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Modelling the economics of climate change is daunting. Many existing methodologies from social and physical sciences need to be deployed, and new modelling techniques and ideas still need to be developed. Existing bread-and-butter micro- and macroeconomic tools, such as the expected utility framework, market equilibrium concepts and representative agent assumptions, are far from adequate. Four key issues—along with several others—remain inadequately addressed by economic models of climate change, namely: (1) uncertainty, (2) aggregation, heterogeneity and distributional implications (3) technological change, and most of all, (4) realistic damage functions for the economic impact of the physical consequences of climate change. This paper assesses the main shortcomings of two generations of climate-energy-economic models and proposes that a new wave of models need to be developed to tackle these four challenges. This paper then examines two potential candidate approaches—dynamic stochastic general equilibrium (DSGE) models and agent-based models (ABM). The successful use of agent-based models in other areas, such as in modelling the financial system, housing markets and technological progress suggests its potential applicability to better modelling the economics of climate change.

National net zero emission targets could, if fully implemented, reduce best estimates of projected global average temperature increase to 2.0–2.4 °C by 2100, bringing the Paris Agreement temperature goal within reach. A total of 131 countries are discussing, have announced or have adopted net zero targets, covering 72% of global emissions. These targets could substantially lower projected warming as compared to currently implemented policies (2.9–3.2 °C) or pledges submitted to the Paris Agreement (2.4–2.9 °C). Current pledges for emissions cuts are insufficient to meet the Paris Agreement temperature goal. The wave of net zero targets being discussed and adopted could make the Paris goal possible if further countries follow suit.

Moisture availability is a strong determinant of decomposition rates in forests worldwide. Climate models suggest that many terrestrial ecosystems are at risk from future droughts, suggesting moisture limiting conditions will develop across a range of forests worldwide. The impacts of increasing drought conditions on forest carbon (C) fluxes due to shifts in organic matter decay rates may be poorly characterised due to limited experimental research. To appraise this question, we conducted a meta-analysis of forest drought experiment studies worldwide, examining spatial limits, knowledge gaps and potential biases. To identify limits to experimental knowledge, we projected the global distribution of forest drought experiments against spatially modelled estimates of (i) future precipitation change, (ii) ecosystem total above-ground C and (iii) soil C storage. Our assessment, involving 115 individual experimental study locations, found a mismatch between the distribution of forest drought experiments and regions with higher levels of future drought risk and C storage, such as Central America, Amazonia, the Atlantic Forest of Brazil, equatorial Africa and Indonesia. Decomposition rate responses in litter and soil were also relatively under-studied, with only 30 experiments specifically examining the potential experimental impacts of drought on C fluxes from soil or litter. We propose new approaches for engaging experimentally with forest drought research, utilising standardised protocols to appraise the impacts of drought on the C cycle, while targeting the most vulnerable and relevant forests.

Abstract This work focuses on the efforts being made by King County, Washington to respond to the challenges of global climate change, concentrating on both mitigation and adaptation. King County is a leader in the United States in the development and implementation of meaningful climate change efforts in local government. The county, in conjunction with ICLEI, recently produced a workbook on Preparing for Climate Change at the Local, Regional, and State levels. While the vast majority of local governments in the United States have only taken limited steps to respond to global warming, King County stands out as aggressively looking to move in a new direction. The King County Climate Plan is based on the conviction that climate change is both a problem and an opportunity for communities to improve environmental quality through mitigation of greenhouse gases and simultaneously build resilience to adapt to global climate change. Its exceptional combination of responsibilities in planning and opportunities makes this an invaluable experience to other local governments throughout the world. The work to be presented is a case study that examines the underlying issues and challenges faced by this jurisdiction in adopting its climate change plan; the development and adoption of the plan; issues associated with monitoring and sustaining these efforts; and the broader challenges of building more resilient and adaptive communities. The case study will focus both on procedural issues, as well as, on the types of mitigation and adaptive responses. One aspect of the paper will examine King County's efforts to link climate change efforts/policy/plans to other critical community concerns (e.g., issues of equity and race), and to the economic opportunities that have become critical motivators to successfully as moving forward the county attempts to establish itself as a global leader in meeting the challenges of global climate change.

Green energy technologies (GETs) are environmentally friendly in nature, making a promising contribution to attaining net-zero carbon goals. Although the Pakistani government has begun using GETs to minimize the adverse effects of carbon emissions, consumers' adoption rate is quite low. There are few studies examining consumers' desire to adopt GETs in the country. This study attempts to fill this research gap and also contributes by adding three novel factors to the theory of planned behavior (i.e., green energy technology awareness, openness to experience, and green energy technology discomfort) to comprehensively analyze the impact of various factors influencing consumers' desire to adopt GETs. For this purpose, the study establishes a systematic research framework. Data were collected from (n = 330) households in the five major cities (Peshawar, Abbottabad, Mardan, Mingora, and Swabi) of Khyber Pakhtunkhwa Province via an inclusive questionnaire survey. The formulated hypotheses are evaluated and scrutinized using structural equation modeling. The results reveal that environmental concern (β = 0.245), green energy technology awareness (β = 0.362), openness to experience (β = 0.256), and green energy technology benefits (β = 0.225) positively affect consumers' desire to adopt GETs. On the other hand, green energy technology costs (β = 0.325) and green energy technology discomfort (β = 0.395) have a negative effect on consumers' adoption of GETs. The research findings emphasize the importance of increasing recognition of GETs, reforming policy frameworks, and providing budget-friendly and user-friendly technologies. Research limitations and future research perspectives are also addressed.

Climate change and rising global temperatures pose significant challenges for natural resource management. While developed economies have made progress in addressing these issues, emerging economies are still striving to achieve carbon neutrality, sustainable resource use, and environmental sustainability. This research aims to identify the factors driving carbon emissions in emerging economies over the past three decades. The study establishes a long-run relationship among the factors under investigation by employing various panel diagnostic methods. Non-parametric approaches are used to account for the non-symmetric distribution of panel data. The findings reveal that natural resource components have asymmetric impacts on carbon emissions, with oil rents reducing emissions and mineral rents increasing them. Economic growth and agricultural value added are identified as significant contributors to carbon emissions in the region. On the other hand, renewable energy consumption plays a crucial role in achieving carbon neutrality targets. Gross capital formation exhibits a mixed influence on carbon emissions, being positive and significant in lower quantiles and significantly negative in upper quantiles. These estimates are robust and align with existing literature. The study recommends sustainable resource abstraction and utilization, renewable energy production and consumption improvements, and enhanced capital formation. By providing empirical evidence and policy recommendations, this research contributes to understanding the relationship between these factors and their impact on carbon emissions, facilitating effective strategies for sustainable development and environmental preservation. Xinyang Normal University

Gas-based power plants have attracted more attention in providing electrical energy worldwide because of their lower costs and air pollution. In addition, the use of multi-carrier energy systems has several advantages, such as sustainability benefits and improving performance in supplying the energy demand. This study aims to optimize the total operation cost of multi-carrier energy systems considering the uncertain parameters. The storage technology and consumption side assist the operator in achieving lower costs based on conceptions of demand response programs. Therefore, this study presents a comprehensive mathematical model for the coordinated operation of integrated multi-carrier energy systems while the operational constraints of both gas and power networks are considered. Furthermore, this paper utilizes a new uncertainty modeling method based on Hong's two-point estimate method for addressing the uncertainties of load consumption and wind generation. The proposed model is applied to a gas and power multi-carrier energy system through four case studies. The results affirm the high performance of the presented method and investigate the influence of demand response programs in both sides of energy carriers.