Carbon monoxide concentration forecasting in Santiago, Chile

In the city of Santiago, Chile, air quality is defined in terms of particulate matter with an aerodynamic diameter < or = 10 microm (PM10) concentrations. An air quality forecasting model based on past concentrations of PM10 and meteorological conditions currently is used by the metropolitan agency for the environment, which allows restrictions to emissions to be imposed in advance. This model, however, fails to forecast between 40 and 50% of the days considered to be harmful for the inhabitants every year. Given that a high correlation between particulate matter and carbon monoxide (CO) concentrations is observed at monitoring stations in the city, a model for CO concentration forecasting would be a useful tool to complement information about expected air quality in the city. Here, the results of a neural network-based model aimed to forecast maximum values of the 8-hr moving average of CO concentrations for the next day are presented. Forecasts from the neural network model are compared with those produced with linear regressions. The neural network model seems to leave more room to adjust free parameters with 1-yr data to predict the following year's values. We have worked with 3 yr of data measured at the monitoring station located in the zone with the worst air quality in the city of Santiago, Chile.     

Design of an optimum air monitoring network for exposure assessments

Nonlinear programming techniques are frequently used to design optimum monitoring networks. These mathematically rigorous techniques are difficult to implement or cumbersome when considering other design criteria. This paper presents a more pragmatic approach to the design of an optimal monitoring network to estimate human exposure to hazardous air pollutants. In this approach, an air quality simulation model is used to produce representative air quality patterns, which are then combined with population patterns to obtain typical exposure patterns. These combined patterns are used to determine ‘figures of merit’ for each potential monitoring site, which are used to identify and rank the most favorable sites. The spatial covariance structure of the air quality patterns is used to draw a ‘sphere of influence’ around each site to identify and eliminate redundant monitoring sites. This procedure determines the minimum number of sites required to achieve the desired spatial coverage. This methodology was used to design an optimal ambient air monitoring network for assessing population exposure to hazardous pollutants in the southeastern Ohio River valley.     

Long-term assessment of particulate matter using CHIMERE model

Particulate matter (PM) and aerosols have became a critical pollutant and object of several research applications, due to their increasing levels, especially in urban areas, causing air pollution problems and thus effects on human health. The main purpose of this study is to perform a first long-term air quality assessment for Portugal, regarding aerosols and PM pollution. The CHIMERE chemistry-transport model, forced by the MM5 meteorological fields, was applied over Portugal for 2001 year, with 10 km horizontal resolution, using an emission inventory obtained from a spatial top-down disaggregation of the 2001 national inventory database. The evaluation model exercise shows a model trend to overestimate particulate pollution episodes (peaks) at urban sites, especially in winter season. This could be due to an underprediction of the winter model vertical mixing and also to an overestimation of PM emissions. Simulated inorganic components (ammonium and sulfate) and secondary organic aerosols (SOA) were compared to measurements taken at Aveiro (northwest coast of Portugal). An underestimation of the three components was verified. However, the model is able to predict their seasonal variation. Nevertheless, as a first approach, and despite the complex topography and coastal location of Portugal affected by sea salt natural aerosols emissions, the results obtained show that the model reproduces the PM levels, temporal evolution, and spatial patterns. The concentration maps reveal that the areas with high PM values are covered by the air quality monitoring network.     

Evaluation of an Ion Selective Electrode Monitor for Total Oxidants

The iodide ion selective electrode has potential use for continuous monitoring of total oxidants in ambient air. Total oxidants are measured coulometrically or colorimetrically after oxidation of neutral buffered Kl solution (0.6-1.2M) to free iodine. On the other hand, the iodide electrode can measure much more dilute solutions (<10^-4M). The iodide electrode measures the disappearance of iodide from the absorbing solution. The detector is made from an iodide electrode, reference electrode, an expanded scale pH meter, and millivolt recorder. The iodide electrode shows a constant Nernstian —59 mv change per decade over a dilute solution range although the absolute voltage shows a drift of 1 mv/day. A continuous iodide electrode air monitor was set up and investigated for ambient monitoring. Operational parameters as air and solution flow rates and electrode parameters as response time at different iodide concentrations were investigated. Statistical comparison was made with a Beekman colorimetric total oxidant monitor and a prototype REM chemiluminescent ozone monitor. The iodide electrode monitor was shown capable of continuously monitoring oxidants in the atmosphere being sensitive to changes in ambient concentrations.     

Regulation of Indirect Sources

The Division of Air Pollution Control, Illinois Environmental Protection Agency, has conducted an ambient air quality monitoring project focusing on carbon monoxide levels in and around several indirect sources. An analysis of the data indicates that highway-type pollutant emissions have the greatest impact on receptors in the vicinity of indirect sources. This implies that the principal, localized constraint on the siting of indirect sources will be the carbon monoxide generated on public roadways servicing those indirect sources. Clearly, adequate procedures must be developed to link such highway-type emissions to pollutant concentrations. An area-source model and a line-source model were tested using the data generated during the monitoring project. Favorable results were achieved using the line-source model. The proper siting of indirect sources involves the allocation of roadway capacity by the governmental units responsible for transportation network design, working in conjunction with regional planning bodies. A regulatory structure is suggested which emphasizes a regional approach, and an example of an air quality allocation scheme is given. The methodology is applicable to all automotive air pollutants although, in general, localized sensitivity is lost for N0₂ and photochemical oxi-dants.     

Particulate and sulfur dioxide concentration measurements in Patras,Greece

The purpose of this study was to obtain a better assessment of the Patras, Greece, air quality, in terms of the primary pollutants total suspended particulates (TSPs) and sulfur dioxide (SO2), because limited and short-duration measurements have been conducted in the past. Installation and operation of a mobile air monitoring station at two different locations in the Patras downtown area and one location in the outskirts of the city was undertaken and covered the periods July 1, 1994-January 30, 1995; March 18-August 23, 1995; and April 19-July 27, 1996, respectively. For both pollutants measured at each location, the monthly average concentrations and typical weekly variation of daily averages, as well as the diurnal variations and frequency concentration distributions in each month of the monitoring periods, were calculated and are presented in bar diagrams. The annual and winter period medians and the annual 98th percentile were also calculated and are compared with the limit and guide values provided by the European Economic Community Council Directive 80/779/EEC. In addition, comparison of SO2 values is made with the limit values adopted by the more recent Directive 1999/30/EC. It was found that the TSP and SO2 levels at all locations were very low and were lower than the levels found in Thessaloniki and Athens, Greece. An attempt to explain what had been measured is also undertaken. The data presented are considered essential for future reference and comparison purposes.     

Redundant Measurements of Urban Air Monitoring Networks in Air Quality Reporting

Abstract

This paper describes a statistical method to assess site redundancy of urban air monitoring networks in reporting daily Pollutant Standards Index (PSI), average concentrations, and the number of exceedances. Such a statistical method has identified significant redundancy in monitoring sites for one-year measurements of two air monitoring networks in Taiwan. There are five redundant sites out of 15 monitoring sites in the Taipei area and eight redundant sites out of 18 monitoring sites in the Kaohsiung area. By using the statistical method presented in this paper to downsize the monitoring networks, we can determine not only the number of redundant sites but also the priority of site removals. The derived sub-networks can maintain consistency in reporting air quality without significant changes in the spatial variations of air measurements for an existing air monitoring network.     

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.     

Site Redundancy in Urban Ozone Monitoring

This article describes two statistical methods that enable air pollution control agencies to assess the effectiveness of the spatial distribution of current stationary ozone monitoring networks by providing measures of site redundancy. These methods analyze site redundancy by determining the degree to which ozone measurements at one site can be successfully predicted from data collected at other monitoring sites. The first method, the similarity (SIM) measure, calculates redundancy based on the percentage of common operational days during which two monitoring stations report similar daily maximum ozone concentrations. The second method, a modeling technique, relates site redundancy in ozone measurement to an R-squared statistic from an autoregressive model. The model uses meteorological components recorded at a central location and ozone concentrations reported by the network’s other monitoring stations. Both techniques can assist in effective allocation of limited monitoring resources and offer a statistical approach to ambient air monitoring network design. The techniques are applied to data collected at six ozone monitoring stations in Harris County, Texas, during an eight-year period in the 1980s. The methods identified two sites in the six-site network that exhibit a high degree of redundancy.     

Pennsylvania’s Compuiterized Air Monitoring System

The Pennsylvania Air Pollution Commission has developed a regulatory program based upon the control of local air pollution problems and reduction of pollutant levels in air basins. The geographical boundaries of 10 air basins have been established. The Commission’s air basin regulations will provide for the reduction of over-all pollutant levels and for emergency procedures in the event of adverse meteorological conditions. The paper discusses the format and objectives of the program.

In order to effectively enforce the air basin regulations and maintain the necessary surveillance of the state’s air quality, a "computerized real time on-line integrated air monitoring-data handling system" has been designed. The system will incorporate a network to constantly monitor the air in each air basin.The primary objectives of the system are: 1. Constant surveillance of air pollution in the air basins.

2. Provide information on air pollution potential alerts.

3. Aid in further development of air quality criteria and regulations.

The air monitoring network is estimated to include approximately 25 remote stations. Each remote will contain air pollution and meteorological sampling equipment and hardware to telemeter to a central station. The data will be transmitted over leased telephone lines. The central station in Harrisburg will contain the necessary hardware to receive and process data, calculate and display results and permit supervisory control of the network. Output options will include immediate display of edited data, command and alarm information, and presentation of statistical results.

Although the air monitoring system is one of the principle ingredients of the program, the air basin concept encompasses other component systems designed to knit together the entire air pollution control program in Pennsylvania.     

Particulate and Sulfur Dioxide Concentration Measurements in Patras,Greece

Abstract

The purpose of this study was to obtain a better assessment of the Patras, Greece, air quality, in terms of the primary pollutants total suspended particulates (TSPs) and sulfur dioxide (SO₂), because limited and short-duration measurements have been conducted in the past. Installation and operation of a mobile air monitoring station at two different locations in the Patras downtown area and one location in the outskirts of the city was undertaken and covered the periods July 1, 1994-January 30, 1995; March 18-August 23, 1995; and April 19-July 27, 1996, respectively. For both pollutants measured at each location, the monthly average concentrations and typical weekly variation of daily averages, as well as the diurnal variations and frequency concentration distributions in each month of the monitoring periods, were calculated and are presented in bar diagrams. The annual and winter period medians and the annual 98th percentile were also calculated and are compared with the limit and guide values provided by the European Economic Community Council Directive 80/779/EEC. In addition, comparison of SO₂ values is made with the limit values adopted by the more recent Directive 1999/30/EC. It was found that the TSP and SO₂ levels at all locations were very low and were lower than the levels found in Thessaloniki and Athens, Greece. An attempt to explain what had been measured is also undertaken. The data presented are considered essential for future reference and comparison purposes.     

Forecasts using neural network versus Box-Jenkins methodology for ambient air quality monitoring data

This study explores ambient air quality forecasts using the conventional time-series approach and a neural network. Sulfur dioxide and ozone monitoring data collected from two background stations and an industrial station are used. Various learning methods and varied numbers of hidden layer processing units of the neural network model are tested. Results obtained from the time-series and neural network models are discussed and compared on the basis of their performance for 1-step-ahead and 24-step-ahead forecasts. Although both models perform well for 1-step-ahead prediction, some neural network results reveal a slightly better forecast without manually adjusting model parameters, according to the results. For a 24-step-ahead forecast, most neural network results are as good as or superior to those of the time-series model. With the advantages of self-learning, self-adaptation, and parallel processing, the neural network approach is a promising technique for developing an automated short-term ambient air quality forecast system.     

环境空气质量自动监测站的管理与维护

随着工业化、城镇化的深入推进,二氧化硫、氮氧化物、烟粉尘和挥发性有机物等各类污染物排放到环境中,致使中国大气受到严重污染,给人体的健康、动植物的生长、发育和繁殖等带来负面的影响。为实时监测环境空气质量,建立环境空气质量自动监测站逐渐成为大气污染防治的主要手段。文中以环境空气质量自动监测站为研究对象,提出环境空气质量自动监测站管理与维护面临的问题,探讨相应的解决措施,以期为环境空气质量自动监测站的管理与维护提供参考依据。     

Design of Monitor Networks to Meet Multiple Criteria

For most monitoring networks, demonstration of compliance with ambient air quality standards is only one of many interrelated purposes served. The network also may be needed (1) to assess current air quality, (2) to assess regional background air quality, (3) to determine individual source “culpability,” (4) to validate or calibrate a particular dispersion model, (5) to assess effectiveness of a control strategy, or (6) to determine the risk of damage to certain critical or sensitive receptors. Monitoring to support compliance with Prevention of Significant Deterioration regulations is now also an important issue for many new sources. The same network may have to perform many of these functions for several pollutants that have different source locations and different characteristic averaging times. This paper presents a method for systematically addressing each of these concerns. The method includes use of a statistical computer model, MONITOR. This model provides quantitative estimates of relative probabilities in order to assess whether a particular network design will meet each of these criteria. A sample application of the method is provided.     

Regional Source Quantification model for sulphur oxides in Europe

An air quality model for estimation of emissions on a regional scale is developed. The model uses measured air concentrations and air trajectory transport calculations to determine the emissions. The optimal emission strength is obtained by a least square approximation between measured and estimated air concentrations of pollutants.The Regional Source Quantification (RSQ) model is used on the European Long-Range Transport data base for sulphur oxides collected by the Norwegian Institute for Air Research. The data base consists of about 60,000 SO₂ and SO₄ air quality samples and four times as many 48-h back trajectories. The estimated emission strengths based on about 7500 samples are shown to agree fairly well with the national emission strengths estimated previously from population and industrial density as well as consumption of fuel and raw materials. This is taken as a verification of the RSQ model.Use of the RSQ model in future studies for estimating emissions of other micropollutants is discussed. Optimal location of monitoring stations and emission fields as well as the duration of the study period are related to the standard deviations on the emission strengths.The RSQ model is used not only for emission estimation but also for estimation of optimal decay and oxidation parameters to be used in the air trajectory model. We find the decay parameter for SO₂ to be 1.3 × 10⁻⁵ s⁻¹, and for SO₄ to be 1.6 × 10⁻⁶ s⁻¹. The emission plus initial oxidation to SO₄ is found to contain about 12% of the total sulphur emission, while the succeeding oxidation defined in the air trajectory model is found to be insignificant.     

Assessing the representativeness of monitoring data from an urban intersection site in central London,UK

The wind flow field around urban street-building configurations has an important influence on the microscale pollutant dispersion from road traffic, affecting overall dilution and creating localised spatial variations of pollutant concentration. As a result, the “representativeness” of air quality measurements made at different urban monitoring sites can be strongly dependent on the interaction of the local wind flow field with the street-building geometry surrounding the monitor. The present study is an initial attempt to develop a method for appraising the significance of air quality measurements from urban monitoring sites, using a general application computational fluid dynamics (CFD) code to simulate small-scale flow and dispersion patterns around real urban building configurations. The main focus of the work was to evaluate routine CO monitoring data collected by Westminster City Council at an intersection of street canyons at Marylebone Road, Central London. Many monitors in the UK are purposely situated at urban canyon intersections, which are thought to be local “hot spots” of pollutant emissions, however very limited information exists in the literature on the flow and dispersion patterns associated with them. With the use of simple CFD simulations and the analysis of available monitoring data, it was possible to gain insights into the effect of wind direction on the small-scale dispersion patterns at the chosen intersection, and how that can influence the data captured by a monitor. It was found that a change in wind direction could result in an increase or decrease of monitored CO concentration of up to 80%, for a given level of traffic emissions and meteorological conditions. Understanding and de-coupling the local effect of wind direction from monitoring data using the methods presented in this work could prove a useful new tool for urban monitoring data interpretation.     

Development and implementation of a remote-sensing and in situ data-assimilating version of CMAQ for operational PM2.5 forecasting. Part 1: MODIS aerosol optical depth (AOD) data-assimilation design and testing

This two-part paper reports on the development, implementation, and improvement of a version of the Community Multi-Scale Air Quality (CMAQ) model that assimilates real-time remotely-sensed aerosol optical depth (AOD) information and ground-based PM_2.5 monitor data in routine prognostic application. The model is being used by operational air quality forecasters to help guide their daily issuance of state or local-agency-based air quality alerts (e.g. action days, health advisories). Part 1 describes the development and testing of the initial assimilation capability, which was implemented offline in partnership with NASA and the Visibility Improvement State and Tribal Association of the Southeast (VISTAS) Regional Planning Organization (RPO). In the initial effort, MODIS-derived aerosol optical depth (AOD) data are input into a variational data-assimilation scheme using both the traditional Dark Target and relatively new “Deep Blue” retrieval methods. Evaluation of the developmental offline version, reported in Part 1 here, showed sufficient promise to implement the capability within the online, prognostic operational model described in Part 2. In Part 2, the addition of real-time surface PM_2.5 monitoring data to improve the assimilation and an initial evaluation of the prognostic modeling system across the continental United States (CONUS) is presented.

Implications: Air quality forecasts are now routinely used to understand when air pollution may reach unhealthy levels. For the first time, an operational air quality forecast model that includes the assimilation of remotely-sensed aerosol optical depth and ground based PM_2.5 observations is being used. The assimilation enables quantifiable improvements in model forecast skill, which improves confidence in the accuracy of the officially-issued forecasts. This helps air quality stakeholders be more effective in taking mitigating actions (reducing power consumption, ride-sharing, etc.) and avoiding exposures that could otherwise result in more serious air quality episodes or more deleterious health effects.     

Lagrangian dispersion modeling of vehicular emissions from a highway in complex terrain

Transit traffic through the Austrian Alps is of major concern in government policy. Pollutant burdens resulting from such traffic are discussed widely in Austrian politics and have already led to measures to restrict traffic on transit routes. In the course of an environmental assessment study, comprehensive measurements were performed. These included air quality observations using passive samplers, a differential optical absorption spectroscopy system, a mobile and a fixed air quality monitoring station, and meteorological observations. As was evident from several previous studies, dispersion modeling in such areas of complex terrain and, moreover, with frequent calm wind conditions, is difficult to handle. Further, in the case presented here, different pollutant sources had to be treated simultaneously (e.g., road networks, exhaust chimneys from road tunnels, and road tunnel portals). No appropriate system for modeling all these factors has so far appeared in the literature. A prognostic wind field model coupled with a Lagrangian dispersion model is thus presented here and is designed to treat all these factors. A comparison of the modeling system with results from passive samplers and from a fixed air quality monitoring station proved the ability of the model to provide reasonable figures for concentration distributions along the A10.     

Predictions of U.K. regulated power station contributions to regional air pollution and deposition: a model comparison exercise

Contributions of the emissions from a U.K. regulated fossil-fuel power station to regional air pollution and deposition are estimated using four air quality modeling systems for the year 2003. The modeling systems vary in complexity and emphasis in the way they treat atmospheric and chemical processes, and include the Community Multiscale Air Quality (CMAQ) modeling system in its versions 4.6 and 4.7, a nested modeling system that combines long- and short-range impacts (referred to as TRACK-ADMS [Trajectory Model with Atmospheric Chemical Kinetics-Atmospheric Dispersion Modelling System]), and the Fine Resolution Atmospheric Multi-pollutant Exchange (FRAME) model. An evaluation of the baseline calculations against U.K. monitoring network data is performed. The CMAQ modeling system version 4.6 data set is selected as the reference data set for the model footprint comparison. The annual mean air concentration and total deposition footprints are summarized for each modeling system. The footprints of the power station emissions can account for a significant fraction of the local impacts for some species (e.g., more than 50% for SO2 air concentration and non-sea-salt sulfur deposition close to the source) for 2003. The spatial correlation and the coefficient of variation of the root mean square error (CVRMSE) are calculated between each model footprint and that calculated by the CMAQ modeling system version 4.6. The correlation coefficient quantifies model agreement in terms of spatial patterns, and the CVRMSE measures the magnitude of the difference between model footprints. Possible reasons for the differences between model results are discussed. Finally, implications and recommendations for the regulatory assessment of the impact of major industrial sources using regional air quality modeling systems are discussed in the light of results from this case study.