Combining Satellite-Derived PM2.5 Data and a Reduced-Form Air Quality Model to Support Air Quality Analysis in US Cities.

Air quality models can support pollution mitigation design by simulating policy scenarios and conducting source contribution analyses. The Intervention Model for Air Pollution (InMAP) is a powerful tool for equitable policy design as its variable resolution grid enables intra-urban analysis, the scale of which most environmental justice inquiries are levied. However, InMAP underestimates particulate sulfate and overestimates particulate ammonium formation, errors that limit the model's relevance to city-scale decision-making. To reduce InMAP's biases and increase its relevancy for urban-scale analysis, we calculate and apply scaling factors (SFs) based on observational data and advanced models. We consider both satellite-derived speciated PM2.5 from Washington University and ground-level monitor measurements from the U.S. Environmental Protection Agency, applied with different scaling methodologies. Relative to ground-monitor data, the unscaled InMAP model fails to meet a normalized mean bias performance goal of <±10% for most of the PM2.5 components it simulates (pSO4: -48%, pNO3: 8%, pNH4: 69%), but with city-specific SFs it achieves the goal benchmarks for every particulate species. Similarly, the normalized mean error performance goal of <35% is not met with the unscaled InMAP model (pSO4: 53%, pNO3: 52%, pNH4: 80%) but is met with the city-scaling approach (15%-27%). The city-specific scaling method also improves the R 2 value from 0.11 to 0.59 (ranging across particulate species) to the range of 0.36-0.76. Scaling increases the percent pollution contribution of electric generating units (EGUs) (nationwide 4%) and non-EGU point sources (nationwide 6%) and decreases the agriculture sector's contribution (nationwide -6%).

Nationwide and Regional PM2.5-Related Air Quality Health Benefits From the Removal of Energy-Related Emissions in the United States.

Clean energy policy can provide substantial health benefits through improved air quality. As ambitious clean energy proposals are increasingly considered and adopted across the United States (US), quantifying the benefits of removal of such large air pollution emissions sources is crucial to understanding potential societal impacts of such policy. In this study, we estimate health benefits resulting from the elimination of emissions of fine particulate matter (PM2.5), sulfur dioxide, and nitrogen oxides from the electric power, transportation, building, and industrial sectors in the contiguous US. We use EPA's CO-Benefits Risk Assessment screening tool to estimate health benefits resulting from the removal of PM2.5-related emissions from these energy-related sectors. We find that nationwide efforts to eliminate energy-related emissions could prevent 53,200 (95% CI: 46,900-59,400) premature deaths each year and provide $608 billion ($537-$678 billion) in benefits from avoided PM2.5-related illness and death. We also find that an average of 69% (range: 32%-95%) of the health benefits from emissions removal remain in the emitting region. Our study provides an indication of the potential scale and distribution of public health benefits that could result from ambitious regional and nationwide clean energy and climate mitigation policy.

Satellite Monitoring for Air Quality and Health.

Data from satellite instruments provide estimates of gas and particle levels relevant to human health, even pollutants invisible to the human eye. However, the successful interpretation of satellite data requires an understanding of how satellites relate to other data sources, as well as factors affecting their application to health challenges. Drawing from the expertise and experience of the 2016-2020 NASA HAQAST (Health and Air Quality Applied Sciences Team), we present a review of satellite data for air quality and health applications. We include a discussion of satellite data for epidemiological studies and health impact assessments, as well as the use of satellite data to evaluate air quality trends, support air quality regulation, characterize smoke from wildfires, and quantify emission sources. The primary advantage of satellite data compared to in situ measurements, e.g., from air quality monitoring stations, is their spatial coverage. Satellite data can reveal where pollution levels are highest around the world, how levels have changed over daily to decadal periods, and where pollutants are transported from urban to global scales. To date, air quality and health applications have primarily utilized satellite observations and satellite-derived products relevant to near-surface particulate matter <2.5 µm in diameter (PM2.5) and nitrogen dioxide (NO2). Health and air quality communities have grown increasingly engaged in the use of satellite data, and this trend is expected to continue. From health researchers to air quality managers, and from global applications to community impacts, satellite data are transforming the way air pollution exposure is evaluated.

Satellite Formaldehyde to Support Model Evaluation.

Formaldehyde (HCHO), a known carcinogen classified as a hazardous pollutant by the United States Environmental Protection Agency (U.S. EPA), is measured through monitoring networks across the U.S. Since these data are limited in spatial and temporal extent, model simulations from the U.S. EPA Community Multiscale Air Quality (CMAQ) model are used to estimate ambient HCHO exposure for the EPA National Air Toxics Assessment (NATA). Here, we employ satellite HCHO retrievals from the Ozone Monitoring Instrument (OMI)-the NASA retrieval developed by the Smithsonian Astrophysical Observatory (SAO), and the European Union Quality Assurance for Essential Climate Variables (QA4ECV) retrieval-to evaluate three CMAQ configurations, spanning the summers of 2011 and 2016, with differing biogenic emissions inputs and chemical mechanisms. These CMAQ configurations capture the general spatial and temporal behavior of both satellite retrievals, but underestimate column HCHO, particularly in the western U.S. In the southeastern U.S., the comparison with OMI HCHO highlights differences in modeled meteorology and biogenic emissions even with differences in satellite retrievals. All CMAQ configurations show low daily correlations with OMI HCHO (r = 0.26 - 0.38), however, we find higher monthly correlations (r = 0.52 - 0.73), and the models correlate best with the OMI-QA4ECV product. Compared to surface observations, we find improved agreement over a 24-hour period compared to afternoon-only, suggesting daily HCHO amounts are captured with more accuracy than afternoon amounts. This work highlights the potential for synergistic improvements in modeling and satellite retrievals to support near-surface HCHO estimates for the NATA and other applications.

Integrating Air Quality and Public Health Benefits in U.S. Decarbonization Strategies.

Research on air quality and human health "co-benefits" from climate mitigation strategies represents a growing area of policy-relevant scholarship. Compared to other aspects of climate and energy policy evaluation, however, there are still relatively few of these co-benefits analyses. This sparsity reflects a historical disconnect between research quantifying energy and climate, and research dealing with air quality and health. The air quality co-benefits of climate, clean energy, and transportation electrification policies are typically assessed with models spanning social, physical, chemical, and biological systems. This review article summarizes studies to date and presents methods used for these interdisciplinary analyses. Studies in the peer-reviewed literature (n = 26) have evaluated carbon pricing, renewable portfolio standards, energy efficiency, renewable energy deployment, and clean transportation. A number of major findings have emerged from these studies: [1] decarbonization strategies can reduce air pollution disproportionally on the most polluted days; [2] renewable energy deployment and climate policies offer the highest health and economic benefits in regions with greater reliance on coal generation; [3] monetized air quality health co-benefits can offset costs of climate policy implementation; [4] monetized co-benefits typically exceed the levelized cost of electricity (LCOE) of renewable energies; [5] Electric vehicle (EV) adoption generally improves air quality on peak pollution days, but can result in ozone dis-benefits in urban centers due to the titration of ozone with nitrogen oxides. Drawing from these published studies, we review the state of knowledge on climate co-benefits to air quality and health, identifying opportunities for policy action and further research.

Using Satellites to Track Indicators of Global Air Pollution and Climate Change Impacts: Lessons Learned From a NASA-Supported Science-Stakeholder Collaborative.

The 2018 NASA Health and Air Quality Applied Science Team (HAQAST) "Indicators" Tiger Team collaboration between NASA-supported scientists and civil society stakeholders aimed to develop satellite-derived global air pollution and climate indicators. This Commentary shares our experience and lessons learned. Together, the team developed methods to track wildfires, dust storms, pollen counts, urban green space, nitrogen dioxide concentrations and asthma burdens, tropospheric ozone concentrations, and urban particulate matter mortality. Participatory knowledge production can lead to more actionable information but requires time, flexibility, and continuous engagement. Ground measurements are still needed for ground truthing, and sustained collaboration over time remains a challenge.

Methods, availability, and applications of PM2.5 exposure estimates derived from ground measurements, satellite, and atmospheric models.

Fine particulate matter (PM2.5) is a well-established risk factor for public health. To support both health risk assessment and epidemiological studies, data are needed on spatial and temporal patterns of PM2.5 exposures. This review article surveys publicly available exposure datasets for surface PM2.5 mass concentrations over the contiguous U.S., summarizes their applications and limitations, and provides suggestions on future research needs. The complex landscape of satellite instruments, model capabilities, monitor networks, and data synthesis methods offers opportunities for research development, but would benefit from guidance for new users. Guidance is provided to access publicly available PM2.5 datasets, to explain and compare different approaches for dataset generation, and to identify sources of uncertainties associated with various types of datasets. Three main sources used to create PM2.5 exposure data are ground-based measurements (especially regulatory monitoring), satellite retrievals (especially aerosol optical depth, AOD), and atmospheric chemistry models. We find inconsistencies among several publicly available PM2.5 estimates, highlighting uncertainties in the exposure datasets that are often overlooked in health effects analyses. Major differences among PM2.5 estimates emerge from the choice of data (ground-based, satellite, and/or model), the spatiotemporal resolutions, and the algorithms used to fuse data sources.Implications: Fine particulate matter (PM2.5) has large impacts on human morbidity and mortality. Even though the methods for generating the PM2.5 exposure estimates have been significantly improved in recent years, there is a lack of review articles that document PM2.5 exposure datasets that are publicly available and easily accessible by the health and air quality communities. In this article, we discuss the main methods that generate PM2.5 data, compare several publicly available datasets, and show the applications of various data fusion approaches. Guidance to access and critique these datasets are provided for stakeholders in public health sectors.

Air Quality-Related Health Benefits of Energy Efficiency in the United States.

While it is known that energy efficiency (EE) lowers power sector demand and emissions, study of the air quality and public health impacts of EE has been limited. Here, we quantify the air quality and mortality impacts of a 12% summertime (June, July, and August) reduction in baseload electricity demand. We use the AVoided Emissions and geneRation Tool (AVERT) to simulate plant-level generation and emissions, the Community Multiscale Air Quality (CMAQ) model to simulate air quality, and the Environmental Benefits Mapping and Analysis Program (BenMAP) to quantify mortality impacts. We find EE reduces emissions of NO x by 13.2%, SO2 by 12.6%, and CO2 by 11.6%. On a nationwide, summer average basis, ambient PM2.5 is reduced 0.55% and O3 is reduced 0.45%. Reduced exposure to PM2.5 avoids 300 premature deaths annually (95% CI: 60 to 580) valued at $2.8 billion ($0.13 billion to $9.3 billion), and reduced exposure to O3 averts 175 deaths (101 to 244) valued at $1.6 billion ($0.15 billion to $4.5 billion). This translates into a health savings rate of $0.049/kWh ($0.031/kWh for PM2.5 and $0.018/kWh for O3). These results illustrate the importance of capturing the health benefits of EE and its potential as a strategy to achieve air standards.

Climate Change and Heat-Related Excess Mortality in the Eastern USA.

Climate change will increase extreme heat-related health risks. To quantify the health impacts of mid-century climate change, we assess heat-related excess mortality across the eastern USA. Health risks are estimated using the US Environmental Protection Agency's Environmental Benefits Mapping and Analysis Program (BenMAP). Mid-century temperature estimates, downscaled using the Weather Research and Forecasting model, are compared to 2007 temperatures at 36 km and 12 km resolutions. Models indicate the average apparent and actual summer temperatures rise by 4.5° and 3.3° C, respectively. Warmer average apparent temperatures could cause 11,562 additional annual deaths (95% confidence interval, CI: 2641-20,095) due to cardiovascular stress in the population aged 65 years and above, while higher minimum temperatures could cause 8767 (95% CI: 5030-12,475) additional deaths each year. Modeled future climate data available at both coarse (36 km) and fine (12 km) resolutions predict significant human health impacts from warmer climates. The findings suggest that currently available information on future climates is sufficient to guide regional planning for the protection of public health. Higher resolution climate and demographic data are still needed to inform more targeted interventions.

Air-quality-related health impacts from climate change and from adaptation of cooling demand for buildings in the eastern United States: An interdisciplinary modeling study.

BACKGROUND: Climate 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 FINDINGS: We 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. CONCLUSIONS: This study examines the contribution of future air-pollution-related health damages that are caused by the power sector through heat-driven air conditioning adaptation in buildings. Results show that without intervention, approximately 5%-9% of exacerbated air-pollution-related mortality will be due to increases in power sector emissions from heat-driven building electricity demand. This analysis highlights the need for cleaner energy sources, energy efficiency, and energy conservation to meet our growing dependence on building cooling systems and simultaneously mitigate climate change.

Response of Power Plant Emissions to Ambient Temperature in the Eastern United States.

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 (CO2, SO2, and NOX) 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 SO2 emissions, a 3.60%/°C ± 0.49%/°C increase in NOX emissions, and a 3.32%/°C ± 0.36%/°C increase in CO2 emissions. Sensitivities vary by year and by pollutant, with SO2 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 SO2 emissions, 2.15%/°C ± 0.29%/°C for NOX emissions, and 1.78%/°C ± 0.22%/°C for CO2 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.

Climate change: challenges and opportunities for global health.

IMPORTANCE: Health is inextricably linked to climate change. It is important for clinicians to understand this relationship in order to discuss associated health risks with their patients and to inform public policy. OBJECTIVES: To provide new US-based temperature projections from downscaled climate modeling and to review recent studies on health risks related to climate change and the cobenefits of efforts to mitigate greenhouse gas emissions. DATA SOURCES, STUDY SELECTION, AND DATA SYNTHESIS: We searched PubMed and Google Scholar from 2009 to 2014 for articles related to climate change and health, focused on governmental reports, predictive models, and empirical epidemiological studies. Of the more than 250 abstracts reviewed, 56 articles were selected. In addition, we analyzed climate data averaged over 13 climate models and based future projections on downscaled probability distributions of the daily maximum temperature for 2046-2065. We also compared maximum daily 8-hour average ozone with air temperature data taken from the National Oceanic and Atmospheric Administration, National Climate Data Center. RESULTS: By 2050, many US cities may experience more frequent extreme heat days. For example, New York and Milwaukee may have 3 times their current average number of days hotter than 32°C (90°F). High temperatures are also strongly associated with ozone exceedance days, for example, in Chicago, Illinois. The adverse health aspects related to climate change may include heat-related disorders, such as heat stress and economic consequences of reduced work capacity; respiratory disorders, including those exacerbated by air pollution and aeroallergens, such as asthma; infectious diseases, including vectorborne diseases and waterborne diseases, such as childhood gastrointestinal diseases; food insecurity, including reduced crop yields and an increase in plant diseases; and mental health disorders, such as posttraumatic stress disorder and depression, that are associated with natural disasters. Substantial health and economic cobenefits could be associated with reductions in fossil fuel combustion. For example, greenhouse gas emission policies may yield net economic benefit, with health benefits from air quality improvements potentially offsetting the cost of US and international carbon policies. CONCLUSIONS AND RELEVANCE: Evidence over the past 20 years indicates that climate change can be associated with adverse health outcomes. Health care professionals have an important role in understanding and communicating the related potential health concerns and the cobenefits from policies to reduce greenhouse gas emissions.

Emissions and air quality impacts of truck-to-rail freight modal shifts in the Midwestern United States.

We present an examination of the potential emissions and air quality benefits of shifting freight from truck to rail in the upper Midwestern United States. Using a novel, freight-specific emissions inventory (the Wisconsin Inventory of Freight Emissions, WIFE) and a three-dimensional Eulerian photochemical transport model (the Community Multiscale Air Quality Model, CMAQ), we quantify how specific freight mode choices impact ambient air pollution concentrations. Using WIFE, we developed two modal shift scenarios: one focusing on intraregional freight movements within the Midwest and a second on through-freight movements through the region. Freight truck and rail emissions inventories for each scenario were gridded to a 12 km × 12 km horizontal resolution as input to CMAQ, along with emissions from all other major sectors, and three-dimensional time-varying meteorology from the Weather Research and Forecasting model (WRF). The through-freight scenario reduced monthly mean (January and July) localized concentrations of nitrogen dioxide (NO2) by 28% (-2.33 ppbV) in highway grid cells, and reduced elemental carbon (EC) by 16% (-0.05 µg/m(3)) in highway grid cells. There were corresponding localized increases in railway grid cells of 25% (+0.83 ppbV) for NO2, and 22% (+0.05 µg/m(3)) for EC. The through-freight scenario reduced CO2 emissions 31% compared to baseline trucking. The through-freight scenario yields a July mean change in ground-level ambient PM2.5 and O3 over the central and eastern part of the domain (up to -3%).

Air quality and exercise-related health benefits from reduced car travel in the midwestern United States.

BACKGROUND: Automobile exhaust contains precursors to ozone and fine particulate matter (PM ≤ 2.5 µm in aerodynamic diameter; PM2.5), posing health risks. Dependency on car commuting also reduces physical fitness opportunities. OBJECTIVE: In this study we sought to quantify benefits from reducing automobile usage for short urban and suburban trips. METHODS: We simulated census-tract level changes in hourly pollutant concentrations from the elimination of automobile round trips ≤ 8 km in 11 metropolitan areas in the upper midwestern United States using the Community Multiscale Air Quality (CMAQ) model. Next, we estimated annual changes in health outcomes and monetary costs expected from pollution changes using the U.S. Environmental Protection Agency Benefits Mapping Analysis Program (BenMAP). In addition, we used the World Health Organization Health Economic Assessment Tool (HEAT) to calculate benefits of increased physical activity if 50% of short trips were made by bicycle. RESULTS: We estimate that, by eliminating these short automobile trips, annual average urban PM2.5 would decline by 0.1 µg/m3 and that summer ozone (O3) would increase slightly in cities but decline regionally, resulting in net health benefits of $4.94 billion/year [95% confidence interval (CI): $0.2 billion, $13.5 billion), with 25% of PM2.5 and most O3 benefits to populations outside metropolitan areas. Across the study region of approximately 31.3 million people and 37,000 total square miles, mortality would decline by approximately 1,295 deaths/year (95% CI: 912, 1,636) because of improved air quality and increased exercise. Making 50% of short trips by bicycle would yield savings of approximately $3.8 billion/year from avoided mortality and reduced health care costs (95% CI: $2.7 billion, $5.0 billion]. We estimate that the combined benefits of improved air quality and physical fitness would exceed $8 billion/year. CONCLUSION: Our findings suggest that significant health and economic benefits are possible if bicycling replaces short car trips. Less dependence on automobiles in urban areas would also improve health in downwind rural settings.

Mobile source CO2 mitigation through smart growth development and vehicle fleet hybridization.

This paper presents the results of a study on the effectiveness of smart growth development patterns and vehicle fleet hybridization in reducing mobile source emissions of carbon dioxide (CO2) across 11 major metropolitan regions of the Midwestern U.S. over a 50-year period. Through the integration of a vehicle travel activity modeling framework developed by researchers atthe Oak Ridge National Laboratory with small area population projections, we model mobile source emissions of CO2 associated with alternative land development and technology change scenarios between 2000 and 2050. Our findings suggest that under an aggressive smart growth scenario, growth in emissions expected to occur under a business as usual scenario is reduced by 34%, while the full dissemination of hybrid-electric vehicles throughout the light vehicle fleet is found to offset the expected growth in emissions by 97%. Our results further suggest that high levels of urban densification could achieve reductions in 2050 CO2 emissions equivalent to those attainable through the full dissemination of hybrid-electric vehicle technologies.

Effect of particulate matter air pollution on hospital admissions and medical visits for lung and heart disease in two southeast Idaho cities.

Few, if any, published time series studies have evaluated the effects of particulate matter air exposures by combining hospital admissions with medical visit data for smaller populations. We investigated the relationship between daily particulate matter (<10 microm in aerometric diameter or PM10) exposures with admissions and medical visits (emergency room, urgent care, and family practice) for respiratory and cardiovascular disease in Pocatello and Chubbuck, Idaho (population about 60,000), from November 1994 through March 2000. Within generalized linear models, time, weather, influenza, and day-of-week effects were controlled. In single-pollutant models, respiratory disease admissions and visits increased (7.1-15.4% per 50 microg/m3 PM10) for each age group analyzed, with the highest increases in two groups, children and especially the elderly. Statistical analyses suggest that the results probably did not occur by chance. Sensitivity analyses did not provide strong evidence that the respiratory disease effect estimates were sensitive to reasonable changes in the final degrees of freedom choice for time and weather effects. No strong evidence of confounding by NO2 and SO2 was found from results of multi-pollutant models. Ozone and carbon monoxide data were not available to include multi-pollutant models, but evidence suggests that they were not a problem. Unexpectedly, evidence of an association between PM10 with cardiovascular disease was not found, possibly due to the lifestyles of the mostly Mormon study population. Successful time series analyses can be performed on smaller populations if diverse, centralized databases are available. Hospitals that offer urgent or other primary care services may be a rich source of data for researchers. Using data that potentially represented a wide-range of disease severity, the findings provide evidence that evaluating only hospital admissions or emergency room visit effects may underestimate the overall morbidity due to acute particulate matter exposures. Further work is planned to test this conclusion.

A global comparison of national biodiesel production potentials.

This study presents a consistent, national-level evaluation of potential biodiesel volumes and prices, replicated across 226 countries, territories, and protectorates. Utilizing all commercially exported lipid feedstocks from existing agricultural lands, we compare the upper-limit potential for expanded biodiesel production in terms of absolute biodiesel volumes, profitable potential from biodiesel exports, and potential from expanded vegetable oil production through agricultural yield increases. Country findings are compared across a variety of economic, energy, and environmental metrics. Our results show an upper-limit worldwide volume potential of 51 billion liters from 119 countries; 47 billion of which could be produced profitably at today's import prices. Also significant production gains are possible through increasing agricultural yields: a 12-fold increase over existing potential, primarily hinging on better management of tropical oilseed varietals.

Improved accounting of emissions from utility energy storage system operation.

Several proposed utility-scale energy storage systems in the U.S. will use the spare output capacity of existing electric power systems to create the equivalent of new load-following plants that can rapidly respond to fluctuations in electricity demand and increase the flexibility of baseload generators. New energy storage systems using additional generation from existing plants can directly compete with new traditional sources of load-following and peaking electricity, yet this application of energy storage is not required to meet many of the Clean Air Act standards required of new electricity generators (e.g., coal- or gas-fired power plants). This study evaluates the total emissions that will likely result from the operation of a new energy storage facility when coupled with an average existing U.S. coal-fired power plant and estimates that the emission rates of SO2 and NOx will be considerably higher than the rate of a new plant meeting Clean Air Act standards, even accounting for the efficiency benefits of energy storage. This study suggests that improved emissions "accounting" might be necessary to provide accurate environmental comparisons between energy storage and more traditional sources of electricity generation.

Impact of regional climate change on human health.

The World Health Organisation estimates that the warming and precipitation trends due to anthropogenic climate change of the past 30 years already claim over 150,000 lives annually. Many prevalent human diseases are linked to climate fluctuations, from cardiovascular mortality and respiratory illnesses due to heatwaves, to altered transmission of infectious diseases and malnutrition from crop failures. Uncertainty remains in attributing the expansion or resurgence of diseases to climate change, owing to lack of long-term, high-quality data sets as well as the large influence of socio-economic factors and changes in immunity and drug resistance. Here we review the growing evidence that climate-health relationships pose increasing health risks under future projections of climate change and that the warming trend over recent decades has already contributed to increased morbidity and mortality in many regions of the world. Potentially vulnerable regions include the temperate latitudes, which are projected to warm disproportionately, the regions around the Pacific and Indian oceans that are currently subjected to large rainfall variability due to the El Niño/Southern Oscillation sub-Saharan Africa and sprawling cities where the urban heat island effect could intensify extreme climatic events.

Impact of regional climate change on human health

The World Health Organization estimates that the warming and precipitation trends due to anthropogenic climate change of the past 30 years already claim over 150,000 lives annually. Many prevalent human diseases are linked to climate fluctuations, from cardiovascular mortality and respiratory illnesses due to heatwaves, to altered transmission ofinfectious diseases and malnutrition from crop failures. Uncertainty remains in attributing the expansion or resurgence of diseases to climate change, owing to lack of long-term, high-quality data sets as well as the large influence of socio-economic factors and changes in immunity and drug resistance. Here we review the growing evidence that climateûhealth relationships pose increasing health risks under future projections of climate change and that the warming trend over recent decades has already contributed to increased morbidity and mortality in many regions of the world. Potentially vulnerable regions include the temperate latitudes, which are projected to warm disproportionately, the regions around the Pacific and Indian oceans that are currently subjected to large rainfall variability due to the El Ninÿo/Southern Oscillation sub-Saharan Africa and sprawling cities where the urban heat island effect could intensifyextreme climatic events. (AU)