Validation of three new methods for determination of metal emissions using a modified Environmental Protection Agency Method 301

Three new methods applicable to the determination of hazardous metal concentrations in stationary source emissions were developed and evaluated for use in U.S. Environmental Protection Agency (EPA) compliance applications. Two of the three independent methods, a continuous emissions monitor-based method (Xact) and an X-ray-based filter method (XFM), are used to measure metal emissions. The third method involves a quantitative aerosol generator (QAG), which produces a reference aerosol used to evaluate the measurement methods. A modification of EPA Method 301 was used to validate the three methods for As, Cd, Cr, Pb, and Hg, representing three hazardous waste combustor Maximum Achievable Control Technology (MACT) metal categories (low volatile, semivolatile, and volatile). The modified procedure tested the methods using more stringent criteria than EPA Method 301; these criteria included accuracy, precision, and linearity. The aerosol generation method was evaluated in the laboratory by comparing actual with theoretical aerosol concentrations. The measurement methods were evaluated at a hazardous waste combustor (HWC) by comparing measured with reference aerosol concentrations. The QAG, Xact, and XFM met the modified Method 301 validation criteria. All three of the methods demonstrated precisions and accuracies on the order of 5%. In addition, correlation coefficients for each method were on the order of 0.99, confirming the methods' linear response and high precision over a wide range of concentrations. The measurement methods should be applicable to emissions from a wide range of sources, and the reference aerosol generator should be applicable to additional analytes. EPA recently approved an alternative monitoring petition for an HWC at Eli Lilly's Tippecanoe site in Lafayette, IN, in which the Xact is used for demonstrating compliance with the HWC MACT metal emissions (low volatile, semivolatile, and volatile). The QAG reference aerosol generator was approved as a method for providing a quantitative reference aerosol, which is required for certification and continuing quality assurance of the Xact.     

Application of Harvey-Garabedian model for describing bacterial removal in Sand Abstraction Systems associated with ephemeral rivers

There have been concerted efforts to find alternative sources of water for small rural communities in the Southern Africa region, and one such initiative is Sand Abstraction Systems (SAS) or infiltration galleries. The sand formation of the riverbed of an ephemeral river is utilised as a natural filter giving potable water of high quality, but is prone to pathogenic contamination. The main objective of our study was to test the suitability of Harvey and Garabedian model for describing bacterial removal in SAS. The Harvey and Garabedian model with some modifications was adopted due to the few parameters required in applying the model. The coefficients and media properties were established from laboratory experiments and field studies. The implicit finite difference method was applied to solve the numerical model equation and to simulate the aquifer response to Escherichia coli for Nkayi SAS. The results of the bacterial simulation from the model fitted well with measured field data and with a small margin of error between the field results and the model (+/-5 coliform count/100 ml).     

Nitrogen cycling during seven years of atmospheric CO2 enrichment in a scrub oak woodland

Experimentally increasing atmospheric CO2 often stimulates plant growth and ecosystem carbon (C) uptake. Biogeochemical theory predicts that these initial responses will immobilize nitrogen (N) in plant biomass and soil organic matter, causing N availability to plants to decline, and reducing the long-term CO2-stimulation of C storage in N limited ecosystems. While many experiments have examined changes in N cycling in response to elevated CO2, empirical tests of this theoretical prediction are scarce. During seven years of postfire recovery in a scrub oak ecosystem, elevated CO2 initially increased plant N accumulation and plant uptake of tracer 15N, peaking after four years of CO2 enrichment. Between years four and seven, these responses to CO2 declined. Elevated CO2 also increased N and tracer 15N accumulation in the O horizon, and reduced 15N recovery in underlying mineral soil. These responses are consistent with progressive N limitation: the initial CO2 stimulation of plant growth immobilized N in plant biomass and in the O horizon, progressively reducing N availability to plants. Litterfall production (one measure of aboveground primary productivity) increased initially in response to elevated CO2, but the CO2 stimulation declined during years five through seven, concurrent with the accumulation of N in the O horizon and the apparent restriction of plant N availability. Yet, at the level of aboveground plant biomass (estimated by allometry), progressive N limitation was less apparent, initially because of increased N acquisition from soil and later because of reduced N concentration in biomass as N availability declined. Over this seven-year period, elevated CO2 caused a redistribution of N within the ecosystem, from mineral soils, to plants, to surface organic matter. In N limited ecosystems, such changes in N cycling are likely to reduce the response of plant production to elevated CO2.     

The impact of climate change on global energy use

Robust decision making, a growing approach to infrastructure planning under climate change uncertainty, aims to evaluate infrastructure performance across a wide range of possible conditions and identify the most robust strategies and designs. Robust decision making seeks to find potential weaknesses in systems in order to gird these through a combination of policy, infrastructure, and, in some cases, resilient or recovery strategies. A system can be explored by simulating many combinations of uncertain climatic and economic parameters; statistical clustering can identify parameter thresholds that lead to unacceptable performance. Often, however, uncertain variables are correlated, complicating the robustness analysis and casting doubt upon the thresholds identified. Here, we evaluate the impact of ordinary, hidden correlations in uncertainty parameters that drive simulation in robust decision making. We induced correlations between temperature and key climatic and economic parameters. We tested correlations of 0%, 30%, 60%, and 90% between temperature and the absolute value of precipitation, coefficient of variation, and downward surface solar radiation, and negative correlations between temperature and net variable benefit and the discount rate. We used a calibrated simulation model of a dam system regulating Lake Tana, Ethiopia, to compute the agricultural supply and net present value of the reservoirs. As the correlation strength increased, the results converged in a smaller region. We found that strong correlations depressed robustness scores of lower-performing alternatives and conversely increased results of the higher-performing alternatives. As the correlations increased in favorable alternatives, the failure thresholds became more extreme, speciously suggesting that only intense changes would result in poor performance. This overall analysis highlights the degree to which correlations of an interconnected climatic and economic system can impact outcomes of robust decision making and suggests methods to avoid confounding results.