Alberto Pistocchi

GIS Based Chemical Fate Modeling

Principles and Applications

• Gebundenes Buch

Produktbeschreibung

This book covers the integration of chemical fate modeling for use in Geographic Information System (GIS) functions. It features a practical and hands-on approach that's intended for modelers preparing maps of chemical emissions, and creating landscape and climate properties within a GIS, while chemical fate calculations are performed using specialized model codes. A relevant part of the book also discusses data retrieval and processing as a basis for modeling. As such, the book offers a one-stop reference for practitioners who wish to integrate GIS with chemical modeling.

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Explains how GIS enhances the development of chemical fate and transport models

Over the past decade, researchers have discovered that geographic information systems (GIS) are not only excellent tools for managing and displaying maps, but also useful in the analysis of chemical fate and transport in the environment. Among its many benefits, GIS facilitates the identification of critical factors that drive chemical fate and transport. Moreover, GIS makes it easier to communicate and explain key model assumptions.

Based on the author's firsthand experience in environmental assessment, GIS Based Chemical Fate Modeling explores both GIS and chemical fate and transport modeling fundamentals, creating an interface between the two domains. It then explains how GIS analytical functions enable scientists to develop simple, yet comprehensive spatially explicit chemical fate and transport models that support real-world applications. In addition, the book features:
Practical examples of GIS based model calculations that serve as templates for the development of new applications
Exercises enabling readers to create their own GIS based models
Accompanying website featuring downloadable datasets used in the book's examples and exercises
References to the literature, websites, data repositories, and online reports to facilitate further research
Coverage of important topics such as spatial decision support systems and multi-criteria analysis as well as ecological and human health risk assessment in a spatial context

GIS Based Chemical Fate Modeling makes a unique contribution to the environmental sciences by explaining how GIS analytical functions enhance the development and interpretation of chemical fate and transport models. Environmental scientists should turn to this book to gain a deeper understanding of the role of GIS in describing what happens to chemicals when they are released into the environment.

Produktdetails

• Verlag: Wiley & Sons
• 1. Auflage
• Seitenzahl: 504
• Erscheinungstermin: April 2014
• Englisch
• Abmessung: 287mm x 220mm x 30mm
• Gewicht: 1630g
• ISBN-13: 9781118059975
• ISBN-10: 1118059972
• Artikelnr.: 36701710

Autorenporträt

ALBERTO PISTOCCHI, MSc Eng, MSc Phil, PhD, is Adjunct Professor of Spatial Decision Support Systems at the University of Trento, Italy, and the author of several scientific contributions to the fields of hydrology, environmental assessment, chemical fate and transport modeling, and spatial decision support systems. As a researcher, environmental analyst, and project manager, he has been working for the European Commission's Joint Research Centre, the Emilia Romagna regional government, and other private and public organizations. He is a founding partner (2001) and the scientific director of GECOsistema, a research spin-off from the University of Bologna, Italy.

Inhaltsangabe

Preface xiii Contributors xvii Chapter 1 Chemicals, Models, and GIS:
Introduction 1 1-1 Chemistry, Modeling, and Geography 1 1-2 Mr. Palomar and
Models 2 1-3 What Makes a Model Different? 4 1-4 Simple, Complex, or
Tiered? 7 Compatibility of Emissions and Concentrations 9 Spatiotemporal
Variability 10 Spatial Patterns 12 More Complex Models and the Tale of
Horatii and Curiatii 15 1-5 For Whom is this Book Written? 17 References 19
Chapter 2 Basics of Chemical Compartment Models and Their Implementation
with GIS Functions 23 2-1 Introduction 23 2-2 Phase Partitioning 24 Air
Compartment 24 Surface Water Compartment 25 Soil Compartment 25 2-3
Diffusion, Dispersion, and Advection 26 2-4 Fluxes at the Interfaces 28
Air-Ground Surface Interface 28 Water-Air and Water-Bottom Sediment
Interface 28 Soil-Air and Soil-Water Interface 29 Parameterization of
Advection Velocities and Diffusion/Dispersion Rates 29 2-5 Reactions 32 2-6
Transport Within an Environmental Medium: The Advection-Diffusion Equation
(ADE) 33 Soils 37 Surface Water 38 Atmosphere 39 2-7 Analytical Solutions
40 Example: The Domenico Model 40 Example: Implementation of a River Plug
Flow Model in a Spreadsheet 45 2-8 Box Models, Multimedia and Multispecies
Fate and Transport 47 Example: Implementing a Box Model of Soil
Contamination and Water Pollution Loading in a Spreadsheet 51 2-9 Spatial
Models: Implicit, Explicit, Detailed Explicit, and GIS-Based Schemes 57
References 65 Chapter 3 Basics of GIS Operations 71 3-1 What is GIS? 71
3-2 GIS Data 72 Coordinate Systems 72 Example: Coordinate Transformation 75
Example: Georeference a Map from a Paper Using ArcGIS 77 GIS Formats 81 3-3
GIS Software 92 3-4 GIS Standards 93 Exercise: Browse and Export Geographic
Objects in KML and Combine Them with Layers from a WMS 94 3-5 A
Classification of GIS Operations for Chemical Fate Modeling 99 3-6 Spatial
Thinking 100 3-7 Beyond GIS 103 3-8 Further Progress on GIS 104 References
104 Chapter 4 Map Algebra 107 4-1 Map Algebra Operators and Syntaxes 109
4-2 Using Map Algebra to Compute a Gaussian Plume 112 Example: Using Map
Algebra to Compute Volatilization Rates from Water Bodies 119 4-3 Using Map
Algebra to Implement Isolated Box Models 121 References 124 Chapter 5
Distance Calculations 127 5-1 Concepts of Distance Calculations 127
Example: Feature Buffering 127 Example: Join Based on Distance 129 5-2
Distance Along a Surface and Vertical Distance 134 5-3 Applications of
Euclidean Distance in Pollution Problems 135 5-4 Cost Distance 139
Exercise: Euclidean and Cost distance Calculations 140 References 148
Chapter 6 Spatial Statistics and Neighborhood Modeling in GIS 149 6-1
Variograms: Analyzing Spatial Patterns 149 Exercise: Computing Variograms
of Observed Atmospheric Contaminants 154 6-2 Interpolation 160 6-3 Zonal
Statistics 163 6-4 Neighborhood Statistics and Filters 164 Exercise:
Creating a Population Map from Point and Polygon Data 169 References 170
Chapter 7 Digital Elevation Models, Topographic Controls, and Hydrologic
Modeling in GIS 171 7-1 Basic Surface Analysis 171 7-2 Drainage 178
Example: Pit Filling, Flow Direction, Flow Accumulation, and Flow Length in
ArcGIS 178 Example: Catchment Population in India 183 Example: Travel Time
185 7-3 Using GIS Hydrological Functions in Chemical Fate and Transport
Modeling 187 7-4 Non-D8 Methods and the TauDEM Algorithms 190 7-5 ESRI's
''Darcy Flow'' and ''Porous Puff'' Functions 191 References 193 Chapter 8
Elements of Dynamic Modeling in GIS 195 8-1 Dynamic GIS Models 195 8-2
Studying Time-Dependent Effects With Simple Map Algebra 200 Intermittent
Emissions 200 Lagged Release from Historical Stockpiles 201 Stepwise
Constant Emission and Removal Processes 202 8-3 Decoupling Spatial and
Temporal Aspects of Models: The Mappe Global Approach 203 References 206
Chapter 9 Metamodeling and Source-Receptor Relationship Modeling in GIS
209 9-1 Introduction 209 9-2 Metamodeling 210 9-3 Source-Receptor
Relationships 213 References 215 Chapter 10 Spatial Data Management in
GIS and the Coupling of GIS and Environmental Models 217 10-1 Introduction
217 10-2 Historical Perspective of Emergence of Spatial Databases in
Environmental Domain 218 10-3 Spatial Data Management in GIS: Theory and
History 221 Spatial Database Definition 221 Relational Data Model
Foundations 221 Object Relational Concepts: A Foundation Model for Spatial
Databases--Theoretical Background 224 PostgreSQL/PostGIS Object Relational
Support 225 Oracle Object Relational Support 225 10-4 Spatial Database
Solutions 226 ESRI Geodatabase 226 PostgreSQL and PostGIS 229 Oracle
Locator and Spatial 230 10-5 Simple Environmental Spatiotemporal Database
Skeleton and GIS: Hands-On Examples 230 Simple PostgreSQL/PostGIS
Environmental Spatiotemporal Database Skeleton and QuantumGIS 231 Simple
Oracle XE Environmental Spatiotemporal Database Skeleton 237 10-6
Generalized Environmental Spatiotemporal Database Skeleton and Geographic
Mashups 244 Spatiotemporal Database Skeleton 244 Geographic Mashup 246
References 249 Chapter 11 Soft Computing Methods for the Overlaying of
Chemical Data with Other Spatially Varying Parameters 253 11-1 Introduction
253 11-2 Fuzzy Logic and Expert Judgment 258 11-3 Spatial Multicriteria
Analysis 262 11-4 An Example of Vulnerability Mapping of Water Resources to
Pollution 266 References 276 Chapter 12 Types of Data Required for
Chemical Fate Modeling 279 12-1 Climate and Atmospheric Data 280 12-2 Soil
Data 286 12-3 Impervious Surface Area 289 12-4 Vegetation 289 12-5
Hydrological Data 291 12-6 Elevation Data 293 12-7 Hydrography 296 12-8
Lakes 298 12-9 Stream Network Hydraulic Data 298 12-10 Ocean Parameters 299
12-11 Human Activity 301 Land Use/Land Cover 303 Population 305 Stable
Lights at Night 306 12-12 Using Satellite Images for the Extraction of
Environmental Parameters 306 12-13 Compilations of Data for Chemical Fate
and Transport Modeling 307 References 307 Chapter 13 Retrieval and
Analysis of Emission Data 311 13-1 Characterization of Emissions 311 13-2
Emissions based on Production Volumes 312 13-3 Estimation from Usage or
Release Inventories 313 13-4 Emission Factors 313 13-5 Spatial and Temporal
Distribution of Emissions 314 Diffuse Emissions at Local to Regional Scale
317 Example: Estimating Urban Runoff Contaminants from Land Use and
Population Data in the Province of Naples, Italy 318 Exercise:
Apportionment of Emissions Using a Geographic Pattern 318 13-6 Modeling
Traffic Flows 322 References 326 Chapter 14 Characterization of
Environmental Properties and Processes 329 14-1 Physicochemical Properties
and Partition Coefficients 329 14-2 Aerosol and Suspended Sediments 330
Exercise: Computing SPM in Rivers Using the Formula of Hakanson and
Co-workers 332 14-3 Diffusive Processes 335 14-4 Dispersion 335 14-5
Advective Processes 336 Atmospheric Deposition 336 Soil Water Budget
Calculations 338 Soil Erosion 344 14-6 River and Lake Hydraulic Geometry
344 References 350 Chapter 15 Complex Models, GIS, and Data Assimilation
353 15-1 Atmospheric Transport Models 353 Example: Dispersion Modeling of
an Atmospheric Emission in Australia 354 15-2 Transport in Groundwater and
the Analytic Element Method 361 15-3 GIS Functions of Modeling Systems and
Data Assimilation 361 References 363 Chapter 16 The Issue of Monitoring
Data and the Evaluation of Spatial Models of Chemical Fate 365 16-1
Existing Monitoring Programs 366 16-2 Distributed Sampling 366 16-3 Methods
for the Comparison of Measured and Modeled Concentrations 367 Exercise:
Comparison of Two PCB Soil Concentration Models 368 References 375 Chapter
17 From Fate to Exposure and Risk Modeling with GIS 377 17-1 Exposure and
Risk for Human Health 377 17-2 Models for the Quantification of Chemical
Intake by Humans 382 Exercise: Human Exposure, Intake, and Cancer Risk
Related to Ingestion of Aboveground Produce Contaminated by Gas and Dust
Deposition of 2,3,7,8-TCDD Emitted from an Industrial Emission Source 386
17-3 Ecological and Environmental Risk Assessment 393 Exercise: Mapping
Patch Area and Ecotones in South America 398 17-4 Data for GIS Based Risk
Assessment 400 References 401 Chapter 18 GIS Based Models in Practice:
The Multimedia Assessment of Pollutant Pathways in the Environment (MAPPE)
Model 405 18-1 Introduction 405 18-2 Environmental Compartments Considered
in the Model 407 Atmosphere Compartment 409 Soil Compartment 412 Inland
Water Compartment 413 Seawater 415 18-3 Implementation in GIS: Example with
Lindane 416 Scalar Input Quantities 416 Maps Describing Landscape and
Climate Parameters 418 Air Compartment Calculations 419 Soil Compartment
Calculations 422 Inland Water Compartment Calculations 427 Seawater
Compartment Calculations 434 18-4 Using the Model For Scenario Assessment
436 References 441 Chapter 19 Inverse Modeling and Its Application to
Water Contaminants 443 19-1 Introduction 443 Exercise: Inverse Modeling of
Caffeine in Europe 447 References 451 Chapter 20 Chemical Fate and
Transport Indicators and the Modeling of Contamination Patterns 453 20-1
The Relative Risk Model 453 Example: Relative Risk Assessment for Coastal
Ecosystems Due to Wastewater Emission in South Africa 456 20-2 Use of
Chemical Fate and Transport Indicators in the Context of Relative Risk
Assessment: An Example with Contaminants Applied to Soil 459 Example:
Generic Modeling of Sewage Sludge Soil Application in Mexico 464 References
472 Chapter 21 Perspectives: The Challenge of Cumulative Impacts and
Planetary Boundaries 475 References 478 Index 481