Kyoto commitments: macro and micro insights on trading and the Clean Development Mechanism

The purpose of this paper is twofold. First, we raise some issues related to the expected dimension of the carbon market. This analysis is based on a survey of model results on the implementation of the Kyoto goal with and without reliance on emissions trading. In particular, we consider both the emissions and the financial implications associated with different trading scenarios. Transfers related to international GHG trading might be equivalent to a 400% increase in foreign direct investment to countries with economies in transition. A closer look at the GHG reductions expected from the developing world also suggests that global models may be overly optimistic in their assessment of the contribution of flexibility mechanisms in meeting the Kyoto emission goals. OECD countries may need to rely more on domestic policies to reduce their emissions than what has so far been projected by global models. Second, we use a simple microeconomic model to test the potential contribution of typical power generation technologies in the context of the Clean Development Mechanism. Projects that are defined as additional in terms of the environment but already profitable can bring about significant results at a relatively low price of certified emission reductions. To assume that the contribution of the CDM will come close to what is projected by global models (both for prices and quantities) is to assume that such projects could be credited under the CDM. This revised version was published online in July 2006 with corrections to the Cover Date.     

Mixed Integer Linear Programming Models for Selecting Ground-Level Ozone Control Strategies

The traditional strategy for ground-level ozone control is to apply emission reductions across the board throughout certain time periods and locations. In this paper, we study various mixed integer linear programming (MILP) models that seek to select targeted control strategies for the Dallas Fort-Worth (DFW) region to reduce emissions, in order to achieve the State Implementation Plan (SIP) requirements with minimum cost. Statistics and optimization methods are used to determine a potential set of cost-effective control strategies for reducing ozone. These targeted control strategies are specified for different types of emission sources in various time periods and locations. Three MILP models, a static model, a sequential model, and a dynamic model, are studied in this research. These different MILP models allow decision makers to study how the targeted control strategies change under different circumstances. Meanwhile, two types of auxiliary variables are considered as supplemental control strategies in the optimization if the current set of control strategies is unable to reduce ozone to comply with the 8-h ozone standard. Results from the different models can provide decision makers with information concerning how the effectiveness of the control strategies varies with daily emission patterns and meteorology.     

Marginal Abatement Costs and Marginal Welfare Costs for Greenhouse Gas Emissions Reductions: Results from the EPPA Model

Marginal abatement cost (MAC) curves, relationships between tonnes of emissions abated and the CO₂ (or greenhouse gas (GHG)) price, have been widely used as pedagogic devices to illustrate simple economic concepts such as the benefits of emissions trading. They have also been used to produce reduced-form models to examine situations where solving the more complex model underlying the MAC is difficult. Some important issues arise in such applications: (1) Are MAC relationships independent of what happens in other regions?, (2) are MACs stable through time regardless of what policies have been implemented in the past?, and (3) can one approximate welfare costs from MACs? This paper explores the basic characteristics of MAC and marginal welfare cost (MWC) curves, deriving them using the MIT Emissions Prediction and Policy Analysis model. We find that, depending on the method used to construct them, MACs are affected by policies abroad. They are also dependent on policies in place in the past and depend on whether they are CO₂-only or include all GHGs. Further, we find that MACs are, in general, not closely related to MWCs and therefore should not be used to derive estimates of welfare change. We also show that, as commonly constructed, MACs may be unreliable in replicating results of the parent model when used to simulate GHG policies. This is especially true if the policy simulations differ from the conditions under which the MACs were simulated.     

Environmental impact of electricity relocation: A quasi-natural experiment from interregional electricity transmission

Pollutants such as sulfur would concentrate in the source regions and thus the localized impacts are more obvious. Local balance of electricity by transporting coal has resulted in dense concentration of coal-fired power plants in load centers and caused severe environmental problems. Electricity relocation through interregional transmission is another choice for energy transportation to achieve electricity balance across regions and pollution mitigation. Using interregional electricity transmission (IRET) lines in China as a quasi-natural experiment, this paper assesses the environmental impact of electricity relocation. In the assessment, the grid organization of “province as executor” in China is considered because it affects the sphere of IRET's influence on pollution mitigation. Here we show the environmental benefits of electricity relocation. We find that, electricity relocation through interregional transmission leads to the growth rate of sulfur dioxide (SO₂) emission decreasing 7% in landing areas and Sichuan province benefits most from electricity relocation. It is interesting that there is no significant increase of SO₂ emission growth rate in sending areas compared to counterfactuals if there had no IRET due to more integration of clean energy and improved emission efficiency in sending areas. Placebo study and robustness check show that the results are quite convincing. Therefore, IRET provides an appealing choice for China's environmental control in eastern region, and it is not necessarily at the cost of pollution in western region. The methodology can be applied to assess the environmental impacts of other program or policy elsewhere.     

Review of PSR framework and development of a DPSIR model to assess greenhouse effect in Taiwan

In dealing with the complex issues of greenhouse gas (GHG) emission and climate change mitigation, many interrelated factors such as cost, level of technology development, supply and demand of energy, structure of industry, and expenditures on research and development exist. Using indicators to monitor environmental impacts and evaluate the efficacies of policies and regulations has been practiced for a long time, and it can serve as a useful tool for decision making and for comparison between different countries. Although numerous indicators have been developed for relevant subjects, integrated approaches that consider individual changes, dynamic interaction, and multi-dimensions of indicators are scarce. This paper aimed to develop a Driving Force-Pressure-State-Impact-Response (DPSIR) framework to assess the problems. This DPSIR model is mainly related to energy consumption, environmental impacts, and policy responses. The objectives of the paper were: (1) conduct a literature review on the indicators that have been used in GHG-related studies; (2) develop a DPSIR model that incorporates GHG-related indicators and evaluate their relationships using a cause?Ceffect chain of GHG emission; and (3) develop a calculative method that can be used to explain the dynamic correlation among the interdependent indicators. Taiwan is a significant source of global GHG emissions. A case study, using the developed framework and Taiwan??s actual data of the past two decades, was conducted. The results indicate that regulatory strategies for pollution control are inadequate in terms of ensuring environmental quality, and the nature does not have the capability to revert the impacts from the existing level of pollution.     

An Integrated Assessment by Models for Energy Systems Analysis and Life-Cycle Assessment with a Case Study of Advanced Fossil-Fired Power Plants in China

We developed an integrated assessment (IA) using models for energy systems analysis and life-cycle assessment (LCA). Based on this assessment framework, we developed cost-benefit analysis (CBA) case studies for a hypothetical project designed to introduce advanced fossil-fired power generation technologies in China. Our MARKAL model for Japan confirmed that radical reductions (i.e., 80 % by 2050) of carbon dioxide (CO₂) could be attained from energy systems alone and that credit for emission allowances was required. We evaluated life-cycle costs and emissions of carbon dioxide, sulfur oxide, and nitrogen oxide gases for the energy technologies using an LCA model. Further, we applied a power generation planning model for six Chinese grids to provide a power mix structure, potentially producing credit by installing fossil-fired power generation technology and by using baseline grid emission factors with an average cost of electricity. Finally, by using dynamic emission reductions and additional costs from the two models, we conducted case studies of CBA for a hypothetical project to install the technologies in China. This was accomplished by evaluating emission reductions in monetary terms and by applying a life-cycle impact assessment model. A unique feature of our IA is its dynamic (time-varying) assessment of costs and benefits.     

Assessing Potential for Recovery of Biotic Richness and Indicator Species due to Changes in Acidic Deposition and Lake ph in Five Areas of Southeastern Canada

Biological damage to sensitive aquatic ecosystems is among the most recognisable, deleterious effects of acidic deposition. We compiled a large spatial database of over 2000 waterbodies across southeastern Canada from various federal, provincial and academic sources. Data for zooplankton, fish, macroinvertebrate (benthos) and loon species richness and occurrence were used to construct statistical models for lakes with varying pH, dissolved organic carbon content and lake size. pH changes, as described and predicted using the Integrated Assessment Model (Lam et al., 1998; Jeffries et al., 2000), were based on the range of emission reductions set forth in the Canada/US Air Quality Agreement (AQA). The scenarios tested include 1983, 1990, 1994 and 2010 sulphate deposition levels. Biotic models were developed for five regions in southeastern Canada (Algoma, Muskoka, and Sudbury, Ontario, southcentral Québec, and Kejimkujik, Nova Scotia) using regression tree, multiple linear regression and logistic regression analyses to make predictions about recovery after emission reductions. The analyses produced different indicator species in different regions, although some species showed consistent trends across regions. Generally, the greatest predicted recovery occurred during the final phase of emission reductions between 1994 and 2010 across all taxonomic groups and regions. The Ontario regions, on average, were predicted to recover to a greater extent than either southcentral Québec or the Kejimkujik area of Nova Scotia. Our results reconfirm that pH 5.5–6.0 is an important threshold below which damage to aquatic biota will remain a major local and regional environmental problem. This damage to biodiversity across trophic levels will persist well into the future if no further reductions in sulphate deposition are implemented.     

The GTP of Methane: Modeling Analysis of Temperature Impacts of Methane and Carbon Dioxide Reductions

The Global Temperature Potential (GTP) has recently been proposed as an alternative to the Global Warming Potential (GWP). Using two different Earth Models of Intermediate Complexity, we show that the solution to the 100-year sustained GTP for methane is significantly larger than the equivalent GWP due to the inclusion of future changes in greenhouse gas concentrations in the reference scenario and different atmospheric chemistry assumptions. This result suggests that methane reductions may be undervalued when using GWPs, but the policy implications depend on how the objectives of greenhouse gas policy are defined.     

The FAIR model: A tool to analyse environmental and costs implications of regimes of future commitments

This article describes the policy decision-support tool, FAIR, to assess the environmental and abatement costs implications of international regimes for differentiation of future commitments. The model links long-term climate targets and global reduction objectives with regional emission allowances and abatement costs, accounting for the Kyoto Mechanisms used. FAIR consists of three sub-models: a simple climate model, an emission-allocation model and a cost model. The article also analyses ten different rule-based emission allocation schemes for two long-term concentration stabilisation targets for greenhouse gases. This analysis shows that evaluating regimes requires not only an assessment of the initial allocation, but also of the distribution of abatement costs and the impacts from emissions trading. The Multi-Stage approach (with a gradual increase of Parties adopting emission intensity or reductions targets) and the Triptych approach (with sectoral targets for all Parties) seem to provide the best prospects for most of the Parties when compared to the other allocation schemes analysed.     

Modelling and assessing inter-regional trade of CO2 emission reduction units

A cost-efficient way to allocate carbon dioxide (CO₂) emission reductions among countries or regions is to harmonise their marginal reduction costs. This could be achieved by a market of emission reduction units (ERUs). To model such a market, we use a multi-regional MARKAL-MACRO model. It gives insights into the consequences of co-ordinating CO₂ abatement on regional energy systems and economies. As a numerical application, we assess the establishment of a market of ERUs among three European countries for curbing their CO₂ emissions.     

Examining the uncertainty of carbon emission changes: A systematic approach based on peak simulation and resilience assessment

Efforts to achieve carbon peak is one of the Chinese government's commitments, but the diversity of future development paths leads to the uncertainty of carbon emissions. Based on the carbon peak simulation, this study develops a framework to assess the carbon emission uncertainty, aiming to explore the potential low-carbon paths. The STIRPAT model is firstly introduced to explore the influence of population, economic and technology factors on carbon emissions, which is followed by emission peaks simulation. The resilience theory is then introduced to define the concept of low-carbon resilience (LCR), which refers to the ability to maintain a low level of carbon emissions. The uncertainty of carbon emission changes between different scenarios is identified by considering peaking time, cumulative increase and mitigation process. This study taking 10 Chinese coastal provinces as an example, and results show that all provinces can achieve the target of carbon emission peak in low-emissions scenario, the cumulative growth of carbon emissions is low and can be mitigated over a relatively short term, showing a strong LCR. In high-emissions scenario, Liaoning, Tianjin, Fujian and Guangxi may not have a peak before 2050, the uncertainty of carbon emission changes is relatively high, while Hebei, Jiangsu, Shanghai and Guangdong show relatively low uncertainty for the clear peaking time. The study also designs intermediate scenario to reduce the uncertainty of carbon emission changes to provide reference for each province's emission reduction path. These findings help to understand carbon uncertainty to reduce the risk of increasing cumulative emissions under the scenario of only focusing on peaking times, and provide a basis for future carbon resilience and sustainable emission reduction policies.     

Analysis of the decision-support function of policy assessment in real-world policy making in the field of poverty and social inequalities. Case study on migrant integration policies in the Brussels-Capital Region

Despite its high potential to support decision-making, the role of policy assessment in real-world policy making in the field of poverty and social inequalities remains largely questioned. In this study, we analyse policy assessment's role in a context of real-world policymaking, by means of a case study on a legislative proposal on integration policy for immigrant newcomers in the Brussels-Capital Region, for which we evaluate the potential effects on poverty and social inequalities. We first analyse the policy process surrounding the policy proposal – a process that is often treated as a black box within policy assessment research. Understanding the factors that influence and determine the decision-making process, enables us to gain insight into the potential decision-support function(s). Second, we develop an approach to policy assessment that aims to fully exploit its potential to contribute to the functions of both instrumental and conceptual learning. For this purpose, we propose to introduce the approach of realist evaluation and to focus on evaluating the underlying policy intervention theory from the perspective of poverty and social inequalities. Finally, we illustrate this new approach and its added value by applying it to the legislative proposal on integration policy and analyse its contribution to policy-oriented learning.     

Development and Application of Urban High Temporal-Spatial Resolution Vehicle Emission Inventory Model and Decision Support System

This paper reports on the development and application of an urban high temporal-spatial resolution vehicle emission inventory model and decision support system based on the current situation in China and actual vehicle emission control requirements. The system incorporates a user-friendly modular architecture that integrates a vehicle emission model and a decision support platform and includes scenario analysis and visualisation capabilities. A bottom-up approach based on localised emission factors and actual on-road driving condition has been adopted to develop the system. As a case study of application and evaluation, an emission reduction effect analysis of the supposed low-emission zone (LEZ) policy in Beijing (2012) was conducted. According to the simulated results in the forms of tables, histograms and grid maps, the establishment of this LEZ had a definite effect on the emission reduction of various types of air pollutants, especially carbon monoxide and hydrocarbon. In the system, the simulation methodology for identifying environmental benefits brought by the LEZ policy could be used to assess other similar environmental policies. Through flexible modification of configuration values or input data variables, the efficacy of separate or joint policies could be quantifiably evaluated and graphically displayed.     

Combining Stochastic Optimization and Monte Carlo Simulation to Deal with Uncertainties in Climate Policy Assessment

In this paper, we explore the impact of several sources of uncertainties on the assessment of energy and climate policies when one uses in a harmonized way stochastic programming in a large-scale bottom-up (BU) model and Monte Carlo simulation in a large-scale top-down (TD) model. The BU model we use is the TIMES Integrated Assessment Model, which is run in a stochastic programming version to provide a hedging emission policy to cope with the uncertainty characterizing climate sensitivity. The TD model we use is the computable general equilibrium model GEMINI-E3. Through Monte Carlo simulations of randomly generated uncertain parameter values, one provides a stochastic micro- and macro-economic analysis. Through statistical analysis of the simulation results, we analyse the impact of the uncertainties on the policy assessment.     

Meta-Modeling to Assess the Possible Future of Paris Agreement

In the meta-modeling approach, one builds a numerically tractable dynamic optimization or game model in which the parameters are identified through statistical emulation of a detailed large scale numerical simulation model. In this paper, we show how this approach can be used to assess the economic impacts of possible climate policies compatible with the Paris Agreement. One indicates why it is appropriate to assume that an international carbon market, with emission rights given to different groups of countries will exist. One discusses the approach to evaluate correctly abatement costs and welfare losses incurred by different groups of countries when implementing climate policies. Finally, using a recently proposed meta-model of game with a coupled constraint on a cumulative CO₂ emissions budget, we assess several new scenarios for possible fair burden sharing in climate policies compatible with the Paris Agreement.     

完善排污权有偿使用和交易政策的探讨

中国开展排污权有偿使用和交易试点以来,经过各试点地区的积极探索取得了实质性进展,环境容量的资源意识不断得到提升,部分地区已经初步建立了排污指标有偿使用和交易机制.由于此项工作尚处于起步和探索阶段,仍存在政策和法律滞后、与其他政策关联不足、试点范围局限等问题.提出从完善立法、加强政策关联、注重政策公平以及扩大试点范围等推...     

Determinants of land take at the regional scale: a study concerning Sardinia (Italy)

In its “Roadmap to a Resource Efficient Europe” (Communication COM(2011) 571 of 20 September 2011), the European Commission (EC) established an ambitious goal for the European Union (EU), that of achieving no land take by 2050; towards this aim, a key milestone for the year 2020 was set, by stating that European policies in the programming period 2014–2020 ought to consider both their direct and their indirect impacts on land use in the EU.Within this framework, this paper builds upon the findings of a previous paper (Zoppi and Lai, 2014), in which we estimated the magnitude of land take over a short period of time (2003–2008) in Sardinia, an Italian NUTS2 region, and we assessed whether and how land take is related to a set of variables that are regarded as important determinants in the literature, such as parcel size, accessibility, and proximity to main cities and towns, to the coastline, or to protected areas.In this paper we study the land-taking process taking Sardinia as a case study, in two larger time periods, 1960–1990 and 1990–2008. We assess if, and to what extent, these factors reveal similar, or different, effects in the two periods, and try to identify consistencies concerning the determinants of land take.     

Vector-Borne Diseases, Development & Climate Change

Vector-borne diseases are feared to extend their range in a future where global warming has occurred. There is considerable concern about scourges such as malaria re-invading currently temperate regions and reaching into higher altitudes in Africa. In this paper we examine the various factors thought to determine potential infectivity of malaria, and its actual outbreak in the context of a dynamic integrated assessment model. We quantify: (i) the role of demographics in placing a larger population in harms way; (ii) the role of climate change in increasing the potential geographic range and severity of the risk of infection; and (iii) the role of economic and social development in limiting the occurrence of malaria. We then explore the climate and economic implications of various climate policies in their effectiveness to limit potential infectivity of malaria. In illustration of these issues we present the climate-related and economics-related impacts of unilateral CO₂ control by OECD on incidence of malaria in non-OECD nations. The model presented here, although highly stylized in its representation of socio-economic factors, provides strong evidence of the role of socio-economic factors in determination of malaria incidence. The case study offers insights into unintended adverse consequences of well-meaning climate policies. This revised version was published online in July 2006 with corrections to the Cover Date.     

Regulation of pesticide discharge into surface and groundwater under uncertainty: A model for environmental risk‐profitability tradeoffs and policy selection

The presence of contaminants in environmental media as well as the desire to maintain a high level of economic activity has led to an important and difficult decision‐making problem for both public policy decision makers and the general public. In one sense, all of the interested parties are likely to be concerned about the potential health risks posed by the presence of contaminants in environmental media and the need to design/implement policies for their mitigation and/or removal. At the same time, however, there also appear to be concerns about the cost of these policies. These costs could be measured in terms of the potential losses in economic activity that are likely to occur when a policy is adopted. The policy can be selected from a range of alternatives, with the choice being driven in part by the stakeholders represented in the policy decision problem. In this case, two general goals might be considered: minimizing environmental risk and minimizing the economic impact of the policy considered. These two objectives are likely to be viewed as conflicting goals, and the nature of the tradeoffs between them must be taken into account in the policy selection process. This paper presents the development of a zero–one weighted goal programming model that can be used to select a preferred policy that minimizes surface and groundwater contamination as well as the economic costs of environmental policy selection. A safety rule model is developed first and then extended to the zero–one weighted goal programming formulation. The stochastic aspects of these structures are emphasized throughout. The paper also addresses a number of issues related to implementation of the model.     

南京市机动车污染物减排因素分析

以南京市机动车排污监控系统的实时检测数据为基础,简述了南京市机动车减排效果,在“十二五”期间南京市机动车保有量增长71.8%的背景下,实现了污染物排放量削减18.8%,单车平均排放CO、HC、NOx较3年前分别下降了33%,31%和36%;排放标准和使用年限二因素方差分析表明,其对NOx、CO和HC排放值的影响由大到小排序均为：油品质量〉排放标准〉使用年限。提出,进一步提升油品质量至关重要。