Silvio Nocera

A Joint Probability Density Function for Reducing the Uncertainty of Marginal Social Cost of Carbon Evaluation in Transport Planning

This chapter aims at defining a fair value for the Marginal Social Cost of Carbon (MSCC) to be used within transport planning, briefly discussing how it is influenced by economic and scientific uncertainty, with the scope of helping researchers, stakeholders and decision makers to choose among the current range of values of four orders of magnitude provided from the scientific literature. The method here proposed estimates a joint probability density function for MSCC using a database of almost 600 available estimates, and then defines a subsample of 80 to be used for the evaluation of transport planning policies and projects, so that the variability of MSCC decreases significantly to a single order of magnitude.

Transport Policy: Social Media and User-Generated Content in a Changing Information Paradigm

Rapid and recent developments in social media networks are providing a vision amongst transport suppliers, governments and academia of ‘next-generation’ information channels. This chapter identifies the main requirements for a social media information harvesting methodology in the transport context and highlights the challenges involved. Three questions are addressed concerning (1) The ways in which social media data can be used alongside or potentially instead of current transport data sources, (2) The technical challenges in text mining social media that create difficulties in generating high quality data for the transport sector and finally, (3) Whether there are wider institutional barriers in harnessing the potential of social media data for the transport sector. The chapter demonstrates that information harvested from social media can complement, enrich (or even replace) traditional data collection. Whilst further research is needed to develop automatic or semi-automatic methodologies for harvesting and analysing transport-related social media information, new skills are also needed in the sector to maximise the benefits of this new information source.

A use-chain model to deal with uncertainties. A focus on GHG emission inventories

ABSTRACT The measurements necessary to estimate GHG emission inventories create uncertainty. Currently emission inventories are built on statistical data, parameters and some “other information.” Investigating the role of the latter has driven this analysis, since it has proven to be a key concept in understanding and reducing uncertainty. This article proposes a use-chain model to guide researchers in choosing the appropriate available method to deal with uncertainty. The model involves three main parts: data production, data analysis and data use. The findings suggest, first, that statistical techniques, although crucial, do not represent the only possible way to reduce uncertainty; and, second, that the appropriate way to deal with uncertainty depends on whether one is dealing with data production or data analysis or data use, each characterized by a different degree of specificity and by a different influence of the surrounding context.

The impacts of climate change on tourist mobility in mountain areas

ABSTRACT This study investigates the effects of climate change on tourist mobility in mountain areas, distinguishing between infrastructure, transport operation and travel demand. We examine change in tourist travel demand by proposing a two-step approach to forecast its future development. A multi-origin, multi-destination model for tourism demand quantifies the variation in overnight stays within a given region, and a linear, deterministic model determines the traffic-related implications. The method, tested on the Autonomous Province of South Tyrol (Italy), exhibits expected variations in winter and summer travel demand up to 2080 under different scenarios. Results reveal that average summer traffic can be more than twice as intense as average winter traffic, contributing to significantly increasing the peak days of congestion along the Provincial road network. Despite this evidence, all stakeholders seem to be at an early stage in incorporating this information into their strategic planning. The need for adequate transport policies and measures is considered essential to obtain the optimal balance of transport modes that will be required in the near future.

The Potential of Road Pricing Schemes for Reducing Carbon Emissions

Road pricing is a transport measure mainly conceived to fund road management, to regulate the demand for traffic and to reduce the number of private vehicles circulating in urban areas. It can also grant benefits in terms of environmental externalities including the reduction of CO 2 emissions, which has recently become one of the most important elements defining the sustainability of a transport system. However, the carbon potential granted by road charging is rarely assessed, thus confirming a sort of secondary role attributed to CO 2 in urban premises. This paper provides an accurate analysis of the relationship between the different forms of road pricing (including distance-based, congestion-based and pay-as-you-drive) and their effective role in terms of carbon reduction, which in some contexts is higher than 10%. Furthermore, practical suggestions to policy makers in terms of implementation of the measure are discussed, highlighting the precautions necessary to include a fair carbon evaluation into an overall effective analysis. DOI: http://dx.doi.org/10.4995/CIT2016.2016.3215