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BackgroundClimate change negatively impacts human health through heat stress and exposure to worsened air pollution, amongst other pathways. Indoor use of air conditioning can be an effective strategy to reduce heat exposure. However, increased air conditioning use increases emissions of air pollutants from power plants, in turn worsening air quality and human health impacts. We used an interdisciplinary linked model system to quantify the impacts of heat-driven adaptation through building cooling demand on air-quality-related health outcomes in a representative mid-century climate scenario.Methods and findingsWe used a modeling system that included downscaling historical and future climate data with the Weather Research and Forecasting (WRF) model, simulating building electricity demand using the Regional Building Energy Simulation System (RBESS), simulating power sector production and emissions using MyPower, simulating ambient air quality using the Community Multiscale Air Quality (CMAQ) model, and calculating the incidence of adverse health outcomes using the Environmental Benefits Mapping and Analysis Program (BenMAP). We performed simulations for a representative present-day climate scenario and 2 representative mid-century climate scenarios, with and without exacerbated power sector emissions from adaptation in building energy use. We find that by mid-century, climate change alone can increase fine particulate matter (PM2.5) concentrations by 58.6% (2.50 μg/m3) and ozone (O3) by 14.9% (8.06 parts per billion by volume [ppbv]) for the month of July. A larger change is found when comparing the present day to the combined impact of climate change and increased building energy use, where PM2.5 increases 61.1% (2.60 μg/m3) and O3 increases 15.9% (8.64 ppbv). Therefore, 3.8% of the total increase in PM2.5 and 6.7% of the total increase in O3 is attributable to adaptive behavior (extra air conditioning use). Health impacts assessment finds that for a mid-century climate change scenario (with adaptation), annual PM2.5-related adult mortality increases by 13,547 deaths (14 concentration–response functions with mean incidence range of 1,320 to 26,481, approximately US$126 billion cost) and annual O3-related adult mortality increases by 3,514 deaths (3 functions with mean incidence range of 2,175 to 4,920, approximately US$32.5 billion cost), calculated as a 3-month summer estimate based on July modeling. Air conditioning adaptation accounts for 654 (range of 87 to 1,245) of the PM2.5-related deaths (approximately US$6 billion cost, a 4.8% increase above climate change impacts alone) and 315 (range of 198 to 438) of the O3-related deaths (approximately US$3 billion cost, an 8.7% increase above climate change impacts alone). Limitations of this study include modeling only a single month, based on 1 model-year of future climate simulations. As a result, we do not project the future, but rather describe the potential damages from interactions arising between climate, energy use, and air quality.ConclusionsThis study exa...

Past studies have established strong connections between meteorology and air quality, via chemistry, transport, and natural emissions. A less understood linkage between weather and air quality is the temperature-dependence of emissions from electricity generating units (EGUs), associated with high electricity demand to support building cooling on hot days. This study quantifies the relationship between ambient surface temperatures and EGU air emissions (CO, SO, and NO) using historical data. We find that EGUs in the Eastern U.S. region from 2007 to 2012 exhibited a 3.87% ± 0.41% increase in electricity generation per °C increase during summer months. This is associated with a 3.35%/°C ± 0.50%/°C increase in SO emissions, a 3.60%/°C ± 0.49%/°C increase in NO emissions, and a 3.32%/°C ± 0.36%/°C increase in CO emissions. Sensitivities vary by year and by pollutant, with SO both the highest sensitivity (5.04% in 2012) and lowest sensitivity (2.19% in 2007) in terms of a regional average. Texas displays 2007-2012 sensitivities of 2.34%/°C ± 0.28%/°C for generation, 0.91%/°C ± 0.25%/°C for SO emissions, 2.15%/°C ± 0.29%/°C for NO emissions, and 1.78%/°C ± 0.22%/°C for CO emissions. These results suggest demand-side and supply side technological improvements and fuel choice could play an important role in cost-effective reduction of carbon emissions and air pollution.

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Spatial variability in yields and greenhouse gas emissions from soils has been identified as a key source of variability in life cycle assessments (LCAs) of agricultural products such as cellulosic ethanol. This study aims to conduct an LCA of cellulosic ethanol production from switchgrass in a way that captures this spatial variability and tests results for sensitivity to using spatially averaged results. The Environment Policy Integrated Climate (EPIC) model was used to calculate switchgrass yields, greenhouse gas (GHG) emissions, and nitrogen and phosphorus emissions from crop production in southern Wisconsin and Michigan at the watershed scale. These data were combined with cellulosic ethanol production data via ammonia fiber expansion and dilute acid pretreatment methods and region-specific electricity production data into an LCA model of eight ethanol production scenarios. Standard deviations from the spatial mean yields and soil emissions were used to test the sensitivity of net energy ratio, global warming potential intensity, and eutrophication and acidification potential metrics to spatial variability. Substantial variation in the eutrophication potential was also observed when nitrogen and phosphorus emissions from soils were varied. This work illustrates the need for spatially explicit agricultural production data in the LCA of biofuels and other agricultural products.

The current or “conventional” paradigm for producing process energy in a biorefinery processing cellulosic biomass is on‐site energy recovery through combustion of residual solids and biogas generated by the process. Excess electricity is then exported, resulting in large greenhouse gas (GHG) credits. However, this approach will cause lifecycle GHG emissions of biofuels to increase as more renewable energy sources (wind, solar, etc.) participate in grid‐electricity generation, and the GHG credits from displacing fossil fuel decrease. To overcome this drawback, a decentralized (depot‐based) biorefinery can be integrated with a coal‐fired power plant near a large urban area. In an integrated, decentralized, depot‐based biorefinery (IDB), the residual solids are co‐fired with coal either in the adjacent power plant or in coal‐fired boilers elsewhere to displace coal. An IDB system does not rely on indirect GHG credits through grid‐electricity displacement. In an IDB system, biogas from the wastewater treatment facility is also upgraded to biomethane and used as a transportation biofuel. The GHG savings per unit of cropland in the IDB systems (2.7–2.9 MgCO2/ha) are 1.5–1.6 fold greater than those in a conventional centralized system (1.7–1.8 MgCO2/ha). Importantly, the biofuel selling price in the IDBs is lower by 28–30 cents per gasoline‐equivalent liter than in the conventional centralized system. Furthermore, the total capital investment per annual biofuel volume in the IDB is much lower (by ~80%) than that in the conventional centralized system. Therefore, utilization of biomethane and residual solids in the IDB systems leads to much lower biofuel selling prices and significantly greater GHG savings per unit of cropland participating in the biorefinery system compared to the conventional centralized biorefineries.

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