Assessing direct and indirect emissions of greenhouse gases in road transportation, taking into account the role of uncertainty in the emissions inventory

• Published in: Environmental impact assessment review Vol. 69; pp. 82 - 93
• Main Authors: La Notte, Alessandra, Tonin, Stefania, Lucaroni, Greti
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Inc 01.03.2018; Elsevier BV
• Subjects: Accounting; Accounting procedures; AIR POLLUTION ABATEMENT; Climate change; Climate effects; CONCENTRATION RATIO; Data processing; Data quality; Direct and indirect emissions; EARTH ATMOSPHERE; ECONOMIC IMPACT; Emission; Emission inventories; Emission measurements; Emissions; Emissions control; ENERGY BALANCE; ENVIRONMENTAL POLICY; ENVIRONMENTAL SCIENCES; GHG inventory; Global warming potential; GREENHOUSE EFFECT; GREENHOUSE GASES; Insurance; INVENTORIES; ITALY; Measurement methods; MEASURING METHODS; Regional development; Regions; RELIABILITY; ROAD TRANSPORT; Road transportation; Roads & highways; Transportation; Uncertainty; Vehicle transportation; Vehicles; Uncertainty; Global warming potential; Direct and indirect emissions; GHG inventory; Vehicle transportation
• ISSN: 0195-9255; 1873-6432
• DOI: 10.1016/j.eiar.2017.11.008

Greenhouse gas (GHG) concentration in the atmosphere has increased since the beginning of the industrial era, with dramatic effects on climate change. Transportation is one of the main sources of GHGs, with more than two-thirds of transport-related GHG emissions attributable to road vehicles. Any policy that aims to reduce GHG emissions needs robust measuring methods that guarantee the quality and reliability of primary data and estimates. However, these estimates are subject to uncertainty, both at the stage of compiling accounting tables and at the stage of using this information to formulate a specific policy question. This paper considers how to reduce uncertainty in estimating GHG emissions from road transportation, with specific reference to a regional emissions inventory in Italy. We propose the application of a use-chain model that can tackle uncertainty in measuring GHG emissions by enhancing the quality of the emissions data registry in the inventory. This new metric, which we call emission value at risk (VaR), draws from methodologies and concepts employed in the insurance and financial sectors. Moreover, additional assessments are performed, integrating the inventory data with those available in the regional energy balance and disaggregated sectoral economic dataset. The results show that a sound accounting method enables uncertainty in emission data to be taken into account, thus improving the design of appropriate strategies to reduce GHG emissions. •The use-chain model implemented in this paper is effective in minimizing uncertainty.•Data integration is important to reduce uncertainty.•An innovative metric, Emission Value at Risk, was used to adjust uncertainty values.•Indirect impacts of economic activities change the estimate of GHG emissions.