Will the circle be unbroken: a history of the U.S. National Ambient Air Quality Standards

In celebration of the 100th anniversary of the Air & Waste Management Association, this review examines the history of air quality management (AQM) in the United States over the last century, with an emphasis on the ambient standards programs established by the landmark 1970 Clean Air Act (CAA) Amendments. The current CAA system is a hybrid of several distinct air pollution control philosophies, including the recursive or circular system driven by ambient standards. Although this evolving system has resulted in tremendous improvements in air quality, it has been far from perfect in terms of timeliness and effectiveness. The paper looks at several periods in the history of the U.S. program, including: (1) 1900-1970, spanning the early smoke abatement and smog control programs, the first federal involvement, and the development of a hybrid AQM approach in the 1970 CAA; (2) 1971-1976, when the first National Ambient Air Quality Standards (NAAQS) were set and implemented; (3) 1977-1993, a period of the first revisions to the standards, new CAA Amendments, delays in implementation and decision-making, and key science/policy/legislative developments that would alter both the focus and scale of air pollution programs and how they are implemented; and (4) 1993-2006, the second and third wave of NAAQS revisions and their implementation in the context of the 1990 CAA. This discussion examines where NAAQS have helped drive implementation programs and how improvements in both effects and air quality/control sciences influenced policy and legislation to enhance the effectiveness of the system over time. The review concludes with a look toward the future of AQM, emphasizing challenges and ways to meet them. The most significant of these is the need to make more efficient progress toward air quality goals, while adjusting the system to address the growing intersections between air quality management and climate change.     

An analysis of numerical models of air pollutant exposure and vegetation response

A number of empirical (statistical, regression oriented) and mechanistic (process oriented) models are presently available to examine the relationship between air pollution stress and plant response. These models have their strengths and weaknesses. In all these models, a major concern is the numerical definition of the pollutant exposure kinetics (dose). At present there are no numerical definitions of dose which make satisfactory biological sense. A key issue is the existence of a biological time clock where plants respond differently to the pollutant stress at different stages of their growth. On the other hand, policy makers and regulatory personnel prefer a simple approach which would facilitate implementation and administration of ambient air quality standards. Long-term air pollutant averaging techniques create artifacts due to the non-normal distribution of ambient concentrations. A more appropriate approach may be the use of 'median' and 'percentiles' computed from short duration pollutant concentrations. Such an approach would be free of the influence of the non-normal distribution, but would require the development of appropriate exposure-response models. Any transfer of results from unit level models to regional level leads to 'scaling error'. There is no general agreement among researchers on how to deal with the scale problem. While this situation persists, any policy formulated on regional impact assessment must acknowledge the uncertainty.     

California Experience with Air Quality Standards

Air quality standards have existed in California for almost six years. They have become an important part of the State’s air pollution control program.

The two principal uses of the standards have been to establish the goals for controlling motor vehicle emissions and to provide a basis for evaluating air quality throughout the State. The standards have also proved to be valuable as a means of communicating on air pollution problems with legislators, administrators, the press, the public, and dischargers of pollutants.

Lack of adequate data on the effects of varying concentrations of contaminants of concern in air pollution is a serious limitation in any effort to establish air quality standards.It is important that this data be obtained.

The concept of employing air quality standards as administrative goals is not unique to the air pollution field but is part of a broad trend to utilize standards for insuring a satisfactory environment. Those engaged in the air pollution field can expect to see increasing emphasis on such standards.

Air quality standards do not provide a magic formula for eliminating air pollution; they are but one element in a comprehensive program. They have limitations and are no better than the data upon which they are based. The standards, however, can play an important role in preserving satisfactory air quality and protecting man’s health.

In using air quality standards, one should keep in mind the comments of H. W. Streeter⁵ on water quality standards—“Let us devise them, try them, revise them, and apply them, but also remember that they are but ’feeble instruments of the human will’ and like all other such tools are made to be discarded for better ones when they become worn out.“     

Coupling air quality and land use modeling within an optimization framework

Land use regulations and air quality standards can be effective tools to control air pollution. Atmospheric transport/chemistry simulation models could be used to develop suitable regulations and standards; however, these models are not as efficient as air quality management models developed from embedding governing equations for atmospheric transport/chemistry into an optimization framework. Formulations of two steady-state air quality management models are presented to facilitate the development or evaluation of land use strategies to protect regional air quality from pollution generated from distributed point or nonpoint sources. Both models are linear programs constructed with equations that describe steady-state atmospheric pollutant fate and transport. The first model determines feasible pollutant loading patterns for multiple land use activities to accommodate the greatest regional population. The second model ascertains patterns of expanded land use which have a minimum impact on air quality. The primary goal of this paper is to explain how air pollution and land use modeling may be coupled to create an effective management tool to aid scientists and engineers with decisions affecting air quality and land use. The secondary goal is to show the types of air quality and regulatory information which could be obtained from these models. This latter goal is attained with general conclusions as consequence of applying ‘duality theory.’     

Federal Regulations for New Source Performance Standards

Section 111 of the Clean Air Act Amendments of 1970 authorizes the U.S. Environmental Protection Agency (EPA) to impose emission standards (NSPS) on those stationary sources that are determined to be significant contributors to air pollution and that consequently endanger the public health or welfare. In five years EPA promulgated 19 final and 1 proposed NSPS for stationary sources. Section 112 of the Act authorizes EPA to promulgate national emission standards for hazardous air pollutants (NESHAPS). EPA promulgated three final and 1 proposed regulation under Section 112. In addition, EPA promulgated NSPS for three "designated" pollutants from specific sources under Section Hid. EPA’s use of Section 111 and 112 authority provides for a quick response emission control program compared to the relatively slow process of establishing additional ambient air quality standards and having the states adopt implementation plans (Section 109). Three court cases, argued in the U.S. Court of Appeals for the District of Columbia, established basic guidelines for future promulgation of NSPS although certain legal actions are still pending. Proposed amendments to the Clean Air Act would further broaden and strengthen EPA’s direct regulatory authority.     

The Stack Height Requirements Implicit In the Federal Standards of Performance For New Stationary Sources

The promulgation of Federal standards of performance for certain classes of new stationary sources requires that such sources have minimum stack heights to meet also the requirements of national air quality standards. The determination of minimum stack height is complicated by the fact that the performance and air quality standards are stated on different averaging time bases; that the extent of preemption of the assimilative capacity of the air by any individual source will vary among jurisdictions and, in some cases, among different geographic areas of a single jurisdiction; and that some new sources will be designed to emit appreciably less than the performance standard requirement. However, these complications can be resolved and equations and charts prepared from which minimum stack height can be selected.     

Air Quality Standards National And International

The advantages and disadvantages of establishingworldwide air quality standards are reviewed. Inter-national standards would represent the best and mostadvanced procedures and might lead to improvementin standards in some countries where air quality isfar from adequate. International standards alsowould permit accurate comparisons of air pollutionamong countries and would provide a sound basis forcombatting pollution.     

A Survey Technique for Determining The Representativeness of Urban Air Monitoring Stations With Respect to Carbon Monoxide

An air quality survey technique for measuring the horizontal spatial variation of carbon monoxide concentrations in urban areas is described; it was used to determine how representative an urban air monitoring station is of concentrations throughout the city.

The survey technique was applied in San Jose, Calif., where 1128 samples were collected over a six-month period and were compared with the values recorded simultaneously at the urban air monitoring station. All samples were collected at “breathing height” within a 13-square-mile grid which included the downtown area as well as surrounding residential and industrial locations. Three basic sampling strategies were employed to answer specific questions about the distribution of carbon monoxide concentration: (7) walking sampling, in which samples were obtained while walking along the sidewalks of congested downtown streets, (2) random spatial sampling, in which samples were collected at randomly selected points in the urban grid, and (3) specialized sampling in the immediate vicinity of the air monitoring station.

The results indicate that pedestrians on downtown streets in San Jose can be exposed to concentrations above the federal air quality standards without these values being observed at the air monitoring station. There also is evidence that, at any instant of time, similar values of carbon monoxide exist throughout this city (within a 13-square mile area), provided that measurements are not made in close proximity to streets. Furthermore, the higher concentrations observed in the immediate vicinity of streets decrease quite rapidly with increasing horizontal distance from these streets.

These findings, in the view of the authors, raise serious doubts as to whether it is possible to determine if air quality standards as currently defined are actually being met in urban areas using data from present-day air monitoring stations.     

Modeling Analysis of Power Plants for Compliance Extensions in 51 Air Quality Control Regions

Past studies indicate a nationwide potential low-sulfur coal supply deficit in 1975 arising from extremely low-sulfur State Implementation Plan requirements which cannot ail be met in time by available coal and gas cleaning technology. One means to alleviate this net deficit would be to grant variances where at least primary air quality standards would be maintained.

An extensive modeling analysis was conducted by EPA and Walden Research on a large number of power plants in 51 AQCRs located in 20 states to determine if compliance extensions at these plants could significantly reduce the projected deficit of lowsulfur coal. Using simulation modeling, air quality impact at each plant for projected 1975 operations was determined with application of SIP regulatory requirements and with a full variance from SIP requirements for coal-fired boilers. The results from this investigation indicate that the attainment of primary SO2 air quality standards for the coal-fired plants would probably not be jeopardized by the application of full variance status to 34% of the plants and limited variance status to an additional 22% of the plants. No variance is appropriate for the remaining plants. The projected annual reduction In low-sulfur coal demand (less than 1.0% sulfur) is approximately 137 million tons. The projected shift in the average coal sulfur distribution is from 1.2% under SIP status to 2.1% under the applicable variance status. The power plant variance strategy appears, then, to offer a potentially feasible approach toward alleviating the low-sulfur coal deficit problem without jeopardizing attainment of primary air quality standards. It should be emphasized that compliance extensions are not the only way, or the most desirable way, of dealing with this problem. The final selection of a strategy for a given state or AQCR and the implementation of that strategy involve many questions and policy matters beyond the scope of this study.     

Rethinking the ozone standard

Six properties appear desirable for any set of ozone attainment criteria: (1) sufficient stringency to protect public health, (2) simplicity and understandability, (3) sensitivity to real changes in air quality, (4) stability against meteorological fluctuations, (5) use of as much data as possible, and (6) equivalence between the stringency the criteria appear to mandate, and what they actually mandate. We consider how the federal attainment criteria might be improved with respect to Properties 4 through 6 while being equally strong on 1 through 3. Whether the federal standard meets Property 1 has been the subject of debate, but our analysis would apply also to a modified standard. We show that there are subtleties in how improvements might be made. In particular, basing the attainment status on a statistic with low variance may not lead to a more stable criterion, and although it is easy to find a criterion that makes it hard for a district with bad air to reach attainment, or a district with good air to get out of attainment, it is hard to find a criterion that does both. This suggests using different criteria for districts that are out of attainment from districts that are in attainment. Initially the burden of proof would be on the district to prove that its air is of attainment quality. However, once the district has achieved attainment the burden of proof would shift; the district would remain in attainment unless there was strong evidence to the contrary.(ABSTRACT TRUNCATED AT 250 WORDS)     

Demonstrating attainment of the air quality standards: integration of observations and model predictions into the probabilistic framework

This paper introduces an integrated observational-modeling approach to transform the deterministic nature of attainment demonstrations of the National Ambient Air Quality Standard (NAAQS) into the probabilistic framework. While the methods presented here can be used to address any air quality standard that is based on extreme values, this paper focuses on the application to the 1-hr and 8-hr NAAQS for ozone. Extreme value statistics and resampling techniques are applied to estimate the probability of exceeding the NAAQS for both 1-hr and 8-hr ozone concentrations. Within the integrated observation-modeling analysis approach, we show that the model-to-model differences in the predicted responses to emission reductions are smaller than the model-to-model differences in predicted absolute ozone concentrations. We illustrate that the emission reductions stemming from a real-world emission control strategy would substantially reduce the probability of exceeding the NAAQS over a large portion of the eastern United States, especially for the 8-hr average ozone concentrations.     

Demonstrating Attainment of the Air Quality Standards: Integration of Observations and Model Predictions into the Probabilistic Framework

ABSTRACT

This paper introduces an integrated observational-modeling approach to transform the deterministic nature of attainment demonstrations of the National Ambient Air Quality Standard (NAAQS) into the probabilistic framework. While the methods presented here can be used to address any air quality standard that is based on extreme values, this paper focuses on the application to the 1-hr and 8-hr NAAQS for ozone. Extreme value statistics and resampling techniques are applied to estimate the probability of exceeding the NAAQS for both 1-hr and 8-hr ozone concentrations. Within the integrated observation-modeling analysis approach, we show that the model-to-model differences in the predicted responses to emission reductions are smaller than the model-to-model differences in predicted absolute ozone concentrations. We illustrate that the emission reductions stemming from a real-world emission control strategy would substantially reduce the probability of exceeding the NAAQS over a large portion of the eastern United States, especially for the 8-hr average ozone concentrations.     

Future Impacts of Distributed Power Generation on Ambient Ozone and Particulate Matter Concentrations in the San Joaquin Valley of California

ABSTRACT

Distributed power generation—electricity generation that is produced by many small stationary power generators distributed throughout an urban air basin—has the potential to supply a significant portion of electricity in future years. As a result, distributed generation may lead to increased pollutant emissions within an urban air basin, which could adversely affect air quality. However, the use of combined heating and power with distributed generation may reduce the energy consumption for space heating and air conditioning, resulting in a net decrease of pollutant and greenhouse gas emissions. This work used a systematic approach based on land-use geographical information system data to determine the spatial and temporal distribution of distributed generation emissions in the San Joaquin Valley Air Basin of California and simulated the potential air quality impacts using state-of-the-art three-dimensional computer models. The evaluation of the potential market penetration of distributed generation focuses on the year 2023. In general, the air quality impacts of distributed generation were found to be small due to the restrictive 2007 California Air Resources Board air emission standards applied to all distributed generation units and due to the use of combined heating and power. Results suggest that if distributed generation units were allowed to emit at the current Best Available Control Technology standards (which are less restrictive than the 2007 California Air Resources Board standards), air quality impacts of distributed generation could compromise compliance with the federal 8-hr average ozone standard in the region.

IMPLICATIONS The San Joaquin Valley is a fast growing region that demands increasing power generation to sustain the economic development, and at the same time it is one of the worst polluted areas in the United States. Hence, the region demands alternatives that minimize the air quality impacts of power generation. This paper addresses the air quality impacts of distributed generation of power, an alternative to central power generation that can potentially reduce greenhouse gas and pollutant emissions throughout the United States.     

Evaluation of air quality zone classification methods based on ambient air concentration exposure

Air quality zones are used by regulatory authorities to implement ambient air standards in order to protect human health. Air quality measurements at discrete air monitoring stations are critical tools to determine whether an air quality zone complies with local air quality standards or is noncompliant. This study presents a novel approach for evaluation of air quality zone classification methods by breaking the concentration distribution of a pollutant measured at an air monitoring station into compliance and exceedance probability density functions (PDFs) and then using Monte Carlo analysis with the Central Limit Theorem to estimate long-term exposure. The purpose of this paper is to compare the risk associated with selecting one ambient air classification approach over another by testing the possible exposure an individual living within a zone may face. The chronic daily intake (CDI) is utilized to compare different pollutant exposures over the classification duration of 3 years between two classification methods. Historical data collected from air monitoring stations in Kuwait are used to build representative models of 1-hr NO₂ and 8-hr O₃ within a zone that meets the compliance requirements of each method. The first method, the “3 Strike” method, is a conservative approach based on a winner-take-all approach common with most compliance classification methods, while the second, the 99% Rule method, allows for more robust analyses and incorporates long-term trends. A Monte Carlo analysis is used to model the CDI for each pollutant and each method with the zone at a single station and with multiple stations. The model assumes that the zone is already in compliance with air quality standards over the 3 years under the different classification methodologies. The model shows that while the CDI of the two methods differs by 2.7% over the exposure period for the single station case, the large number of samples taken over the duration period impacts the sensitivity of the statistical tests, causing the null hypothesis to fail. Local air quality managers can use either methodology to classify the compliance of an air zone, but must accept that the 99% Rule method may cause exposures that are statistically more significant than the 3 Strike method.

Implications: A novel method using the Central Limit Theorem and Monte Carlo analysis is used to directly compare different air standard compliance classification methods by estimating the chronic daily intake of pollutants. This method allows air quality managers to rapidly see how individual classification methods may impact individual population groups, as well as to evaluate different pollutants based on dosage and exposure when complete health impacts are not known.     

Development of risk-based air quality management strategies under impacts of climate change

Climate change is forecast to adversely affect air quality through perturbations in meteorological conditions, photochemical reactions, and precursor emissions. To protect the environment and human health from air pollution, there is an increasing recognition of the necessity of developing effective air quality management strategies under the impacts of climate change. This paper presents a framework for developing risk-based air quality management strategies that can help policy makers improve their decision-making processes in response to current and future climate change about 30-50 years from now. Development of air quality management strategies under the impacts of climate change is fundamentally a risk assessment and risk management process involving four steps: (1) assessment of the impacts of climate change and associated uncertainties; (2) determination of air quality targets; (3) selections of potential air quality management options; and (4) identification of preferred air quality management strategies that minimize control costs, maximize benefits, or limit the adverse effects of climate change on air quality when considering the scarcity of resources. The main challenge relates to the level of uncertainties associated with climate change forecasts and advancements in future control measures, since they will significantly affect the risk assessment results and development of effective air quality management plans. The concept presented in this paper can help decision makers make appropriate responses to climate change, since it provides an integrated approach for climate risk assessment and management when developing air quality management strategies. Implications: Development of climate-responsive air quality management strategies is fundamentally a risk assessment and risk management process. The risk assessment process includes quantification of climate change impacts on air quality and associated uncertainties. Risk management for air quality under the impacts of climate change includes determination of air quality targets, selections of potential management options, and identification of effective air quality management strategies through decision-making models. The risk-based decision-making framework can also be applied to develop climate-responsive management strategies for the other environmental dimensions and assess costs and benefits of future environmental management policies.     

California Statewide Assessment of the Effects of Ozone on Crop Productivity

Six properties appear desirable for any set of ozone attainment criteria: (1) sufficient stringency to protect public health, (2) simplicity and understandability, (3) sensitivity to real changes in air quality, (4) stability against meteorological fluctuations, (5) use of as much data as possible, and (6) equivalence between the stringency the criteria appear to mandate, and what they actually mandate. We consider how the federal attainment criteria might be improved with respect to Properties 4 through 6 while being equally strong on 1 through 3. Whether the federal standard meets Property 1 has been the subject of debate, but our analysis would apply also to a modified standard. We show that there are subtleties in how improvements might be made. In particular, basing the attainment status on a statistic with low variance may not lead to a more stable criterion, and although it is easy to find a criterion that makes it hard for a district with bad air to reach attainment, or a district with good air to get out of attainment, it is hard to find a criterion that does both. This suggests using different criteria for districts that are out of attainment from districts that are in attainment. Initially the burden of proof would be on the district to prove that its air is of attainment quality. However, once the district has achieved attainment the burden of proof would shift; the district would remain in attainment unless there was strong evidence to the contrary. An evaluation of a set of criteria based on this idea showed improvements over the federal criteria with respect to the last three desirable properties-stability, use of data, and equivalent stringency-with some sacrifice in simplicity and sensitivity.     

Air toxics in Canada measured by the National Air Pollution Surveillance (NAPS) program and their relation to ambient air quality guidelines

This study reports ambient concentrations of 63 air toxics that were measured in Canada by the National Air Pollution Surveillance (NAPS) program over the period 2009–2013. Measured concentrations are compared with ambient air quality guidelines from Canadian jurisdictions, and compounds that exceeded guidelines are identified and discussed. Although this study does not assess risk or cumulative effects, air toxics that approached guidelines are also identified so that their potential contribution to ambient air toxics pollution can be considered. Eleven air toxics exceeded at least one guideline, and an additional 16 approached guidelines during the study period. Four compounds were measured using methods whose detection limits exceeded a guideline value, three of which could not be compared with guidelines, since they were not detected in any samples. The assessment of several metal(loid) concentrations is tentative, since they were measured only in fine particulate matter (PM) but compared with guidelines based on coarse or total PM. Improvements to sampling and analysis techniques for the latter compounds as well as for those whose methods are subject to known uncertainties would improve confidence in reported concentrations and their relation to applicable guidelines. Analysis of sampling strategies for all compounds found to exceed or approach guidelines would contribute to ensuring that their spatiotemporal coverage is adequate. Examination of the air toxics not measured by NAPS but having guidelines in Canadian jurisdictions or being included in other programs such as the U.S. National-Scale Air Toxics Assessment (NATA) would contribute to ensuring that the full suite of pollutants relevant to ambient air quality in Canada is subject to adequate study. The results of this study can be applied to evaluating the effectiveness of toxic substances management in Canada.

Implications: Recent measurements of 63 air toxics in Canada by the National Air Pollution Surveillance (NAPS) program showed that 11 compounds exceeded daily or annual ambient air quality guidelines and that an additional 16 compounds approached such guidelines within an order of magnitude. The results of this study can be applied to evaluating the effectiveness of toxic substances management in Canada and to identifying compounds that merit further investigation.     

Selected International Receptor-Based Air Quality Standards

Abstract

The ambient air quality standards (AAQS) of twenty-one nations for eight commonly regulated substances are presented. Many countries are adding a receptor-based component to their air quality management, which traditionally have been emission oriented. Automation of air quality monitoring stations has meant that local air quality evaluation can now be more easily achieved. However, a majority of countries have no active air quality standards (emission or receptor-based) or ambient air quality monitoring. One possible monitoring procedure is outlined and the variation in international standards is discussed.     

Future impacts of distributed power generation on ambient ozone and particulate matter concentrations in the San Joaquin Valley of California

Distributed power generation-electricity generation that is produced by many small stationary power generators distributed throughout an urban air basin-has the potential to supply a significant portion of electricity in future years. As a result, distributed generation may lead to increased pollutant emissions within an urban air basin, which could adversely affect air quality. However, the use of combined heating and power with distributed generation may reduce the energy consumption for space heating and air conditioning, resulting in a net decrease of pollutant and greenhouse gas emissions. This work used a systematic approach based on land-use geographical information system data to determine the spatial and temporal distribution of distributed generation emissions in the San Joaquin Valley Air Basin of California and simulated the potential air quality impacts using state-of-the-art three-dimensional computer models. The evaluation of the potential market penetration of distributed generation focuses on the year 2023. In general, the air quality impacts of distributed generation were found to be small due to the restrictive 2007 California Air Resources Board air emission standards applied to all distributed generation units and due to the use of combined heating and power. Results suggest that if distributed generation units were allowed to emit at the current Best Available Control Technology standards (which are less restrictive than the 2007 California Air Resources Board standards), air quality impacts of distributed generation could compromise compliance with the federal 8-hr average ozone standard in the region.     

Conjunctive Use of Models to Design Cost-Effective Ozone Control Strategies

Abstract

The management of tropospheric ozone (O₃) is particularly difficult. The formulation of emission control strategies requires considerable information including: (1) emission inventories, (2) available control technologies, (3) meteorological data for critical design episodes, and (4) computer models that simulate atmospheric transport and chemistry. The simultaneous consideration of this information during control strategy design can be exceedingly difficult for a decision-maker. Traditional management approaches do not explicitly address cost minimization. This study presents a new approach for designing air quality management strategies; a simple air quality model is used conjunctively with a complex air quality model to obtain low-cost management strategies. A simple air quality model is used to identify potentially good solutions, and two heuristic methods are used to identify cost-effective control strategies using only a small number of simple air quality model simulations. Subsequently, the resulting strategies are verified and refined using a complex air quality model. The use of this approach may greatly reduce the number of complex air quality model runs that are required. An important component of this heuristic design framework is the use of the simple air quality model as a screening and exploratory tool. To achieve similar results with the simple and complex air quality models, it may be necessary to “tweak” or calibrate the simple model. A genetic algorithm-based optimization procedure is used to automate this tweaking process. These methods are demonstrated to be computationally practical using two realistic case studies, which are based on data from a metropolitan region in the United States.