Biofuel refinery location and supply chain planning under traffic congestion

This research focuses on planning biofuel refinery locations where the total system cost for refinery investment, feedstock and product transportation and public travel is minimized. Shipment routing of both feedstock and product in the biofuel supply chain and the resulting traffic congestion impact are incorporated into the model to decide optimal locations of biofuel refineries. A Lagrangian relaxation based heuristic algorithm is introduced to obtain near-optimum feasible solutions efficiently. To further improve optimality, a branch-and-bound framework (with linear programming relaxation and Lagrangian relaxation bounding procedures) is developed. Numerical experiments with several testing examples demonstrate that the proposed algorithms solve the problem effectively. An empirical Illinois case study and a series of sensitivity analyses are conducted to show the effects of highway congestion on refinery location design and total system costs.     

Estimation of cost and CO2 emissions with a sustainable cross-border supply chain in the automobile industry: A case study of Thailand and neighboring countries

CO₂ emissions are increasing because of the growth in the cross-border supply chain, which is leading the locations of assembly plants and suppliers to spread across a wider area. Given that one passenger vehicle needs more than 20,000 components and parts, the automobile industry exploits the cross-border supply chain. Recently, the free cross-border movement of people, goods, capital, and information has accelerated in Asia. Therefore, a sustainable cross-border supply chain is required to reduce both CO₂ emissions and cost. This study estimates total CO₂ emissions per vehicle including production and transportation processes in Thailand and neighboring countries and the change in CO₂ emissions based on future policy scenarios that consider the automobile market and locational conditions in 2030. The results show that locating production close to the place of consumption and the electricity emissions factors in each country should be considered.     

Towards a global CO2 calculation standard for supply chains: Suggestions for methodological improvements

Improving the efficiency and sustainability of supply chains is a shared aim of the transport industry, its customers, governments as well as industry organisations. To optimize supply chains and for the identification of best practice, standards for their analysis are needed in order to achieve comparable evaluations. This need for an evaluation standard also applies to CO₂ emission calculations. This research focuses on the transportation within supply chains and possible approaches towards a global standard for calculating its CO₂ emissions. In the recent past, several organisations, national and international, have come forward with possible methods, tools and databases for the calculation of CO₂ emissions along supply chains, but almost all of them do not cover the entire transportation chain. Also standards for CO₂ emissions of products and production in general do exist but they do not take the particular requirements of transportation into consideration. Therefore a global standard specifically for transportation could not yet be introduced. The EN 16258 standard is the only international standard for emission calculation of transportation in supply chains. It was therefore analyzed as a possible starting point for a global standardization approach. Analysis shows it too contains gaps and ambiguities which render comparisons of supply chains difficult. These gaps of the EN 16258 are analyzed, followed by suggestions for methodological improvements for their closure. The research concludes with an outlook on next steps needed towards a global CO₂ calculation standard for transportation within supply chains.     

VISSIM/MOVES integration to investigate the effect of major key parameters on CO2 emissions

This paper looks at CO₂ emissions on limited access highways in a microscopic and stochastic environment using an optimal design approach. Estimating vehicle emissions based on second-by-second vehicle operation allows the integration of a microscopic traffic simulation model with the latest US Environmental Protection Agency’s mobile source emissions model to improve accuracy. A factorial experiment on a test bed prototype of the I-4 urban limited access highway corridor located in Orlando, Florida was conducted to identify the optimal settings for CO₂ emissions reduction and to develop a microscopic transportation emission prediction model. An exponentially decaying function towards a limiting value expressed in the freeway capacity is found to correlate with CO₂ emission rates. Moreover, speeds between 55 and 60 mph show emission rate reduction effect while maintaining up to 90% of the freeway’s capacity. The results show that speed has a significant impact on CO₂ emissions when detailed and microscopic analysis of vehicle operations of acceleration and deceleration are considered.     

The two-echelon time-constrained vehicle routing problem in linehaul-delivery systems considering carbon dioxide emissions

Multi-echelon distribution strategy is primarily to alleviate the environmental (e.g., energy consumption and emissions) consequence of logistics operations. Differing from the long-term strategic problems (e.g., the two-echelon vehicle routing problem (2E-VRP), the two-echelon location routing problem (2E-LRP) and the truck and trailer routing problem (TTRP)) that make location decisions in depots or satellites, the paper introduces a short-term tactical problem named the two-echelon time-constrained vehicle routing problem in linehaul-delivery systems (2E-TVRP) considering carbon dioxide (CO₂) emissions. The linehaul level and the delivery level are linked through city distribution centers (CDCs). The 2E-TVRP, which takes CO₂ emissions per ton-kilometer as the objective, has inter-CDC linehaul on the 1st level and delivery from CDCs to satellites on the 2nd level. The Clarke and Wright savings heuristic algorithm (CW) improved by a local search phase is put forward. The case study shows the applicability of the model to real-life problems. The results suggest that the vehicle scheduling provided by the 2E-TVRP is promising to reduce the CO₂ emissions per ton-kilometer of the linehaul-delivery system. Adjusting the central depot location or developing the loaded-semitrailer demand among O-D pairs to eliminate empty-running of tractors will contribute to reduce the CO₂ emission factor.     

Prediction of vehicle CO2 emission and its application to eco-routing navigation

Transportation sector accounts for a large proportion of global greenhouse gas and toxic pollutant emissions. Even though alternative fuel vehicles such as all-electric vehicles will be the best solution in the future, mitigating emissions by existing gasoline vehicles is an alternative countermeasure in the near term. The aim of this study is to predict the vehicle CO₂ emission per kilometer and determine an eco-friendly path that results in minimum CO₂ emissions while satisfying travel time budget. The vehicle CO₂ emission model is derived based on the theory of vehicle dynamics. Particularly, the difficult-to-measure variables are substituted by parameters to be estimated. The model parameters can be estimated by using the current probe vehicle systems. An eco-routing approach combining the weighting method and k-shortest path algorithm is developed to find the optimal path along the Pareto frontier. The vehicle CO₂ emission model and eco-routing approach are validated in a large-scale transportation network in Toyota city, Japan. The relative importance analysis indicates that the average speed has the largest impact on vehicle CO₂ emission. Specifically, the benefit trade-off between CO₂ emission reduction and the travel time buffer is discussed by carrying out sensitivity analysis in a network-wide scale. It is found that the average reduction in CO₂ emissions achieved by the eco-friendly path reaches a maximum of around 11% when the travel time buffer is set to around 10%.     

Evaluating the effects of green port policy: Case study of Kaohsiung harbor in Taiwan

The paper evaluates the effectiveness of strategies designed to reduce these pollutants in port areas, based on a newly developed assessment model to calculate emissions. The case study found that the strategy of reducing the ship’s speed to 12 knots is most effective in cutting fuel consumption and costs, as well as emissions. Adopting an onshore power supply system could reduce CO₂ emission by 57.16% and PM by 39.4%. By adopting the strategies of both reduced speed and cold ironing emissions control, a reduction in emissions of 71% to 91% can be achieved with a 20 nautical mile reduced speed zone. Therefore, the goals of reductions in emissions to improve port areas air quality could be achieved through adopting a green port policy in the future.     

Application of the support vector machine and heuristic k-shortest path algorithm to determine the most eco-friendly path with a travel time constraint

This study aims to determine an eco-friendly path that results in minimum CO₂ emissions while satisfying a specified budget for travel time. First, an aggregated CO₂ emission model for light-duty cars is developed in a link-based level using a support vector machine. Second, a heuristic k-shortest path algorithm is proposed to solve the constrained shortest path problem. Finally, the CO₂ emission model and the proposed eco-routing model are validated in a real-world network. Specifically, the benefit of the trade-off between CO₂ emission reduction and the travel time budget is discussed by carrying out sensitivity analysis on a network-wide scale. A greater spare time budget may enable the eco-routing to search for the most eco-friendly path with higher probability. Compared to the original routes selected by travelers, the eco-friendly routes can save an average of 11% of CO₂ emissions for the trip OD pairs with a straight distance between 6 km and 9 km when the travel time budget is set to 10% above the least travel time. The CO₂ emission can also be reduced to some degree for other OD pairs by using eco-routing. Furthermore, the impact of market penetration of eco-routing users is quantified on the potential benefit for the environment and travel-time saving.     

An epsilon-optimal algorithm considering greenhouse gas emissions for the management of a ship’s bunker fuel

This paper provides an algorithm to minimize the fixed ordering, purchase, and inventory-carrying costs associated with bunker fuel together with ship time costs; and environmental costs associated with greenhouse gas emissions. It determines the optimum ship speed, bunkering ports, and amounts of bunker fuel for a given ship’s route. To solve the problem, we use an epsilon-optimal algorithm by deriving a property. The algorithm is illustrated by applying it to typical sample data obtained and the effects of bunker prices, carbon taxes, and ship time costs on the ship speed are analyzed. The results indicate that the ship speed and CO₂ emissions are highly sensitive to the factors considered.     

The impact of alternative routeing and packaging scenarios on carbon and sulphate emissions in international wine distribution

There is a large body of research related to carbon footprint reduction in supply chains and logistics from a wide range of sectors; however the decarbonisation of freight transport is mostly explored from a single mode perspective and at a domestic/regional level. This paper takes into account a range of alternative transport modes, routes and methods with particular reference to UK wine imports from two regions: northern Italy and Southeast Australia. The research examines supply chain structures, costs and the environmental impact of international wine distribution to the UK. A number of options are evaluated to calculate the carbon footprint and sulphate emissions of alternative route, mode, method of carriage, and packaging combinations. The estimation of CO₂e emissions incorporates three main elements - cargo mass, distance and method of carriage; sulphate emissions are derived from actual ship routes, engine power and operational speeds. The bottling of wine either at source or close to destination is also taken into consideration. The key findings are: there are major differences between the environmental footprint of different routeing and packaging scenarios; the international shipping leg almost always has a much larger footprint than inland transport within the UK except in the hypothetical case of the rail shipments from Italy using flexitanks. With reference to sulphate, the lowest cost scenario among the sea maximizing options is also the sulphate minimising solution.     

An optimization model for bus fleet replacement with budgetary and environmental constraints

ABSTRACT

As maintenance and operation costs increase with usage over time, equipment is replaced when the value of new equipment is more attractive. Some methods have been developed to solve this problem. In the public transport sector, such problems are frequently analyzed by fleet managers and determined by bus age restriction regulations. We propose an Integer Programming model that integrates both budgetary and environmental constraints (CO₂ emissions) which, as far as we know, have not previously been studied in conjunction. The study aims to determine the optimal replacement plan for a fleet of diesel buses of different size, age, maintenance costs and emissions rates, with new (less polluting) diesel buses over a time horizon of 50 years. The results indicate that it is possible to reduce emissions with a low annual budget using an optimal replacement policy.     

Freight Transport Deceleration: Its Possible Contribution to the Decarbonisation of Logistics

The paper challenges the conventional view that the movement of goods through supply chains must continue to accelerate. The compression of freight transit times has been one of the most enduring logistics trends but may not be compatible with governmental climate change policies to cut greenhouse gas emissions by 60–80% by 2050. Opportunities for cutting CO₂ emissions by ‘despeeding' are explored within a freight decarbonisation framework and split into three categories: direct, indirect and consequential. Discussion of the direct carbon savings focuses on the trucking and deep-sea container sectors, where there is clear evidence that slower operation cuts cost, energy and emissions and can be accommodated within current supply chain requirements. Indirect emission reductions could accrue from more localised sourcing and a relaxation of just-in-time (JIT) replenishment. Acceleration of logistical activities other than transport could offset increases in freight transit times, allowing the overall carbon intensity of supply chains to reduce with minimal loss of performance. Consequential deceleration results from other decarbonisation initiatives such as freight modal split and a shift to lower carbon fuels. Having reviewed evidence drawn from a broad range of sources, the paper concludes that freight deceleration is a promising decarbonisation option, but raises a number of important issues that will require new empirical research.     

The effect of complex models of externalities on estimated optimal tolls

Transport externalities such as costs of emissions and accidents are increasingly being used within appraisal and optimisation frameworks alongside the more traditional congestion analysis to set optimal transport policies. Models of externalities and costs of externalities may be implemented by a simple constant cost per vehicle-km approach or by more complex flow and speed dependent approaches. This paper investigates the impact of using both simple and more complex models of CO₂ emissions and cost of accidents on the optimal toll for car use and upon resulting welfare levels. The approach adopted is to use a single link model with a technical approach to the representation of the speed-flow relationship as this reflects common modelling practice. It is shown that using a more complex model of CO₂ emitted increases the optimal toll significantly compared to using a fixed cost approach while reducing CO₂ emitted only marginally. A number of accident models are used and the impact on tolls is shown to depend upon the assumptions made. Where speed effects are included in the accident model, accident costs can increase compared to the no toll equilibrium and so tolls should in this case be reduced compared to the congestion optimal toll. Finally it is shown that the effect of adding variable CO₂ emission models along with a fixed cost per vehicle-km for accidents can increase the optimal toll by 44% while increasing the true welfare gained by only 8%. The results clearly demonstrate that model assumptions for externalities can have a significant impact on the resulting policies and in the case of accidents the policies can be reversed.

Impact of horizontal geometric design of two-lane rural roads on vehicle co2 emissions

In 2014, highway vehicles accounted for 72.8% of all Greenhouse Gases emissions from transportation in Europe. In the United States (US), emissions follow a similar trend. Although many initiatives try to mitigate emissions by focusing on traffic operations, little is known about the relationship between emissions and road design. It is feasible that some designs may increase average flow speed and reduce accelerations, consequently minimizing emissions.This study aims to evaluate the impact of road horizontal alignment on CO₂ emissions produced by passenger cars using a new methodology based on naturalistic data collection. Individual continuous speed profiles were collected from actual drivers along eleven two-lane rural road sections that were divided into 29 homogeneous road segments. The CO₂ emission rate for each homogeneous road segment was estimated as the average of CO₂ emission rates of all vehicles driving, estimated by applying the VT-Micro model.The analysis concluded that CO₂ emission rates increase with the Curvature Change Rate. Smooth road segments normally allowed drivers to reach higher speeds and maintain them with fewer accelerations. Additionally, smother segments required less time to cover the same distance, so emissions per length were lower. It was also observed that low mean speeds produce high CO₂ emission rates and they increase even more on roads with high speed dispersions.Based on this data, several regression models were calibrated for different vehicle types to estimate CO₂ emissions on a specific road segment. These results could be used to incorporate sustainability principles to highway geometric design.     

The impact of depot location,fleet composition and routing on emissions in city logistics

This paper investigates the combined impact of depot location, fleet composition and routing decisions on vehicle emissions in city logistics. We consider a city in which goods need to be delivered from a depot to customers located in nested zones characterized by different speed limits. The objective is to minimize the total depot, vehicle and routing cost, where the latter can be defined with respect to the cost of fuel consumption and CO₂ emissions. A new powerful adaptive large neighborhood search metaheuristic is developed and successfully applied to a large pool of new benchmark instances. Extensive analyses are performed to empirically assess the effect of various problem parameters, such as depot cost and location, customer distribution and heterogeneous vehicles on key performance indicators, including fuel consumption, emissions and operational costs. Several managerial insights are presented.     

Sustainable cold supply chain management under demand uncertainty and carbon tax regulation

Increasing awareness of sustainability in supply chain management has prompted organizations and individuals to consider environmental impacts when managing supply chains. The issues concerning environmental impacts are significant in cold supply chains due to substantial carbon emissions from storage and distribution of temperature-sensitive product. This paper investigates the impact of carbon emissions arising from storage and transportation in the cold supply chain in the presence of carbon tax regulation, and under uncertain demand. A two-stage stochastic programming model is developed to determine optimal replenishment policies and transportation schedules to minimize both operational and emissions costs. A matheuristic algorithm based on the Iterated Local Search (ILS) algorithm and a mixed integer programming is developed to solve the problem in realistic sizes. The performance and robustness of the matheuristic algorithm are analyzed using test instances in various sizes. A real-world case study in Queensland, Australia is used to demonstrate the application of the model. The results highlight that higher emissions price does not always contribute to the efficiency of the cold supply chain system. Furthermore, the analyses indicate that using heterogeneous fleet including light duty and medium duty vehicles can lead to further cost saving and emissions reduction.     

Multi-period planning of closed-loop supply chain with carbon policies under uncertainty

Climate change and greenhouse gases emissions have caused countries to implement various carbon regulatory mechanisms in some industrial sectors around the globe to curb carbon emissions. One effective method to reduce industry environmental footprint is the use of a closed-loop supply chain (CLSC). The decision concerning the design and planning of an optimal network of the CLSC plays a vital role in determining the total carbon footprint across the supply chain and also the total cost. In this context, this research proposes an optimization model for design and planning a multi-period, multi-product CLSC with carbon footprint consideration under two different uncertainties. The demand and returns uncertainties are considered by means of multiple scenarios and uncertainty of carbon emissions due to supply chain related activities are considered by means of bounded box set and solve using robust optimization approach. The model extends further to investigate the impact of different carbon policies such as including strict carbon cap, carbon tax, carbon cap-and-trade, and carbon offset on the supply chain strategic and operational decisions. The model captures trade-offs that exist among supply chain total cost and carbon emissions. Also, the proposed model optimizes both supply chain total cost and carbon emissions across the supply chain activities. The numerical results reveal some insightful observations with respect to CLSC strategic design decisions and carbon emissions under various carbon policies and at the end we highlighted some managerial insights.     

Should subsidies to urban passenger transport be increased? A spatial CGE analysis for a German metropolitan area

In many countries passenger transport is significantly subsidized in a variety of ways for various reasons. The objective of this paper is to examine efficiency, distributional, environmental (CO₂ emissions) and spatial effects of increasing different kinds of passenger transport subsidies discriminating between household types, travel purposes and travel modes. The effects are calculated by applying a numerical spatial general equilibrium approach calibrated to an average German metropolitan area. In extension to most studies focusing on only one kind of subsidy, we compare the effects of different transport subsidies within the same unified framework that allows to account for two features not yet considered simultaneously in studies on transport subsidies: endogenous labor supply and location decisions. Furthermore, congestion, travel mode choice, travel related CO₂ emissions and institutional details regarding the tax system in Germany are taken into account. The results suggest that optimal subsidy levels are either small or even zero. While subsidizing public transport is welfare enhancing, subsidies to urban road traffic reduce aggregate urban welfare. Concerning the latter it is shown that making investments in urban road infrastructure capacity or reducing gasoline taxes may even be harmful to residents using predominantly automobile. In contrast, pure commuting subsidies hardly affect aggregate urban welfare, but distributional effects are substantial. All policies cause suburbanization of city residents and (except for subsidizing public transport) contribute to urban sprawl by raising the spatial imbalance of residences and jobs but the effect is relatively small. In addition, the policies induce a very differentiated pattern regarding distributional effects, benefits of landowners and environmental effects.     

Reducing CO<Subscript>2</Subscript> from cars in the European Union

The European Union (EU) recently adopted CO₂ emissions mandates for new passenger cars, requiring steady reductions to 95 gCO₂/km in 2021. We use a multi-sector computable general equilibrium (CGE) model, which includes a private transportation sector with an empirically-based parameterization of the relationship between income growth and demand for vehicle miles traveled. The model also includes representation of fleet turnover, and opportunities for fuel use and emissions abatement, including representation of electric vehicles. We analyze the impact of the mandates on oil demand, CO₂ emissions, and economic welfare, and compare the results to an emission trading scenario that achieves identical emissions reductions. We find that vehicle emission standards reduce CO₂ emissions from transportation by about 50 MtCO₂ and lower the oil expenditures by about €6 billion, but at a net added cost of €12 billion in 2020. Tightening CO₂ standards further after 2021 would cost the EU economy an additional €24–63 billion in 2025, compared with an emission trading system that achieves the same economy-wide CO₂ reduction. We offer a discussion of the design features for incorporating transport into the emission trading system.     

High-speed rail's potential for the reduction of carbon dioxide emissions from short haul aviation: a longitudinal study of modal substitution from an energy generation and renewable energy perspective

Abstract

This paper quantifies and evaluates, utilising a ‘bottom-up’ approach, the effect on CO₂ emissions of a modal shift from short-haul air travel to high-speed rail (HSR), based on projected passenger movements, between Sydney and Melbourne, Australia during the period 2010–2030. To date, peer-reviewed studies assessing the CO₂ emissions from these competing modes of high-speed transportation have been restricted principally to a cross-sectional assessment, with a Eurocentric bias. This present comparative study seeks to address a gap in the literature by assessing, longitudinally, the CO₂ emissions associated with the proposed operation of HSR against the ‘business-as-usual’ air scenario between Sydney and Melbourne. Under the assumed 50/50 modal shift, and the Australian government's current renewable electricity target, an annual reduction in CO₂ emissions of approximately 14% could be achieved when compared with a ‘business-as-usual’ air scenario. This percentage reduction represents a 62 kt reduction in base year, 2010, and a 114 kt reduction in the final year, 2030. In total, the overall reduction achieved by such a modal shift, under the assumed conditions, during the period 2010–2030, equates to approximately 1.87 Mt of CO₂. Importantly, if the electrical energy supply for HSR operations was further ‘decarbonised’, then it follows that a greater emission reduction would be achieved.