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.     

A Finite Line Source Dispersion Model for Mobile Source Air Pollution

The body of information presented in this paper is directed to individuals interested in dispersion modeling, and in particular to those concerned with evaluation of air quality in the vicinities of airports and roadways. The paper describes briefly the formulation and application of a finite line source dispersion model constructed on the basis of a Gaussian-type transport kernel. The formulation is sufficiently general that any arbitrary orientation of the line can be handled. For cases where the line is at small angles with respect to the wind, approximate expressions as well as segmentation of the line, if necessary, are used. These are Integrated into the general algorithmic scheme by means of a series of geometric tests. The general capabilities of the model are tested first with some hypothetical cases and then with actual air quality data. The latter case studies correspond to three separate periods of air quality monitoring at O’Hare Airport during which the aircraft emissions and the ground vehicle emissions play alternately important roles. The generally good agreement between model predictions and air quality data provides support for the validity of the approach. The overall efficiency of the model in terms of computer time as well as its limitations are briefly discussed.     

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     

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.     

The Formulation of Emission Control Strategies Using a Cubic Polynomial Approximation

Assuming the existence of an ambient air standard for a given pollutant, there is some agreement that emission standards for local area and point sources should be established by formulating and testing various “control strategies” with use of a computer diffusion model. The procedure requires several, perhaps many, computer simulations of pollutant dispersion followed by an analysis of the results of each simulation. Part of this analysis is to include an “optimization” of sorts which is intended to provide a workable control strategy which, in turn, is to indicate required emission level reductions for point sources. This paper is intended to describe and apply an approximation technique which, when used in conjunction with a diffusion model, could be of value in determining acceptable emission levels for point sources.     

Source Inventory IBM System for Particulate and Gaseous Pollutants

A source inventory IBM system of air pollutants is described which makes use of an existing IBM card index-registration system in an established air pollution control district and which employs efficient utilization of engineering time, including computer services, to establish and maintain current a detailed source inventory of point sources of emissions.     

Effects of measurement uncertainty on air quality summary statistics

This paper examines the effects of measurement uncertainty on various summary statistics that are routinely used in air quality data analysis. Analytical approximations and computer simulation techniques are employed to illustrate and quantify how the uncertainty associated with an individual measurement results in an uncertainty for different summary statistics. Measurement uncertainty may be viewed as consisting of bias and imprecision. It is shown that even when there is no bias for individual measurements it is possible for imprecision alone to result in bias for certain commonly used summary statistics. Different types of statistics are shown to be less influenced by measurement imprecision and, consequently, a data set may be acceptable for some purpose but not for others. The desired precision of the summary statistic may be viewed as a guide in determining an acceptable level of imprecision for individual measurements.     

空气中PM_(10)浓度的BP神经网络预报研究

建立了某市PM10浓度预报的分段BP神经网络模型,经验证,所建立的BP预报模型,预测精度比较高,PM10日平均浓度误差大多在-0．010～0．010mg／m^3范围内,相对误差在-20％～20％,表明BP神经网络对PM10的浓度预报是一种有效的工具。     

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.     

Screening and Scenarios of Traffic Emissions at Trier,Germany

SCOPE AND BACKGROUND: In the course of the European Council Directive on permissible air pollutant limit values, valid starting from 2005 there is an urgent call for action, particularly for fine dust (PM10). Current investigations (Junk & Helbig 2003, Reuter & Baumüller 2003) show that the limit values in certain places in congested areas are exceeded. Only if it is possible to locate these Hot Spots purposeful measures to reduce the ambient air pollution can be conducted. For an efficient identification of these Hot Spots numerical computer models or establishing special measurements networks are too expensive. Using the statistical model STREET 5.0 (KTT 2003) a cost-effective screening of the air pollution situation caused by the traffic can be done. METHODS: STREET is based on the 3-dimensional micro-scale non-hydrostatic flow- and dispersion model MISCAM (Eichhorn 1989). The results of over 100.000 different calculations with MISCAM are stored in a Database and used to calculate the emissions with STREET. In collaboration with the city council of Trier more than 150 streets were investigated, mapped, and calculated. A special urban climate measuring network supplies the necessary meteorological input data about the wind field and precipitation events in the valley of the Moselle. Information about road width and road orientation as well as building density was derived from aerial photographs. Traffic censuses and mobile air pollutants measurements supplied the remaining input data. We calculated the mean annual air pollutant concentrations for NO2, CO, SO2, O3, benzene as well as PM10. RESULTS: A comparison of the model results with the values obtained from the stations of the central emission measuring network of Rhineland-Palatinate (ZIMEN, annual report 2002) shows very good agreements. The model was not only used to calculate the annual air pollutant but also for urban planning and management. The absolute level of the air pollutant is mainly dependent on the amount of traffic in the street canyons. Therefore four different case-scenarios with varying quantity of traffic were calculated and interpreted for each street. The results of the calculation show that on the basis of the mean values for both NO2 and benzene, it is not to be expected that the limits PERSPECTIVES: Furthermore the model can be used to find the maximum tolerable numbers of cars for a street without exceeding the air pollutant thresholds.     

Analysis and Modeling of Air Quality at Street Intersections

Four roadway intersection air pollution models were compared to experimental data and evaluated. The models included the recently developed Texas Intersection Model (TEXIN), The Intersection Midblock Model (IMM), the program MICRO and the Indirect Source Guidelines. Data obtained by Texas A&M University at two intersections in Texas and by CALTRANS at an intersection in California were used for the evaluation. The TEXIN Model performed best in all comparisons to the data. The IMM was almost as accurate as TEXIN but required an order of magnitude more input information and computer time. MICRO and the Indirect Source Guidelines performed poorly.     

Evaluation of Episode Control Schemes Through Air Quality Data Analysis

Prediction performance of various air pollution episode models are first compared with that of a persistence model which is based on the assumption that present concentrations persist to a future time. The comparisons are made by computing a correlation coefficient for different lead times between the observed and predicted values, and an auto-correlation function of the air quality data to which the episode model is applied. The persistence of high levels of air pollution is next examined, using existing air quality data, by constructing frequency distributions of air pollution episode duration for various concentration thresholds. Based on the results of persistence analysis, the flaws of currently used episode management schemes are discussed and some alternative episode management schemes are presented. Methodologies and parameters to evaluate the anticipated performances of episode management schemes are developed and some examples are worked out. In conclusion, it is suggested that a combination of episode persistence analysis and air pollution meteorological forecasting could lead to a workable air pollution episode management scheme.     

Improved space–time forecasting of next day ozone concentrations in the eastern US

There is an urgent need to provide accurate air quality information and forecasts to the general public and environmental health decision-makers. This paper develops a hierarchical space–time model for daily 8-h maximum ozone concentration (O₃) data covering much of the eastern United States. The model combines observed data and forecast output from a computer simulation model known as the Eta Community Multi-scale Air Quality (CMAQ) forecast model in a very flexible, yet computationally fast way, so that the next day forecasts can be computed in real-time operational mode. The model adjusts for spatio-temporal biases in the Eta CMAQ forecasts and avoids a change of support problem often encountered in data fusion settings where real data have been observed at point level monitoring sites, but the forecasts from the computer model are provided at grid cell levels. The model is validated with a large amount of set-aside data and is shown to provide much improved forecasts of daily O₃ concentrations in the eastern United States.     

The Limitations of Air Quality Standards

This paper describes a diffusion model designed to permit calculation of seasonal average concentrations of an air pollutant, in particular, sulfur dioxide. The calculations can encompass multiple sources and multiple receptors. For each receptor location the model sums the effect of all sources over a wide range of meteorological conditions. Input data include source pollutant emissions, source configuration and location, receptor location, and meteorological data expressed as a joint frequency distribution of wind direction, wind speed, stability. To determine the model’s accuracy, concentration estimates for St. Louis, Mo., are compared with measured SO₂ concentrations. The overall correlation with observed data is satisfactory. A computer program to handle the numerous calculations was written in Fortran IV language for use on an IBM 1130 computer.     

Air Pollution Emissions from Increased Industrial Coal Use in the Northeastern United States

Evaluating the air pollution impacts of energy use in the industrial sector is difficult because of the diversity and multiplicity of sources and a general lack of systematic, up-to-date data collection mechanisms. Fuel-specific energy consumption for a multi-state region is provided by the U.S. Department of Energy PIES model for a base year (1975), together with scenarios for future years. A computer model developed in this study—the Sub-regional Energy and Emissions Model (SEEM)—is applied to disaggregate the regional industrial figures to the county level according to fuel type and industrial category at the two-digit SIC level. The resulting emissions of total suspended particulates (TSP) and sulfur dioxide (SO₂) for all industrial categories are estimated at the county level by Incorporating county-specific air pollution regulations in SEEM, and are then aggregated to larger geographical regions. The model has been applied to evaluate the increased air pollution impacts of industrial energy use in the northeastern United States for two alternative 1990 scenarios: (1) the midrange/trendlong PIES projections, and (2) a Coal Replacement Scenario, which assumes a higher percentage of fuel burned in new boilers will be coal. The results are discussed in terms of implications for air pollution control policy.     

Interpreting Urban Carbon Monoxide Concentrations by Means of a Computerized Blood COHb Model

A practical, inexpensive computer model for estimating the level of blood carboxyhemoglobin (percent COHb) as a function of time for measured carbon monoxide concentrations (ppm CO) was developed from data from published studies on the assimilation of CO into the blood of human subjects. The model was designed to consider more realistically the dynamic characteristics of urban CO concentrations measured continuously at air monitoring stations, and it was applied to a year's CO data measured at the San Jose CA, air monitoring station (8760 hourly values).

The results indicate that the model can be used by local air pollution control agencies to calculate and print out estimated COHb levels alongside continuous CO concentration data. According to the model, the National Ambient Air Quality Standards (NAAQS) for CO sometimes were violated in San Jose without exceeding 2% COHb, as well as the converse: 2% COHb was exceeded without violating the standards. The model's estimated COHb levels also provided an advance warning of impending violation of the 8-hr CO NAAQS, and analysis of the model's response to CO "spikes" suggests that averaging periods as short as 10 or 15 minutes are necessary to preserve completely the dynamic characteristics of ambient CO monitoring data. These findings suggest that the margin of safety included in the current CO NAAQS, would not be the same if the actual time variation of measured CO concentrations is taken into account.     

Spatial interpretation of ambient air quality for the territory of the Czech Republic

A method for spatial interpretation and visualisation of measured air quality data is presented that may serve as a tool for ambient air quality characterisation using the least possible number of factors. This method enables comparison of different areas in relative terms and has practical consequences in decision making and public information. The 1996 data for the Czech Republic was used as a database. According to my results, not a single universal indicator can fully describe the ambient air quality albeit the three factors identified as "ambient air pollution", "ground-level ozone" and "wet atmospheric deposition" which are recommended. These selected factors represent three different aspects of ambient air quality and its impact on receptors. For the above factors black and white charts are presented classifying the Czech Republic territory into five categories as to relative ambient air quality. The air quality picture differs for the respective factors considerably.     

Computer Analysis of the California Cycle

The current trend toward greater instrumentation in analysis of automobile exhaust gases is sure to increase in future years. This will come about as a result of increased activity to find a solution to air pollution problems resulting from automobile exhaust gases. Owing to the complex driving cycle needed to evaluate vehicle emission, considerable time has been required to analyze and interpret the records from any run. To alleviate this analytic problem, an automatic data logger was obtained that records on magnetic tape the signal from a number of analytical instruments each second (in binary coded decimal form). These records are then analyzed on a computer to give integrated and averaged results over the specified driving cycle. There is no longer any need for manual evaluation of the data. In addition to the standard analyses already mentioned, the use of the data logger permits a much more complete analysis of what is happening in a vehicle. For example, the analytical instruments used include an oxygen analyzer in addition to carbon dioxide, carbon monoxide, and hydrocarbons. With these measurements the air-fuel ratio of any or all driving conditions can be calculated.     

An empirical relationship between PM(2.5) and aerosol optical depth in Delhi Metropolitan

Atmospheric remote sensing offers a unique opportunity to compute indirect estimates of air quality, which are critically important for the management and surveillance of air quality in megacities of developing countries, particularly in India and China, which have experienced elevated concentration of air pollution but lack adequate spatial-temporal coverage of air pollution monitoring. This article examines the relationship between aerosol optical depth (AOD) estimated from satellite data at 5 km spatial resolution and the mass of fine particles ≤2.5 μm in aerodynamic diameter (PM(2.5)) monitored on the ground in Delhi Metropolitan where a series of environmental laws have been instituted in recent years.PM(2.5) monitored at 113 sites were collocated by time and space with the AOD computed using the data from Moderate Resolution Imaging Spectroradiometer (MODIS onboard the Terra satellite). MODIS data were acquired from NASA's Goddard Space Flight Center Earth Sciences Distributed Active Archive Center (DAAC). Our analysis shows a significant positive association between AOD and PM(2.5). After controlling for weather conditions, a 1% change in AOD explains 0.52±0.202% and 0.39±0.15% change in PM(2.5) monitored within ±45 and 150 min intervals of AOD data. This relationship will be used to estimate air quality surface for previous years, which will allow us to examine the time-space dynamics of air pollution in Delhi following recent air quality regulations, and to assess exposure to air pollution before and after the regulations and its impact on health.     

A chamberless field exposure system for ozone enrichment of short vegetation

Only few studies have been conducted as yet which focus on the effects of rising tropospheric ozone levels on semi-natural vegetation under free-air conditions. A new technical approach was used to examine the response of calcareous grassland to ozone employing a chamberless fumigation system. Four different ozone regimes were applied (1-, 1.33-, 1.66- and 2-fold ambient air levels) with five replicates each. Ozone enrichment was carried out on circular plots of 2 m in diameter by a computer controlled exposure system. Transparent windscreens encircling each plot accelerated the mixing of ambient air and ozone released. Thus, the use of blowers could be avoided. The exposure system presented here is regarded as an appropriate technique for free-air trace gas enrichment on short vegetation avoiding microclimatic alterations known to affect plant growth and pollutant uptake. Furthermore, the chosen technical set-up was rather cost-effective. Hence, it enabled the establishment of a larger number of replications providing the basis for results of higher statistical power.