Surface Air Pollutant Concentration Frequency Distributions: Implications for Urban Modeling

With the development of ambient air quality standards (AAQS), the need arises to describe the characteristics of regional surface air-pollutant concentration frequency distributions. In the evaluation of land use plans, numerous agencies will be concerned with evaluating the effectiveness of emission zoning and/or control actions. On a regional basis, one means of performing this assessment lies in determining the changes in the pollutant frequency distributions resulting from control actions.

This study presents new data concerning the surface air-pollutant concentration frequency distributions observed for area sources and continuous point sources, and compares these distributions with those of the pertinent meteorological variables describing the transport and diffusion of the pollutant. The observed surface air pollutant frequency distributions are compared to those corresponding to simple modeling concepts from either an urban area source or a continuous point source. For an urban source and a relatively inert pollutant like CO, we found that the observed frequency distribution for CO surface air concentration parallels the approximately log-normal frequency distribution of the reciprocal of the wind speed. We show that the constant relating these two well-correlated frequency distributions can be determined either experimentally or with a numerical simulation model of air pollution. The usefulness of numerical models in air pollution is discussed.     

Application of a scenario-based modeling system to evaluate the air quality impacts of future growth

The structure and design of future urban development can have significant adverse effects on air pollutant emissions as well as other environmental factors. When considering the future impact of growth on mobile source emissions, we generally model the increase in vehicle kilometers traveled (VKT) as a function of population growth. However, diverse and poorly planned urban development (i.e., urban sprawl) can force higher rates of motor vehicle use and in return increase levels of pollutant emissions than alternative land-use scenarios. The objective of this study is to develop and implement an air quality assessment tool that takes into account the influence of alternative growth and development scenarios on air quality.The use of scenario-based techniques in land use planning has been around since the late 1940s and been tested in many different applications to aid in decision-making. In this study, we introduce the development of an advanced interactive scenario-based land use and atmospheric chemistry modeling system coupled with a GIS (Geographical Information System) framework. The modeling system is designed to be modular and includes land use/land cover information, transportation, meteorological, emissions, and photochemical modeling components. The methods and modularity of the developed system allow its application to both broad areas and applications.To investigate the impact of possible land use change and urbanization, we evaluated a set of alternative future patterns of land use developed for a study area in Southwest California. Four land use and two population variants (increases of 500k and 1M) were considered. Overall, a Regional Low-Density Future was seen to have the highest pollutant emissions, largest increase in VKT, and the greatest impact on air quality. On the other hand, a Three-Centers Future appeared to be the most beneficial alternative future land-use scenario in terms of air quality. For all cases, the increase in population was the main factor leading to the change on predicted pollutant levels.     

The Nationwide Program for Maintenance of Air Quality

The initial state implementation plans concentrated on attainment of the ambient air quality standards in the relatively polluted areas of the country. Many of these plans must now be modified to ensure that the ambient standards will be maintained for the foreseeable future, and to ensure that significant deterioration of air quality in clean areas of the country is prevented.

The existing implementation plans currently contain many measures which are applicable to the maintenance and deterioration efforts, but additional measures must also be developed. Many of these additional measures will involve future planning activities—most common of which will be land use planning activities.

The point is made that, after existing sources have reduced their emissions to the lowest practical level, further air pollution control can only be accomplished by implementing rational planning procedures for management of any new sources of air pollution. This will require extensive cooperation among the air pollution control community; regional, state, and local planning agencies; state and local governments; and the general public in order to ensure that future land use plans include appropriate air quality considerations.     

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.     

Application of genetic algorithms for the design of ozone control strategies

Designing air quality management strategies is complicated by the difficulty in simultaneously considering large amounts of relevant data, sophisticated air quality models, competing design objectives, and unquantifiable issues. For many problems, mathematical optimization can be used to simplify the design process by identifying cost-effective solutions. Optimization applications for controlling nonlinearly reactive pollutants such as tropospheric ozone, however, have been lacking because of the difficulty in representing nonlinear chemistry in mathematical programming models. We discuss the use of genetic algorithms (GAs) as an alternative optimization approach for developing ozone control strategies. A GA formulation is described and demonstrated for an urban-scale ozone control problem in which controls are considered for thousands of pollutant sources simultaneously. A simple air quality model is integrated into the GA to represent ozone transport and chemistry. Variations of the GA formulation for multiobjective and chance-constrained optimization are also presented. The paper concludes with a discussion of the practically of using more sophisticated, regulatory-scale air quality models with the GA. We anticipate that such an approach will be practical in the near term for supporting regulatory decision-making.     

Review of Singapore's air quality and greenhouse gas emissions: current situation and opportunities

Singapore has many environmental accomplishments to its credit. Accessible data on air quality indicates that all criteria pollutants satisfy both U.S. Environmental Protection Agency (EPA) and World Health Organization (WHO) air quality standards and guidelines, respectively. The exception is PM2.5 (particles with an aerodynamic diameter < or = 2.5 microm), which is not currently considered a criteria pollutant in Singapore but may potentially be the major local air pollution problem and cause for health concern. Levels of other airborne pollutants as well as their physical and chemical processes associated with local formation, transformation, dispersion, and deposition are not known. According to available emission inventories, Singapore contribution to the total atmospheric pollution and carbon budget at the regional and global scales is small. Emissions per unit gross domestic product (GDP) are low compared with other countries, although Singapore's per-capita GDP and per-capita emissions are among the highest in the world. Some information is available on health effects, but the impacts on the ecosystem and the complex interactions of air pollution and climate change at a regional level are also unknown. This article reviews existing available information on atmospheric pollution and greenhouse gas emissions and proposes a multipollutant approach to greenhouse gas mitigation and local air quality. Singapore, by reducing its per-capita emissions, increasing the availability of information (e.g., through regularly publishing hourly and/or daily PM2.5 concentrations) and developing a research agenda in this area, would likely be seen to be a model of a high-density, livable, and sustainable city in Southeast Asia and other tropical regions worldwide.     

Effective pollutant emission heights for atmospheric transport modelling based on real-world information

Emission data needed as input for the operation of atmospheric models should not only be spatially and temporally resolved. Another important feature is the effective emission height which significantly influences modelled concentration values. Unfortunately this information, which is especially relevant for large point sources, is usually not available and simple assumptions are often used in atmospheric models. As a contribution to improve knowledge on emission heights this paper provides typical default values for the driving parameters stack height and flue gas temperature, velocity and flow rate for different industrial sources. The results were derived from an analysis of the probably most comprehensive database of real-world stack information existing in Europe based on German industrial data. A bottom-up calculation of effective emission heights applying equations used for Gaussian dispersion models shows significant differences depending on source and air pollutant and compared to approaches currently used for atmospheric transport modelling.     

Cross-Media Environmental Impacts of Air Pollution Regulations for a Coal-Fired Power Plant

The types and rates of pollutant emissions from a coal-fired power plant depend upon plant design, coal characteristics, and environmental control policy. In the past, air pollution regulations were often promulgated without rigorous analysis of the resulting energy penalties and secondary environmental impacts that occur in other environmental media (air, land, or water), which are counterproductive to overall environmental quality. This paper describes a Comparative Assessment Model that has been developed to consider systematically such tradeoffs for conventional and advanced coal-to-electric technologies. The model is applied to quantify the secondary (“cross-media”) environmental and resource impacts resulting from alternative air pollution control policies that reduce sulfur dioxide emissions from a 1000 MW power plant. Multimedia pollutant burdens are presented, together with the increased requirements for coal, limestone, and water that are incurred in generating a fixed net quantity of electricity. The development of sound public policy requires that environmental regulations be sensitive to adverse effects in all environmental media, and that tradeoffs involved in the regulation of specific pollutants to one medium be rigorously and systematically characterized.     

Application of Genetic Algorithms for the Design of Ozone Control Strategies

ABSTRACT

Designing air quality management strategies is complicated by the difficulty in simultaneously considering large amounts of relevant data, sophisticated air quality models, competing design objectives, and unquantifiable issues. For many problems, mathematical optimization can be used to simplify the design process by identifying cost-effective solutions. Optimization applications for controlling nonlinearly reactive pollutants such as tropospheric ozone, however, have been lacking because of the difficulty in representing nonlinear chemistry in mathematical programming models.

We discuss the use of genetic algorithms (GAs) as an alternative optimization approach for developing ozone control strategies. A GA formulation is described and demonstrated for an urban-scale ozone control problem in which controls are considered for thousands of pollutant sources simultaneously. A simple air quality model is integrated into the GA to represent ozone transport and chemistry. Variations of the GA formulation for multiobjective and chance-constrained optimization are also presented. The paper concludes with a discussion of the practicality of using more sophisticated, regulatory-scale air quality models with the GA. We anticipate that such an approach will be practical in the near term for supporting regulatory decision-making.     

Mapping air quality zones for coastal urban centers

This study presents a new method that incorporates modern air dispersion models allowing local terrain and land–sea breeze effects to be considered along with political and natural boundaries for more accurate mapping of air quality zones (AQZs) for coastal urban centers. This method uses local coastal wind patterns and key urban air pollution sources in each zone to more accurately calculate air pollutant concentration statistics. The new approach distributes virtual air pollution sources within each small grid cell of an area of interest and analyzes a puff dispersion model for a full year’s worth of 1-hr prognostic weather data. The difference of wind patterns in coastal and inland areas creates significantly different skewness (S) and kurtosis (K) statistics for the annually averaged pollutant concentrations at ground level receptor points for each grid cell. Plotting the S-K data highlights grouping of sources predominantly impacted by coastal winds versus inland winds. The application of the new method is demonstrated through a case study for the nation of Kuwait by developing new AQZs to support local air management programs. The zone boundaries established by the S-K method were validated by comparing MM5 and WRF prognostic meteorological weather data used in the air dispersion modeling, a support vector machine classifier was trained to compare results with the graphical classification method, and final zones were compared with data collected from Earth observation satellites to confirm locations of high-exposure-risk areas. The resulting AQZs are more accurate and support efficient management strategies for air quality compliance targets effected by local coastal microclimates.

Implications: A novel method to determine air quality zones in coastal urban areas is introduced using skewness (S) and kurtosis (K) statistics calculated from grid concentrations results of air dispersion models. The method identifies land–sea breeze effects that can be used to manage local air quality in areas of similar microclimates.     

Conjunctive use of models to design cost-effective ozone control strategies

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     

Kosetice, Czech Republic--ten years of air pollution monitoring and four years of evaluating the origin of persistent organic pollutants

The regional observatory Kosetice is a central European background station. Unique continuous monitoring from 1988 on is held here. POP (persistent organic pollutant) concentration values of air samples from Kosetice taken between 1996 and 2005 were statistically processed. Values of Czech ambient air quality standards were not exceeded. Concentrations of polycyclic aromatic hydrocarbons reached two maxima, in 1996 and 2001-2002. Polychlorinated biphenyls concentrations reached the highest values in 1997 and 1998 and hexachlorocyclohexanes concentrations in 1998. DDTs, hexachlorobenzene and pentachlorobenzene were analysed as well. Long-range transport of pollutants between 2002 and 2005 was evaluated using the Potential Source Contribution Function hybrid receptor model. Indicated potential source areas of PCBs coincide with many well-known urban and industrialised areas, while the indicated potential source areas of HCHs and DDTs coincide with many agricultural and/or forested regions and the potential source areas of HCB comprise all land use types.     

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.     

Atmospheric composition change – global and regional air quality

Air quality transcends all scales with in the atmosphere from the local to the global with handovers and feedbacks at each scale interaction. Air quality has manifold effects on health, ecosystems, heritage and climate. In this review the state of scientific understanding in relation to global and regional air quality is outlined. The review discusses air quality, in terms of emissions, processing and transport of trace gases and aerosols. New insights into the characterization of both natural and anthropogenic emissions are reviewed looking at both natural (e.g. dust and lightning) as well as plant emissions. Trends in anthropogenic emissions both by region and globally are discussed as well as biomass burning emissions. In terms of chemical processing the major air quality elements of ozone, non-methane hydrocarbons, nitrogen oxides and aerosols are covered. A number of topics are presented as a way of integrating the process view into the atmospheric context; these include the atmospheric oxidation efficiency, halogen and HO_x chemistry, nighttime chemistry, tropical chemistry, heat waves, megacities, biomass burning and the regional hot spot of the Mediterranean. New findings with respect to the transport of pollutants across the scales are discussed, in particular the move to quantify the impact of long-range transport on regional air quality. Gaps and research questions that remain intractable are identified. The review concludes with a focus of research and policy questions for the coming decade. In particular, the policy challenges for concerted air quality and climate change policy (co-benefit) are discussed.     

Application of Gas-Aerosol Adsorption Data to the Selection of Air Quality Standards

A quantitative approach is presented for selecting air quality standards which take into account pollutant gas-aerosol synergistic effects. These synergistic health effects have been postulated to be due to the adsorption or absorption of the pollutant gas by the aerosol particles. The approach presented in this paper assumes that the synergistic toxic agent is the adsorbed pollutant gas. Therefore, limiting the concentration of the adsorbed pollutant gas limits the magnitude of the synergistic effects. The concentration of the adsorbed pollutant gas is related to the concentrations of the gaseous phase pollutant gas and the atmospheric aerosol using the Langmuir adsorption isotherm. An example is presented of the selection of air quality standards for sulfur dioxide and the atmospheric aerosol using concentration data for these two pollutants along with health effect data.     

Air quality measurements—From rubber bands to tapping the rainbow

It is axiomatic that good measurements are integral to good public policy for environmental protection. The generalized term for “measurements” includes sampling and quantitation, data integrity, documentation, network design, sponsorship, operations, archiving, and accessing for applications. Each of these components has evolved and advanced over the last 200 years as knowledge of atmospheric chemistry and physics has matured. Air quality was first detected by what people could see and smell in contaminated air. Gaseous pollutants were found to react with certain materials or chemicals, changing the color of dissolved reagents such that their light absorption at selected wavelengths could be related to both the pollutant chemistry and its concentration. Airborne particles have challenged the development of a variety of sensory devices and laboratory assays for characterization of their enormous range of physical and chemical properties. Advanced electronics made possible the sampling, concentration, and detection of gases and particles, both in situ and in laboratory analysis of collected samples. Accurate and precise measurements by these methods have made possible advanced air quality management practices that led to decreasing concentrations over time. New technologies are leading to smaller and cheaper measurement systems that can further expand and enhance current air pollution monitoring networks.

Implications: Ambient air quality measurement systems have a large influence on air quality management by determining compliance, tracking trends, elucidating pollutant transport and transformation, and relating concentrations to adverse effects. These systems consist of more than just instrumentation, and involve extensive support efforts for siting, maintenance, calibration, auditing, data validation, data management and access, and data interpretation. These requirements have largely been attained for criteria pollutants regulated by National Ambient Air Quality Standards, but they are rarely attained for nonroutine measurements and research studies.     

Review of Singapore's air quality and greenhouse gas emissions: Current situation and opportunities

Singapore has many environmental accomplishments to its credit. Accessible data on air quality indicates that all criteria pollutants satisfy both U.S. Environmental Protection Agency (EPA) and World Health Organization (WHO) air quality standards and guidelines, respectively. The exception is PM_2.5 (particles with an aerodynamic diameter ≤2.5 μm), which is not currently considered a criteria pollutant in Singapore but may potentially be the major local air pollution problem and cause for health concern. Levels of other airborne pollutants as well as their physical and chemical processes associated with local formation, transformation, dispersion, and deposition are not known. According to available emission inventories, Singapore's contribution to the total atmospheric pollution and carbon budget at the regional and global scales is small. Emissions per unit gross domestic product (GDP) are low compared with other countries, although Singapore's per-capita GDP and per-capita emissions are among the highest in the world. Some information is available on health effects, but the impacts on the ecosystem and the complex interactions of air pollution and climate change at a regional level are also unknown. This article reviews existing available information on atmospheric pollution and greenhouse gas emissions and proposes a multipollutant approach to greenhouse gas mitigation and local air quality. Singapore, by reducing its per-capita emissions, increasing the availability of information (e.g., through regularly publishing hourly and/or daily PM_2.5 concentrations) and developing a research agenda in this area, would likely be seen to be a model of a high-density, livable, and sustainable city in Southeast Asia and other tropical regions worldwide.

Implications Singapore is widely recognized for its environmental achievements and often cited as a model of a high-density, livable, and sustainable city. This article reviews available information with the aim to provide a reference for future scientific research of strategic relevance for Singapore's air quality and greenhouse gas mitigation management under a multipollutant framework. However, the limited publicly accessible data and little scientific information prevent a comprehensive assessment of the local air quality and greenhouse gas emissions. Singapore's dynamic economy and strong profile in advanced science and technological innovation have the potential to enhance the research agenda in this area, which is not yet well developed in tropical cities.     

Air Pollution Research Needs: Herbaceous and Ornamental Plants and Agriculturally Generated Pollutants

Effects of various air pollutants on economically important crops and ornamentals have been studied since before the turn of the century.

Summaries of this research on the effects of air pollutants, that have appeared in criteria documents developed by the Environmental Protection Agency, should be reviewed with respect to differences in plant susceptibility found in various regions of the country. These susceptibility differences are associated with variations in both environmental conditions and distribution of pollutants. Research efforts on air pollution injury to vegetation have often been poorly coordinated leaving many gaps in our knowledge. A better assessment of the impact of air pollution on vegetation is required to attain realistic controls for pollutants affecting agriculture. Research areas of major concern include: baseline information on effects of pollutants on agricultural productivity; dose-response information to support predictive mathematical models for acute and chronic studies of growth, yield, and quality effects; effects of pollutants interacting with other pollutants and with insects and plant diseases; mechanisms of pollutant action; genetic changes related to pollutant effects; effects of environmental stresses on plant response to pollutants; evaluation of plants including soil microbes as pollutant sinks; development of techniques to minimize pollutant effects; and, the effects of agricultural chemicals as air pollutants. There is a need for studies that consider the whole plant in its natural environment. Conceptual models interrelating pollutant effects and their interactions and ultimately mathematical models will be needed to develop an intelligent approach to land management. The effects of agriculturally produced pollutants on plants and other receptors must be identified and quantified.     

Modeling emissions for three-dimensional atmospheric chemistry transport models

Poor air quality is still a threat for human health in many parts of the world. In order to assess measures for emission reductions and improved air quality, three-dimensional atmospheric chemistry transport modeling systems are used in numerous research institutions and public authorities. These models need accurate emission data in appropriate spatial and temporal resolution as input. This paper reviews the most widely used emission inventories on global and regional scales and looks into the methods used to make the inventory data model ready. Shortcomings of using standard temporal profiles for each emission sector are discussed, and new methods to improve the spatiotemporal distribution of the emissions are presented. These methods are often neither top-down nor bottom-up approaches but can be seen as hybrid methods that use detailed information about the emission process to derive spatially varying temporal emission profiles. These profiles are subsequently used to distribute bulk emissions such as national totals on appropriate grids. The wide area of natural emissions is also summarized, and the calculation methods are described. Almost all types of natural emissions depend on meteorological information, which is why they are highly variable in time and space and frequently calculated within the chemistry transport models themselves. The paper closes with an outlook for new ways to improve model ready emission data, for example, by using external databases about road traffic flow or satellite data to determine actual land use or leaf area. In a world where emission patterns change rapidly, it seems appropriate to use new types of statistical and observational data to create detailed emission data sets and keep emission inventories up-to-date.

Implications: Emission data are probably the most important input for chemistry transport model (CTM) systems. They need to be provided in high spatial and temporal resolution and on a grid that is in agreement with the CTM grid. Simple methods to distribute the emissions in time and space need to be replaced by sophisticated emission models in order to improve the CTM results. New methods, e.g., for ammonia emissions, provide grid cell–dependent temporal profiles. In the future, large data fields from traffic observations or satellite observations could be used for more detailed emission data.     

A spatial multicriteria model for determining air pollution at sample locations

Atmospheric pollution in urban centers has been one of the main causes of human illness related to the respiratory and circulatory system. Efficient monitoring of air quality is a source of information for environmental management and public health. This study investigates the spatial patterns of atmospheric pollution using a spatial multicriteria model that helps target locations for air pollution monitoring sites. The main objective was to identify high-priority areas for measuring human exposures to air pollutants as they relate to emission sources. The method proved to be viable and flexible in its application to various areas.

Implications:?Spatial multicriteria models provide a tool for air pollution management in urban areas. Analytic hierarchy process (AHP) modeling can help with the process of prioritizing monitoring site locations and minimizing costs.