AERMOD performance evaluation for three coal-fired electrical generating units in Southwest Indiana.

UNLABELLED: An evaluation of the steady-state dispersion model AERMOD was conducted to determine its accuracy at predicting hourly ground-level concentrations of sulfur dioxide (SO2) by comparing model-predicted concentrations to a full year of monitored SO2 data. The two study sites are comprised of three coal-fired electrical generating units (EGUs) located in southwest Indiana. The sites are characterized by tall, buoyant stacks,flat terrain, multiple SO2 monitors, and relatively isolated locations. AERMOD v12060 and AERMOD v12345 with BETA options were evaluated at each study site. For the six monitor-receptor pairs evaluated, AERMOD showed generally good agreement with monitor values for the hourly 99th percentile SO2 design value, with design value ratios that ranged from 0.92 to 1.99. AERMOD was within acceptable performance limits for the Robust Highest Concentration (RHC) statistic (RHC ratios ranged from 0.54 to 1.71) at all six monitors. Analysis of the top 5% of hourly concentrations at the six monitor-receptor sites, paired in time and space, indicated poor model performance in the upper concentration range. The amount of hourly model predicted data that was within a factor of 2 of observations at these higher concentrations ranged from 14 to 43% over the six sites. Analysis of subsets of data showed consistent overprediction during low wind speed and unstable meteorological conditions, and underprediction during stable, low wind conditions. Hourly paired comparisons represent a stringent measure of model performance; however given the potential for application of hourly model predictions to the SO2 NAAQS design value, this may be appropriate. At these two sites, AERMOD v12345 BETA options do not improve model performance. IMPLICATIONS: A regulatory evaluation of AERMOD utilizing quantile-quantile (Q-Q) plots, the RHC statistic, and 99th percentile design value concentrations indicates that model performance is acceptable according to widely accepted regulatory performance limits. However, a scientific evaluation examining hourly paired monitor and model values at concentrations of interest indicates overprediction and underprediction bias that is outside of acceptable model performance measures. Overprediction of 1-hr SO2 concentrations by AERMOD presents major ramifications for state and local permitting authorities when establishing emission limits.

Comparative life cycle assessment of copper and gold recovery from waste printed circuit boards: Pyrometallurgy, chemical leaching and bioleaching.

Printed circuit boards (PCBs) make up a substantial amount of electronic waste (e-waste) generated annually. Waste PCBs contain high quantities of copper and gold in comparison to natural ores. As such, "urban mining" of waste PCBs to recover these metals is of commercial interest. In this work, we used life cycle assessment to compare the environmental impact of four copper and gold recovery processes. We evaluated pyrometallurgy, chemical leaching, and bioleaching, as well as a hybrid leaching process that uses bioleaching to recover copper and chemical leaching to recover gold. Furthermore, we considered differences in environmental impact based on differences in electricity sources. If electricity comes from fossil fuels, the pyrometallurgical process results in the lowest environmental impact in all impact categories studied. If electricity comes from carbon-free sources, the pyrometallurgical process results in the lowest environmental impact in all categories studied except global warming, where the hybrid leaching process results in the lowest impact. In all cases, metal recovery from waste PCBs leads to lower environmental impact than primary metal production. Our goal is to guide e-waste recyclers towards more environmentally sustainable metal recovery processes and to provide knowledge gaps in the field to guide future research.

Regionalized chemical footprint method to identify aquatic ecotoxicity hotspots of hard disk drive rare-earth magnets.

The chemical footprint (ChF), which combines life cycle assessment (LCA) and quantitative risk assessment principles, shows promise for exploring localized toxicity impacts of manufacturing processes, which is not achievable with LCA alone. An updated ChF method was applied to the global annual production of a hard disk drive (HDD) rare-earth element (REE) magnet assembly, assuming a supply chain in East and Southeast Asia. Existing REE magnet assembly LCA inventories were combined with supplier manufacturing locations to create a cradle-to-gate spatial unit process inventory. Emissions from the electricity grid for each manufacturing site were downscaled to hydrobasins of interest using the Global Power Plant Database. The predicted no effect concentration (PNEC) was chosen as the ecotoxicity pollution boundary to determine the threshold for dilution of each chemical of concern (CoC) and to calculate the ChF. Finally, a high-resolution hydrological database provided volumes of the freshwater river reach draining each hydrobasin and was used to calculate the dilution capacity (DC), that is, the volume required to remain at or below the PNEC for each CoC. The total ChF of annual REE magnet assembly production was 6.91E12 m3 , with hotspots in watersheds in China and Thailand where REEs are processed and steel metalworking takes place. Metals were the primary CoCs, with cadmium and chromium(VI) comprising 77% of total ChF. Dilution factors ranged from 5E-09 to 9E + 03 of the DC of the waterbody, reflecting the spatial variability in both emissions and DC. An advanced ChF method was demonstrated for HDD REE magnets. Scoping is a key step required to reduce model complexity. The use of regionalized fate factors and standardized hydrological data sets improves the comparability of ChFs across hydrobasins. Additional work to combine data sets into readily available tools is needed to increase usability and standardization of the ChF method and promote wider adoption. Integr Environ Assess Manag 2023;19:272-283. © 2022 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Evaluation of Drinking Water Disinfectant Byproducts Compliance Data as an Indirect Measure for Short-Term Exposure in Humans.

In the absence of shorter term disinfectant byproducts (DBPs) data on regulated Trihalomethanes (THMs) and Haloacetic acids (HAAs), epidemiologists and risk assessors have used long-term annual compliance (LRAA) or quarterly (QA) data to evaluate the association between DBP exposure and adverse birth outcomes, which resulted in inconclusive findings. Therefore, we evaluated the reliability of using long-term LRAA and QA data as an indirect measure for short-term exposure. Short-term residential tap water samples were collected in peak DBP months (May-August) in a community water system with five separate treatment stations and were sourced from surface or groundwater. Samples were analyzed for THMs and HAAs per the EPA (U.S. Environmental Protection Agency) standard methods (524.2 and 552.2). The measured levels of total THMs and HAAs were compared temporally and spatially with LRAA and QA data, which showed significant differences (p < 0.05). Most samples from surface water stations showed higher levels than LRAA or QA. Significant numbers of samples in surface water stations exceeded regulatory permissible limits: 27% had excessive THMs and 35% had excessive HAAs. Trichloromethane, trichloroacetic acid, and dichloroacetic acid were the major drivers of variability. This study suggests that LRAA and QA data are not good proxies of short-term exposure. Further investigation is needed to determine if other drinking water systems show consistent findings for improved regulation.