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Modeling methods for the assessment of the ecological impacts of road maintenance sites
Abstract
Road transport is a major source of environmental pollution. Cars and trucks, which are the most common types of vehicles, exhaust a variety of pollutants (e.g., nitrogen oxides and particulate matter) that are detrimental to human health. Research on the ecological impacts of road vehicles has highlighted the importance of reducing pollutant emissions. This chapter aims to investigate the impacts of road maintenance sites on pollution in the surrounding environment, which is a slightly different and interdisciplinary aspect of the problem.
Road pavement and infrastructure (bridges, viaducts, and tunnels) must be maintained for the road network to function properly. Maintenance sites interrupt the normal flow of traffic, which leads to traffic jams, higher travel times, and pollutant emissions.
This chapter explores a variety of approaches to traffic emissions modeling to identify a numerical model capable of determining the ecological impacts of maintenance sites on the surrounding environment. A simple simulation will be conducted to demonstrate the importance of the subject. Research gaps are presented at the end of the chapter to guide future studies.
... Vyas & Varia (2023) studied the impacts of work zones on traffic congestions and related externalities (e.g., pollution). Mehrabani et al. (2021) used some approaches to evaluate vehicle emissions within the limits of a work zone. Sun et al. (2022) proposed a bilevel approach to minimize the drivers travel time and the pollutant emissions, by optimizing the use of the available lanes. ...
Major maintenance interventions on highways (e.g., for the safety improvement of tunnels and viaducts) involve the presence of work zones for extended periods of time and along wide sections of the infrastructure. These interventions lead to supply changes, especially a reduction in capacity, causing a decrease in the performance of the transportation system, which users experience with increased traffic congestion and economic losses in terms of productivity. This paper aims to demonstrate that proper traffic management and work zone planning allow for a significant reduction of such impacts. In relation to traffic management, possible solutions consist of diverting traffic flows onto alternative routes (if possible, using primary roads) or keeping them in the remaining lanes along the work zone. In terms of work zone planning, leverage can be applied, on the one hand, through the design of thework zone layout and maintenance scheme and, on the other, through the duration and scheduling of the interventions. The methodology proposed in this paper is based on traffic simulation models in order to assess different maintenance scenarios under varying demand levels (i.e., during the rush hour and off-peak hours, weekdays and weekends, summer and winter months) and vehicular compositions (i.e., percentage of heavy vehicles), with the goal of identifying the scenario that minimizes the impacts on users. Modelling evidence on a real case study of tunnel maintenance interventions on an Italian highway is reported, discussing the policy implications on the basis of quantitative indicators, such as level of service, duration of delays, length of queues, and economic impacts.
... One of the most critical factors in the transportation planning process is solving the traffic assignment problem (Bamdad Mehrabani et al., 2021). Traffic assignment determines the routes that are used by vehicles based on certain behavioral principles, such as, for example, each vehicle seeks to minimize its own travel time. ...
User equilibrium (UE) and system optimal (SO) are among the essential principles for solving the traffic assignment problem. Many studies have been performed on solving the UE and SO traffic assignment problem; however, the majority of them are either static (which can lead to inaccurate predictions due to long aggregation intervals) or analytical (which is computationally expensive for large-scale networks). Besides, most of the well-known micro/meso traffic simulators, do not provide a SO solution of the traffic assignment problem. To this end, this study proposes a new simulation-based dynamic system optimal (SB-DSO) traffic assignment algorithm for the SUMO simulator, which can be applied on large-scale networks. A new swapping/convergence algorithm, which is based on the logit route choice model, is presented in this study. This swapping algorithm is compared with the Method of Successive Average (MSA) which is very common in the literature. Also, a surrogate model of marginal travel time was implemented in the proposed algorithm, which was tested on real and abstract road networks (both on micro and meso scales). The results indicate that the proposed swapping algorithm has better performance than the classical swapping algorithms (e.g. MSA). Furthermore, a comparison was made between the proposed SB-DSO and the current simulation-based dynamic user equilibrium (SB-DUE) traffic assignment algorithm in SUMO. This proposed algorithm helps researchers to better understand the impacts of vehicles that may follow SO routines in future (e.g., Connected and Autonomous Vehicles (CAVs)).
... The rapid increase in the contribution of technologies in transportation provides the opportunity to reduce some of the traditional transportation problems. One of these technologies is CAVs, which are expected to positively affect various aspects of transportation, including capacity and safety (11)(12)(13)(14)(15). CAV technology has two main features: automation and connectivity. ...
Fundamental diagrams (FDs) present the relationship between flow, speed, and density, and give some valuable information about traffic features such as capacity, congested and uncongested situations, and so forth. On the other hand, high accuracy speed-density models can produce more efficient FDs. Although numerous speed-density models are presented in the literature, there are very few models for connected and autonomous vehicles (CAVs). One of the recent spend-density models that takes into account the penetration rate of CAVs is provided by Lu et al. However, the estimation power of this model has not been tested against other speed-density models, and it has not been applied to high-speed networks such as freeways. Thus, this paper made a comparison between the Lu speed-density model and a well-known speed-density model (Papageorgiou) in freeway and grid networks. Different CAV behaviors (aggressive, normal, and conservative) are evaluated in this comparison. The comparison has been made between two speed-density models using the mean absolute percentage error (MAPE) and a t-test. The MAPE and t-test results show that differences between the two speed-density models are not significant in two case studies and that Lu is a powerful speed-density model to estimate speed compared with a well-known speed-density model. For the sake of comparing the above-mentioned models, this paper investigates the impact of CAVs on capacity based on FDs. The results suggest that the magnitude of the impacts of CAVs on road capacity (capacity increment percentage) which are obtained from two speed-density models are very close to each other. Also, the extent to which CAVs affect road capacity is highly dependent on their behavior.
... This section presents and discusses the findings from the random and fixed-effect estimators. As presented in Table 1.3, Model [1]e [6] show the findings from random-effect estimator while Model [7]e [12] show the findings from the fixed-effect estimator. Considering the argument of this paper, we observe from Table 1.3 that air transport infrastructure significantly increases carbon emissions while rail transportation insignificantly reduces carbon emissions. ...
... This section presents and discusses the findings from the random and fixed-effect estimators. As presented in Table 1.3, Model [1]e [6] show the findings from random-effect estimator while Model [7]e [12] show the findings from the fixed-effect estimator. Considering the argument of this paper, we observe from Table 1.3 that air transport infrastructure significantly increases carbon emissions while rail transportation insignificantly reduces carbon emissions. ...
Nowadays, environmental issues are a significant problem that are growing rapidly and have not been properly addressed. Unsolved problems resulting from environmental pollution indicate people's inability to manage local problems over external issues. Globally, the natural and built environments are under threat, due to climatic disturbances: sudden, destructive heavy rains and repetitive floods due to intense tropical storms. Environmental issues have become more widespread and intense due to increasing industrial and human impacts on the environment. There is a need for an effort to achieve the objective of increasing ecoefficiency in several sectors of the economy envisaged in the national sustainable development strategy. The term sustainability is a key element of the ecological balance. Sustainable development requires a consistent supply of fuels such as hydrogen which, in the long term, is both sustainable and readily available at an affordable price that can be used for every needy work without harming the social impact. For a long time, it has been recognized that resource depletion and environmental pollution are the byproducts of industrial production.
Evaluating road networks’ performance during and after a disruption and/or malfunction is of great importance. The performance of the road networks includes four concepts: reliability, vulnerability, robustness, and resilience. Among these concepts, the concept of resilience, which evaluates the road network’s performance after a disruption/malfunction, is very significant. On the other hand, given that the road network is one of the primary sources of air pollution and plays a crucial role in urban sustainability, the amount of polluted emission should be considered in road network performance (resilience) analysis. The literature presents several measures such as travel time, queue length, recovery time, network’s total cost, etc., to study road network resiliency. A review of previous studies demonstrates that the number of studies that considered environmental aspects in road network resiliency evaluation is scarce. Therefore, in this study, new network resilience measures that consider environmental factors are presented. These new measures show how the amount of polluted emission will change when a disruption occurs in the road network. After introducing and defining these new environmental resiliency measures, the Sioux Falls road network is simulated as the case study in Aimsun. The Sioux Falls road network (based on new resiliency measures) is evaluated when the speed of links (sections) is reduced randomly. The London Emission Model (LEM) is used for estimating the amount of polluted emission.KeywordsRoad network resiliencyUrban sustainabilityPolluted emissionTraffic simulationEnvironmental aspectsAimsun
Tourist areas are one of the most populated parts of cities. Air quality in these spaces is critical as they are more susceptible to the particles emitted by vehicles. The concentration of exhaust emissions around these sensitive locations may cause untreatable health issues for visitors, commuters, and citizens. Heavy-duty vehicles (HVs) are one of the most influential factors creating adverse impacts on air quality. This study proposes a state-of-the-art simulation-based approach to study the relationship between an HV’s speed, its fuel consumption, and its contribution to exhaust emissions in sensitive locations. For this purpose, air pollution and fuel consumption in various scenarios were simulated and compared. The proposed method was applied to one of the most popular tourist areas in Trento (Italy), using VISSIM and EnViVer traffic simulation software packages. The results confirmed the impact of vehicle speed on fuel consumption and the amount of emission. The results showed that a 100-km/h increase in the speed of both light vehicles and HV can increase the NOx and volatile organic compound emissions by approximately 20%. Also, CO emissions and fuel consumption increase by approximately 33% when the HV speed increases from 30 to 50km/h. The emission per seat can be decreased by up to 40% and 27% by 20- and 10-km/h reductions in speed, respectively, together with a 100% increase in the HV percentage. Implementing this proposed method could avoid the unintentional negative impacts of air pollution on susceptible visitors.
Modern Environmental Analysis Techniques for Pollutants presents established environmental analysis methods, rapidly emerging technologies, and potential future research directions. As methods of environmental analysis move toward lower impact, lower cost, miniaturization, automation, and simplicity, new methods emerge and ultimately improve the accuracy of their analytical results. This book gives in-depth, step-by-step descriptions of a variety of techniques, including methods used in sampling, field sample handling, sample preparation, quantification, and statistical evaluation. Modern Environmental Analysis Techniques for Pollutants aims to deliver a comprehensive and easy-to-read text for students and researchers in the environmental analysis arena and to provide essential information to consultants and regulators about analytical and quality control procedures helpful in their evaluation and decision-making procedures. https://www.elsevier.com/books/modern-environmental-analysis-techniques-for-pollutants/mustansar-hussain/978-0-12-816934-6
This paper analyses the relevance of the traffic delay generated during the A-8 Spanish Motorway maintenance activities in order to make recommendations for inclusion within the LCA of roads. Six congestion scenarios combining the level of service of the Motorway and the alternative N-634 route have been evaluated using two software packages: KyUCP (macro-simulation) and Aimsun (micro-simulation), whose results have been transferred into emissions using MOVES. After performing the LCA considering a functional unit of a 1-km lane with an analysis period of 30 years, results show the huge importance of this stage in all the scenarios analysed.
A perfect storm of new technologies and new business models is transforming not only our vehicles, but everything about how we get around, and how we live our lives.
The JRC report “The future of road transport - Implications of automated, connected, low-carbon and shared mobility” looks at some main enablers of the transformation of road transport, such as data governance, infrastructures, communication technologies and cybersecurity, and legislation. It discusses the potential impacts on the economy, employment and skills, energy use and emissions, the sustainability of raw materials, democracy, privacy and social fairness, as well as on the urban context.
It shows how the massive changes on the horizon represent an opportunity to move towards a transport system that is more efficient, safer, less polluting and more accessible to larger parts of society than the current one centred on car ownership. However, new transport technologies, on their own, won't spontaneously make our lives better without upgrading our transport systems and policies to the 21st century. The improvement of governance and the development of innovative mobility solutions will be crucial to ensure that the future of transport is cleaner and more equitable than its car-centred present.
Traffic flow patterns severely impact vehicle carbon emissions. A field test was conducted in this study to obtain fuel consumption and traffic volume data under various traffic flow patterns and to explore the relationship between traffic flow patterns and vehicle carbon emissions. Carbon emission data were obtained via the indirect carbon emission accounting method proposed by the Intergovernmental Panel on Climate Change. Carbon emission prediction models for diesel trucks and gasoline passenger cars were established respectively with volume to capacity ratio as an explanatory variable. The results show that carbon emissions are highest under the congested flow conditions, followed by unstable flow, free flow, and steady flow. The relationship between the volume to capacity ratio and carbon emissions is a cubic curve function. The carbon emissions of trucks and passenger cars with a volume to capacity ratio of 0.4 to 0.5 are relatively small. The proposed carbon emissions models effectively quantify the carbon emissions of vehicles under different traffic flow patterns. The results of this study may provide data to support and a workable reference for expressway operation management and future low-carbon expressway expansion construction projects.
Speed is one of the main functional factors that affect road safety in terms of both collision occurrence and collision severity. Previous studies have shown that several roadside and geometric features affect road safety and operating speed. This paper aims to evaluate the effects of roadside and geometric features on operating speed and collision frequency, simultaneously. For this purpose, the operating speed data of 103 segments along with their accident data and roadside and geometric characteristics were collected. Structural equation modelling (SEM) with latent variables was employed to model operating speed and collision frequency, simultaneously. Two latent variables including “geometric effect” and “roadside effect” were defined in SEM. The first latent variable is the combination of the natural logarithm of the segment length, longitudinal slope, the presence of a 2-meter paved shoulder, and curvature of the segment. The indicators of the second latent variable are the number of accesses and the presence of residential land use. The results show that the latent variable “roadside effect” increases collision frequency by a standard regression weight of 3.455; however, it reduces operating speed by a standard regression weight of –0.385. Also, the latent variable “geometric effect” causes an opposite effect on collision frequency and operating speed by the standard regression weight of –5.313 and 0.730, respectively. Besides, lower operating speed causes a reduction in the collision frequency by the standard regression weight of 7.734. The results of this study can be useful for designers and road safety agencies to improve road safety.
This study tried to clarify the magnitude of CO2 emissions from highway construction and maintenance in China through life cycle assessment (LCA) method. For this, 227 real highway projects constructed from the year 2000 to 2011 in Zhejiang Province, China are classified into six types by two categories of N road (62 projects without grand bridge, great bridge and tunnel) and Y road (165 projects with the same road structures) and three sub-categories of (i) newly constructed road, (ii) replacing pavement road and (iii) full rehabilitated road. Significant influential factors of LCA results were revealed through multivariate linear regression models, combined with data quality assessment and sensitivity analysis. Numerical interval of assessment results indicate that the construction emissions of N highway project are more centralized to no more than 2900 t/lane-km, while Y project have a normal upper boundary of construction CO2 emissions, about 5000 t/lane-km. The contribution of maintenance to CO2 emissions probably could exceed that of newly construction both for Y project and N project. In addition, the pavement replacing and rehabilitation could bring about large amount of CO2 emissions which even match with the CO2 emissions from cumulative traffic volume during highway's life cycle. There are common factors for six categories. Cement and steel are the top largest CO2 emissions contributors and sensitive factors for N road and Y road. The LCA results are not sensitive to the local construction materials but sensitive to the emission factor of diesel used in transportation and on-site construction.
Calculating fuel consumption and emissions is a typical offline analysis step that uses the data previously obtained by simulations or observations. Depending on the ag-gregation level and level of detail, we distinguish several global, macroscopic, and microscopic approaches. The macroscopic modes takes as total vehicle mileage, average speed, traffic density and traffic volume as input .The output are fuel consumption or emissions in kg per meter. For the microscopic models, the inputs are speed and acceleration profiles (as obtained from microscopic simulations or real trajectory data) and the engine speed (as obtained from gear-shift schemes). The output of the model are instantaneous fuel consumption and emission rates (CO2 and others) on a single-vehicle basis.
The Life Cycle Assessment (LCA) is a method which aggregates the environmental impacts associated within the life cycle of a pavement. Incorporation of LCA has been mostly focused on the emissions produced in the construction phase and in its constituents, such as material extraction and manufacturing, hauling of materials, etc. Less emphasis has been given to emissions caused by traffic delays during maintenance operations due to lack of well-defined methodology and unfamiliarity about the magnitude of these emissions. In this study, an approach is proposed to include traffic delay emissions by combining Users Cost approach of Life Cycle Cost Analysis (LCCA) with Motor Vehicle Emissions Simulator (MOVES 2014) developed by the United States Environmental Protection Agency (US EPA). The LCA was performed for four different pavement designs and their Global Warming Potential (GWP) were included in the assessment. The GWP of the four designs with and without considering traffic delay emissions (in carbon dioxide equivalents: CO2e) were 53, 51, 50, and 22 versus 6.1, 4.5, 4.3, and 13 thousand tons per mile, respectively. The differences between the GWP with and without traffic delay emissions suggests that there is a need to include traffic delay emissions in the LCA to better estimate environmental impact.
This paper uses a case study of a UK inter-urban road, to explore the impact of extending the system boundary of road pavement life cycle assessment (LCA) to include increased traffic emissions due to delays during maintenance. Some previous studies have attempted this but have been limited to hypothetical scenarios or simplified traffic modelling, with no validation or sensitivity analysis. In this study, micro-simulation modelling of traffic was used to estimate emissions caused by delays at road works, for several traffic management options. The emissions were compared to those created by the maintenance operation, estimated using an LCA model. In this case study, the extra traffic emissions caused by delays at road works are relatively small, compared to those from the maintenance process, except for hydrocarbon emissions. However, they are generally close to, or above, the materiality threshold recommended in PAS2050 for estimating carbon footprints, and reach 5–10% when traffic flow levels are increased (hypothetically) or when traffic management is imposed outside times of lowest traffic flow. It is recommended, therefore, that emissions due to traffic disruption at road works should be included within the system boundary of road pavement LCA and carbon footprint studies and should be considered in developing guidelines for environmental product declarations of road pavement maintenance products and services.
Objective:
Work zone safety is one of the top priorities for transportation agencies. In recent years, a considerable volume of research has sought to determine work zone crash characteristics and causal factors. Unlike other non-work zone-related safety studies (on both crash frequency and severity), there has not yet been a comprehensive review and assessment of methodological approaches for work zone safety. To address this deficit, this article aims to provide a comprehensive review of the existing extensive research efforts focused on work zone crash-related analysis and modeling, in the hopes of providing researchers and practitioners with a complete overview.
Methods:
Relevant literature published in the last 5 decades was retrieved from the National Work Zone Crash Information Clearinghouse and the Transport Research International Documentation database and other public digital libraries and search engines. Both peer-reviewed publications and research reports were obtained. Each study was carefully reviewed, and those that focused on either work zone crash data analysis or work zone safety modeling were identified. The most relevant studies are specifically examined and discussed in the article.
Results:
The identified studies were carefully synthesized to understand the state of knowledge on work zone safety. Agreement and inconsistency regarding the characteristics of the work zone crashes discussed in the descriptive studies were summarized. Progress and issues about the current practices on work zone crash frequency and severity modeling are also explored and discussed. The challenges facing work zone safety research are then presented.
Conclusions:
The synthesis of the literature suggests that the presence of a work zone is likely to increase the crash rate. Crashes are not uniformly distributed within work zones and rear-end crashes are the most prevalent type of crashes in work zones. There was no across-the-board agreement among numerous papers reviewed on the relationship between work zone crashes and other factors such as time, weather, victim severity, traffic control devices, and facility types. Moreover, both work zone crash frequency and severity models still rely on relatively simple modeling techniques and approaches. In addition, work zone data limitations have caused a number of challenges in analyzing and modeling work zone safety. Additional efforts on data collection, developing a systematic data analysis framework, and using more advanced modeling approaches are suggested as future research tasks.
Even though motor vehicle accidents related to work zones represent a small percentage of the total number of crashes, the phenomenon is significant and work zones can be considered a critical point for the safety of both vehicle occupants and workers. This study analyses the speed of vehicles approaching work zones aiming to understand the drivers’ speed behaviour. This work shows that drivers do not obey the temporary speed limit and that they reduce speeds only when the lane width is reduced, resulting in high deceleration rates. These results should be taken into careful consideration when designing work zone sites.
Traffic congestion frequently occurs during rush hour periods and in work zones, and can account for a significant share of vehicle emissions and air quality impacts. This study estimates vehicle emissions from light- and heavy-duty vehicles (LDVs, HDVs) in work zone and rush hour congestion, which are compared to emissions under free-flow traffic conditions. Field experiments collected second-by-second vehicle speed and acceleration data on typical weekdays along a freeway segment that experienced both rush hour and work zone congestion. The collected data were smoothed and used in the Comprehensive Modal Emissions Model (CMEM) to generate second-by-second emissions. For LDVs and when expressed as g mi−1 vehicle−1, the highest emission rates of hydrocarbons (HC), carbon monoxide (CO) and nitrogen oxide (NOx) occurred during the transitional period when traffic changed from free-flow to congested conditions and vice-versa; the lowest rates occurred during low speed work zone congestion periods. However, the highest fuel consumption rates and the highest carbon dioxide (CO2) emissions occurred under work zone congestion, while the lowest fuel consumption and CO2 emissions occurred with rush hour congestion. On a link or emission density basis (e.g., g mi−1 s−1), rush hour congestion had the highest emission and fuel consumption rates. Results for HDVs differed in that work zone congestion was associated with the highest emissions of HC, CO and CO2, and the highest fuel consumption, while NOx emission rates under the different traffic conditions were similar. On an emission density basis, however, the rush hour congestion again was associated with the highest emissions of CO, NOx and CO2 (but not HC). The differences between congestion and free-flow conditions highlight the importance of accounting for congestion in emission, exposure and health risk evaluations, as well as transportation planning.
Urbanization growth and aging infrastructures necessitate new infrastructure construction projects in congested urban areas. Urban construction projects interrupt the regular on-road vehicle traffic flow that affects air pollution concentration in the adjacent areas. The project schedule, however, is a possible contributor to the air pollution which has been neglected to date. This research proposes a new framework to account for the impact of different urban project schedule alternatives on air pollution emission near the construction zones. The proposed framework uses the capabilities of vehicle traffic simulation to evaluate air pollution emission of different construction schedule alternatives and reduce the resulting emission in urban construction projects. The capability of the proposed framework is verified in a real grade separation case. Pollution concentration shows a potential reduction of up to 41% in sensitive locations. The achieved resulting values represent potential emission reduction of 7.8% for CO2, 8.2% for NOx, and 3.8% for PM10. The achieved results in the case study confirm the impact of the construction schedule on the air pollution emission throughout the project’s construction. It justifies the application of the framework in the congested urban areas. The proposed framework in the research contributes to the sustainable improvement of urban infrastructure projects.
This study aims to demonstrate a new approach for estimating fuel consumption from vehicles circulating on urban roads with different levels of congestion. A microscopic dynamic traffic model (AIMSUN) was coupled with an instantaneous emissions model (CRUISE) and their output was used to refine the average speed model (COPERT) functions. The integrated methodology was applied in an urban corridor in Turin using two validated vehicle models of Euro 5 passenger cars. Three traffic conditions were examined, corresponding to free-flow, normal and congested traffic. New average speed – fuel consumption functions were developed for free and congested traffic, which successfully estimated the differences in fuel consumption when moving from normal to other conditions. The results showed that under congested conditions the fuel consumption can increase by more than 18% in some cases, indicating the significance of incorporating similar congestion algorithms in macro emission models. Moreover, if a more comprehensive method does not exist, the standard COPERT functions could be used to estimate fuel consumption under congested traffic conditions.
This paper investigates the neglected potential of carbon dioxide (CO 2 ) emissions reduction from highway maintenance projects. Conventional assessment (CA) on fuel combustion of off-road equipment during maintenance, and a comprehensive life cycle assessment (LCA) on the materials production, fuel production, traffic delay and maintenance equipment were conducted for four typical maintenance schemes in a real highway project in China, through Microsoft spreadsheet models, VISSIM and CMEM model. The focus of the case study was to understand the magnitude and source of the gap of CO 2 emissions assessment results between LCA and CA. In this study, we also checked scenarios that apply a few mitigation options from several industrial sectors in four typical maintenance schemes to investigate how significant potential for decarbonization of the highway maintenance might be neglected without using LCA. Results suggest that there exists an obvious gap between the total CO 2 emissions per lane per kilometer of CA and that of LCA, and the gap is even up to 22 times of the CA results in this specific case study. Traffic delay caused by the lane closure has the largest contribution to the gap, while the shares of materials production and fuel production match. The scenarios analysis of mitigation strategies associated with the transport sector and other industrial sectors indicates that the LCA model could effectively identify the dominant inputs and CO 2 emissions outputs of individual maintenance process in the complicated transport system, while CA may neglect or underestimate the potential for adopting some mitigation strategies, especially for mitigation options from other industrial sectors.
Despite recent efforts to improve work zone safety, the frequency and severity of crashes at work zones are still considerably high. The effect of work zones on traffic safety can be exacerbated by adverse weather conditions. As an example, a sudden reduction in visibility may intensify the severity of work zone crashes. There is a lack of studies that strive to gain a good understanding of the effect of weather on the severity of work zone crashes. In this study, an Ordered Probit Model was developed to identify factors affecting the severity of work zone crashes in different spatial, temporal, and environmental conditions in Washington state using five-year of work zone-related crashes (2009–2013). The interesting findings of this study showed that weather and lighting conditions are among the most important factors influencing the severity of crashes at work zones. Lack of daylight was found to be a determining factor in increasing the severity of work zone crashes, specifically, during dusk and dawn. It was also found that although drivers have less severe work zone-related crashes in adverse weather conditions, the interactions between adverse weather conditions and other contributing factors might increase the severity of work zone crashes. The results of this study will help traffic engineers to design effective safety countermeasures considering different contributing factors including the weather and lighting conditions in the work zone planning and installation stages to prevent safety deficiencies.
Shifting work zones from daytime to nighttime is a potential solution to air quality issues on roadway with high traffic volume and where it is undesirable to close lanes during peak hours. The expected benefit of such shifting is to reduce total fuel consumption and on-road vehicle emissions. However, the magnitude of emission reductions and air quality impacts has not been examined comprehensively at work zones. The study presented in this paper investigated the traffic-related emission impacts of work zones using an urban freeway case study. A VISSIM test bed combined with the Environmental Protection Agency’s MOVES emission model was used to estimate total emissions assuming daytime and nighttime lane-closure scenarios. Vehicle emissions were estimated using a link-based method and operating mode-based method. The results from both methods demonstrated that nighttime construction has a significant impact on both traffic speeds and vehicle emissions, primarily as a result of reductions in vehicle miles traveled. In addition, a horizontal comparison between the results from the two methods was made to assess the impact of different emission estimation approaches. The outcomes from the comparison highlight the potential importance of the operating mode-based approach for accurately estimate total traffic emission quantities when data or simulations are available.
Traffic interruption by lane closures in construction work zones (CWZ) is unavoidable when road maintenance activities are undertaken. This study evaluated the fuel consumption and greenhouse gas (GHG) emissions generated by on-road vehicles under various CWZ situations for highway maintenance and rehabilitation. The scenario factorials were developed considering traffic volumes, vehicle types, drive cycles, highway categories, and work zone traffic operation plans. Fuel consumption and GHG emissions were selected as the environmental impact indicators and were estimated using the motor vehicle emission simulator (MOVES). For the freeway scenarios, fuel consumption, and GHG emissions increased by 85 percent and 86 percent, respectively, under heavily congested CWZ compared to free flow condition without CWZ. For the multilane (4-or 6-lane) road scenarios, fuel consumption, and GHG emission increased by 83 percent and 84 percent, respectively, under heavily congested CWZ, compared to uncongested traffic condition without CWZ. Mitigating CWZ traffic congestion from heavy (average speed 5 mph) to medium congestion (average speeds 25 mph for a freeway and 15 mph for a multilane road) in the CWZ would reduce fuel consumption and GHG emissions by 40 percent on a freeway and 32 percent on a multilane road. The study results are useful to analyze pavement life cycles with alternative maintenance treatments, lane closure strategies, and construction/traffic management plans.
This study proposes an integrated simulation approach, which consist of a microscopic traffic simulation model, a vehicle dynamics model, and an emission estimation model, in order to estimate emissions based on more reliable vehicle performance measures. The vehicle performance measures such as engine power and engine speed significantly relate to the amount of emissions, and road curvatures and inclinations are the core inputs affecting these vehicle performance measures. Therefore, providing reliable vehicle performance measures reflecting the road geometric attributes is critical for a reliable emission estimation. This study proposes to use the microscopic traffic simulation model for generating vehicle trajectories, which is advantageous in modeling various traffic situations, and the vehicle dynamics model for producing the vehicle performance measures based on the vehicle trajectories. Finally, the outputs from the vehicle dynamics model are fed into the emission estimation model to compute emission measures. This study conducted a case-study using two road sections, one is a hypothesized road section including various curvatures and inclinations with regular variations, and the other is a Kesselberg road section, which is an actual geometry in Bayern, Germany. The emission measures are estimated in these case-study road sections using both an existing simulation approach and the proposed integrated simulation approach. The difference between these two emission estimation approaches is discussed in terms of the emission measures, including fuel consumption, nitrogen oxides, and particulate matters.
Work zones on freeways usually affect the quality of service for road users. Aiming to reduce traffic flow disruptions to a minimum, Hessen Mobil – Road and Traffic Management installed an innovative reversible lane system in a work zone on Autobahn A 3 south-east of Frankfurt, Germany. The section with three lanes and temporary hard shoulder running in both directions carries a high amount of commuter traffic with considerable fluctuations in peak traffic flow direction. During road works, four lanes in the peak direction and three lanes in the non-peak direction could be maintained through the use of a reversible lane system. The paper discusses the effects of the reversible lane system on traffic flow and road safety. Radar measurements revealed a maximum traffic volume of roughly 1500 veh/h on the reversible lane, which is around 25% of the total traffic volume during peak hours. The capacity of the work zone was estimated with the stochastic capacity estimation technique based on models for censored data. Compared with the capacity of the unaffected three-lane carriageway with temporary hard shoulder running, a decrease of the capacity by 14% to 17% was estimated for the four-lane work zone configuration including the reversible lane, depending on the direction. The difference between the capacities in both directions can be explained by the different lane geometries at the respective beginning of the work zone, leading to a higher number of lane changing manoeuvers directly upstream of the lane diverge in one direction. The traffic flow analysis also yielded a considerable impact of the work zone on peak hour traffic demand volumes, which were reduced by approximately 1000 veh/h. Similar to other freeway work zones, the road safety analysis revealed an increase of accident rates during road works. However, based on police accident reports only 10% of the total number of accidents and none of the severe accidents could be linked to particular features of the reversible lane system. Altogether, the investigation shows that a reversible lane system is a useful, safe and accepted instrument of intelligent traffic management for freeway work zones with high fluctuations in peak traffic flow direction. At the analyzed work zone, estimated travel time losses of 400000 veh*h could be saved during two months of road works by the application of the reversible lane compared with a permanent lane reduction in one direction.
There are two broad areas of pollution that pose ongoing negative impacts to the public. These are legacy pollution and ongoing releases. Legacy pollution refers to toxic chemical releases into the environment during a time pre-dating strict environmental enforcement practices. “Standard of Care” is a term of art that is generally defined as the degree of prudence and caution required of an individual who is under a duty of care. Generally, it is thought to concern the degree of caution that a reasonable person should exercise in a given situation so as to avoid causing injury. It is the watchfulness, attention, caution, and prudence that a reasonable person under the same or similar circumstances would exercise. Strict environmental enforcement has made the single most difference in overall improved environmental performance by industry. The fear of fines, penalties, and even imprisonment of owners and operators who violate statutory obligations under pollution control permits have driven industry on the whole to adopt BMPs and to make investments into controls. Finally, good corporate governance includes environmental stewardship as a foundation. From the most general standpoint, Responsible Care means acting in a responsible manner toward public and worker safety, protecting the environment, and respecting the properties and quality of life of others.
Emphasizing sound, cost-effective management rather than emergency repairs, this comprehensive volume offers practical guidelines on evaluating and managing pavements for airports, municipalities, and commercial real estate firms. © 2005 Springer Science+Business Media, LLC. All rights reserved.
The greenhouse gas (GHG) emissions associated with road construction activities are analyzed. The main focus of this analysis is on the vehicle emissions associated with alternative project staging approaches, specifically a full closure of the road during construction, versus an intermittent road closure. The analysis includes the direct and upstream emissions associated with materials, construction equipment, mobilization of resources to the work site, and maintenance activity associated with the project over its lifetime. The analysis is based on one case study of a road project in New Jersey. The assumptions underlying the staging analysis are based on hypothetical approaches. Results provide an assessment of the main sources of project related emissions and the ability to minimize total project emissions by minimizing traffic disruption. In the analysis with a full closure of the road, traffic disruption accounts for 26% of total emissions, while with an intermittent road closure, traffic disruption accounts for only 2% of total emissions. The other main sources are from materials and life-cycle maintenance. The analysis demonstrates the feasibility of minimizing project related GHG emissions during road construction activities.
This paper quantifies the effects of newer, more efficient vehicle technologies, traffic volume changes, incidents and work zones on emissions production from on-road traffic. The effects are studied using microscopic traffic simulation and developed emissions estimation tools that together can capture emissions effects from the operating parameters of vehicles. An emissions estimation tool is used to estimate CO2, CO, CH4, THC, NOx, SOx, PM10 and PM2.5 emissions from on-road traffic. A case study of Montgomery County, Maryland’s I-270-MD-355 corridor, including connecting arterials, was conducted. This indicates that vehicle composition greatly affects the amount of emissions, and significant potential for reaching emissions reduction goals exists through improvements in vehicle mix efficiencies within the traffic composition. Further work zones and traffic incidents reduce the amount of emissions produced due to reduced average speeds, while per vehicle emissions rise over the span of the simulation network and simulation period. Models are also developed to support GHG emissions analyses for other comparable roadways.
As a result of the continuously increasing numbers of motor vehicles in metropolitan areas worldwide, road traffic emission levels have been recognized as a challenge during the planning and management of transportation. Experiments were conducted to collect on-road emission data using portable emission measurement systems in two Chinese cities in order to estimate real traffic emissions and energy consumption levels and to build computational models for operational transport environment projects. In total, dynamic pollutant emissions and fuel consumption levels from dozens of light duty vehicles, primarily from four different vehicle classes, were measured at a second-by-second level. Using the collected data, several microscopic emission models including CMEM, VT-Micro, EMIT, and POLY were evaluated and compared through calibration and validation procedures. Non-linear optimization methods are applied for the calibration of the CMEM and EMIT models. Numerical results show that the models can realize performance levels close to the CMEM model in most cases. The VT-Micro model shows advantages in its unanimous performance and ability to describe low emission profiles while the EMIT model has a clear physics basis and a simple model structure. Both of them can be applied when extensive emission computation is required in estimating environmental impacts resulting from dynamic road traffic.
Life cycle assessment is being accepted by the road industry to measure such key environmental impacts as the energy consumption and carbon footprint of its materials and laying processes. Previous life cycle studies have indicated that the traffic vehicles account for the majority of fuel consumption and emissions from a road. Contractors and road agencies are looking for road maintenance works that have the least overall environmental impact considering both the roadwork itself and the disrupted traffic. We review life cycle assessment studies and describe the development of a model for pavement construction and maintenance, detailing the methodology and data sources. The model is applied to an asphalt pavement rehabilitation project in the UK, and the micro-simulation program VISSIM is used to model the traffic on that road section. The simulation results are fed into a traffic emissions model and emissions from the roadwork and the traffic are compared. The additional fuel consumption and emissions by the traffic during the roadwork are significant. This indicates that traffic management at road maintenance projects should be included in the life cycle assessment analysis of such work.
Urban air quality is generally poor at traffic intersections due to variations in vehicles’ speeds as they approach and leave. This paper examines the effect of traffic, vehicle and road characteristics on vehicular emissions with a view to understand a link between emissions and the most likely influencing and measurable characteristics. It demonstrates the relationships of traffic, vehicle and intersection characteristics with vehicular exhaust emissions and reviews the traffic flow and emission models. Most studies have found that vehicular exhaust emissions near traffic intersections are largely dependent on fleet speed, deceleration speed, queuing time in idle mode with a red signal time, acceleration speed, queue length, traffic-flow rate and ambient conditions. The vehicular composition also affects emissions. These parameters can be quantified and incorporated into the emission models. There is no validated methodology to quantify some non-measurable parameters such as driving behaviour, pedestrian activity, and road conditions
This paper considers the effect of active speed management on traffic-induced emissions. In particular, the traffic emissions caused by acceleration and deceleration of vehicles are modelled based on an instantaneous emission model integrated with a microscopic traffic simulation model. The emission model is based on empirical measurements which relate vehicle emission to the type, the instantaneous speed and acceleration of the vehicle. The traffic model captures the second-by-second speed and acceleration of individual vehicles travelling in a road network based on their individual driving style, the vehicle mechanics, and their interaction with other traffic and with traffic control in the network. The integrated model is applied to test a new technology to actively manage the driving speed of the vehicles in an urban network. Their impacts on vehicle emission in the network are assessed to give an indication of the relative effectiveness of the different technological designs and different levels of driver responses. The results show that, while the speed management has effectively reduced the average speed of the traffic, their impact on vehicle emissions is complex. For the study network, the frequent acceleration and deceleration movements in the network has significantly reduced the effect of the reduced average speed on emission. The net results are that the active speed management has no significant impact on pollutant emissions. The study suggests that the analysis of the environmental impacts of any traffic management and control policies is a complex issue and requires detailed analysis of not only their impact on average speeds but also on other aspects of vehicle operation such as acceleration and deceleration.
Energy consumption and Greenhouse Gas Emission from highway work zone traffic in pavement life cycle assessment
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