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Abstract There is evidence that local traffic density and living near major roads can adversely affect health outcomes. We aimed to assess the relationship between local road length, proximity to primary highways, and cause-specific mortality in the 1991 Canadian Census Health and Environment Cohort (CanCHEC). In this long-term study of 2.6 million people, based on completion of the long-form census in 1991 and followed until 2011, we used annual residential addresses to determine the total length of local roads within 200 m of postal code representative points and the postal code's distance to primary highways. The association between exposure to traffic and cause-specific non-accidental mortality was estimated using Cox proportional hazards models, adjusting for individual covariates and contextual factors, including census division-level proportion in high school, the percentage of recent immigrants, and neighborhood income. We performed sensitivity analyses, including adjustment for exposure to PM 2.5 , NO 2 , or O 3 , restricting to subjects in core urban areas, and spatial variation by climatic zone. The hazard ratio (HR) for all non-accidental mortality associated with an interquartile increase in length of local roads was 1.05 (95% CI 1.04, 1.05), while for an interquartile range increase in proximity to primary highways, the HR was 1.03 (95% CI 1.02, 1.04). HRs by traffic quartile increased with increasing lengths of local roads, as well as with closer proximity to primary highways, for all mortality causes. The associations were stronger within subjects' resident in urban core areas, attenuated by adjustment for PM 2.5 , and HRs showed limited spatial variation by climatic zone. In the CanCHEC cohort, exposure to higher road density and proximity to major traffic roads was associated with increased mortality risk from cerebrovascular and cardiovascular disease, ischemic heart disease, COPD, respiratory disease, and lung cancer, with unclear results for diabetes. Highlights • The association between exposure to traffic and mortality was estimated using Cox proportional hazards models. • Hazard ratios (HRs) for mortality related to length of local roads and proximity to primary highways were calculated. • HRs by traffic quartile increased with greater lengths of local roads, and with closer proximity to main highways. • The associations were stronger within subjects' resident in urban core areas, attenuated by adjustment for PM 2.5. • HRs showed limited spatial variation by climatic zone. [ABSTRACT FROM AUTHOR]

Public health concerns regarding adverse health effects for populations spending significant amounts of time near high traffic roadways has increased substantially in recent years. Roadside features, including solid noise barriers, have been investigated as potential methods that can be implemented in a relatively short time period to reduce air pollution exposures from nearby traffic. A field study was conducted to determine the influence of noise barriers on both on-road and downwind pollutant concentrations near a large highway in Phoenix, Arizona, USA. Concentrations of nitrogen dioxide, carbon monoxide, ultrafine particles, and black carbon were measured using a mobile platform and fixed sites along two limited-access stretches of highway that contained a section of noise barrier and a section with no noise barrier at-grade with the surrounding terrain. Results of the study showed that pollutant concentrations behind the roadside barriers were significantly lower relative to those measured in the absence of barriers. The reductions ranged from 50% within 50 m from the barrier to about 30% as far as 300 m from the barrier. Reductions in pollutant concentrations generally began within the first 50 m of the barrier edge; however, concentrations were highly variable due to vehicle activity behind the barrier and along nearby urban arterial roadways. The concentrations on the highway, upwind of the barrier, varied depending on wind direction. Overall, the on-road concentrations in front of the noise barrier were similar to those measured in the absence of the barrier, contradicting previous modeling results that suggested roadside barriers increase pollutant levels on the road. Thus, this study suggests that noise barriers do reduce potential pollutant exposures for populations downwind of the road, and do not likely increase exposures to traffic-related pollutants for vehicle passengers on the highway. [ABSTRACT FROM AUTHOR]

Modelling approaches for simulating air and stormwater pollution due to on-road vehicles are reviewed and discussed. Models for traffic, emissions, atmospheric dispersion, and stormwater contamination are studied with particular emphasis on their couplings to create a modelling chain. The models must be carefully selected according to the requirements and level of detail of the integrated modelling chain. Although a fair amount of research has been conducted to link air pollution and road traffic, many questions related to spatio-temporal scales, domains of validity, consistency among models, uncertainties of model simulation results, and interfaces between models remain open. The aim of this work is to review the current status of the relationships between traffic, emissions, air quality, and water quality models, to recommend modelling approaches and to propose some directions for improving the state of the science. The difficulties and challenges associated with model coupling are illustrated with specific examples. [ABSTRACT FROM AUTHOR]

This article presents the development of a estimation model using an artificial neural network to estimate the traffic factor parameter, which reflects changes in travel time for a single transport connection. The modeling of traffic is highly challenging due to the complex and non-linear nature of road systems, the interactions between diverse road users, and the ripple effects of congestion. The research problem addressed is the need to consider a wide range of factors that contribute to congestion, as identified in the literature. To address this challenge, a universal Feedforward Neural Network (FNN) was designed, specifically the Multilayer Perceptron (MLP) 38–10-1 model. The input layer neurons of the MLP receive a vector of input values representing various factors such as road types, technical properties, time of day, days of the week, incidents, weather conditions, and population density. The model was trained using a dataset consisting of 41,945 records of fully completed input variables, extracted from a larger dataset of 300,000 travel time measurements collected from a real transport network mapped on a macro scale (Mazovia, Poland). During the research, the model achieved a satisfactory level of Mean Absolute Percentage Error (MAPE) for the test set (9.12%) and a Normalized Root Mean Squared Error (NRMSE) below 0.02, indicating good estimation performance. Furthermore, this work proposes specialized models with the structure of MLP 34–10-1 for individual types of roads, which also demonstrated satisfactory estimation abilities. These models have practical applications in traffic management and planning. Overall, this research addresses the research problem of modeling factors for predicting travel time changes using an artificial neural network approach. The developed models provide accurate estimations and offer potential applications in transportation systems. [ABSTRACT FROM AUTHOR]

Atmospheric emission inventories are important tools for studying air quality and to set up possible remediation plans in areas characterised by nonattainment of the limit values established by legislation. In industrialised countries a considerable fraction of the emissions is due to road traffic, in particular in urban areas. For this reason emissions from road traffic must be estimated as accurately as possible, a task that can be performed, for the European vehicle fleet, thanks to the availability of the COPERT III methodology. This methodology is powerful and accurate, even if its algorithms can be difficult to apply in a regional emission inventory; moreover the collection of the necessary input data requires a lot of resources and time. This paper describes the road traffic emission inventory estimated for Region Sardinia (Italy) with a bottom-up approach. The estimation has been done by means of a software tool (EMITRA—EMIssions from road TRAnsport) which implements the COPERT III methodology. The resulting emission inventory has been compared against another emission inventory for Sardinia and against emission inventories for other Italian regions, to evaluate its reliability. [Copyright &y& Elsevier]

Size resolved emission factors for submicrometer particles related to trace gases have been obtained from measurement data at a suburban road side, with a traffic intensity of 18,000 vehicles per day. Number of particles with diameter 10–368 nm, trace gases (NO, NOx,O3 and SO2), traffic and meteorology parameters were measured outside of Göteborg, Sweden. Size distributions of small particles at the site are presented and their relation to meteorological and traffic related variables was evaluated. Wind speed correlated negatively with 10–368 nm particles and temperature correlated negatively with the smaller particles (10–60 nm). Nitric oxide was shown to be a better tracer for traffic related ultrafine particles, than traffic intensity itself.The calculated emission factor, with errors at 95% confidence level, for particles in the range 10–368 nm is presented in relation to nitrogen oxides. The emission factors were 268±60 and 176±37 particles cm-3 per ppb NO and NOx, respectively. The particle emission factors for 10–100, 10–50, 50–170 and 170–368 nm were 260±70, 228±52, 41±11 and <1 particle cm-3 per ppb NO, respectively. The size distribution of the emissions is given by number of particles normalised by the width of the size bin, i.e. in units of dNd log Dp-1 ppb-1. The maximum normalised emission factor was 450 cm-3 per ppb NO for 20 nm particles. The shape of the size distribution of emissions revealed one sharp peak at 20 nm, with a small shoulder at 70 nm. [Copyright &y& Elsevier]

This study attempts to make use of traffic behaviour on the aggregate level to estimate congestion on urban arterial and sub-arterial roads of a city exhibiting heterogeneous traffic conditions by breaking the route into independent segments and approximating the origin-destination based traffic flow behaviour of the segments. The expected travel time in making a trip is modelled against sectional traffic characteristics (flow and speed) at origin and destination points of road segments, and roadway and segment traffic characteristics such as diversion routes are also tried in accounting for travel time. Predicted travel time is then used along with free flow time to determine the state of congestion on the segments using a congestion index (CI). A development of this kind may help in understanding traffic and congestion behaviour practically using easily accessible inputs, limited only to the nodes, and help in improving road network planning and management. [ABSTRACT FROM AUTHOR]

Abstract: Large scale road traffic is a complex system that could be modelled with a multilevel approach. Most of the multilevel models from the literature have fixed a priori the two levels of detail (micro-meso, micro-macro, meso-macro). This paper has two goals: it presents the state of the art related to large scale traffic models, and it gives the main research direction to create a novel multilevel model that support dynamic selection of the level during the simulation. Our proposal is based on an organizational modelling approach and the use of the concept of holon (agent composed of agents). [ABSTRACT FROM AUTHOR]

This paper presents a method for defining and improving the traffic conditions in a set of cross section in the city of Cluj-Napoca, using microsimulation software for the traffic. Simulation models are designed to mimic the behavior of traffic in a time and space transport system in order to predict the system's performance. A simulation model studies a real world system, considering mathematical and logical concepts associated with the system operation and analyzes them using complex computer programming. Each simulation model presents a set of advantages such as: it can be more accurate than an analytical approach, it is able to test new conditions, it can improve the perspective concerning the significance of variables and of the way these variables interact. A case study is presented, using a set of three street intersections. In these intersections measurements of traffic during morning peak hours were performed. The measurements were acquired both manually and automatically, using time slots of 15 minutes each. The collected data was also used for model calibration. With the help of microsimulation software and a well-balanced model, information regarding traffic conditions can be found, resulting in analyses of the traffic evolutions. Some traffic conditions issues are identified and a set of improvement suggestions are presented. The measures proposed in this paper need to be tested and further optimized also by means of microsimulation, before being implemented, in order to obtain satisfactory results. The area under investigation exhibits quite large delays in traffic, in present-day conditions. This means smaller displacement speed, and, implicitly, more toxic emissions, that make the system be farther from the idea of sustainable transportation. [ABSTRACT FROM AUTHOR]

The continuous increase of vehicle fleet along with the development of road transport networks has associated a wide range of externalities. Main types of externalities refer to environmental impact, expressed as Greenhouse Gas Emissions, raw materials depletion, energy and fuel consumption or disruption of ecosystem equilibrium, social impact, expressed as quality of people life, human health and economic impact, expressed as economic growth. The current development of road transport promotes a growing interest for sustainable and eco-friendly transportation worldwide. In the context of a wide range of externalities, the present paper aims to emphasize the ecological impact associated with road transportation traffic, customized for specific road networks from North-East Region of Romania and expressed in atmospheric polluting emissions. In correlation with traffic pollution, the current research highlights the exponential increase of the greenhouse gas effect and fuel consumption, providing specific strategies, necessary for the improvement of road network sustainability, based on the results of the undertaken study. The analysis of the environmental impact implies a quantitative assessment of energy consumption and CO2e emissions produced by road traffic. In this respect has been carried out the evaluation of atmospheric pollution produced by the traffic recorded in 2010, using the annual daily average traffic for the year in question. Based on the coefficients of traffic evolution it has been forecasted the pollution level for 2015, 2020 and 2030. The calculations have been performed based on the current configuration of the vehicle fleet from NE Region of Romania, investigated for two types of roads, namely a road with an optimum pavement condition in comparison with a road pavement with distresses. For the first case study, was considered a road pavement suitable rehabilitated, by intervention works of maintenance and rehabilitation, applied to an optimum moment. This case study presents the ideal situation, from traffic sustainability point of view, since the vehicles speed isn’t influenced by the pavement condition, the road level of service is free flow. The evaluation performed for this particular case study showed that, for the current vehicle fleet and average vehicles speed, the environmental impact expressed in pollutant emissions registers the lowest values. For the second case study, the evaluation focused on the ecological impact associated with the road traffic, based on the current road network pavement condition. Considering the traffic congestion and pollution increase due to road distresses, the studies in the present paper were focused on the pollution level, specific to County of Iaşi road network. For a proper analysis of pollutant emissions, associated with road transport traffic, has been used European Environment Agency (EEA) computer software COPERT 4. The software was developed to perform evaluations of air pollutant and greenhouse gas emissions specific to road transport, the deliverables being consistent with the latest regulations in the field. The research objective was to deliver intervention strategies and scenarios, related with the high increase in vehicles fleet, usage of alternative fuels and CO2e emissions level, towards sustainable road transportation. [ABSTRACT FROM AUTHOR]

This article describes the methods of mathematical modeling and simulation of processes of local interaction in transport systems. Described transport flow models, developed by the author, based on extension of the microscopic Treiber's model and on the queuing theory. These models cover more details of behavior of flow participants on signal-controlled crossroads. modification. The article describes a model of traffic on the ring road. [ABSTRACT FROM AUTHOR]

Microblogs like Twitter 1 are sources for a lot of useful information. But these information are unstructured. To automatically process it, these information have to be extracted with the help of natural language processing techniques. Corresponding systems for information extraction have to be trained and validated with manual annotated data. This paper presents an approach for the cooperative creation of annotated corpora for training and validation of information extraction systems supported by statistical analyses. 1 https://twitter.com/ [ABSTRACT FROM AUTHOR]

Many transportation agencies such as Departments of Transportation in the USA are using Asset Management Optimization models to plan their maintenance and rehabilitation projects. Currently available commercial solutions are often focused only on global asset performance/money spent aspect of the problem and do not take into account the benefits of synergy between the projects, i.e. the benefits of scheduling nearby projects in the same year in order to take advantage of fixed cost savings due to economies of scale. At the strategic level adding variables and constraints to account for these economies of scale are not practical since such models often already have millions of variables and constraints and adding anything new could reduce the performance significantly. Looking at the problem from a tactical perspective however it is possible to run an analysis on the global work plan that can improve cost savings from economies of scale with subtle changes to the originally analyzed performance. For example, in case of pavement management it is a common result to see gaps in the produced theoretical work plans along a route that would result in increased mobilizations to accomplish the plan. This results in extra costs both for the agency and road user. A common result might suggest fixing miles 1-8 and 9-10 in the one year and then fixing mile 8-9 in a subsequent year. Even if this solution provided the best performance for the money it is impractical to actually do it, it would make much more sense to simply fix entire 10 mile segment while achieving almost the same performance and saving mobilization costs which can be significant cost savings. A project coordination optimization model would analyze economies of scale problems such as these while also considering network constraints such as limited budgets and resources available within the administrative unit managing the work plan. This paper proposes an optimization model, referred to as Project Coordination model throughout the paper, that would attempt to improve an already created work plan by slightly changing the project schedules such that the adjusted plan would achieve similar performance while providing a more practical solution by maximizing economies of scale with reduced delivery and mobilization costs. The results of applying proposed model to one illustrative example and two real life work plans are presented and thoroughly analyzed. [ABSTRACT FROM AUTHOR]

Effects of source inhomogeneity on pollutant dispersion from a cubic building array are investigated as a function of the external wind direction. Using building-resolving large-eddy simulation, it is found that the results depend strongly on the source location and source uniformity inside a near-field region defined by a radius of homogenisation (RAD) based on the spatial autocorrelation of the pollutant concentration. The sensitivity of the RAD to the source location changes abruptly around 30° and is greatly reduced for wind angles between 30 and 45°, in agreement with velocity statistics and the mean horizontal streamlines. The optimal source allocation, which is a proxy for emissions from time-dependent traffic, also changes around 30°. This work clarifies the relationship between inhomogeneous velocity and pollutant statistics and may be applied to the formulation of traffic control policy. [Display omitted] • Pollutant concentrations in the near field are sensitive to the source distribution. • The extent of the near field can be estimated using a simple statistical method. • Near-field dispersion strongly reflects velocity statistics near the source. • Optimal source allocations are determined for different external wind directions. • Velocity and near-field pollutant statistics change dramatically around 30°. [ABSTRACT FROM AUTHOR]

Abstract: Time–activity patterns are an important determinant of personal exposure to air pollution. This is demonstrated by measuring personal exposure of 16 participants for 7 consecutive days: 8 couples of which one person was a full-time worker and the other was a homemaker; both had a very different time–activity pattern. We used portable aethalometers to measure black carbon levels with a high temporal resolution and a PDA with GPS-logger and electronic diary. The exposure to black carbon differs between partners by up to 30%, although they live at the same location. The activity contributing most to this difference is transport: Average exposure in transport is 6445 ng m−3, followed by exposure during shopping (2584 ng m−3). Average exposure is lowest while sleeping (1153 ng m−3) and when doing home-based activities (1223 ng m−3). Full-time workers spend almost twice as much time in transport as the homemakers. As a result of the study design we measured in several different homes, shops, cars, etc. enabling a better insight in true overall exposure in those microenvironments. Other factors influencing personal exposure are: background concentrations and location of residence in an urban, suburban or rural environment. [Copyright &y& Elsevier]

Abstract: An integrated modelling approach is adopted to estimate microscale urban traffic emissions. The modelling framework consists of a traffic microsimulation model developed in PARAMICS, a microscopic emissions model (Comprehensive Modal Emissions Model), and two dispersion models, AERMOD and the Quick Urban and Industrial Complex (QUIC). This framework is applied to a traffic network in downtown Toronto, Canada to evaluate summer time morning peak traffic emissions of carbon monoxide (CO) and nitrogen oxides (NO x ) during five weekdays at a traffic intersection. The model predicted results are validated against sensor observations with 100% of the AERMOD modelled CO concentrations and 97.5% of the QUIC modelled NO x concentrations within a factor of two of the corresponding observed concentrations. Availability of local estimates of ambient concentration is useful for accurate comparisons of predicted concentrations with observed concentrations. Predicted and sensor measured concentrations are significantly lower than the hourly threshold Maximum Acceptable Levels for CO (31 ppm, ∼90 times lower) and NO2 (0.4 mg/m3, ∼12 times lower), within the National Ambient Air Quality Objectives established by Environment Canada. [Copyright &y& Elsevier]

Hydraulic fracturing (fracking) has been used extensively in the US and Canada since the 1950s and offers the potential for significant new sources of oil and gas supply. Numerous other countries around the world (including the UK, Germany, China, South Africa, Australia and Argentina) are now giving serious consideration to sanctioning the technique to provide additional security over the future supply of domestic energy. However, relatively high population densities in many countries and the potential negative environmental impacts that may be associated with fracking operations has stimulated controversy and significant public debate regarding if and where fracking should be permitted. Road traffic generated by fracking operations is one possible source of environmental impact whose significance has, until now, been largely neglected in the available literature. This paper therefore presents a scoping-level environmental assessment for individual and groups of fracking sites using a newly-created Traffic Impacts Model (TIM). The model produces estimates of the traffic-related impacts of fracking on greenhouse gas emissions, local air quality emissions, noise and road pavement wear, using a range of hypothetical fracking scenarios to quantify changes in impacts against baseline levels. Results suggest that the local impacts of a single well pad may be short duration but large magnitude. That is, whilst single digit percentile increases in emissions of CO 2 , NO x and PM are estimated for the period from start of construction to pad completion (potentially several months or years), excess emissions of NO x on individual days of peak activity can reach 30% over baseline. Likewise, excess noise emissions appear negligible (< 1 dBA) when normalised over the completion period, but may be considerable (+ 3.4 dBA) in particular hours, especially in night-time periods. Larger, regional scale modelling of pad development scenarios over a multi-decade time horizon give modest CO 2 emissions that vary between 2.5 and 160.4 kT, dependent on the number of wells, and individual well fracking water and flowback waste requirements. The TIM model is designed to be adaptable to any geographic area where the required input data are available (such as fleet characteristics, road type and quality), and we suggest could be deployed as a tool to help reach more informed decisions regarding where and how fracking might take place taking into account the likely scale of traffic-related environmental impacts. [ABSTRACT FROM AUTHOR]

This paper focused on modelling Black Carbon (BC) concentrations in two busy street canyons, the Crown and Belliard Street in Brussels. The used original Operational Street Pollution Model was adapted to BC by eliminating the chemical module and is noted here as CANS BC . Model validations were performed using temporal BC data from the fixed measurement network in Brussels. Subsequently, BC emissions were adjusted so that simulated BC concentrations equalled the observed ones, averaged over the whole period of simulation. Direct validations were performed for the Crown Street, while BC model calculations for the Belliard Street were validated indirectly using the linear relationship between BC and NO x . Concerning the Crown Street, simulated and observed half-hourly BC concentrations correlated well ( r = 0.74) for the period from July 1st, 2011 till June 30th, 2013. In particular, CANS BC performed very well to simulate the monthly and diurnal evolutions of averaged BC concentrations, as well as the difference between weekdays and weekends. This means that the model correctly handled the meteorological conditions as well as the variation in traffic emissions. Considering dispersion, it should however be noted that BC concentrations are better simulated under stable than under unstable conditions. Even if the correlation on half-hourly NO x concentrations was slightly lower ( r = 0.60) than the one of BC, indirect validations of CANS BC for the Belliard Street yielded comparable results and conclusions as described above for the Crown Street. Based on our results, it can be stated that CANS BC is suitable to accurately simulate BC concentrations in the street canyons of Brussels, under the following conditions: (i) accurate vehicle counting data is available to correctly estimate traffic emissions, and (ii) vehicle speeds are measured in order to improve emission estimates and to take into account the impact of the turbulence generated by moving vehicles on the local dispersion of BC. [ABSTRACT FROM AUTHOR]

Abstract: Ground vibrations due to road traffic constitute a major environmental problem. This paper presents a numerical model for the analysis and prediction of the ground vibrations due to the road traffic. A car model with four degrees of freedom is used for the determination of the load due to the road traffic. The load is then introduced in a 3D finite difference model for the determination of the traffic-induced ground vibrations. The numerical model is validated using field data. Numerical analyses show that both the amplitude and frequency of the traffic-induced vibrations are mainly affected by the vehicle speed, the road unevenness and the vehicle suspension system. Some recommendations are suggested for the reduction of these vibrations. [Copyright &y& Elsevier]

Abstract: Air pollution is a common problem in mega-cities in Asia, resulting in high levels of particulate matter (PM). In this study, 24 h samples of airborne particulate matter (PM2.5 and PM10) was collected for two weeks in urban locations in Kabul and Mazar-e Sharif, Afghanistan. The samples were analyzed for twenty n-alkanes, fifteen polycyclic aromatic hydrocarbons (PAHs) and eighteen oxygenated PAHs (oxy-PAHs). The results were compared to a reference location in Umeå, Sweden. The main objectives were: to characterize the organic fraction in PM2.5, with focus on oxy-PAHs, PAHs and n-alkanes, assess relationships between compound groups, and investigate possible source categories. Mean PM10, levels were 260 μg m−3, and 334 μg m−3 and mean PM2.5 levels were 86 μg/m3and 68 μg m−3 in Kabul and Mazar-e Sharif, respectively. The higher ratio of PM2.5 to PM10 in Kabul than Mazar-e Sharif or Umeå was reflected in the high number of small particles, as collected by a particle counter. Kabul and Mazar-e Sharif had high levels of PAHs and oxy-PAHs compared to Umeå and previously reported data from Western countries. Generally, the highest individual levels of oxy-PAHs were found for ketones (0.27–33 ng m−3), whereas the quinone levels were lower (0.027–3.1 ng m−3). High correlations (r > 0.96) between PAHs and oxy-PAHs were found at both locations. Diagnostics for n-alkanes, such as the carbon preference index, and the most abundant species, C max, and the presence of unresolved complex mixture indicated a higher contribution from coal and petroleum sources in Kabul. Models generated by principal component analysis (PCA) and positive matrix factorization (PMF) both suggested separate sources for lower molecular weight n-alkanes and higher molecular weight n-alkanes. The PAHs and the oxy-PAHs were not separated in either the PCA or the PMF models, indicating that they had similar sources and are perhaps relatively unspecific as source markers. Nevertheless, the PAHs and oxy-PAHs were good markers for bad air quality in the urban locations in Afghanistan in comparison to data from Western countries. Based on the models and diagnostic ratios it is suggested that traffic and combustion of coal and biomass were the dominating sources of the high levels of particle-bound organic compounds. [Copyright &y& Elsevier]

Abstract: Introduction: A common contention is that the construction of highway bypasses negatively impacts the economy of local communities by reducing pass-by traffic for businesses. However, as access to specific business'' account records is limited, this impact is difficult to quantify. Another common contention is that bypasses contribute to a reduction in overall crashes in the community and in the surrounding areas. Even though a large number of bypasses have been constructed in the State of Iowa over the past several years, their actual impact in terms of traffic safety has not been quantified. Objectives: This study seeks answers to the following questions: (a) Are bypasses in Iowa associated with a reduction in crash frequencies and crash rates on the bypassed highway? (b) Do bypasses in Iowa introduce a reduction of overall crash frequencies and rates or do they merely shift crashes from the highways through the communities to the bypasses with no significant overall reduction? Method: We obtained crash information from the Iowa DOT at 19 sites on which a bypass was constructed sometime during the past 23years. We also obtained the same information at six sites used as comparison sites on which no bypasses were constructed at least until 2005. We them employed a Bayesian approach to estimating the association between the construction of the bypass and crash rates, while also accounting for other factors. Results: The construction of bypasses in Iowa is associated with a significant increase in traffic safety both on the main road through town and on the combined main road and bypass roadway. [Copyright &y& Elsevier]