Abstract
Cost-effective air pollution emission control has been in focus for decades in international air pollution regulations. Despite large observed emission reductions for many air pollutants, environmental and human health problems persist and more efforts are needed. However, some stakeholders are concerned that the costs for remaining emission control measures are prohibitively high. There are several reasons for concern, and one can be the difference in investment perspectives—i.e. costs of borrowing and time constraints—held by stakeholders. By using the integrated assessment model GAINS, we study whether differences in investment perspectives of Nordic stakeholders influence measures selected for cost-effective emission control and can motivate concerns for high costs of emission control. We distinguish the control cost calculations between a social planner perspective and a corporate perspective and apply these to the GAINS model database on emission control measures. A cost-minimized selection of measures in 2030 is then calculated for increasing environmental and health ambitions for both perspectives. The results show an irregular pattern, but for a range of ambition levels the corporate perspective affects the selection of measures and implies surplus costs for the Nordic social planner of up to 120 million € per year. This is 36% more expensive than the costs of the social planners’ selection. Conversely, from a corporate perspective the social planners’ selection can imply cost increases of up to 180 million €. We therefore suggest that control of investment perspective effects should be standard in analysis of cost-effective air pollution measures.Graphical abstract
Highlights
Cost-effectiveness of pollution control is an important criteria when setting policy ambition levels in the Gothenburg Protocol of the Air Convention (United Nations 2013) and the EU National Emission Ceilings (NEC) Directive (Official Journal of the European Union 2016), both controlling European emissions of sulphur dioxide (SO2), nitrogen oxides (NOx), ammonia (NH3), fine particular matter (PM2.5), and non-methane volatile organic compounds (NMVOCs)
In the analysis presented in this paper, the social planner perspective implies a 4% interest rate on investment (Godard 2009), which is close to other common literature values of 3.5% (Moore et al 2004) and corresponds to the value chosen in contemporary air pollution policy analysis (Amann 2015)
There are two major deviations from the costs of the social planner strategy if Nordic emission reductions are achieved with the corporate strategy
Summary
Cost-effectiveness of pollution control is an important criteria when setting policy ambition levels in the Gothenburg Protocol of the Air Convention (United Nations 2013) and the EU National Emission Ceilings (NEC) Directive (Official Journal of the European Union 2016), both controlling European emissions of sulphur dioxide (SO2), nitrogen oxides (NOx), ammonia (NH3), fine particular matter (PM2.5), and non-methane volatile organic compounds (NMVOCs). Given the site-specific nature of air pollution dispersion, damages, and emission control, the international policy and research community use integrated assessment models (IAMs) such as the Greenhouse Gas—Air Pollution Interactions and Synergies (GAINS) model (Amann et al 2011) to analyse cost-effectiveness of different policy options. Likely based on the similar cost calculation principles (Graham and Harvey 2001), the two perspectives differ with respect to risk and time constraints, as well as costs of acquiring financial resources for investments (Grout 2003). These differences mainly imply that different interest rates and time constraints are used in calculations. No strict definition of the social planner seems to exist, in our paper the social planner tries to achieve the largest benefit for society by reducing emissions where the largest impact on the environment and human health can be achieved at the lowest costs, with cheap access to capital (low interest rates) and long-term time constraints
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