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Methods for sulfate air quality management

Cass, Glen R. and McMurry, Pamela S. and Houseworth, James E. (1980) Methods for sulfate air quality management. Environmental Quality Laboratory Report, 16 v.1-3. California Institute of Technology , Pasadena, CA. (Unpublished)

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Executive Summary Abstract: A study of methods for sulfate air quality control strategy design has been conducted. Analytical tools developed were tested within a case study of the nature and causes of the high sulfate concentrations observed in the Los Angeles area. A principal objective was to investigate the least costly means for sulfate air quality improvement in that locale. A long-run average emissions to air quality model was derived which computes pollutant concentrations from Lagrangian marked particle statistics based on the time sequence of measured wind speed, wind direction, and inversion base motion. Physical assumptions drawn from analysis of existing air quality and meteorological data were used to adapt this model to a specific application -- sulfate air quality prediction in Los Angeles. An energy and sulfur balance on the fate of energy resources containing sulfur was developed to test the consistency of a sulfur oxides emissions inventory for that air basin. Then material balance arguments were used to trace sulfur flows within that regional energy economy through the air quality model which also conserves sulfur mass. Sulfate air quality model predictions were compared to historical observations over the years 1972 through 1974. 'The sulfate air quality impact of individual emission source classes was estimated at a large number of air monitoring sites. A hybrid theoretical-empirical model was constructed which explains the relationship between sulfate air quality and prevailing visibility at Los Angeles. An estimate was made of the visibility improvement which would have accured if Los Angeles sulfate concentrations were reduced by 50 percent on each past day of record. Then two emissions control strategy example calculations were performed to illustrate the means by which the air quality model results could be used to evaluate the cost of attaining such an air quality improvement. Volume 2 Abstract: Particulate sulfate air pollutants contribute to visibility deterioration and are of current public health concern. This study develops the technical understanding needed for sulfate air quality control strategy design. Methods which link sulfate air quality and air quality impacts on visibility to the cost of controlling sulfur oxides air pollutant emissions are presented. These techniques are tested by application to the Los Angeles Basin over the years 1972 through 1974. An air quality simulation model is developed which directly calculates long-term average sulfate concentrations under unsteady meteorological conditions. Pollutant concentrations are estimated from Lagrangian marked-particle statistics based on the time sequence of historical measured wind speed, wind direction and inversion base height motion. First order chemical reactions and ground level pollutant dry deposition are incorporated within a computational scheme which conserves pollutant mass. Techniques are demonstrated for performing both mass balance and energy balance calculations on flows of energy resources containing sulfur throughout the economy of an air quality control region. The energy and sulfur balance approach is used to check the consistency of a spatially and temporally resolved air quality modeling emission inventory for the South Coast Air Basin. Next the air quality model is validated against sulfur oxides emissions and sulfate air quality patterns observed in the Los Angeles Basin over each month of the years 1972 through 1974. A seasonal variation in the rate of SO2 oxidation to form sulfates is inferred. Overall average SO2 oxidation rates of about 6% per hour prevail during late spring, summer and early fall, while mean SO2 oxidation rates of between 0.5% per hour and 3% per hour prevail from October through February of our test years. From the model results, it is concluded that three to five major SOx source classes plus background sulfates must be considered simultaneously at most monitoring sites in order to come close to explaining observed sulfate levels. The implication is that a mixed strategy aimed simultaneously at a number of specified source types will be needed if substantial sulfate air quality improvements are to be achieved within this particular airshed. Techniques are developed for analysis of the long-run impact of pollutant concentrations on visibility. Existing statistical models for light scattering by aerosols which use particle chemical composition as a key to particle size and solubility are modified so that the relative humidity dependence of light-scattering by hygroscopic aerosols could be represented in a more physically realistic manner. Coefficients are fitted to the model based on ten years of air pollution control agency routine air monitoring data taken at downtown Los Angeles. Sulfates are found to be the most effective light scatterers in the Los Angeles atmosphere. It is estimated that the visibility impact of reducing sulfates to a half or to a quarter of their measured historic values on each past day of record would be manifested most clearly in a reduction in the number of days per year of less than three-mile visibility. The number of days of average visibility less than ten miles would be little affected. Two retrospective examples are worked to show how the results of the air quality simulation models may be used to define a variety of sulfate air quality control strategy options. It is suggested that a package of technological emissions control measures and institutional changes (including natural gas price deregulation) may provide greater improvements in both sulfate air quality and visibility at less cost than can be obtained from a purely technological solution to the Los Angeles sulfate problem.

Item Type:Report or Paper (Technical Report)
Additional Information:© by GLEN ROWAN CASS - 1980. Final Report to the STATE OF CALIFORNIA AIR RESOURCES BOARD: completion of research under ARB Contract No. A6-061-87. Acknowledgement - this work was supported by the California Air Resources Board (Contract No. A6-061-87), by a grant from the Ford Foundation (No. 740-0469) and by gifts to the Environmental Quality Laboratory. Disclaimer: The statements and conclusions in this report are those of the Contractor and not necessarily those of the State Air Resources Board. The mention of commercial products, their source, or their use in connection with material reported herein is not to be construed as either an actual or implied endorsement of such products. In early 1973, discussions with Professor Lester Lees led us to conclude that a "clean fuel" shortage would develop in the Los Angeles area in the late 1970's. Increased sulfur oxides emissions from increased fuel oil combustion were expected to eventually provoke a change in sulfur oxides emission control policy in Southern California. From Professor Sheldon Friedlander's instruction in the dynamics of aerosol formation, it was concluded that the sulfate air quality impact of these increasing sulfur oxides emissions would provide the most pressing questions for scientific research and for emission control strategy engineering. Professor Norman H. Brooks provided advice and encouragement throughout this project, and was indispensable in arranging for the substantial financial resources needed to complete this research. Professor Roger Noll's insight into the economics of regularion helped to frame questions for emission control strategy analysis. Professor Joel Franklin's instruction in stochastic processes led me to attempt the approach to air quality modeling employed in Chapter 3 of this study, while discussion with Professor Fredrick Shair helped to sharpen the physical assumptions built into that modeling effort. These faculty members have served as the advisory committee for this project. I am especially grateful to my principal advisor, Lester Lees, for giving me the liberty to pursue this research task by the methods which I felt would be necessary in order to cope with a complex air quality problem over a period of many years within the context of one of the world's most extensively industrialized urban areas. Without the advice on computing provided by Dr. Robert C. Y. Koh, completion of this research project within a reasonable length of time would have been impossible. Nearly all of the computations performed in this study were expedited by use of Bob Koh's universal data handling system called MAGIC. The computer-generated graphs in this thesis are examples of the excellent results which were quickly attainable by use of MAGIC. Many members of the staff of Caltech's Environmental Quality Laboratory contributed to this project's success. The energy and sulfur balance study of Appendix A3 was co-authored by Pamela S. McMurry, while the crude oil characterization of Appendix A1 was co-authored by James Houseworth. David Saxokin edited the graphics. Anna Pechanec persisted through three consecutive attempts to reproduce previously published traffic count data for Los Angeles until we got the emissions inventory grid aligned properly. Gregory J. McRae read and commented on drafts of this work, and (believe it or not) succeeded in shortening the final version by several hundred pages. Charles Hales, Betsy Krieg, Tom Lawler and Lewis Hashimoto helped me to acquire the raw data for this study, almost all of which had to be transcribed by hand onto computer load sheets, followed by keypunching. They also helped with literature searches and preliminary data analysis tasks. Margo Huffman, Pat Hofmann, Diane Davis, Jeanie Cass and Dana Leimbach typed this manuscript. Pat Rankin organized the flow of work during the typing phase. Jeanie Cass prepared the index to contents, figures and tables. Their patience with many revisions is gratefully acknowledged. Work in this study has benefited from discussions with technical staff of the Environmental Quality Laboratory, Dr. John Seinfeld's research group in Chemical Engineering, and Dr. Sheldon Friedlander's group in Environmental Health Engineering. In particular, thanks are due to Dr. Robert G. Lamb, who took the time to comment on the air quality model derived in Chapter 3. While not all of the improvements that he suggested could be incorporated within our computing budget, the model validation effort of Chapter 5 benefited greatly from a few last-minute changes, particularly from his challenge that horizontal diffusion could not be neglected. Conversations with Drs. Paul T. Roberts, Warren H. White, Susanne Hering, Cliff Davidson, Peter H. McMurry, William Goodin and John Trijonis have been useful in hammering out approaches to specific problems as they arose in the course of this work. The South Coast Air Quality Management District (and its predecessor agencies) went to considerable effort to cooperate in providing data for this study. Special thanks are due to Eric Lemke, Janet Dickinson, John Nevitt, Arthur Davidson, Margaret Brunelle, Margil Wadley, Wayne Zwiacher, Ken Overturf, Julian Foon, Paul Chu, Sanford Weiss, Robert Murray, Herbert Whitehead, Martin Kaye, and Steve Menkus for answering an endless number of questions or for making staff available to provide answers when information was needed that went beyond that normally required to complete the District's mission. Joseph Stuart and Robert Lunche directed the District during the period that this work was performed. Staff of the Southern California Edison Company, Chevron Research Corporation, Union Oil Company, the Southern California Gas Company, Kaiser Steel, and KVB Incorporated have cooperated by providing data for this analysis, or by commenting on work in progeess. The librarians at Union Oil and at ARCO have been helpful in obtaining documents not normally collected by a university library. During the period of the research project, the Los Angeles Air Pollution Control District, the Orange County Air Pollution Control District, the Riverside County Air Pollution Control District and the San Bernardino County Air Pollution Control District were first consolidated into the Southern California Air Pollution Control District and then reorganized into the South Coast Air Quality Management District. Throughout this thesis, the attempt has been made to cite the organizational name prevailing at the time that a particular piece of referenced information was collected. The abbreviation APCD when used refers to the work of the above organizations. This work was carried out within the academic program of the Environmental Engineering Science Department of the California Institute of Technology. The Environmental Quality Laboratory at Caltech provided a financial foothold for the project and much staff assistance. The author's support was provided by the Joseph Warren Barker Fellowship in Engineering, given by the Research Corporation; by a Rockwell International Graduate Fellowship, and by Graduate Research Assistantships financed by research grants and by private gifts to the Environmental Quality Laboratory. The bulk of the cost of this project was met by a grant from the Ford Foundation (No. 740-0469) and by the California Air Resources Board (Contract No. A6-061-87). The California Air Resources Board and their Research Department headed by Dr. John Holmes have cooperated by giving us free rein to approach this problem without constraint or preconditions. Jack Suder has been the contract monitor. All findings and conclusions are solely the responsibility of the authors and the Caltech advisory committee. Glen R. Cass Pasadena, California
Group:Environmental Quality Laboratory
Funding AgencyGrant Number
California Air Resources Board A6-061-87
Ford Foundation740-0469
Record Number:CaltechEQL:EQL-R-16
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Usage Policy:You are granted permission for individual, educational, research and non-commercial reproduction, distribution, display and performance of this work in any format.
ID Code:25731
Deposited By: Imported from CaltechEQL
Deposited On:07 Jun 2005
Last Modified:04 Feb 2016 00:13

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