An Approach to Air Quality Management Standards

The Clean Air Amendments of 1970 impose a stringent set of uniform air quality standards and a rigid timetable for achieving them. Such an approach is open to serious question, since it fails to take account of variations in relevant local conditions. This paper sketches a proposal for a more realistic approach to air quality. It suggests a program of management standards that would reflect the needs and circumstances of particular regions. An institutional framework is outlined that would consider the technical, economic, and social constraints that determine how quickly and how much any area can improve its air quality. The framework would provide the needed flexibility, and would employ a feedback approach that avoids the need to resolve all uncertainties before any progress can be made. At the same time, it would impose a timetable and planning process to assure that all feasible progress in air quality improvement is realized nationwide.     

A Quantitative Approach to the Traffic Air Quality Problem: The Traffic Air Quality Index

Abstract

The Traffic Air Quality (TAQ) model is a simple tool to estimate traffic fine particulate emissions on roadways (g/km) and can be used for both real-time analysis and for localized conformity analysis (“hot-spot” analysis for nonattainment areas) as defined by 40 CFR 93.123. This paper is a follow-up to a study published earlier regarding the development of the TAQ model. This paper shows how local air quality levels can be a factor in traffic management in nonattainment areas. Similar to the industrial source quotas measured in tons per year, it is proposed that road segments are to be assigned emission quotas (or TAQ indices) measured in pollutant mass emitted per road length (g/km) above which traffic-measures have to be taken to reduce the fine-particulates emissions on such road links. The TAQ model as well as traffic-rerouting measures along with the Intelligent Transportation System (ITS) protocols can be used to have a real-time control of the traffic conditions along expressways to maintain the fine-particulates emissions below the quota assigned per road link and consequently improving the over all local air quality in nonattainment areas.     

An Index and Model of Human Response to Air Quality

This study undertook an empirical Investigation of human response to air quality. Home interviews of 475 respondents living in 22 neighborhoods of Los Angeles County had elicited information on respondent socioeconomic characteristics, behavioral patterns, and measures of human response to air quality. This data base was then augmented with nine measures of actual air quality for six time frames for each neighborhood.

An observer-based air quality index (OBAQI) was constructed based upon which combination of air quality variables correlated best with the percentage of neighborhood respondents who perceived “smoggy air.” The best combination (OBAQI 3) consisted of prevailing visibility, O₃, and SO₂, each measured as the annual number of days that a selected standard had been equalled or exceeded. Subsequently, multiple regression models were constructed using this index as a predictor of aggregated perception of air quality. In addition to a general model for all neighborhoods, separate models were constructed for clusters of neighborhoods of similar micrometeorology as approximated by uniform elevations and/or coastal distances. Zones of homogeneous air quality and micrometeorology were then defined. Within these zones variation in four measures of human response to air quality was associated with respondent socioeconomic characteristics and behavioral patterns. Both the index and model could prove useful in gauging public response to proposed actions of air quality management districts.     

An Efficient Gaussian-Plume Multiple-Source Air Quality Algorithm

The information presented in this paper is directed to air pollution scientists with an interest in applying air quality simulation models. RAM is the three letter designation for this efficient Gaussian-plume multiple-source air quality algorithm. RAM is a method of estimating short-term dispersion using the Gaussian steady-state model. This algorithm can be used for estimating air quality concentrations of relatively stable pollutants for averaging times from an hour to a day in urban areas from point and area sources. The algorithm is applicable for locations with level or gently rolling terrain where a single wind vector for each hour is a good approximation to the flow over the source area considered. Calculations are performed for each hour. Hourly meteorological data required are wind direction, wind speed, stability class, and mixing height. Emission information required of point sources consists of source coordinates, emission rate, physical height, stack gas volume flow and stack gas temperature. Emission information required of area sources consists of south-west corner coordinates, source area, total area emission rate and effective area source height. Computation time is kept to a minimum by the manner in which concentrations from area sources are estimated using a narrow plume hypothesis and using the area source squares as given rather than breaking down all sources to an area of uniform elements. Options are available to the user to allow use of three different types of receptor locations: 1 ) those whose coordinates are input by the user, 2) those whose coordinates are determined by thé model and are downwind óf significant point and area sources where maxima are likely to occur, and 3) those whose coordinates are determined by the model to give good area coverage of a specific portion of the region. Computation time is also decreased by keeping the number of receptors to a minimum.     

A Cost-Benefit Approach to Air Pollution Control

Air pollution has plagued the urban areas of our Nation for many years, both as a serious health hazard and as a costly economic burden. Users of the air as a waste disposal medium have treated it as a free resource with no regard for the damages incurred by receptors of the dirty air. Unfortunately, no self-regulating market forces exist that will bring this diseconomy into an acceptable equilibrium. An outside regulating force, which can affect abatement of air pollution, is needed to achieve control of air pollution to a level acceptable to a community. A prerequisite of any proposed regulatory action to be applied by an outside force, however, is the need to define an acceptable level of pollution. One means of accomplishing the task is to apply an economic evaluation, in the form of a cost-benefit analysis, to the problem. Previous analyses of the economic aspects of air pollution have stressed only one side of the problem. That is, they have dealt only with the cost of control or the damages caused by air pollution. No analysis has combined both aspects into a meaningful analysis of the overall economic impact. The objective of this paper is to present a technique that can be used to find the level of pollution abatement in an area that balances the cost of controlling pollution with the benefits received from its control. To present a clearer picture of this technique and its results, it has been applied to the Washington, D. C. area to find the optimum level of particulate abatement. This method is generally applicable to any area, in which an air pollution problem exists.     

Analysis of Air Quality Observations with the Aid of the Source-Receptor Relationship Approach

Abstract

In this study, an attempt was made to analyze time series of air quality measurements (O₃, SO₂, SO₄ ^2?NO_x) conducted at a remote place in the eastern Mediterranean (Finokalia at Crete Island in 1999) to obtain concrete information on potential contributions from emission sources. For the definition of a source-receptor relationship, advanced meteorological and dispersion models appropriate to identify “areas of influence” have been used. The model tools used are the Regional Atmospheric Modeling System and the Lagrangian-type particle dispersion model (forward and backward in time), with capabilities to derive influence functions and definition of “areas of influence.” When high levels of pollutants have been measured at the remote location of Finokalia, particles are released from this location (receptor) and traced backward in time. The influence function derived from particle distributions characterizes dispersion conditions in the atmosphere and also provides information on potential contributions from emission sources within the modeling domain to this high concentration. As was shown in the simulation results, the experimental site of Finokalia in Crete is influenced during the selected case studies, primarily by pollutants emitted from the urban conglomerate of Athens. Secondarily, it is influenced by polluted air masses arriving from Italy and/or the Black Sea Region. For some specific cases, air pollutants monitored at Finokalia were possibly related to war activities in the West Balkan Region (Kosovo).     

A Qualitative Approach to Evaluating the Anticipated Reliability of a Photochemical Air Quality Simulation Model for a Selected Application

ABSTRACT

Photochemical air quality simulation models are now used widely in evaluating the merits of alternative emissions control strategies on spatial scales from metropolitan to sub-continental. Greatly varying levels of resources have been available to support modeling, from relatively comprehensive databases and evaluation of performance to a paucity of aerometric data for developing model inputs. Where data are sparse, many alternative outcomes are consistent with the knowledge at hand. Where performance evaluation is inadequately supported, the probability of error may be high. In each instance, uncertainties may be large when compared with the signal of interest, and thus confidence in the reliability of the model as an estimator of future air quality may come into question.

This paper proposes a qualitative procedure for assessing whether a particular application of a modeling system is likely to be potentially unreliable, suggesting that either (1) modification and further evaluation is needed, if supportable, prior to adoption for regulatory application; or (2) the model should not be used if improvement is not supportable. The procedure is proposed for use by policy-makers, staffs of public agencies, air quality managers, environmental staffs of industrial organizations, and other interested parties. The proposed use of the procedure is (1) to assess, a priori, whether a proposed application is likely to be judged questionable or unacceptably uncertain in outcome; and (2) to provide, a posteriori, a basis for judging quickly the likely quality of model performance. The procedure is presented with tropospheric ozone as the pollutant of concern. With adjustments, however, the procedure should be applicable for particu-late matter and other pollutants of interest.     

Modeling to Evaluate Contribution of Oil and Gas Emissions to Air Pollution

Oil and gas production in the Western United States has increased considerably over the past 10 years. While many of the still limited oil and gas impact assessments have focused on potential human health impacts, the typically remote locations of production in the Intermountain West suggests that the impacts of oil and gas production on national parks and wilderness areas (Class I and II areas) could also be important. To evaluate this, we utilize the Comprehensive Air quality Model with Extensions (CAMx) with a year-long modeling episode representing the best available representation of 2011 meteorology and emissions for the Western United States. The model inputs for the 2011 episodes were generated as part of the Three State Air Quality Study (3SAQS). The study includes a detailed assessment of oil and gas (O&G) emissions in Western States. The year-long modeling episode was run both with and without emissions from O&G production. The difference between these two runs provides an estimate of the contribution of the O&G production to air quality. These data were used to assess the contribution of O&G to the 8 hour average ozone concentrations, daily and annual fine particulate concentrations, annual nitrogen deposition totals and visibility in the modeling domain. We present the results for the Class I and II areas in the Western United States. Modeling results suggest that emissions from O&G activity are having a negative impact on air quality and ecosystem health in our National Parks and Class I areas.

Implications: In this research, we use a modeling framework developed for oil and gas evaluation in the western United States to determine the modeled impacts of emissions associated with oil and gas production on air pollution metrics. We show that oil and gas production may have a significant negative impact on air quality and ecosystem health in some national parks and other Class I areas in the western United States. Our findings are of particular interest to federal land managers as well as regulators in states heavy in oil and gas production as they consider control strategies to reduce the impact of development.     

“分析家”被动采样器在区域空气质量评估中的应用

简要介绍“分析家”（Analyst）被动采样器的结构、原理及在中意项目：“分析家”被动采样器在苏州空气监测系统预评估阶段的应用。     

Ozone Air Quality Models

Abstract

The field of ozone air quality modeling, or as it is commonly referred to, photochemical air quality modeling, has undergone rapid change in recent years. Improvements in model components, as well as in methods of interpreting model performance, have contributed to this change. Attendant with this rapid change has been a growing need for those developing and using air quality models and policy makers to have a common understanding of the use and role of models in the decision making process. This Critical Review highlights recent advances and continuing problem areas in photochemical air quality modeling. Emphasis is placed on the components and input data for such models, model performance evaluation, and the implications for their use in regulatory decisions.     

The Annual Average: An Alternative to the Second Highest Value as a Measure of Air Quality

It is common practice to use the second highest value both in determining compliance with the once-per-year air quality standards (AQS) and as a measure of air quality in pollutant trend studies and rollback calculations. A study of the variation in the second highest 8 hr carbon monoxide concentration observed at the CAMP stations 1962-72 is presented. It is shown that, for a given annual average, the second highest value can differ by a factor of 2 due to random variation. The annual average is linearly related to the observed average of the second highest value and is shown to be a good predictor of the percent of time the carbon monoxide AQS is exceeded. It is concluded that the annual average, which is less variable and not as greatly influenced by erroneous measurements, is the preferred measure of air quality for trend studies and air quality projections.     

Impact of NOx Emissions Released from a Gas Turbine-Based Power Plant on the Ambient Air Quality

The number of gas turbine- (GT-) based power plants is rapidly increasing to meet the world’s power demands. Until a few years ago, fossil fuel, and specifically fuel oil, was considered the major energy source for gas turbine operation. Due to the high amount of pollution that fuel oil generates, natural gas has become a popular source of energy due to its lower emissions compared to fuel oil. As a result, many GTs have switched to natural gas as an alternative to fuel oil. However, pollutants expelled from GT-based power plants operating on natural gas impact surrounding air quality. The objective of this study was to examine the dispersion of nitrogen oxides (NO_x) emitted from a GT-based power plant located in the Sultanate of Oman. Supported by CALPUFF dispersion modeling software, six scenarios were investigated in this study. The first four scenarios considered a case where the GT-based power plant was operating on natural gas during winter and summer and for open and combined cycle modes. The remaining two scenarios considered, for both open and combined cycle modes, the case where the GT-based power plant was operating on fuel oil. Whether run by natural gas or fuel oil, CALPUFF simulation results for both seasons showed that NO_x concentrations were higher when GTs were used in the combined cycle mode. The concentrations were still lower than the allowable concentrations set by the United States Environmental Protection Agency (U.S. EPA) standards. In contrast, for the case where the power plant operated on fuel oil, the NO_x one-hour average simulated results exceeded the allowable limits only when the combined cycle mode was activated.     

气相色谱法测定气体中的二溴甲烷

建立了一种简便快速测定空气中二溴甲烷的方法，即空气中的二溴甲烷经Tenax管吸附，TJ-618热解析仪解析，电子捕获检测器检测，该法线性关系良好，其精密度及回收率均符合方法学要求，方法结果简单、快速、准确、可靠。     

Monte Carlo Simulation Techniques Applied to Air Quality Impact Assessment

Hammersly and Handscomb¹ describe Monte Carlo Methods as a branch of experimental mathematics concerned with experiments on random numbers. The purpose of this paper is to suggest methods through which this powerful technique can be applied to the problem of evaluating the return period of a concentration estimate.