Social science research to inform solar geoengineering.

What are the benefits and drawbacks, and for whom?.

Modeling migration patterns in the USA under sea level rise.

Sea level rise in the United States will lead to large scale migration in the future. We propose a framework to examine future climate migration patterns using models of human migration. Our framework requires that we distinguish between historical versus climate driven migration and recognizes how the impacts of climate change can extend beyond the affected area. We apply our framework to simulate how migration, driven by sea level rise, differs from baseline migration patterns. Specifically, we couple a sea level rise model with a data-driven model of human migration and future population projections, creating a generalized joint model of climate driven migration that can be used to simulate population distributions under potential future sea level rise scenarios. The results of our case study suggest that the effects of sea level rise are pervasive, expanding beyond coastal areas via increased migration, and disproportionately affecting some areas of the United States.

Climate econometric models indicate solar geoengineering would reduce inter-country income inequality.

Exploring heterogeneity in the economic impacts of solar geoengineering is a fundamental step towards understanding the risk tradeoff associated with a geoengineering option. To evaluate impacts of solar geoengineering and greenhouse gas-driven climate change on equal terms, we apply macroeconomic impact models that have been widely applied to climate change impacts assessment. Combining historical evidence with climate simulations of mean annual temperature and precipitation, we project socio-economic outcomes under high anthropogenic emissions for stylized climate scenarios in which global temperatures are stabilized or over-cooled by blocking solar radiation. We find impacts of climate changes on global GDP-per-capita by the end of the century are temperature-driven, highly dispersed, and model dependent. Across all model specifications, however, income inequality between countries is lower with solar geoengineering. Consistent reduction in inter-country inequality can inform discussions of the distribution of impacts of solar geoengineering, a topic of concern in geoengineering ethics and governance debates.

Can virtual water trade save water resources?

At times, certain areas of China suffering from water shortages. While China's government is spurring innovation and infrastructure to help head off such problems, it may be that some water conservation could help as well. It is well-known that water is embodied in traded goods-so called "virtual water trade" (VWT). In China, it seems that many water-poor areas are perversely engaged in VWT. Further, China is engaging in the global trend of fragmentation in production, even as an interregional phenomenon. Perhaps something could be learned about conserving or reducing VWT, if we knew where and how it is practiced. Given some proximate causes, perhaps viable policies could be formulated. To this end, we employ China's multiregional input-output tables straddling two periods to trace the trade of a given region's three types of goods: local final goods, local intermediate goods, and goods that shipped to other regions and countries. We find that goods traded interregionally in China in 2012 embodied 30.4% of all water used nationwide. Nationwide, water use increased substantially over 2007-2012 due to greater shipment volumes of water-intensive products. In fact, as suspected, the rise in value chain-related trade became a major contributing factor. Coastal areas tended to be net receivers of VWT from interior provinces, although reasons differed, e.g. Shanghai received more to fulfill final demand (67.8% of net inflow) and Zhejiang for value-chain related trade (40.2% of net inflow). In sum, the variety of our findings reveals an urgent need to consider trade types and water scarcity when developing water resource allocation and conservation policies.

New approach for optimal electricity planning and dispatching with hourly time-scale air quality and health considerations.

Integrating accurate air quality modeling with decision making is hampered by complex atmospheric physics and chemistry and its coupling with atmospheric transport. Existing approaches to model the physics and chemistry accurately lead to significant computational burdens in computing the response of atmospheric concentrations to changes in emissions profiles. By integrating a reduced form of a fully coupled atmospheric model within a unit commitment optimization model, we allow, for the first time to our knowledge, a fully dynamical approach toward electricity planning that accurately and rapidly minimizes both cost and health impacts. The reduced-form model captures the response of spatially resolved air pollutant concentrations to changes in electricity-generating plant emissions on an hourly basis with accuracy comparable to a comprehensive air quality model. The integrated model allows for the inclusion of human health impacts into cost-based decisions for power plant operation. We use the new capability in a case study of the state of Georgia over the years of 2004-2011, and show that a shift in utilization among existing power plants during selected hourly periods could have provided a health cost savings of $175.9 million dollars for an additional electricity generation cost of $83.6 million in 2007 US dollars (USD2007). The case study illustrates how air pollutant health impacts can be cost-effectively minimized by intelligently modulating power plant operations over multihour periods, without implementing additional emissions control technologies.