Pilot-Scale Demonstration of an Innovative Treatment for Vapor Emissions

ABSTRACT

Researchers from the National Renewable Energy Laboratory recently conducted a pilot-scale study at McClellan Air Force Base (AFB) in Sacramento, CA. The objective of the test was to determine the effectiveness of an ambient-temperature, solar-powered photocatalytic oxidation treatment unit for destroying emissions of chlorinated organic compounds from an air stripper. This paper reports test results and discusses applications and limitations of the technology.

A 10-standard-cubic-foot-per-minute (SCFM) (28.3 L/min) slip stream of air from an air stripper at Operative Unit 29-31 at McClellan AFB was passed through a reactor that contained a lightweight, perforated, inert support coated with photoactive titanium dioxide. The reactor faced south and was tilted at a 45° angle from vertical so that the light-activated catalyst received most of the available sunlight. An online portable gas chro-matograph with two identical columns simultaneously analyzed the volatile organic compounds contained in the reactor inlet and outlet air streams. Summa canister grab samples of the inlet and outlet were also collected and sent to a certified laboratory for U.S. Environmental

Protection Agency Method TO-14 analysis and verification of our field analyses. Three weeks of testing demonstrated that the treatment system's destruction and removal efficiencies (DREs) are greater than 95% at 10 SCFM with UV intensities at or greater than 1.5 milliwatts/square centimeter (mW/cm²). DREs greater than 95% at 20 SCFM were obtained under conditions where UV irradiation measured at or greater than 2 mW/cm². In Sacramento, this provided 6 hours of operation per clear or nearly clear day in April. A solar tracking system could extend operating time. The air stream also contained trace amounts of benzene. We observed no loss of system performance during testing.     

An Intelligent Emissions Controller for Fuel Lean Gas Reburn in Coal-Fired Power Plants

ABSTRACT

The application of artificial intelligence techniques for performance optimization of the fuel lean gas reburn (FLGR) system is investigated. A multilayer, feedforward artificial neural network is applied to model static nonlinear relationships between the distribution of injected natural gas into the upper region of the furnace of a coal-fired boiler and the corresponding oxides of nitrogen (NO_x) emissions exiting the furnace. Based on this model, optimal distributions of injected gas are determined such that the largest NO_x reduction is achieved for each value of total injected gas. This optimization is accomplished through the development of a new optimization method based on neural networks. This new optimal control algorithm, which can be used as an alternative generic tool for solving multidimensional nonlinear constrained optimization problems, is described and its results are successfully validated against an off-the-shelf tool for solving mathematical programming problems. Encouraging results obtained using plant data from one of Commonwealth Edison's coal-fired electric power plants demonstrate the feasibility of the overall approach.

Preliminary results show that the use of this intelligent controller will also enable the determination of the most cost-effective operating conditions of the FLGR system by considering, along with the optimal distribution of the injected gas, the cost differential between natural gas and coal and the open-market price of NO_x emission credits. Further study, however, is necessary, including the construction of a more comprehensive database, needed to develop high-fidelity process models and to add carbon monoxide (CO) emissions to the model of the gas reburn system.     

Statistical Considerations in Determining the Health Significance of Constituents of Airborne Particulate Matter

ABSTRACT

Because of the U.S. Environmental Protection Agency’s (EPA) new ambient air quality standard for fine particles, the need is likely to continue for more detailed scientific investigation of various types of particles and their effects on human health. Epidemiology studies have become the method of choice for investigating health responses to such particles and to other air pollutants in community settings. Health effects have been associated with virtually all of the gaseous criteria pollutants and with the major constituents of airborne particulate matter (PM), including all size fractions less than about 20 gm, inorganic ions, carbonaceous particles, metals, crustal material, and biological aerosols. In many of the more recent studies, multiple pollutants or agents (including weather variables) have been significantly associated with health responses, and various methods have been used to suggest which ones might be the most important. In an ideal situation, classical least-squares regression methods are capable of performing this task. However, in the real world, where most of the pollutants are correlated with one another and have varying degrees of measurement precision and accuracy, such regression results can be misleading. This paper presents some guidelines for dealing with such collinearity and model comparison problems in both single- and multiple-pollutant regressions. These techniques rely on mean effect (attributable risk) rather than statistical significance per se as the preferred indicator of importance for the pollution variables.     

Estimates of Particle Hygroscopicity during the Southeastern Aerosol and Visibility Study

ABSTRACT

Aerosol water content was determined from relative humidity controlled optical particle counter (ASASP-X) size distribution measurements made during the Southeastern Aerosol and Visibility Study (SEAVS) in the Great Smoky Mountains National Park during summer 1995. Since the scattering response function of the ASASP-X is sensitive to particle refractive index, a technique for calibrating the ASASP-X for any real refractive index was developed. A new iterative process was employed to calculate water mass concentration and wet refractive index as functions of relative humidity. Experimental water mass concentrations were compared to theoretically predicted values assuming only ammonium sulfate compounds were hygroscopic. These comparisons agreed within experimental uncertainty. Estimates of particle hygroscopicity using a rural aerosol model of refractive index as a function of relative humidity demonstrated no significant differences from those made with daily varying refractive index estimates. Although aerosol size parameters were affected by the assumed chemical composition, forming ratios of these parameters nearly canceled these effects.     

Electricity from Fossil Fuels without CO2 Emissions: Assessing the Costs of Carbon Dioxide Capture and Sequestration in U.S. Electricity Markets

ABSTRACT

The decoupling of fossil-fueled electricity production from atmospheric CO₂ emissions via CO₂ capture and sequestration (CCS) is increasingly regarded as an important means of mitigating climate change at a reasonable cost. Engineering analyses of CO₂ mitigation typically compare the cost of electricity for a base generation technology to that for a similar plant with CO₂ capture and then compute the carbon emissions mitigated per unit of cost. It can be hard to interpret mitigation cost estimates from this plant-level approach when a consistent base technology cannot be identified. In addition, neither engineering analyses nor general equilibrium models can capture the economics of plant dispatch. A realistic assessment of the costs of carbon sequestration as an emissions abatement strategy in the electric sector therefore requires a systems-level analysis. We discuss various frameworks for computing mitigation costs and introduce a simplified model of electric sector planning. Results from a “bottom-up” engineering-economic analysis for a representative U.S. North American Electric Reliability Council (NERC) region illustrate how the penetration of CCS technologies and the dispatch of generating units vary with the price of carbon emissions and thereby determine the relationship between mitigation cost and emissions reduction.     

A Cost-Effective Weighing Chamber for Particulate Matter Filters

ABSTRACT

Particulate matter (PM) is a ubiquitous air pollutant that has been receiving increasing attention in recent years due in part to the association between PM and a number of adverse health outcomes, including mortality and increases in emergency room visits and respiratory symptoms, as well as exacerbation of asthma and decrements in lung function.^1-5 As a result, the ability to accurately sample ambient PM has become important, both to researchers and to regulatory agencies. The federal reference method for the determination of fine PM as PM_2.5 in the atmosphere recommends that particle-sampling filters be conditioned and weighed in an environment with constant temperature and relative humidity (RH).⁶ It is also recommended that vibration, electrostatic charges, and contamination of the filters from laboratory air be minimized to reduce variability in filter weight measurements. These controls have typically been maintained in small, environmentally controlled “cleanrooms.” As an alternative to constructing an elaborate cleanroom, we have designed, and presented in this paper, an inexpensive weighing chamber to maintain the necessary level of humidity control.     

Air Quality in Selected Megacities

Abstract

About half of the world's population now lives in urban areas because of the opportunity for a better quality of life. Many of these urban centers are expanding rapidly, leading to the growth of megacities, which are often defined as metropolitan areas with populations exceeding 10 million inhabitants. These concentrations of people and activity are exerting increasing stress on the natural environment, with impacts at urban, regional and global levels. In recent decades, air pollution has become one of the most important problems of megacities. Initially, the main air pollutants of concern were sulfur compounds, which were generated mostly by burning coal. Today, photochemical smog—induced primarily from traffic, but also from industrial activities, power generation, and solvents—has become the main source of concern for air quality, while sulfur is still a major problem in many cities of the developing world. Air pollution has serious impacts on public health, causes urban and regional haze, and has the potential to contribute significantly to global climate change. Yet, with appropriate planning megacities can efficiently address their air quality problems through measures such as application of new emission control technologies and development of mass transit systems.

This review is focused on nine urban centers, chosen as case studies to assess air quality from distinct perspectives: from cities in the industrialized nations to cities in the developing world. This review considers not only megacities, but also urban centers with somewhat smaller populations, for while each city—its problems, resources, and outlook—is unique, the need for a holistic approach to complex environmental problems is the same. There is no single strategy to reduce air pollution in megacities; a mix of policy measures will be needed to improve air quality. Experience shows that strong political will coupled with public dialogue is essential to effectively implement the regulations required to address air quality.     

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.     

Real-Time Measurements of Jet Aircraft Engine Exhaust

Abstract

Particulate-phase exhaust properties from two different types of ground-based jet aircraft engines—high-thrust and turboshaft—were studied with real-time instruments on a portable pallet and additional time-integrated sampling devices. The real-time instruments successfully characterized rapidly changing particulate mass, light absorption, and polycyclic aromatic hydrocarbon (PAH) content. The integrated measurements included particulate-size distributions, PAH, and carbon concentrations for an entire test run (i.e., “run-integrated” measurements). In all cases, the particle-size distributions showed single modes peaking at 20–40nm diameter. Measurements of exhaust from high-thrust F404 engines showed relatively low-light absorption compared with exhaust from a turboshaft engine. Particulate-phase PAH measurements generally varied in phase with both net particulate mass and with light-absorbing particulate concentrations. Unexplained response behavior sometimes occurred with the real-time PAH analyzer, although on average the real-time and integrated PAH methods agreed within the same order of magnitude found in earlier investigations.