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National levels of personal health-care access and quality can be approximated by measuring mortality rates from causes that should not be fatal in the presence of effective medical care (ie, amenable mortality). Previous analyses of mortality amenable to health care only focused on high-income countries and faced several methodological challenges. In the present analysis, we use the highly standardised cause of death and risk factor estimates generated through the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) to improve and expand the quantification of personal health-care access and quality for 195 countries and territories from 1990 to 2015. We mapped the most widely used list of causes amenable to personal health care developed by Nolte and McKee to 32 GBD causes. We accounted for variations in cause of death certification and misclassifications through the extensive data standardisation processes and redistribution algorithms developed for GBD. To isolate the effects of personal health-care access and quality, we risk-standardised cause-specific mortality rates for each geography-year by removing the joint effects of local environmental and behavioural risks, and adding back the global levels of risk exposure as estimated for GBD 2015. We employed principal component analysis to create a single, interpretable summary measure–the Healthcare Quality and Access (HAQ) Index–on a scale of 0 to 100. The HAQ Index showed strong convergence validity as compared with other health-system indicators, including health expenditure per capita (r=0·88), an index of 11 universal health coverage interventions (r=0·83), and human resources for health per 1000 (r=0·77). We used free disposal hull analysis with bootstrapping to produce a frontier based on the relationship between the HAQ Index and the Socio-demographic Index (SDI), a measure of overall development consisting of income per capita, average years of education, and total fertility rates. This frontier allowed us to better quantify the maximum levels of personal health-care access and quality achieved across the development spectrum, and pinpoint geographies where gaps between observed and potential levels have narrowed or widened over time. Between 1990 and 2015, nearly all countries and territories saw their HAQ Index values improve; nonetheless, the difference between the highest and lowest observed HAQ Index was larger in 2015 than in 1990, ranging from 28·6 to 94·6. Of 195 geographies, 167 had statistically significant increases in HAQ Index levels since 1990, with South Korea, Turkey, Peru, China, and the Maldives recording among the largest gains by 2015. Performance on the HAQ Index and individual causes showed distinct patterns by region and level of development, yet substantial heterogeneities emerged for several causes, including cancers in highest-SDI countries; chronic kidney disease, diabetes, diarrhoeal diseases, and lower respiratory infections among middle-SDI countries; and measles and tetanus among lowest-SDI countries. While the global HAQ Index average rose from 40·7 (95% uncertainty interval, 39·0–42·8) in 1990 to 53·7 (52·2–55·4) in 2015, far less progress occurred in narrowing the gap between observed HAQ Index values and maximum levels achieved; at the global level, the difference between the observed and frontier HAQ Index only decreased from 21·2 in 1990 to 20·1 in 2015. If every country and territory had achieved the highest observed HAQ Index by their corresponding level of SDI, the global average would have been 73·8 in 2015. Several countries, particularly in eastern and western sub-Saharan Africa, reached HAQ Index values similar to or beyond their development levels, whereas others, namely in southern sub-Saharan Africa, the Middle East, and south Asia, lagged behind what geographies of similar development attained between 1990 and 2015. This novel extension of the GBD Study shows the untapped potential for personal health-care access and quality improvement across the development spectrum. Amid substantive advances in personal health care at the national level, heterogeneous patterns for individual causes in given countries or territories suggest that few places have consistently achieved optimal health-care access and quality across health-system functions and therapeutic areas. This is especially evident in middle-SDI countries, many of which have recently undergone or are currently experiencing epidemiological transitions. The HAQ Index, if paired with other measures of health-system characteristics such as intervention coverage, could provide a robust avenue for tracking progress on universal health coverage and identifying local priorities for strengthening personal health-care quality and access throughout the world. Bill & Melinda Gates Foundation.

The increasing production of ethanol has been established as an important contributor to future energy independence. Although ethanol demand is increasing, a growing economic trend in decreased profitability and resource conflicts have called into question the future of grain-based ethanol production Growing emphasis is being placed on utilizing cellulosic feedstocks to produce ethanol, and the need for renewable resources has made the development of cellulosic ethanol a national priority. Cellulosic ethanol production plants are being built in many areas of the United States to evaluate various feedstocks and processes. The waste streams from many varying processes that are being developed contain a variety of components. Differences in ethanol generation processes and feedstocks are producing waste streams unique to biofuel production, which could be potentially harmful to the environment if adequate care is not taken to manage those risks. Waste stream management and utilization of the cellulosic ethanol process are equally important components of the development of this industry.

The U.S. Environmental Protection Agency (EPA)'s PM2.5 Chemical Speciation Network (CSH) and the Interagency Monitoring of Protected Visual Environments (IMPROVE) network use X-ray fluorescence (XRF) analysis to quantify trace elements in samples of fine particles less than 2.5 microns in aerodynamic diameter (PM2.5). Methods for calculating uncertainty values for XRF results vary considerably among laboratories and instrument makes and models. To support certain types of modeling and data analysis, uncertainty estimates are required that are consistent within and between monitoring programs, and that are independent of the laboratories that performed the analyses and the analytical Instrumentation used. The goal of this work was to develop a consensus model for uncertainties associated with XRF analysis of PM2.5 filter samples. The following important components of uncertainty are included in the model described herein: variability in peak area, calibration, field sampling, and attenuation of X-ray intensity for light elements. This paper includes a detailed analysis of how attenuation uncertainties for light elements are derived. For the remaining uncertainty components included in the model, an approach and recommendations are presented to ensure that laboratories performing this type of analysis can use similar equations and parameterizations. By applying this uniform approach, it is illustrated how the uncertainties reported by the CSN and IMPROVE network laboratories can be brought into very good agreement. The proposed method is best applied at the time of data generation, but retrospective estimation of uncertainties in existing datasets is also possible. This paper serves to document the equations used for calculating the uncertainties in speciated PM2.5 data currently being posted on EPA's Air Quality System database for the PM2.5 CSN program.

Twentieth-century land management has altered the structure and composition of mixed-conifer forests and decreased their resilience to fire, drought, and insects in many parts of the Interior West. These forests occur across a wide range of environmental settings and historical disturbance regimes, so their response to land management is likely to vary across landscapes and among ecoregions. However, this variation has not been well characterized and hampers the development of appropriate management and restoration plans. We identified mixed-conifer types in central Oregon based on historical structure and composition, and successional trajectories following recent changes in land use, and evaluated how these types were distributed across environmental gradients. We used field data from 171 sites sampled across a range of environmental settings in two subregions: the eastern Cascades and the Ochoco Mountains. We identified four forest types in the eastern Cascades and four analogous types with lower densities in the Ochoco Mountains. All types historically contained ponderosa pine, but differed in the historical and modern proportions of shade-tolerant vs. shade-intolerant tree species. The Persistent Ponderosa Pine and Recent Douglas-fir types occupied relatively hot-dry environments compared to Recent Grand Fir and Persistent Shade Tolerant sites, which occupied warm-moist and cold-wet environments, respectively. Twentieth-century selective harvesting halved the density of large trees, with some variation among forest types. In contrast, the density of small trees doubled or tripled early in the 20th century, probably due to land-use change and a relatively cool, wet climate. Contrary to the common perception that dry ponderosa pine forests are the most highly departed from historical conditions, we found a greater departure in the modern composition of small trees in warm-moist environments than in either hot-dry or cold-wet environments. Furthermore, shade-tolerant trees began infilling earlier in cold-wet than in hot-dry environments and also in topographically shaded sites in the Ochoco Mountains. Our new classification could be used to prioritize management that seeks to restore structure and composition or create resilience in mixed-conifer forests of the region.