Interplay between ethanol and electric vehicles as low carbon mobility options for passengers in the municipality of São Paulo

The Brazilian cities as well as many of the large urban centers in the world continue to expand, increasing the demand for mobility and transport, while, at the same time, the same cities are investing in greenhouse gas (GHG) mitigation to avoid climate change. Brazil's urbanization rate increased from 26% in 1940 to almost 70% in 1980. During this period, the Brazilian population tripled and the urban population multiplied by seven. In 2010, the transport sector in São Paulo accounted for 71% of the total emissions released by the energy sector. Ethanol has been considered a fuel with less greenhouse gas emissions, when compared with fossil fuels. However, ethanol production would have to double to meet the expected demand. Electric vehicles (EVs) market is expanding around the world, and is also an option to reduce the transport emissions, if powered by clean electricity. To assess whether the adoption of EVs might bring more benefits than the current ethanol, we develop prospective scenarios supported by the Long-range Energy Alternatives Planning (LEAP) simulation tool, taking a bottom-up tank-to-wheel approach to consider the CO₂ emissions of car in São Paulo. The scenario considering a substitution of 25% of gasoline-powered cars by EV in 2030 showed a reduction in energy consumption and CO₂ emissions, around 15% and 26% respectively in that year in comparison with 2015. We discuss the interplay between ethanol and EV, also considering emission coefficients from life cycle analysis conducted in Brazil, and concluded EV will have higher positive impact on climate change mitigation than ethanol.     

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.     

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.     

The effect of a roundabout corridor's design on selecting the optimal crosswalk location: A multi-objective impact analysis

Crosswalks located at mid-block segment between roundabouts can provide a good balance among delay, carbon dioxide (CO₂) emissions, and relative difference between vehicles and pedestrians speed. However, when considering local pollutant criteria, the optimal crosswalk location may be different to that obtained for CO₂. This paper described a multi-objective analysis of pedestrian crosswalk locations, with the objectives of minimizing delay, emissions, and relative difference between vehicles and pedestrians speed. Accounting for the difference between global (e.g., CO₂) and local pollutants (monoxide carbon, nitrogen oxides, and hydrocarbons) was one the main considerations of this work. Vehicle activity along with traffic and pedestrian flows data at six roundabout corridors in Portugal, one in Spain, and one in the United States were collected and extracted. A simulation environment using VISSIM, Vehicle Specific Power, and Surrogate Safety Assessment Model models was used to evaluate traffic operations along the sites. The Fast Non-Dominated Sorting Genetic Algorithm (NSGA-II) was implemented to further search optimal crosswalk locations. The results yielded improvements to both delay and emissions by using site-optimized crosswalks. The findings also revealed that the spacing between intersections widely influenced the optimal crosswalk location along a mid-block section. If the spacing is low (<100 m), the crosswalk location will be approximately in 20%–30% of the spacing length. For spacing values between 140 and 200 m, crosswalks would be located at the midway position. When a specific pollutant criterion was considered, no significant differences were observed among optimal crosswalk data sets.     

Emissions and exposure costs of electric versus conventional vehicles: A case study in Texas

The emissions and human exposure impacts of electric vehicle (EV) adoption, especially in comparison to conventional gasoline- or diesel-powered engines, depend on numerous factors including geography, electricity generation, and fuel mix. Results of any analysis also vary depending on the nature of data collected and their level of aggregation by time or location. This paper combines several approaches to develop a robust estimate of these impacts specific to the state of Texas by considering marginal emissions by time of day, as well as location of vehicle and power plant emissions. The authors estimate health and other external costs of operating an EV in the state at approximately $62 per year, compared with an average of $136 for a passenger car powered by gasoline.     

Transitions to low carbon transport futures: strategic conversations from London and Delhi

Climate change is a global problem and across the world there are major difficulties being experienced in reducing carbon dioxide (CO₂) emissions. The transport sector in particular is finding it difficult to reduce CO₂ emissions. This paper reports on two studies carried out by the authors in London (UK) and Delhi (India). It considers the common objectives for transport CO₂ reduction, but the very different contexts and baselines, potentials for change, and some possible synergies.Different packages of measures are selected and scenarios developed for each context which are consistent with contraction and convergence objectives. CO₂ reduction potentials are modelled and quantified by package and scenario. London is considering deep reductions on current transport CO₂ emission levels; Delhi is seeking to break the huge projected rise in transport CO₂ emissions.The scale of policy intervention required to achieve these goals is huge and there is certainly little public discussion of the magnitude of the changes required. The paper argues for a ‘strategic conversation’ at the city level, using scenario analysis, to discuss the priorities for intervention in delivering low carbon transport futures. A greater focus is required in developing participatory approaches to decision making, alongside network investments, urban planning, low emission vehicles and wider initiatives. Aspirations towards equitable target emissions may assist in setting sufficiently demanding targets. Only then is a wider awareness and ownership of potential carbon efficient transport futures likely to take place.     

A method for the estimation of greenhouse gas emissions based on road geometric design and its application to South Korea

South Korea has the tenth highest greenhouse gas (GHG) emissions worldwide, of which 16% originates from the road sector. Existing estimation methods of road GHG emissions have various limitations, such as low accuracy or the ability to only estimate GHG emissions within a limited area. Therefore, this study aimed to develop a methodology to estimate GHG emissions while considering various geometric designs of roads, including both vertical and horizontal alignment. The developed method is more objective and reliable than existing methodologies that consider only vertical alignment. First, Lamm's theory on travel speed profiles was applied to predict GHG emissions. Then, this study attempted to overcome the limited spatial estimation capacity of existing methods by considering upstream and downstream geometric design parameters simultaneously. Second, this study used the GHG operation mode extracted from the MOtor Vehicle Emission Simulator (MOVES), a modeling system that estimates emissions for mobile sources at the national, county, and project levels for criteria air pollutants, GHGs, and air toxicity. The operation mode includes vehicle type, fuel, and other factors, and is designed to estimate GHG emissions at 1-s intervals. Based on the results of the analysis, the effectiveness of the new method was compared to existing methods using an economic analysis (e.g., cost–benefits from the reduced emissions). This study presents a method for performing sensitive estimations of GHG emissions according to the geometric design of roads, which can be used to collect more accurate data on GHG emissions.     

Fleet deployment, network design and hub location of liner shipping companies

A mixed integer linear programming formulation is proposed for the simultaneous design of network and fleet deployment of a deep-sea liner service provider. The underlying network design problem is based on a 4-index (5-index by considering capacity type) formulation of the hub location problem which are known for their tightness. The demand is elastic in the sense that the service provider can accept any fraction of the origin–destination demand. We then propose a primal decomposition method to solve instances of the problem to optimality. Numerical results confirm superiority of our approach in comparison with a general-purpose mixed integer programming solver.     

Potential performance of urban land use and transport strategies in reducing greenhouse gas emissions: Khon Kaen case study,Thailand

ABSTRACT

Transport activities are a key contributor to greenhouse gas (GHG) emissions, global warming, and climate change. In Thailand, private cars are the second largest generator (after trucks) of GHG emissions from the transport sector. This article presents an analysis and evaluation of the implementation of land use and transport measures for reducing GHG emissions in the road network of the Khon Kaen University (KKU) area in Khon Kaen, Thailand. This research applied a bottom-up method to estimate the baseline GHG emissions for several scenarios by adopting the Clean Development Mechanism 2 (CDM2) and Pollution Control Department (PCD) methods over a 20-year planning horizon. The cleaner technology strategy clearly showed the greatest performance in reducing the GHG emission, followed by land use planning and restriction of private vehicle usage. The public transit improvement strategy illustrated the least GHG emissions reduction. Integrated scenarios clearly illustrated larger potential benefits, more effective than the individual scenarios. For both individual and integrated scenarios, the potential performances of the GHG emissions reduction estimated by the PCD method were greater than those assessed by the CDM2 method.     

The joint replenishment and delivery scheduling of the one-warehouse, n-retailer system

We deal with the joint replenishment and delivery scheduling of the one-warehouse, n-retailer system in this paper. We suggest a more flexible policy for the joint replenishment and delivery scheduling of a warehouse compared with the existing researches. We introduce the mathematical model and two efficient algorithms for the joint replenishment and delivery scheduling of the warehouse. Subsequently, we develop the hybrid genetic algorithm (GA) and compare it with two efficient heuristic algorithms for extensive computational experiments. Further, we show the advantages of our GA in dealing easily with resource restrictions.