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    Road to glory or highway to hell? Global road access and climate change mitigation
    (Bristol : IOP Publ., 2020) Wenz, Leonie; Weddige, Ulf; Jakob, Michael; Steckel, Jan Christoph
    Transportation infrastructure is considered a key factor for economic development and poverty alleviation. The United Nations have explicitly included the provision of transport infrastructure access, e.g. through all-season road access, in their Sustainable Development Goal agenda (SDGs, target 9.1). Yet, little is known about the number of people lacking access to roads worldwide, the costs of closing existing access gaps and the implications of additional roads for other sustainability concerns such as climate change mitigation (SDG-13). Here we quantify, for 250 countries and territories, the percentage of population without road access in 2 km. We find that infrastructure investments required to provide quasi-universal road access are about USD 3 trillion. We estimate that the associated cumulative CO2 emissions from construction work and additional traffic until the end of the century amount to roughly 16 Gt. Our geographically explicit global analysis provides a starting point for refined regional studies and for the quantification of further environmental and social implications of SDG-9.1.
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    Nighttime light data reveal lack of full recovery after hurricanes in Southern US
    (Bristol : IOP Publ., 2022) Barton-Henry, Kelsey; Wenz, Leonie
    As the climate warms, many areas of the world are experiencing more frequent and extreme weather events. Hurricanes carry some of the costliest short-term socioeconomic repercussions via economic losses and people displaced. There is, however, little quantitative evidence regarding medium- to long-term effects, nor factors moderating recovery. Here we show that areas affected by hurricanes of category 4 or 5 in the southern US between 2014 and 2020 generally do not demonstrate full recovery in the longer term. Utilizing Visible Infrared Imaging Radiometer Suite nighttime light (NTL) data as a proxy for economic activity and population density, we build a timeline of recovery via NTL radiance levels. We exploit the difference in the eligibility for aid from the Federal Emergency Management Agency (FEMA) to apply a quasi-experimental method to identify changes in NTL radiance attributable to hurricanes. We find that after three years, affected areas demonstrate a reduction in NTL radiance levels of between 2% and 14% compared to the pre-disaster period. Combining these results with machine learning techniques, we are able to investigate those factors that contribute to recovery. We find counties demonstrating smaller reductions in NTL radiance levels in the months following the hurricane are buoyed by the amount of FEMA aid received, but that this aid does not foster a longer-term return to normal radiance levels. Investigating areas receiving FEMA aid at the household and individual level, we find age and employment are more important than other demographic factors in determining hurricane recovery over time. These findings suggest that aid may be more important in motivating short-term recovery for public entities than for individuals but is not sufficient to guarantee complete recovery in the longer term.