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Kelly A.,Envecon Inc. | Lumbreras J.,Technical University of Madrid | Maas R.,Netherlands Environmental Assessment Agency | Pignatelli T.,Sustainable Development Technology | And 2 more authors.
Environmental Science and Policy | Year: 2010

The Gothenburg Protocol set national emission ceilings for transboundary air pollutants in 2010. These ceilings were formulated in 1999 using the Regional Air Pollution Information and Simulation (RAINS) model and national forecast data. The 2010 ceiling deadline is approaching as is a revision process which may lead to the setting of emission ceilings for 2020. This paper considers the original 1999 projections of six countries that were used within the RAINS model to inform the setting of their respective Gothenburg Protocol 2010 emission ceilings. These data are then contrast against recent inventory data and contemporary short-term forecasts out to 2010. These recent forecasts indicate that major downward shifts in the trends of pollutant emissions have been achieved, and whilst compliance challenges remain, there is a clear indication of the potential of such international agreements and their associated legislative and policy driven mechanisms. However, in a process governed by a maxim of achieving international environmental objectives at 'least-cost', the recent experience offers some valuable lessons. Specifically, in relation to the accuracy of energy projections and assumptions of other relevant variables in the modelling process. This paper considers these lessons and opens a discussion on the role of more adaptable mechanisms for the ongoing management of international agreements with long-term compliance horizons. © 2009 Elsevier Ltd. All rights reserved. Source

Fu M.,University College Dublin | Kelly A.,Envecon Inc.
Transportation Research Part D: Transport and Environment | Year: 2011

This paper examines whether regional characteristics can have a significant impact on the engine sizes of the car fleet in Ireland. Disposable income is found to be the dominant factor in determining the purchase probabilities of car engine size, but in addition a combination of high population density and the availability of rail transport can reduce the demand for medium and large engine sized vehicles, as well as for new cars generally. Bus services, however, only serve as a substitute for small engine cars. © 2011 Elsevier Ltd. Source

Fu M.,University College Dublin | Fu M.,Guangdong University of foreign Studies | Kelly J.A.,Envecon Inc. | Clinch J.P.,University College Dublin
Applied Geography | Year: 2014

Reducing solid fuel use for home heating can reduce both carbon emissions and air pollution within residential areas and thereby provide for improved environmental and health outcomes. The general models used to identify the determinants of solid fuel use often focus upon socioeconomic factors. Utilising an extended spatial econometric approach our results show proximity to a solid fuel resource as the most significant factor. Other spatially evaluated attributes, such as temperature, legislated solid-fuel sale restrictions and gas network coverage, are also found to have significant impacts on solid fuel use choices. Clear spatial dependence patterns are found for the effects of these attributes, with further evidence of large spill-over effects for neighbouring areas in the case of proximity to either a peat bog or an area subject to a ban on the sale of smoky coal. The research engages a blend of GIS and spatial econometric analysis to generate maps for both a fuel poverty risk and a resistance to fuel change index. These outcomes can serve to informthe design and deployment of effective and equitable solid-fuel and environmental policy interventions. Suggested policy interventions include conservation of peat bogs, expansion of smoky coal ban areas and the development of gas network coverage to specific areas. In addition to the policy support outcomes, the paper offers technical and methodological innovations in relation to combining spatial attributes with econometric models, handling large spatial matrices, understanding direct and indirect effects, and visibly presenting estimated values with spatial dependence. © 2014 Elsevier Ltd. Source

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