Impact of local traffic exclusion on near-road air quality: findings from the New York City "Summer Streets" campaign

We monitored curbside airborne particulate matter (PM) concentrations and its proinflammatory capacity during 3 weekends when vehicle traffic was excluded from Park. Ave., New York City. Fine PM concentration peaked in the morning regardless of traffic while ultrafine PM was 58% lower during mornings without traffic. Ultrafine PM concentration varied linearly with traffic flow, while fine PM spiked sharply in response to random traffic events that were weakly correlated with the traffic signal cycle. Ultrafine PM concentrations decayed exponentially with distance from a cross street with unrestricted traffic flow, reaching background levels within 100 m of the source. IL-6 induction was typically highest on Friday afternoons but showed no clear relationship to the presence of traffic. The coarse fraction (>2.5 μm) had the greatest intrinsic inflammatory capacity, suggesting that coarse PM still warrants attention even as the research focus is shifting to nano-particles.     

A Preliminary Study of Modeling the Air Pollution Effects fromTraffic Engineering Alternatives

Three separate mathematical models were combined to calculate the changes in carbon monoxide (CO) concentrations that might result from traffic engineering changes. The three models used were: (1) The Dynamic Highway Transportation model (DHTM) which relates traffic flow patterns to physical parameters and traffic signal characteristics of a network; (2) an emission model that predicts CO emissions from traffic flow parameters such as number of stops, idling time, etc; and (3) the APRAC-1A urban diffusion model which calculates CO concentrations from source distributions and meteorological factors. The composite model was applied to traffic in downtown Chicago for a specific set of meteorological conditions. Results are compared for two traffic signal control schemes. In those blocks where concentrations were highest, the model indicates a 20% reduction is possible through improved traffic signal controls. The model should be useful for testing other traffic control measures.     

Measurement and three-dimensional modeling of airflow and pollutant dispersion in an undersea traffic tunnel

Airflow and pollutant dispersion in a cross-harbor traffic tunnel were experimentally and numerically studied. Concentrations of the gaseous pollutants CO, NOx, and total hydrocarbons (THC) at three axial locations in the tunnel, together with traffic flow rate, traffic speed, and types of vehicle were measured. Three-dimensional (3D) turbulent flow and dispersion of air pollutants in the tunnel were modeled and solved numerically using the finite volume method. Traffic emissions were modeled accordingly as banded line sources along the tunnel floor. The results reveal that cross-sectional concentrations are nonuniformly distributed and that concentrations rise with downstream distance. The piston effect of vehicles alone can provide 9-23% dilution of air pollutants in the tunnel, compounded to a 23-74% dilution effect according to the ventilation condition.     

Exploring the processes governing roadside pollutant concentrations in urban street canyon

This paper describes an in-depth analysis to investigate the huge variation in the measured roadside air-pollutant concentrations of carbon monoxide and nitrogen dioxide in terms of the traffic flow levels, the orientation of the street to the prevailing wind, the wind speed, temperature and barometric pressure. The work has attempted to develop generic parameters that can be applied to other urban areas. However, in the absence of a measure of congestion at the site in Palermo (Italy), the methodological approach proposed used the simultaneous noise measurements, in units of decibels (B), to help parameterise a generic congestion indicator in terms of the traffic flow. The potential transferability of the approach was demonstrated for a site in Marylebone Road, London (UK), given the similarity of the two study sites, canyon shape, traffic characteristics and road orientation. The results showed that, within the range of data available, noise levels could be used as a proxy for flow change on the shoulders of the peak hour and hence congestion and a generic relationship with factors statistically significant at 99 % confidence allows roadside concentrations due to traffic to be estimated with a regression coefficient of R ²?=?0.73 (R?=?0.85). The research demonstrates that whilst there are indeed underlying relationships that can explain the roadside concentrations based on traffic and meteorological conditions, evidence is presented that confirms the complexity of the physical and chemical processes that govern roadside concentrations.     

Measurement and Three-Dimensional Modeling of Airflow and Pollutant Dispersion in an Undersea Traffic Tunnel

Abstract

Airflow and pollutant dispersion in a cross-harbor traffic tunnel were experimentally and numerically studied. Concentrations of the gaseous pollutants CO, NO_x, and total hydrocarbons (THC) at three axial locations in the tunnel, together with traffic flow rate, traffic speed, and types of vehicle were measured. Three-dimensional (3D) turbulent flow and dispersion of air pollutants in the tunnel were modeled and solved numerically using the finite volume method. Traffic emissions were modeled accordingly as banded line sources along the tunnel floor. The results reveal that cross-sectional concentrations are nonuniformly distributed and that concentrations rise with downstream distance. The piston effect of vehicles alone can provide 9–23% dilution of air pollutants in the tunnel, compounded to a 23–74% dilution effect according to the ventilation condition.     

A field study of factors influencing the concentrations of a traffic-related pollutant in the vicinity of a complex urban junction

The paper describes a field study focused on the dispersion of a traffic-related pollutant within an area close to a busy intersection between two street canyons in Central London. Simultaneous measurements of airflow, traffic flow and carbon monoxide concentrations ([CO]) are used to explore the causes of spatial variability in [CO] over a full range of background wind directions. Depending on the roof-top wind direction, evidence of both flow channelling and recirculation regimes were identified from data collected within the main canyon and the intersection. However, at the intersection, the merging of channelled flows from the canyons increased the flow complexity and turbulence intensity. These features, coupled with the close proximity of nearby queuing traffic in several directions, led to the highest overall time-average measured [CO] occurring at the intersection. Within the main street canyon, the data supported the presence of a helical flow regime for oblique roof-top flows, leading to increased [CO] on the canyon leeward side. Predominant wind directions led to some locations having significantly higher diurnal average [CO] due to being mostly on the canyon leeward side during the study period. For all locations, small changes in the background wind direction could cause large changes in the in-street mean wind angle and local turbulence intensity, implying that dispersion mechanisms would be highly sensitive to small changes in above roof flows. During peak traffic flow periods, concentrations within parallel side streets were approximately four times lower than within the main canyon and intersection which has implications for controlling personal exposure. Overall, the results illustrate that pollutant concentrations can be highly spatially variable over even short distances within complex urban geometries, and that synoptic wind patterns, traffic queue location and building topologies all play a role in determining where pollutant hot spots occur.     

Source profiles and ozone formation potentials of volatile organic compounds in three traffic tunnels in Kaohsiung,Taiwan

Twenty-five volatile organic compounds (VOCs) up to C10 were measured using Carbotrap multibed thermal adsorption tubes during the morning and afternoon rush hours on four different days in all three traffic tunnels in Kaohsiung, Taiwan. A gas chromatograph (GC) equipped with a flame-ionization detector (FID) was then used to analyze the VOCs. The analytical results show that VOC concentrations increase with traffic flow rate, and emission profiles in the three tunnels are mostly in the range C2-C6. In addition to the traffic conditions and vehicle type, the pattern of emissions in each tunnel was also influenced by other factors, such as vehicle age, nearby pollution sources, and the spatial or temporal variation of VOCs in the urban atmosphere. The ozone formation potential (OFP) in each tunnel was assessed based on the maximum incremental reactivities of the organic species, demonstrating that OFP increases with traffic flow rate. Vehicle distribution influences the contributions of organic group to OFP in a tunnel. Meanwhile, when ranked in descending order of contribution to OFP in all tunnels, the organic groups followed the sequence olefins, aromatics, and paraffins.     

A numerical experiment of roadside diffusion under traffic-produced flow and turbulence

Roadside air pollution due to heavy traffic is one of the unsettled issues in the atmospheric environment in urban areas. As a practical application of a Computational Fluid Dynamics (CFD) model, a coupled mesoscale-CFD model was applied to the Ikegamicho area of Kawasaki City, Japan. For this study, the effects of traffic-produced flow and turbulence (TPFT) on the dispersion of the pollutants near the heavy traffic road were mainly investigated in an actual urban area. First, a series of preliminary CFD calculations was conducted for a road tunnel field experiment to obtain a fitting parameter for the traffic-produced flow. The calculation was then performed for 24 h in December 2005 around Ikegamicho, and the results were compared with the data at a roadside monitoring post in the area, located 10 m from the boundary of the ground road. In general, the effect of traffic-produced flow and turbulence was limited at the downstream side of the roads. The maximum concentration of NO_x was reduced and smoothed out along the traffic flow by the traffic-produced flow and turbulence on the road. The effects of traffic-produced turbulence on the dispersion of pollutants were greater than those of traffic-produced flow; however, the effects of traffic-produced flow were not negligible. The concentration of pollutants was not particularly dependent on the turbulent Schmidt number because most of the emission sources were introduced as volume sources in the present calculations, and the effect caused by differences in the material diffusion coefficient was not particularly significant at the outside of the road.     

Differences in airborne particle and gaseous concentrations in urban air between weekdays and weekends

Airborne particle number concentrations and size distributions as well as CO and NO_x concentrations monitored at a site within the central business district of Brisbane, Australia were correlated with the traffic flow rate on a nearby freeway with the aim of investigating differences between weekday and weekend pollutant characteristics. Observations over a 5-year monitoring period showed that the mean number particle concentration on weekdays was (8.8±0.1)×10³ cm⁻³ and on weekends (5.9±0.2)×10³ cm⁻³—a difference of 47%. The corresponding mean particle number median diameters during weekdays and weekends were 44.2±0.3 and 50.2±0.2 nm, respectively. The differences in mean particle number concentration and size between weekdays and weekends were found to be statistically significant at confidence levels of over 99%. During a 1-year period of observation, the mean traffic flow rate on the freeway was 14.2×10⁴ and 9.6×10⁴ vehicles per weekday and weekend day, respectively—a difference of 48%. The mean diurnal variations of the particle number and the gaseous concentrations closely followed the traffic flow rate on both weekdays and weekends (correlation coefficient of 0.86 for particles). The overall conclusion, as to the effect of traffic on concentration levels of pollutant concentration in the vicinity of a major road (about 100 m) carrying traffic of the order of 10⁵ vehicles per day, is that about a 50% increase in traffic flow rate results in similar increases of CO and NO_x concentrations and a higher increase of about 70% in particle number concentration.     

Model calculation of environmentally friendly traffic flows in a rapidly growing urban centre in India

The paper highlights the application of an integrated decision support system for calculation of environmental friendly traffic flows in urban networks under different management strategies. Each proposed alternative is evaluated using a GIS and GPS environment that may, on a local basis, affect the environmental burden and contribute to pollution load in the region. For each link of the network an environmental capacity is calculated, taking into consideration the hydrodynamic theory based traffic flow dependent on the length of the road network and the average traffic volume and speed. The studied management options include: modifying the existing road network; road widening activities; bus bay relocation; construction of RUB/ROBs; rescheduling the work activities; parking management. The integrated transportation decision support system offers entirely new way of using the GIS, GPS and field survey data for model calculation of pollution load from road traffic to devise environmentally friendly traffic flows.     

Development of an empirical model to estimate real-world fine particulate matter emission factors: the traffic air quality model

The purpose of the study was to quantify the impact of traffic conditions, such as free flow and congestion, on local air quality. The Borman Expressway (I-80/94) in Northwest Indiana is considered a test bed for this research because of the high volume of class 9 truck traffic traveling on it, as well as the existing and continuing installation of the Intelligent Transportation System (ITS) to improve traffic management along the highway stretch. An empirical traffic air quality (TAQ) model was developed to estimate the fine particulate matter (PM2.5) emission factors (grams per kilometer) based solely on the measured traffic parameters, namely, average speed, average acceleration, and class 9 truck density. The TAQ model has shown better predictions that matched the measured emission factor values more than the U.S. Environmental Protection Agency (EPA)-PART5 model. During congestion (defined as flow-speeds < 50 km/hr [30 mi/hr]), the TAQ model, on average, overpredicted the measured values only by a factor of 1.2, in comparison to a fourfold underprediction using the EPA-PART5 model. On the other hand, during free flow (defined as flow-speeds > 80 km/hr [50 mi/hr]), the TAQ model was conservative in that it overpredicted the measured values by 1.5-fold.     

Separate determination of PM10 emission factors of road traffic for tailpipe emissions and emissions from abrasion and resuspension processes

Little is known about the relevance of mechanically produced particles of road traffic from abrasion and resuspension processes in relation to the exhaust pipe particles. In this paper, emission factors of PM₁₀ and PM₁ for light and heavy-duty vehicles were derived for different representative traffic regimes from concentration differences of particles and nitrogen oxides (NO_x) in ambient air upwind and downwind of busy roads, or alternatively of kerbsides and nearby background sites. Hereby, PM₁ was interpreted as direct exhaust emissions and PM₁₀-PM₁ as mechanically produced emissions from abrasion and resuspension processes. The results show that abrasion and resuspension processes represent a significant part of the total primary PM₁₀ emissions of road traffic. At sites with relatively undisturbed traffic flow they are in the same range as the exhaust pipe emissions. At sites with disturbed traffic flow due to traffic lights, emissions from abrasion/resuspension are even higher than those from the exhaust pipes.     

Longitudinal emissions evaluation of mixed (cooperative) adaptive cruise control traffic flow and its relationship with stability

ABSTRACT

Cooperative adaptive cruise control (CACC) vehicles need vehicle-to-vehicle (V2 V) communication to achieve CACC function. When a CACC vehicle follows a manual-driven vehicle (MDV) without V2 V communication, it needs degenerate to adaptive cruise control (ACC). By using real experiments, California PATH program indicated that ACC vehicles are apt to be unstable, which may have negative influence on fuel consumption and traffic emissions. Hence, this paper studies the impacts of the mixed CACC-MDV traffic on fuel consumption and emissions, by taking into consideration partial degenerations from stable CACC vehicles to unstable ACC vehicles. To deal with this, microscopic simulations were adopted by using car-following models. Then, an appropriate emission model was used for evaluating the emission impacts under different CACC market penetration rates (MPRs). In order to obtain reliable evaluation results, the models validated by PATH program using real experimental data were employed as the CACC and ACC car-following models. In addition, we also analytically investigated stability of the mixed traffic flow under different CACC MPRs, in order to explore its relationship with the emission impacts. The results show that the fuel consumption and emissions firstly increase and then decrease with the increase of the CACC MPR. This means the mixed traffic under some ranges of CACC MPRs will produce more fuel consumption and emissions, compared with the full MDVs traffic. It indicates that stability situations of the mixed traffic qualitatively influence the impact trend of CACC MPRs on fuel consumption and emissions. Then, V2 V communication equipments on MDVs are not only encouraging but also essential to avoid the deterioration of fuel consumption and emissions of the mixed traffic flow.     

A Comparative Study of Aluminum Smelter Roof Vent Sampling Methods

Abstract

The purpose of the study was to quantify the impact of traffic conditions, such as free flow and congestion, on local air quality. The Borman Expressway (I-80/94) in Northwest Indiana is considered a test bed for this research because of the high volume of class 9 truck traffic traveling on it, as well as the existing and continuing installation of the Intelligent Transportation System (ITS) to improve traffic management along the highway stretch. An empirical traffic air quality (TAQ) model was developed to estimate the fine particulate matter (PM_2.5) emission factors (grams per kilometer) based solely on the measured traffic parameters, namely, average speed, average acceleration, and class 9 truck density. The TAQ model has shown better predictions that matched the measured emission factor values more than the U.S. Environmental Protection Agency (EPA)-PART5 model. During congestion (defined as flow-speeds <50 km/hr [30 mi/hr]), the TAQ model, on average, overpredicted the measured values only by a factor of 1.2, in comparison to a fourfold underprediction using the EPA-PART5 model. On the other hand, during free flow (defined as flow-speeds >80 km/hr [50 mi/hr]), the TAQ model was conservative in that it overpredicted the measured values by 1.5-fold.     

Removal of lead and zinc ions from aqueous solution using Amasya zeolites from Turkey

A 3-D Eulerian-Lagrangian approach to moving vehicles is presented that takes into account the traffic-induced flow rate and turbulence. The method is applied to pollutant dispersion in an individual street canyon and a system of two street canyons forming a perpendicular intersection. The approach is based on computational fluid dynamics (CFD) calculations using a Eulerian approach for continuous phase and a Lagrangian approach for moving vehicles. The wind speed was assigned values of 4, 7 and 12 m/s. One-way and two-way traffic with different traffic rates per lane is considered. In the case of the intersection, a longitudinal wind direction was assumed. Predictions show differences in the pollutant dispersion in the case of one-way and two-way traffic.     

A semi-empirical box modeling approach for predicting the carbon monoxide concentrations at an urban traffic intersection

Emissions generated roadside and at intersections are observed to be affected when there is a sudden change in the traffic flow pattern or increase in the vehicular population, particularly, during peak hours and during special events. The vehicles that queue up at traffic intersections spend a longer amount of time in idle driving mode generating more pollutant emissions per unit time. Other driving patterns (i.e., acceleration, deceleration and cruising) are also observed at intersections, affecting the emission pattern and therefore the resulting pollutant concentrations. The emission rate is not only affected by the increase in the vehicular population but also by the constantly changing traffic flow patterns and vehicles’ driving modes. The nature of the vehicle flows also affects the rate and nature of the dispersion of pollutants in the vicinity of the road, influencing the pollutant concentration. It is, therefore, too complex to simulate the effect of such dynamics on the resulting emission rates using conventional deterministic causal models.In view of this, a simple semi-empirical box model based on the ‘traffic flow rate’, is demonstrated in the present study for estimating the hourly average carbon monoxide (CO) concentrations on a 1-week data at one of the busiest traffic intersections in Delhi. The index of agreement for a whole week, was found to be 0.84, suggesting that the semi-empirical model is 84% error free. A value of 0.87 was found for weekdays and 0.75 for weekend days. The correlation coefficient for the whole week was found to be 0.75, with 0.78 for the weekdays and 0.62 for the weekend days. The RMSE and RRMSE were found to be 1.87% and 41% for a whole week, with 1.81% and 39.93% for the weekdays and 2.0% and 43.47% for the weekend days, respectively. Specific vehicle emission rates are optimized in this study for individual vehicle category, which may be useful in assessing their impacts on the air quality when there is a significant change in a specific vehicular population and the traffic pattern.     

Benefits of mitigated ambient air quality due to transportation control on childhood asthma hospitalization during the 2002 summer Asian games in Busan, Korea

The objective of this study is to see whether there were any health benefits of mitigated air pollution concentration due to reduced traffic flow during a citywide intervention for the 2002 Summer Asian Games. Relative risks of hospitalization for childhood asthma during the post-Asian Game period compared with the baseline period were estimated using a time-series analysis of the generalized additive Poisson model. Fourteen consecutive days of traffic volume control in Busan during the Games reduced all regulated air pollutant levels by 1-25%. The estimated relative risk of hospitalization during the post-Games period over the baseline period was 0.73 (95% confidence interval [CI] = 0.49, 1.11). We observed that this reduced air pollution was unique in 2002 when the traffic volume reduction program was applied during the Games period. This empirical data provides epidemiologic evidence of the health benefits resulting from environmental interventions to reduce ambient air pollution.     

Road traffic impact on urban water quality: a step towards integrated traffic,air and stormwater modelling

Methods for simulating air pollution due to road traffic and the associated effects on stormwater runoff quality in an urban environment are examined with particular emphasis on the integration of the various simulation models into a consistent modelling chain. To that end, the models for traffic, pollutant emissions, atmospheric dispersion and deposition, and stormwater contamination are reviewed. The present study focuses on the implementation of a modelling chain for an actual urban case study, which is the contamination of water runoff by cadmium (Cd), lead (Pb), and zinc (Zn) in the Grigny urban catchment near Paris, France. First, traffic emissions are calculated with traffic inputs using the COPERT4 methodology. Next, the atmospheric dispersion of pollutants is simulated with the Polyphemus line source model and pollutant deposition fluxes in different subcatchment areas are calculated. Finally, the SWMM water quantity and quality model is used to estimate the concentrations of pollutants in stormwater runoff. The simulation results are compared to mass flow rates and concentrations of Cd, Pb and Zn measured at the catchment outlet. The contribution of local traffic to stormwater contamination is estimated to be significant for Pb and, to a lesser extent, for Zn and Cd; however, Pb is most likely overestimated due to outdated emissions factors. The results demonstrate the importance of treating distributed traffic emissions from major roadways explicitly since the impact of these sources on concentrations in the catchment outlet is underestimated when those traffic emissions are spatially averaged over the catchment area.     

Improving the accuracy of emission inventories with a machine-learning approach and investigating transferability across cities

ABSTRACT

This study presents a novel method for integrating the output of a microscopic emission modeling approach with a regional traffic assignment model in order to achieve an accurate greenhouse gas (GHG, in CO_2-eq) emission estimate for transportation in large metropolitan regions. The CLustEr-based Validated Emission Recalculation (CLEVER) method makes use of instantaneous speed data and link-based traffic characteristics in order to refine on-road GHG inventories. The CLEVER approach first clusters road links based on aggregate traffic characteristics, then assigns representative emission factors (EFs), calibrated using the output of microscopic emission modeling. In this paper, cluster parameters including number and feature vector were calibrated with different sets of roads within the Greater Toronto Area (GTA), while assessing the spatial transferability of the algorithm. Using calibrated cluster sets, morning peak GHG emissions in the GTA were estimated to be 2,692 tons, which is lower than the estimate generated by a traditional, average speed approach (3,254 tons). Link-level comparison between CLEVER and the average speed approach demonstrates that GHG emissions for uncongested links were overestimated by the average speed model. In contrast, at intersections and ramps with more congested links and interrupted traffic flow, the average speed model underestimated GHG emissions. This proposed approach is able to capture variations in traffic conditions compared to the traditional average speed approach, without the need to conduct traffic simulation.

Implications: A reliable traffic emissions estimate is necessary to evaluate transportation policies. Currently, accuracy and transferability are major limitations in modeling regional emissions. This paper develops a hybrid modeling approach (CLEVER) to bridge between computational efficiency and estimation accuracy. Using a k-means clustering algorithm with street-level traffic data, CLEVER generates representative emission factors for each cluster. The approach was validated against the baseline (output of a microscopic emission model), demonstrating transferability across different cities .     

Monitoring of Benzene in Ambient Air with Organic Vapor Badges

The original Texas Intersection Model (TEXIN) for air quality near street intersections has been widely adopted across the nation. At the request of transportation agencies from several states, the TEXIN model was revised to improve its performance and flexibility. The new capabilities include T-intersections, one-way streets, four-way stops, inspection/maintenance capabilities, anti-tampering programs and a short-cut emissions algorithm. TEXIN2 uses the CMA procedures for estimating traffic flow parameters, MOBILE3 to determine free flowing traffic cruise emissions, and CALINE3 to model the pollutant distribution downwind of an intersection. The new model, TEXIN2, offers the user more accurate simulations with enhanced versatility while still requiring a minimal amount of input data.