimation using artificial neural network approach. Proceedings of the 93rd Annual Meeting of the Transportation Research Board, Washington, DC, January

[34] Zhu Y, Hinds W C, Kim S, Sioutas C (2002). Concentration and size distribution of ultrafine particles near a major highway. J Air Waste Manag Assoc, 52(9): 1032–1042

[35] Zhu Y, Kuhn T, Mayo P, Hinds W C (2006). Comparison of daytime and nighttime concentration profiles and size distributions of ultrafine particles near a major highway. Environ Sci Technol, 40(8): 2531–2536

[36] Zito P, Chen H B, Bell M C (2008). Predicting real-time roadside CO and NO₂ concentrations using neural networks. IEEE Trans Intell Transp Syst, 9(3): 514–522

RIGHTS & PERMISSIONS

Higher Education Press and Springer-Verlag Berlin Heidelberg