Statistics in Environmental Monitoring and Assessment details how statistics plays an essential role in every step of an environmental monitoring and assessment program, from the sampling design to the data management, and data analysis methods to extract meaningful information for environmental quality management. Large temporal and spatial variations of the environmental variables present a great challenge for producing a representative characterization of the status of any given environmental media, water, air, biota, or solid. This book explains these issues in an easy-to-understand manner…mehr
Statistics in Environmental Monitoring and Assessment details how statistics plays an essential role in every step of an environmental monitoring and assessment program, from the sampling design to the data management, and data analysis methods to extract meaningful information for environmental quality management. Large temporal and spatial variations of the environmental variables present a great challenge for producing a representative characterization of the status of any given environmental media, water, air, biota, or solid. This book explains these issues in an easy-to-understand manner and illustrates using actual applications in real-life case studies, each of which comes with a clear explanation for every related fundamental concept and methodology that details the statistical methods used in the analysis and considerations taken when using a particular method. Primarily intended for graduate students in environmental sciences who wish to use statistics as a research tool, it will also benefit researchers who are interested in applications of statistical methods for designing environmental monitoring programs and analysis of environmental data to assess the status of various environmental matrices. This book is organised in three parts with Part I providing a review of the basics of statistics, Part II focusing on sampling designs, and Part III focusing on applications of statistical methods for data analysis.
Shinichi Okamoto is a professor emeritus of Tokyo University of Information Sciences, holding a doctorate degree from Waseda University. He worked for the Industrial Pollution Control Association of Japan (currently the JEMAI) for nine years then joined the Tokyo University of Information Sciences, as a professor and retired in 2014, having served as the dean of the undergraduate and graduate schools. He has published 36 books or book chapters, and about 160 academic papers, offered intensive lectures on Statistics in the sampling design course, once a year since 2000, as a visiting professor at AIT. In 2004, he received the Teaching Award for this course from the School of Environment, Resources and Development of AIT. Nguyen Thi Kim Oanh is a distinguished professor at the Asian Institute of Technology (AIT) with over 35 years of working experience in research and education. She has been affiliated with the Environmental Engineering and Management Program of AIT since 1997 and is the founding director of the AIT research Centre for Nexus of Air Quality, Health, Ecosystem, and Climate. Recognised for her efforts in characterising environmental pollution issues in Asian developing countries, Prof. Kim Oanh has been selected to serve in several professional organisations and has been credited with over 200 peer-reviewed scientific papers and book chapters, 2 books (ed.), and many important development reports.
Inhaltsangabe
Preface About the authors 1 Introduction PART I Fundamentals of Statistics 2 Descriptive and Inferential Statistics 3 Sample and Distribution 4 Inferential Statistics 5 Analysis of variance 6 Correlation and Regression Analysis 7 Multivariate analyses PART II Applications for Sampling and Measurement 8 Monitoring tool in environmental quality management 9 Sampling design from theory to practical applications in environmental monitoring 10 Industrial pollution monitoring 11 Monitoring to Assess the Impacts of Industrial Discharges on The Environment 12 Design and implementation of ambient air pollution monitoring programme in Asian regional project of AIRPET 13 Sampling and analysis for particulate matter: Kashima SPM study 14 Temporal resolution and averaging time of concentrations 15 Spatial resolution of concentration data and optimal placement of monitoring stations 16 Quality assurance of the IPCAJ's acid rain study 17 Quality assurance of air tracer dispersion experiments for roadways 18 Characteristics of concentrations calculated by air quality model 19 Evaluation of air quality model performance PART III Applications for Data Analysis 20 Types of statistical data and analysis methods suitable for their analysis 21 Applications of principal component analysis and exploratory factor analysis 22 Statistical analyses for air quality predictions 23 Receptor models 24 Statistical analysis methods for questionnaire survey data: Case studies on environmental valuation
Preface About the authors 1 Introduction PART I Fundamentals of Statistics 2 Descriptive and Inferential Statistics 3 Sample and Distribution 4 Inferential Statistics 5 Analysis of variance 6 Correlation and Regression Analysis 7 Multivariate analyses PART II Applications for Sampling and Measurement 8 Monitoring tool in environmental quality management 9 Sampling design from theory to practical applications in environmental monitoring 10 Industrial pollution monitoring 11 Monitoring to Assess the Impacts of Industrial Discharges on The Environment 12 Design and implementation of ambient air pollution monitoring programme in Asian regional project of AIRPET 13 Sampling and analysis for particulate matter: Kashima SPM study 14 Temporal resolution and averaging time of concentrations 15 Spatial resolution of concentration data and optimal placement of monitoring stations 16 Quality assurance of the IPCAJ's acid rain study 17 Quality assurance of air tracer dispersion experiments for roadways 18 Characteristics of concentrations calculated by air quality model 19 Evaluation of air quality model performance PART III Applications for Data Analysis 20 Types of statistical data and analysis methods suitable for their analysis 21 Applications of principal component analysis and exploratory factor analysis 22 Statistical analyses for air quality predictions 23 Receptor models 24 Statistical analysis methods for questionnaire survey data: Case studies on environmental valuation
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