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.     

Fuel cycle emissions and life cycle costs of alternative fuel vehicle policy options for the City of Houston municipal fleet

Municipal fleet vehicle purchase decisions provide a direct opportunity for cities to reduce emissions of greenhouse gases (GHG) and air pollutants. However, cities typically lack comprehensive data on total life cycle impacts of various conventional and alternative fueled vehicles (AFV) considered for fleet purchase. The City of Houston, Texas, has been a leader in incorporating hybrid electric (HEV), plug-in hybrid electric (PHEV), and battery electric (BEV) vehicles into its fleet, but has yet to adopt any natural gas-powered light-duty vehicles. The City is considering additional AFV purchases but lacks systematic analysis of emissions and costs. Using City of Houston data, we calculate total fuel cycle GHG and air pollutant emissions of additional conventional gasoline vehicles, HEVs, PHEVs, BEVs, and compressed natural gas (CNG) vehicles to the City's fleet. Analyses are conducted with the Greenhouse Gases, Regulated Emissions, and Energy use in Transportation (GREET) model. Levelized cost per kilometer is calculated for each vehicle option, incorporating initial purchase price minus residual value, plus fuel and maintenance costs. Results show that HEVs can achieve 36% lower GHG emissions with a levelized cost nearly equal to a conventional sedan. BEVs and PHEVs provide further emissions reductions, but at levelized costs 32% and 50% higher than HEVs, respectively. CNG sedans and trucks provide 11% emissions reductions, but at 25% and 63% higher levelized costs, respectively. While the results presented here are specific to conditions and vehicle options currently faced by one city, the methods deployed here are broadly applicable to informing fleet purchase decisions.     

The effect of uncertainty on US transport-related GHG emissions and fuel consumption out to 2050

The future of US transport energy requirements and emissions is uncertain. Transport policy research has explored a number of scenarios to better understand the future characteristics of US light-duty vehicles. Deterministic scenario analysis is, however, unable to identify the impact of uncertainty on the future US vehicle fleet emissions and energy use. Variables determining the future fleet emissions and fuel use are inherently uncertain and thus the shortfall in understanding the impact of uncertainty on the future of US transport needs to be addressed. This paper uses a stochastic technology and fleet assessment model to quantify the uncertainties in US vehicle fleet emissions and fuel use for a realistic yet ambitious pathway which results in about a 50% reduction in fleet GHG emissions in 2050. The results show the probability distribution of fleet emissions, fuel use, and energy consumption over time out to 2050. The expected value for the fleet fuel consumption is about 450 and 350 billion litres of gasoline equivalent with standard deviations of 40 and 80 in 2030 and 2050, respectively. The expected value for the fleet GHG emissions is about 1360 and 850 Mt CO₂ equivalent with standard deviation of 130 and 230 in 2030 and 2050 respectively. The parameters that are major contributors to variations in emissions and fuel consumption are also identified and ranked through the uncertainty analysis. It is further shown that these major contributors change over time, and include parameters such as: vehicle scrappage rate, annual growth of vehicle kilometres travelled in the near term, total vehicle sales, fuel economy of the dominant naturally-aspirated spark ignition vehicles, and percentage of gasoline displaced by cellulosic ethanol. The findings in this paper demonstrate the importance of taking uncertainties into consideration when choosing amongst alternative fuel and emissions reduction pathways, in the light of their possible consequences.     

The effectiveness and costs of speed reductions on emissions from international shipping

Greenhouse gas emissions from international shipping are an increasing concern. The paper evaluates whether vessel speed reduction can be a potentially cost-effective CO₂ mitigation option for ships calling on US ports. By applying a profit-maximizing equation to estimate route-specific, economically-efficient speeds, we explore policy impacts of a fuel tax and a speed reduction mandate on CO₂ emissions. The profit-maximizing function incorporates opportunity costs associated with speed reduction that go unobserved in more traditional marginal abatement cost analyses. We find that a fuel tax of about $150/ton fuel will lead to average speed-related CO₂ reductions of about 20–30%. Moreover, a speed reduction mandate targeted to achieve 20% CO₂ reduction in the container fleet costs between $30 and $200 per ton CO₂ abated, depending on how the fleet responds to a speed reduction mandate.     

Economic costs and environmental impacts of alternative fuel vehicle fleets in local government: An interim assessment of a voluntary ten-year fleet conversion plan

Vehicle fleets are widely viewed by policy makers as attractive first markets for introduction of alternative fuel technologies. Although, it is essential to understand the environmental benefits and economic challenges involved in fleet conversion, the literature provides little understanding of the implementation issues associated with alternative fuel vehicles. This paper examines the cost effectiveness and environmental impact of the conversion of a 180 plus vehicle fleet to alternative fuel vehicle technologies by a public organization at the mid-point of the project implementation. Using multi-year micro data on fuel usage, operational and capital expenditures, mileage and emissions, the paper examines conversion costs and infrastructure investments required, extent of user adoption, and emissions reductions achieved. Results are discussed in terms of their implications for managerial practice in local government fleet agencies and for future research.     

Evolution of the household vehicle fleet: Anticipating fleet composition, PHEV adoption and GHG emissions in Austin, Texas

In today’s world of volatile fuel prices and climate concerns, there is little study on the relationship between vehicle ownership patterns and attitudes toward vehicle cost (including fuel prices and feebates) and vehicle technologies. This work provides new data on ownership decisions and owner preferences under various scenarios, coupled with calibrated models to microsimulate Austin’s personal-fleet evolution.Opinion survey results suggest that most Austinites (63%, population-corrected share) support a feebate policy to favor more fuel efficient vehicles. Top purchase criteria are price, type/class, and fuel economy. Most (56%) respondents also indicated that they would consider purchasing a Plug-in Hybrid Electric Vehicle (PHEV) if it were to cost $6000 more than its conventional, gasoline-powered counterpart. And many respond strongly to signals on the external (health and climate) costs of a vehicle’s emissions, more strongly than they respond to information on fuel cost savings.Twenty five-year simulations of Austin’s household vehicle fleet suggest that, under all scenarios modeled, Austin’s vehicle usage levels (measured in total vehicle miles traveled or VMT) are predicted to increase overall, along with average vehicle ownership levels (both per household and per capita). Under a feebate, HEVs, PHEVs and Smart Cars are estimated to represent 25% of the fleet’s VMT by simulation year 25; this scenario is predicted to raise total regional VMT slightly (just 2.32%, by simulation year 25), relative to the trend scenario, while reducing CO₂ emissions only slightly (by 5.62%, relative to trend). Doubling the trend-case gas price to $5/gallon is simulated to reduce the year-25 vehicle use levels by 24% and CO₂ emissions by 30% (relative to trend).Two- and three-vehicle households are simulated to be the highest adopters of HEVs and PHEVs across all scenarios. The combined share of vans, pickup trucks, sport utility vehicles (SUVs), and cross-over utility vehicles (CUVs) is lowest under the feebate scenario, at 35% (versus 47% in Austin’s current household fleet). Feebate-policy receipts are forecasted to exceed rebates in each simulation year.In the longer term, gas price dynamics, tax incentives, feebates and purchase prices along with new technologies, government-industry partnerships, and more accurate information on range and recharging times (which increase customer confidence in EV technologies) should have added effects on energy dependence and greenhouse gas emissions.     

Just-in-time delivery for green fleets: A feedback control approach

With increasing attention being paid to greenhouse gas (GHG) emissions, the transportation industry has become an important focus of approaches to reduce GHG emissions, especially carbon dioxide equivalent (CO₂e) emissions. In this competitive industry, of course, any new emissions reduction technique must be economically attractive and contribute to good operational performance. In this paper, a continuous-variable feedback control algorithm called GEET (Greening via Energy and Emissions in Transportation) is developed; customer deliveries are assigned to a fleet of vehicles with the objective function of Just-in-Time (JIT) delivery and fuel performance metrics akin to the vehicle routing problem with soft time windows (VRPSTW). GEET simultaneously determines vehicle routing and sets cruising speeds that can be either fixed for the entire trip or varied dynamically based on anticipated performance. Dynamic models for controlling vehicle cruising speed and departure times are proposed, and the impact of cruising speed on JIT performance and fuel performance are evaluated. Allowing GEET to vary cruising speed is found to produce an average of 12.0–16.0% better performance in fuel cost, and −36.0% to +16.0% discrepancy in the overall transportation cost as compared to the Adaptive Large Neighborhood Search (ALNS) heuristic for a set of benchmark problems. GEET offers the advantage of extremely fast computational times, which is a substantial strength, especially in a dynamic transportation environment.     

Well-to-wheel costs,primary energy demand,and greenhouse gas emissions for the production and operation of conventional and alternative vehicles

This study provides a comprehensive comparison of well-to-wheel (WTW) energy demand, WTW GHG emissions, and costs for conventional ICE and alternative passenger car powertrains, including full electric, hybrid, and fuel cell powertrains. Vehicle production, operation, maintenance, and disposal are considered, along with a range of hydrogen production processes, electricity mixes, ICE fuels, and battery types. Results are determined based on a reference vehicle, powertrain efficiencies, life cycle inventory data, and cost estimations. Powertrain performance is measured against a gasoline ICE vehicle. Energy carrier and battery production are found to be the largest contributors to WTW energy demand, GHG emissions, and costs; however, electric powertrain performance is highly sensitive to battery specific energy. ICE and full hybrid vehicles using alternative fuels to gasoline, and fuel cell vehicles using natural gas hydrogen production pathways, are the only powertrains which demonstrate reductions in all three evaluation categories simultaneously (i.e., WTW energy demand, emissions, and costs). Overall, however, WTW emission reductions depend more on the energy carrier production pathway than on the powertrain; hence, alternative energy carriers to gasoline for an ICE-based fleet (including hybrids) should be emphasized from a policy perspective in the short-term. This will ease the transition towards a low-emission fleet in Switzerland.     

Development of two driving cycles for utility vehicles

Driving cycles are used to assess vehicle fuel consumption and pollutant emissions. The premise in this article is that suburban road-work vehicles and airport vehicles operate under particular conditions that are not taken into account by conventional driving cycles. Thus, experimental data were acquired from two pickup trucks representing both vehicle fleets that were equipped with a data logger. Based on experimental data, the suburban road-work vehicle showed a mixed driving behavior of high and low speed with occasional long periods of idling. In the airport environment, however, the driving conditions were restricted to airport grounds but were characterized by many accelerations and few high speeds. Based on these measurements, microtrips were defined and two driving cycles proposed. Fuel consumption and pollutant emissions were then measured for both cycles and compared to the FTP-75 and HWFCT cycles, which revealed a major difference: at least a 31% increase in fuel consumption over FTP-75. This increased fuel consumption translates into higher pollutant emissions. When CO₂ equivalent emissions are taken into account, the proposed cycles show an increase of at least 31% over FTP-75 and illustrate the importance of quantifying fleet speed patterns to assess CO₂ equivalent emissions so that the fleet manager can determine potential gains in energy or increased pollutant emissions.     

Road vehicle emission inventory of a Brazilian metropolitan area and insights for other emerging economies

The vehicle fleet in the Ceará state has grown 180% over the last ten years. The growth of the resulting emissions is unknown in view of the expansion of this fleet in the greater Fortaleza Metropolitan Area (FMA). The largest fleet in the FMA is in the Fortaleza city itself, where flex fuel vehicles predominate (∼30%). Flex fuel motorcycles increased significantly (greater than 800%) between 2010 and 2015. This paper aims to estimate the road vehicle emissions of carbon monoxide (CO), non-methane hydrocarbons (NMHC), aldehydes (RCHO), nitrogen oxides (NO_x), and particulate matter (PM) from the main road vehicle fleets of Fortaleza and its metropolitan area using a macrosimulation, bottom-up method, between 2010 and 2015. The results showed that road vehicle emissions of CO, NMHC and RCHO increased mainly by Otto cycle vehicles increase due to the introduction of flex fuel vehicles; however, the NO_x and PM emissions noticeable reduction is also a result of emission policies that seed the introduction of new technologies. In 2015, more than 70,000 tons of CO (21.2 ton/1000person), 8000 tons of NMHC (2.5 ton/1000person), 290 tons of RCHO (0.09 ton/1000person), 15,000 tons of NO_x (4.4 ton/1000person) and 600 tons of PM (0.2 ton/1000person) were emitted in the region under study. Comparing with other Brazilian regions, FMA emit higher levels of pollutants per inhabitant than the state of São Paulo and the state of Rio de Janeiro but lower levels than Porto Alegre city.     

Impacts of replacement of engine powered vehicles by electric vehicles on energy consumption and CO2 emissions

This paper evaluates the impacts on energy consumption and carbon dioxide (CO₂) emissions from the introduction of electric vehicles into a smart grid, as a case study. The AVL Cruise software was used to simulate two vehicles, one electric and the other engine-powered, both operating under the New European Driving Cycle (NEDC), in order to calculate carbon dioxide (CO₂) emissions, fuel consumption and energy efficiency. Available carbon dioxide data from electric power generation in Brazil were used for comparison with the simulated results. In addition, scenarios of gradual introduction of electric vehicles in a taxi fleet operating with a smart grid system in Sete Lagoas city, MG, Brazil, were made to evaluate their impacts. The results demonstrate that CO₂ emissions from the electric vehicle fleet can be from 10 to 26 times lower than that of the engine-powered vehicle fleet. In addition, the scenarios indicate that even with high factors of CO₂ emissions from energy generation, significant reductions of annual emissions are obtained with the introduction of electric vehicles in the fleet.     

Improvement in the estimation and back-extrapolation of CO2 emissions from the Irish road transport sector using a bottom-up data modelling approach

Road transport is a major source of CO₂ emissions in Ireland and accounts for almost 96% of the total CO₂ emissions from the transport sector. Following the recent adopted UNFCCC reporting guidelines on annual inventories [24/CP.19], this study applied the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (2006 IPCC GLs) tier 3 approach to estimate CO₂ emissions from road transport at the vehicle category level, for the first time in Ireland. For this, disaggregated datasets were prepared based on year of vehicle registration and mileage since registration of the vehicle. Such an approach provided a more realistic national scenario in comparison to the use of average mileage degradation in emission calculations. This investigation comprised a recalculation of previous emissions estimates (1990–2012) and an estimation of CO₂ emissions in 2013 using a previously unavailable level of data disaggregation for vehicle mileage as well as using vehicle class specific data and an improved bottom-up estimation methodology in COPERT. Historic vehicle fleet data were restructured, annual mileage data were estimated in relation to the fleet data and back extrapolated using a regression approach.The results showed that the mileage degradation was not only subject to fuel technology, engine size, and age but also the emissions class and vehicle category. It was also observed that the disaggregated level of data provided a different CO₂ emissions split among the vehicle categories than that of previous estimations which were based on an aggregated level of data. Previous emissions inventories (1990–2012) were shown to have underestimated the share from diesel fuelled passenger cars by more than 56% in 2012. Diesel fuelled passenger cars were also found to account for the majority of CO₂ emissions from road transport activities in Ireland in 2013. The level and trend assessment showed that emissions from Euro-II and Euro-III classed vehicles especially for passenger cars, which have a significant contribution to the total emission in 2013 have caused an increase in fleet level emissions in Ireland. In addition, the results also showed that the emissions share from Light Duty Vehicles and Heavy Duty Vehicles were overestimated by previous investigations. This paper highlights the importance of the resolution of data used in emissions inventory preparation which may impact upon future projections and policy formulation. The findings of this investigation are also discussed in relation their implications for road transport policy, including carbon taxation and future policy options aimed at achieving EU emissions target in 2020.     

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.     

System for assessing Aviation’s Global Emissions (SAGE), Part 2: Uncertainty assessment

This paper focuses on assessing and applying the Federal Aviation Administration’s System for assessing Aviation’s Global Emissions (SAGE), Version 1.5, to evaluate global aircraft fuel consumption and emissions. The model is capable of computing fuel burn and emissions on a flight-by-flight, fleet and global basis. Here, a parametric study was conducted to rank-order the effects that the modeling uncertainties had on estimates of fuel burn and emissions. Statistical methods were applied to analyze both the random and systematic errors of the model. Also, applying the model to a sample policy analysis case allowed an examination of more stringent engine certification standards for mitigating aviation emissions. Uncertainties of the model were carefully accounted for in the fuel burn and emissions scenarios of the policy options. Results show that for some applications, SAGE may be used to resolve small differences in fleet emissions performance. Although the absolute uncertainty in flight-by-flight NO_x predictions from the model are of the order of 40%, results show that it is well within the current capabilities of the model to distinguish between the fleet average NO_x emissions associated with the typical NO_x stringency options considered in policy analyses.     

Recent advances in automotive technology and the cost-effectiveness of fuel economy improvement

The potential for improving the fuel economy of conventional, gasoline-powered automobiles through optimized application of recent technology advances is analyzed. Results are presented at three levels of technical certainty, ranging from technologies already in use to technologies facing technical constraints (such as emissions control problems) which might inhibit widespread use. A fleet-aggregate, engineering-economic analysis is used to estimate a range of U.S. new car fleet average fuel economy levels achievable given roughly 10 years of lead time. Technology cost estimates are compared to fuel savings in order to determine likely cost-effective levels of fuel economy, which are found to range from 39 miles per gallon to 51 miles per gallon depending on technology certainty level. The corresponding estimated increases in average new car price range from $540 to $790 (1993$). Estimated fuel savings payback times average less than 3 years and the cost of conserved energy averages $0.50 per gallon, indicating that these levels of fuel economy improvement are cost-effective over a vehicle lifetime. A vehicle stock turnover model is used to project the reductions in gasoline consumption and associated emissions that would follow if the estimated fuel economy levels are achieved. Potential trade-offs regarding vehicle performance, safety, and emissions are also discussed.     

Potential of low viscosity oils to reduce CO2 emissions and fuel consumption of urban buses fleets

This paper shows the results of a comparative fleet test the main objective of which was to measure the influence of Low Viscosity Oils (LVO) over the fuel consumption and CO₂ emissions of urban buses. To perform this test, 39 urban buses, classified into candidate and reference groups depending on the engine oil viscosity, covered a 60,000 km mileage corresponding to two rounds of standard Oil Drain Interval (ODI). In the same way, for 9 buses of the 39 buses, the effect of differential LVO over fuel consumption and their interaction with engine LVO was assessed during the second ODI.Test results confirm that the use of LVO could reduce fuel consumption, hence CO₂ emissions. However, special attention should be taken prior to its implementation in a fleet, particularly if the vehicles are powered by engines with high mechanical and thermal stresses during vehicle operation because this could lead to friction loss increase, loss of the potential fuel consumption reduction of LVO and, in the worst scenario, higher rates of engine wear.     

The time-dependent pollution-routing problem

The Time-Dependent Pollution-Routing Problem (TDPRP) consists of routing a fleet of vehicles in order to serve a set of customers and determining the speeds on each leg of the routes. The cost function includes emissions and driver costs, taking into account traffic congestion which, at peak periods, significantly restricts vehicle speeds and increases emissions. We describe an integer linear programming formulation of the TDPRP and provide illustrative examples to motivate the problem and give insights about the tradeoffs it involves. We also provide an analytical characterization of the optimal solutions for a single-arc version of the problem, identifying conditions under which it is optimal to wait idly at certain locations in order to avoid congestion and to reduce the cost of emissions. Building on these analytical results we describe a novel departure time and speed optimization algorithm for the cases when the route is fixed. Finally, using benchmark instances, we present results on the computational performance of the proposed formulation and on the speed optimization procedure.     

The potential of turboprops for reducing aviation fuel consumption

To assist in aviation systems planning in the context of fuel price uncertainty and environmental regulation, we take a total logistics cost approach and evaluate three representative aircraft (narrow body, regional jet, and turboprop) for operating and passenger preference costs over a range of fuel prices. Homogenous fleets of each vehicle category are compared for operating and passenger costs over a range of fuel prices and route distances and the minimum cost fleet mix is determined. In general, as fuel prices increase, the turboprop offers a lower operating cost per seat over a wider range of distances when compared with both jet aircraft models. The inclusion of passenger costs along with operating costs decreases the number of fuel price and distance pairs where the turboprop exhibits the lower cost. This analysis shows that the aircraft that exhibits the lowest cost is highly sensitive to fuel prices and passenger costs and points to the important balance between saving fuel and serving passengers.     

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.     

A comparison of technologies for carbon-neutral passenger transport

In this study, the use of energy carriers based on renewable energy sources in battery-powered electric vehicles (BPEVs), fuel-cell electric vehicles (FCEVs), hybrid electric vehicles (HEVs) and internal combustion engine vehicles (ICEVs) is compared regarding energy efficiency, emission and cost. There is the potential to double the primary energy compared with the current level by utilising vehicles with electric drivetrains. There is also major potential to increase the efficiency of conventional ICEVs. The energy and environmental cost of using a passenger car can be reduced by 50% solely by using improved ICEVs instead of ICEVs with current technical standard. All the studied vehicles with alternative powertrains (HEVs, FCEVs, and BPEVs) would have lower energy and environmental costs than the ICEV. The HEVs, FCEVs and BPEVs have, however, higher costs than the future methanol-fuelled ICEV, if the vehicle cost is added to the energy and environmental costs, even if significant cost reductions for key technologies such as fuel cells, batteries and fuel storages are assumed. The high-energy efficiency and low emissions of these vehicles cannot compensate for the high vehicle cost. The study indicates, however, that energy-efficiency improvements, combined with the use of renewable energy, would reduce the cost of CO₂ reduction by 40% compared with a strategy based on fuel substitution only.