This book demonstrates the measurement, monitoring and mapping of environmental contaminants in soil & sediment, surface & groundwater and atmosphere. This book explores state-of-art techniques based on methodological and modeling in modern geospatial techniques specifically focusing on the recent trends in data mining techniques and robust modeling. It also presents modifications of and improvements to existing control technologies for remediation of environmental contaminants. In addition, it includes three separate sections on contaminants, risk assessment and remediation of different existing and emerging pollutants. It covers major topics such as: Radioactive Wastes, Solid and Hazardous Wastes, Heavy Metal Contaminants, Arsenic Contaminants, Microplastic Pollution, Microbiology of Soil and Sediments, Soil Salinity and Sodicity, Aquatic Ecotoxicity Assessment, Fluoride Contamination, Hydrochemistry, Geochemistry, Indoor Pollution and Human Health aspects. The content of this book will be of interest to researchers, professionals, and policymakers whose work involves environmental contaminants and related solutions.

Spatial Modeling of Environmental Pollution and Ecological Risk provides valuable information and insights for researchers, students and professionals in geography, hydrology, sedimentology, soil science, agriculture, engineering and GIS as they face increasingly complex challenges around development strategies for a sustainable society. Written by the world’s leading researchers in their field, each article will begin with a short introductory essay that includes an overview of the sections' papers. Individual chapters focus on the core themes of research and knowledge and some topics that have received lesser attention. Each chapter will review the current understanding of knowledge regarding the present study and scope and consider where future efforts should be directed. Discusses issues at the forefront of present research in environmental science, bioscience, ecology, pedogeomorphology, landscape, geoscience, forestry, hydrology and GIS Explores state-of-art techniques based on methodological and modeling in modern Deep learning and Machine learning geospatial techniques through case studies Describes novel control strategies, remediation and eco-restoration, and conservation techniques for sustainable development

Environmental modelling has enjoyed a long tradition, but there is a defined need to continually address both the power and the limitations of such models, as well as their quantitative assessment. This book showcases modern environmental modelling methods, the basic theory behind them and their incorporation into complex environmental investigations. It highlights advanced computing technologies and how they have led to unprecedented and adaptive modelling, simulation and decision-support tools to study complex environmental systems, and how they can be applied to current environmental concerns. This volume is essential reading for researchers in academia, industry and government-related bodies who have a vested interest in all aspects of environmental modelling. Features include: A range of modern environmental modelling techniques are described by experts from around the world, including the USA, Canada, Australia, Europe and Thailand; many examples from air, water, soil/sediment and biological matrices are covered in detail throughout the book; key chapters are included on modelling uncertainty and sensitivity analysis; and, a selection of figures are provided in full colour to enable greater comprehension of the topics discussed.

Environmental multimedia models (EMMs) have been used in environmental risk assessment since they reflect the interactive transport and fate processes of chemicals within multi-compartmental environmental systems. However, these existing models are limited in their abilities to predict contaminant concentrations in the multimedia environment at a better temporal-spatial resolution, especially for regional scale site contamination problems. A novel regional numerical multimedia environmental modeling (RNEMM) approach is developed in this thesis for the multimedia environment. RNEMM consists of a water quality simulation module for river network system, a gaseous phase simulation module, a mass balance analysis module for soil, a food web module and a health risk assessment module. Two key developments are achieved to integrate these modules into the entire system: integrating different modules with non-uniform boundary conditions and inter-media flux, and coupling the modules based on practical considerations of regional scale multimedia contamination problems. Importantly, four validations related to the RNEMM development are conducted. First, a new model in 1D and 2D are established through considering the non-uniform boundary conditions and inter-media flux. Numerical algorithms, including the finite element method (FEM) and finite volume method (FVM), are used to solve the governing equations. The measured results in two landfill cases are used to validate the spatial and temporal accuracy of predicted concentrations obtained from these models. Second, a regional spatial environmental multimedia model (RSEMM) is developed by coupling the modules based on a different concept (i.e., a water quality model for the river network and a fugacity model) to provide predicted concentration profiles of contaminants at a regional scale. A third regional site validation is conducted through a case in the urban area of Tianjin City and reasonable results have been obtained through the comparison of simulated and measured results. Subsequently, based on the two key developments, a regional numerical multimedia environmental modeling (RNEMM) approach is developed and tested by assessing spatial eco-environmental exposure risk of perfluorooctane sulfonate (PFOS) in the pearl river basin. The exposure risk assessment for children and adults is further conducted based on the integrated risk assessment model. In conclusion, the RNEMM can serve as a comprehensive management tool to assess and control the exposure risks associated with emerging contaminants on regional water, soil, and ecosystem at an adequate spatial-temporal resolution.

This book demonstrates the measurement, monitoring, mapping and modelling of soil pollution and land resources. This book explores state-of-the-art techniques based on open sources software & R statistical programming and modelling in modern geo-computation techniques specifically focusing on the recent trends in data mining/machine learning techniques and robust modelling in soil resources. Soil and agricultural systems are an integral part of the global environment and human well‐being, providing multiple goods and services essential for people worldwide and crucial for sustainable development. Soil contamination is an environmental hazard and has become a big issue related to environmental health. The challenge of the twenty-first century is to reduce the contaminant load and bring it to below permissible level. The contamination is not only a problem affecting local environments at the place of occurrence but also spreading to other regions because of easy transportation of pollutants. This leads to direct and indirect contamination of land and aquatic systems, surface water and groundwater, inducing significant risks for natural ecosystems. In this context, the spatial modelling, prediction, efficient use, risk assessment, protection and management of soil resources in the agriculture system are the key to achieving sustainable development goals and ensuring the promotion of an economically, socially and environmental sustainability future. The aim of this book on soil contaminants and environmental health: application of geospatial technology is to identify the soil and sediment quality, sources of contaminants and risk assessment and focuses on the decision-making and planning point of view through GIS data management techniques. This book covers major topics such as spatial modelling in soil and sediments pollution and remediation; radioactive wastes, microbiology of soil and sediments, soil salinity and sodicity, pollution from landfill sites, soil erosion and contamination from agricultural activities, heavy metal pollution and health risk; environmental impact and risk assessment, sustainable land use, landscape management and governance, soil degradation and risk assessment, agricultural soil pollution, pollution due to urban activities, soil pollution by industrial effluents and solid wastes, pollution control and mitigation in extreme environments. The content of this book is of interest to researchers, professionals and policy-makers whose work is in soil science and agriculture practices. The book equips with the knowledge and skills to tackle a wide range of issues manifested in geographic data, including those with scientific, societal and environmental implications.

While technology is developing at a fast pace, urban planners and cities are still behind in finding effective ways to use technology to address citizen’s needs. Multiple aspects of sustainable urbanism are brought together in this book, along with advanced technologies and their connections to urban planning and management. It integrates urban studies, smart cities, AI, IoT, remote sensing, and GIS. Highlights include land use planning, spatial planning, and ecosystem-based information to improve economic opportunities. Urban planners and engineers will understand the use of AI in disaster management and the use of GIS in finding suitable landfill sites for sustainable waste management. Features Explains the process of urban heritage conservation, including the process of urban renewal and its regeneration and the role of citizens in urban renewal, planning, and management. Includes several case studies highlighting urban environmental problems and challenges in developed and developing countries and the ways for converting urban areas into smart cities. Focuses on urban resources, the supply of energy in smart cities, and their proper management practices. Introduces the role of remote sensing, GIS, and IoT in making a smart city and meeting sustainable goals. Analyzes unique case studies, their challenges and obstacles, and proposes a set of factors to understanding smart city initiatives and projects.