Regional Analysis

Sustainable energy transitions involve the shift of resources between competing industrial sectors and political constituencies. Stakeholders in this process have varying degrees of political and economic power, and understanding how political economic factors influence clean energy transitions is crucial to effective policy formulation and facilitating transitions to sustainable energy systems. In partnership with the Joint Institute for Strategic Energy Analysis (JISEA), UNU-WIDER gathered together a substantial group of experts from around the world—from both developed and developing countries—to launch a multidisciplinary research project seeking to contribute to our enhanced understanding of these factors. The project sought to facilitate an energy transition that will generate very large environmental and economic benefits, particularly over the long run. The beneficiaries of clean energy transitions are highly diffuse and include future generations not yet born. This book is the distilled essence of the cross-cutting academic project. I express my sincere and professional appreciation to the large group of expert authors for their dedication to the project, and to my fellow editors in helping bring together the book for readers to enjoy and absorb along with the findings and policy implications.

Book Summary

The Grand Ethiopian Renaissance Dam (GERD) will not only be Africa’s largest dam, but it is also essential for future cooperation and development in the Nile River Basin and East African region. This book, after setting out basin-level legal and policy successes and failures of managing and sharing Nile waters, articulates the opportunities and challenges surrounding the GERD through multiple disciplinary lenses.

It sets out its possibilities as a basis for a new era of cooperation, its regional and global implications, the benefits of cooperation and coordination in dam filling, and the need for participatory and transparent decision making. By applying law, political science and hydrology to sharing water resources in general and to large-scale dam building, filling and operating in particular, it offers concrete qualitative and quantitative options that are essential to promote cooperation and coordination in utilising and preserving Nile waters. The book incorporates the economic dimension and draws on recent developments including: the signing of a legally binding contract by Egypt, Ethiopia and Sudan to carry out an impact assessment study; the possibility that the GERD might be partially operational very soon, the completion of transmission lines from GERD to Addis Ababa; and the announcement of Sudan to commence construction of transmission lines from GERD to its main cities. The implications of these are assessed and lessons learned for transboundary water cooperation and conflict management.

Mercury (Hg) emissions pose a global problem that requires global cooperation for a solution. However, neither emissions nor regulations are uniform world-wide, and hence the impacts of regulations are also likely to vary regionally. We report here an approach to model the effectiveness of regulations at different scales (local, regional, global) in reducing Hg deposition and fish Hg concentrations in the Laurentian Great Lakes (GL) region. The potential effects of global change on deposition are also modeled. We focus on one of the most vulnerable communities within the region, an Indigenous tribe in Michigan's Upper Peninsula (UP) with a high fish consumption rate. For the GL region, elements of global change (climate, biomass burning, land use) are projected to have modest impacts (<5% change from the year 2000) on Hg deposition. For this region, our estimate of the effects of elimination of anthropogenic emissions is a 70% decrease in deposition, while our minimal regulation scenario increases emissions by 35%. Existing policies have the potential to reduce deposition by 20% with most of the reduction attributable to U.S. policies. Local policies within the Great Lakes region show little effect, and global policy as embedded in the Minamata Convention is projected to decrease deposition by approximately 2.8%. Even within the GL region, effects of policy are not uniform; areas close to emission sources (Illinois, Indiana, Ohio, Pennsylvania) experience larger decreases in deposition than other areas including Michigan's UP. The UP landscape is highly sensitive to Hg deposition, with nearly 80% of lakes estimated to be impaired. Sensitivity to mercury is caused primarily by the region's abundant wetlands. None of the modeled policy scenarios are projected to reduce fish Hg concentrations to the target that would be safe for the local tribe. Regions like Michigan's UP that are highly sensitive to mercury deposition and that will see little reduction in deposition due to regulations require more aggressive policies to reduce emissions to achieve recovery. We highlight scientific uncertainties that continue to limit our ability to accurately predict fish Hg changes over time.

Climate change and freshwater quality are well-linked. Changes in climate result in changes in streamflow and rising water temperatures, which impact biochemical reaction rates and increase stratification in lakes and reservoirs. Using two water quality modeling systems (the Hydrologic and Water Quality System; HAWQS and US Basins), five climate models, and two greenhouse gas (GHG) mitigation policies, we assess future water quality in the continental U.S. to 2100 considering four water quality parameters: water temperature, dissolved oxygen, total nitrogen, and total phosphorus. Once these parameters are aggregated into a water quality index, we find that, while the water quality models differ under the baseline, there is more agreement between future projections. In addition, we find that the difference in national-scale economic benefits across climate models is generally larger than the difference between the two water quality models. Both water quality models find that water quality will more likely worsen in the East than in the West. Under the business-as-usual emissions scenario, we find that climate change is likely to cause economic impacts ranging from 1.2 to 2.3 (2005 billion USD/year) in 2050 and 2.7 to 4.8 in 2090 across all climate and water quality models.

Changes in tropical wetland, ruminant or rice emissions are thought to have played a role in recent variations in atmospheric methane (CH4) concentrations. India has the world’s largest ruminant population and produces ~ 20% of the world’s rice. Therefore, changes in these sources could have significant implications for global warming. Here, we infer India’s CH4 emissions for the period 2010–2015 using a combination of satellite, surface and aircraft data. We apply a high-resolution atmospheric transport model to simulate data from these platforms to infer fluxes at sub-national scales and to quantify changes in rice emissions. We find that average emissions over this period are 22.0 (19.6–24.3) Tg yr−1, which is consistent with the emissions reported by India to the United Framework Convention on Climate Change. Annual emissions have not changed significantly (0.2 ± 0.7 Tg yr−1) between 2010 and 2015, suggesting that major CH4 sources did not change appreciably. These findings are in contrast to another major economy, China, which has shown significant growth in recent years due to increasing fossil fuel emissions. However, the trend in a global emission inventory has been overestimated for China due to incorrect rate of fossil fuel growth. Here, we find growth has been overestimated in India but likely due to ruminant and waste sectors.

Extreme precipitation events pose a significant threat to public safety, natural and managed resources, and the functioning of society. Changes in such high-impact, low-probability events have profound implications for decision-making, preparation and costs of mitigation and adaptation efforts. Understanding how extreme precipitation events will change in the future and enabling consistent and robust projections is therefore important for the public and policymakers as we prepare for consequences of climate change.

Projection of extreme precipitation events, however, particularly at the local scale, presents a critical challenge: the climate model-based simulations of precipitation that we currently rely on for such projections—general circulation models (GCMs)—are not very realistic, mainly due to the models’ coarse spatial resolution. This coarse resolution precludes adequate representation of highly influential, small-scale features such as moisture convection and topography. Regional circulation models (RCMs) provide much higher resolution and better representation of such features, and are thus often perceived as an optimum approach to producing more accurate heavy precipitation statistics than GCMs. However, they are much more computationally intensive, time-consuming and expensive to run.

In a previous paper, the researchers developed an algorithm that detects the occurrence of heavy precipitation events based on climate models’ well-resolved, large-scale atmospheric circulation conditions associated with those events—rather than relying on these models’ simulated precipitation. The algorithm’s results corresponded with observations with much greater precision than the model-simulated precipitation.

In this paper, the researchers show that the performance of the new algorithm in detecting heavy precipitation event is not dependent on the model resolution and even better than that of precipitation simulated from RCMs. The algorithm thus presents a robust and economic way to assess extreme precipitation frequency across a broad range of GCMs and multiple climate change scenarios with minimal computational requirements.   

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