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.

Impact of Outdoor Air Pollution on Indoor Air Quality in Low-Income Homes during Wildfire Seasons

“…Outdoor pollutant concentrations monotonically decreased with increasing distance from the closest major road, a finding in good agreement with a number of previous studies [61,62,63]. It was noted in our study, however, that the geometric means of PN 0.5–2.5 , BC, and NO 2 outdoor concentrations had more significant decline than CO with increasing distance from the major road (Figure 8).…”

Geographical Variation of COPD Mortality and Related Risk Factors in Jiading District, Shanghai

“…However, they selected the length of local roads within a 200 m radius of postal code centroid rather than residential distance to the closest road as indicator, which might explain part of the geographical heterogeneity observed since different traffic parameters led to various sensitivity in estimates of exposure ( 11 ). The discrepancy between the results of residential proximity to highway and road might be due to a wide emission range of pollutants on expressways and a declined concentration with increasing distance ( 29 ).…”

Traffic exhaust to wildfires: PM2.5 measurements with fixed and portable, low-cost LoRaWAN-connected sensors

“…Devices installed at the roadside showed substantially elevated readings of PM 2.5 compared to background air quality figures from the nearest DPIE Air Quality Monitoring Station in Pearce Park, Liverpool (Fig 7). Values at the intersection of Bigge St and Scott St were generally around an order of magnitude greater than background, consistent with more severe pollution caused by stopstart traffic [37][38][39]. There were few similarities between the 2 time-series, suggesting that the air quality at the roadside was mainly influenced by local pollution, from motor vehicles; as has been found in cities in other countries [40][41][42][43].…”