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This paper investigates the impact of transition risk on a firm's low-carbon production. As the world is facing global climate change, the Intergovernmental Panel on Climate Change (IPCC) has set the idealized carbon-neutral scenario around 2050. In the meantime, many carbon reduction scenarios, known as Shared Socioeconomic Pathways (SSPs) have been proposed in the literature for different production sectors in a more comprehensive socio-economic context. We consider, on the one hand, a firm that aims to optimize its emission level under the double objectives of maximizing its production profit and respecting the emission mitigation scenarios. Solving the penalized optimization problem provides the optimal emission according to a given SSP benchmark. On the other hand, such transitions affect the firm's credit risk. We model the default time by using the structural default approach. We are particularly concerned with how, by following different SSPs scenarios, the adopted strategies may influence the firm's default probability. [ABSTRACT FROM AUTHOR]

Governments around the world are seeking an effective mechanism to cope with air pollution and climate change. The allocation of emission allowances, which is a key mechanism in the cap-and-trade system, is an important and intricate puzzle faced by environmental agencies. In this paper, we build a Stackelberg model to explore the emission allowance allocation mechanism design from an operations perspective. We demonstrate the feasibility and effectiveness of a linear emission allowance allocation mechanism. The results show that the emission allowance allocated by the government should always be insufficient to satisfy the ex-post emission demand at the industry level, even with low-carbon investment. To analyze the impacts on firms' decision-makings, we explore a scenario in which two firms in the same industry sell a homogenous product to the market. The optimal low-carbon investment and production decisions are significantly affected by these market and carbon-related factors. Numerical examples are presented to further demonstrate the results that our paper has derived and investigate the optimal operational decisions of the two firms. Several meaningful management insights on allocation mechanism design and low-carbon operations of firms are obtained. [ABSTRACT FROM AUTHOR]

An introduction is presented which discusses reports on topics including environmental coalitions, climate change algorithms, and European Union Emissions Trading Scheme.

Global climate change has encouraged international and regional adoption of pollution taxes and carbon emission reduction policies. Europe has taken the leadership in environmental regulations by introducing the European Union Emissions Trading System (EU-ETS) in 2005 and by promoting a set of policies destined to lower carbon emissions from energy, industrial, and transport sectors. These environmental policies have significantly affected the production choices of these European sectors. Considering this framework, the objective of this paper is to evaluate the effects of the application of environmental policies in a multitiered closed-loop supply chain network where raw material suppliers, manufacturers, consumers, and recovery centers operate. In particular, we assume that manufacturers are subject to the EU-ETS and a carbon tax is imposed on truck transport. In this way, the developed model captures carbon emission regulations, recycling, transportation and technological factors within a unified framework. In particular, it allows for evaluating the impacts of the considered environmental regulations on carbon emissions, product flows, and prices. The proposed model is optimized and solved by using the theory of variational inequalities. Our analysis shows that the combined application of the EU-ETS at the manufacturers' tier and the carbon tax on truck transport implies additional costs for producers that reduce their good provisions. On the other side, this has a positive outcome for the environment since $$\hbox {CO}_2$$ emissions reduce. Moreover, an increase of the efficiency level of the recycling process increments the availability of reusable raw material in the reverse supply chain. Finally, the distance between a couple of CLSC tiers plays a very important role. The lower is the distance covered by vehicles, the higher is the production of goods and the lower is the amount of $$\hbox {CO}_2$$ emitted. [ABSTRACT FROM AUTHOR]

Mitigation and adaptation represent two solutions to the issue of global warming. While mitigation aims at reducing $$\hbox {CO}_2$$ emissions and preventing climate change, adaptation encompasses a broad scope of techniques used to reduce the impacts of climate change once they have occurred. Both have direct costs on a country's gross domestic product, but costs also arise from temperature increases due to inaction. This paper introduces a tipping point in a real options model and analyzes optimal investment choices in mitigation and their timing. [ABSTRACT FROM AUTHOR]

We present two solution algorithms for a large-scale integrated assessment model of climate change mitigation: the well known Negishi algorithm and a newly developed Nash algorithm. The algorithms are used to calculate the Pareto-optimum and competitive equilibrium, respectively, for the global model that includes trade in a number of goods as an interaction between regions. We demonstrate that in the absence of externalities both algorithms deliver the same solution. The Nash algorithm is computationally much more effective, and scales more favorably with the number of regions. In the presence of externalities between regions the two solutions differ, which we demonstrate by the inclusion of global spillovers from learning-by-doing in the energy sector. The non-cooperative treatment of the spillover externality in the Nash algorithm leads to a delay in the expansion of renewable energy installations compared to the cooperative solution derived using the Negishi algorithm. [ABSTRACT FROM AUTHOR]