MAD Water: Integrating Modular, Adaptive, and Decentralized Approaches for Water Security in the Climate Change Era.

Centralized water infrastructure has, over the last century, brought safe and reliable drinking water to much of the world. But climate change, combined with aging and underfunding, is increasingly testing the limits of-and reversing gains made by-these large-scale water systems. To address these growing strains and gaps, we must assess and advance alternatives to centralized water provision and sanitation. The water literature is rife with examples of systems that are neither centralized nor networked, but still meet water needs of local communities in important ways, including: informal and hybrid water systems, decentralized water provision, community-based water management, small drinking water systems, point-of-use treatment, small-scale water vendors, and packaged water. Our work builds on these literatures by proposing a convergence approach that can integrate and explore the benefits and challenges of modular, adaptive, and decentralized ("MAD") water provision and sanitation, often foregrounding important advances in engineering technology. We further provide frameworks to evaluate justice, economic feasibility, governance, human health, and environmental sustainability as key parameters of MAD water system performance.

Personal hardship narrows the partisan gap in COVID-19 and climate change responses.

The COVID-19 pandemic in the United States was characterized by a partisan gap. Democrats were more concerned about this novel health threat, more willing to socially distance, and more likely to support policies aimed at mitigating the spread of the virus than Republicans. In cross-sectional analyses of three nationally representative survey waves in 2020, we find that adverse experience with COVID-19 is associated with a narrowing of the partisan gap. The mean difference between Republicans and Democrats in concern, policy support, and behavioral intentions narrows or even disappears at high levels of self-reported adverse experience. Reported experience does not depend on party affiliation and is predicted by local COVID-19 incidence rates. In contrast, analyses of longitudinal data and county-level incidence rates do not show a consistent relationship among experience, partisanship, and behavior or policy support. Our findings suggest that self-reported personal experience interacts with partisanship in complex ways and may be an important channel for concern about novel threats such as the COVID-19 pandemic. We find consistent results for self-reported experience of extreme weather events and climate change attitudes and policy preferences, although the association between extreme weather and experience and climate change is more tenuous.

Voting in a global pandemic: Assessing dueling influences of Covid-19 on turnout.

OBJECTIVE: We investigate the impact of a global health crisis on political behavior. Specifically, we assess the impact of Covid-19 incidence rates, and the impact of temporal and spatial proximity to the crisis, on voter turnout in the 2020 Brazilian municipal elections. METHODS: We use Ordinary Least Squares and Spatial Durbin Error models to evaluate sub-national variation in municipal-level Covid-19 incidence and voter turnout. We include controls for political, economic, health, and state context. RESULTS: Ceteris paribus, increasing deaths in the month leading up to the election from 0.01 to 1 per 1000 people is associated with a 5 percentage point decrease in turnout; higher cases and deaths earlier in the pandemic are generally associated with higher turnout. Covid-19 incidence rates in nearby municipalities affect local turnout in the same directions. CONCLUSION: Higher Covid-19 incidence near the time of the election decreases voter turnout, while incidence farther from the election increases voter turnout.