Air Quality in the 21st Century.

By: Romano, Gaia CContributor(s): Conti, Alice GPublisher: New York : Nova Science Publishers, Incorporated, 2008Copyright date: ©2010Description: 1 online resource (408 pages)Content type: text Media type: computer Carrier type: online resourceISBN: 9781617613906Subject(s): Air quality management.;Air pollutionGenre/Form: Electronic books. Additional physical formats: Print version:: Air Quality in the 21st CenturyDDC classification: 628.5/3 LOC classification: TD883 -- .A5766 2010ebOnline resources: Click to View
Contents:
Intro -- AIR QUALITY IN THE 21ST CENTURY -- CONTENTS -- PREFACE -- PARAMETERS CONTROLLING AMBIENT AIRBENZENE CONCENTRATIONS AND HUMANEXPOSURE IN A MEDIUM SIZED SOUTHEASTERNEUROPEAN CITY -- ABSTRACT -- 1. INTRODUCTION -- 2. MATERIALS AND METHODS -- 2.1. General Information -- 2.2. Measurements Campaign Design -- 2.2.1. Ambient air Measurements -- 2.2.2. Personal Exposure Measurements -- 2.3. Instruments and Apparatus -- 2.4. Quality Assurance and Quality Control -- 3. AMBIENT AIR CONCENTRATIONS -- 3.1. Environmental Data -- 3.1.1 Traffic Data -- 3.1.2. Meteorological Data -- 3.1.3. Urban Ambient Air Benzene Concentrations -- 3.2. Parameters Rising Ambient air Benzene Levels in Local Scale -- 3.2.1. Traffic Density -- 3.2.1.1. General Information -- 3.2.1.2. Data -- 3.2.1.3. Modelling Techniques -- 3.2.1.3.1. DET Model -- 3.2.1.3.2. ANN Model -- 3.2.1.4. Models Evaluation and Discussion -- 3.2.2. Street Canyon Effect -- 3.2.3. Filling Station Proximity -- 3.2.3.1. General Information -- 3.2.3.2. Measurements Results -- 3.2.3.2.1. Passive Sampling Results -- 3.2.3.2.2. Active Sampling Results -- 3.2.3.2.3. Traffic Data -- 3.2.3.2.4. Meteorological Data -- 3.2.3.3. Interpretation Using Models -- 3.2.3.3.1. Model Formulations -- 3.2.3.3.2. Evaluation and Optimization of CALINE 4 -- 3.2.3.4. Contribution of Filling Stations to the Observed Benzene Concentrations -- 4. PERSONAL EXPOSURE RESULTS -- 4.1. General -- 4.2. Control Group -- 4.3. Policemen -- 4.4. Filling Station Employees -- 4.4.1. Introduction -- 4.4.2. Methodology -- 4.4.3. Artificial Neural Network (ANN) Modeling Development -- 4.4.4. Measurements Results -- 4.4.4.1. Environmental Data-Amount of Gasoline Traded -- 4.4.4.2. Personal Exposure Results -- 4.4.5. Artificial Neural Network Modelling Results -- 4.4.6. Relative Importance of the Parameters Constituting the Exposure Pattern.
4.5. Taxi Drivers -- 4.6. Active Sampling Personal Exposure -- 5. CANCER RISK ASSESSMENT -- 6. THE EFFECT OF CHANGES IN TRAFFIC FLOW PATTERNS ONEMISSIONS BY THE MEANS OF ENVIRONMENTAL POLICY -- 7. CONCLUSIONS -- 8. REFERENCES -- METEOROLOGICAL ASPECTS OF AIR QUALITY -- ABSTRACT -- 1. INTRODUCTION -- 2. THE ATMOSPHERIC BOUNDARY LAYER -- 3. MESOSCALE MODELS FOR AIR QUALITY FORECASTS -- 3.1. Case Study and Model Set up -- 3.2. Results -- 4. DIFFICULTIES OF THE STABLE BOUNDARY LAYER -- -Turbulence -- -Longwave Radiative Transfer -- -Soil And Vegetation -- -Elevated Nighttime Wind Maximum -- -Gravity Waves -- - Interactions -- 5. DISPERSION AND MEANDERING IN STABLE BOUNDARY LAYERS -- 5.2. Intermittency in Stable Boundary Layers -- A) Single Station Observations: The Wageningen Field -- B) Spatial Development -- C) Wavelet Analysis -- D) A Climatology of Intermittency of Nighttime Turbulence. -- 6. THE STABLE BOUNDARY-LAYER HEIGHT -- 6.1. Background -- 6.2. Observations -- a) CASES-99 -- b) Sodankylä -- c)Cabauw -- d)SHEBA -- e) SABLES98 -- 6.3. USING DIMENSIONAL ANALYSIS FOR DERIVATION AN EQUATIONFOR THE STABLE BOUNDARY LAYER HEIGHT -- A) Three Dimensionless Groups -- b) Verification -- C) On the Relevance of the Coriolis Parameter F: Two Dimensionless Groups Only -- 6.4. An Alternative Theoretically Based Formulation for the StableBoundary Layer Height -- 6.4.1. Background -- 6.4.3. Results -- 6.5. CONCLUSIONS -- 7. CLOSURE -- ACKNOWLEDGEMENTS -- REFERENCES -- A QUANTITATIVE COMPARISON OF ANGSTROM'STURBIDITY PARAMETERS (α,β) RETRIEVED INDIFFERENT SPECTRAL RANGES BASED ONSPECTRAL SOLAR EXTINCTION MEASUREMENTS -- ABSTRACT -- INTRODUCTION -- EXPERIMENTAL MEASUREMENTS -- THEORETICAL BACKGROUND AND METHODOLOGY -- Definitions -- The Angstrom Parameters -- RESULTS -- Comparisons of Angstrom α Values -- Comparisons of Angstrom β Values -- CONCLUSION.
REVIEWED BY -- REFERENCES -- SIMULTANEOUS EVALUATION OF ODOR EPISODESAND AIR QUALITY. METHODOLOGY TO IDENTIFYAIR POLLUTANTS AND THEIR ORIGIN COMBININGCHEMICAL ANALYSIS (TD-GC/MS),SOCIAL PARTICIPATION, ANDMATHEMATICAL SIMULATIONS TECHNIQUES -- ABSTRACT -- 1. INTRODUCTION -- 2. ODOR IMPACT AND AIR QUALITY ASSESSMENT ANDMANAGEMENT FOR URBAN AREAS -- 3. METEOROLOGICAL ANALYSIS -- 4. SOCIAL PARTICIPATION -- 4.1. Model of Social Participation for Controlling Odor Episodes and AirQuality: Identifying Chemical Compounds and their Sources -- 4.1.1. Participation Levels -- 4.1.1.1. Sensory and Occurrence Data -- 4.1.2. Annoyance Level Evaluation -- 5. IMPACT MAPS -- 6. CHEMICAL CONTROL -- 6.1. Air Sampler Development -- 6.2. Analytical Methodology -- 6.2.1. Multi-sorbent Tubes -- 6.2.2. Analytical Instrumentation -- 6.3. Concentration Maps -- 6.4. Odor Maps -- 6.5. Air Quality Determination -- 6.5.1. Outdoor Air -- 6.5.2. Indoor Air -- 6.6. Identification of Recently Identified Pollutants and UnderstudiedCompounds -- 7. CASE STUDIES -- 7.1. Back-Trajectory Application -- 7.2. Application of Integrated Methodology (Social Participation, ChemicalControl and Numerical Modeling) -- 7.2.1. Description of the Study Area -- 7.2.2. Meteorological Analysis -- 7.2.3. Impact Maps -- 7.2.4. Social Control (Social Participation) -- 7.2.5. Chemical Control -- 7.2.5.1. Qualitative VOC Determination -- 7.2.5.2. Quantitative VOC Determination -- 7.2.5.3. Concentration Maps -- 8. CONCLUSIONS -- REFERENCES -- LICHEN BIOMONITORING OF AIR POLLUTION:ISSUES FOR APPLICATIONSIN COMPLEX ENVIRONMENTS -- ABSTRACT -- INTRODUCTION -- LICHEN DIVERSITY VALUE (LDV) METHOD -- MONITORING IN A VARIABLE ENVIRONMENT -- OBJECTIVE AND APPROACH -- WORKED EXAMPLE I. POLLUTION-RELATED SIGNAL ANDCLIMATE-RELATED NOISE IN LICHEN BIOMONITORING ATREGIONAL SCALE: A CASE-STUDY FROM LIGURIA (NW ITALY).
MATERIALS AND METHODS -- Sampling Design -- Lichen Sampling -- Data Analysis -- RESULTS -- DISCUSSION -- i) To Define Homogeneous Bioclimatic Regions -- ii) To Identify the Influence of Each Atmospheric Pollutant for EachBioclimatic Region and to Analyse Trends of Biodiversity Indices -- iii) To Elaborate Proper Scales for Interpreting lichen Biomonitoring Data -- WORKED EXAMPLE II. BIOMONITORING OF AIR POLLUTION INFOREST ECOSYSTEMS: PROBLEMS AND PERSPECTIVES -- MATERIALS AND METHODS -- The Study in Tuscany -- The Study in Liguria -- RESULTS -- Casentino National Park -- Liguria -- DISCUSSION -- Casentino National Park -- Liguria -- WORKED EXAMPLE III. NON POLLUTION-RELATED NOISE INLICHEN BIOMONITORING AT WITHIN-SITE SCALE:A CASE STUDY FROM ITALIAN-SLOVENIAN BORDERLINE -- MATERIALS AND METHODS -- Survey Area -- Sampling Strategy -- Non-pollution Related Factors -- Data Analysis -- RESULTS -- Local Epiphytic Vegetation -- Lichen Diversity Variability at within-Plot Scale -- LDV Variability and Non Pollution-related Factors -- DISCUSSION -- LDV variability at within- and between-sites scale: pollution and nonpollution-related predictors -- GENERAL CONCLUSIONS -- REFERENCES -- HYDROCARBON CONTAMINATION ANDENVIRONMENTAL HEALTH QUALITY: AN OVERVIEW -- ABSTRACT -- INTRODUCTION -- CONCEPT OF ENVIRONMENTAL QUALITY -- Definition of the Environment -- Major Components of the Environment -- 1. Soil -- 2. Water -- 3. Atmosphere -- Environmental Impact Assessment -- CONCEPT OF HYDROCARBONS -- PRIMARY SOURCES OF HYDROCARBON CONTAMINANTS ANDENVIRONMENTAL/HEALTH IMPACT -- Crude Oils -- Oil Spill -- Natural Gas -- Gas Flaring -- Produced Water -- Lubricating Oils -- Coal -- SECONDARY SOURCES OF HYDROCARBON CONTAMINANTS ANDENVIRONMENTAL / HEALTH IMPACT -- Oil Refinery -- Petrochemicals / Petrochemical Plants -- Flue Gases / Vehicle Emissions -- i) Carbon Monoxide (CO).
ii) Sulfur Dioxide (SO2) -- iii) Oxides of Nitrogen -- Leaded Gasoline -- Trace Heavy Metals -- Biological Decay of Sewage and Refuse -- Odors -- Biomass / Wood Fuels -- Spent Oil-based Drilling Fluid and Oily Drill Cuttings -- The Greenhouse Gases and Global Warming -- OTHER MINOR SOURCES OF HYDROCARBON CONTAMINATION -- Natural Seeps and Organic Matter -- Shale Oil and Condensates -- CONCLUSION AND RECOMMENDATIONS -- REFERENCES -- BIVARIATE STOCHASTIC VOLATILITY MODELSAPPLIED TO MEXICO CITY OZONE POLLUTIONDATA -- Abstract -- 1. Introduction -- 2. Bivariate Stochastic Volatility Models (BSV) -- 2.1. Model I -- 2.2. Model II -- 2.3. Model III -- 2.4. Model IV -- 2.5. Model V -- 2.6. Model VI -- 3. Bayesian Analysis -- 3.1. Class I -- 3.2. Class II -- 3.3. Class III -- 4. Model Selection -- 5. An Application to theWeekly Ozone Averages in Mexico City -- 5.1. Description of the Data -- 5.2. Application of the Models and Results -- 5.2.1. Model I -- 5.2.2. Model II -- 5.2.3. Model III -- 5.2.4. Model IV -- 5.2.5. Model V -- 5.2.6. Model VI -- 5.2.7. Model Selection -- 6. Conclusion -- Acknowledgements -- References -- OPTIMIZATION APPROACHES FOR AIR QUALITYMONITORING NETWORK DESIGN -- ABSTRACT -- INTRODUCTION -- AQMN-RESULTS -- AIR QUALITY MONITORING SITING CRITERION -- METHODOLOGY DESCRIPTION -- 1. Representation of Spatial-Temporal Patterns -- 2. Detection of Violations over Ambient Standards -- UTILITY FUNCTION APPROACH -- 1. Structure of the Utility Function -- 2. Computational Algorithm of the Utility Function Based on SinglePollutant -- 3. Computational Algorithm of the Utility Function Based on MultiPollutants Network Design -- CASE STUDY -- STUDY AREA OPTIMIZATION MODELING RESULTS DISCUSSION -- 1. Single Pollutant Monitoring Network Optimization Modeling Results -- 2. Multi-Pollutant Monitoring Network Optimization Modeling Results -- REFERENCES.
SENSITIVITY OF LAND USE PARAMETERS ANDPOPULATION ON THE PREDICTION OFCONCENTRATION USINGTHE AERMOD MODEL FOR AN URBAN AREA.
Summary: This book presents the latest research on the crucial issues and the standards necessary to assess, monitor and increase air quality.Particular emphasis is paid to problems related to urban air quality.
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Intro -- AIR QUALITY IN THE 21ST CENTURY -- CONTENTS -- PREFACE -- PARAMETERS CONTROLLING AMBIENT AIRBENZENE CONCENTRATIONS AND HUMANEXPOSURE IN A MEDIUM SIZED SOUTHEASTERNEUROPEAN CITY -- ABSTRACT -- 1. INTRODUCTION -- 2. MATERIALS AND METHODS -- 2.1. General Information -- 2.2. Measurements Campaign Design -- 2.2.1. Ambient air Measurements -- 2.2.2. Personal Exposure Measurements -- 2.3. Instruments and Apparatus -- 2.4. Quality Assurance and Quality Control -- 3. AMBIENT AIR CONCENTRATIONS -- 3.1. Environmental Data -- 3.1.1 Traffic Data -- 3.1.2. Meteorological Data -- 3.1.3. Urban Ambient Air Benzene Concentrations -- 3.2. Parameters Rising Ambient air Benzene Levels in Local Scale -- 3.2.1. Traffic Density -- 3.2.1.1. General Information -- 3.2.1.2. Data -- 3.2.1.3. Modelling Techniques -- 3.2.1.3.1. DET Model -- 3.2.1.3.2. ANN Model -- 3.2.1.4. Models Evaluation and Discussion -- 3.2.2. Street Canyon Effect -- 3.2.3. Filling Station Proximity -- 3.2.3.1. General Information -- 3.2.3.2. Measurements Results -- 3.2.3.2.1. Passive Sampling Results -- 3.2.3.2.2. Active Sampling Results -- 3.2.3.2.3. Traffic Data -- 3.2.3.2.4. Meteorological Data -- 3.2.3.3. Interpretation Using Models -- 3.2.3.3.1. Model Formulations -- 3.2.3.3.2. Evaluation and Optimization of CALINE 4 -- 3.2.3.4. Contribution of Filling Stations to the Observed Benzene Concentrations -- 4. PERSONAL EXPOSURE RESULTS -- 4.1. General -- 4.2. Control Group -- 4.3. Policemen -- 4.4. Filling Station Employees -- 4.4.1. Introduction -- 4.4.2. Methodology -- 4.4.3. Artificial Neural Network (ANN) Modeling Development -- 4.4.4. Measurements Results -- 4.4.4.1. Environmental Data-Amount of Gasoline Traded -- 4.4.4.2. Personal Exposure Results -- 4.4.5. Artificial Neural Network Modelling Results -- 4.4.6. Relative Importance of the Parameters Constituting the Exposure Pattern.

4.5. Taxi Drivers -- 4.6. Active Sampling Personal Exposure -- 5. CANCER RISK ASSESSMENT -- 6. THE EFFECT OF CHANGES IN TRAFFIC FLOW PATTERNS ONEMISSIONS BY THE MEANS OF ENVIRONMENTAL POLICY -- 7. CONCLUSIONS -- 8. REFERENCES -- METEOROLOGICAL ASPECTS OF AIR QUALITY -- ABSTRACT -- 1. INTRODUCTION -- 2. THE ATMOSPHERIC BOUNDARY LAYER -- 3. MESOSCALE MODELS FOR AIR QUALITY FORECASTS -- 3.1. Case Study and Model Set up -- 3.2. Results -- 4. DIFFICULTIES OF THE STABLE BOUNDARY LAYER -- -Turbulence -- -Longwave Radiative Transfer -- -Soil And Vegetation -- -Elevated Nighttime Wind Maximum -- -Gravity Waves -- - Interactions -- 5. DISPERSION AND MEANDERING IN STABLE BOUNDARY LAYERS -- 5.2. Intermittency in Stable Boundary Layers -- A) Single Station Observations: The Wageningen Field -- B) Spatial Development -- C) Wavelet Analysis -- D) A Climatology of Intermittency of Nighttime Turbulence. -- 6. THE STABLE BOUNDARY-LAYER HEIGHT -- 6.1. Background -- 6.2. Observations -- a) CASES-99 -- b) Sodankylä -- c)Cabauw -- d)SHEBA -- e) SABLES98 -- 6.3. USING DIMENSIONAL ANALYSIS FOR DERIVATION AN EQUATIONFOR THE STABLE BOUNDARY LAYER HEIGHT -- A) Three Dimensionless Groups -- b) Verification -- C) On the Relevance of the Coriolis Parameter F: Two Dimensionless Groups Only -- 6.4. An Alternative Theoretically Based Formulation for the StableBoundary Layer Height -- 6.4.1. Background -- 6.4.3. Results -- 6.5. CONCLUSIONS -- 7. CLOSURE -- ACKNOWLEDGEMENTS -- REFERENCES -- A QUANTITATIVE COMPARISON OF ANGSTROM'STURBIDITY PARAMETERS (α,β) RETRIEVED INDIFFERENT SPECTRAL RANGES BASED ONSPECTRAL SOLAR EXTINCTION MEASUREMENTS -- ABSTRACT -- INTRODUCTION -- EXPERIMENTAL MEASUREMENTS -- THEORETICAL BACKGROUND AND METHODOLOGY -- Definitions -- The Angstrom Parameters -- RESULTS -- Comparisons of Angstrom α Values -- Comparisons of Angstrom β Values -- CONCLUSION.

REVIEWED BY -- REFERENCES -- SIMULTANEOUS EVALUATION OF ODOR EPISODESAND AIR QUALITY. METHODOLOGY TO IDENTIFYAIR POLLUTANTS AND THEIR ORIGIN COMBININGCHEMICAL ANALYSIS (TD-GC/MS),SOCIAL PARTICIPATION, ANDMATHEMATICAL SIMULATIONS TECHNIQUES -- ABSTRACT -- 1. INTRODUCTION -- 2. ODOR IMPACT AND AIR QUALITY ASSESSMENT ANDMANAGEMENT FOR URBAN AREAS -- 3. METEOROLOGICAL ANALYSIS -- 4. SOCIAL PARTICIPATION -- 4.1. Model of Social Participation for Controlling Odor Episodes and AirQuality: Identifying Chemical Compounds and their Sources -- 4.1.1. Participation Levels -- 4.1.1.1. Sensory and Occurrence Data -- 4.1.2. Annoyance Level Evaluation -- 5. IMPACT MAPS -- 6. CHEMICAL CONTROL -- 6.1. Air Sampler Development -- 6.2. Analytical Methodology -- 6.2.1. Multi-sorbent Tubes -- 6.2.2. Analytical Instrumentation -- 6.3. Concentration Maps -- 6.4. Odor Maps -- 6.5. Air Quality Determination -- 6.5.1. Outdoor Air -- 6.5.2. Indoor Air -- 6.6. Identification of Recently Identified Pollutants and UnderstudiedCompounds -- 7. CASE STUDIES -- 7.1. Back-Trajectory Application -- 7.2. Application of Integrated Methodology (Social Participation, ChemicalControl and Numerical Modeling) -- 7.2.1. Description of the Study Area -- 7.2.2. Meteorological Analysis -- 7.2.3. Impact Maps -- 7.2.4. Social Control (Social Participation) -- 7.2.5. Chemical Control -- 7.2.5.1. Qualitative VOC Determination -- 7.2.5.2. Quantitative VOC Determination -- 7.2.5.3. Concentration Maps -- 8. CONCLUSIONS -- REFERENCES -- LICHEN BIOMONITORING OF AIR POLLUTION:ISSUES FOR APPLICATIONSIN COMPLEX ENVIRONMENTS -- ABSTRACT -- INTRODUCTION -- LICHEN DIVERSITY VALUE (LDV) METHOD -- MONITORING IN A VARIABLE ENVIRONMENT -- OBJECTIVE AND APPROACH -- WORKED EXAMPLE I. POLLUTION-RELATED SIGNAL ANDCLIMATE-RELATED NOISE IN LICHEN BIOMONITORING ATREGIONAL SCALE: A CASE-STUDY FROM LIGURIA (NW ITALY).

MATERIALS AND METHODS -- Sampling Design -- Lichen Sampling -- Data Analysis -- RESULTS -- DISCUSSION -- i) To Define Homogeneous Bioclimatic Regions -- ii) To Identify the Influence of Each Atmospheric Pollutant for EachBioclimatic Region and to Analyse Trends of Biodiversity Indices -- iii) To Elaborate Proper Scales for Interpreting lichen Biomonitoring Data -- WORKED EXAMPLE II. BIOMONITORING OF AIR POLLUTION INFOREST ECOSYSTEMS: PROBLEMS AND PERSPECTIVES -- MATERIALS AND METHODS -- The Study in Tuscany -- The Study in Liguria -- RESULTS -- Casentino National Park -- Liguria -- DISCUSSION -- Casentino National Park -- Liguria -- WORKED EXAMPLE III. NON POLLUTION-RELATED NOISE INLICHEN BIOMONITORING AT WITHIN-SITE SCALE:A CASE STUDY FROM ITALIAN-SLOVENIAN BORDERLINE -- MATERIALS AND METHODS -- Survey Area -- Sampling Strategy -- Non-pollution Related Factors -- Data Analysis -- RESULTS -- Local Epiphytic Vegetation -- Lichen Diversity Variability at within-Plot Scale -- LDV Variability and Non Pollution-related Factors -- DISCUSSION -- LDV variability at within- and between-sites scale: pollution and nonpollution-related predictors -- GENERAL CONCLUSIONS -- REFERENCES -- HYDROCARBON CONTAMINATION ANDENVIRONMENTAL HEALTH QUALITY: AN OVERVIEW -- ABSTRACT -- INTRODUCTION -- CONCEPT OF ENVIRONMENTAL QUALITY -- Definition of the Environment -- Major Components of the Environment -- 1. Soil -- 2. Water -- 3. Atmosphere -- Environmental Impact Assessment -- CONCEPT OF HYDROCARBONS -- PRIMARY SOURCES OF HYDROCARBON CONTAMINANTS ANDENVIRONMENTAL/HEALTH IMPACT -- Crude Oils -- Oil Spill -- Natural Gas -- Gas Flaring -- Produced Water -- Lubricating Oils -- Coal -- SECONDARY SOURCES OF HYDROCARBON CONTAMINANTS ANDENVIRONMENTAL / HEALTH IMPACT -- Oil Refinery -- Petrochemicals / Petrochemical Plants -- Flue Gases / Vehicle Emissions -- i) Carbon Monoxide (CO).

ii) Sulfur Dioxide (SO2) -- iii) Oxides of Nitrogen -- Leaded Gasoline -- Trace Heavy Metals -- Biological Decay of Sewage and Refuse -- Odors -- Biomass / Wood Fuels -- Spent Oil-based Drilling Fluid and Oily Drill Cuttings -- The Greenhouse Gases and Global Warming -- OTHER MINOR SOURCES OF HYDROCARBON CONTAMINATION -- Natural Seeps and Organic Matter -- Shale Oil and Condensates -- CONCLUSION AND RECOMMENDATIONS -- REFERENCES -- BIVARIATE STOCHASTIC VOLATILITY MODELSAPPLIED TO MEXICO CITY OZONE POLLUTIONDATA -- Abstract -- 1. Introduction -- 2. Bivariate Stochastic Volatility Models (BSV) -- 2.1. Model I -- 2.2. Model II -- 2.3. Model III -- 2.4. Model IV -- 2.5. Model V -- 2.6. Model VI -- 3. Bayesian Analysis -- 3.1. Class I -- 3.2. Class II -- 3.3. Class III -- 4. Model Selection -- 5. An Application to theWeekly Ozone Averages in Mexico City -- 5.1. Description of the Data -- 5.2. Application of the Models and Results -- 5.2.1. Model I -- 5.2.2. Model II -- 5.2.3. Model III -- 5.2.4. Model IV -- 5.2.5. Model V -- 5.2.6. Model VI -- 5.2.7. Model Selection -- 6. Conclusion -- Acknowledgements -- References -- OPTIMIZATION APPROACHES FOR AIR QUALITYMONITORING NETWORK DESIGN -- ABSTRACT -- INTRODUCTION -- AQMN-RESULTS -- AIR QUALITY MONITORING SITING CRITERION -- METHODOLOGY DESCRIPTION -- 1. Representation of Spatial-Temporal Patterns -- 2. Detection of Violations over Ambient Standards -- UTILITY FUNCTION APPROACH -- 1. Structure of the Utility Function -- 2. Computational Algorithm of the Utility Function Based on SinglePollutant -- 3. Computational Algorithm of the Utility Function Based on MultiPollutants Network Design -- CASE STUDY -- STUDY AREA OPTIMIZATION MODELING RESULTS DISCUSSION -- 1. Single Pollutant Monitoring Network Optimization Modeling Results -- 2. Multi-Pollutant Monitoring Network Optimization Modeling Results -- REFERENCES.

SENSITIVITY OF LAND USE PARAMETERS ANDPOPULATION ON THE PREDICTION OFCONCENTRATION USINGTHE AERMOD MODEL FOR AN URBAN AREA.

This book presents the latest research on the crucial issues and the standards necessary to assess, monitor and increase air quality.Particular emphasis is paid to problems related to urban air quality.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2019. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.

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