Health benefits and control costs of tightening particulate matter emissions standards for coal power plants - The case of Northeast Brazil.

Exposure to ambient particulate matter (PM) caused an estimated 4.2 million deaths worldwide in 2015. However, PM emission standards for power plants vary widely. To explore if the current levels of these standards are sufficiently stringent in a simple cost-benefit framework, we compared the health benefits (avoided monetized health costs) with the control costs of tightening PM emission standards for coal-fired power plants in Northeast (NE) Brazil, where ambient PM concentrations are below World Health Organization (WHO) guidelines. We considered three Brazilian PM10 (PMx refers to PM with a diameter under x micrometers) emission standards and a stricter U.S. EPA standard for recent power plants. Our integrated methodology simulates hourly electricity grid dispatch from utility-scale power plants, disperses the resulting PM2.5, and estimates selected human health impacts from PM2.5 exposure using the latest integrated exposure-response model. Since the emissions inventories required to model secondary PM are not available in our study area, we modeled only primary PM so our benefit estimates are conservative. We found that tightening existing PM10 emission standards yields health benefits that are over 60 times greater than emissions control costs in all the scenarios we considered. The monetary value of avoided hospital admissions alone is at least four times as large as the corresponding control costs. These results provide strong arguments for considering tightening PM emission standards for coal-fired power plants worldwide, including in regions that meet WHO guidelines and in developing countries

Riverine ecosystem services and the thermoelectric sector: strategic issues facing the Northeastern United States

Major strategic issues facing the global thermoelectric sector include environmental regulation, climate change and increasing electricity demand. We have addressed such issues by modeling thermoelectric generation in the Northeastern United States that is reliant on cooling under five sensitivity tests to evaluate losses/gains in power production, thermal pollution and suitable aquatic habitat, comparing the contemporary baseline (2000–2010) with potential future states. Integral to the analysis, we developed a methodology to quantify river water availability for cooling, which we define as an ecosystem service. Projected climate conditions reduce river water available for efficient power plant operations and the river\u27s capacity to absorb waste heat, causing a loss of regional thermoelectric generation (RTG) (2.5%) in some summers that, compared to the contemporary baseline, is equal to the summertime electricity consumption of 1.3 million Northeastern US homes. Vulnerabilities to warm temperatures and thermal pollution can be alleviated through the use of more efficient natural gas (NG) power plants that have a reduced reliance on cooling water. Conversion of once-through (OT) to cooling tower (CT) systems and the Clean Water Act (CWA) temperature limit regulation, both of which reduce efficiencies at the single plant level, show potential to yield beneficial increases in RTG. This is achieved by obviating the need for large volumes of river water, thereby reducing plant-to-plant interferences through lowering the impact of upstream thermal pollution and preserving a minimum standard of cooling water. The results and methodology framework presented here, which can be extrapolated to other regional assessments with contrasting climates and thermoelectric profiles, can identify opportunities and support decision-making to achieve more efficient energy systems and riverine ecosystem protection

Environmental Audit improvements in industrial systems through FRAM

Environmental risk management requires specific methodologies to focus audit activities on the most critical elements of production systems. Limited resources require a clear motivation to put attention on specific technological, human, organizational components, and often should address the monitor of interactions among these elements. Recent research in environmental risk looks at methods to deal with complexity as interesting tools to reduce real impacts on pollution and consumption. In this paper, we provide evidence of the advantage in using the Functional Resonance Analysis Method (FRAM), not only to identify the criticalities of a complex production system but to provide a methodology to continuously improve the audit activities in parallel with the introduction of technique to reduce environmental risk. The case study presents the evolution of environmental audit in a sinter plant, proving the need for a review of the criticality list and the successful application of FRAM to refocus the control activities

Air pollution modelling using a graphics processing unit with CUDA

The Graphics Processing Unit (GPU) is a powerful tool for parallel computing. In the past years the performance and capabilities of GPUs have increased, and the Compute Unified Device Architecture (CUDA) - a parallel computing architecture - has been developed by NVIDIA to utilize this performance in general purpose computations. Here we show for the first time a possible application of GPU for environmental studies serving as a basement for decision making strategies. A stochastic Lagrangian particle model has been developed on CUDA to estimate the transport and the transformation of the radionuclides from a single point source during an accidental release. Our results show that parallel implementation achieves typical acceleration values in the order of 80-120 times compared to CPU using a single-threaded implementation on a 2.33 GHz desktop computer. Only very small differences have been found between the results obtained from GPU and CPU simulations, which are comparable with the effect of stochastic transport phenomena in atmosphere. The relatively high speedup with no additional costs to maintain this parallel architecture could result in a wide usage of GPU for diversified environmental applications in the near future.Comment: 5 figure

Improving regional ozone modeling through systematic evaluation of errors using the aircraft observations during the International Consortium for Atmospheric Research on Transport and Transformation

During the operational phase of the ICARTT field experiment in 2004, the regional air quality model STEM showed a strong positive surface bias and a negative upper troposphere bias (compared to observed DC-8 and WP-3 observations) with respect to ozone. After updating emissions from NEI 1999 to NEI 2001 (with a 2004 large point sources inventory update), and modifying boundary conditions, low-level model bias decreases from 11.21 to 1.45 ppbv for the NASA DC-8 observations and from 8.26 to −0.34 for the NOAA WP-3. Improvements in boundary conditions provided by global models decrease the upper troposphere negative ozone bias, while accounting for biomass burning emissions improved model performance for CO. The covariances of ozone bias were highly correlated to NOz, NOy, and HNO3 biases. Interpolation of bias information through kriging showed that decreasing emissions in SE United States would reduce regional ozone model bias and improve model correlation coefficients. The spatial distribution of forecast errors was analyzed using kriging, which identified distinct features, which when compared to errors in postanalysis simulations, helped document improvements. Changes in dry deposition to crops were shown to reduce substantially high bias in the forecasts in the Midwest, while updated emissions were shown to account for decreases in bias in the eastern United States. Observed and modeled ozone production efficiencies for the DC-8 were calculated and shown to be very similar (7.8) suggesting that recurring ozone bias is due to overestimation of NOx emissions. Sensitivity studies showed that ozone formation in the United States is most sensitive to NOx emissions, followed by VOCs and CO. PAN as a reservoir of NOx can contribute to a significant amount of surface ozone through thermal decomposition