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BackgroundTropospheric ozone and black carbon (BC), a component of fine particulate matter (PM ≤ 2.5 µm in aerodynamic diameter; PM(2.5)), are associated with premature mortality and they disrupt global and regional climate.ObjectivesWe examined the air quality and health benefits of 14 specific emission control measures targeting BC and methane, an ozone precursor, that were selected because of their potential to reduce the rate of climate change over the next 20-40 years.MethodsWe simulated the impacts of mitigation measures on outdoor concentrations of PM(2.5) and ozone using two composition-climate models, and calculated associated changes in premature PM(2.5)- and ozone-related deaths using epidemiologically derived concentration-response functions.ResultsWe estimated that, for PM(2.5) and ozone, respectively, fully implementing these measures could reduce global population-weighted average surface concentrations by 23-34% and 7-17% and avoid 0.6-4.4 and 0.04-0.52 million annual premature deaths globally in 2030. More than 80% of the health benefits are estimated to occur in Asia. We estimated that BC mitigation measures would achieve approximately 98% of the deaths that would be avoided if all BC and methane mitigation measures were implemented, due to reduced BC and associated reductions of nonmethane ozone precursor and organic carbon emissions as well as stronger mortality relationships for PM(2.5) relative to ozone. Although subject to large uncertainty, these estimates and conclusions are not strongly dependent on assumptions for the concentration-response function.ConclusionsIn addition to climate benefits, our findings indicate that the methane and BC emission control measures would have substantial co-benefits for air quality and public health worldwide, potentially reversing trends of increasing air pollution concentrations and mortality in Africa and South, West, and Central Asia. These projected benefits are independent of carbon dioxide mitigation measures. Benefits of BC measures are underestimated because we did not account for benefits from reduced indoor exposures and because outdoor exposure estimates were limited by model spatial resolution.

We developed and tested spectroscopic models derived by partial least squares regression (PLSR) using data from the Commonwealth Scientific and Industrial Research Organisation's (CSIRO) national soil database (NatSoil) and soil samples from the Australian National Soil Archive. Models were constructed for 21 soil attributes, and their predictability assessed using the R2, ranged from 0.57 for bicarbonate extractable available phosphorus to 0.92 for the sum of the exchangeable bases. Investigating the spectral library coverage with a suite of 1484 unknown samples from a geochemical survey of Australian catchments, we found that the models could be used to predict many soil attributes in a geographically diverse set of samples. Additional keywords: mid infrared, mid-IR diffuse reflectance spectroscopy, FT- IR, particle size, sample preparation, sand, silt, clay, organic carbon. Received 15 June 2015, accepted 13 August 2015, published online 13 October 2015, Introduction Consistent and reliable information on soil attributes is needed to understand, manage and conserve the soil. It is needed for environmental, hydrological and crop modelling, to study the effects [...]

Mid-infrared (mid-IR) diffuse reflectance spectroscopy can be used to effectively analyse soil, but the preparation of soil samples by grinding is time consuming. Soil samples are usually finely ground to a particle size of less than 0.250 mm because the spectrometer's beam aperture is approximately 1-2 mm in diameter. Larger particles can generate specular reflections and spectra that do not adequately represent the soil sample. Grinding soil to small particle sizes enables the diffuse reflectance of light and more representative sample measurements. Here, we report on research that investigates the effect that grinding to different particle sizes have on soil mid-IR spectra. Our aims were to compare the effect of grinding soil to different particle sizes (2.000 mm, 1.000 mm, 0.500 mm, 0.250 mm and 0.106 mm) on the frequencies of mid-IR spectra, and compare the effect of these particle sizes on the accuracy of spectroscopic calibrations to predict organic carbon, sand, silt and clay contents. Using the Commonwealth Scientific and Industrial Research Organisation's (CSIRO) National visible-near infrared database, we selected 227 soil samples from the National Soil Archive for our experiments, and designed an experiment whereby each soil sample was ground in triplicate to the different particle sizes. These ground samples were measured using an FT-IR spectrometer with a spectral range of 4000-600 [cm.sup.-1]. Grinding to particle sizes that are ≤ 2.000 mm reduces subsample variability. Smaller particle sizes produce finer and sharper absorption features, which are related to organic carbon, and clay and sand mineralogies. Generally, better predictions for clay, sand and soil organic carbon contents were achieved using soil that is more finely ground, but there were no statistically significant differences between predictions that use soil ground to 1 mm, 0.5 mm, 0.25 mm. Grinding did not affect predictions of silt content. Recommendations on how much grinding is required for mid-IR analysis should also consider the time, cost and effort needed to prepare the soil samples as well as the purpose of the analysis. Additional keywords: mid infrared, mid-IR diffuse reflectance spectroscopy, FT-IR, particle size, sample preparation, sand, silt, clay, organic carbon. Received 22 January 2015, accepted 4 June 2015, published online 1 October 2015, Introduction Mid-infrared (mid-IR) spectroscopy is an effective soil analytical technique that provides rapid and inexpensive soil information. Research has shown that absorptions in the mid-IR portion of the electromagnetic spectrum [...]