Numerical Methods in Environmental Data Analysis

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Numerical Methods in Environmental Data Analysis
Numerical Methods in Environmental Data Analysis
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Contents
Preface
1 - Overview on data treatment
	1. Introduction
		1.1 Mathematical technique
		1.2 Computational technique
		1.3 Statistical data treatment
	References
2 - Case study in environmental pollution research
	1. Introduction
		1.1 Air pollution
			1.1.1 Causes of air pollution
			1.1.2 Effects of air pollution
			1.1.3 Control of air pollution
			1.1.4 Vehicular pollution
			1.1.5 Gas flaring
			1.1.6 Bioaerosol production as a source of air pollution
		1.2 Land pollution
			1.2.1 Causes of land pollution
			1.2.2 Effects of land pollution
			1.2.3 Control measures for land pollution
			1.2.4 Soil contamination
		1.3 Water pollution
			1.3.1 Causes of water pollution
			1.3.2 Effects of water pollution
			1.3.3 Control measures for water pollution
			1.3.4 Well pollution and why it is still a problem in developing countries
				1.3.4.1 Dangers of well pollution
				1.3.4.1 Dangers of well pollution
				1.3.4.2 Policy of well pollution
				1.3.4.2 Policy of well pollution
			1.3.5 Bore-hole pollution
			1.3.6 River contamination
		1.4 Noise pollution
			1.4.1 Sources of noise pollution
			1.4.2 Effects of noise pollution
		1.5 Radioactive pollution
			1.5.1 Causes of radioactive pollution
			1.5.2 Effect of radioactive pollution
		1.6 Electronic waste pollution
	References
	Further reading
3 - Typical environmental challenges
	1. Introduction
		1.1 Thermal comfort as a source of environmental concern
		1.2 Rainfall as a source of environmental concern
		1.3 Recent environmental crisis and the problem of climate change
	References
4 - Generating environmental data: Progress and shortcoming
	1. Method of generating environmental data: common challenges, safety, and errors
		1.1 Data quality and errors
		1.2 Satellite measurement
		1.3 Modeling procedure
		1.4 Experimental procedure
			1.4.1 Safety rules
				1.4.1.1 Safety for environmental field researcher
				1.4.1.1 Safety for environmental field researcher
				1.4.1.2 Safety for environmental laboratory researcher
				1.4.1.2 Safety for environmental laboratory researcher
					1.4.1.2.1 Safety location rules
					1.4.1.2.1 Safety location rules
			1.4.2 Pre-experimental safety
			1.4.3 Experimental safety rules
			1.4.4 Post- experimental safety
			1.4.5 General safety rules
	2. Common errors in laboratory practice
	3. Maintaining laboratory apparatus
	References
5 - Root finding technique in environmental research
	1. Application of root finding technique to environmental data
		1.1 The root finding method
			1.1.1 Newton's method
			1.1.2 Secant method
			1.1.3 Bisection method
		1.2 Modification of the root finding method to data application
			1.2.1 Additivity (superposition)
			1.2.2 Homogeneity (linearity)
				1.2.2.1 Example 1: performing root finding technique using Microsoft Excel Package
				1.2.2.1 Example 1: performing root finding technique using Microsoft Excel Package
					1.2.2.1.1 Using the Newton's method
					1.2.2.1.1 Using the Newton's method
					1.2.2.1.2 Using the secant method
					1.2.2.1.2 Using the secant method
					1.2.2.1.3 Using the bisection method
					1.2.2.1.3 Using the bisection method
		1.3 Computational application of root finding method to data application
			1.3.1 Computational application to Newton's method
			1.3.2 Computational application to secant method
			1.3.3 Computational application to bisection method
				1.3.3.1 Code5.8
				1.3.3.1 Code5.8
	Reference
6 - Numerical differential analysis in environmental research
	1. Introduction
		1.1 Euler method
		1.2 Improved Euler method
		1.3 Runge–Kutta method
		1.4 Predictor Corrector method
		1.5 Midpoint method
		1.6 Application of numerical methods of solving differentiation in environmental research
		1.7 Computational processing of numerical methods for solving differential equation
			1.7.1 The Euler's method
		1.8 Computational application of derivatives to environmental data
		1.9 Case 1: derivative of experimental data
	References
	Further reading
7 - Numerical integration application to environmental data
	1. Introduction
		1.1 Midpoint
		1.2 Trapezoidal rule
		1.3 Simpson's rule
		1.4 Computational application of numerical integration
	References
8 - Numerical interpolation in environmental research
	1. Introduction
	2. Application of interpolation to environmental data
	3. Lagrange interpolation
	4. Newton interpolation
	5. Spline interpolation
	6. Computational application of interpolation
	References
	9 - Environmental/atmospheric numerical models formulations: model review
	1. Introduction
		1.1 Global forecast system
		1.2 NOGAPS-ALPHA model
		1.3 Global Environmental Multiscale Model (GEM)
		1.4 European Center for Medium Range Weather Forecasts
		1.5 Unified Model (UKMO)
		1.6 French global atmospheric forecast model (ARPEGE)
		1.7 Weather Research and Forecasting (WRF)
		1.8 Japan Meteorological Agency Nonhydrostatic Model (JMA-NHM)
		1.9 The fifth generation mesoscale model
		1.10 Advanced Region Prediction System (ARPS)
		1.11 High Resolution Limited Area Model (HIRLAM)
		1.12 Global Environmental Multiscale limited area model
		1.13 ALADIN model
		1.14 Eta model
		1.15 Microscale model (MIMO)
		1.16 Regional atmospheric modeling system (RAMS)
	References
	Further reading
Index
	A
	B
	C
	D
	E
	F
	G
	H
	I
	J
	L
	M
	N
	O
	P
	Q
	R
	S
	T
	U
	V
	W
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