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The U.S. EPA developed the Regional Haze Rule to address Section 7491 of the 1977 Clean Air Act Amendments to prevent any future and remedy any existing visibility impairment due to manmade air pollution at Federal Class I areas (CIAs). The rule addresses this national goal by requiring states to show they are making progress toward estimated natural conditions by 2064 for the 20% anthropogenically Most Impaired Days (MID). For the MID, days that have high haze contributions from wildfires and windblown dust tend to be excluded using haze contributions from Carbon and crustal material as surrogates. To show progress toward natural conditions in 2064, a Uniform Rate of Progress Glidepath is defined as a straight line from measured 2000–2004 IMPROVE MID Baseline to natural conditions in 2064. Photochemical modeling is used to project the observed IMPROVE 2014–2018 MID visibility to 2028 that is compared to the Glidepath at 2028 to determine whether the MID visibility at a CIA is on a path toward natural visibility conditions in 2064. This paper discusses an alternative approach for showing progress toward no manmade impairment by using modeling results to generate a U.S. Anthropogenic Emissions Rate of Progress (RoP). The CAMx photochemical grid model was run for a current year (representing 2014–2018), 2028 future year and a 2002 past year and source apportionment was used to isolate the contributions of U.S. anthropogenic emissions to PM concentrations and visibility extinction. A RoP slope line is drawn from the 2002 visibility extinction due to U.S. anthropogenic emissions to zero in 2064 and the CAMx 2028 visibility for U.S. anthropogenic emissions is compared with the RoP slope line at 2028 to determine whether visibility due to U.S. anthropogenic emissions is on a path toward no U.S. manmade impairment in 2064. Implications: The U.S. EPA Regional Haze Rule guidance to show progress toward no U.S. manmade visibility impairment at Class I Areas by 2064 backs into the U.S. manmade impairment contribution by using total atmospheric haze based on measured PM concentrations and subtracting uncertain estimates of routine natural and episodic (i.e. wildfires and windblown dust) natural conditions. The guidance also recommends accounting for visibility contributions due to international anthropogenic and prescribed fire emissions that are also uncertain. This paper presents an alternative approach that models the contributions of U.S. anthropogenic emissions to visibility for past, current and future years using source apportionment to show that U.S. anthropogenic emissions visibility impairment at Class I areas are on a path toward no contribution in 2064. Many U.S. anthropogenic emissions (e.g. power plants with continuous emissions monitoring systems) are better known and characterized than international, fire and natural emissions so the alternative approach should provide a better assessment of whether U.S. anthropogenic emissions are on a path toward no manmade impairment in 2064 than using trends in the measured visibility most impaired days that rely on uncertain estimates of haze due to wildfire, windblown dust, and international emissions and uncertain estimates of natural conditions in 2064. [ABSTRACT FROM AUTHOR]

The Western Regional Air Partnership (WRAP) has developed a modeling platform to simulate the formation of haze-causing particles that impact federally-protected lands in the western United States. To assist state air quality planners in determining which emission sources are likely candidates for future mitigation, several source apportionment scenarios were evaluated, and two sets of results for the year 2028 are presented here: 1) a "high-level important regional sources" version, with broad emission categories (i.e. U.S. anthropogenic, international anthropogenic, natural, and fires), and 2) a "low-level anthropogenic emission sources within individual states" version, which refines the U.S. anthropogenic contribution to specific emission sectors within individual WRAP region states. Eight examples are discussed, which reflect the variation in source apportionment results at national parks, wilderness areas, and wildlife refuges in the western U.S. and suggest which emission sectors are candidates for mitigation to improve future visibility. In 2028, the contribution of domestic anthropogenic emissions at the eight sites ranges from 17% to 58%, with significant impacts from oil and gas production, fossil fuel electric generation, and federally-regulated mobile sources. The contribution from international anthropogenic sources can also be considerable, and ranges from 17% to 43%. Most sectors that are emitting sulfur dioxide (SO2) and nitrogen oxides (NOx), which are the two most likely particle precursors to be curtailed in the states' Regional Haze plans, are declining. For example, in the 13 contiguous WRAP region states, NOx emissions from on-road mobile sources and electric generating units (EGUs) declined by 738 kton/yr (29% decrease) and 65 kton/yr (31% decrease), respectively, in 2028 as compared to current emission estimates, and SO2 emissions from EGUs declined by 42 kton/yr (29% decrease). NOx emissions from oil and gas development also declined by 25 kton/yr (9% decrease) but rose for SO2 emissions by 12 kton/yr (20% increase). Implications: The goal of the Regional Haze Rule (RHR) is to improve visibility at federally-protected areas, and to eventually arrive at natural conditions by the year 2064. Source apportionment tools within regional air quality models are useful for identifying which emission regions and sectors are contributing to haze-causing particles and can indicate to air quality planners where additional emission controls may be warranted. [ABSTRACT FROM AUTHOR]

This paper describes a study to evaluate the capability of a photochemical grid modeling system to predict changes in ozone concentrations in response to emission changes over a period of several years. The development of regulatory emission control plans to meet air quality standards primarily relies on modeled projections of future-year air quality, although a weight of evidence approach (which takes into account a number of factors including modeling results, model evaluation and other pertinent information such as ambient trends) is recommended and is also typically used as part of the attainment demonstration. Thus, it is important to determine if the modeling system used to project future-year quality can correctly simulate ozone responses to the projected emissions reductions. Uncertainties and errors in modeled projections can lead to erroneous estimates of emissions controls required to attain the standards. We use two existing regulatory modeling databases, employed for forecasting future-year air quality in the South Coast Air Basin (SoCAB) of California, for a number of historical years to evaluate the ability of the system to accurately simulate the observed changes in air quality over a multi-year period. The evaluation results with the older (2012) database show that the modeling system consistently under-predicts the reductions in ozone in response to emission reductions over the years. Model response improves with the newer (2016) database with good agreement at some locations, but the system still tends to under-predict ozone responses by as much as a factor of 2 in recent years for the Basin maximum ozone design value. This suggests that future-year estimates of ozone design values may be overly conservative, resulting in emission controls that are technologically challenging or very expensive to implement. The development of better emission inventories and model inputs is recommended to develop a modeling system that more accurately responds to emission changes. Future regulatory planning should include dynamic evaluation in addition to the traditional operational evaluation of the model to provide more confidence to all stakeholders that the resulting policy decisions are necessary to attain the air quality standards and to protect public health. [ABSTRACT FROM AUTHOR]

Abstract: We conducted four source apportionment simulations using the Community Multiscale Air Quality (CMAQ) photochemical grid modelling system in order to investigate and assess the relative importance of specific emissions sources and/or geographic regions on ambient ozone and PM air quality in the Alberta Oil Sands Region (AOSR). Local point and area sources, medium range transport of mobile sources and biogenic emissions were examined. The elimination of emissions from local stationary point sources reduced 8-h ozone concentrations and greatly reduces the PM2.5 concentrations in AOSR; similar results are seen in the local area source zero-out simulations but with less ozone and PM2.5 reductions than seen in the local point source zero-out run. Although the mobile source medium-range transport reduced 8-h ozone concentrations in the urban plume from Edmonton that results in some ozone and PM2.5 concentration reductions in the southern part of the AOSR, it has little effect on the elevated ozone and PM2.5 concentrations in the oil sands development area of the AOSR where the highest ozone and PM2.5 concentrations are estimated. The elimination of all anthropogenic emissions in Alberta so that only biogenic emissions remained resulted in large reductions in 8-h ozone concentrations in the AOSR, with the highest remaining ozone in the 50–52ppb range occurring south of Fort McMurray; very low PM2.5 concentrations are also estimated across Alberta, including the AOSR, when anthropogenic emissions are eliminated in Alberta. [Copyright &y& Elsevier]

Abstract: Operational, diagnostic, and comparative evaluations of two one-atmosphere regional models were performed for the full calendar year 2002 in support of regional haze regulatory applications in the eastern US. Using consistent emissions, meteorological and air quality data sets, the community multi-scale air quality and comprehensive air quality model with extensions models were exercised on a nested 36/12km grid system and evaluated across a broad range of time and space scales for numerous gas-phase and fine particulate species derived from routine and research-grade ambient measurements at six monitoring networks. Performance by both models for speciated fine particulate matter (PM) across the eastern US ranged from quite good (e.g., SO4 2−) to poor (e.g., soil). For most species, model bias was higher in the winter and lower (usually negative) in the summer suggesting potential issues related to vertical mixing (e.g., too little in winter), temporal allocation of emissions, and/or other model science processes or inputs. These results may be used to (a) guide one-atmosphere model refinements, (b) improve data input preparation procedures, (c) evaluate methods for rigorous, stressful performance testing, and (d) clarify the uncertainty in model estimates for regional haze and PM2.5 control strategy programs. [Copyright &y& Elsevier]

Abstract: Photochemical grid models are being used in technical analyses by the Visibility Improvement State and Tribal Association of the Southeast (VISTAS), a regional air quality planning organization in the southeastern United States, to support state implementation plans for regional haze and related air quality issues. VISTAS has embarked on a multi-phase process of testing and evaluating regional meteorological, emissions and air quality models that will be used to project visibility improvements as required by the regional haze rule. VISTAS has generated 2002 annual emissions and meteorological inputs for two photochemical grid models, the community multi-scale air quality (CMAQ) and the comprehensive air-quality model with extensions (CAMx), at a 36km resolution for the continental US and at 12km resolution for the eastern US. The two models were evaluated using speciated PM measurements from various monitoring networks and detailed analysis was performed for organic carbon (OC) mass using the IMPROVE, STN, and SEARCH networks. The differences in model performance between CMAQ and CAMx were used as a diagnostic tool to investigate performance issues for several compounds. CAMx performed substantially better than CMAQ for OC (defined as 1.4×measured organic carbon) which led to investigations into methods for improving the CMAQ OC model performance. The treatment of secondary organic aerosol (SOA) was identified as an area needing improvements in both models. The impact of replacing the CMAQ SOA parameters with those from CAMx was investigated. Further analysis identified several processes that are potentially important for SOA formation that are not treated in either model including, polymerization of the SOA into non-volatile particles and SOA formation from sesquiterpene, isoprene and other biogenic VOCs. A prototype mechanism for several of these missing processes was developed and the CMAQ SOA module was enhanced to include these SOA formation processes. SOA yields, specifically from biogenic emissions, were increased by the modified SOA module and CMAQ model performance for particulate OC at the IMPROVE, SEARCH, and STN sites in the VISTAS region was improved. [Copyright &y& Elsevier]

The Visibility Improvement State and Tribal Association of the Southeast (VISTAS) is one of five Regional Planning Organizations that is charged with the management of haze, visibility, and other regional air quality issues in the United States. The VISTAS Phase I work effort modeled three episodes (January 2002, July 1999, and July 2001) to identify the optimal model configuration(s) to be used for the 2002 annual modeling in Phase II. Using model configurations recommended in the Phase I analysis, 2002 annual meteorological (Mesoscale Meterological Model [MM5]), emissions (Sparse Matrix Operator Kernal Emissions [SMOKE]), and air quality (Community Multiscale Air Quality [CMAQ]) simulations were performed on a 36-km grid covering the continental United States and a 12-km grid covering the Eastern United States. Model estimates were then compared against observations. This paper presents the results of the preliminary CMAQ model performance evaluation for the initial 2002 annual base case simulation. Model performance is presented for the Eastern United States using speciated fine particle concentration and wet deposition measurements from several monitoring networks. Initial results indicate fairly good performance for sulfate with fractional bias values generally within ±20%. Nitrate is overestimated in the winter by approximately ±50% and underestimated in the summer by more than ±100%. Organic carbon exhibits a large summer underestimation bias of approximately ±100% with much improved performance seen in the winter with a bias near zero. Performance for elemental carbon is reasonable with fractional bias values within ±40%. Other fine particulate (soil) and coarse particular matter exhibit large (80-150%) overestimation in the winter but improved performance in the summer. The preliminary 2002 CMAQ runs identified several areas of enhancements to improve model performance, including revised temporal allocation factors for ammonia emissions to improve nitrate performance and addressing missing processes in the secondary organic aerosol module to improve OC performance. [ABSTRACT FROM AUTHOR]

Version 4.10s of the comprehensive air-quality model with extensions (CAMx) photochemical grid model has been developed, which includes two options for representing particulate matter (PM) size distribution: (1) a two-section representation that consists of fine (PM2.5) and coarse (PM2.5-10) modes that has no interactions between the sections and assumes all of the secondary PM is fine; and (2) a multisectional representation that divides the PM size distribution into N sections (e.g., N = 10) and simulates the mass transfer between sections because of coagulation, accumulation, evaporation, and other processes. The model was applied to Southern California using the two-section and multisection representation of PM size distribution, and we found that allowing secondary PM to grow into the coarse mode had a substantial effect on PM concentration estimates. CAMx was then applied to the Western United States for the 1996 annual period with a 36-km grid resolution using both the twosection and multisection PM representation. The Community Multiscale Air Quality (CMAQ) and Regional Modeling for Aerosol and Deposition (REMSAD) models were also applied to the 1996 annual period. Similar model performance was exhibited by the four models across the Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network monitoring networks. All four of the models exhibited fairly low annual bias for secondary PM sulfate and nitrate but with a winter overestimation and summer underestimation bias. The CAMx multisectional model estimated that coarse mode secondary sulfate and nitrate typically contribute <10% of the total sulfate and nitrate when averaged across the more rural IMPROVE monitoring network. [ABSTRACT FROM AUTHOR]

Summary 1. Crop damage caused by pest bird species is an economic problem in agricultural areas world-wide. Previous research in North America has focused on estimating regional loss of yield for economic purposes, and largely ignored small-scale variation in crop damage. If a bird depredation problem is perceived, farmers need to know how to identify areas of their farms that are most susceptible to bird damage so that they may focus their deterrent efforts most efficiently. 2. We developed sensitive sampling and analysis techniques to allow the identification of spatial and temporal patterns in bird damage to wine grapes at the level of single vineyards. 3. We used visual estimation techniques and novel data collection and management procedures to detect small-scale spatiotemporal patterns in bird damage to Baco Noir and Vidal (ice-wine) grape varieties in the St Catharine’s area of Ontario, Canada, during the 1998 and 1999 ripening seasons. We detected three overall trends in study vineyards: (i) bird damage was greatest on the edges of vineyards and decreased with distance towards the centre; (ii) bird damage was vertically stratified in vineyards, with grape clusters near the top of vines sustaining more damage than those close to the ground; and (iii) bird damage increased at specific times during the ripening season. 4. An exotic species, the European starling, was responsible for most of the crop damage. Starlings foraged by making short forays into vineyards from perches in adjacent vegetation. This kind of foraging behaviour was reflected in the spatial damage patterns measured in our study plots. 5. We suggest that the data presented here are more useful than estimates of total loss of yield to the managers of individual farms, because they identify the areas of vineyards most susceptible to bird damage. Future field experiments should evaluate the utility of focusing deterrent measures only in the most highly susceptible areas of crop fields.... [ABSTRACT FROM AUTHOR]

Focuses on the use of emission tests to model the impact of fuel/vehicle changes on ozone formation in parts of the United States. Effect of gasoline on the ozone; Overall assessment of emissions from light-duty vehicles.

The 2017 revisions to the Regional Haze Rule clarify that visibility progress at Class I national parks and wilderness areas should be tracked on days with the highest anthropogenic contributions to haze (impairment). We compare the natural and anthropogenic contributions to haze in the western United States in 2011 estimated using the Environmental Protection Agency (EPA) recommended method and using model projections from the Comprehensive Air Quality Model with Extensions (CAMx) and the Particulate Source Apportionment Tool (PSAT). We do so because these two methods will be used by states to demonstrate visibility progress by 2028. If the two methods assume different natural and anthropogenic contributions, the projected benefits of reducing U.S. anthropogenic emissions will differ. The EPA method assumes that episodic elevated carbonaceous aerosols greater than an annual 95th percentile threshold are natural events. For western U.S. IMPROVE monitoring sites reviewed in this paper, CAMx-PSAT confirms these episodes are impacted by carbon from wildfire or prescribed fire events. The EPA method assumes that most of the ammonium sulfate is anthropogenic in origin. At most western sites CAMx-PSAT apportions more of the ammonium sulfate on the most impaired days to global boundary conditions and anthropogenic Canadian, Mexican, and offshore shipping emissions than to U.S. anthropogenic sources. For ammonium nitrate and coarse mass, CAMx-PSAT apportions greater contributions to U.S. anthropogenic sources than the EPA method assigns to total anthropogenic contributions. We conclude that for western IMPROVE sites, the EPA method is effective in selecting days that are likely to be impacted by anthropogenic emissions and that CAMx-PSAT is an effective approach to estimate U.S. source contributions. Improved inventories, particularly international and natural emissions, and further evaluation of global and regional model performance and PSAT attribution methods are recommended to increase confidence in modeled source characterization. Implications: The western states intend to use the CAMx model to project visibility progress by 2028. Modeled visibility response to changes in U.S. anthropogenic emissions may be less than estimated using the EPA assumptions based on total U.S. and international anthropogenic contributions to visibility impairment. Additional model improvements are needed to better account for contributions to haze from natural and international emissions in current and future modeling years. These improvements will allow more direct comparison of model and EPA estimates of natural and anthropogenic contributions to haze and future visibility progress. [ABSTRACT FROM AUTHOR]

One of the potential environmental issues associated with oil sands development is increased ozone formation resulting from NO X and volatile organic compound emissions from bitumen extraction, processing and upgrading. To manage this issue in the Athabasca Oil Sands Region (AOSR) in northeast Alberta, a regional multi-stakeholder group, the Cumulative Environmental Management Association (CEMA), developed an Ozone Management Framework that includes a modelling based assessment component. In this paper, we describe how the Community Multi-scale Air Quality (CMAQ) model was applied to assess potential ground-level ozone formation and impacts on ambient air quality and vegetation health for three different ozone precursor cases in the AOSR. Statistical analysis methods were applied, and the CMAQ performance results met the U.S. EPA model performance goal at all sites. The modelled 4th highest daily maximum 8-h average ozone concentrations in the base and two future year scenarios did not exceed the Canada-wide standard of 65 ppb or the newer Canadian Ambient Air Quality Standards of 63 ppb in 2015 and 62 ppb in 2020. Modelled maximum 1-h ozone concentrations in the study were well below the Alberta Ambient Air Quality Objective of 82 ppb in all three cases. Several ozone vegetation exposure metrics were also evaluated to investigate the potential impact of ground-level ozone on vegetation. The chronic 3-months SUM60 exposure metric is within the CEMA baseline range (0–2000 ppb-hr) everywhere in the AOSR. The AOT40 ozone exposure metric predicted by CMAQ did not exceed the United Nations Economic Commission for Europe (UN/ECE) threshold of concern of 3000 ppb-hr in any of the cases but is just below the threshold in high-end future emissions scenario. In all three emission scenarios, the CMAQ predicted W126 ozone exposure metric is within the CEMA baseline threshold of 4000 ppb-hr. This study outlines the use of photochemical modelling of the impact of an industry (oil sands) on ground-level ozone levels as an air quality management tool in the AOSR. It allows an evaluation of the relationships between the pollutants emitted to the atmosphere and potential ground level ozone concentrations throughout the AOSR thereby extending the spatial coverage of the results beyond the monitoring network and also allowing an assessment of the potential impacts of possible future emission cases. [ABSTRACT FROM AUTHOR]

The current U.S. emission control requirements for on-road motor vehicles are driven by the ozone problem in the South Coast Air Basin (SoCAB) in southern California. Based on ozone modeling performed for Air Quality Management Plans (AQMPs), the SoCAB ozone attainment plan requires large (>80%) amounts of emission reductions in oxides of nitrogen (NOx) from current levels with more modest (~40%) controls on Volatile Organic Compounds (VOC). The shelter in place orders in response to the 2020 COVID-19 pandemic resulted in an immediate reduction in emissions, but instead of ozone being reduced, in 2020 the SoCAB saw some of the highest observed ozone levels in decades. We used the abrupt emissions reductions from 2019 to 2020 caused by COVID-19 to conduct a dynamic model evaluation of the Community Multiscale Air Quality (CMAQ) model to evaluate whether the models used to develop ozone control plans can correctly simulate the ozone response to the emissions reductions. Ozone modeling was conducted for three scenarios: 2019 Base, 2020 business-as-usual (i.e., without COVID reductions), and 2020 COVID. We found that modeled ozone changes between 2019 and 2020 were generally consistent with the observed ozone changes. We determined that meteorology played the major role in the increases in ozone between 2019 and 2020; however, the reduction in NOX emissions also caused ozone increases in Los Angeles County and into western San Bernardino County, with more widespread ozone decreases further to the east. [ABSTRACT FROM AUTHOR]

Air quality models are increasingly used to develop estimates of dry and wet deposition of sulfate and nitrate in watersheds (because of lack of measurements) in an effort to determine the acidifying deposition load into the aquatic systems. These models need to be rigorously evaluated to ensure that one can rely on the modeled quantities instead of the measured quantities. In the United State (U.S.), these models have been proposed for use in establishing national standards based on modeled quantities. The U.S. Environmental Protection Agency (EPA) is considering aquatic acidification as the main ecological endpoint of concern in determining the secondary national ambient air quality standards for nitrogen oxides and sulfur oxides. Acidification is tied to depositions of sulfur and nitrogen, which are linked to ambient concentrations of the elements. As EPA proposes to use a chemical transport model in linking deposition to ambient concentration, it is important to investigate how the currently used chemical transport models perform in predicting depositions and ambient concentrations of relevant chemical species and quantify the variability in their estimates. In this study, several annual simulations by multiple chemical transport models for the entire continental U.S. domain are evaluated against available measurement data for depositions and ambient concentrations of sulfur oxides and reactive nitrogen species. The model performance results vary by evaluation time-scale and geographical region. Evaluation of annualized quantities (annual average ambient concentrations and annual total depositions) suppresses the large variances shown in the evaluation using the observation's native shorter-term time-scales (e.g., weekly). In addition, there is a large degree of bias and error (especially for deposition fluxes) in the modeling results that brings to question the suitability of using air quality models to provide estimates of deposition loads. Variability in the ratio of deposition to ambient concentration, so-called the Transference Ratio that EPA has proposed to use in linking deposition to ambient concentration, is also examined. Our study shows that the Transference Ratios as well as total reduced nitrogen deposition, another modeled parameter EPA proposed to use in the process of determining the new secondary standard, vary considerably by geographical region and by model simulation. [ABSTRACT FROM AUTHOR]

Abstract: The Community Multiscale Air Quality (CMAQ) and the Sparse Matrix Operator Kernel Emissions (SMOKE) modeling systems were used to simulate emissions and air quality in North Eastern Alberta where a rapid rise in oil sands development has caused air quality concerns over the last decade. The models were run on a 36/12/4 km domain for the four month period of May through August 2002. A model performance evaluation was conducted by comparing the CMAQ model estimates against ambient air quality measurements. In the Alberta oil sands region, the model tended to achieve or nearly achieve ozone model performance goals, albeit with an underestimation bias. The magnitudes of the observed PM2.5 concentrations were matched by the modeling system, except when the observed PM2.5 concentrations were influenced by emissions from forest fires in which case the model underestimated the observed PM2.5 concentrations. The CMAQ-estimated 4th highest daily maximum 8-hour ozone concentrations in the oil sands region were below the 65 ppb Canada Wide Standard (CWS) as well as the 58 ppb Alberta Management Plan Trigger Level. The highest estimated ozone concentrations occurred near the oil sands development area just north of Fort McMurray with values approaching, but below, the 58 ppb Management Plan Trigger Level; estimated ozone concentrations are much lower in the farther northern portions of the oil sands region. The acute (i.e., maximum 3-day value) SUM60 vegetative ozone exposure metric was mostly less than 100 ppb h, which is below the threshold of concern for crops. However, just north of Fort McMurray there were small areas where the acute SUM60 metric exceeded the 500–700 ppb h threshold of concern for crops with maximum values in plumes from sources in the oil sands mine area of ∼900 ppb h. The maximum chronic (three-month average) SUM60 ozone exposure metric was below the thresholds of concern. The CMAQ-estimated maximum 98th percentile 24-hour average PM2.5 concentration occurs in the mine area north of Fort McMurray and was below the CWS threshold (30 μg m−3), however it was above the Alberta Management Plan Trigger Level (20 μg m−3). The estimated 98th percentile 24- hour average PM2.5 concentrations were mostly in the 2–6 μg m−3 range with regions of higher PM2.5 concentrations predicted just north of Fort McMurray in the oil sands development region. [Copyright &y& Elsevier]

Two efficient methods to study relationships between particulate matter (PM) concentrations and emission sources are compared in the three-dimensional comprehensive air quality model with extensions (CAMx). Particulate source apportionment technology (PSAT) is a tagged species method that apportions concentrations of PM components to their respective primary precursors, e.g., sulfate is apportioned to SOx, nitrate to NOx, etc. The decoupled direct method (DDM) calculates first-order sensitivities of PM concentrations to model inputs. Both tools were applied to two month long (February and July) PM modeling episodes and evaluated against changes in PM concentrations due to various emission reductions. The results show that source contributions calculated by PSAT start to deviate from the actual model responses as indirect effects from limiting reactants or nonprimary precursor emissions become important. The DDM first-order sensitivity is useful for determining source contributions only if the model response to input changes is reasonably linear. For secondary inorganic PM, the response is linear for emission reductions of 20% in all cases considered and reasonably linear for reductions of 100% in the case of on-road mobile sources. The model response for secondary organic aerosols and primary PM remains nearly linear to 100% reductions in anthropogenic emissions. [ABSTRACT FROM AUTHOR]

We assessed the nutritional importance of mat provisioning to females during egg production and its effects on clutch parameters (egg size, length of the laying period) in Common Terns Sterna hirundo: (1) we estimated the costs of egg production by modeling the daily protein, lipid, and energy requirements of laying females, and (2) compared these costs to both the amount, and the timing, of the male's contribution via mate provisioning. Net lipid, net protein, and gross energy requirements for a three-egg clutch were estimated to be 5.4 g, 8.6 g, and 569 kJ respectively. Peak protein and lipid requirements occurred one (day -1) and two (day -2) days before laying, respectively. Peak energy requirement occurred on day -1; a cost of 127% to 157% above maintenance. Variation in male provisioning effort (in terms of energy and nutrients delivered) paralleled variation in predicted female requirements for egg production at the level of individual pairs. Males delivered protein in excess of the female's requirements on all days investigated. Male lipid delivery accounted for 45% of female net requirement on the day when demand was greatest (day -2), but exceeded requirements on all other days. However, the proportion of the female's total energy budget (egg production, maintenance, and activity costs) that was supplied by her mate rose from an average of 29% on day -2 to 76% during the interval between second and third eggs. Paradoxically, females that were fed at higher rates during the interval between first and second eggs produced clutches with lower total volumes, smaller last-laid eggs, and clutches with a greater egg-size hierarchy than conspecifics receiving less food from their mates. Also, females fed at higher rates during the interval between second and third eggs took longer to produce their clutch. These negative relationships between mate provisioning and clutch parameters contrast with previous studies in this and other species. [ABSTRACT FROM AUTHOR]

Presents an obituary of ornithologist and zoologist Roger Malcolm Evans.

Abstract A three-dimensional chemical transport model, PMCAMx, was used to quantify the contribution of biomass burning organic aerosol (bbOA) to total organic aerosol (OA) concentrations in the continental U.S. Simulations were performed during three seasonally-representative months (April, July, and September 2008). Biomass burning is predicted to contribute 9% of the domain-averaged OA in April, 28% in July and 13% in September. Secondary OA from semivolatile and intermediate volatility organic compounds is the largest contributor to bbOA concentrations for all months simulated, followed by fresh primary OA. PMCAMx bbOA predictions using the Volatility Basis Set were compared to the results of CAMx version 6.10 that assumes that bbOA is nonvolatile and inert. PMCAMx predicts 66%, 113%, and 108% higher average concentration values of bbOA for April, July, and September, respectively. Predicted OA concentrations at biomass-impacted sites were compared to observed values from the STN and IMPROVE networks. The treatment of biomass burning emissions as semivolatile and reactive improved model performance during the spring and summer. During the fall both models overpredicted the OA levels, suggesting that the fire emissions may have been overestimated. In this case the additional SOA produced in PMCAMx resulted in worse performance. Highlights • Treatment of biomass burning emissions as semivolatile improved model performance. • Biomass burning contributes 9% of the OA in April, 28% in July, 13% in September. • Secondary biomass burning OA can be more important on average than primary. [ABSTRACT FROM AUTHOR]

Acid deposition is a potential environmental impact of oil sands development in the Athabasca Oil Sands Region (AOSR) in Northeastern Alberta. An acid deposition management framework has been established to manage this issue. This framework includes an acid deposition modelling and time-to-effect impact assessment component that was recently implemented for four acidifying emissions cases using the Community Multi-scale Air Quality (CMAQ) model. Predicted gross Potential Acid Input (PAI) deposition in the AOSR increases from the historical to existing case with further increases predicted in two future cases due to the projected increase in NOx emissions. On average the total predicted PAI deposition in the AOSR is approximately 40% sulphur deposition and 60% nitrogen deposition. Sulphur deposition decreases by 7% from the historical to existing cases due to the reductions in SO 2 emissions that have occurred in the AOSR but increases by 5% from the existing to future case 1 and by 8% from existing to future case 2 even though continued AOSR SO 2 emission decreases were modelled. This is likely the result of the deposition reduction associated with a single large reduction in SO 2 emissions from one facility's main stack being offset elsewhere in the AOSR by deposition increases due to small increases in SO 2 emissions from several in situ sources with shorter stacks. Average nitrogen deposition over the AOSR increases by 10% from the historical to existing case and then further increases by 10.6% from the existing case to future case 1 and by 12.3% from the existing case to future case 2. The increasing relevance of NOx emissions over SO 2 emissions in the AOSR suggests that a robust treatment of nitrogen chemistry such as in CMAQ is required for conducting deposition assessments in the region. The modelling results provide information that can be used to inform oil sands emission management priorities in the context of acid deposition and nitrogen eutrophication impact minimization. [ABSTRACT FROM AUTHOR]

Abstract: Policy Relevant Background (PRB) ozone, as defined by the US Environmental Protection Agency (EPA), refers to ozone concentrations that would occur in the absence of all North American anthropogenic emissions. PRB enters into the calculation of health risk benefits, and as the US ozone standard approaches background levels, PRB is increasingly important in determining the feasibility and cost of compliance. As PRB is a hypothetical construct, modeling is a necessary tool. Since 2006 EPA has relied on global modeling to establish PRB for their regulatory analyses. Recent assessments with higher resolution global models exhibit improved agreement with remote observations and modest upward shifts in PRB estimates. This paper shifts the paradigm to a regional model (CAMx) run at 12km resolution, for which North American boundary conditions were provided by a low-resolution version of the GEOS-Chem global model. We conducted a comprehensive model inter-comparison, from which we elucidate differences in predictive performance against ozone observations and differences in temporal and spatial background variability over the US. In general, CAMx performed better in replicating observations at remote monitoring sites, and performance remained better at higher concentrations. While spring and summer mean PRB predicted by GEOS-Chem ranged 20–45ppb, CAMx predicted PRB ranged 25–50ppb and reached well over 60ppb in the west due to event-oriented phenomena such as stratospheric intrusion and wildfires. CAMx showed a higher correlation between modeled PRB and total observed ozone, which is significant for health risk assessments. A case study during April 2006 suggests that stratospheric exchange of ozone is underestimated in both models on an event basis. We conclude that wildfires, lightning NO x and stratospheric intrusions contribute a significant level of uncertainty in estimating PRB, and that PRB will require careful consideration in the ozone standard setting process. [Copyright &y& Elsevier]

Abstract: Past photochemical modeling of the western United States (US) using the Comprehensive Air quality Model with extensions (CAMx) and the Community Multiscale Air Quality (CMAQ) model has resulted in large springtime ozone over predictions in the complex high-elevation terrain of the western United States (US). Comparisons against rural measurement data have shown that both models over predicted ozone levels by 20ppb or more. A systematic investigation using CAMx revealed that excessive vertical transport in mountainous terrain draws down upper tropospheric ozone introduced by the lateral boundary conditions (developed by a global chemistry model), which can routinely exceed 1ppm near the tropopause. This is not an unreasonable concentration at such altitudes during the spring, and there is observational evidence that stratospheric ozone intrusions result in occasional large ground-level concentrations in the western US, but not at the frequency and intensity simulated by the CAMx and CMAQ models. Past versions of CAMx and CMAQ possess similar algorithms to diagnose vertical velocity, and similar first-order accurate vertical advection algorithms. These similarities, in conjunction with poor vertical resolution of the upper troposphere, have resulted in similar ozone performance issues. Numerous approaches were explored with CAMx in an attempt to externally reduce the rates of vertical transport over complex terrain. Ultimately, we formulated and tested a new vertical advection methodology that included improvements to how vertical velocities are determined and introduced a second-order accurate advection solver technique. Together these improvements proved to yield the most successful results in reducing upper tropospheric ozone transport to the surface. CAMx was then run to simulate ozone throughout the western US for a full year to evaluate the effects of the new vertical transport algorithm on model performance. Ozone performance improvements exceeded those achieved through the application of arbitrary reductions in the upper tropospheric/stratospheric lateral boundary conditions. [Copyright &y& Elsevier]

Abstract: Natural emissions adopted in current regional air quality modeling are updated to better describe natural background ozone and PM concentrations for North America. The revised natural emissions include organosulfur from the ocean, NO from lightning, sea salt, biogenic secondary organic aerosol (SOA) precursors, and pre-industrial levels of background methane. The model algorithm for SOA formation was also revised. Natural background ozone concentrations increase by up to 4ppb in annual average over the southeastern US and Gulf of Mexico due to added NO from lightning while the revised biogenic emissions produced less ozone in the central and western US. Natural PM2.5 concentrations generally increased with the revised natural emissions. Future year (2018) simulations were conducted for several anthropogenic emission reduction scenarios to assess the impact of the revised natural emissions on anthropogenic emission control strategies. Overall, the revised natural emissions did not significantly alter the ozone responses to the emissions reductions in 2018. With revised natural emissions, ozone concentrations were slightly less sensitive to reducing NOx in the southeastern US than with the current natural emissions due to higher NO from lightning. The revised natural emissions have little impact on modeled PM2.5 responses to anthropogenic emission reductions. However, there are substantial uncertainties in current representations of natural sources in air quality models and we recommend that further study is needed to refine these representations. [Copyright &y& Elsevier]

An on-line and an off-line version of a computationally efficient particulate matter source apportionment algorithm have been developed and compared using the three-dimensional chemical transport model PMCAMx. Both versions of the algorithm use source specific-species that track the contributions of source locations or source classes. The two versions showed a good agreement with each other and with more accurate, computationally demanding methods. The off-line algorithm (Particulate Source Apportionment Technology, PSAT) is simpler to implement, has a lower computational cost and is suitable for a range of source apportionment studies. As a first application, PSAT was used to investigate the contribution of power plant SO2 emissions to particulate sulfate concentrations in the Eastern United States. The impact of the transport of SO2 emissions from the Chicago, IL area and the impact of these emissions on particulate sulfate concentration in surrounding areas were also studied as a second application. The implementation of PSAT for the SO2/particulate sulfate system only resulted in a 1% increase in computation time over the base simulation. The algorithm provides a computationally efficient platform for the study of pollutant transport and source contributions on regional scales. [Copyright &y& Elsevier]

Describes the building of the legal foundation for an effective public health system in the U.S. Improvement of the system's capacity in the context of evolving health challenges; Factors affecting the delivery of essential public health services; Provision of public health services to state residents.

Guidance for the performance evaluation of three-dimensional air quality modeling systems for particulate matter and visibility is presented. Four levels are considered: operational, diagnostic, mechanistic, and probabilistic evaluations. First, a comprehensive model evaluation should be conducted in at least two distinct geographical locations and for several meteorological episodes. Next, streamlined evaluations can be conducted for other similar applications if the comprehensive evaluation is deemed satisfactory. In all cases, the operational evaluation alone is insufficient, and some diagnostic evaluation must always be carried out. Recommendations are provided for designing field measurement programs that can provide the data needed for such model performance evaluations.

We report the case of a patient, DrO, who has impaired auditory comprehension but intact written comprehension. His ability to repeat words that he cannot comprehend, and his good performance on auditory lexical decision, suggestthat DrO has an impairment of the mappings between the lexical representations of spoken words and theircorresponding semantic representations; a word meaning deafness. DrO`s ability to understand heard words depends on their imageability and length, such that he is worse at comprehending words that are both short and abstract.This is interpreted in terms ofphonologicalandsemantic distinctiveness. [ABSTRACT FROM AUTHOR]

A three-dimensional chemical transport model, PMCAMx-SR, was applied in the continental U.S. to investigate the contribution of prescribed burning and other biomass burning sources to the total organic aerosol (OA) concentrations. Simulations were performed during three seasonally-representative months (April, July and September 2008). Prescribed biomass burning organic aerosol (bbOA) emission rates were estimated to be approximately 300, 80 and 250 tn d−1 during April, July and September respectively. Prescribed burning was limited during July due to the prevailing weather conditions. Prescribed burning is responsible for 45% of the total bbOA emissions during the simulated spring period, 20% during the fall, and just 3% during the summer. The predicted maximum hourly prescribed bbOA concentration reached approximately 100 μg m−3 during April in South Carolina and during September in New Mexico, whereas it was less than 15 μg m−3 during July in Arkansas. The average contribution of prescribed burning to OA in the continental U.S. is quite low (less than 5%) and 60–70% is predicted to be secondary OA. Biomass burning secondary organic aerosol (bbSOA) levels far away from the prescribed fires are predicted to exceed 2 μg m−3. In states with intensive prescribed burning activities this source is predicted to contribute 20–40% of the OA on a monthly average basis. In these states (for example South Carolina during April), the predictions reveal that people can be exposed for 20 h per month on average to bbOA levels exceeding 5 μg m−3 and for 200 h to levels above 0.5 μg m−3. This should be contrasted to 220 h of exposure to bbOA above 5 μg m−3 and 650 h to bbOA above 0.5 μg m−3 for states and periods with intense wild fires (for example California during July). • Prescribed burning contributes 20–40% of organic aerosol in some US states. • The average contribution of prescribed burning to OA in the US is less than 5%. • On average 60–70% is predicted to be secondary OA. • Exposures to OA from prescribed burning are significant but lower than wildfires. [ABSTRACT FROM AUTHOR]

Recent updates to U.S. regulatory guidelines for modeling impacts of single sources to secondary pollutants, such as ozone (O 3) and fine particulate matter (PM 2.5), require the use of established photochemical models with a complete treatment of gas-phase and aerosol chemistry as the preferred method for a Tier 2 demonstration approach. Such models include photochemical grid models (PGMs), as well as Lagrangian puff models with the requisite treatment of processes governing the formation of secondary pollutants from their precursors. SCICHEM is an open source reactive puff model that includes treatments for gas, aerosol, and aqueous-phase chemistry that are comparable to those in PGMs. The dispersion component of SCICHEM is based on the state-of-the-science puff model, SCIPUFF (Second-order Closure Integrated Puff). The model is a valuable tool that requires fewer resources and setup cost to run than PGMs to calculate the impacts of a single source or a small number of sources on downwind ozone and PM 2.5. This paper describes a model inter-comparison study of secondary pollutant impacts due to emissions from a hypothetical coal-fired power plant stack. The models compared in this study include SCICHEM and the two most commonly used PGMs, CMAQ and CAMx. Stacks are located in 4 separate regions of the U.S. with distinct differences in chemical environments and geographical features. The key inputs (hypothetical stack parameters and emission rates, meteorology) to the three models are based on a common dataset for consistency. The source impacts calculated by the PGMs are based on zero-out simulations (i.e., with and without the source of interest) as well as the source apportionment tools available in CAMx, while SCICHEM directly predicts source impacts in a single simulation. Annual simulations are conducted to determine the frequency distribution of source impacts over the 4 regions. The comparison of model results shows both similarities and differences in the frequencies and magnitudes of peak impacts predicted by the three models. There is good agreement among all models in their predictions of 98th and 99th percentile impacts. • Recent regulatory guidelines require use of photochemical models for Tier 2 single source secondary ozone and PM 2.5 impacts. • Models should be based on sound science. • Candidate models include Photochemical Grid Models (PGMs) as well as photochemical Lagrangian models. • This study compares single source ozone and secondary PM 2.5 impacts predicted by PGMs and a photochemical Lagrangian model. [ABSTRACT FROM AUTHOR]

Background: In 2015, 2200 patients attended the Cardiac Catheterisation Laboratory in University Hospital Waterford. 3,142 procedures were completed. This gives an average of 60 cases per week. As a quality improvement initiative, the cath lab nursing staff undertook a patient experience survey to illuminate the positive and negative aspects of the care provided in our centre. The aim of this survey was to use these results to guide improvements in the quality of patient care. Method: Lean's six sigma approach of define, measure, analyse, improve and control was chosen as a suitable methodology. We sourced a validated patient satisfaction tool from another health system and adapted it for local context. The survey looked at the admissions process, the pre, intra and post operative experience of the patient. A Likert scale was used. The survey was completed over a four week period. Results: A total of 66 patients participated in the survey, giving us a 48% response rate. Overall the results were favourable and demonstrated a high level of patient satisfaction. This included aspects such as courtesy and respect shown by staff, cleanliness of the clinical areas and the clarity of information imparted by staff. Areas requiring attention as highlighted by the respondents included the ambient temperature of the clinical areas and aspects of the diet offered to patients post procedure. Twenty percent of patients reported fair to poor for the temperature questions and supplemented this with comments. In relation to dietary requirements, 6% reported between fair and poor. This was also reflected in the comments provided. Conclusion: The patient experience survey was a very useful exercise and based on our findings, two quality improvement plans, for room temperature and diet, have been implemented. A six month follow-up survey is planned. [ABSTRACT FROM AUTHOR]