Assessing the Impact of the Clean Development Mechanism

Annually, nearly 500 gigatonnes of CO2 are exchanged between terrestrial ecosystems and the atmosphere, and this exchange is clearly affected by human activities related to the Earth's forests. Governments are therefore willing to draft legislation incentivizing forest activities that sequester carbon to combat climate change. In this review, we examine issues related to the creation of carbon offset credits through forest conservation, burning of wood biomass in lieu of fossil fuels, and intensive commercial management that accounts for all carbon fluxes, including postharvest. In doing so, we study the costs of monitoring, measuring, and contracting; the principal-agent problem; and questions related to life cycle analyses of CO2. We can only conclude that greater care is likely needed in the future to identify carbon offsets from forestry activities if these are to be traded in emissions markets.

The Economics of Forest Carbon Offsets

As an important evaluation transformation index, exploring green total factor productivity (GTFP) trend and related key factors is significant for China's economy entering into high‐quality development and green transformation. In this study, stochastic frontier analysis (SFA) and kernel density function are used to evaluate GTFP growth trend for 36 China's industrial sectors during 2000–2016, and system generalized method of moment is used to explore their key driving factors. The results are as follows: First, SFA supplies efficient estimation for GTFP growth information. The 36 industrial sectors are classified into three emission types, that is, high‐, moderate‐, and low emission. Second, GTFP growth differs significantly in three types of sectors. With kernel density results for 36 sectors, the curve of GTFP growth has shifted upward and toward the left since 2010. For high‐emission type sectors, their kernel curve has also moved upward and toward the left. The curve of moderate‐emission type sectors significantly shifted toward the left, whereas the curve of low‐emission type moved upward. Third, based on regression estimation results, environmental regulatory policy, resource input structure, foreign direct investment, and energy‐type structure significantly influence GTFP growth. Technology innovation makes insignificant impact on GTFP for industrial sectors. In conclusion, sectorial heterogeneity should be paid more focus in order to improve their growth, especially for high‐emission type sectors. Green technology innovation is the most potential factor in the future to stimulate GTFP growth in China. © 2019 Society of Chemical Industry and John Wiley & Sons, Ltd.

Which factors stimulate industrial green total factor productivity growth rate in China? An industrial aspect

Aid and aid institutions constitute an important element of the global response to interlinked global developmental and environmental challenges. As such, these institutions are now being drawn into new arenas beyond the traditional focus on improving the livelihoods of poor people in low-income countries. Development aid, by itself, cannot “save the planet.” Nevertheless, development aid and development institutions do have the potential to become important catalytic actors in achieving developmental and global environmental objectives. This requires bold reforms and political action. Without appropriate restructuring of the international institutional architecture to confront the new development context combined with the necessary complementary policy frameworks, future aid, including aid for environmental objectives, risks substantially under-performing.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/rode.12291

Aid, Environment and Climate Change

Opening the Black Box of Carbon Finance “Additionality”: The Political Economy of Carbon Finance Effectiveness across Tanzania, Uganda, and Moldova

This research studies whether the Clean Development Mechanism (CDM) of the Kyoto Protocol achieves its objective of emission reductions in the host countries. It empirically investigates the impacts of CDM projects on CO₂ emission reductions for 60 CDM host countries over 2005-10. This research makes use of the newly-developed econometric methods for dynamic panel data models associated with X-differencing procedure. It provides evidence in support of a decline in CO₂ emissions in the CDM host countries. It has important policy implications that encourage the international community to support developing countries’ efforts towards low-carbon development via CDM projects.

https://www.econstor.eu/bitstream/10419/80945/1/722479611.pdf

Is the clean development mechanism effective for emission reductions

One of the dual objectives of the Clean Development Mechanism (CDM) of the Kyoto Protocol is to promote sustainable development in the host countries. With different CDM indicators for 58 CDM host countries over 2005-10, this paper empirically assesses whether CDM project development fulfils this objective of sustainable development. Using a unique dynamic panel data method based on long-differences of the model, this research provides evidence in support of significant contribution to sustainable development of CDM projects in the host countries. It sheds light on the role of CDM projects in the process of sustainable development with clear policy implications for developing countries and the wider world.

/pdf/is-the-clean-development-mechanism-promoting-sustainable-b95hnbxawo.pdf

Is the Clean Development Mechanism Promoting Sustainable Development

This research studies whether the Clean Development Mechanism (CDM) of the Kyoto Protocol achieves its objective of emission reductions in the host countries. It empirically investigates the impacts of CDM projects on CO? emission reductions for 60 CDM host countries over 2005-10. This research makes use of the newly-developed econometric methods for dynamic panel data models associated with X-differencing procedure. It provides evidence in support of a decline in CO? emissions in the CDM host countries. It has important policy implications that encourage the international community to support developing countries´ efforts towards low-carbon development via CDM projects.

Is the Clean Development Mechanism Effective for Emission Reductions

As the system becomes more intelligent and embedded, the operating environment is gradually changed from closed, static, and controllable to more open, dynamic, and difficult to control. As a result, the design of complex software systems is faced with many challenges arising from the uncertainty of the environment (UoE). On the one hand, ignoring the UoE to manually describe requirements is not only a tough job, but it can also hinder the discovery of potential requirements; on the other hand, it is a challenge to integrate the representation of and reasoning of UoE into the process of modeling complex systems. Based on the analysis of the characteristics of complex systems engineering, this paper takes solving the UoE caused by stakeholders preferences and complex environment context as the entry point and designs a fuzzy control decision-making framework. Specifically, the framework contributes to the spiral of complex systems while solving the UoE by constructing a closed-loop intelligent system based on automatic data flow between information space and physical space for environment sensing, uncertainty analysis, requirements mining, fuzzy reasoning, decision execution as well as feedback optimization. Finally, the framework is validated with a concrete example of an adaptive treadmill system based on the support tools developed. 

Jingjing He

Papers

Is the clean development mechanism effective for emission reductions

Is the Clean Development Mechanism Promoting Sustainable Development

Is the Clean Development Mechanism Effective for Emission Reductions

Is the Clean Development Mechanism Promoting Sustainable Development

Fuzzy control decision-making framework adapted to the uncertainty environment of complex software system