Coupling climate and economic models in a cost-benefit framework: A convex optimisation approach

In this paper, we present a general method, based on a convex optimisation technique, that facilitates the coupling of climate and economic models in a cost-benefit framework. As a demonstration of the method, we couple an economic growth model à la Ramsey adapted from DICE-99 with an efficient intermediate complexity climate model, C-GOLDSTEIN, which has highly simplified physics, but fully 3-D ocean dynamics. As in DICE-99, we assume that an economic cost is associated with global temperature change: this change is obtained from the climate model, which is driven by the GHG concentrations computed from the economic growth path. The work extends a previous paper in which these models were coupled in cost-effectiveness mode. Here we consider the more intricate cost-benefit coupling in which the climate impact is not fixed a priori. We implement the coupled model using an oracle-based optimisation technique. Each model is contained in an oracle, which supplies model output and information on its sensitivity to a master program. The algorithm Proximal-ACCPM guarantees the convergence of the procedure under sufficient convexity assumptions. Our results demonstrate the possibility of a consistent, cost-benefit, climate-damage optimisation analysis with a 3-D climate model.     

A modular approach to Integrated Assessment modeling

In this paper, we present a new approach to model coupling that probably forms the methodological basis of a new generation of Integrated Assessment models. This approach respects the knowledge and expertise that is embodied in existing models and encourages their gradual evolution. Modularity is the guiding principle. Our approach is distinguished by the way modules are coupled which is based on an interplay of a job control module, a numerical coupling module, and a couple of stand-alone functional modules. The numerical coupling module - the core component - serves to treat the feedbacks between the functional modules. A first implemented example that couples an economic and a climate module by means of a two-phase meta-optimization is presented here. The algorithm and mathematical structure behind are discussed as well as important features such as convergence behavior and reliability.     

人工神经网络用于铅的化学形态模拟计算

用前馈线性网络法求解水体系中Ｐｂ（２＋）与ＯＨ－之间的反应常数，不同训练算法对求解结果的精度、收敛速度及权值均有影响．结果表明，批处理算法的精度最好，权值不出现负值，但运算时间最长；在线算法的精度虽不如批处理算法，而比数据变换－在线算法好，权值有时会出现负值．运算时间较长；数据变换－在线算法的优点是运算时间短，但相对误差较大，权值出现负值的机会多。采用反馈网络模拟计算铅的各种化学形态的浓度．用物料核算的方法对反馈网络模型进行检验表明，此种模型用于平衡计算是可行的，详细分析了理论模拟和实验曲线的差异的原因，温度的影响最小，在４＜ｐＨ＜９时，ＣＯ有重要的影响．在国代检验时，ｎ值取整所引入的误差的影响亦不可忽视。从本文的结果可以看到，采用前馈网络和反馈网络相结合的方法考察水体中的化学形态是可行的．从而为解决这一类问题提供了一种可能的途径．     

The spatial convergence and drivers of environmental efficiency under haze constraints - Evidence from China

Haze has seriously threatened the ecological environment and public health, so researching environmental efficiency under haze constraints is significant in managing pollution and evaluating the balance between economic development and environmental health. Based on the panel data of China's 99 cities during 2005–2017, this paper uses α-convergence and β-convergence models to analyze the spatial convergence of environmental efficiency under haze constraints and its drivers in China,specifically in Eastern China, Central China, and Western China.The main results are as follows: (1) The trend of environmental efficiency under haze constraints in these regions evidently follows a dumbbell curve. In recent years, it has been growing slowly in Eastern China, Central China, and Western China, and the environmental efficiency in the Eastern China is the highest, the Central China is the second, and the Western China is the lowest; (2) it demonstrates both α-convergence and β-convergence in Central China, Western China, and Eastern China, and the speed of convergence is the fastest in the Central China, the second in the Western China and the slowest in the Eastern China; there is a “catch-up effect” in cities from less environmentally efficient regions to more efficient regions; and (3) Industrial structure and degree of trade dependence have a significantly negative correlation; characteristics of the region and dependence on foreign investment have significantly positive correlations with the environmental efficiency of Eastern China and Central China; environmental regulations and economic scale limit the improvement of environmental efficiency of Central China and Western China; and technological innovation significantly impacts Eastern China only. Although the paper refers to the specific evidence of China, with haze as a new indicator in the comprehensive evaluation of environmental efficiency can be extended to other developing countries as well as to other pollutants such as land pollution and waste water. The understanding of drivers of environmental efficiency under haze constraints in China provides international policy-makers with valuable reference for formulating effective measures to balance the dilemma between economic development and environmental health.     

Playing Pollution Games with Thermal Electricity Generators

This paper discusses the economic and environmental implications of a stylised electricity market with transmission grid constraints and shared temporal pollution standards that restrict the joint strategy space of the agents. These are problematic to enforce if individual monitoring is impossible or very expensive. For such situations, we propose a time-dependent (or “open-loop dynamic”), game-theoretic model capable of analysing coupled constraints equilibria, also known as generalised Nash. We compute these equilibria for thermal generators subjected to annual pollution limits and instantaneous grid restrictions for a three-node dc model with a two-period load duration curve. The model illustrates the possibility that well-meaning environmental regulation might harm consumer surplus. It also highlights the cost to efficiency of regulatory attempts to ease the burden of compliance.     

Global Emission Ceiling Versus International Cap and Trade: What is the Most Efficient System to Solve the Climate Change Issue?

We model the climate change issue as a pollution control game with the purpose of comparing two possible departures from the business as usual (BAU) where countries noncooperatively choose their emission levels. In the first scenario, players have to agree on a global emission cap (GEC) that is enforced by a uniform taxation scheme. They still behave strategically when choosing emission levels but are now subject to the coupled constraint imposed by the cap. The second scenario consists of the implementation of an international cap and trade (ICT) system. In this case, players decide on their emission quotas, and emission trading is allowed. A three heterogenous player quadratic game serves as a basis for the analysis. When the cap is binding, among all the coupled constraints Nash equilibria, we select a particular normalized equilibrium by solving a variational inequality. Comparing the normalized equilibrium with the Nash equilibria of the BAU and the ICT, we first show that if the cap is appropriately chosen, then the GEC system improves all players’ payoffs, relative to the BAU. The GEC system may thus be unanimously approved whereas the ICT is not, because moving from the BAU to the ICT is costly for one player. Second, for some values of the cap, all players get a higher payoff under the GEC than under the ICT. Therefore, the GEC outperforms the ICT both in terms of feasibility and efficiency.     

An Optimization Model for Integrated Coastal Management: Development and a Case Study Using Italy’s Comacchio Municipality

In this paper, I develop an optimization model for integrated coastal management in which decisions arise from an area-based algorithm that minimizes predicted damage caused by beach erosion and inshore flooding, while accounting for economic, social, and environmental losses. The model favors the involvement of stakeholders in coastal management, but does not use complicated assessment procedures for non-economic indicators or relative weights to combine economic, social, and environmental indicators. Instead, the integration between economic activities or properties and the environmental status and landscape is represented objectively and non-linearly by referring to initial and sustainability conditions, combined with budgetary and environmental constraints. The model successfully accounted for both human and environmental dynamics by depicting delayed effects, neighborhood externalities, and feedback effects. It calculated a single optimal value for each integrated coastal management strategy, which permitted the support of future decisions and the evaluation of past decisions. The model’s insights were based on reliable estimates, with reliability determined by calculating the confidence level. The model was successfully applied to Italy’s Comacchio coastal municipality, where it revealed the priorities for optimal beach nourishment, dune fixation, and residential and holiday housing development based on budget constraints, beach losses, flood damage, pollution impacts, and land-use constraints.     

KLUM@GTAP: Introducing Biophysical Aspects of Land-Use Decisions into a Computable General Equilibrium Model a Coupling Experiment

In this paper, the global agricultural land use model Kleines Land Use Model is coupled to an extended version of the computable general equilibrium model (CGE) Global Trade Analysis Project in order to consistently assess the integrated impacts of climate change on global cropland allocation and its implication for economic development. The methodology is innovative as it introduces dynamic economic land-use decisions based also on the biophysical aspects of land into a state-of-the-art CGE; it further allows the projection of resulting changes in cropland patterns on a spatially more explicit level. A convergence test and illustrative future simulations underpin the robustness and potentials of the coupled system. Reference simulations with the uncoupled models emphasise the impact and relevance of the coupling; the results of coupled and uncoupled simulations can differ by several hundred percent.

Application of the Morris algorithm for sensitivity analysis of the REALM model for the Goulburn irrigation system

The REALM modelling shell is widely used in Australia as a water allocation modelling tool. It has been used to develop the Goulburn System Model (GSM) of the Goulburn, Broken, Loddon and Campaspe Rivers in northeastern Victoria. REALM represents the river and irrigation system as a network of storages and carriers. The model has been optimised to best represent the water harvesting and allocation for use by water management authorities. The model is analysed to assess the sensitivity of a subset of the model outputs, to a subset of the system parameters. The New Morris algorithm uses sampling paths generated in the space of the parameters, to generate points at which the model is run (to generate the model outputs). These model runs are then used to estimate the first and second-order effects of the parameters on the outputs. The results illustrate the mild linkage of the Goulburn and Broken systems, and the Broken system also shows differences between minimum and average outflows. The Goulburn is more sensitive to some of the numerical convergence parameters used in the allocation software, while the Broken is less sensitive to these factors. The numerical convergence factors also lead to important second-order effects.     

A simplified model for reservoir operation considering the water quality issues: Application of the Young conflict resolution theory

In this study, an algorithm combining a multi-objective genetic algorithm (GA)-based optimization model and a water quality simulation model is developed for determining a trade-off curve between objectives related to the allocated water quantity and quality. To reduce the run-time of the GA-based optimization model, the main problem is decomposed to long-term and annual optimization models. The reliability of water supply is considered to be the objective function in the long-term stochastic optimization model, but the objective functions of the annual models are related to both the allocated water quantity and quality. The operating policies obtained using this long-term model provide the time series of the optimum reservoir water storages at the beginning and the end of each water year. In the next step, these optimal reservoir storage values are considered as constraints for water storage in the annual reservoir operation optimization models. The epsilon-constraint method is then used to develop a trade-off curve between the reliability of water supply and the average allocated water quality. The Young conflict resolution theory, which incorporates the existing conflicts among decision-makers and stakeholders, is used for selecting the best solution on the trade-off curve. The monthly reservoir operating rules are then calculated using an Adaptive Neuro-Fuzzy Inference System, which is trained using the optimal operating policies. The proposed model is applied to the 15-Khordad Reservoir in the central part of Iran. The results show that this simplified procedure does not reduce the accuracy of the reservoir operating policies and it can effectively reduce the computational burden of the previously developed models.     

Estimation of Emissions of γ-Hexachlorcyclohexane from the Great Lakes–St. Lawrence Ecosystem Using a Coupled Efficient Kalman Filter–Atmospheric Transport–Soil Model

An efficient linear Kalman filter has been combined with a coupled atmospheric transport and soil–air exchange model to determine organochlorine pesticides emissions on the regional scale. In this study, results of -HCH emissions from the Great Lakes–St. Lawrence ecosystem, estimated from the coupled model, are presented and discussed. A source receptor technique is used to identify a priori the locations of emission sources of -HCH, the emissions are then updated through a Kalman filtering procedure which minimizes the weighted difference between the predicted mixing ratios from the coupled model and the measured concentrations over the Great Lakes–St. Lawrence river region. Two experiments using the inverse algorithm are carried out. In the first experiment, the coupled atmospheric transport and soil–air exchange model is implemented to predict -HCH air and soil concentrations. Emissions are then updated every 12 days using the updated soil concentrations and emission factors. However, the updated emissions are not input into the coupled atmospheric transport and soil–air exchange model. On the other hand, in the second experiment the updated emissions are fed back to the coupled model, so that the model is reinitialized in each 12 days. The results from the inverse technique for the year 1995 have been compared with grided -HCH emission inventory in Canada, generated by emission factors. It is shown that the estimated emissions of -HCH are consistent with the measured emissions. It is found that the St. Lawrence valley has larger emissions of -HCH than the Great Lakes region, indicating an opposite distribution to the emission usage inventory, but in agreement with the measured -HCH concentration.     

A Linear-Programming-Based Strategy for Bioremediation of Oil-Polluted Marine Environments

A linear programming problem is considered with the aim to determine the optimal discharge point and the optimal discharge rate of a nutrient to be released to a marine environment polluted with oil. The objective is to minimize the total discharge of nutrient into the system provided that the concentrations of nutrient will reach critical values sufficient to eliminate oil residuals in certain affected zones through bioremediation. An initial boundary-value 3D problem for the advection–diffusion equation and its adjoint problems are considered to model, estimate, and control the dispersion of nutrient in a limited region. It is shown that the advection–diffusion problem is well posed, and its solution satisfies the mass balance equation. In each oil-polluted zone, the mean concentration of nutrient is determined by means of an integral formula in which the adjoint model solution serves as a weight function. Critical values of these mean concentrations are used as the constraints of linear programming problem. Some additional constraints are posed in order to limit not only the local discharge of the nutrient, but also the mean concentration of this substance in the whole region. Both constraints serve for environmental protection. The ability of the new method is demonstrated by numerical experiments on the remediation in oil-polluted channel using three control zones. The experiments show that the optimal discharge rate can always be got with a simple combination of step functions.     

An Linear Programming Model for Batch Optimization in the Ecological Zinc Production

This paper presents a mathematical model for solving the blending composition problem used in the zinc smelting process. The model proposes an objective function maximizing profit in terms of the total income from the sale of zinc on the market and the cost of producing zinc. In addition to the constraints contained in the basic mathematical model, the constraints, which are in accordance with the specific production process of zinc and environmental requirements, are developed. This paper proposes a model that can align three contradictory demands (technological, economic, and environmental) present in zinc production. The results, obtained by numerical experiments, confirm the assumption that it is possible to assemble such an optimal batch that will “reconcile” all contradictory demands. This model can be applied to other similar processes of production with minor changes.     

Climate Impact Response Functions for Terrestrial Ecosystems

We introduce climate impact response functions as a means for summarizing and visualizing the responses of climate-sensitive sectors to changes in fundamental drivers of global climate change. In an inverse application, they allow the translation of thresholds for climate change impacts (‘impact guard-rails’) into constraints for climate and atmospheric composition parameters (‘climate windows’). It thus becomes feasible to specify long-term objectives for climate protection with respect to the impacts of climate change instead of crude proxy variables, like the change in global mean temperature. We apply the method to assess impacts on terrestrial ecosystems, using the threat to protected areas as the central impact indicator. Future climate states are characterized by geographically and seasonally explicit climate change patterns for temperature, precipitation and cloud cover, and by their atmospheric CO₂ concentration. The patterns are based on the results of coupled general circulation models. We study the sensitivity of the impact indicators and the corresponding climate windows to the spatial coverage of the analysis and to different climate change projections. This enables us to identify the most sensitive biomes and regions, and to determine those factors which significantly influence the results of the impact assessment. Based on the analysis, we conclude that climate impact response functions are a valuable means for the representation of climate change impacts across a wide range of plausible futures. They are particularly useful in integrated assessment models of climate change based on optimizing or inverse approaches where the on-line simulation of climate impacts by sophisticated impact models is infeasible due to their high computational demand. This revised version was published online in July 2006 with corrections to the Cover Date.     

An eco-sustainable green approach for heavy metals management: two case studies of developing industrial region

Multifaceted issues or paradigm of sustainable development should be appropriately addressed in the discipline of environmental management. Pollution of the biosphere with toxic metals has accelerated dramatically since the beginning of the Industrial Revolution. In present review, comparative assessment of traditional chemical technologies and phytoremediation has been reviewed particularly in the context of cost-effectiveness. The potential of phytoremediation and green chemicals in heavy metals management has been described critically. Further, the review explores our work on phytoremediation as green technology during the last 6 years and hand in hand addresses the various ecological issues, benefits and constraints pertaining to heavy metal pollution of aquatic ecosystems and its phytoremediation as first case study. Second case study demonstrates the possible health implications associated with use of metal contaminated wastewater for irrigation in peri-urban areas of developing world. Our researches revealed wetland plants/macrophytes as ideal bio-system for heavy metals removal in terms of both ecology and economy, when compared with chemical treatments. However, there are several constraints or limitations in the use of aquatic plants for phytoremediation in microcosm as well as mesocosm conditions. On the basis of our past researches, an eco-sustainable model has been proposed in order to resolve the certain constraints imposed in two case studies. In relation to future prospect, phytoremediation technology for enhanced heavy metal accumulation is still in embryonic stage and needs more attention in gene manipulation area. Moreover, harvesting and recycling tools needs more extensive research. A multidisciplinary research effort that integrates the work of natural sciences, environmental engineers and policy makers is essential for greater success of green technologies as a potent tool of heavy metals management.     

Prospects and Constraints of Desert Agriculture: Lessons from West Omdurman

Sudan is the largest country in Africa with an area of about 2.5 million km²; the country hosts a population of about 31 million people. About two-thirds of the country area is located within arid and semi-arid regions. Recently, especially during the last half of the previous century, these regions were subject to various forms of land degradation. This paper discusses the general prospects and constraints of desert agriculture. It also presents a detailed case study of West Omdurman, which is located in a semi-desert climatic zone. The ambitious plans to utilise the area for agricultural production were initiated because of the relatively fertile soil, availability of water and the proximity of the area to marketing and export centres. The paper discusses the different land use systems experienced in the area, reasons for failure are identified and possible remedies discussed. In addition, constraints facing the proposed West Omdurman Canal Project are also discussed. Finally, the paper reviews the major research findings of Rawakeeb Dryland Research Center with regard to promoting agricultural productivity.     

An environmental game with coupling constraints

We consider a game where players face environmental constraints. We derive and compare noncooperative, cooperative and umbrella scenarios. In the latter, the players couple their environmental constraints and implement Rosen’s normalized equilibrium. It is shown that the cooperative outcome can be generated as a normalized equilibrium and that the results obtained in the literature do not necessarily generalize to this constrained setting.     

Groundwater quality assessment based on rough sets attribute reduction and TOPSIS method in a semi-arid area, China

In order to enrich and improve the groundwater quality assessment system, a new coupled assessment model based on rough set attribute reduction and the technique for order preference by similarity to ideal solution (TOPSIS) was proposed. The proposed model was applied in the groundwater quality assessment of a semi-arid area, northwest China. The results show that most chemical indices except NH (4) (+) , F(-), and Mn meet the Standards for Drinking Water of China and the groundwater quality overall is good. All assessed water samples are found to be fit for human consumption according to the comprehensive assessment results. Rough set attribute reduction for groundwater quality assessment is practical. The assessment results after attribute reduction show a good consistency with those before attribute reduction. Rough set attribute reduction and TOPSIS evaluation coupled model is clear in ideas and simple in calculation, and evaluation results are reasonable as well. The coupled model can be applied to solve many multiple criteria decision making problems such as groundwater quality assessment.     

A game theoretic approach for interbasin water resources allocation considering the water quality issues

In this paper, a new game theoretic methodology is developed for interbasin water transfer management with regard to economic, equity, and environmental criteria. The main objective is to supply the competing users in a fair way, while the efficiency and environmental sustainability criteria are satisfied and the utilities of water users are incorporated. Firstly, an optimization model is developed to proportionally allocate water to the competing users in water donor and receiving basins based on their water demands. Secondly, for different coalitions of water users, the water shares of the coalitions are determined using an optimization model with economic objectives regarding the physical and environmental constraints of the system. In order to satisfy water-quality requirements, the impacts of decreasing the instream flow in donor basin are estimated using a water-quality simulation model, and the required treatment levels for effluents discharged into the river, downstream of the water transfer point are determined. Finally, to achieve equity and to provide sufficient incentives for water users to participate in the cooperation, some cooperative game theoretic approaches are utilized for reallocation of net benefits to water users. This model is applied to a large-scale interbasin water allocation problem including two different basins struggling with water scarcity in Iran. The results show that this model can be utilized as an effective tool for optimal interbasin water allocation management involving stakeholders with conflicting objectives subject to physical and environmental constraints.     

Urban water resource management for sustainable environment planning using artificial intelligence techniques

In the current era, water is a significant resource for socio-economic growth and the protection of healthy environments. Properly controlled water resources are considered a vital part of development, which reduces poverty and equity. Conventional Water system Management maximizes the existing water flows available to satisfy all competing demands, including on-site water and groundwater. Therefore, Climatic change would intensify the specific challenges in water resource management by contributing to uncertainty. Sustainable water resources management is an essential process for ensuring the earth's life and the future. Nonlinear effects, stochastic dynamics, and hydraulic constraints are challenging in ecological planning for sustainable water development. In this paper, Adaptive Intelligent Dynamic Water Resource Planning (AIDWRP) has been proposed to sustain the urban areas' water environment. Here, an adaptive intelligent approach is a subset of the Artificial Intelligence (AI) technique in which environmental planning for sustainable water development has been modeled effectively. Artificial intelligence modeling improves water efficiency by transforming information into a leaner process, improving decision-making based on data-driven by combining numeric AI tools and human intellectual skills. In AIDWRP, Markov Decision Process (MDP) discusses the dynamic water resource management issue with annual use and released locational constraints that develop sensitivity-driven methods to optimize several efficient environmental planning and management policies. Consequently, there is a specific relief from the engagement of supply and demand for water resources, and substantial improvements in local economic efficiency have been simulated with numerical outcomes.