Global projections of heat exposure of older adults.

The global population is aging at the same time as heat exposures are increasing due to climate change. Age structure, and its biological and socio-economic drivers, determine populations' vulnerability to high temperatures. Here we combine age-stratified demographic projections with downscaled temperature projections to mid-century and find that chronic exposure to heat doubles across all warming scenarios. Moreover, >23% of the global population aged 69+ will inhabit climates whose 95th percentile of daily maximum temperature exceeds the critical threshold of 37.5 °C, compared with 14% today, exposing an additional 177-246 million older adults to dangerous acute heat. Effects are most severe in Asia and Africa, which also have the lowest adaptive capacity. Our results facilitate regional heat risk assessments and inform public health decision-making.

Population Aging and Heat Exposure in the 21st Century: Which U.S. Regions Are at Greatest Risk and Why?

BACKGROUND AND OBJECTIVES: The co-occurring trends of population aging and climate change mean that rising numbers of U.S. older adults are at risk of intensifying heat exposure. We estimate county-level variations in older populations' heat exposure in the early (1995-2014) and mid (2050) 21st century. We identify the extent to which rising exposures are attributable to climate change versus population aging. RESEARCH DESIGN AND METHODS: We estimate older adults' heat exposure in 3,109 counties in the 48 contiguous U.S. states. Analyses use NASA NEX Global Daily Downscaled Product (NEX-GDDP-CMIP6) climate data and county-level projections for the size and distribution of the U.S. age 69+ population. RESULTS: Population aging and rising temperatures are documented throughout the United States, with particular "hotspots" in the Deep South, Florida, and parts of the rural Midwest. Increases in heat exposure by 2050 will be especially steep in historically colder regions with large older populations in New England, the upper Midwest, and rural Mountain regions. Rising temperatures are driving exposure in historically colder regions, whereas population aging is driving exposure in historically warm southern regions. DISCUSSION AND IMPLICATIONS: Interventions to address the impacts of temperature extremes on older adult well-being should consider the geographic distribution and drivers of this exposure. In historically cooler areas where climate change is driving exposures, investments in warning systems may be productive, whereas investments in health care and social services infrastructures are essential in historically hot regions where exposures are driven by population aging.

Heterogeneous climate change impacts on electricity demand in world cities circa mid-century.

Rising ambient temperatures due to climate change will increase urban populations' exposures to extreme heat. During hot hours, a key protective adaptation is increased air conditioning and associated consumption of electricity for cooling. But during cold hours, milder temperatures have the offsetting effect of reducing consumption of electricity and other fuels for heating. We elucidate the net consequences of these opposing effects in 36 cities in different world regions. We couple reduced-form statistical models of cities' hourly responses of electric load to temperature with temporally downscaled projections of temperatures simulated by 21 global climate models (GCMs), projecting the effects of warming on the demand for electricity circa 2050. Cities' responses, temperature exposures and impacts are heterogeneous, with changes in total annual consumption ranging from [Formula: see text] to 5.7%, and peak power demand increasing by as much as 9.5% at the multi-GCM median. The largest increases are concentrated in more economically developed mid-latitude cities, with less developed urban areas in the tropics exhibiting relatively small changes. The results highlight the important role of the structure of electricity demand: large temperature increases in tropical cities are offset by their inelastic responses, which can be attributed to lower air-conditioning penetration.

Inequality in the availability of residential air conditioning across 115 US metropolitan areas.

Continued climate change is increasing the frequency, severity, and duration of populations' high temperature exposures. Indoor cooling is a key adaptation, especially in urban areas, where heat extremes are intensified-the urban heat island effect (UHI)-making residential air conditioning (AC) availability critical to protecting human health. In the United States, the differences in residential AC prevalence from one metropolitan area to another is well understood, but its intra-urban variation is poorly characterized, obscuring neighborhood-scale variability in populations' heat vulnerability and adaptive capacity. We address this gap by constructing empirically derived probabilities of residential AC for 45,995 census tracts across 115 metropolitan areas. Within cities, AC is unequally distributed, with census tracts in the urban "core" exhibiting systematically lower prevalence than their suburban counterparts. Moreover, this disparity correlates strongly with multiple indicators of social vulnerability and summer daytime surface UHI intensity, highlighting the challenges that vulnerable urban populations face in adapting to climate-change driven heat stress amplification.

Amplification of future energy demand growth due to climate change.

Future energy demand is likely to increase due to climate change, but the magnitude depends on many interacting sources of uncertainty. We combine econometrically estimated responses of energy use to income, hot and cold days with future projections of spatial population and national income under five socioeconomic scenarios and temperature increases around 2050 for two emission scenarios simulated by 21 Earth System Models (ESMs). Here we show that, across 210 realizations of socioeconomic and climate scenarios, vigorous (moderate) warming increases global climate-exposed energy demand before adaptation around 2050 by 25-58% (11-27%), on top of a factor 1.7-2.8 increase above present-day due to socioeconomic developments. We find broad agreement among ESMs that energy demand rises by more than 25% in the tropics and southern regions of the USA, Europe and China. Socioeconomic scenarios vary widely in the number of people in low-income countries exposed to increases in energy demand.

Urban emissions hotspots: Quantifying vehicle congestion and air pollution using mobile phone GPS data.

On-road emissions vary widely on time scales as short as minutes and length scales as short as tens of meters. Detailed data on emissions at these scales are a prerequisite to accurately quantifying ambient pollution concentrations and identifying hotspots of human exposure within urban areas. We construct a highly resolved inventory of hourly fluxes of CO, NO2, NOx, PM2.5 and CO2 from road vehicles on 280,000 road segments in eastern Massachusetts for the year 2012. Our inventory integrates a large database of hourly vehicle speeds derived from mobile phone and vehicle GPS data with multiple regional datasets of vehicle flows, fleet characteristics, and local meteorology. We quantify the 'excess' emissions from traffic congestion, finding modest congestion enhancement (3-6%) at regional scales, but hundreds of local hotspots with highly elevated annual emissions (up to 75% for individual roadways in key corridors). Congestion-driven reductions in vehicle fuel economy necessitated 'excess' consumption of 113 million gallons of motor fuel, worth âˆ¼ $415M, but this accounted for only 3.5% of the total fuel consumed in Massachusetts, as over 80% of vehicle travel occurs in uncongested conditions. Across our study domain, emissions are highly spatially concentrated, with 70% of pollution originating from only 10% of the roads. The 2011 EPA National Emissions Inventory (NEI) understates our aggregate emissions of NOx, PM2.5, and CO2 by 46%, 38%, and 18%, respectively. However, CO emissions agree within 5% for the two inventories, suggesting that the large biases in NOx and PM2.5 emissions arise from differences in estimates of diesel vehicle activity. By providing fine-scale information on local emission hotspots and regional emissions patterns, our inventory framework supports targeted traffic interventions, transparent benchmarking, and improvements in overall urban air quality.

Cities, traffic, and CO2: A multidecadal assessment of trends, drivers, and scaling relationships.

Emissions of CO2 from road vehicles were 1.57 billion metric tons in 2012, accounting for 28% of US fossil fuel CO2 emissions, but the spatial distributions of these emissions are highly uncertain. We develop a new emissions inventory, the Database of Road Transportation Emissions (DARTE), which estimates CO2 emitted by US road transport at a resolution of 1 km annually for 1980-2012. DARTE reveals that urban areas are responsible for 80% of on-road emissions growth since 1980 and for 63% of total 2012 emissions. We observe nonlinearities between CO2 emissions and population density at broad spatial/temporal scales, with total on-road CO2 increasing nonlinearly with population density, rapidly up to 1,650 persons per square kilometer and slowly thereafter. Per capita emissions decline as density rises, but at markedly varying rates depending on existing densities. We make use of DARTE's bottom-up construction to highlight the biases associated with the common practice of using population as a linear proxy for disaggregating national- or state-scale emissions. Comparing DARTE with existing downscaled inventories, we find biases of 100% or more in the spatial distribution of urban and rural emissions, largely driven by mismatches between inventory downscaling proxies and the actual spatial patterns of vehicle activity at urban scales. Given cities' dual importance as sources of CO2 and an emerging nexus of climate mitigation initiatives, high-resolution estimates such as DARTE are critical both for accurately quantifying surface carbon fluxes and for verifying the effectiveness of emissions mitigation efforts at urban scales.