Emission Strength Validation Using Four-Dimensional Data Assimilation: Application to Primary Aerosol and Precursors to Ozone and Secondary Aerosol

ABSTRACT

Three-dimensional air quality models (AQMs) represent the most powerful tool to follow the dynamics of air pollutants at urban and regional scales. Current AQMs can account for the complex interactions between gas-phase chemistry, aerosol growth, cloud and scavenging processes, and transport. However, errors in model applications still exist due in part to limitations in the models themselves and in part to uncertainties in model inputs. Four-dimensional data assimilation (FDDA) can be used as a top-down tool to validate several of the model inputs, including emissions inventories, based on ambient measurements. Previously, this FDDA technique was used to estimate adjustments in the strength and composition of emissions of gas-phase primary species and O₃ precursors.

In this paper, we present an extension to the FDDA technique to incorporate the analysis of particulate matter (PM) and its precursors. The FDDA approach consists of an iterative optimization procedure in which an AQM is coupled to an inverse model, and adjusting the emissions minimizes the difference between ambient measurements     

Analysis of a Summertime PM2.5 and Haze Episode in the Mid-Atlantic Region

Abstract

Observations of the mass and chemical composition of particles less than 2.5 μm in aerodynamic diameter (PM_2.5), light extinction, and meteorology in the urban Baltimore-Washington corridor during July 1999 and July 2000 are presented and analyzed to study summertime haze formation in the mid-Atlantic region. The mass fraction of ammoniated sulfate (SO₄ ^2-) and carbonaceous material in PM_2.5 were each ～50% for cleaner air (PM_2.5 < 10 μg/m³) but changed to ～60% and ～20%, respectively, for more polluted air (PM_2.5 > 30 μg/m³). This signifies the role of SO₄ ^2- in haze formation. Comparisons of data from this study with the Interagency Monitoring of Protected Visual Environments network suggest that SO₄ ^2? is more regional than carbonaceous material and originates in part from upwind source regions. The light extinction coefficient is well correlated to PM_2.5 mass plus water associated with inorganic salt, leading to a mass extinction efficiency of 7.6 ± 1.7 m²/g for hydrated aerosol. The most serious haze episode occurring between July 15 and 19, 1999, was characterized by westerly transport and recirculation slowing removal of pollutants. At the peak of this episode, 1-hr PM_2.5 concentration reached ～45 μg/m³, visual range dropped to ～5 km, and aerosol water likely contributed to ～40% of the light extinction coefficient.     

Spatial Differences in Outdoor PM10 Mass and Aerosol Composition in Mexico City

Abstract

Twenty-five MiniVol samplers were operated throughout the Mexico City metropolitan region from February 22 through March 22, 1997, to evaluate the variability of PM₁₀ concentrations and composition. The highest PM₁₀ concentrations were found in neighborhoods with unpaved or dirty roads, and elements related to crustal material were the main cause of differences from nearby (<200 m) monitors that were not adjacent to the roadbed. SO₄ ^2?concentrations were homogeneous across the city. SO₄ ^2?measured at the city boundaries was about two-thirds of the concentrations measured within the urbanized area, indicating that most SO₄ ^2? is of regional origin. Elemental carbon (EC) and organic carbon (OC) concentrations were highly variable, with higher concentrations in areas that had high diesel traffic and older vehicles. Spatial correlations among PM₁₀ concentrations were high, even though absolute concentrations were variable, indicating a common effect of meteorology on the concentration or dispersion of local emissions.     

Simultaneous Sampling of Gas- and Aerosol-Phase TDI with a Triple Filter System

Abstract

A new triple filter system sampler/model is proposed for the precise and accurate simultaneous sampling and determination of gas- and aerosol-phase 2,4-toluene diisocyanate (TDI). The system consists of two front Teflon filters for sampling aerosol-phase TDI and a final coated glass fiber filter to collect gas-phase TDI. The aerosol-phase TDI is collected on the first Teflon filter, while the second Teflon filter is used to estimate gaseous TDI adsorbed by the first. According to the gas adsorption test of two Teflon filters in series, the TDI gas adsorption fraction of the two filters is almost the same. Results of the evaporation test using pure TDI aerosols collected on the Teflon filter show that significant evaporation of the compound does not occur during sampling. These two findings allow the use of a model to estimate accurate gasand aerosol-phase TDI concentrations. The comparison test with an annular denuder shows that the triple filter system can minimize the TDI sampling bias between the dual filter and the annular denuder systems.     

Modeling and Spatially Distributing Forest Net Primary Production at the Regional Scale

Abstract

Forest, agricultural, rangeland, wetland, and urban landscapes have different rates of carbon sequestration and total carbon sequestration potential under alternative management options. Changes in the proportion and spatial distribution of land use could enhance or degrade that area’s ability to sequester carbon in terrestrial ecosystems. As the ecosystems within a landscape change due to natural or anthropogenic processes, they may go from being a carbon sink to a carbon source or vice versa. Satellite image analysis has been tested for timely and accurate measurement of spatially explicit land use change and is well suited for use in inventory and monitoring of terrestrial carbon. The coupling of Landsat Thematic Mapper (TM) data with a physiologically based forest productivity model (PnET-II) and historic climatic data provides an opportunity to enhance field plot-based forest inventory and monitoring methodologies. We use periodic forest inventory data from the U.S. Department of Agriculture (USDA) Forest Service’s Forest Inventory and Analysis (FIA) Program to obtain estimates of forest area and type and to generate estimates of carbon storage for evergreen, deciduous, and mixed-forest classes. The area information is used in an accuracy assessment of remotely sensed forest cover at the regional scale. The map display of modeled net primary production (NPP) shows a range of forest carbon storage potentials and their spatial relationship to other landscape features across the southern United States. This methodology addresses the potential for measuring and projecting forest carbon sequestration in the terrestrial biosphere of the southern United States.     

Systematic Development of an Artificial Neural Network Model for Real-Time Prediction of Ground-Level Ozone in Edmonton,Alberta, Canada

Abstract

Ground-level ozone is a secondary pollutant that has recently gained notoriety for its detrimental effects on human and vegetation health. In this paper, a systematic approach is applied to develop artificial neural network (ANN) models for ground-level ozone (O₃) prediction in Edmonton, Alberta, Canada, using ambient monitoring data for input. The intent of these models is to provide regulatory agencies with a tool for addressing data gaps in ambient monitoring information and predicting O₃ events. The models are used to determine the meteorological conditions and precursors that most affect O₃ concentrations. O₃ time-series effects and the efficacy of the systematic approach are also assessed. The developed models showed good predictive success, with coefficient of multiple determination values ranging from 0.75 to 0.94 for forecasts up to 2 hr in advance. The inputs most important for O₃ prediction were temperature and concentrations of nitric oxide, total hydrocarbons, sulfur dioxide, and nitrogen dioxide.     

The Steubenville Comprehensive Air Monitoring Program (SCAMP): Overview and Statistical Considerations

Abstract

Average concentrations of particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM_2.5) in Steubenville, OH, have decreased by more than 10 μg/m³ since the landmark Harvard Six Cities Study¹ associated the city’s elevated PM_2.5 concentrations with adverse health effects in the 1980s. Given the promulgation of a new National Ambient Air Quality Standard (NAAQS) for PM_2.5 in 1997, a current assessment of PM_2.5 in the Steubenville region is warranted. The Steubenville Comprehensive Air Monitoring Program (SCAMP) was conducted from 2000 through 2002 to provide such an assessment. The program included both an outdoor ambient air monitoring component and an indoor and personal air sampling component. This paper, which is the first in a series of four that will present results from the outdoor portion of SCAMP, provides an overview of the outdoor ambient air monitoring program and addresses statistical issues, most notably autocorrelation, that have been overlooked by many PM_2.5 data analyses. The average PM_2.5 concentration measured in Steubenville during SCAMP (18.4 μg/m³) was 3.4g/m³ above the annual PM_2.5 NAAQS. On average, sulfate and organic material accounted for ～31% and 25%, respectively, of the total PM_2.5 mass. Local sources contributed an estimated 4.6 μg/m³ to Steubenville’s mean PM_2.5 concentration. PM_2.5 and each of its major ionic components were significantly correlated in space across all pairs of monitoring sites in the region, suggesting the influence of meteorology and long-range transport on regional PM_2.5 concentrations. Statistically significant autocorrelation was observed among time series of PM_2.5 and component data collected at daily and 1-in-4-day frequencies during SCAMP. Results of spatial analyses that accounted for autocorrelation were generally consistent with findings from previous studies that did not consider autocorrelation; however, these analyses also indicated that failure to account for autocorrelation can lead to incorrect conclusions about statistical significance.     

Integrated Assessment Modeling of Atmospheric Pollutants in the Southern Appalachian Mountains. Part I: Hourly and Seasonal Ozone

Abstract

Recently, a comprehensive air quality modeling system was developed as part of the Southern Appalachians Mountains Initiative (SAMI) with the ability to simulate meteorology, emissions, ozone, size- and composition-resolved particulate matter, and pollutant deposition fluxes. As part of SAMI, the RAMS/EMS-95/URM-1ATM modeling system was used to evaluate potential emission control strategies to reduce atmospheric pollutant levels at Class I areas located in the Southern Appalachians Mountains. This article discusses the details of the ozone model performance and the methodology that was used to scale discrete episodic pollutant levels to seasonal and annual averages. The daily mean normalized bias and error for 1-hr and 8-hr ozone were within U.S. Environment Protection Agency guidance criteria for urban-scale modeling. The model typically showed a systematic overestimation for low ozone levels and an underestimation for high levels. Because SAMI was primarily interested in simulating the growing season ozone levels in Class I areas, daily and seasonal cumulative ozone exposure, as characterized by the W126 index, were also evaluated. The daily ozone W126 performance was not as good as the hourly ozone performance; however, the seasonal ozone W126 scaled up from daily values was within 17% of the observations at two typical Class I areas of the SAMI region. The overall ozone performance of the model was deemed acceptable for the purposes of SAMI’s assessment.     

Multiple comparisons of organic,microbial, and fine particulate pollutants in typical indoor environments: Diurnal and seasonal variations

This study was performed to investigate the possible sources as well as seasonal and diurnal variations of indoor air pollutants in widely used four different environments (house, office, kindergarten, and primary school) in which people spend most of their time. Bioaerosol levels and species, volatile organic compound (VOC) levels, and PM_2.5 (particulate matter with an aerodynamic diameter ≤2.5 μm) levels were determined in different parts of these environments in parallel with outdoor sampling. Air pollution samplings were carried out in each microenvironment during five subsequent days in both winter and summer in Ankara, Turkey. The results indicated that bioaerosol, VOC, and PM_2.5 levels were higher in the winter than in the summer. Moreover, PM_2.5 and bioaerosol levels showed remarkable daily and diurnal variations, whereas a good correlation was found between the VOC levels measured in the morning and in the afternoon. Bacteria levels were, in general, higher than fungi levels. Among the VOCs, toluene was the most predominant, whereas elevated n-hexane levels were also observed in the kindergarten and the primary school, probably due to the frequent wet cleaning during school days. According to factor analysis, several factors were found to be significantly influencing the indoor air quality (IAQ), and amongst them, VOC-based products used indoors ranked first. The overall results indicate that grab sampling in naturally ventilated places may overestimate or underestimate the IAQ due to the inhomogeneous composition of indoor air caused by irregular exchanges with the outdoor air according to the season and/or occupants' habits.

Implications Seasonal and diurnal variations of VOCs, PM_2.5, bioaerosols in house, office, and schools were observed, in which PM_2.5 and bioaeorosols showed marked both intra- and interday variability, but VOCs did not. VOC-containing products were the most common source of air pollutants affecting the indoor air quality. External factors affecting the indoor air quality were season and indirectly ventilation. A grab sample cannot be representative in evaluating the air quality of a naturally ventilated environment precisely.     

Multispecies remote sensing measurements of vehicle emissions on Sherman Way in Van Nuys,California

As part of the 2010 Van Nuys tunnel study, researchers from the University of Denver measured on-road fuel-specific light-duty vehicle emissions from nearly 13,000 vehicles on Sherman Way (0.4 miles west of the tunnel) in Van Nuys, California, with its multispecies Fuel Efficiency Automobile Test (FEAT) remote sensor a week ahead of the tunnel measurements. The remote sensing mean gram per kilogram carbon monoxide (CO), hydrocarbon (HC), and oxide of nitrogen (NO_x) measurements are 8.9% lower, 41% higher, and 24% higher than the tunnel measurements, respectively. The remote sensing CO/NO_x and HC/NO_x mass ratios are 28% lower and 20% higher than the comparable tunnel ratios. Comparisons with the historical tunnel measurements show large reductions in CO, HC, and NO_x over the past 23 yr, but little change in the HC/NO_x mass ratio since 1995. The fleet CO and HC emissions are increasingly dominated by a few gross emitters, with more than a third of the total emissions being contributed by less than 1% of the fleet. An example of this is a 1995 vehicle measured three times with an average HC emission of 419 g/kg fuel (two-stroke snowmobiles average 475 g/kg fuel), responsible for 4% of the total HC emissions. The 2008 economic downturn dramatically reduced the number of new vehicles entering the fleet, leading to an age increase (>1 model year) of the Sherman Way fleet that has increased the fleet's ammonia (NH₃) emissions. The mean NH₃ levels appear little changed from previous measurements collected in the Van Nuys tunnel in 1993. Comparisons between weekday and weekend data show few fleet differences, although the fraction of light-duty diesel vehicles decreased from the weekday (1.7%) to Saturday (1.2%) and Sunday (0.6%).

Implications: On-road remote sensing emission measurements of light-duty vehicles on Sherman Way in Van Nuys, California, show large historical emission reductions for CO and HC emissions despite an older fleet arising from the 2008 economic downturn. Fleet CO and HC emissions are increasingly dominated by a few gross emitters, with a single 1995 vehicle measured being responsible for 4% of the entire fleet's HC emissions. Finding and repairing and/or scrapping as little as 2% of the fleet would reduce on-road tailpipe emissions by as much as 50%. Ammonia emissions have locally increased with the increasing fleet age.