Browse FSI scholarship on geopolitics, global health, energy, cybersecurity and more.
Featured Publications
Autocrats vs. Democrats: China, Russia, America, and the New Global Disorder
A clear-eyed look from Michael McFaul at how the rise of autocratic China and Russia are compelling some to think that we have entered a new Cold War—and why we must reject that thinking in order to prevail.
Gi-Wook Shin explores how Japan, Australia, China, and India achieved economic power and sustained momentum by responding to risks and challenges such as demographic crises, brain drain, and geopolitical tensions.
Crop productivity is potentially affected by several air pollutants, although these are usually studied in isolation. A significant challenge to understanding the effects of multiple pollutants in many regions is the dearth of air quality data near agricultural fields. Here we empirically estimate the effect of four key pollutants (ozone (O3), particulate matter (PM), sulfur dioxide (SO2), and nitrogen dioxide (NO2)) on maize and soybean yields in the United States using a combination of administrative data and satellite-derived yield estimates. We identify clear negative effects of exposure to O3, PM, and SO2 in both crops, using yields measured in the vicinity of monitoring stations. We also show that while stations measuring NO2 are too sparse to reliably estimate a yield effect, the strong gradient of NO2 concentrations near power plants allows us to more precisely estimate NO2 effects using satellite measured yield gradients. The presence of some powerplants that turn on and others that shut down during the study period are particularly useful for attributing yield gradients to pollution. We estimate that total yield losses from these pollutants averaged roughly 5% for both maize and soybean over the past two decades. While all four pollutants have statistically significant effects, PM and NO2 appear more damaging to crops at current levels than O3 and SO2. Finally, we find that the significant improvement in air quality since 1999 has halved the impact of poor air quality on major crops and contributed to yield increases that represent roughly 20% of overall yield gains over that period.
Quantification of the sector-specific financial impacts of historical global warming represents a critical gap in climate change impacts assessment. The multiple decades of county-level data available from the U.S. crop insurance program – which collectively represent aggregate damages to the agricultural sector largely borne by U.S. taxpayers – present a unique opportunity to close this gap. Using econometric analysis in combination with observed and simulated changes in county-level temperature, we show that global warming has already contributed substantially to rising crop insurance losses in the U.S. For example, we estimate that county-level temperature trends have contributed $US2017 23.9 billion – or 17% – of the national-level crop insurance losses over the 1991-2017 period. Further, we estimate that observed warming contributed approximately one third of total losses in the most costly single year (2012). In addition, analyses of a large suite of global climate model simulations yield very high confidence that anthropogenic climate forcing has increased U.S. crop insurance losses. These sector-specific estimates provide important quantitative information about the financial costs of the global warming that has already occurred (including the costs of individual extreme events), as well as the economic value of mitigation and/or adaptation options.
This essay is a part of an exchange based on Francis Fukuyama’s “Making the Internet Safe for Democracy” from the April 2021 issue of the Journal of Democracy.
Natural infrastructure such as parks, forests, street trees, green roofs, and coastal vegetation is central to sustainable urban management. Despite recent progress, it remains challenging for urban decision-makers to incorporate the benefits of natural infrastructure into urban design and planning. Here, we present an approach to support the greening of cities by quantifying and mapping the diverse benefits of natural infrastructure for now and in the future. The approach relies on open-source tools, within the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) software, that compute biophysical and socio-economic metrics relevant to a variety of decisions in data-rich or data-scarce contexts. Through three case studies in China, France, and the United States, we show how spatially explicit information about the benefits of nature enhances urban management by improving economic valuation, prioritizing land use change, and promoting inclusive planning and stakeholder dialogue. We discuss limitations of the tools, including modeling uncertainties and a limited suite of output metrics, and propose research directions to mainstream natural infrastructure information in integrated urban management.
