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Even as the evidence of global warming mounts, the international response to this serious threat is coming unraveled. The United States has formally withdrawn from the 1997 Kyoto Protocol; other key nations are facing difficulty in meeting their Kyoto commitments; and developing countries face no limit on their emissions of the gases that cause global warming. In this clear and cogent book-reissued in paperback with an afterword that comments on recent events--David Victor explains why the Kyoto Protocol was never likely to become an effective legal instrument. He explores how its collapse offers opportunities to establish a more realistic alternative. Global warming continues to dominate environmental news as legislatures worldwide grapple with the process of ratification of the December 1997 Kyoto Protocol. The collapse of the November 2000 conference at the Hague showed clearly how difficult it will be to bring the Kyoto treaty into force. Yet most politicians, policymakers, and analysts hailed it as a vital first step in slowing greenhouse warming. David Victor was not among them. Kyoto's fatal flaw, Victor argues, is that it can work only if emissions trading works. The Protocol requires industrialized nations to reduce their emissions of greenhouse gases to specific targets. Crucially, the Protocol also provides for so-called \"emissions trading,\" whereby nations could offset the need for rapid cuts in their own emissions by buying emissions credits from other countries. But starting this trading system would require creating emission permits worth two trillion dollars--the largest single invention of assets by voluntary international treaty in world history. Even if it were politically possible to distribute such astronomical sums, the Protocol does not provide for adequate monitoring and enforcement of these new property rights. Nor does it offer an achievable plan for allocating new permits, which would be essential if the system were expanded to include developing countries. The collapse of the Kyoto Protocol--which Victor views as inevitable--will provide the political space to rethink strategy. Better alternatives would focus on policies that control emissions, such as emission taxes. Though economically sensible, however, a pure tax approach is impossible to monitor in practice. Thus, the author proposes a hybrid in which governments set targets for both emission quantities and tax levels. This offers the important advantages of both emission trading and taxes without the debilitating drawbacks of each. Individuals at all levels of environmental science, economics, public policy, and politics-from students to professionals--and anyone else hoping to participate in the debate over how to slow global warming will want to read this book.

The intensification of the global climate crisis has thrust the imperative of controlling greenhouse gas emissions into the spotlight, commanding the attention of individuals, industries, and nations alike. Reducing carbon emissions and maximizing carbon utilization have assumed paramount significance in the contemporary industrial landscape. Within this overarching context, Carbon Capture, Utilization, and Storage (CCUS) technology has emerged as a transformative and pivotal means of addressing the multifaceted challenges posed by escalating emissions.Among the diverse CCUS methodologies, enhanced oil recovery (EOR) has distinguished itself as an up-and-coming technique, offering economic viability and environmental impact. Simultaneously, enhanced gas recovery (EGR) has recently gained momentum due to its remarkable potential as a negative carbon technology.This study employs an integrated approach to gain a deeper and more precise understanding of how reservoir heterogeneity influences the geological utilization of CO2.It commences with the utilization of FLAC3D and the \"gast\" tool in R language to generate comprehensive data fields that quantitatively characterize heterogeneity in terms of porosity standard deviation and correlation length. Subsequently, the research conducts a comprehensive and methodical analysis of how heterogeneity impacts CO2 gas displacement.

Plants remove carbon dioxide from the atmosphere through photosynthesis. Because agriculture’s productivity is based on this process, a combination of technologies to reduce emissions and enhance soil carbon storage can allow this sector to achieve net negative emissions while maintaining high productivity. Unfortunately, current row-crop agricultural practice generates about 5% of greenhouse gas emissions in the United States and European Union. To reduce these emissions, significant effort has been focused on changing farm management practices to maximize soil carbon. In contrast, the potential to reduce emissions has largely been neglected. Through a combination of innovations in digital agriculture, crop and microbial genetics, and electrification, we estimate that a 71% (1,744 kg CO₂e/ha) reduction in greenhouse gas emissions from row crop agriculture is possible within the next 15 y. Importantly, emission reduction can lower the barrier to broad adoption by proceeding through multiple stages with meaningful improvements that gradually facilitate the transition to net negative practices. Emerging voluntary and regulatory ecosystems services markets will incentivize progress along this transition pathway and guide public and private investments toward technology development. In the difficult quest for net negative emissions, all tools, including emission reduction and soil carbon storage, must be developed to allow agriculture to maintain its critical societal function of provisioning society while, at the same time, generating environmental benefits.

The purpose of this paper is to explore whether the implementation of carbon emissions trading policy (CETP) promotes carbon finance, proxied by investment and financing facilitating carbon emissions reduction (IFCER), and reduces carbon emissions. Evidence shows that first, CETP is effective in stimulating IFCER and reducing carbon emissions. Second, the effects of CETP persist over time. Third, the effects of CETP taking effect in pilot regions can spill over to non-pilot regions nearby. Fourth, the effect is more pronounced in eastern and wealthy regions. Finally, R&D and industrial upgrading have a mediating effect linking CETP to IFCER and carbon emissions.

This book presents recent advances in green communications and networking for wired, wireless, and smart-grid networks. These technologies not only provide the emission reduction and energy savings in Information and Communication Technology (ICT) products and services, but also enable low GHG emissions in other industries, such as electric power. The text covers new algorithms, protocols, and network architectures to make cellular networks more energy efficient. It also includes a rich set of references in each chapter.

This research investigates the application of machine learning models to optimise renewable energy systems and contribute to achieving Net Zero emissions targets. The primary objective is to evaluate how machine learning can improve energy forecasting, grid management, and storage optimisation, thereby enhancing the reliability and efficiency of renewable energy sources. The methodology involved the application of various machine learning models, including Long Short-Term Memory (LSTM), Random Forest, Support Vector Machines (SVMs), and ARIMA, to predict energy generation and demand patterns. These models were evaluated using metrics such as Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). Key findings include a 15% improvement in grid efficiency after optimisation and a 10–20% increase in battery storage efficiency. Random Forest achieved the lowest MAE, reducing prediction error by approximately 8.5%. The study quantified CO2 emission reductions by energy source, with wind power accounting for a 15,000-ton annual reduction, followed by hydropower and solar reducing emissions by 10,000 and 7500 tons, respectively. The research concludes that machine learning can significantly enhance renewable energy system performance, with measurable reductions in errors and emissions. These improvements could help close the “ambition gap” by 20%, supporting global efforts to meet the 1.5 °C Paris Agreement targets.

Tropical deforestation is estimated to cause about one-quarter of anthropogenic carbon emissions, loss of biodiversity, and other environmental services. United Nations Framework Convention for Climate Change talks are now considering mechanisms for avoiding deforestation (AD), but the economic potential of AD has yet to be addressed. We use three economic models of global land use and management to analyze the potential contribution of AD activities to reduced greenhouse gas emissions. AD activities are found to be a competitive, low-cost abatement option. A program providing a 10% reduction in deforestation from 2005 to 2030 could provide 0.3-0.6 Gt (1 Gt = 1 x 10⁵ g) CO₂·yr⁻¹ in emission reductions and would require $0.4 billion to $1.7 billion·yr⁻¹ for 30 years. A 50% reduction in deforestation from 2005 to 2030 could provide 1.5-2.7 Gt CO₂·yr⁻¹ in emission reductions and would require $17.2 billion to $28.0 billion·yr⁻¹. Finally, some caveats to the analysis that could increase costs of AD programs are described.

Though interfirm collaboration on carbon emission reduction, the cross-enterprise flow of emission reduction resources and improved efficiency in greenhouse gas reduction can be realized. Especially in the context of big data, enterprises can find suitable partners for emission reduction faster and more accurately through interfirm collaboration. However, similar to other cooperative modes, revenue allocation is the key to ensuring the stability of the collaborative emission reduction system. Based on the premise of carbon trading, this paper discusses revenue allocation among enterprises participating in the collaborative emission reduction process under complete information in a big data context. Specifically, we constructed a Shapley value analysis model of revenue allocation for interfirm collaboration on carbon emission reduction, and amended this model with investment cost and risk-bearing. Consequently, this research provides not only a theoretical basis for solving the problem of revenue distribution in the process of collaborative emission reductions among enterprises but also a theoretical guide for enterprises countermeasures following the completion of China's future carbon trading mechanism.

Owing to the rising concerns about environmental degradation worldwide, firms in several developed and developing countries are pursuing carbon emission reduction targets. In addition, in recent years, there is evidence of a shift in consumer preferences in favour of low-carbon products. Using a theoretical model, where the shift in consumer preferences is explicitly incorporated, we evaluate the impact of carbon emission reduction cost-sharing on supply chain profit. In our model, consumers are willing to pay a higher price for low-carbon products and hence the retailer considers sharing the cost of carbon emission reduction with the manufacturer. Our model also includes a carbon trading mechanism. We identify a range of carbon emission reduction cost-sharing such that both supply chain enterprises are better-off. We find that, while achieving the aim of carbon emission reduction, consumer preference for low-carbon products can benefit both supply chain enterprises. Numerical simulations show that carbon emission reduction cost-sharing increases the retailer’s order quantity as well as the profit and hence there is an incentive for the two supply chain enterprises to cooperate.