A multi-criteria analysis framework including environmental and health impacts for evaluating traffic calming measures at the road network level

Recent interests in both vehicle emissions and public health have facilitated the development of more eco-friendly transportation systems. This study developed a multi-criteria evaluation framework to evaluate the effectiveness of traffic calming measures (TCMs) from the various perspectives at the road network level; operational efficiency, traffic safety, environmental and health impacts. The proposed methodology employs four-step sequential simulation experiments, including driving, traffic flow, emissions, and air dispersion simulations. The results obtained from these four simulations are used to evaluate the effectiveness in terms of safety and operational efficiency in addition to environmental and health impacts. A multi-criteria value function based on the weights estimated from the analysis of an analytical hierarchy process (AHP) is applied in the evaluation framework. As an application, chicanes and speed humps widely implemented in Korean school zones were evaluated at the road network level. The proposed simulation-based approach is expected to be effectively used for the decision-making process in selecting better alternatives for TCM.     

Life-cycle CO2 emissions and influential factors for asphalt highway construction and maintenance activities in China

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.     

Determinants of collective transport mode choice and its impacts on trip satisfaction in urban tourism

The continuous growth of tourism has important environmental impacts and transports account for a large proportion of the CO₂ emissions generated by tourists. Understanding the motivations and characteristics of collective transport users in contemporary cities may contribute to promote more sustainable forms of tourism. Based on an extensive questionnaire to international tourists in Barcelona, this study employs a multinomial logistic regression to explore the links among visitors' characteristics, motivations, and means of transportation, while an ordinal logistic regression is applied to investigate whether the preference for collective transport has an impact on the satisfaction with the trip. The novelty of our approach is testing the hypothesis that the choice of collective transports is more related to trip motivations (professional, leisure, or personal) than to socio-demographic or personal characteristics of tourists. The results show that professional travelers are more oriented to the use of private cars, but they prefer collective transports when the length of stay is higher and combined with other trip motivations. Also, using collective transports is linked to high satisfaction with the visit for the tourists using this form of transportation. This study puts forward policy implications and suggestions for future research directions, in particular regarding the utilization of non-motorized forms of transportation cities.     

Green accessibility: Estimating the environmental costs of network-time prisms for sustainable transportation planning

Accessibility, or the ease to participate in activities and obtain resources in a given environment, is crucial for evaluating transportation systems. Greater accessibility is often achieved by increasing individuals' potential mobility. However, potential mobility, if realized by motorized modes, can also generate negative environmental impacts such as fossil fuel consumption and greenhouse gas (GHG) emissions. While the negative environmental impacts of greater mobility are acknowledged, there has been a lack of research to validate those impacts using empirical data, especially considering variations in individuals' mobility levels. This paper presents a method for estimating the expected environmental costs of accessibility represented by a network-time prism (NTP). A NTP delimits all accessible locations within a network and the available time for an individual to present at each location given a scheduled trip origin and destination, a time budget and the maximum achievable speeds along network edges. Estimating the expected environmental costs of a NTP involves three steps: (1) semi-Markov techniques to simulate the probabilities to move along network edges at given times; (2) the speed profiles for reachable edges, and (3) a cost function that translates speeds into environmental impacts. We focus on air quality and employ the motor vehicle emission simulator MOVESLite to estimate the CO₂ emissions at both the edge and prism levels. We calibrate and validate the methods for experimental NTPs defined within the Phoenix, AZ, USA road and highway network using vehicles instrumented with GPS-enabled onboard diagnostic devices (OBD). We demonstrate the effectiveness of our method through two scenarios and investigate the impact of changes in mobility levels on the expected CO₂ emissions associated with the experimental NTPs.     

Dynamic linkages between tourism transportation expenditures,carbon dioxide emission,energy consumption and growth factors: evidence from the transition economies

Tourism transport profoundly affects economic growth, energy consumption and carbon dioxide emissions. This study is an attempt to examine the impact of international tourism transportation expenditures, energy demand, foreign direct investment inflows, trade openness and urban population on carbon dioxide emission and per capita income for the panel of 11 transition Economies, over the period of 1995–2013. The results show that per capita income escalates the carbon dioxide emission (CO₂), which deteriorates the natural environment. International tourism receipts and international tourism expenditures for travel items are associated with the intensifying CO₂ emission and per capita income in the region. The study confirmed the energy-led emissions, FDI-led emissions, FDI-led growth, income-led emissions, income-led energy demand, trade-led growth and trade-led energy demand. The causality results further substantiate the the tourism-led growth and FDI hypothesis in the region. Finally, the variance decomposition analysis confirmed the following results, that is, (i) per capita income is the contributor that least influences CO₂ emissions, (ii) urban population influences per capita income and (iii) international tourism transportation expenditures will influence CO₂ emissions and per capita income for the next 10-year period.     

Greenhouse gas emissions from flying can offset the gain from reduced driving in dense urban areas

Numerous studies have illustrated how denser urban forms lead to smaller greenhouse gas (GHG) emissions from passenger transport. Many of these studies have excluded aviation since the association between urban structure and air travel is not as intuitive as it is the case of ground travel. However, several recent studies have concluded that air travel is a significant contributor to the GHGs from passenger transport. Furthermore, even air travel habits depend heavily on lifestyles and socio-economic factors that are related to the urban form. Here we analyse the interactions between urban structure and different transportation modes and their GHG impacts in Finland. The study utilises the data from the Finnish Transportation Agency’s passenger traffic survey from May 2010 to May 2011, which includes over 12 000 people and over 35 000 trips. The survey is based on one-day travel diaries and also includes additional data on long-distance trips from a longer period. Methodologically, the study takes a traveller’s perspective to assess the GHG emissions from passenger transport. We found that (1) air travel breaks the pattern where GHG emissions decrease with increasing density of urban structures, and (2) in the metropolitan region there is a clear trade-off between car-ownership and air travel in the middle income class. The main policy implication of our study is that air travel must be included in GHG assessments and mitigation strategies targeting travel behaviour. In dense urban regions, the emissions of air travel have the potential to offset the gain from reduced private driving.     

Modeling different penetration rates of eco-driving in urban areas: Impacts on traffic flow and emissions

Climate change and air quality are two main environmental challenges in metropolitan areas. As road transportation is one of the main contributors, public administrations are facing these problems with a number of complementary policy measures: shift to cleaner modes, new fuels and vehicle technologies, demand management, and the use of information and communication technologies (ICT) applied to transportation. Eco-driving is one of the measures that present large fuel savings at individual level. Although these savings are well documented in the literature, few studies focus on how eco-drivers driving patterns affect the surrounding vehicles and the traffic in general, and more particularly what would be the impact when the number of eco-drivers grows. Using a traffic microsimulation tool, four models in urban context have been built, corresponding to the different types of urban roads. Both the base-case and the parameters setting to simulate eco-driving have been calibrated with real data collected through floating vehicles performing the trips with normal and eco behaviors. In total, 72 scenarios were simulated, varying the type of road, traffic demand, and the percentage of eco-drivers. Then, the CO₂ and NO_x emissions have been estimated through a microscopic emission model. The results show that in scenarios with low or medium demand levels and increasing number of eco-drivers, the effects are positive in terms of emissions. On the other side, with high percentage of eco-drivers and high traffic demand, the emissions rise. Higher headways and smooth acceleration and decelerations increase congestion, producing higher emissions globally.     

Spatial-modal scenarios of greenhouse gas emissions from commuting in Hong Kong

Transportation is a major source of greenhouse gas emissions in cities. Multiple strategies including green technologies, transport management, urban planning and behavior changes are required to mitigate transport emissions. This paper aims to introduce an analytical framework to investigate the impacts of different spatial-modal strategies on reducing commuting emissions. Based on the optimization approach of excess commuting, the proposed framework incorporates the minimum, maximum and random (unpredictable) travel outcomes to inform planning of an urban form embedded with fewer emissions. This analytical framework is applied to Hong Kong to estimate the emissions ranges (the minimum and maximum amounts) under 42 spatial-modal scenarios - a combination of six spatial strategies (status quo, monocentric, highly polycentric, moderately polycentric, dual-centric and tri-centric) and seven modal strategies (status quo, pro-rail (high), pro-rail (moderate), pro-bus (high), pro-bus (moderate), pro-car (high) and pro-car (moderate)). The findings illustrate the emissions impacts if Hong Kong is further developed following a job concentration or decentralization principle. It also indicates that if Hong Kong is reconstructed to be a city with multiple CBDs, a dual-centric strategy is desirable because both minimum and maximum commuting are shorter than that of a tri-centric strategy. Moreover, the modal strategy to actively promote rail usage shows more impacts on emissions reduction and car usage should be maintained at the current level. If commuter's travl is less predictable, the high rail usage under a dual-centric city form is a more sustainable spatial-modal strategy. The proposed analytical framework of city's commuting emissions affected by structural and modal changes is transferrable to other places and could offer planners different benchmarks of travel pattern to substantiate their sustainable city planning vision.     

Probabilistic assessment of fleet-level noise impacts of projected technology improvements

Demand projections for civil aviation have forecast increases in operations in future decades. Increases in demand are beneficial to the growth and advancement of the aviation industry, but also come with the threat of significant increase in environmental impacts. In response, the industry is focusing on programs to develop technologies for reductions in fuel burn, NO_x emissions, and noise. While aircraft-level impacts are an obvious metric of success, it is difficult to make informed robust technology investment decisions with respect to noise without understanding the fleet-level impacts. Fleet-level predictions of noise for technology explorations are especially complicated because it is computationally expensive, highly combinatorial, and airport-specific. Recently, rapid automated airport noise models have been developed, which can be simulated using Design of Experiments (DOE). The results of these simulations are used to generate surrogate models for airport noise contour area, which can be summed to yield a fleet-level impact. These models make use of simplifying assumptions to provide estimates of airport-level noise that are substantially cheaper to compute. They can be used to perform parametric trade-off analyses in conjunction with the equivalency assumption. Equivalency asserts that environmental impacts of a technology infused aircraft can be represented by scaled operations of the baseline aircraft in the same class. This simple assumption allows for the modeling of technology and market penetration factors under the same units: operations. This research uses surrogate models in conjunction with the equivalency assumption to examine two potential technology scenarios in a target forecast year, simulating technology and market performance factors to identify vehicle classes that could have the greatest impact in reducing contour area. Results show that technology and market performance of future notional Small Single Aisle and Large Single Aisle vehicle aircraft have the highest positive correlations with potential reductions in contour area.     

Comparing the impacts of local land use and urban spatial structure on household VMT and GHG emissions

To highlight the role of sustainable urban spatial structure in reducing household vehicle miles traveled (VMT) and CO₂ emissions, this empirical study of the 121 largest urban areas (UAs) in the U.S. compares the effects of local land use and UA scale spatial structure in a multilevel analysis framework. The results show that centralized population and mezzo scale jobs-housing balance as well as higher UA population density can significantly reduce VMT and CO₂ emissions. The combined effects of all UA level variables, including population-weighted density (PWD), are found to be on par with the elasticity of VMT with regard to a census tract level compactness index. Further, we find that urban spatial structure moderates local urban form effects on travel behavior. For example, while 10% more compact census tracts are associated with 5% fewer VMT in UAs with the sample average PWD, such as St. Louis and Pittsburgh, this estimated local effect increases to 7.5% and 10% in UAs where PWD is as high as in Chicago and New York, respectively. The findings of this study strongly support policy programs that aim to boost “articulated densities” in the urban region and call for stronger institutional frameworks for regional planning.     

Assessment of transport emissions impact and the associated social cost for Chengdu,China

Chengdu, the capital city of Sichuan province, is the fourth biggest city in China with over 15 million residents and 3.4 million vehicles. In Chengdu, transport and other mobile sources accounted for over 27% of the city's PM_2.5 emissions (CDEPB, 2016), posing negative impacts on public health, local environment, and the climate. This study estimated impacts from transport-related emissions (CO₂, CH₄, N₂O, PM₁₀, PM_2.5, NO_X, SO_X, CO, and HC) and evaluated the associated social cost for Chengdu from 2005 to 2013. The study also assessed the city's transport performance in terms of its eco-efficiency with the socioeconomic and environmental concerns. The activity-based methodology was adopted to produce the emission inventories, while utilizing meta-analysis and localizing the emission social cost factors based on Chengdu's economic and demographic reality to support social cost assessment. The study marks the first attempt in literature to evaluate Chengdu's transport emission social cost. The following were observed in the study: (i) in 2013, the social cost of all transport emissions in Chengdu was around US$3 billion, with the lowest estimate of US$449 million and the highest estimate of US$4.7 billion; (ii) trucks, private cars, and motorcycles were the major contributors, while NO_X, PM_2.5, and CO were the key pollutants to public health; (iii) if GHGs (CO₂, CH₄, and N₂O) were excluded, the upper range of social cost of transport air pollutants would be from US$2.4 billion to US$4.1 billion, or 1.6%–2.8% of the Chengdu's GDP.     

Including aviation emissions in the EU ETS: Much ado about nothing? A review

The European Community, motivated by the rapid growth of the aviation industry and related impacts on climate change, has decided to include aviation in the European Emissions Trading Scheme (EU ETS). Mitigation policies such as the EU ETS are considered to be necessary in order to change travel behaviour and induce operational and technological changes in the aviation industry that will result in lower environmental impacts. This paper reviews the available impact assessments of the proposed emissions trading scheme for airlines published between 2005 and 2009. It analyses the methods used and finds that the models used are often over-simplified, omitting important variables or that the reliability and robustness of the modelling results are reduced by linking models that are based on different assumptions. The paper also summarises the possible environmental (CO₂ emissions) and economic (air fares, demand for airline services, supply of airline services, competitiveness, GDP, carbon price) impacts in the studies reviewed for the year 2020. Overall, the effects are found to be small: for example, CO₂ emissions are expected to decline by a maximum of 3.8% and the maximum impact on GDP in the EU was found to be ?0.002%. The reasons for these insignificant impacts are analysed in this paper; it is also found that there are some positive aspects of including aviation in the EU ETS.     

Hinterland operations of sea ports do matter: Dry port usage effects on transportation costs and CO2 emissions

Decreasing carbon dioxide (CO₂) emissions is one of the most important tasks for the society in the 21st century. One possibility to decrease emissions originating from transportation is to utilize more rails instead of relying simply on road transportation. In the dry port concept an inland intermodal terminal is connected to a sea port using railways. This study analyzes impacts of dry ports in a Finnish context. We compare two different configurations: In the first one shippers drive directly to a sea port, while in the second one they use dry ports. The systems are evaluated by using discrete-event simulation. In the systems we are interested in two issues: (1) Level of CO₂ emissions, and (2) Costs to transport the goods in different configurations. We use different scenarios for future energy prices and estimate both the costs and CO₂ emission development in these scenarios. We also compare the results to a situation, where emissions are minimized instead of costs. Implications on larger scale are also discussed, for example in the Baltic Sea and North Sea area, where strict sulfur emission restrictions are seen to harm sea transport and increase concentration on small number of sea ports.     

Ex-post environmental and traffic assessment of a speed reduction strategy in Madrid's inner ring-road

Since urban traffic is a major source of CO₂ and NO_x emissions, cities play a key role averting climate change and combating air pollution. Most researchers agree on the need of designing comprehensive mitigation strategies instead of applying isolated measures. Nevertheless, it is important to understand the specific impact and scope of each measure to look for the most effective synergies among them. In 2004, the Madrid City Council launched a plan to re-design its inner ring-road to move traffic out of the city centre. For safety reasons the planned speed limit for the full-renovated South-West section was finally reduced from 90 km/h to 70 km/h. Besides contributing to traffic safety, this strategy could also be seen as positive to the environment due to the associated reduced fuel consumption and lower emissions. However, lower speed limits have lower rates of community acceptance due to its impact on average travel times at the individual level. This paper conducts an ex-post evaluation of this speed reduction strategy to explore its environmental and traffic performance impacts. The results support the thesis that, in this velocity range, lower speed limits present important opportunities for reducing GHG and air pollution in the section affected by the measure, without substantially altering traffic performance. The implementation of the new speed limit policy produces a 14.4% and 16.4% reduction in CO₂ and NO_x emissions respectively, while global travel time remains virtually constant and the saturation rate decreases slightly. Besides, this cost-effective measure reveals great potential to reduce air pollution in highly populated urban areas located next to urban highways. This work provides local policy makers and city managers with useful insights regarding potential co-benefits of traffic optimization and speed reduction management to reduce mobile source emissions in urban environments.     

Major environmental impacts of European tourist transport

By merging European passenger transport demand data with international tourism data, a new data model was created, giving insight in the environmental impacts of tourism transport between the places of residence of European Union citizens and their tourist destinations. Analysis with this data model shows that, of the environmental impacts considered (climate change, air quality, noise and nature/landscape), climate change generates more than half of the externalities of tourist transport. Policies with the objective of reducing the external cost of European tourism should focus on measures reducing the impacts of tourist air transportation and intercontinental tourism.     

Exploring the spatial impacts of human activities on urban traffic crashes using multi-source big data

Traffic crashes are geographical events, and their spatial patterns are strongly linked to the regional characteristics of road network, sociodemography, and human activities. Different human activities may have different impacts on traffic exposures, traffic conflicts and speeds in different transportation geographic areas, and accordingly generate different traffic safety outcomes. Most previous researches have concentrated on exploring the impacts of various road network attributes and sociodemographic characteristics on crash occurrence. However, the spatial impacts of human activities on traffic crashes are unclear. To fill this gap, this study attempts to investigate how human activities contribute to the spatial pattern of the traffic crashes in urban areas by leveraging multi-source big data. Three kinds of big data sources are used to collect human activities from the New York City. Then, all the collected data are aggregated into regional level (ZIP Code Tabulation Areas). Geographically Weighted Poisson Regression (GWPR) method is applied to identify the relationship between various influencing factors and regional crash frequency. The results reveal that human activity variables from multi-source big data significantly affect the spatial pattern of traffic crashes, which may bring new insights for roadway safety analyses. Comparative analyses are further performed for comparing the GWPR models which consider human activity variables from different big data sources. The results of comparative analyses suggest that multiple big data sources could complement with each other in the coverage of spatial areas and user groups, thereby improving the performance of zone-level crash models and fully unveiling the spatial impacts of human activities on traffic crashes in urban areas. The results of this study could help transportation authorities better identify high-risky regions and develop proactive countermeasures to effectively reduce crashes in these regions.     

Carbon dioxide emissions and inland container transport in Taiwan

The aim of this study is to estimate the carbon dioxide (CO₂) emissions from inland container transport during the time period of 1998-2008 and predicts the trend of these emissions. The analyses show that the CO₂ emission from inland container transport in 1992 reached 1.03 million tonnes, and the figure drastically increased by 89.3% to 1.95 million tonnes in 2008. Using a multiple regression model, gross domestic product (GDP) and oil price are found to be the key drivers for CO₂ emission. The CO₂ mitigation strategies are discussed in the policy suggestions given that Taiwan is warming at twice global average rate.     

The impact of metropolitan,county, and local land use on driving emissions in US metropolitan areas: Mediator effects of vehicle travel characteristics

Many municipalities in the U.S. pursue compact development to reduce greenhouse gas (GHG) emissions from driving. Despite the efforts, however, recent studies suggest that some land use strategies such as densification and mixed-use development may result in slower vehicle movements, and consequently generate more driving emissions. Since vehicle miles of travel (VMT) is only a proxy and not an exact measure of emissions, reduction in VMT may not lead to a proportional reduction in transportation GHG emissions. Aside from local land use efforts, regional factors also influence vehicle travel and associated emissions.This study investigates the relationship between land use, vehicle travel, and driving emissions in the selected U.S. metropolitan areas at multiple geographic levels. The study employed structural equation modeling (SEM) techniques to examine how land use influences vehicle travel characteristics and associated emissions. The main data sources for the analyses include the 2009 National Household Travel Survey (NHTS) add-on samples and the Smart Location Database (SLD) from the U.S. Environmental Protection Agency (EPA). The study results show that VMT reduction and the associated environmental benefit do not show a one-on-one relationship due to the emissions penalty of lowered vehicle operating speed. Vehicle travel and associated emissions are not only influenced by local urban form factors but also affected by the greater geographical context.     

Assessing cumulative environmental effects from major public transport projects

The conventional assessment of proposed major UK transport schemes has not served to highlight well the induced and interacting nature of environmental impacts. This article identifies links between Strategic Environmental Assessment (SEA) and Environmental Impact Assessment (EIA), using the Cross River Tram in London as an illustrative case study. From a literature review and local authority interviews, a framework and recommendations for the assessment of major transport projects are set out. For transport projects where environmental and land-use impacts are likely, it is suggested that Cumulative Effects Assessment (CEA) has the potential to make a strong positive contribution to the assessment of transport projects for sustainable urban development.     

Exploring multiple eco-routing guidance strategies in a commuting corridor

The introduction of eco-routing systems has been suggested as a promising strategy to reduce carbon dioxide emissions and criteria pollutants. The objective of this study is to scrutinize the impacts of an eco-routing guidance system on emissions through the use of a case study in a commuting corridor. This research aims at assessing the potential environmental benefits in terms of different pollutant emissions. Simultaneously, it addresses the extent of variations in system travel time (S_TT) that each eco-routing strategy implies. The methodology consists of three distinct phases. The first phase corresponds to the adjustment of a microsimulation platform of traffic and emissions with empirical data previously collected. Second, to volume-emission-functions (VEF), developed based on the integrated modeling structure. Final, to different scenarios of traffic flow optimization performed at the network level based on a simplified assignment procedure. The results show that if the traffic assignment is performed with the objective to minimize overall impacts, then the total system environmental damage costs can be reduced up to 9% with marginal oscillations in total S_TT. However, if drivers are advised based on their own emissions minimization, total system emissions may be higher than under the standard user equilibrium flow pattern. Specifically, environmentally friendly navigation algorithms focused on individual goals may tend to divert traffic to roads with less capacity affecting the performance of the remaining traffic. This case study brings new insights about the difficulties and potentials of implementing such systems.