Roadside Air Research Articles

Air quality simulation of existing city block using chemistry-coupled CFD model

In urban area, roadside air pollution is a serious environmental issue. In order to evaluate the roadside air pollution, it is requires to consider the both of chemical reaction and shape of buildings. In this study, a chemistry-coupled CFD (computational fluid dynamics) model was applied to assess the roadside air quality in a real situation. CBM-IV (Carbon bond mechanism IV) was used as the chemical reaction model coupled to the CFD model. The performance of the chemistry-coupled CFD model was tested in Umeda-shindo (Osaka prefecture), where roadside monitoring station is located, 24 hours on 23rd August 2010. The boundary conditions were calculated by air quality model WRF-CMAQ (Weather Research and Forecasting - Community Multiscale Air Quality Modeling System). Results showed that comparing with the observation data, the chemistry-coupled CFD results showed better accuracy in NOx concentration than the WRF-CMAQ data. In a real situation, the building geometry and mobile emission were found to have great impacts on the urban air quality in the CFD simulation, emphasizing the importance to assess the roadside air pollution with high spatial resolution.

Analysis of roadside air pollution in Osaka City using biomonitoring method

Analysis of roadside air pollution in Osaka City using biomonitoring method

Residuals in the modelling of pollution concentration depending on meteorological conditions and traffic flow, employing decision trees

Two data mining methods – a random forest and boosted regression trees – were used to model values of roadside air pollution depending on meteorological conditions and traffic flow, using the example of data obtained in the city of Wrocław in the years 2015–2016. Eight explanatory variables – five continuous and three categorical – were considered in the models. A comparison was made of the quality of the fit of the models to empirical data. Commonly used goodness-of-fit measures did not imply a significant preference for either of the methods. Residual analysis was also performed; this showed boosted regression trees to be a more effective method for predicting typical values in the modelling of NO2, NOx and PM2.5, while the random forest method leads to smaller errors when predicting peaks.

Advanced Solar Photocatalytic Asphalt for Removal of Vehicular NOx

Conventional use of solar energy is to convert it into a useful form, e.g. heat or electricity. Alternatively, solar radiation can be used to activate photocatalyst for direct functional photocatalytic applications. In the present research, solar photocatalytic asphalt was developed for removal of vehicular nitrogen oxides (NOx) to mitigate the roadside air pollution problem. Visible-light activated photocatalytic asphalt was fabricated by embedding carbon-modified titanium dioxide (C-TiO2) onto asphalt surface under proper heat treatment. Material characterizations were conducted to study the surface and light absorption properties. Chamber tests of NOx removal were conducted under the conditions that simulated the ambient environment under solar irradiation. The experimental results show that NOx removal by C-TiO2 photocatalytic asphalt is viable, and is better than the more commonly used P25. The parametric analysis also reveals that the material fabrication process can be optimized for making photocatalytic asphalt that is highly effective, durable and cost-effective. This study demonstrates successful use of solar radiation via photocatalysis for functional application that can solve environmental problem.

Lower vehicular primary emissions of NO2 in Europe than assumed in policy projections

Many European countries do not meet legal air quality standards for ambient nitrogen dioxide (NO2) near roads; a problem that has been forecasted to persist to 2030. Although European air quality standards regulate NO2 concentrations, emissions standards for new vehicles instead set limits for NO x —the combination of nitric oxide (NO) and NO2. From around 1990 onwards, the total emissions of NO x declined significantly in Europe, but roadside concentrations of NO2—a regulated species—declined much less than expected. This discrepancy has been attributed largely to the increasing usage of diesel vehicles in Europe and more directly emitted tailpipe NO2. Here we apply a data-filtering technique to 130 million hourly measurements of NO x , NO2 and ozone (O3) from roadside monitoring stations across 61 urban areas in Europe over the period 1990–2015 to estimate the continent-wide trends of directly emitted NO2. We find that the ratio of NO2 to NO x emissions increased from 1995 to around 2010 but has since stabilized at a level that is substantially lower than is assumed in some key emissions inventories. The proportion of NO x now being emitted directly from road transport as NO2 is up to a factor of two smaller than the estimates used in policy projections. We therefore conclude that there may be a faster attainment of roadside NO2 air quality standards across Europe than is currently expected. The fraction of NO2 in NO x emitted from European road transport is up to a factor of two smaller than used in policy projections, suggests an analysis of 130 million roadside observations. Roadside air quality standards may thus be obtained faster.

MOBILE ATMOSPHERIC SENSING

Abstract. Atmospheric quality dramatically deteriorates over the past decades around themetropolitan areas of China. Due to the coal combustion, industrial air pollution, vehicle waste emission, etc., the public health suffers from exposure to such air pollution as fine particles of particulates, sulfur and carbon dioxide, etc. Many meteorological stations have been built to monitor the condition of air quality over the city. However, they are installed at fixed sites and cover quite a small region. The monitoring results of these stations usually do NOT coincide with the public perception of the air quality. This paper is motivated to mimic the human breathing along the citys transportation network by the mobile sensing vehicle of atmospheric quality. To obtain the quantitative perception of air quality, the Environmental Monitoring Vehicle of Wuhan University (EMV-WHU) has been developed to automatically collect the data of air pollutants. The EMV-WHU is equipped with GPS/IMU, sensors of PM2.5, carbon dioxide, anemometer, temperature, humidity, noise, and illumination, as well as the visual and infrared camera. All the devices and sensors are well collaborated with the customized synchronization mechanism. Each sort of atmospheric data is accompanied with the uniform spatial and temporal label of high precision. Different spatial and data-mining techniques, such as spatial correlation analysis, logistic regression, spatial clustering, are employed to provide the periodic report of the roadside air quality. With the EMV-WHU, constant collection of the atmospheric data along the Luoyu Road of Wuhan city has been conducted at the daily peak and non-peak time for half a year. Experimental results demonstrated that the EMV is very efficient and accurate for the perception of air quality. Comparative findings with the meteorological stations also show the intelligence of big data analysis and mining of all sorts of EMV measurement of air quality. It is promising for the aerial and emergent air quality monitoring over the sky of big cities, if EMV-WHU be miniaturized for the unmanned aerial vehicles(UAV) in the future.

Projecting impacts of two-wheelers on urban air quality of Douala, Cameroon

Douala, one of the fastest developing cities of Cameroon, has been experiencing unprecedented growth of two-wheelers (motorbikes) and poor perceived air quality. The city has no air quality monitoring system and no air quality data. The only survey that reported the carbon monoxide (CO) levels was carried out by the World Bank under the Clean Air Initiative in 2002 and another study of traffic counts in 2008. In this study, the World Bank CO concentration levels of 2002 have been validated by back projecting the 2008 traffic scenario using vehicular emission and line source dispersion models and future scenarios up to 2015 have been projected at one of the busiest traffic intersections. The potential impacts of Euro emissions standards to improve the roadside air quality in Douala were studied. The results showed that the CO levels increased by a factor of 18 for a period from 2002 to 2015 with an annual increase of 65% in two-wheelers and 31% in cars. The estimated population of two-wheelers in 2015 was found to be 23 times higher than in 2002, which, by 2035, is expected to grow by 533% and the car ownership by 146%. If Euro II and III emissions standards are gradually implemented on two-wheelers in Cameroon, CO levels along roadways are expected to be reduced by about 70%. These results may be helpful to policy makers to prepare an air quality management plan for the city.

Estimation of the traffic related anthropogenic heat release using BTEX measurements – A case study in Abu Dhabi

The rate of release of anthropogenic heat—heat that results from human activity (mainly motorized transportation and air-conditioning)—is a crucial input to urban microclimate models. Traffic related anthropogenic heat, in particular, is notoriously difficult to estimate and often evades systematic treatment, especially in developing countries where traffic intensity indicators are either not routinely recorded or not publicly available. The most challenging aspect is the derivation of a typical daily profile of the anthropogenic heat release rate, which is essential for the accuracy of the urban microclimate models, given the dynamic nature of the heat island phenomenon. The basic premise of this study is that the traffic intensity profile, and hence the traffic related anthropogenic heat rate profile(s), can be inferred from urban air pollutant concentration measurements. Volatile organic compounds such as Benzene, Toluene, Ethylbenzene and m-, p-, o-Xylenes (BTEX) are the most relevant in this context. A new methodology is proposed for deriving normalized daily profile(s) of traffic related heat release rates using one year of hourly BTEX measurements recorded by a road-side air quality monitoring station in downtown Abu Dhabi. These normalized profiles are calibrated using average traffic related heat release rates derived from a ‘top-down’ analysis of aggregate transportation data. The calibrated daily profiles are subsequently validated according to a ‘bottom-up’ approach whereby the total number of circulating vehicles at a specific time of the day is estimated from satellite images of several carefully selected representative urban districts. The daily traffic related anthropogenic heat rate profile(s) derived according to this methodology are consistent with expectations and comparable to those reported in the literature for comparable cities. The daily profile presents two peaks, the first at about 8am and the second, more pronounced, at about 9pm. The average workday sensible heat release rate is estimated to be 11.4W/m2 with an evening peak of about 19W/m2. The peak latent heat rate is approximately 1.9W/m2 which amounts to about 10% of the sensible rate.

An Agent Based Traffic Regulation System for the Roadside Air Quality Control

This paper describes an on-road air quality monitoring and control approach by proposing an agent-based system for modeling the urban road network infrastructure, establishing the real-time and predicted air pollution indexes in different road segments and generating recommendations and regulation proposals for road users. This can help by reducing vehicle emissions in the most polluted road sections, optimizing the pollution levels while maximizing the vehicle flow. For this, we use data sets gathered from a set of air quality monitoring stations, embedded low-cost e-participatory pollution sensors, contextual data, and the road network available data. These data are used in the air quality indexes calculation and then the generation of a dynamic traffic network. This network is represented by a weighted graph in which the edges weights evolve according to the pollution indexes. In this paper, we propose to combine the benefits of agent technology with both machine learning and big data tools. An artificial neural networks model and the Dijkstra algorithm are used for air quality prediction and the least polluted path finding in the road network. All data processing tasks are performed over a Hadoop-based framework: HBase and MapReduce.

Evaluating impacts of two-wheeler emissions on roadside air quality in the vicinity of a busy traffic intersection in Douala, Cameroon

Air quality is deteriorated due to heavy traffic in the urban centers of Cameroon in Central Africa. The Douala city has witnessed unprecedented growth of vehicles, particularly motorbikes (two-wheelers), which are the primary cause of roadside pollutants. However, the menace of pollution, due to the use of old cars over 12 years, continues. The main objective of this study has been to evaluate the impacts of two-wheelers and old cars on the pollutants originated at the Ndokoti intersection in Douala using a combine field and air quality modeling and assess the effect on urban population. The study uses a semi-empirical model to compute vehicular emission rate, the Gaussian plume model for pollutants dispersion, and the Robust Uniform World Model for assessing impacts of pollutant levels on urban population. The results show that during traffic jam, the concentrations of CO and NO2 increase with the age of cars and found to be higher with the increase in number of two-wheelers. Using models, scenarios such as a car plying together with 2, 4, 6, and 8 two-wheelers have been developed to determine the influence of the two-wheelers on the pollutant concentration. The estimated pollutant concentrations match well with the measured concentrations. The average roadside CO concentration increases from 60 (scenario 1) to 180 mg m−3 (scenario 5), indicating the prominent impact of two-wheelers on air quality. The comparison of the roadside concentrations in Douala and the guidelines of the WHO show that a large exceedance of up to about 300%, depending on the scenario.

Differential neural network approach in information process for prediction of roadside air pollution by peat fire

The paper presents a novel differential neural network model estimating the dispersion of CO emissions from a peat fire near a highway. We have developed approaches for the optimization of the model on the base of simulated and experimental measurements of CO concentrations in the area of dispersion of the smoke cloud. The numerical solutions of the problem are presented in the form of neural network approximations by the Gaussian model and in the form of neural network approximate solutions of partial differential equations. The trained neural network model can be used for the prediction of emergency when wind speed and direction and other fire parameters are changing. The method is also recommended for the development of air quality monitoring and predicting information systems.

Roadside air quality and implications for control measures: A case study of Hong Kong

Traffic related air pollution is one of major environmental issues in densely populated urban areas including Hong Kong. A series of control measures has been implemented by Hong Kong government to cut traffic related air pollutants, including retrofitting the Euro II and Euro III buses with selective catalytic reduction (SCR) devices to lower nitrogen dioxide (NO2) emissions. In order to reveal the real-life roadside air quality and evaluate the effectiveness of the control measures, this study first analyzed the recent six-year data regarding concentrations of pollutants typically associated with traffic recorded in two governmental roadside monitoring stations and second conducted on-site measurements of concentration of pollutants at pedestrian level near five selected roads. Given that there is a possibility of ammonia leakage as a secondary pollutant from SCR devices, a special attention was paid to the measurements of ammonia level in bus stations and along roadsides. Important influencing factors, such as traffic intensity, street configuration and season, were analyzed. Control measures implemented by the government are effective to decrease the traffic emissions. In 2014, only NO2 cannot achieve the annual air quality objective of Hong Kong. However, it is important to find that particulate matters, rather than NO2, post potentially a short-term exposure risk to passengers and pedestrians. Based on the findings of this study, specific control measures are suggested, which are intended to further improve the roadside air quality.

The impacts of roadside vegetation barriers on the dispersion of gaseous traffic pollution in urban street canyons

Vegetation barriers have been widely applied along urban streets to improve roadside air quality. For a deep investigation of their influences, field measurements and numerical simulations are performed in this study. Carbon monoxide (CO) is selected as a representative of gaseous traffic emissions for both field observations and numerical models. Computational Fluid Dynamics (CFD) models of the standard k-ε turbulent model and Eulerian approach for species transport are solved by FLUENT solver. Results obtained from numerical simulations show a good agreement with field observations on the distribution of roadside CO. In perpendicular wind conditions, both field observations and numerical simulations present a prominent CO reduction over the slow lanes (footpath and bikeway) when vegetation barriers exist. To effectively mitigate roadside air pollution, numerical simulations also provide the optimal heights for roadside vegetation barriers in the given street canyons. For street canyons with an aspect ratio (the ratio of building height to street width) ranging from 0.3 to 1.67, 1.1m can be used as an optimal height, and 2.0m could serve as an alternative if tall vegetation barriers are considered. For street canyons with an aspect ratio of lower than 0.3, 0.9m to 2.5m can be considered as the optimal heights for roadside vegetation barriers. According to sensitivity analysis, the optimal heights for vegetation barriers are largely insensitive to wind velocities in the given street canyons. In the more complicated urban street canyons and complex meteorological conditions, the optimal heights can be determined by specific numerical simulations. These findings are expected to provide important insights into alleviation of gaseous mobile emissions in terms of vegetation barrier design in urban streets.

Development and Application of a Next Generation Air Sensor Network for the Hong Kong Marathon 2015 Air Quality Monitoring.

This study presents the development and evaluation of a next generation air monitoring system with both laboratory and field tests. A multi-parameter algorithm was used to correct for the impact of environmental conditions on the electrochemical sensors for carbon monoxide (CO) and nitrogen dioxide (NO2) pollutants. The field evaluation in an urban roadside environment in comparison to designated monitors showed good agreement with measurement error within 5% of the pollutant concentrations. Multiple sets of the developed system were then deployed in the Hong Kong Marathon 2015 forming a sensor-based network along the marathon route. Real-time air pollution concentration data were wirelessly transmitted and the Air Quality Health Index (AQHI) for the Green Marathon was calculated, which were broadcast to the public on an hourly basis. The route-specific sensor network showed somewhat different pollutant patterns than routine air monitoring, indicating the immediate impact of traffic control during the marathon on the roadside air quality. The study is one of the first applications of a next generation sensor network in international sport events, and it demonstrated the usefulness of the emerging sensor-based air monitoring technology in rapid network deployment to supplement existing air monitoring.

Roadside Air Pollutants along Elected Roads in Nairobi City, Kenya

This paper presents a statistical analysis of air quality monitoring in Nairobi city, at three major roads and Industrial Area, a site closer to the main industrial activities. The study was carried out using different gas analyzers and samplers. From the statistical analysis it was found that, there were extremely high values of black carbon which went beyond the upper limit of the instruments (50,000 A‹g/m3) during the day on Ladhis road. Nakumatt Junction site recorded extreme values of Black carbon (14,008 A‹g/m3) in the evening hours, while at Pangani Roundabout site, the diurnal mean value was extreme (14,446.5 A‹g/m3) for the period. None of the four sites exceeded the WHO 24 h limit for both PM10 (50 μg/ m3) and PM2.5 (25 μg/m3). The 24 h mean values of PM10 in the three sites also did not exceed the ambient air quality tolerance Kenyan limit of 100 μg/Nm3 and 150 μg/Nm3 in industrial area. The diurnal mean of SO2 over the four sites was generally low with the highest amount of 1.08 ppb recorded at Pangani Roundabout. This amount is far much below the diurnal WHO and Kenyan limit of 10 ppb and 48 ppb respectively. The global background concentration of carbon monoxide ranges between 0.05-0.12 ppm. The mean 24 h amount of CO in all the sites was above the background concentration, with Pangani Roundabout recording the highest amount of 1.73 ppm. The eight h means for ozone in all the sites were below WHO limit of 51 ppb with the highest amount of 20.2 ppb recorded in industrial area.

NOx and NO2 Benefits of Advanced SCR Systems

All buses were tested over the bus Route 7 through the city of Brighton & Hove which is an important central corridor for public transport in the east and west directions and has the characteristics of inclination, traffic congestion and road junctions where road-side air quality measurements show elevated levels of NOx and NO2. The outward journey is about 9 km and contains both uphill and downhill driving, but is net downhill. The return journey follows a highly similar 9 km route and is net uphill. The route altitude varies from sea-level up to 60 m with several sharp inclines and declines, operation on flat terrain is minimal, Figure 2. Open image in new window FIGURE 2 Route 7 — Altitude versus distance on route outbound (to Marina) and inbound (to depot) journeys (© Ricardo) The busses were driven around the route in a manner that was considered to be representative of normal service, including specified dwell times at each bus stop and a fixed break period between the outbound journey and the return. Each bus drove Route 7 three times with the same driver and the Euro IV bus was driven on two further runs, each by an additional driver with a different characteristic style. In order to replicate the true duty cycle, all buses were loaded with ballast equal to 70 % of the maximum passenger loading. For safety reasons the truck undertook a slightly modified route to avoid tight corners, and made fewer halts. Truck tests were conducted with an empty trailer and with a trailer loaded with 20 t of concrete ballast. Data were continuously acquired and careful extraction of the data permitted the emissions within specific geographic zones to be evaluated within the resolution of the GPS, against traffic control measures, the air quality monitoring stations and bus stops. In agreement with the Brighton & Hove Bus and Coach Company, it was analysed the emissions profiles from Route 7 in both directions and in particular from North Street which is a congested 420 m road restricted to buses, taxis and occasional delivery truck. It is in the centre of Brighton, frequented by many pedestrians, with an average slope of 3 % and an air quality monitoring station situated close to the roadside.

Diurnal and seasonal variations of NO, NO 2 and PM 2.5 mass as a function of traffic volumes alongside an urban arterial

Abstract Urban arterial corridors are landscapes that give rise to short and long-term exposures to transportation-related pollution. With high traffic volumes and a wide mix of road users, urban arterial environments are important targets for improved exposure assessment to traffic-related pollution. A common method to estimate exposure is to use traffic volumes as a proxy. The study presented here analyzes a unique yearlong dataset of simultaneous roadside air quality and traffic observations for a U.S. arterial to assess the reliability of using traffic volumes as a proxy for traffic-related exposure. Results show how the relationships of traffic volumes with NO and NO 2 vary not only by time of day and season but also by time aggregation. At short-term aggregations (15 min) nitrogen oxides were found to have a significant linear relationship with traffic volumes during morning hours for all seasons although variability was still high (r 2 = 0.1–0.45 NO, r 2 = 0.14–0.27 NO 2 ), and little to no relationship during evening periods (r 2 2 2 ). Comparisons with coarse annual results validate the use of traffic volumes to estimate annual exposure concentrations for morning periods (r 2 = 0.89 NO, r 2 = 0.87 NO 2 ) and evening NO 2 ( r 2 = 0.46). Traffic volumes are a weak or poor predictor for annual evening NO (r 2 = −0.09) and short-term 15 min aggregations. Seasonal and diurnal characterizations show that roadside PM 2.5 (mass) measurements do not have a relationship with local traffic volumes, leading us to conclude that PM 2.5 mass is more tied to regional sources and meteorological conditions. As epidemiology and personal exposure assessment research aims to study health impacts and pollutant levels encountered by pedestrians, bicyclists, those waiting for transit, and other road users, these results show when traffic volumes alone can be a reliable proxy for exposure and when this approach is not warranted.

Characterization of gaseous and semi-volatile organic compounds emitted from field burning of rice straw

Rice straw (RS) field burning, commonly practiced in Asia, produces large amounts of toxic air pollutants but has not been comprehensively characterized. This study conducted field and laboratory measurements for gaseous pollutants and semi-VOCs (16 PAHs, 16 chlorinated pesticides and 14 PCBs) in RS burning smoke to determine emission factors (EFs) and emission concentration profiles. Paddy burning experiments were done following common practices used by farmers in Southeast Asia and EFs were estimated using the carbon balance method. Laboratory hood experiments simulated burning of dry RS (moisture content ∼ 5%) and normal RS (moisture ∼ 23–30%). Semi-VOCs were analyzed separately in the particulate (PM) and gas phases, and the levels measured in smoke were compared with those in the paddy background and in general ambient air to identify enrichment of the compounds. Lower EFs of all pollutants were obtained for hood burning dry RS as compared to hood burning normal RS. EFs of all detected pollutants in the field burning were higher than hood burning. The EFs of field burning in mg kg−1 RS were 760 for benzene, 230 for toluene, 510 for SO2, 490 for NO2, 260 for total PAHs (88% in gas phase), 0.11 for total PCBs (59% in gas phase) and 0.23 for OCPs (62% in gas phase). The EF of aldehydes determined in the hood experiment was 80–150 mg kg−1 RS. As compared to ambient air, RS smoke had significant enrichment of light PAHs, fluoranthene in PM and acenaphthylene in gas phase. Smoke had a higher proportion of benzene in BTEX than roadside air. Levels of PCBs, OCPs and aldehydes were higher in the burning smoke compared to ambient air, but there was no significant enrichment of particular compounds. This study provides appropriate ranges of EFs for developing emission inventory of RS spread field burning.

Effect of road blockages on local air pollution during the Hong Kong protests and its implications for air quality management

Roadside air quality in urban areas is largely affected by the traffic emissions. Changes in emissions and transport control policy are often assumed to yield benefits in air quality, but have often not always been effective in producing perceptible improvements due to the complexity of meteorological conditions. This study evaluates the air quality before, during and after a temporary roadway blockage event in Hong Kong that took place during Hong Kong protests from late September to mid-December, 2014. The local regulatory air quality monitoring data from both roadside and general ambient stations were used to assess the impact of roadway blockages on the air quality. There was a public perception of improved air quality, but analysis of the data shows the changes can be difficult to discern. This study showed some benefits deriving from road blockages on the local air quality, but the impact was not always apparent because of seasonal variation in meteorological conditions and synoptic transport of pollutants. The finding suggests care is required before making policy changes based on claimed benefits of shifting transport routes. The study highlights the needs to remove seasonal and meteorological change when examining air pollution data to develop strategies to improve air quality.

서울시 도로변지역과 인근 주거 밀집지역의 실시간 대기 중 PM<sub>2.5</sub>농도 비교

In 2013, International Agency for Research on Cancer (IARC) concluded that outdoor air pollution is carcinogenic to humans, with the particulate matter component of air pollution most closely associated with sufficient evidence of increased cancer incidence by exposure to particulate matter component of air pollution. Motor vehicles are one of a major emission sources of fine particle (PM2.5) in urban areas. A large number of epidemiological studies have reported a positive association of morbidity or mortality with distance from the roadside. We conducted this study to assess the association of PM2.5 concentrations measured at roadside hotspots with those at adjacent residential sites using real-time PM2.5 monitors. We conducted real-time PM2.5 measurements for rush hour periods (08:00∼10:00 and 18:00∼20:00) at 9 roadside air monitoring Hotspot sites in metropolitan Seoul over 3 weeks from October 1 to 21, 2013. Simultaneous measurements were conducted in residential sites within a 100 m radius from each roadside air monitoring site. A SidePak AM510 was used for the real-time PM2.5 measurements. Medians of roadside PM2.5 concentrations ranged from 9.8 µg/m 3 to 38.3 µg/m 3 , while corresponding median values at adjacent residential sites ranged from 4.4 µg/m 3 to 37.3 µg/m 3 . PM2.5 concentrations of residential sites were 0.97 times of hotspot roadside sites. Distributions of PM2.5 concentrations in roadside and residential areas were also very similar. Real-time PM2.5 concentrations at residential sites, (100 m adjacent), showed similar levels to those at roadside sites. Increasing the distance between roadside and residential sites, if needed, should be considered to protect urban resident populations from PM2.5 emitted by traffic related sources.