Diffusion Of Low-carbon Technologies Research Articles

An evolutionary analysis of the diffusion of low-carbon technology innovation in supply networks

In an era increasingly defined by the urgent need to address energy sustainability and environmental degradation, the advancement of low-carbon technologies stands at the forefront of global governmental agendas. Despite China's pioneering efforts in the adoption and development of low-carbon initiatives, its status as the preeminent global carbon emitter highlights the significant challenges impeding the widespread adoption of these innovations. This study delves into these complexities by employing a sophisticated complex network evolutionary game model that intricately weaves together consumer preferences and carbon pricing as pivotal determinants of utility. By examining the influence of corporate strategic decisions on the diffusion of low-carbon technologies, our research provides an insightful micro-level analysis that diverges from the macro-level orientation typically dominating the field. This nuanced approach not only sheds light on the mechanics of low-carbon technology dissemination but also contributes to a more comprehensive understanding of how to effectively navigate and surmount the barriers to low-carbon technological progress. Through this exploration, our study seeks to augment the discourse on the propagation of low-carbon technologies, offering vital insights for policymakers, industry stakeholders, and the broader academic community on fostering a more sustainable and low-carbon future.

Tracking two decades of global gallium stocks and flows: A dynamic material flow analysis

Gallium (Ga) has recently garnered significant attention as a crucial byproduct element due to its crucial role in advancing low-carbon technologies and its globally imbalanced supply-demand. Understanding the global Ga flows and stocks can contribute to discovering ways to mitigate potential supply risks. In this study, we applied a material flow analysis to map the global Ga cycle from 2000 to 2021. Our results reveal the following results: (1) Over the past two decades, a cumulative 15.3% (313240.8 tons) of the total Ga reserves has been consumed through host metals (i.e., bauxite and zinc ores) mining. However, affected by actual demand, only 5549.7 tons of Ga have been extracted. Moreover, China has gradually become the dominant supplier of primary Ga globally, relying on its robust alumina industry. (2) The consumption pattern of global Ga is becoming increasingly complex. Driven by the diffusion of low-carbon technologies, primary Ga consumption has grown from 101 tons in 2000 to 432 tons in 2021. With a low material efficiency, only 2143.4 tons of Ga ultimately enter final products from semi-products. (3) The global Ga stock reached 956.7 tons in 2021 with significant recycling potential. However, commercial recycling systems were not established, and Ga resources in end-of-life (EoL) final products are mostly wasted. Given the anticipated growth of Ga demand, more coordinated efforts among different regions to promote technological innovation and improve recycling and circularity rates are urgently needed to ensure global Ga supply and a shared green future.

Blocking the sun? Social movements, industries, and the adoption of solar energy in the United States

Despite scholars' growing interest in sustainability transitions, they have paid little attention to how organizational opponents and allies of the climate movement shape the diffusion of low-carbon technologies. Drawing on literature on social movements, social psychology, and environmental sociology, this study develops new arguments about how environmental non-governmental organizations (ENGOs) and the fossil fuel industry influence the adoption of solar photovoltaic (PV) panels. Using an original data set, we assess these arguments by conducting quantitative analyses that test the direct and mediated effects of the ENGOs and fossil fuel industry on the installation of solar PV technology by residents and commercial enterprises in over fifteen thousand U.S. cities during a nine-year period. Findings suggest that local ENGOs promote both types of adoption, but their effect also depends on solar irradiance. Conversely, local fossil fuel companies directly inhibit residential and commercial adoption of PV technologies. We discuss the implications of our results for future research on the diffusion of low-carbon technologies and on energy transitions.

Competitive firms’ low-carbon technology diffusion under pollution regulations: A network-based evolutionary analysis

To investigate the diffusion degree of low-carbon technology in competitive firms and the influence of different pollution regulations, we constructed an evolutionary game model representing three environmental mechanisms: total amount control and trading, carbon tax, and subsidy, within a complex firm network. By analyzing the effects of carbon quotas, tax rates, and subsidy rates, we comprehensively assessed the performance of these mechanisms in terms of diffusion degree, firm profits, consumer surplus, environmental damage, and social welfare. The study results demonstrated distinct outcomes for each environmental mechanism. Under the subsidy mechanism, low-carbon technology exhibited the highest diffusion degree, suggesting its efficacy in promoting widespread adoption. However, it is worth noting that the higher the subsidy, the more environmental pollution it led to, which presents a trade-off between environmental benefits and financial incentives. On the other hand, the carbon tax mechanism resulted in minimal pollution, reflecting its potential as an effective tool for environmental regulation. Finally, the cap-and-trade mechanism emerged as the most favorable option, as it maximized social welfare while effectively addressing environmental concerns.

Research on low-carbon technology diffusion among enterprises in networked evolutionary game

The diffusion of low-carbon technologies (LCTs) is one of the important measures to mitigate carbon emissions. Local governments, enterprises, and consumers are crucial participants in the complex adaptive LCT diffusion system. In this context, this study builds an evolutionary game model based on a complex network comprised of three sub-networks, which respectively represent the connections of local governments, enterprises and consumers. Using this model, this research explores the impacts of homogeneous subsidies, heterogeneous subsidies, homogeneous carbon taxes, heterogeneous carbon taxes, targeted penalties, market demand, and policy mixes combined with these instruments on LCT diffusion. The results show that carbon taxes, subsidies, and penalties can all promote the diffusion of LCTs. The comprehensive effect of LCT diffusion brought by heterogeneous subsidies or carbon taxes is slightly better than those achieved by the fixed subsidy or the carbon tax equal to their respective mean values. Compared with pure carbon tax and subsidy policies, the mixed policy of introducing targeted fines brings a more obvious LCT diffusion effect. However, none of these policy interventions can achieve the complete spread of LCTs. Meanwhile, increasing the potential market demand for low-carbon products can achieve a very significant diffusion of LCTs. And when the proportion of white consumers reaches 0.9, the full proliferation of LCTs can be realized. This research develops a valuable framework that enriches the modeling practice of the diffusion of LCTs and provides insights for implementing well-designed policy packages.

Multi-sector technology diffusion in urgent net-zero transitions: Niche splintering in carbon capture technology

Transitioning to net-zero greenhouse gas emissions by mid-century requires rapid diffusion of low-carbon technologies across numerous sectors. Multi-purpose technologies are expected to solve sustainability problems in several sectors. Given the mid-century deadline, diffusion of such technologies must happen in multiple sectors simultaneously instead of sequentially. Since different sectors have their own set of preferences, technical needs, and institutional characteristics, simultaneous interactions with several sectors increases the complexity of diffusion processes. We contribute a new perspective on the diffusion of multi-purpose technologies in the context of urgent grand challenges. Drawing on insights from the ‘niche anchoring’ and ‘technology speciation’ literatures, we present a framework that puts actors and their sense-making at the centre of the diffusion process. The framework is applied to the case of carbon capture in Norway, which has recently been applied in multiple new user sectors simultaneously. We find that diversity in needs, expectations, and technological solutions leads to increased uncertainty and ‘niche splintering’, which hampers rapid anchoring and diffusion of carbon capture. In addition to our framework for multi-sector technology diffusion, the paper also contributes by highlighting challenges for diffusing carbon capture to multiple sectors at the rate seen in many net-zero strategies and mitigation scenarios.

Research on the Effect of Information Infrastructure Construction on Low-Carbon Technology Knowledge Flow

The cross-regional diffusion of low-carbon technology knowledge is conducive to the development of low-carbon technology and increases the emission reduction contribution of the wider land. However, the flow of low-carbon technology knowledge faces many obstacles such as information, geography, and local protectionism. This paper focuses on whether and how information infrastructure construction can promote the flow of low-carbon technology knowledge under the digital wave. Through the low-carbon technology patents of category Y02 under the classification standard of Cooperative Patent Classification (CPC) and by matching them to the city level to measure the low-carbon technology knowledge flow, empirical research finds that: information infrastructure cannot only directly promote the low-carbon technology knowledge flow, but also indirectly promote the low-carbon technology diffusion by increasing foreign direct investment and human capital. The role of information infrastructure in promoting low-carbon technology knowledge is more obvious in the central and western regions and non-resource-based cities. Finally, in view of the current development situation of low-carbon technology knowledge flows in China, the paper puts forward policy recommendations to vigorously promote the construction of information infrastructure, to gradually increase the network density and the number of network nodes, release the digital economic dividend, and form a spatial pattern of coordinated development of regional knowledge flows.

Low-carbon technology diffusion and economic growth of China: an evolutionary general equilibrium framework

The thorough transition of energy system is required to achieve the Paris Agreement goal. Computable general equilibrium (CGE) models are a common tool for estimating the energy transition pathway and the impact of low-carbon policies on economic growth. However, CGE models encounter challenges on modeling diffusion of new technologies. This study proposed a novel evolutionary dynamic general equilibrium model to capture the nonlinear, path-dependent and S-shaped technology diffusion process, and examined the low-carbon transition pathway of power sector and its impact on economic growth of China. We found that imposing a moderate carbon tax and avoiding the over-reliance on coal-fired power could achieve the near-zero emissions of power sector, avoid the large economic loss and hasten the economic growth in the long term. The evolutionary framework may be useful for developing the next-generation model, particularly for simulating the diffusion of new technologies, and their structural effects on economic dynamics.

Spatial Convergence of Carbon Productivity: Theoretical Analysis and Chinese Experience.

Based on the neoclassical framework, we propose the convergence hypothesis of carbon productivity under sustainable growth and prove the different effects of knowledge spillover and technology diffusion on convergence. The convergence hypothesis is tested using China’s provincial spatial dynamic panel data from 1995 to 2019. The results show that China’s provincial carbon productivity has conditional convergence and club convergence characteristics. The convergence speed of dynamic panel regression estimation is greater than that of cross-sectional regression. The convergence rate of dynamic spatial panel regression estimation is faster depending on the spatial spillover difference between the two technologies. In the early stage, the provincial spatial dependence of China’s carbon productivity is mainly knowledge spillover, and the convergence rate is lower than that of the closed economy. Over the past decade, the spatial spillover, dominated by low-carbon technology diffusion, has become the dominant force. The convergence rate is significantly faster than that of a non-spatial-dependent economy. In addition, the mechanism test found that the development of energy efficiency dominates the spatial transfer of technology, so the overall convergence of carbon productivity in China mainly comes from the apparent convergence of energy efficiency in provinces and cities. Our conclusion provides a new reference for the emission reduction actions of countries worldwide because the spatial knowledge spillover carried by capital flows is not conducive to the pursuit of carbon productivity in less developed regions. On the contrary, the dissemination and diffusion of low-carbon technologies can significantly reduce carbon equivalent input in the production process, accelerating the pursuit of developing countries or regions.

Simulating the impact of demand-side policies on low-carbon technology diffusion: A demand-supply coevolutionary model

Alleviating the pressure of climate and energy calls for an improved understanding of how policy interventions influence the diffusion of low-carbon technologies (LCTs) among enterprises. With the rapid convergence of supply-side policy effects, implementing demand-side policies to drive LCT diffusion may be a promising area for carbon abatement action. This study proposes a demand-supply coevolutionary model embedded in two-layer network is to capture the LCT diffusion among supply-side enterprises and low-carbon consumption diffusion among demand-side consumers. Using this model, we simulate the effects of demand-side policies, including public procurement, financial incentives for consumers, public information dissemination, and policy mixes combined with these instruments on LCT diffusion. The results show that public procurement can effectively facilitate LCT diffusion and restrain the magnitudes of market fluctuations caused by demand-side dynamics in the diffusion process. The high consumer incentives facilitate the rapid diffusion of LCTs, but there are noticeable diminishing marginal effects; even if subsidies are only used on the demand side, the promotion effect on LCT can still be achieved through the demand-supply interaction. Furthermore, the public information dissemination improves LCT diffusion and stabilizes the adaptive behavior of enterprises, but its time-lag effect leads to the pattern of “hot policies and cold markets.” The introduction of policy mixes verifies these findings and reveals that although the public information dissemination is constrained by other policies, it may still be the premise of large-scale LCT diffusion. This study develops a valuable framework that enriches the modeling practice of LCT and provides insights for implementing well-designed policy packages.

Do environmental regulations promote low-carbon diffusion among different scales of enterprise? A complex network-based evolutionary game approach

To mitigate the detrimental effects of climate change exacerbated by excessive carbon emissions, China has introduced a series of environmental regulations designed to promote low-carbon technology diffusion among enterprises. The existing literature ignores the heterogeneity of the scales of enterprises, making it extremely difficult to put forward targeted policies for enterprises of different scales. In this study, we employ a complex network-based evolutionary game approach to analyze the effect of environmental regulations on the diffusion of low-carbon technology, and thereby determine the relationship between the degree of diffusion and the strength of regulations at different scales of enterprise. The results revealed that with respect to the degree of diffusion, there are significant differences in the sensitivity of enterprises in 20- and 100-scale networks to the imposition of three types of environmental regulation (innovation subsidy, carbon tax, and punishment). When the scale of the network is fixed, fluctuation in the change in degree becomes larger, and even irregular, with an increase in enterprise scale. With an increase in network scale for small, medium, and large enterprises, the range of variation in the degree of diffusion becomes smaller. In small, medium, and large enterprises, when the scale of the network increases from 20 to 100, the degree of diffusion will increase in response to the same strength of innovation subsidy, carbon tax, and punishment. With an increase in innovation subsidies, the diffusion degree of large enterprises will improve slightly. Moreover, for large enterprises, increasing the strength of punishment has no obvious effects with regards to improving the degree of diffusion. At all scales of enterprise, in both the 20- and 100-sacle networks, the degree of diffusion will increase with an increase in the strength of the carbon tax.

Transforming the s-shape: Identifying and explaining turning points in market diffusion curves of low-carbon technologies in Austria

The need for rapid decarbonization of the energy system calls for an improved understanding how policy action may accelerate the market diffusion of low-carbon technologies. Turning points, in other words, i.e. points in time when market growth curves change direction, occur when politics, policy, and technology streams converge. Investigating photovoltaics, residential heat pump, and electric vehicle diffusion in Austria from 1970/1990 to 2018, we constellate when and why turning points occurred. Analyzing market statistics with the mathematical method of change point analysis allows identifying turning points and growth functions in diffusion curves. We used the Multiple Streams Approach to structure archival documents and findings from expert interviews to reconstruct critical events in past socio-political and socio-technological developments which triggered turning points. We find that observed diffusion processes change direction and pace at specific moments in time, rather than following a uniform s-shape. Mandatory regulations are key levers, but need to be supplemented by events in the respective streams: In the politics stream, overarching political strategies and model policies in other countries set the stage for low-carbon technologies. In the technology stream, R&D programs, product development, and quality labels support technological advancement. In the policy stream, however, ad-hoc subsidy programs tend to produce patchwork policies or only temporarily boost market diffusion. Continuously monitoring market processes may allow anticipation of upcoming turning points when the implementation of integrated policies can push combinations of complementary technologies.

Exploring the dynamics of low-carbon technology diffusion among enterprises: An evolutionary game model on a two-level heterogeneous social network

For mitigating carbon emissions, series of policies have been formulated by governments to promote the diffusion of low-carbon technologies (LCTs). Enterprises' strategic choices and consumers' decisions have a pivotal impact on LCT diffusion. In this context, this study builds an evolutionary game model based on a social network comprised of two sub-networks with different typologies, which respectively depict the connections of enterprises and consumers. Enterprises choose to produce either low-carbon or un-low-carbon products according to the evolutionary game theory. Consumers purchase preferable products repeatedly according to their demands. Using the model, this research explores the impacts of carbon taxes, subsidies, and the demand for low-carbon products. The results show that carbon taxes have increasing marginal effectiveness in promoting LCT diffusion; high carbon taxes can mitigate the fluctuations of LCT diffusion caused by consumers' repeat purchases; while using the data from the electric vehicle industry, enterprises do not manifest high sensitivity to mild carbon taxation. Different from taxation, the effectiveness of subsidization diminishes and results in inefficiency. A large demand for low-carbon products can prominently stimulate enterprises to adopt LCTs. However, if demand increases from a low level, the fluctuation of LCT diffusion is magnified. This magnification does not last if demand continues to increase.

Network structures, environmental technology and contagion

ABSTRACT Diffusion of low-carbon technologies is critical to global decarbonization efforts aimed at achieving the Paris Agreement climate goals. In this paper, we represent a social system as a network of agents and model the process of technology diffusion as a contagion propagating in such a network. By setting the necessary conditions for an agent to switch (i.e. to adopt the technology), we address the question of how to maximize the contagion of a technology subject to learning effects (e.g. solar PV) in a network of agents. We focus the analysis on the influence of the network structure and technological learning on diffusion. Our numerical results show that clusters of agents are critical in the process of technology contagion although they generate high levels of variance in aggregate diffusion. Whatever the network structure, learning effects ease the technology contagion in social networks. Key policy insights: Policy makers should take advantage of, or favour, clustered organizations to deploy renewables (e.g. cooperatives of farmers, online social networks) Social dimensions are critical in the design of environmental policies (e.g. peer effects) Technologies subject to learning effects spread further in the population When considering social connections, policy makers should design policies to cope with uncertainty in diffusion (clustered organizations exhibit high levels of uncertainty in adoption).

Is the coherence of coal phase-out and electrolytic hydrogen production the golden path to effective decarbonisation?

We analyse whether Germany will fall short of the country’s decarbonisation targets. Bearing this potential failure in mind, the present study investigates technological options and their effectiveness for decarbonising the energy system from a systemic perspective. We consider the country’s coal phase-out, the increasing amounts of electricity from renewable energy sources, more efficient heating concepts as well as the evolving of smart charging infrastructures and large-scale storage options. Based on the declared plans of the federal authorities and alternative proposals of environmental associations, ten distinct decarbonisation scenarios for the period from 2020 to 2030 form the basis of our models. Using the Energy PLAN simulation tool, annual and hourly performance indicators were computed in order to evaluate the effectiveness of decarbonisation measures. In particular, we examine the increasing usage of electrolysers for both the absorption of excess electricity and the production of hydrogen as a substitute for fossil fuels in relation to the timing of the coal phase-out. Pursuing this approach, we demonstrate the coherence between coal phase-out policies and low carbon technology diffusion. Our findings reveal that implementing the coal phase-out earlier than has been scheduled by the country’s Commission on Growth, Structural Change and Employment mitigates the non-achievement of the decarbonisation targets. Moreover, our results suggest the upscaling of domestic electrolyser capacity to up to 9554 MW by 2030.

A Trade Policy Agenda for the Diffusion of Low-Carbon Technologies

This article proposes that the function of trade rules with respect to low-carbon technology diffusion should be to address the identified market-related barriers preventing cross-border dispersion of the necessary technologies. By doing so, it seeks to expand the discussion in the WTO regarding trade, technology transfer, and climate change beyond the traditional confines of intellectual property issues. To that effect, it outlines a new framework against the normative background of Common Concern of Humankind, an emerging legal doctrine. This is further followed by highlighting the key areas of action, which includes - market access reform to reduce costs, process and production measures (PPMs) to increase demand for clean technologies, and making rational and appropriate incentives available domestically and also for exports. Trade and Climate, Low-carbon technology diffusion, Transfer of technology, Market failure, Technology market reform, Common concern of humankind

Modeling the emission trading scheme from an agent-based perspective: System dynamics emerging from firms’ coordination among abatement options

Though sharing a similar practice form, the emission trading scheme is distinguished from traditional financial markets: firms coordinate three abatement options at the micro level, including allowance trading, output adjustment, and low-carbon technology adoption. Then, at the macro level, this leads to dynamic interactions among allowance market, output market, and low-carbon technology diffusion. This is the fundamental characteristic of the emission trading scheme, and modeling the dynamics behind is a major difficulty for relevant studies, especially when following complexities are considered: (1) different planning horizons of the three abatement options, (2) heterogeneity among sectors and firms, and (3) details of firms’ production and optional low-carbon technologies. Aiming at this difficulty, we establish an agent-based model for the emission trading scheme, and within a novel multi-level time frame, the fundamental characteristic is reflected and the complexities are considered. Firms’ production and low-carbon technologies are discretely modeled at a process level from a bottom-up perspective, and based on European data, our model is calibrated to cover 5 industrial sectors, 11 emission-intensive products, 25 production processes, and 52 low-carbon technologies. With this model, the emergence properties and uncertainty of the system are captured, and the non-linear impact of the abatement target is reflected and discussed. We find that, after a certain level, higher target leads to lower allowance price uncertainty but stronger output impact, which is a trade-off for setting the abatement target.

Simulating policy interventions in the interfirm diffusion of low-carbon technologies: An agent-based evolutionary game model

Policy interventions are frequently used by authorities around the world to mitigate carbon emissions. However, economic systems are essentially complex adaptive systems, which often exhibit unexpected responses to exogenous interventions and leave intervenors in a dilemma, even if the interventions are elaborately designed. To explore the behaviors of the diffusion system regarding low-carbon technologies, this study builds an agent-based model (ABM) to simulate enterprises’ reactions to multiple policy interventions aimed at spurring low-carbon technology diffusion. The simulated enterprises are in a complex network where they play evolutionary games with their neighbors, which enables the model to possess two critical features of economic systems: adaptiveness and equilibrium. The model reveals a dilemma of policy interventions: intuitively, carbon taxes, asymmetric penalties (only imposed on un-low-carbon enterprises) and subsidies can improve the diffusion, which is consistent with previous research; counter-intuitively, all these policies turn out to be inefficient or even harmful to low-carbon enterprises because of the diffusion system’s high adaptiveness. Specifically, when carbon taxes and penalties increase, both the low-carbon and un-low-carbon enterprises end up with the equilibrium of equivalent but lower profits. In contrast, all the enterprises earn equivalent but more profits even though subsidies are only given to the low-carbon enterprises, which implies that the un-low-carbon enterprises (indirectly) grab a portion of the subsidies and accordingly weaken the incentive effect of subsidies. These system behaviors are summarized as “equalizing effect” because the system tends to equalize the impact of both positive and negative interventions among all enterprises even though the policy interventions are asymmetrically imposed on one type of the enterprises. The findings also indicate that policies implemented to enlarge green market sizes can help policymakers bypass the dilemma.

Beyond the Paris Agreement: Intellectual Property, Innovation Policy, and Climate Justice

The multidisciplinary field of climate law and justice needs to address the topic of intellectual property, climate finance, and technology transfer to ensure effective global action on climate change. The United Nations Framework Convention on Climate Change 1992 (UNFCCC) established a foundation for the development, application and diffusion of low-carbon technologies. Against this background, it is useful to analyse how the Paris Agreement 2015 deals with the subject of intellectual property, technology transfer, and climate change. While there was discussion of a number of options for intellectual property and climate change, the final Paris Agreement 2015 contains no text on intellectual property. There is text, though, on technology transfer. The Paris Agreement 2015 relies upon technology networks and alliances in order to promote the diffusion and dissemination of green technologies. In order to achieve technology transfer, there has been an effort to rely on a number of formal technology networks, alliances, and public–private partnerships—including the UNFCCC Climate Technology Centre and Network (CTCN); the World Intellectual Property Organization’s WIPO GREEN; Mission Innovation; the Breakthrough Energy Coalition; and the International Solar Alliance. There have been grand hopes and ambitions in respect of these collaborative and co-operative ventures. However, there have also been significant challenges in terms of funding, support, and operation. In a case of innovation policy pluralism, there also seems to be a significant level of overlap and duplication between the diverse international initiatives. There have been concerns about whether such technology networks are effective, efficient, adaptable, and accountable. There is a need to better align intellectual property, innovation policy, and technology transfer in order to achieve access to clean energy and climate justice under the framework of the Paris Agreement 2015. At a conceptual level, philosophical discussions about climate justice should be grounded in pragmatic considerations about intellectual property and technology transfer. An intellectual property mechanism is necessary to provide for research, development, and deployment of clean technologies. There is a need to ensure that the technology mechanism of the Paris Agreement 2015 can enable the research, development, and diffusion of clean technologies at a scale to address the global challenges of climate change.

Macroeconomic impact of stranded fossil fuel assets

Several major economies rely heavily on fossil fuel production and exports, yet current low-carbon technology diffusion, energy efficiency and climate policy may be substantially reducing global demand for fossil fuels1–4. This trend is inconsistent with observed investment in new fossil fuel ventures1,2, which could become stranded as a result. Here, we use an integrated global economy–environment simulation model to study the macroeconomic impact of stranded fossil fuel assets (SFFA). Our analysis suggests that part of the SFFA would occur as a result of an already ongoing technological trajectory, irrespective of whether or not new climate policies are adopted; the loss would be amplified if new climate policies to reach the 2 °C target of the Paris Agreement are adopted and/or if low-cost producers (some OPEC countries) maintain their level of production (‘sell out’) despite declining demand; the magnitude of the loss from SFFA may amount to a discounted global wealth loss of US$1–4 trillion; and there are clear distributional impacts, with winners (for example, net importers such as China or the EU) and losers (for example, Russia, the United States or Canada, which could see their fossil fuel industries nearly shut down), although the two effects would largely offset each other at the level of aggregate global GDP.