Health impact assessment of coal-fired boiler retirement at the Martin Drake and Comanche power plants

Includes bibliographical references.Health impact assessment (HIA) is a suite of tools used to characterize potential health effects of policies, projects, or regulations. The objective of this HIA was to understand the impact of decommissioning units at two large coal-fired power plants on mortality and morbidity in the Southern Front Range region of Colorado. Based on Community Multiscale Air Quality (CMAQ) chemical transport models of fine particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5) and ozone (O3), we modeled five potential emissions reductions scenarios and estimated the potential health benefits of reduced exposures to PM2.5 and ozone for premature deaths, cardiovascular and respiratory hospitalizations, and other health outcomes for ZIP codes in the Southern Front Range region, including the cities of Denver, Colorado Springs, and Pueblo. Health Benefits Scenarios 1 and 2 estimated the health benefits of shutting down most units at the Comanche plant in Pueblo, CO (one newer unit remained operational) relative to a baseline scenario using emissions from 2011 (Scenario 1) or a counterfactual baseline scenario that accounted for sulfur dioxide emissions controls (scrubbers) installed at the Martin Drake plant in Colorado Springs in 2016 (Scenario 2). Health Benefits Scenario 3 estimated the benefits of shutting down the Martin Drake plant relative to the 2011 baseline. Health Benefits Scenario 4 estimated the health benefits of shutting down the Martin Drake power plant and shutting down all but one boiler at the Comanche power plant relative to a 2011 emissions baseline. Health Benefits Scenario 5 estimated the marginal health benefits of decommissioning these plants (with one remaining coal-fired boiler at Comanche) relative to a counterfactual baseline year that considered emissions controls installed at the Martin Drake facility in 2016. In addition to estimating the number of deaths, hospitalizations, and other health outcomes that would potentially be avoided by reducing emissions at these facilities, we also estimated the monetary impact using outcome valuations typically used in US EPA health benefits analyses and examined the environmental justice implications of reduced emissions and exposures across the Southern Front Range. • For Health Benefits Scenario 1 (Comanche Units 3 and 4 were “zeroed out” and compared to a baseline where all other emissions were at 2011 levels), we estimated that reducing population exposures to PM2.5 would result in 1 (95% CI: 0 - 1) fewer premature death each year. Reductions in PM2.5 and O3 exposures would also result in fewer restricted activity days among adults [5 (95% CI: -3 – 95)] and fewer missed school days for children [27 (95% CI: -19- 582)]. Benefits of retiring the Comanche units were similar when emissions controls at Martin Drake are taken into account (Health Benefits Scenario 2). • For Health Benefits Scenario 3 (emissions at Martin Drake were “zeroed out”), we estimated that reducing population exposures to PM2.5 and O3 would result in 4 (95% CI: 2 - 5) and < 1 (95% CI: 0 - 1) fewer premature deaths each year, respectively. Reductions in PM2.5 and O3 exposures would also result in fewer restricted activity days among adults [10 (95% CI: 0 – 74)] and fewer missed school days for children [4 (95% CI: 2- 5)]. • For Health Benefits Scenario 4, we estimated that reducing population exposures to PM2.5 and O3 would result in 4 (95% CI: 2 - 6) and < 1 (95% CI: 0 - 1) fewer premature deaths each year, respectively. Among the largest annual health benefits are avoided asthma symptom days among children [16 (95% CI: -1 – 141) due to PM2.5 and 13 (95% CI: -348 - 972) due to O3] and minor restricted activity days among adults [69 (95% CI: 0 - 488) due to PM2.5 and 71 (95% CI: -31 - 750) due to O3]. We also estimated that, for Health Benefits Scenario 1, children in the study area would miss 77 (95% CI: -77 - 1180) fewer days of school each year due to lower O3 exposures. • Annual health benefits were lower for Health Benefits Scenario 5 compared to Scenario 4 due to the smaller change in exposure concentration after accounting for the control technologies installed at Martin Drake in 2016. For Health Benefits Scenario 5, we estimated that reducing population exposures to PM2.5 and O3 would result in 2 (95% CI: 1 - 3) and < 1 (95% CI: 0 - 1) fewer premature deaths each year, respectively. Other annual benefits under Health Benefits Scenario 2 included 2 (95% CI: -17 – 44) and 9 (-242 – 678) avoided asthma symptom days due to PM2.5 and O3 exposures, respectively; 28 (95%CI: -2 – 188) and 48 (95%CI: -16 – 513) minor restricted activity days due to PM2.5 and O3 exposures; and 53 (95% CI: -48 – 833) avoided school absences among children due to O3 exposures. • Monetized health benefits when both plants were “zeroed out” ranged from $4.2 million (95$2.1 million - $7.2 million) for Health Benefits Scenario 4 to$1.7 million (95% CI: $0.8 million – 3.2 million) for Health Benefits Scenario 5. Benefits tended to be smaller when only one plant was considered. In all of the analyses, the monetized impacts were driven by the value of avoided premature mortality. In addition, we found that ZIP codes with lower median incomes tended to receive a greater share of the health benefits of decreasing exposures to PM2.5 and O3 resulting from power plant shutdowns. This finding suggests that reducing emissions at the power plants could potentially alleviate some environmental justice concerns in the area

Secondary organic aerosol formation from in-use motor vehicle emissions using a potential aerosol mass reactor.

Secondary organic aerosol (SOA) formation from in-use vehicle emissions was investigated using a potential aerosol mass (PAM) flow reactor deployed in a highway tunnel in Pittsburgh, Pennsylvania. Experiments consisted of passing exhaust-dominated tunnel air through a PAM reactor over integrated hydroxyl radical (OH) exposures ranging from ∼ 0.3 to 9.3 days of equivalent atmospheric oxidation. Experiments were performed during heavy traffic periods when the fleet was at least 80% light-duty gasoline vehicles on a fuel-consumption basis. The peak SOA production occurred after 2-3 days of equivalent atmospheric oxidation. Additional OH exposure decreased the SOA production presumably due to a shift from functionalization to fragmentation dominated reaction mechanisms. Photo-oxidation also produced substantial ammonium nitrate, often exceeding the mass of SOA. Analysis with an SOA model highlight that unspeciated organics (i.e., unresolved complex mixture) are a very important class of precursors and that multigenerational processing of both gases and particles is important at longer time scales. The chemical evolution of the organic aerosol inside the PAM reactor appears to be similar to that observed in the atmosphere. The mass spectrum of the unoxidized primary organic aerosol closely resembles ambient hydrocarbon-like organic aerosol (HOA). After aging the exhaust equivalent to a few hours of atmospheric oxidation, the organic aerosol most closely resembles semivolatile oxygenated organic aerosol (SV-OOA) and then low-volatility organic aerosol (LV-OOA) at higher OH exposures. Scaling the data suggests that mobile sources contribute ∼ 2.9 ± 1.6 Tg SOA yr(-1) in the United States, which is a factor of 6 greater than all mobile source particulate matter emissions reported by the National Emissions Inventory. This highlights the important contribution of SOA formation from vehicle exhaust to ambient particulate matter concentrations in urban areas

Quantifying proximity, confinement, and interventions in disease outbreaks: a decision support framework for air-transported pathogens

Includes bibliographical references (pages H-I).The inability to communicate how infectious diseases are transmitted in human environments has triggered avoidance of interactions during the COVID-19 pandemic. We define a metric, Effective ReBreathed Volume (ERBV), that encapsulates how infectious pathogens, including SARS-CoV-2, transport in air. ERBV separates environmental transport from other factors in the chain of infection, allowing quantitative comparisons among situations. Particle size affects transport, removal onto surfaces, and elimination by mitigation measures, so ERBV is presented for a range of exhaled particle diameters: 1, 10, and 100 μm. Pathogen transport depends on both proximity and confinement. If interpersonal distancing of 2 m is maintained, then confinement, not proximity, dominates rebreathing after 10–15 min in enclosed spaces for all but 100 μm particles. We analyze strategies to reduce this confinement effect. Ventilation and filtration reduce person-to-person transport of 1 μm particles (ERBV1) by 13–85% in residential and office situations. Deposition to surfaces competes with intentional removal for 10 and 100 μm particles, so the same interventions reduce ERBV10 by only 3–50%, and ERBV100 is unaffected. Prior knowledge of size-dependent ERBV would help identify transmission modes and effective interventions. This framework supports mitigation decisions in emerging situations, even before other infectious parameters are known

Long-term particulate matter modeling for health effect studies in California – Part 2: Concentrations and sources of ultrafine organic aerosols

Organic aerosol (OA) is a major constituent of ultrafine particulate matter (PM_0. 1). Recent epidemiological studies have identified associations between PM_0. 1 OA and premature mortality and low birth weight. In this study, the source-oriented UCD/CIT model was used to simulate the concentrations and sources of primary organic aerosols (POA) and secondary organic aerosols (SOA) in PM_0. 1 in California for a 9-year (2000–2008) modeling period with 4 km horizontal resolution to provide more insights about PM_0. 1 OA for health effect studies. As a related quality control, predicted monthly average concentrations of fine particulate matter (PM_2. 5) total organic carbon at six major urban sites had mean fractional bias of −0.31 to 0.19 and mean fractional errors of 0.4 to 0.59. The predicted ratio of PM_2. 5 SOA ∕ OA was lower than estimates derived from chemical mass balance (CMB) calculations by a factor of 2–3, which suggests the potential effects of processes such as POA volatility, additional SOA formation mechanism, and missing sources. OA in PM_0. 1, the focus size fraction of this study, is dominated by POA. Wood smoke is found to be the single biggest source of PM_0. 1 OA in winter in California, while meat cooking, mobile emissions (gasoline and diesel engines), and other anthropogenic sources (mainly solvent usage and waste disposal) are the most important sources in summer. Biogenic emissions are predicted to be the largest PM_0. 1 SOA source, followed by mobile sources and other anthropogenic sources, but these rankings are sensitive to the SOA model used in the calculation. Air pollution control programs aiming to reduce the PM_0. 1 OA concentrations should consider controlling solvent usage, waste disposal, and mobile emissions in California, but these findings should be revisited after the latest science is incorporated into the SOA exposure calculations. The spatial distributions of SOA associated with different sources are not sensitive to the choice of SOA model, although the absolute amount of SOA can change significantly. Therefore, the spatial distributions of PM_0. 1 POA and SOA over the 9-year study period provide useful information for epidemiological studies to further investigate the associations with health outcomes

Influence of vapor wall loss in laboratory chambers on yields of secondary organic aerosol

Atmospheric secondary organic aerosol (SOA) has important impacts on climate and air quality, yet models continue to have difficulty in accurately simulating SOA concentrations. Nearly all SOA models are tied to observations of SOA formation in laboratory chamber experiments. Here, a comprehensive analysis of new experimental results demonstrates that the formation of SOA in laboratory chambers may be substantially suppressed due to losses of SOA-forming vapors to chamber walls, which leads to underestimates of SOA in air-quality and climate models, especially in urban areas where anthropogenic SOA precursors dominate. This analysis provides a time-dependent framework for the interpretation of laboratory chamber experiments that will allow for development of parameterized models of SOA formation that are appropriate for use in atmospheric models

Simulating secondary organic aerosol in a regional air quality model using the statistical oxidation model – Part 2: Assessing the influence of vapor wall losses

The influence of losses of organic vapors to chamber walls during secondary organic aerosol (SOA) formation experiments has recently been established. Here, the influence of such losses on simulated ambient SOA concentrations and properties is assessed in the University of California at Davis / California Institute of Technology (UCD/CIT) regional air quality model using the statistical oxidation model (SOM) for SOA. The SOM was fit to laboratory chamber data both with and without accounting for vapor wall losses following the approach of Zhang et al. (2014). Two vapor wall-loss scenarios are considered when fitting of SOM to chamber data to determine best-fit SOM parameters, one with “low” and one with “high” vapor wall-loss rates to approximately account for the current range of uncertainty in this process. Simulations were run using these different parameterizations (scenarios) for both the southern California/South Coast Air Basin (SoCAB) and the eastern United States (US). Accounting for vapor wall losses leads to substantial increases in the simulated SOA concentrations from volatile organic compounds (VOCs) in both domains, by factors of  ∼  2–5 for the low and  ∼  5–10 for the high scenarios. The magnitude of the increase scales approximately inversely with the absolute SOA concentration of the no loss scenario. In SoCAB, the predicted SOA fraction of total organic aerosol (OA) increases from  ∼  0.2 (no) to  ∼  0.5 (low) and to  ∼  0.7 (high), with the high vapor wall-loss simulations providing best general agreement with observations. In the eastern US, the SOA fraction is large in all cases but increases further when vapor wall losses are accounted for. The total OA ∕ ΔCO ratio captures the influence of dilution on SOA concentrations. The simulated OA ∕ ΔCO in SoCAB (specifically, at Riverside, CA) is found to increase substantially during the day only for the high vapor wall-loss scenario, which is consistent with observations and indicative of photochemical production of SOA. Simulated O : C atomic ratios for both SOA and for total OA increase when vapor wall losses are accounted for, while simulated H : C atomic ratios decrease. The agreement between simulations and observations of both the absolute values and the diurnal profile of the O : C and H : C atomic ratios for total OA was greatly improved when vapor wall-losses were accounted for. These results overall demonstrate that vapor wall losses in chambers have the potential to exert a large influence on simulated ambient SOA concentrations, and further suggest that accounting for such effects in models can explain a number of different observations and model–measurement discrepancies

Oxygenated Aromatic Compounds are Important Precursors of Secondary Organic Aerosol in Biomass Burning Emissions

Biomass burning is the largest combustion-related source of volatile organic compounds (VOCs) to the atmosphere. We describe the development of a state-of-the-science model to simulate the photochemical formation of secondary organic aerosol (SOA) from biomass-burning emissions observed in dry (RH <20%) environmental chamber experiments. The modeling is supported by (i) new oxidation chamber measurements, (ii) detailed concurrent measurements of SOA precursors in biomass-burning emissions, and (iii) development of SOA parameters for heterocyclic and oxygenated aromatic compounds based on historical chamber experiments. We find that oxygenated aromatic compounds, including phenols and methoxyphenols, account for slightly less than 60% of the SOA formed and help our model explain the variability in the organic aerosol mass (R² = 0.68) and O/C (R² = 0.69) enhancement ratios observed across 11 chamber experiments. Despite abundant emissions, heterocyclic compounds that included furans contribute to ∼20% of the total SOA. The use of pyrolysis-temperature-based or averaged emission profiles to represent SOA precursors, rather than those specific to each fire, provide similar results to within 20%. Our findings demonstrate the necessity of accounting for oxygenated aromatics from biomass-burning emissions and their SOA formation in chemical mechanisms

Modeling Secondary Organic Aerosol Formation From Emissions of Combustion Sources

Atmospheric aerosols exert a large influence on the Earth’s climate and cause adverse public health effects, reduced visibility and material degradation. Secondary organic aerosol (SOA), defined as the aerosol mass arising from the oxidation products of gas-phase organic species, accounts for a significant fraction of the submicron atmospheric aerosol mass. Yet, there are large uncertainties surrounding the sources, atmospheric evolution and properties of SOA. This thesis combines laboratory experiments, extensive data analysis and global modeling to investigate the contribution of semi-volatile and intermediate volatility organic compounds (SVOC and IVOC) from combustion sources to SOA formation. The goals are to quantify the contribution of these emissions to ambient PM and to evaluate and improve models to simulate its formation. To create a database for model development and evaluation, a series of smog chamber experiments were conducted on evaporated fuel, which served as surrogates for real-world combustion emissions. Diesel formed the most SOA followed by conventional jet fuel / jet fuel derived from natural gas, gasoline and jet fuel derived from coal. The variability in SOA formation from actual combustion emissions can be partially explained by the composition of the fuel. Several models were developed and tested along with existing models using SOA data from smog chamber experiments conducted using evaporated fuel (this work, gasoline, fischertropschs, jet fuel, diesels) and published data on dilute combustion emissions (aircraft, on- and off-road gasoline, on- and off-road diesel, wood burning, biomass burning). For all of the SOA data, existing models under-predicted SOA formation if SVOC/IVOC were not included. For the evaporated fuel experiments, when SVOC/IVOC were included predictions using the existing SOA model were brought to within a factor of two of measurements with minor adjustments to model parameterizations. Further, a volatility-only model suggested that differences in the volatility of the precursors were able to explain most of the variability observed in the SOA formation. For aircraft exhaust, the previous methods to simulate SOA formation from SVOC and IVOC performed poorly. A more physically-realistic modeling framework was developed, which was then used to show that SOA formation from aircraft exhaust was (a) higher for petroleumbased than synthetically derived jet fuel and (b) higher at lower engine loads and vice versa. All of the SOA data from combustion emissions experiments were used to determine source-specific parameterizations to model SOA formation from SVOC, IVOC and other unspeciated emissions. The new parameterizations were used to investigate their influence on the OA budget in the United States. Combustion sources were estimated to emit about 2.61 Tg yr-1 of SVOC, IVOC and other unspeciated emissions (sixth of the total anthropogenic organic emissions), which are predicted to double SOA production from combustion sources in the United States. The contribution of SVOC and IVOC emissions to global SOA formation was assessed using a global climate model. Simulations were performed using a modified version of GISS GCM II’. The modified model predicted that SVOC and IVOC contributed to half of the OA mass in the atmosphere. Their inclusion improved OA model-measurement comparisons for absolute concentrations, POA-SOA split and volatility (gas-particle partitioning) globally suggesting that atmospheric models need to incorporate SOA formation from SVOC and IVOC if they are to reasonably predict the abundance and properties of aerosols. This thesis demonstrates that SVOC/IVOC and possibly other unspeciated organics emitted by combustion sources are very important precursors of SOA and potentially large contributors to the atmospheric aerosol mass. Models used for research and policy applications need to represent them to improve model-predictions of aerosols on climate and health outcomes. The improved modeling frameworks developed in this dissertation are suitable for implementation into chemical transport models.</p