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.     

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.     

The impacts of combustion emissions on air quality and climate – From coal to biofuels and beyond

Combustion processes have inherent characteristics that lead to the release in the environment of both gaseous and particulate pollutants that have primary and secondary impacts on air quality, human health, and climate. The emissions from the combustion of fossil fuels and biofuels and their atmospheric impacts are reviewed here with attention given to the emissions of the currently regulated pollutant gasses, primary aerosols, and secondary aerosol precursors as well as the emissions of non-regulated pollutants. Fuels ranging from coal, petroleum, liquefied petroleum gas (LPG), natural gas, as well as the biofuels; ethanol, methanol, methyl tertiary-butyl ether (MTBE), ethyl tertiary-butyl ether (ETBE), and biodiesel, are discussed in terms of the known air quality and climate impacts of the currently regulated pollutants. The potential importance of the non-regulated emissions of both gasses and aerosols in air quality issues and climate is also discussed with principal focus on aldehydes and other oxygenated organics, polycyclic aromatic hydrocarbons (PAHs), and nitrated organics. The connection between air quality and climate change is also addressed with attention given to ozone and aerosols as potentially important greenhouse species.     

Methodologies for incorporation of synergistic effects in the calculation of the Pollutant Standards Index

The United States Environmental Protection Agency (EPA) developed the Pollutant Standards Index (PSI) in order to provide the public with an overall assessment of daily air quality. PSI values are determined from measured concentrations of five criteria air pollutants carbon monoxide, nitrogen dioxide, ozone, sulfur dioxide, and particulate matter (PM-10). In general, the PSI can be considered a useful tool in the assessment of air quality as it relates to health effects. However, the current method of PSI calculation is subject to certain inherent limitations. These limitations include the fact that the PSI neglects the role of synergism between the individual pollutants in affecting air quality and health. It is very likely that the combination of certain pollutants is more harmful than each acting individually. Since the general population is exposed to more than one of the criteria pollutants at a given time, revising the current PSI methodology to account for such synergism would be useful and helpful to the public. In the current work, two methodologies for synergistic PSI calculation have been evaluated. The first option (Option 1) is dominated by the principle of threshold levels. When further research determines more accurate levels, the methodology may be of value for future synergistic PSI evaluations. The second option (Option 2) is an attempt to incorporate the correlation of pollutant concentrations with health effects (as determined by increased hospital admissions) into the synergism evaluation. The underlying philosophy of this methodology holds the most promise for accurate synergistic PSI calculation. Comprehensive research and experimentation would be beneficial in creating a more accurate PSI function equation. The main advantage of these hypothetical methodologies is that the current PSI method would still be valid for initial PSI calculation. The dissimilarity is in the calculation of the critical (i.e. reportable) PSI value. It is no longer a matter of the highest PSI value among the pollutants being an accurate representative of air quality. Instead, each of the PSI values obtained is applied to a separate equation to determine a synergistic PSI. When above-average pollutant concentrations are recorded, the possibility of synergistic behavior increases and would be demonstrated with the application of both options. The advantage of Option 1 (versus Option 2) is that the equation was derived from a recognized approach to synergism in combination with the ideas of threshold levels. The advantage of Option 2 is that it is an attempt to correlate concentration levels with health effects observed in the health industry. It is possible that a combination of both philosophies will eventually lead to the development of a synergistic PSI methodology worthy of approval by the EPA.     

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.’     

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.     

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.     

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.     

Application of satellite remote-sensing data for source analysis of fine particulate matter transport events

Satellite sensors have provided new datasets for monitoring regional and urban air quality. Satellite sensors provide comprehensive geospatial information on air quality with both qualitative imagery and quantitative data, such as aerosol optical depth. Yet there has been limited application of these new datasets in the study of air pollutant sources relevant to public policy. One promising approach to more directly link satellite sensor data to air quality policy is to integrate satellite sensor data with air quality parameters and models. This paper presents a visualization technique to integrate satellite sensor data, ground-based data, and back trajectory analysis relevant to a new rule concerning the transport of particulate matter across state boundaries. Overlaying satellite aerosol optical depth data and back trajectories in the days leading up to a known fine particulate matter with an aerodynamic diameter of <2.5 microm (PM2.5) event may indicate whether transport or local sources appear to be most responsible for high PM2.5 levels in a certain location at a certain time. Events in five cities in the United States are presented as case studies. This type of analysis can be used to help understand the source locations of pollutants during specific events and to support regulatory compliance decisions in cases of long distance transport.     

Multiple regression analysis in modeling of columnar ozone in Peninsular Malaysia

This study aimed to predict monthly columnar ozone (O₃) in Peninsular Malaysia by using data on the concentration of environmental pollutants. Data (2003–2008) on five atmospheric pollutant gases (CO₂, O₃, CH₄, NO₂, and H₂O vapor) retrieved from the satellite Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) were employed to develop a model that predicts columnar ozone through multiple linear regression. In the entire period, the pollutants were highly correlated (R?=?0.811 for the southwest monsoon, R?=?0.803 for the northeast monsoon) with predicted columnar ozone. The results of the validation of columnar ozone with column ozone from SCIAMACHY showed a high correlation coefficient (R?=?0.752–0.802), indicating the model’s accuracy and efficiency. Statistical analysis was utilized to determine the effects of each atmospheric pollutant on columnar ozone. A model that can retrieve columnar ozone in Peninsular Malaysia was developed to provide air quality information. These results are encouraging and accurate and can be used in early warning of the population to comply with air quality standards.     

Daily variation in the properties of urban ultrafine aerosol—Part I: Physical characterization and volatility

A summer air quality monitoring campaign focusing on the evolution of ultrafine (<180 nm in diameter) particle concentrations was conducted at an urban site in Los Angeles during June–July 2006. Previous observations suggest that ultrafine aerosol at this site are generally representative of the Los Angeles urban environment. Continuous and intermittent gas and aerosol measurements were made over 4 weeks with consistent daily meteorological conditions. Monthly averages of the data suggest the strong influence of commute traffic emissions on morning observations of ultrafine particle concentrations. By contrast, in the afternoon our measurements provide evidence of secondary photochemical reactions becoming the predominant formation mechanism of ultrafine aerosols. The ultrafine number concentration peak occurs in the early afternoon, before the maximum ozone concentration is observed. The source of this offset is unknown and requires further investigation. It is possible that the chemical mechanisms responsible for secondary organic aerosol formation evolve as atmospheric conditions change and/or secondary semi-volatile components of the aerosol re-volatilize due to the elevated peak temperatures observed (ca. 30–35 °C) combined with the increased atmospheric dilution during that time. Measurements of the volatility of the ultrafine aerosol are consistent with this interpretation as overall volatility increases in the afternoon and there is less evidence of external mixing. Composition data presented in the companion paper support these conclusions [Ning et al., 2007. Daily variation in chemical characteristics of urban ultrafine aerosols and inference of their sources. Environmental Science and Technology, in press].     

Analysis of Toxic Air Contaminant Data Containing Concentrations Below the Limit of Detection

Air quality data often contain several observations reported only as below the analytical limit of detection (LOD), resulting in “censored” data sets. Such censored and/or truncated data sets tend to complicate statistical analysis. This paper discusses various procedures for estimating mean concentration and Its 95 percent confidence bounds from air contaminant data sets which contain values that are reported as below the LOD, A quantitative approach for assessing the uncertainty Inherent In the estimated mean concentration due to (a) presence of values below the LOD In the data set, and (b) natural variability of atmospheric concentration data, is described. The utility of this approach In the analysis and interpretation of ambient pollutant concentration data Is demonstrated for both hypothetical and observed singly-censored data sets, and for a multiply-censored, multi-pollutant observed concentration data set. The methodologies discussed here should be particularly useful In verifying compliance with environmental regulations, and In estimating the risks associated with long-term exposure of populations to toxic air contaminants and assessing the uncertainty associated with these estimates.     

The Optical Evaluation of Smoke or Participate Matter Collected on Filter Paper

Many food, fiber, forage, and forest crops and a number of animals are adversely affected by a variety of air pollutants. The more important and generally occurring of these pollutants are ethylene, fluorides, ozone, peroxyacyl nitrates (PAN), and sulfur oxides. Their effects upon animals and plants can best be judged by criteria which describe the reaction of biologic materials to pollutant concentration and exposure time. Four criteria are recognized: (1) interference with enzyme systems; (2) change in cellular chemical constituents and physical structure; (3) retardation of growth and reduction in production from altered metabolism; and (4) acute immediate tissue degeneration. Information on tissue degenerative effects due to these pollutants is the most common; there are some reports on growth and productivity reduction; but little data are available on cellular alterations and interference with enzymes. Determination and measurement of the latter two criteria are essential to the ultimate definition and prediction of the significance of the effects of pollutants on growth and productivity of agriculture. Dosage data are available which indicate the degenerative effects of some specific pollutants on certain tissues of hosts. Political-social judgments can be made because of the knowledge of the effects of these specific pollutants; this knowledge thus permits the establishment of standards which define air quality necessary for the protection of agriculture. The importance of combined pollutant effects mitigates against the ready setting of standards on an airshed or significant regional basis. The setting of standards for a single polluiant effects upon crops and animals effectively serves as a precedent and indicates the necessity of establishing air quality values for pollutant mixtures emitted into and produced within the air resource at different geographic locations as the polluted air moves throughout the typically multigovernment jurisdictions of the airsheds.     

La chimie du plomb et du brome particulaire en atmosphere urbaine: I — Situation moyenne

Lead and Bromine aerosols are mainly abundant in the fine size fraction of atmospheric aerosol in Paris. Their time dependance concentration in relation with air trajectories at 850 mb can be explained if a mainly automotive contribution is assumed.Bromine to lead ratio is used to estimate the relative contribution of this important pollutant source.     

Application of Satellite Remote-Sensing Data for Source Analysis of Fine Particulate Matter Transport Events

Abstract

Satellite sensors have provided new datasets for monitoring regional and urban air quality. Satellite sensors provide comprehensive geospatial information on air quality with both qualitative imagery and quantitative data, such as aerosol optical depth. Yet there has been limited application of these new datasets in the study of air pollutant sources relevant to public policy. One promising approach to more directly link satellite sensor data to air quality policy is to integrate satellite sensor data with air quality parameters and models. This paper presents a visualization technique to integrate satellite sensor data, ground-based data, and back trajectory analysis relevant to a new rule concerning the transport of particulate matter across state boundaries. Overlaying satellite aerosol optical depth data and back trajectories in the days leading up to a known fine particulate matter with an aerodynamic diameter of <2.5 μm (PM_2.5) event may indicate whether transport or local sources appear to be most responsible for high PM_2.5 levels in a certain location at a certain time. Events in five cities in the United States are presented as case studies. This type of analysis can be used to help understand the source locations of pollutants during specific events and to support regulatory compliance decisions in cases of long distance transport.     

An Air Quality Data Analysis System for Interrelating Effects,Standards, and Needed Source Reductions: Part 3. Vegetation Injury

Acute leaf injury data are analyzed for 19 plant species exposed to ozone or sulfur dioxide. The data can be depicted by a new leaf injury mathematical model with two characteristics: (1) a constant percentage of leaf surface is injured by an air pollutant concentration that is inversely proportional to exposure duration raised to an exponent; (2) for a given exposure duration, the percent leaf injury as a function of pollutant concentration tends to fit a lognormal frequency distribution. Leaf injury as a function of laboratory exposure duration is modeled and compared with ambient air pollutant concentration measurements for various averaging times to determine which exposure durations are probably most important for setting ambient air quality standards to prevent or reduce visible leaf injury. The 8 hour average appears to be most important for most of the plants investigated for most sites, 1 hr concentrations are important for most plants at a few sites, and 3 hr S0₂ concentrations are important for some plants, especially those exposed to isolated point sources of the pollutant. The 1, 3, and 8 hr threshold injury concentrations are listed for each of the 19 plant species studied. To prevent or reduce acute leaf injury, fixed, nonoverlapping ambient air quality measurements and standards are recommended for averaging times of 1, 3, and 8hr.     

Patterns and concentrations of PM10 in a mountainous basin region

In this study, continuous data of PM10 (particles with aerodynamic diameter < 10 microns) concentration measurements for a 4-yr period were analyzed. These measurements have been carried out in the Eordea Basin, an industrial area in the northwestern mountainous region of Greece. The annual, monthly, and diurnal patterns are presented and investigated regarding the prevailing meteorological conditions and atmospheric processes that affect the ambient concentrations of PM10. The effect of wind on controlling PM10 concentration is also discussed. Based on the data analysis, an attempt is made to provide useful information about air quality levels, taking into account U.S. Environmental Protection Agency air quality standards.     

Traffic and Meteorological Impacts on Near-Road Air Quality: Summary of Methods and Trends from the Raleigh Near-Road Study

Abstract

A growing number of epidemiological studies conducted worldwide suggest an increase in the occurrence of adverse health effects in populations living, working, or going to school near major roadways. A study was designed to assess traffic emissions impacts on air quality and particle toxicity near a heavily traveled highway. In an attempt to describe the complex mixture of pollutants and atmospheric transport mechanisms affecting pollutant dispersion in this near-highway environment, several real-time and time-integrated sampling devices measured air quality concentrations at multiple distances and heights from the road. Pollutants analyzed included U.S. Environmental Protection Agency (EPA)-regulated gases, particulate matter (coarse, fine, and ultrafine), and air toxics. Pollutant measurements were synchronized with real-time traffic and meteorological monitoring devices to provide continuous and integrated assessments of the variation of near-road air pollutant concentrations and particle toxicity with changing traffic and environmental conditions, as well as distance from the road. Measurement results demonstrated the temporal and spatial impact of traffic emissions on near-road air quality. The distribution of mobile source emitted gas and particulate pollutants under all wind and traffic conditions indicated a higher proportion of elevated concentrations near the road, suggesting elevated exposures for populations spending significant amounts of time in this microenvironment. Diurnal variations in pollutant concentrations also demonstrated the impact of traffic activity and meteorology on near-road air quality. Time-resolved measurements of multiple pollutants demonstrated that traffic emissions produced a complex mixture of criteria and air toxic pollutants in this microenvironment. These results provide a foundation for future assessments of these data to identify the relationship of traffic activity and meteorology on air quality concentrations and population exposures.     

Traffic and meteorological impacts on near-road air quality: summary of methods and trends from the Raleigh Near-Road Study

A growing number of epidemiological studies conducted worldwide suggest an increase in the occurrence of adverse health effects in populations living, working, or going to school near major roadways. A study was designed to assess traffic emissions impacts on air quality and particle toxicity near a heavily traveled highway. In an attempt to describe the complex mixture of pollutants and atmospheric transport mechanisms affecting pollutant dispersion in this near-highway environment, several real-time and time-integrated sampling devices measured air quality concentrations at multiple distances and heights from the road. Pollutants analyzed included U.S. Environmental Protection Agency (EPA)-regulated gases, particulate matter (coarse, fine, and ultrafine), and air toxics. Pollutant measurements were synchronized with real-time traffic and meteorological monitoring devices to provide continuous and integrated assessments of the variation of near-road air pollutant concentrations and particle toxicity with changing traffic and environmental conditions, as well as distance from the road. Measurement results demonstrated the temporal and spatial impact of traffic emissions on near-road air quality. The distribution of mobile source emitted gas and particulate pollutants under all wind and traffic conditions indicated a higher proportion of elevated concentrations near the road, suggesting elevated exposures for populations spending significant amounts of time in this microenvironment. Diurnal variations in pollutant concentrations also demonstrated the impact of traffic activity and meteorology on near-road air quality. Time-resolved measurements of multiple pollutants demonstrated that traffic emissions produced a complex mixture of criteria and air toxic pollutants in this microenvironment. These results provide a foundation for future assessments of these data to identify the relationship of traffic activity and meteorology on air quality concentrations and population exposures.     

A methodology to urban air quality assessment during large time periods of winter using computational fluid dynamic models

The representativeness of point measurements in urban areas is limited due to the strong heterogeneity of the atmospheric flows in cities. To get information on air quality in the gaps between measurement points, and have a 3D field of pollutant concentration, Computational Fluid Dynamic (CFD) models can be used. However, unsteady simulations during time periods of the order of months, often required for regulatory purposes, are not possible for computational reasons. The main objective of this study is to develop a methodology to evaluate the air quality in a real urban area during large time periods by means of steady CFD simulations. One steady simulation for each inlet wind direction was performed and factors like the number of cars inside each street, the length of streets and the wind speed and direction were taken into account to compute the pollutant concentration. This approach is only valid in winter time when the pollutant concentrations are less affected by atmospheric chemistry. A model based on the steady-state Reynolds-Averaged Navier–Stokes equations (RANS) and standard k-? turbulence model was used to simulate a set of 16 different inlet wind directions over a real urban area (downtown Pamplona, Spain). The temporal series of NO_x and PM₁₀ and the spatial differences in pollutant concentration of NO₂ and BTEX obtained were in agreement with experimental data. Inside urban canopy, an important influence of urban boundary layer dynamics on the pollutant concentration patterns was observed. Large concentration differences between different zones of the same square were found. This showed that concentration levels measured by an automatic monitoring station depend on its location in the street or square, and a modelling methodology like this is useful to complement the experimental information. On the other hand, this methodology can also be applied to evaluate abatement strategies by redistributing traffic emissions.