The contribution of wildfire to PM2.5 trends in the USA.

Steady improvements in ambient air quality in the USA over the past several decades, in part a result of public policy1,2, have led to public health benefits1-4. However, recent trends in ambient concentrations of particulate matter with diameters less than 2.5 µm (PM2.5), a pollutant regulated under the Clean Air Act1, have stagnated or begun to reverse throughout much of the USA5. Here we use a combination of ground- and satellite-based air pollution data from 2000 to 2022 to quantify the contribution of wildfire smoke to these PM2.5 trends. We find that since at least 2016, wildfire smoke has influenced trends in average annual PM2.5 concentrations in nearly three-quarters of states in the contiguous USA, eroding about 25% of previous multi-decadal progress in reducing PM2.5 concentrations on average in those states, equivalent to 4 years of air quality progress, and more than 50% in many western states. Smoke influence on trends in the number of days with extreme PM2.5 concentrations is detectable by 2011, but the influence can be detected primarily in western and mid-western states. Wildfire-driven increases in ambient PM2.5 concentrations are unregulated under current air pollution law6 and, in the absence of further interventions, we show that the contribution of wildfire to regional and national air quality trends is likely to grow as the climate continues to warm.

Climate and health benefits of a transition from gas to electric cooking.

Household electrification is thought to be an important part of a carbon-neutral future and could also have additional benefits to adopting households such as improved air quality. However, the effectiveness of specific electrification policies in reducing total emissions and boosting household livelihoods remains a crucial open question in both developed and developing countries. We investigated a transition of more than 750,000 households from gas to electric cookstoves-one of the most popular residential electrification strategies-in Ecuador following a program that promoted induction stoves and assessed its impacts on electricity consumption, greenhouse gas emissions, and health. We estimate that the program resulted in a 5% increase in total residential electricity consumption between 2015 and 2021. By offsetting a commensurate amount of cooking gas combustion, we find that the program likely reduced national greenhouse gas emissions, thanks in part to the country's electricity grid being 80% hydropower in later parts of the time period. Increased induction stove uptake was also associated with declines in all-cause and respiratory-related hospitalizations nationwide. These findings suggest that, when the electricity grid is largely powered by renewables, gas-to-induction cooking transitions represent a promising way of amplifying the health and climate cobenefits of net-carbon-zero policies.

Using machine learning to assess the livelihood impact of electricity access.

In many regions of the world, sparse data on key economic outcomes inhibit the development, targeting and evaluation of public policy1,2. We demonstrate how advancements in satellite imagery and machine learning (ML) can help ameliorate these data and inference challenges. In the context of an expansion of the electrical grid across Uganda, we show how a combination of satellite imagery and computer vision can be used to develop local-level livelihood measurements appropriate for inferring the causal impact of electricity access on livelihoods. We then show how ML-based inference techniques deliver more reliable estimates of the causal impact of electrification than traditional alternatives when applied to these data. We estimate that grid access improves village-level asset wealth in rural Uganda by up to 0.15 standard deviations, more than doubling the growth rate during our study period relative to untreated areas. Our results provide country-scale evidence on the impact of grid-based infrastructure investment and our methods provide a low-cost, generalizable approach to future policy evaluation in data-sparse environments.

Oil and aid revenue produce equal demands for accountability as taxes in Ghana and Uganda.

Received wisdom argues that citizens more readily demand accountability from government for taxes than for nontax revenue from oil or foreign aid, giving rise to an important mechanism underlying the "resource curse," which posits that nontax revenue causes citizen quiescence and hampers government accountability. However, in developing countries, obfuscation through value-added taxes and strong popular feelings of ownership over all revenues may minimize differences across revenue sources. Identical experiments on representative samples of Ghanaians and Ugandans, and similar experiments on members of parliament, probe the effects of different sources and delivery channels of government revenues on citizens' actions to monitor governments and members of parliament (MPs') beliefs about accountability pressures. Roughly half of all citizens take action to monitor all 3 sources. However, neither Ghanaians nor Ugandans demand more accountability for taxes than oil or aid when the revenues go to the government. MPs likewise saw no difference. Citizens do differentiate between aid money given to nongovernmental organizations (NGOs) compared with revenues delivered to the government. Findings are robust to numerous alternatives and subgroups. Against strong expectations from prior research, little evidence exists showing that taxes strengthen citizens' demands for accountability or that MPs perceive differences across revenue sources in these 2 representative African countries. However, aid channeled through NGOs motivates more accountability pressures.