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An efficient climate policy is based on cost-benefit analysis (CBA) and equates marginal abatement costs across all forcing agents affecting climate change. In CBA, the agents' contributions to radiative forcing (RF) must be consistently priced (i.e. the social cost of RF, occurring at a specific time, must be the same regardless of the agent causing it). We present a concept that enables doing so. The Social Cost of Forcing (SCF) is the monetary value of the social damage caused by marginal RF at a given instant (Wm − 2 ). Any forcing agent whose temporal decay profile and radiative efficiency are known can be priced based on it. Prices obtained for distinct agents are consistent in CBA, as long as the same SCF and discounting assumptions are applied. Hence, the SCF is a concise way to communicate social cost information: mutually consistent prices for any set of forcing agents can be obtained based on a single Integrated Assessment Model output, the SCF. We explain the theoretical foundations of the concept and illustrate its practical applications with two examples: (1) we derive SCF-based prices for CO 2 and CH 4 , and (2) we estimate the social cost of albedo changes in a boreal forest stand. [ABSTRACT FROM AUTHOR]

In cost-benefit analysis of climate policy there are two main approaches to discounting, each with implications conflicting with our moral intuitions. Thus, discounted utilitarianism implies that we hardly need to protect future generations against climate change, while classical utilitarianism implies that we should reduce our consumption across the board to benefit future generations. The insolubility of the debate derives from the fact that both classical and discounted utilitarianism permit only a single discount rate for all consequences occurring in the same future year, while our intuitions clearly do distinguish between consequences, depending on whether we cause adverse effects on other people's interests and violate their rights. Most people share the moral intuition that we ought to refrain from harming others, and ought to compensate them if we were unable to prevent harm. To regain a reflective equilibrium between such deontological intuitions and economic theory there is a need to accept different discount rates for different situations: a zero consumption discount rate in the case of cost-benefit analysis of measures to prevent wrongful harm to future generations, and standard discounting in all other cases. Applying a zero consumption discount rate means that future generations are automatically largely compensated for climate damage that remains unmitigated. [ABSTRACT FROM AUTHOR]

• Optimization-based indirect estimation of willingness to pay for technology adoption. • WTP estimation using market data and implicit life-cycle cost-benefit analysis. • Estimating WTP's empirical probability distribution using Monte Carlo methods. • Providing deeper understanding of market barriers and policy implication for adoption. Adopting energy-efficient and clean technologies is key to climate change mitigation and meeting long-term sustainability goals because they significantly reduce energy consumption and related carbon emissions. Understanding existing barriers and drivers for the adoption of these energy-efficient and clean technologies will be crucial to meeting ambitious national energy and emissions targets, and the customers' willingness to pay (WTP) is a key factor in understanding the potential for scaling-up adoption. However, in practice, commonly-used WTP estimation methods such as survey or purchase experiments are not always practical or feasible due to budget, time, labor or data constraints. This study proposes a new constrained optimization-based indirect estimation of WTP for energy technology adoption using customers' implicit life-cycle cost-benefit analysis and market data. The empirical probability distribution of WTP is estimated using the Monte Carlo methods. This new indirect estimation method provides a deeper understanding of the barriers and customers' willingness to adopt high efficiency and clean energy technologies, and informs the development of supporting policies and programs needed to accelerate market adoption. [ABSTRACT FROM AUTHOR]

Highlights: [•] A cost benefit analysis of owning and operating a V2G capable electric school bus was conducted. [•] Electric school bus fleets with V2G are cost effective with today’s technology. [•] Variables that maximize V2G revenues have the most influence in the analysis. [•] Schools can save money while mitigating climate change and improving public health. [ABSTRACT FROM AUTHOR]