This paper provides a detailed analysis of the Tokyo Metropolitan Emissions Trading Scheme (Tokyo ETS), Japan’s first emissions trading scheme with mandatory cap initiated by the government of Tokyo. Unlike trading schemes in other countries, the Tokyo ETS covers indirect emissions from the commercial sector. It is well known that a variety of market barriers impede full realization of energy efficiency opportunities, especially in the commercial sector. Experiences with the Tokyo ETS should therefore provide important lessons for the design of climate change mitigation policies, especially when targeting the commercial sector. The emissions from covered entities have been drastically reduced from those at the scheme’s outset, with an average 14% reduction as of the end of the first commitment period of five years (2010–2014) compared with 2009 levels. This paper shows that the Tokyo ETS alone did not cause these reductions; there were other drivers. Among them, the energy savings triggered by the Great East Japan Earthquake in 2011 were crucial. The contribution of credit trading, in contrast, was limited since most of the covered entities reduced emissions by themselves. Through an investigation of official reports, an assessment of the emissions data from the covered entities compared to those of uncovered entities and in-depth interviews with firms covered by the scheme, this paper confirms that the main drivers of emissions reductions by covered entities were separate from the ETS. In fact, the advisory aspect of the scheme seems to be much more important in encouraging energy-saving actions.
Key policy insights
Most of the observed emission reductions were not caused by the Tokyo ETS alone.
An advisory instrument was crucial to the effectiveness of the Tokyo ETS.
The experience of the Tokyo ETS suggests that making full use of the advantages of emissions trading is difficult in the case of the commercial sector.
Price signals have not provided a stimulus to climate change mitigation actions, which implies that establishing a cap to yield effective carbon prices poses a challenge.
This article shows the potential impact on global GHG emissions in 2030, if all countries were to implement sectoral climate policies similar to successful examples already implemented elsewhere. This assessment was represented in the IMAGE and GLOBIOM/G4M models by replicating the impact of successful national policies at the sector level in all world regions. The first step was to select successful policies in nine policy areas. In the second step, the impact on the energy and land-use systems or GHG emissions was identified and translated into model parameters, assuming that it would be possible to translate the impacts of the policies to other countries. As a result, projected annual GHG emission levels would be about 50 GtCO2e by 2030 (2% above 2010 levels), compared to the 60 GtCO2e in the ‘current policies’ scenario. Most reductions are achieved in the electricity sector through expanding renewable energy, followed by the reduction of fluorinated gases, reducing venting and flaring in oil and gas production, and improving industry efficiency. Materializing the calculated mitigation potential might not be as straightforward given different country priorities, policy preferences and circumstances.
Key policy insights
Considerable emissions reductions globally would be possible, if a selection of successful policies were replicated and implemented in all countries worldwide.
This would significantly reduce, but not close, the emissions gap with a 2°C pathway.
From the selection of successful policies evaluated in this study, those implemented in the sector ‘electricity supply’ have the highest impact on global emissions compared to the ‘current policies’ scenario.
Replicating the impact of these policies worldwide could lead to emission and energy trends in the renewable electricity, passenger transport, industry (including fluorinated gases) and buildings sector, that are close to those in a 2°C scenario.
Using successful policies and translating these to policy impact per sector is a more reality-based alternative to most mitigation pathways, which need to make theoretical assumptions on policy cost-effectiveness.
To assess the potential impacts of the US withdrawal from the Paris Agreement, this study applied GCAM-TU (an updated version of the Global Change Assessment Model) to simulate global and regional emission pathways of energy-related CO2, which show that US emissions in 2100 would reduce to ?2.4?Gt, ?0.7?Gt and ?0.2?Gt under scenarios of RCP2.6, RCP3.7 and RCP4.5, respectively. Two unfavourable policy scenarios were designed, assuming a temporary delay and a complete stop for US mitigation actions after 2015. Simulations by the Model for the Assessment of Greenhouse-gas Induced Climate Change (MAGICC) indicate that the temperature increase by 2100 would rise by 0.081°C–0.161°C compared to the three original RCPs (Representative Concentration Pathways) if US emissions were kept at their 2015 levels until 2100. The probability of staying below 2°C would decrease by 6–9% even if the US resumes mitigation efforts for achieving its Nationally Determined Contribution (NDC) target after 2025. It is estimated by GCAM-TU that, without US participation, increased reduction efforts are required for the rest of the world, including developing countries, in order to achieve the 2°C goal, resulting in 18% higher global cumulative mitigation costs from 2015 to 2100.Key policy insights
President Trump’s climate policies, including planned withdrawal from the Paris Agreement, cast a shadow on international climate actions, and would lower the likelihood of achieving the 2°C target.
To meet the 2°C target without the US means increased reduction efforts and mitigation costs for the rest of the world, and considerable economic burdens for major developing areas.
Active state-, city- and enterprise-level powers should be supported to keep the emission reduction gap from further widening even with reduced mitigation efforts from the US federal government.
