Accounting for Climate Change (eBook)

Title Page 3
Copyright Page 4
Table of Contents 5
Accounting for Climate Change: Introduction 6
Uncertainties of a Regional Terrestrial Biota Full Carbon Account: A Systems Analysis 10
1 Introduction 10
2 Basic Definitions 12
3 Uncertainties of the Regional Full Carbon Account 13
4 Requirements for the Terrestrial Biota Regional Full Carbon Account 16
5 Assessing Uncertainties 17
6 Some Practical Implementations and Results from Case Studies 19
7 Conclusion 24
References 25
National Greenhouse Gas Inventories: Understanding Uncertainties versus Potential for Improving Reliability 27
1 Introduction 27
2 Methodology: How to Assess the Uncertainty of National Emission Inventories 28
3 Results 28
4 Discussion 29
4.1 Excluding Sources with High Uncertainty 29
4.2 Covariance and the Definition of Adequate System Boundaries 30
4.3 Significance of Subjective Interpretation of Uncertainty 31
4.4 Rigid Accounting as a Method of Assessing Emissions 32
5 Conclusions 33
References 33
Practical Policy Applications of Uncertainty Analysis for National Greenhouse Gas Inventories 35
1 Introduction 36
2 Using Uncertainty Estimates to Adjust Inventories 37
2.1 Two Possible Adjustment Mechanisms 38
2.2 Characteristics of the Adjustment Factor and Implications for the Uncertainty Analysis 42
3 Adjustments to Emissions Trading Ratios Based on the Uncertainty of Emissions 45
3.1 Trading Ratios: Upper Bound Emissions are Unchanged 47
3.2 Trading Ratios: Probabilities of Exceeding Emissions Commitments are Unchanged 50
3.3 Characteristics of the Trading Ratio and Uncertainty Analysis 51
3.3.1 Fulfilling Environmental Goals: The Impacts of Trading on Environmental Quality 52
3.3.2 Administrative Complexity 54
3.3.3 Implications for Trading Ratios in Practice 55
4 Uncertainty Analysis as a Tool for Inventory Improvement 55
5 Conclusions 57
References 58
Modeling Afforestation and the Underlying Uncertainties 59
1 Introduction 59
2 Description of the Model and Experiment 60
2.1 Description of the Model 60
2.2 Submodel of Available Water in an Ecosystem 61
2.3 Calibration and Testing of the Model 62
2.4 Modeling of the Parameter Uncertainties 63
2.5 Numerical Experiment 63
3 Results and Discussion 64
4 Conclusions 65
References 65
Spatial GHG Inventory: Analysis of Uncertainty Sources. A Case Study for Ukraine 67
1 Introduction 67
2 Basic Approach 68
2.1 National Level 69
2.2 Regional Level 69
2.3 Plot Level 70
3 A Geoinformation Technology for Distributed GHG Inventories 70
4 Inventory at the Regional Level: Energy Sector 72
5 Spatial Analysis of GHG Emissions 73
6 Results of Spatial Inventory and Uncertainty Reduction 74
7 Conclusions 77
References 78
Prior to Economic Treatment of Emissions and Their Uncertainties Under the Kyoto Protocol: Scientific Uncertainties That Must Be Kept in Mind 79
1 Introduction 79
2 Setting the Stage for Working within a Consistent FGA-Uncertainty-Verification Framework 80
2.1 A Brief Science–Theoretical Discourse: Plausibility, Validation, and Verification 81
2.2 Accounting Versus Diagnostic and Prognostic Modeling 82
2.3 Uncertainty Concept 82
3 Bottom–Up Versus Top–down Accounting: Verification of Emissions 84
4 Bottom–Up/Top–Down Verification of Emissions and Temporal Detection of Emissions Signals 84
5 Temporal Detection of Emission Signals 86
5.1 Detectability Versus Statistical Significance 86
5.2 No Credibility Without Uncertainty 86
5.3 Different Techniques–Different Endings 87
6 Conclusions 92
References 93
Processing National CO2 Inventory Emissions Data and their Total Uncertainty Estimates 96
1 Introduction 96
2 Notation Used 97
3 A Nonparametric Method 98
3.1 Basic Assumptions and Simplifications 98
3.2 Smoothing and Uncertainty Analysis 98
3.2.1 Smoothing Splines 98
3.2.2 Uncertainty Analysis 99
3.2.3 Application to Real Data 99
4 Empirical Parametric Models 101
4.1 Estimation of the Parameter gi 102
4.2 Piecewise Exponential Model 103
5 Geometric Brownian Motion 105
5.1 Geometric Brownian Model for the Emissions 105
5.2 Arithmetic Brownian Model for the Logarithm of the Emissions 106
6 Conclusions 108
References 109
Extension of EU Emissions Trading Scheme to Other Sectors and Gases: Consequences for Uncertainty of Total Tradable Amount 111
1 Introduction 111
2 Uncertainties in Different Emissions Trading Schemes 113
3 Materials and Methods 114
4 Results 116
5 Discussion and Conclusions 117
References 119
Compliance and Emissions Trading under the Kyoto Protocol: Rules for Uncertain Inventories 121
1 Introduction 121
2 Notation and Problem Formulation 123
3 The Interval Type of Uncertainty 123
3.1 Compliance Proving 123
4 Adjustment of the Basic Committed Level 125
5 Uncertainties in Emissions Trading 127
6 Tradable Permits Under Uncertainty 128
6.1 Compliance with Undershooting 129
6.2 Compliance with Adjustment of the Commitment Level 129
6.3 Compliance Proving and Trading Mechanism 130
7 Simulation of a Carbon Market with Effective Permits 130
7.1 Database 130
7.2 No Uncertainty Market 131
7.3 Market with Uncertainties 131
7.3.1 Effective Emission Permits 131
7.3.2 Market with Undershooting 132
7.3.3 Market with Adjustments 132
7.4 Simulation Results 132
7.4.1 Trading with Effective Permits Under Undershooting 132
7.4.2 Trading with Effective Permits Under Adjustment 134
8 The Stochastic Type of Uncertainty 134
8.1 Compliance Proving 134
8.2 Adjustment of the Basic Committed Level 136
8.3 Uncertainties in Emissions Trading 136
9 Conclusions 137
References 138
The Impact of Uncertainty on Banking Behavior: Evidence from the US Sulfur Dioxide Emissions Allowance Trading Program 141
1 Introduction 141
2 The Sulfur Dioxide Market, Uncertainty, and Banking 143
3 A Model of Emissions Trading under Uncertainty 146
4 The Data 147
5 Estimation and Empirical Findings 149
5.1 Allowances Banking Behavior 149
5.2 Uncertainty 149
5.3 Estimation 149
5.4 Findings 150
6 Conclusion 150
Appendix 151
References 152
Tradable Permit Systems: Considering Uncertaintyin Emission Estimates 154
1 Introduction 154
2 The Modeling Framework 156
3 The Data 157
4 Results of Simulations 157
5 Conclusions 158
Appendix 158
References 159

"Compliance and Emissions Trading under the Kyoto Protocol: Rules for Uncertain Inventories (p. 539-540)

Zbigniew Nahorski · Joanna Horabik ·Matthias Jonas

Abstract A solution is proposed for proving compliance with emission targets and for emissions trading in the event of uncertainties in reported emission inventories. The solution is based on the undershooting concept, from which the mathematical conditions for both proving compliance with a risk α and calculating effective emissions for trading are derived. Based on the reported emission units, the number of permits granted is reduced in proportion to the uncertainty in the inventory. A country whose inventory has higher uncertainty is thereby allotted fewer permits than a country with the same inventory but smaller uncertainty.

Keywords greenhouse gas inventory uncertainty · compliance with Kyoto Protocol · risk of noncompliance · undershooting · emissions trading · effective tradable permits

1 Introduction

Uncertainty in greenhouse gas (GHG) inventories has been estimated to be in the 5–20% range, depending on the methodology used and its scope (Monni, Syri, Pipatti & Savolainen, 2004a; Rypdal & Winiwarter, 2001). Even if the assumptions of some of the computations need to be uni?ed and possibly recalculated, uncertainty is still believed to be about 10–12% or more for most countries (Winiwarter, 2007) and is therefore typically larger than countries’ reduction commitments.

Thus, uncertainty seems to be a major problem both in proving compliance and in implementing the ?exible mechanisms introduced in the Kyoto Protocol: emissions trading (Article 16[b]); joint implementation (Article 6); and the clean development mechanism (Article 12). In this paper we deal with tradable permits, but the ideas presented can be extended to other mechanisms. Uncertainty varies among the Parties to the Kyoto Protocol and according to different emissions activities.

For example, there are better- or poorer-quality inventories and there are moreor less-credible GHG emission reductions. Thus, under the ?exible mechanisms, better- or poorerquality “goods” are offered for sale or exchange. Should these be treated on an equal basis? In the absence of explicit rules for governing this problem, the market itself is unlikely to resolve it; and leaving it unresolved may undermine the credibility of the whole emission reduction process.

The problem of uncertainty in inventories is covered somewhat inadequately in the literature. Assessments of uncertainty have been carried out and compared for several countries; see, for example, Charles, Jones, Salway, Eggleston and Milne (1998); Lim et al. (1999); Gawin (2002); Jonas and Nilsson (2001); Monni, Syri and Savolainen (2004b); Nilsson et al. (2000); Rypdal and Winiwarter (2001); Rypdal and Zhang (2000); van Amstel, Oliver and Ruyssenaars (2000); Salway et al. (2002) see also a compendium in Gugele, Huttunen and Ritter (2005).

There have been a number of rather vague references to excluding the most uncertain activities from emissions trading (Monni et al., 2004a; Victor, 1991). In Godal (2000) and Godal, Ermolev, Klaassen and Obersteiner (2003) undershooting as the basis for proving compliance is proposed. Similar ideas have been formulated in Gupta, Oltshoorn and Rotenberg (2003) and Gillenwater, Sussman and Cohen (2007). The latter especially presents a solution close to that contained in this paper. A review of other methods, in particular, those related to detectability of changes in emissions, can be found in Jonas et al. (2004a; 2004b)."