An analysis of the greenhouse gas emissions profile of airlines flying the Australian international market

International commercial flights (with the exception of flights between countries in European Union including Iceland, Norway and Liechtenstein) are currently not subject to greenhouse gas emission reduction regulation. To formulate effective and efficiency policy to manage greenhouse gas emissions from air transport, policy makers need to determine the emissions profiles of all airlines currently flying into their country or region. In this paper, we use 2012 data on airlines' aircraft characteristics, passenger load and cargo load (obtained from statistics reported by Australian Government Bureau of Infrastructure, Transport and Regional Economics) to estimate the volume and carbon efficiency on each international route flying to and from Australia. This is the first study to use actual passenger and cargo load data to determine the greenhouse gas (specifically CO₂) efficiency of airlines operating in the Australian international aviation market. Airlines' CO₂ emission profile is dependent on many factors including but not limited to the aircraft used, payload, route taken, weather conditions. Our results reveal that the airlines’ CO₂ emission profile is not only dependent on the aircraft used and the number of passengers but also the amount of cargo on each flight.     

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.     

Uncovering the spatiotemporal patterns of CO2 emissions by taxis based on Individuals' daily travel

Traffic-related carbon dioxide (CO₂) emissions have become a major problem in cities. Especially, the CO₂ emissions induced by taxis account for a high proportion in total CO₂ emissions. The availability of taxi trajectory data presents new opportunities for addressing CO₂ emissions induced by taxis. Few previous studies have analyzed the impact of human trips on CO₂ emissions. This paper investigates trip-related CO₂ emission patterns based on individuals' travel behavior using taxi trajectory data. First, we propose a trip purpose inference method that takes into account the spatiotemporal attractiveness of POIs to divide human trips into different types. Further, we reveal the spatiotemporal patterns of CO₂ emissions from various types of trips, including temporal regularity and periodicity as well as spatial distribution of “black areas”. Finally, comparative analysis of CO₂ emissions for different kinds of trips based on trip behavior is conducted using three variables, namely trip distance, trip duration and trip speed. This study is helpful for us to understand how to make travel and cities more sustainable through modifying people's trip behaviors or taxi trips.     

Assessment of out-of-state truck activity in California

The continued growth of interstate freight trucking brings with it the potential for inaccuracies in official government statistics on trucks’ road use and pollutant emission contributions. State government agency emission estimates for states within the US commonly rely on in-state truck and fuel use records. Consequently, these records can incompletely reflect overall truck activity and emissions by neglecting the trucks that are registered and/or are fueled out of state. An in-person interview survey of 433 heavy-duty truck drivers was conducted at select points of entry into California to better understand the contribution of out-of-state trucks, their fuel use, and their emissions in California. The results indicate that non-California-registered trucks and non-California-diesel fuel make up approximately 30% of Class 8 heavy-duty truck mileage on California roads. Non-California-registered-truck mileage is disproportionately concentrated in four California air basins that have significant air quality issues.     

Cooperation among truck carriers in seaport containerized transportation

Nowadays the majority of goods passing through seaports are transported by road, resulting in a large number of empty movements and high total costs. This paper proposes an optimization model for the cooperative planning of multiple truck carrier operations in a seaport environment for maximizing the total profit derived from their cooperation. A compensation mechanism is introduced to motivate carriers to share their trips. Time windows, trip deadlines and fleet sizes are considered. The planning approach is evaluated using real data sets from the Italian port of Genoa. Numerous scenarios are tested and an extensive computational analysis is reported.     

Factors of electric vehicle adoption: A comparison of conventional and electric car users based on an extended theory of planned behavior

Increasing the share of battery electric vehicles (BEV) in the total car fleet is regarded as a promising way to reduce local car emissions. Based on online surveys in Denmark and Sweden, this study compares BEV users' (n = 673) and conventional vehicle (CV) users' (n = 1794) socio-demographic profiles, attitudinal profiles, and mobility patterns. In line with previous research, BEV users are typically male, highly educated, have high incomes, and often more than one car in their household. Additionally, BEV users perceive less functional barriers toward BEV use and have more positive attitudes and norms than CV users. The different profiles of these user groups suggest a separate analysis of potential factors of BEV adoption in both groups. In regression analyses, CV and BEV users' intention to use/purchase a BEV is modeled based on factors of the Theory of Planned Behavior extended by personal norm, perceived mobility necessities, and BEV experience. For CV users, symbolic attitudes related to BEVs are the most important factor of intention, while perceived functional barriers in terms of driving range are most relevant for BEV users' intention. How BEV users cope with trips of longer distance seems of particular relevance. In multiple car households, we found the percentage of actual BEV usage related to the type of other cars in the household, perceived functional barriers of BEVs as well as (successful) behavioral adaption to longer trips by BEVs. Based on the results, we discuss ways to increase BEV adoption for current users and non-users.     

Expanding the positive utility of travel through weeklong tracking: Within-person and multi-environment variability of ideal travel time

Travel has been found to have a positive utility—often measured as a desire for non-zero travel time. Although past studies have found that desired travel time varies by trip attributes, they often focused on a single trip purpose (e.g., commute) or single time point (e.g., peak period of one day) and rarely captured variation within individuals and across multiple travel environments. To address these limitations, we employed a smartphone-based travel behavior survey of 186 users making 4397 trips in the Washington, DC, and Blacksburg, VA metropolitan areas. For each user, multiple trips were recorded and the user was asked to repeatedly report on the ideal travel time for each trip. We found that desired travel time varied across different trip environmental characteristics and purposes. Ideal travel time was longer for active travel trips, leisure trips, weekend trips, and when the user conducted activities during trips (e.g., talking, using the phone, looking at the landscape) and traveled with companions. Our study suggests the need for more realistic estimation of the value of travel time savings and the need for quantifying the effect of multitasking during travel on people's willingness to reduce travel time. Practitioners should also consider providing better urban infrastructure for pedestrians and bicyclists to fulfill their trips, as their ideal travel times closely match actual travel times.     

Light-duty electric vehicles in the gulf? Techno-economic assessment and policy implications

We investigate the economic and technological potential for adoption of Electric Vehicles (EVs) in Abu Dhabi through a parametric assessment, a public attitude survey, and a diffusion model. Abu Dhabi, similar to fossil-fuel-rich countries in its region, features a car-dependent society and energy subsidies while being situated in hot, desert environment challenging to EVs. We compare conventional vehicles and EVs in the region accounting for the higher use of air-conditioning (AC) in the actual climatic and driving pattern conditions of Abu Dhabi developing an EV AC consumption penalty model. Average annual AC penalty in fuel consumption over normal testing conditions is 16% for conventional vehicles and 25% for EVs based on hourly weather and vehicle utilization patterns. For 250 days per year, the expected EV range is higher than 75% of the nominal value. During the five hottest days of the recorded year, it can drop to 60% but still covering the average daily driving of the majority of users with a single charge with a 25kWh battery. With partial subsidies offered for both fuel and electricity, EV adoption impacts the state in terms of opportunity costs for these fuels in addition to environmental externalities. We calculate the state and user benefits in a parametric analysis dependent on driving distance and battery costs. If the battery cost is $325/kWh, direct and internalized benefits and costs are balanced when the EV is driven 60 km/day. A diffusion scenario of 5% by 2030 results in cumulative net savings of 6.4 million barrels of oil, a reduction of 517.000 tonnes of CO₂, and a cumulative net benefit of $127 million.     

Do rural older adults take fewer trips than their urban counterparts for lack of a ride?

Aging and the presence of one or more illnesses result in limited travel for many adults age 65 and over. Yet, the need to get to essential, social, and non-emergency medical destinations endures. At some point in their life, older adults become dependent on family/friends, or rely on for-profit/not-for-profit transportation services for their mobility needs, while some do not go on certain trips. Researchers have studied out-of-home activity and mobility of older adults using data on trips taken. There is a gap, however, in understanding trips not taken in the older adult population in rural versus urban locations. Our objectives in this paper are: (i) to investigate unmet travel needs of older adults by relying on responses for trips not taken; (ii) to examine how personal abilities, living situation, and socio-demographic factors are associated with trips not taken to various destinations; and (iii) to compare the likelihood of trips not taken due to lack of a ride in urban versus rural locations across the age and income spectrum. Our data come from a phone survey conducted across the province of Alberta, Canada, in 2017–18 (n = 1390). We specify ordinal logistic models where the dependent variable is how often a respondent did not undertake a trip due to not having a ride to various trip destinations. We find that rural seniors are more likely to not take trips compared to older adults in cities, holding all else equal including driving cessation, worsening health, and disability. Rural seniors who live alone or in low-density housing are also more likely to not take trips compared to urban older adults. Household income, however, tempers these location preferences. Our findings suggest that rural older adults can be supported through income transfers, community-based low-cost travel, and moving to higher-density residential locations.     

Decomposing excess commuting: a Monte Carlo simulation approach

Excess or wasteful commuting is measured as the proportion of actual commute that is over minimum (optimal) commute when assuming that people could freely swap their homes and jobs in a city. Studies usually rely on survey data to define actual commute, and measure the optimal commute at an aggregate zonal level by Linear Programming (LP). Travel time from a survey could include reporting errors and respondents might not be representative of the areas they reside; and the derived optimal commute at an aggregate areal level is also subject to the zonal effect. Both may bias the estimate of excess commuting. Based on the 2006–2010 Census for Transportation Planning Package (CTPP) data in Baton Rouge, Louisiana, this research uses a Monte Carlo approach to simulate individual resident workers and individual jobs within census tracts, estimate commute distance and time from journey-to-work trips, and define the optimal commute based on simulated individual locations. Findings indicate that both reporting errors and the use of aggregate zonal data contribute to miscalculation of excess commuting.     

Examining commuting patterns using Floating Car Data and circular statistics: Exploring the use of new methods and visualizations to study travel times

In this paper, we focus on the spatial distribution of travel time differences between car and public transport during peak and off-peak hours using geospatial methods and circular statistics. To that end, we combine two origin-destination matrices: one contains the number of simulated commuting trips and the other contains accurate travel times measured using either Floating Car Data or transit data. The combination of both matrices reveals that differences in travel time during peak and off-peak hours are high for intra-city commuting and low for inter-city commuting.     

Tourism and electricity consumption in 9 European countries: a decomposition analysis approach

ABSTRACT

Tourism is a major economic activity constituting one of the main sectors in economic terms. European countries traditionally play a significant role in the overall international tourism flow. However, while tourism has a noticeable positive impact on economic development, it also contributes to environmental degradation by increasing energy consumption and therefore emissions. This paper analyses the relationships between Hotel and Restaurant electricity consumption and tourism growth in 9 European countries during 2004–2012, for which there is a sufficient amount of data available. A decomposition analysis based on log-mean Divisia index method (LMDI I) is conducted to examine electricity consumption on this sector and their components. Five decomposition factors are considered: energy intensity (EI), physical capital intensity (KI), physical and human capital relationship (KL), human capital intensity (LI) and the tourism factor (T). Results show the evolution of energy consumption related to this sector, identifying the driving forces that have influenced it.     

How do carriers price connecting flights? Evidence from intercontinental flights from Europe

In civil aviation, hub-and-spoke (HS) networks are used by all large carriers. The importance of this system implies that many travelers use connecting flights. Nevertheless, only scarce knowledge is available on price formation of these trips. In this paper, we focus on the fares of connecting intercontinental flights, with one stop and at least one competing direct flight. We develop a simple model of a HS network, with imperfect substitutability between direct and indirect flights and Cournot competition on every route in the network. We test the model empirically, using reported fares for flights from seven European origins, including the five major airports in Europe, to five non-European destinations. We find that the fare of a connecting flight can be expressed as the weighted average of the fare of its direct competitor, the travel times of both flights its costs and the monetary value of the utility attached to the trip. The weight of the direct fare decreases as product diversity increases.     

A comparative study of driving performance in metropolitan regions using large-scale vehicle trajectory data: Implications for sustainable cities

Volatile driving, characterized by hard accelerations and braking, can contribute substantially to higher energy consumption, tailpipe emissions, and crash risks. Drivers’ decisions to maintain speed, accelerate, brake rapidly, or jerk their vehicle are largely constrained by their unique regional and metropolitan contexts. These contexts may be characterized by their geography, roadway structure, traffic management, driving population, etc. This study captures how people generally drive in a region using large-scale vehicle trajectory data, implying how energy is consumed and how emissions are produced in regional transportation systems. Specifically, driving performance in four U.S. metropolitan areas (Los Angeles, San Francisco, Sacramento, and Atlanta) is compared, taking advantage of large-scale behavioral data (78.7 million seconds of speed records), collected by in-vehicle global positioning systems (GPSs) as part of regional surveys. Comparative analysis shows significant regional differences in terms of volatile driving and time spent to accelerate, brake, and jerk the vehicle during daily trips. Correlates of higher volatility are also explored, e.g., battery electric vehicles show low volatility, as expected. This study proposes a novel way to compare regional driving performance by successfully turning GPS driving data into valuable knowledge that can be applied in practice by developing regional driving performance indices. The new indices can also be used to compare regional performance over time and to imply the levels of sustainability of regional transportation systems. This study contributes by proposing a way to extract useful information from large-scale driving data.     

Will the EU-ETS instigate airline network reconfigurations?

Based on the proposal of the European Commission on including the aviation sector into the European Emission Trading Scheme, a route-based analysis is conducted simulating cost and demand implications for selected airlines. For a scenario of €20/tons CO₂, results indicate that the EU-ETS CO₂-based cost increases for the airlines are between €9 and €27 per route and therefore, as an individual factor, are not high enough to instigate major route reconfigurations among European airlines.     

Traffic exposure near the Los Angeles–Long Beach port complex: using GPS-enhanced tracking to assess the implications of unreported travel and locations

Traffic exposure assessments could misclassify the extent and locations of exposure if traditional recall surveys and self-reported travel diaries do not record all participant activities. The Harbor Communities Time Location Study (HCTLS) examines the nature, extent and implications of underreported locations/trips in a case study which used portable Global Positioning Systems (GPS) devices to track the diurnal patterns and traffic exposure of 47 residents of communities near the Los Angeles–Long Beach port complex. Participants were similar to adults nationwide in time spent indoors, in-vehicle, and outdoors, but spent more time indoors at home (78% vs. 66%). Overall, participants did not report nearly half (49%) of the locations and trips identified in GPS-enhanced data on their activity diaries, resulting in about 3 h/day in unreported locations and 0.6 h/day in unreported trips. The probability of a location/trip being underreported was systematically correlated with participant and location/trip characteristics. Self-reported data missed about 50 min of heightened air pollution exposures during the 5 h/day on average participants spent in high-traffic areas and about 30 min during the 4 h/day near truck routes. GPS-enhanced methods provide opportunities to more precisely characterize exposure periods and tools to identify facility, roadway, and land use types of the greatest concern for mitigation efforts.     

Investigations on the distribution of air transport traffic and CO2 emissions within the European Union

This study analyses the structure of air traffic and its distribution among the different countries in the European Union, as well as traffic with an origin or destination in non-EU countries. Data sources are Eurostat statistics and actual flight information from EUROCONTROL. Relevant variables such as the number of flights, passengers or cargo tonnes and production indicators (RPKs) are used together with fuel consumption and CO₂ emissions data. The segmentation of air traffic in terms of distance permits an assessment of air transport competition with surface transport modes.The results show a clear concentration of traffic in the five larger countries (France, Germany, Italy, Spain and UK), in terms of RPKs. In terms of distance the segment between 500 and 1000 km in the EU, has more flights, passengers, RTKs and CO₂ emissions than larger distances. On the environmental side, the distribution of CO₂ emissions within the EU Member States is presented, together with fuel efficiency parameters. In general, a direct relationship between RPKs and CO₂ emissions is observed for all countries and all distance bands. Consideration is given to the uptake of alternative fuels. Segmenting CO₂ emissions per distance band and aircraft type reveals which flights contribute the most the overall EU CO₂ emissions. Finally, projections for future CO₂ emissions are estimated, according to three different air traffic growth and biofuel introduction scenarios.     

Calculating load factors for the transatlantic airline market using supply and demand data – A note on the identification of gaps in the available airline statistics

This paper takes a critical view of the verification of load factors for the direct transatlantic airline market by combining supply and demand-data. The supply-related data originate from the Official Airline Guide, a well-known data source that contains information on scheduled flights. The demand-related data originate from the Marketing Information Data Transfer database, a data set containing information on actual airline bookings. Combining both data sets enables us to calculate the seat occupancy of direct flights between North-West Europe and the US for 2001. Based on the results, we assess the utility of the joint use of these data sources for aviation economic research, and identify various gaps in the available airline statistics.     

Measuring underreporting in accommodation statistics: evidence from Italy

The aim of this paper is to provide a new measure of the underreporting of accommodation statistics in Italian domestic tourism. The analysis employs information from different official surveys. Following the Eurostat recommendations, we compare the Italian trips and holidays surveys and the movements in accommodation establishments, the two major official sources on tourism in Italy and on the activities of persons travelling, respectively. The analysis shows that demand-side estimates exceed accommodation statistics by 16%, on average, over the period 2007–2009 and that the underreporting rate is variable over time. The results highlight the need to explicitly consider this measurement error when analysing the tourism business cycle, forecasting tourism flows and defining tourism policy.     

Estimating social travel demand of senior citizens in the Netherlands

Like many other countries, the Netherlands is experiencing a sharp rise in the ageing population. As age increases, people’s mobility may decrease. However, older people have more leisure time compared to their younger (working) counterparts, and potentially spend more time on social activities. Therefore, this group can possibly increase social travel demand. However, to date, the travel demand for social activities of senior citizens has received only little attention. This paper studies trip-making for social purposes, with a special focus on the demographic ageing factors. Using social activity diary data, models are estimated to predict the number of social trips, the travel distance and mode of transport for social trips. The results indicate that the elderly of today seem to be as mobile as their younger counterparts with respect to the number of social trips. High education and involvement in clubs on average result in more social trips and full time work is found to result in fewer social trips. With regard to trip distance the results show that the average travel distance does not decrease as people get older. Full time work is found to result in longer social trips. Shorter trips were found for people in urban as well as rural areas. Trips for the purpose of visiting or joint activities tend to be longer than average. With regard to transport mode choice the results indicate that older seniors (75+) are less likely to choose the bicycle, relative to driving. No other significant age effects were found. Significant effects were found for gender, household structure, education level, car ownership, having a disability, urban density, distance and the purpose of the social activity.