Reflecting on progress since the 2005 NARSTO emissions inventory report

Emission inventories are the foundation for cost-effective air quality management activities. In 2005, a report by the public/private partnership North American Research Strategy for Tropospheric Ozone (NARSTO) evaluated the strengths and weaknesses of North American emissions inventories and made recommendations for improving their effectiveness. This paper reviews the recommendation areas and briefly discusses what has been addressed, what remains unchanged, and new questions that have arisen. The findings reveal that all emissions inventory improvement areas identified by the 2005 NARSTO publication have been explored and implemented to some degree. The U.S. National Emissions Inventory has become more detailed and has incorporated new research into previously under-characterized sources such as fine particles and biomass burning. Additionally, it is now easier to access the emissions inventory and the documentation of the inventory via the internet. However, many emissions-related research needs exist, on topics such as emission estimation methods, speciation, scalable emission factor development, incorporation of new emission measurement techniques, estimation of uncertainty, top-down verification, and analysis of uncharacterized sources. A common theme throughout this retrospective summary is the need for increased coordination among stakeholders. Researchers and inventory developers must work together to ensure that planned emissions research and new findings can be used to update the emissions inventory. To continue to address emissions inventory challenges, industry, the scientific community, and government agencies need to continue to leverage resources and collaborate as often as possible. As evidenced by the progress noted, continued investment in and coordination of emissions inventory activities will provide dividends to air quality management programs across the country, continent, and world.

Implications: In 2005, a report by the public/private partnership North American Research Strategy for Tropospheric Ozone (NARSTO) evaluated the strengths and weaknesses of North American air pollution emissions inventories. This paper reviews the eight recommendation areas and briefly discusses what has been addressed, what remains unchanged, and new questions that have arisen. Although progress has been made, many opportunities exist for the scientific agencies, industry, and government agencies to leverage resources and collaborate to continue improving emissions inventories.     

A Combined Ca(OH)2/NH3 Flue Gas Desulfurization Process for High Sulfur Coal: Results of a Pilot Plant Study

The removal of SO₂ with atomization of a slaked lime slurry and supplemental injection of gaseous NH₃ were tested in a conventional spray dryer/baghouse system for SO₂ concentrations of 2000 ppm and 3000 ppm and a 30° F approach to saturation. Results at 3000 ppm of SO₂ showed an average SO₂ removal efficiency of 90.3 percent at a combined stoichiometric ratio of 0.95-1.10 and an average overall sorbent utilization of 91.6 percent. The overall molal ratio of NH₃/SO₂ reaction was found to be 2:1 under the test conditions Particle size analyses, and EP toxicity tests were conducted on the products of the reactions.     

The Effects of Infiltration and Insulation on the Source Strengths and Indoor Air Pollution from Combustion Space Heating Appliances

Many energy conservation strategies for residences involve reducing house air exchange rates. Reducing the air exchange rate of a house can cause an increase in pollutant levels if there is an indoor pollution source and if the indoor pollutant source strength remains constant. However, if the indoor pollutant source strength can also be reduced, then it is possible to maintain or even improve indoor air quality. Increasing the insulation level of a house is a means of achieving energy conservation goals and, in addition, can reduce the need for space heating and thereby reduce the pollutant source strengths of combustion space heaters such as unvented kerosene space heaters, unvented gas space heaters, and wood stoves. In this paper, the indoor air quality trade-off between reduced infiltration and increased insulation in residences is investigated for combustion space heaters. Two similar residences were used for the experiment. One residence was used as a control and the other residence had infiltration and insulation levels modified. An unvented propane space heater was used as the source in this study. A model was developed to describe the dependence of both indoor air pollution levels and the appliance source strengths on house air exchange rates and house insulation levels. Model parameters were estimated by applying regression techniques to the data. Results show that indoor air pollution levels in houses with indoor combustion space heating pollution sources can be held constant (or lowered) by reducing the thermal conductance by an amount proportional to (or greater than) the reduction of the air exchange rate.     

Modeling Emissions from Elevated Cylindrical Bins

Abstract

This paper demonstrates how wind tunnel modeling data that accurately describe plume characteristics near an unconventional emission source can be used to improve the near-field downwind plume profiles predicted by conventional air pollution dispersion models. The study considers a vertical, cylindrical-shaped, elevated bin similar to large product storage bins that can be found at many industrial plant sites. Two dispersion models are considered: the U.S. Environmental Protection Agency's ISC2(ST) model and the Ontario Ministry of the Environment and Energy's GAS model. The wind tunnel study showed that plume behavior was contrary to what was predicted using conventional dispersion models such as ISC2(ST) and GAS and default values of input parameters. The wind tunnel data were used to develop a protocol for correcting the dispersion models inputs, resulting in a substantial improvement in the accuracy of the dispersion estimates.     

Comparison of Short-Term Variations (15-Minute Averages) in Outdoor and Indoor PM2.5 Concentrations

ABSTRACT

Measurements of 15-min average PM_2.5 concentrations were made with a real-time light-scattering instrument at both outdoor (central monitoring sites in three communities) and indoor (residential) locations over two seasons in the Minneapolis-St. Paul metropolitan area. These data are used to examine within-day variability of PM_2.5 concentrations indoors and outdoors, as well as matched indoor-to-outdoor (I/O) ratios. Concurrent gravimetric measurements of 24-hr average PM_2.5 concentrations were also obtained as a way to compare real-time measures with this more traditional metric. Results indicate that (1) within-day variability for both indoor and outdoor 15-min average PM_2.5 concentrations was substantial and comparable in magnitude to day-to-day variability for 24hr average concentrations; (2) some residences exhibited substantial variability in indoor aerosol characteristics from one day to the next; (3) peak values for indoor short-term (15-min) average PM_2.5 concentrations routinely exceeded 24-hr average outdoor values by factors of 3-4; and (4) relatively strong correlations existed between indoor and outdoor PM_2.5 concentrations for both 24-hr and 15-min averages.     

Forecasting Air Pollution Potential: A Synoptic Climatological Approach

ABSTRACT

This paper describes the development and application of an air pollution potential (APP) forecast model based on a synoptic climatological approach in a heavily industrialized area in Durban, South Africa. The aim of the forecasting procedure, based on a system of orange, red, and all-clear alerts, was to give industry advance warning of periods of poor atmospheric dispersion so that it could take action to reduce emissions. The key meteorological parameter in accurately identifying the commencement of an APP episode was found to be negative surface pressure tendency. Wind direction was the most useful parameter in estimating the end point of an APP episode. The model was very successful in identifying periods of elevated SO₂, but there is a need for further refinement in forecasting the end point of an episode.     

An Environmental Decision-Making Tool for Evaluating Ground-Level Ozone-Related Health Effects

Abstract

A computer model called the Ozone Risk Assessment Model (ORAM) was developed to evaluate the health effects caused by ground-level ozone (O₃) exposure. ORAM was coupled with the U.S. Environmental Protection Agency’s (EPA) Third-Generation Community Multiscale Air Quality model (Models-3/CMAQ), the state-of-the-art air quality model that predicts O₃ concentration and allows the examination of various scenarios in which emission rates of O₃ precursors (basically, oxides of nitrogen [NO_x] and volatile organic compounds) are varied. The principal analyses in ORAM are exposure model performance evaluation, health-effects calculations (expected number of respiratory hospital admissions), economic valuation, and sensitivity and uncertainty analysis through a Monte Carlo simulation. As a demonstration of the system, ORAM was applied to the eastern Tennessee region, and the entire O₃ season was simulated for a base case (typical emissions) and three different emission scenarios. The results indicated that a synergism occurs when reductions in NO_x emissions from mobile and point sources were applied simultaneously. A 12.9% reduction in asthma hospital admissions is expected when both mobile and point source NO_x emissions are reduced (50 and 70%, respectively) versus a 5.8% reduction caused by mobile source and a 3.5% reduction caused by point sources when these emission sources are reduced individually.     

Particulate Emissions from Construction Activities

Abstract

Although it has long been recognized that road and building construction activity constitutes an important source of particulate matter (PM) emissions throughout the United States, until recently only limited research has been directed to its characterization. This paper presents the results of PM₁₀ and PM_2.5 (particles ≤10 μm and ≤2.5 μm in aerodynamic diameter, respectively) emission factor development from the onsite testing of component operations at actual construction sites during the period 1998 –2001. Much of the testing effort was directed at earthmoving operations with scrapers, because earthmoving is the most important contributor of PM emissions across the construction industry. Other sources tested were truck loading and dumping of crushed rock and mud and dirt carryout from construction site access points onto adjacent public paved roads. Also tested were the effects of watering for control of scraper travel routes and the use of paved and graveled aprons at construction site access points for reducing mud and dirt carryout. The PM₁₀ emissions from earthmoving were found to be up to an order of magnitude greater than predicted by AP-42 emission factors drawn from other industries. As expected, the observed PM_2.5:PM₁₀ emission factor ratios reflected the relative importance of the vehicle exhaust and the resuspended dust components of each type of construction activity. An unexpected finding was that PM_2.5 emissions from mud and dirt carryout were much less than anticipated. Finally, the control efficiency of watering of scraper travel routes was found to closely follow a bilinear moisture model.     

Parts-per-trillion LC-MS(Q) analysis of herbicides and transformation products in surface water

The goal of this study was to develop a robust method of analyzing surface water samples for S-triazine herbicides, chloroacetanilide herbicides, and their transformation products (TPs) using solid-phase extraction (SPE) followed by liquid chromatograph-mass spectrometry (LC-MS) with electrospray ionization (ESI) by in-source collision-induced dissociation (ISCID) capability of an orthogonal electrospray ionization probe on a single quadrupole LC-MS system. The method developed here met the goals of the study and yielded estimated method detection limits (EMDLs) averaging 0.3 ± 0.1 ng L(-1) for S-triazines and their TPs and 0.7 ± 0.4 ng L(-1) for chloroacetanilides and TPs. Spiked filtered river water yielded SPE recoveries ranging from 94.2 % ± 4.8 % for S-triazines and TPs after eliminating three compounds with less that 65 % recovery from analysis and 95.9 % ± 19 % for chloroacetanilides and their TPs. The method was field-tested with filtered water samples collected from four sites over a four-month period. Detectible values of S-triazines and TPs ranged from 0.3 to 1540 ng L(-1) with a mean of 79.3 and a median of 19.4 ng L(-1). Detectible values for chloroacetanilides and TPs ranged from 0.31 to 3780 ng L(-1) with a mean of 252 and a median of 25.6 ng L(-1). An additional goal was to determine if the method was useful for microbial degradation studies using native bacterial communities. The bacteria transformed atrazine (2-chloro-4-ethylamino-6-isopropylamino-S-triazine) solely into 2-hydroxy atrazine (2-hydroxy-4-ethylamino-6-isopropylamino-S-triazine) with concentrations of 78.4, 63.3 and 32.5 ng L(-1) after 12 days of incubation compared with 6.3 and 7.1 ng L(-1) for control dark and control sunlight respectively.     

Modeling transit bus fuel consumption on the basis of cycle properties

A method exists to predict heavy-duty vehicle fuel economy and emissions over an "unseen" cycle or during unseen on-road activity on the basis of fuel consumption and emissions data from measured chassis dynamometer test cycles and properties (statistical parameters) of those cycles. No regression is required for the method, which relies solely on the linear association of vehicle performance with cycle properties. This method has been advanced and examined using previously published heavy-duty truck data gathered using the West Virginia University heavy-duty chassis dynamometer with the trucks exercised over limited test cycles. In this study, data were available from a Washington Metropolitan Area Transit Authority emission testing program conducted in 2006. Chassis dynamometer data from two conventional diesel buses, two compressed natural gas buses, and one hybrid diesel bus were evaluated using an expanded driving cycle set of 16 or 17 different driving cycles. Cycle properties and vehicle fuel consumption measurements from three baseline cycles were selected to generate a linear model and then to predict unseen fuel consumption over the remaining 13 or 14 cycles. Average velocity, average positive acceleration, and number of stops per distance were found to be the desired cycle properties for use in the model. The methodology allowed for the prediction of fuel consumption with an average error of 8.5% from vehicles operating on a diverse set of chassis dynamometer cycles on the basis of relatively few experimental measurements. It was found that the data used for prediction should be acquired from a set that must include an idle cycle along with a relatively slow transient cycle and a relatively high speed cycle. The method was also applied to oxides of nitrogen prediction and was found to have less predictive capability than for fuel consumption with an average error of 20.4%.