Abstract

Regional airports are often located very close to the urban area they serve and the increasing traffic rate that many of them have experienced in the last years has produced several impacts on the communities living close to the airport area, mainly aviation noise. If not properly managed, noise impacts produced by airport operations can cut down significantly the development of airport air traffic with direct effects on the economic and territorial systems. Aeronautical noise has greatly reduced in the last decade, due to aircraft design technological improvements and more severe regulations. However, the noise reduction during a single event does not make the issue of the airport location – and then the whole noise impact – less significant. This paper proposes an assessment process to evaluate the effects of actions adopted to reduce airport noise impacts on populated areas. Both airport-related factors – such as number of take-off; day-evening-night distributions of movements; aircraft type; flying paths – and land-use characteristics have been considered and combined in a density index that synthesizes the impacts of airport noise on the territory. The assessment process has been tested on a real case, the airport of Bologna in Northern Italy. The predicted results, compared with available real data for the test case, are significant and encourage the use of the proposed assessment process as decision support system for the airport management.

Abstract

As urbanization gradually modifies natural ecosystems and affects environmental sustainability, urban spatial planning can be used as a tool to address to Urban Metabolism and meet sustainable development targets. The concentration of people in urban areas makes these increasingly requiring for primary products and services as food and energy, and the fulfilment of such needs result in significant carbon emissions. The inclusion of spatial functions as agriculture and renewables in the urban planning can address to this environmental impact, but would require support-planning tools able to explore new land-use allocation strategies within an integrated urban-rural ecosystem. In this paper, we propose an optimization framework for the planning of low carbon urban-rural ecosystems that integrates transport and land-use planning and cope with urban metabolism, involving urban mobility, food transportation, energy supplies. This framework contributes to the literature as it formulates a network between urban, agricultural, energy, and carbon mitigation land-covers and optimizes the horizontal carbon fluxes within an integrated urban-rural environment. In order to minimize carbon emissions by mobility and resources (i.e. food) transportation, the framework aids identifying trade-offs between accessibility and density over the spatial distribution of resource-generating and resource-consuming land-covers. Proof of concept is provided with a realistic numerical example, propelled by real-world data from an Italian region. The land-use allocation solution makes the exemplifying urban-rural ecosystem behaving as carbon sink due to the established green areas and the configuration of the spatial uses. A sensitivity analysis is finally carried out to assess the impacts of mobility and resources transportation on the spatial urban-rural structure and associated carbon emissions. It comes out that the optimal urban configuration to mitigate carbon emissions from transportation integrates urban and rural uses and guarantees accessibility to several functions as cultivated areas, renewables and green covers, responsible to provide food, energy and air cleaning respectively to dwellers.

Abstract

In this paper, we investigate the impact of travel costs, in particular toll costs, on the residential location choice of households, using a stated choice survey. Within the stated choice experiment, car drivers that frequently face traffic congestion, traded-off several trip-related (including toll costs) and house/location-related factors in their decision where to locate. If we look at the influence of different variables, toll and fuel costs seem to be important. Respondents are more sensitive to travel costs (i.e. toll and fuel costs) than to equally high (monthly) housing costs. Travel time appears to play a less important role, as indicated by a low value of time (VOT). In addition, location-related factors, such as the type of location and the number of bedrooms, turn out to be important factors as well. It can be concluded that respondents generally speaking prefer to pay higher housing costs and accept longer travel times to avoid (high) travel costs. Finally, if we look at the difference in preferences in relation to toll and fuel cost, we can conclude that toll costs are valued more negatively than fuel costs, although the differences are small. (C) 2010 Elsevier Ltd. All rights reserved.

Abstract

Most studies on the link between the built environment and modal choice characterize and model this relationship by objectively measureable characteristics such as density and diversity. Recently, within the debate on residential self-selection, attention has also been paid to the importance of subjective influences such as the individual’s perception of the built environment and his/her residential attitudes and preferences, resulting in models that take account of both the objective and subjective characteristics of the built environment. However, self-selection might occur on other points than residential location as well. Expanding the analysis to also include both objective and subjective characteristics at other model levels (i.e., not only stage of life characteristics but also personal lifestyles; not only car availability but also travel attitudes, not only modal choice but also mode specific attitudes) is the purpose of this paper. To this end, a modal choice model for leisure trips is developed using data on personal lifestyles and attitudes, collected via an Internet survey, and estimated using a path model consisting of a set of simultaneously estimated equations between observed variables. While controlling for subjective lifestyles and attitudes, the effects of the built environment and car availability on modal choice can more correctly be determined and thus insights into self-selection mechanisms can be gained. Moreover, we compared the results of a model with and without these subjective influences. The results show that subjective characteristics at various model levels are important decisive factors of modal choices for leisure travel.