An Oligopoly Game of CDR Strategy Deployment in a Steady-State Net-Zero Emission Climate Regime

In this paper, we propose a simple oligopoly game model to represent the interactions between coalitions of countries in deploying carbon dioxide removal (CDR) strategies in a steady-state net-zero emission climate regime that could take place by the end of the twenty-first century. The emission quotas and CDR activities obtained in the solution of this steady-state model could then be used as a target for end-of-period conditions in a dynamic integrated assessment analysis studying the transition to 2100. More precisely, we analyze a steady-state situation where m coalitions exist and behave as m players in a game of supplying emission rights on an international emission trading system. The quotas supplied by a coalition must correspond to the amount of CO₂ captured through CDR activities in the corresponding world region. We use an extension of the computable general equilibrium model GEMINI-E3 to calibrate the payoff functions and compute an equilibrium solution in the noncooperative game.

     

A General Equilibrium Assessment of Climate Change Impacts on Swiss Winter Tourism with Adaptation

Winter alpine tourism has been repeatedly identified as one of the economic sectors most at risk from climate change in Switzerland. However, all of the costs that have been estimated so far for the Swiss tourism sector are, to some extent, misleading as they do not, or only partially, incorporate adaptation possibilities and general equilibrium effects. We attempt to fill this gap using a computable general equilibrium model that is specifically designed for the purposes of this research. Our modeling efforts first consist in creating a tourism sector with a part of it being dependent on snow. We also carefully model the snowmaking technology. Using climate change scenarios on future snow cover, we analyze their impacts on the Swiss ski industry. We find welfare effects for the Swiss economy ranging from − 23 to 113 million CHF in 2050. This range arises from the use of various assumptions concerning adaptation possibilities. We also show that geographical substitutions between international ski destinations have large positive effects for Switzerland. From a more general perspective, our results exemplify the risks of estimating the consequences of climate change based only on domestic impacts of climate change with no adaptation being implemented.

     

Pareto-Improving Supply Subsidy in a Simple General Oligopoly Equilibrium Model with Pollution Permits

We introduce a competitive pollution permit market in a two-sector oligopoly equilibrium model. In this model, one commodity is inelastically supplied by one competitive trader and another one is produced by a finite set of oligopolists, using the first commodity as an input. The production of the second commodity is a polluting activity. We study both the competitive and oligopoly equilibria. We provide some conditions under which a supply subsidy given to the oligopolists that is financed by a tax on the competitive agent is Pareto-improving.

     

Three-dimensional Modelling of Radionuclides Dispersion in a Marine Environment with Application to the Fukushima Dai-ichi Case

In this work, we present the implementation, verification and validation of a three-dimensional model able to reproduce the propagation of \(^{137}C_{s}\) radionuclide in coastal waters and its interaction with suspended sediments, in the framework of the open-source TELEMAC-MASCARET modelling system. The validation of the model was realized by comparing numerical results with field measurements of radionuclides concentration in the Japan Sea nearby the Fukushima Dai-ichi nuclear power plant (NPP). The developed model uses as external forcing the data available immediately after or during the accident, as, e.g. weather conditions (wind, pressure, temperature) and/or the harmonic components of tides. In contrast with previous models implemented in the study area, the model presented here is limited to the coastal area near Fukushima and refined in the coastal area close to the NPP. Numerical results show that the model is able to reproduce the propagation and diffusion of the released \(^{137}C_{s}\) in the vicinity of the Fukushima Dai-ichi NPP. Consequently, we show that the numerical results obtained with a small-scale model with a simple forcing are consistent, at a coastal scale, with models which employed a general circulation model based on data assimilation techniques or variation method for hydrodynamics. Therefore, this model could be employed in an emergency situation, when the dissolved radioactivity is considered.

     

Socioeconomic Risks of Extreme El Niño Event-Related Road Damages in Peru

This study evaluates the socioeconomic risk that extreme El Niño event-related road damages present to Peru by combining an environmental modelling of events’ occurrences in the country with a quantitative modelling of their effects on its economy. The dynamic of occurrence of events is modelled as a stochastic process with a vector autoregressive representation based on historical climatic data, and simulated over a 10-year period with a non-parametric bootstrap procedure. The indirect consequences of events’ related road damages are addressed with a multiregional dynamic computable general equilibrium model through an increase in interregional transportation costs and, more originally, a negative externality effect on activities’ output, which is estimated beforehand using a firm database. We find that extreme El Niño events constitute a significant one-off disaster risk for the country, threatening shifts of???2.8% in GDP and?+?1.9% in poverty rates with an annual probability p?=?1.4%. We further show that they also present a longer-term risk, leading to average annual deviations from normal trend by???0.8% in GDP and?+?0.4% in poverty rate with a probability p?=?12.6% over a 10-year period. However, we finally show that Peru might reduce these socioeconomic risks associated with these non-frequent but recurrent climatic shocks in constructing more disaster-resilient road infrastructure.

     

Effect of dehydrogenase,phosphatase and urease activity in cotton soil after applying thiamethoxam as seed treatment

Soil enzymes are indicators of microbial activities in soil and are often considered as an indicator of soil health and fertility. They are very sensitive to the agricultural practices, pH of the soil, nutrients, inhibitors and weather conditions. To understand the effect of an insecticide, thiamethoxam, on different soil enzyme activities, the experiments were conducted at cotton experimental fields of Punjab Agricultural University, Ludhiana. The results here were presented to understand the impact of thiamethoxam on soil enzyme activities. Thiamethoxam was applied as seed treatment to control the pest. Soil from three localities, i.e. soil in which seed was treated with recommended dose at 2.1 g a.i. kg^?1, soil in which seed was treated with four times recommended dose at 8.4 g a.i. kg^?1 and from the control field, were tested for different enzyme activities. Phosphatase and dehydrogenase activities were high in control soil in comparison to control soil while no effect of this insecticide on urease activity. Thiamethoxam had inhibitory effects on dehydrogenase and phosphatase activities. Therefore, it can be attributed that agricultural practices, weather conditions and use of thiamethoxam might be responsible for the different level of enzyme activities in soil.     

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.     

Interval-Parameter Conditional Value-at-Risk Two-Stage Stochastic Programming Model for Management of End-of-Life Vehicles

The management of end-of-life vehicles conserves natural resources, provides economic benefits, and reduces water, air, and soil pollution. Sound management of end-of-life vehicles is vitally important worldwide thus requiring sophisticated decision-making tools for optimizing its efficiency and reducing system risk. This paper proposes an interval-parameter conditional value-at-risk two-stage stochastic programming model for management of end-of-life vehicles. A case study is conducted in order to demonstrate the usefulness of the developed model. The model is able to provide the trade-offs between the expected profit and system risk. It can effectively control risk at extremely disadvantageous availability levels of end-of-life vehicles. The formulated model can produce optimal solutions under predetermined decision-making risk preferences and confidence levels. It can simultaneously determine the optimal long-term allocation targets of end-of-life vehicles and reusable parts as well as capital investment, production planning, and logistics management decisions within a multi-period planning horizon. The proposed model can efficiently handle uncertainties expressed as interval values and probability distributions. It is able to provide valuable insights into the effects of uncertainties. Compared to the available models, the resulting solutions are far more robust.

     

An Integrated Multicriteria Decision Analysis System for Reducing Air Emissions from Mining Process

The selection of a best alternative method to minimize air pollution and energy consumption for mine sites is a critical task because it encompasses evaluation of different techniques. The aim of this paper is to select most suitable technology for mining system which helps in reducing air pollution and carbon footprints by implementing the multicriteria decision analysis (MCDA) method. The existing methods or frameworks in the mining sector, which have been used in the past to select the sustainable solution, are lacking aid of MCDA, and there is a need to contribute more in this field with a promising decision system. The MCDA method is applied as a probabilistic integrated approach for a mine site in Canada. The analysis involves processing inputs to the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) method which assists in identifying the alternatives, defining the criteria, and thus outranking of the final choice. Moreover, criteria weighting has been determined using analytical hierarchical process (AHP) method. Three categories: reduction of dust/fugitive emission control strategies, reduction in fuel consumption to minimize carbon footprint, and cyanide destruction methods are selected. The probability distributions of criteria weights and output flows are defined by performing uncertainty analysis using the Monte Carlo simulation (MCS). The sensitivity analysis is conducted using Spearman’s rank correlation method and walking criteria weights. The results indicate that the integrated framework provides a reliable way of selecting air pollution control solutions and help in quantifying the impact of different criteria for the selected alternatives.

     

Colloid-Associated Groundwater Contaminant Transport in Homogeneous Saturated Porous Media: Mathematical and Numerical Modeling

During the past two decades, significant efforts have been made to study contaminant transport in the presence of colloids. Several researchers reported that colloidal particles could enhance the migration of contaminants in groundwater by reducing retardation factor. When the colloidal particles are present in the aquifer, the subsurface system can be considered as a three-phase system with two solid phases and an aqueous phase. The interaction between contaminants, colloids, and solid matrix should be considered in assessing the fate and transport of the contaminant in the groundwater flow system. In this study, a one-dimensional numerical model is developed by employing a fully implicit finite difference method. This model is based on mass balance equations and mass partition mechanisms between the carriers and solid matrix, as well as between the carriers and contaminants in a saturated homogeneous porous medium. This phenomenon is presented by two approaches: equilibrium approach and fully kinetic first-order approach. The formulation of the model can be simplified by employing equilibrium partitioning of particles. However, contaminant transport can be predicted more accurately in realistic situations by kinetic modeling. To test the sensitivity of the model, the effect of the various chemical and physical coefficients on the migration of contaminant was investigated. The results of numerical modeling matched favorably with experimental data reported in the literature.     

Water Quality Prediction of Water Sources Based on Meteorological Factors using the CA-NARX Approach

With the increasingly serious problem of surface water environmental safety, it is of great significance to study the changing trend of reservoir water quality, and it is necessary to establish a water quality prediction and early warning system for the management and maintenance of water resources. Aiming at the problem of water quality prediction in reservoirs, a CA-NARX algorithm is designed, which combines the improved dynamic clustering algorithm with the idea of machine learning and the forward dynamic regression neural network. The improved dynamic clustering algorithm is used to classify the eutrophication degree of waterbodies according to the total phosphorus and total nitrogen content. Considering four meteorological factors, air temperature, water temperature, water surface evaporation, and rainfall, synthetically for each water quality condition, the total phosphorus and total nitrogen in the waterbody are forecasted by an improved forward NARX dynamic regression neural network. Based on this, the CA-NARX prediction algorithm can realize short period water quality prediction. Compared with the traditional support vector regression machine model, improved GA-BP neural network, and exponential smoothing method, the CA-NARX model has the least prediction error.

     

Bovine calves as ideal bio-indicators for fluoridated drinking water and endemic osteo-dental fluorosis

Relative susceptibility to fluoride (F) toxicosis in the form of osteo-dental fluorosis was observed in an observational survey of 2,747 mature and 887 immature domestic animals of diverse species living in areas with naturally fluoridated (>1.5 ppm F) drinking water. These animals included buffaloes (Bubalus bubalis), cattle (Bos taurus), camels (Camelus dromedarius), donkeys (Equus asinus), horses (Equus caballus), goats (Capra hircus), and sheep (Ovis aries). Of these mature and immature animals, 899 (32.7 %) and 322 (36.3 %) showed evidence of dental fluorosis with varying grades, respectively. Their incisor teeth were stained with light to deep brownish color. On clinical examination, 31.2 % mature and 10.7 % immature animals revealed periosteal exostoses, intermittent lameness, and stiffness of tendons in the legs as signs of skeletal fluorosis. The maximum susceptibility to fluoride toxicosis was found in bovines (buffaloes and cattle) followed by equines (donkeys and horses), flocks (goats and sheep), and camelids (camels). The bovine calves were found to be more sensitive and highly susceptible to F toxicosis and revealed the maximum prevalence (92.2 %) of dental fluorosis. This indicates that bovine calves are less tolerant and give early sign of F poisoning (dental fluorosis) and therefore, they can be considered as bio-indicators for fluoridated water as well as for endemicity of osteo-dental fluorosis. Causes for variation in susceptibility to F toxicosis (fluorosis) in various species of domestic animal are also discussed.     

Solubilities of hydrophobic compounds in aqueous-organic solvent mixtures

Solubilities of several hydrophobic organic substances (paradichlorobenzene, endrin, naphthalene, and dibutyl phthalate) in aqueous solutions containing up to 0.10 mole fraction of common alcohols and ketones, were measured by gas chromatography. The solubilities are significantly increased by the alcohols and ketones. The results are interpreted in terms of the association of n molecules of alcohol or ketone with each hydrophobic organic molecule. Values of n and the equilibrium constant for this association are reported for each hydrophobic organic-alcohol and organic-ketone combination. The implications of these results for the disposal of toxic wastes by landfilling is discussed.     

Evaluation of Pb (II) biosorption utilizing sugarcane bagasse colonized by <Emphasis Type="Italic">Basidiomycetes</Emphasis>

The contamination of water resources by metallic ions is a serious risk to public health and the environment. Therefore, a great emphasis has been given to alternative biosorption methods that are based on the retention of aqueous-solution pollutants; in the last decades, several agricultural residues have been explored as low-cost adsorbent. In this study, the ability of Pb (II) biosorption using sugarcane bagasse modified by different fungal species was evaluated. The presence of carbonyl, hydroxyl, and carboxyl groups in the biosorbent was observed by spectroscopy in the infrared region. By scanning electron microscopy, changes in the morphology of modified material surfaces were observed. The highest adsorption capacity occurred at pH 5.0, while the shorter adsorbate-adsorbent equilibrium was at 20 min, and the system followed the pseudo-second-order model. The maximum biosorption in isotherms was found at 58.34 mg g^?1 for modified residue by Pleurotus ostreatus U2-11, and the system followed the Langmuir isotherm. The biosorption process was energetically spontaneous with low desorption values. This modification showed great potential for filters to remove Pb (II) and provide the preservation of water resources and animal health.     

Applications of behavioral science to biodiversity management in agricultural landscapes: conceptual mapping and a California case study

Regime shifts of major salinity constituents (Ca, Mg, Na, K, SO₄, Cl, HCO₃, and NO₃) in the lower Salinas River, an agricultural ecosystem, can have major impacts on ecosystem services central to continued agricultural production in the region. Regime shifts are large, persistent, and often abrupt changes in the structure and dynamics of social-ecological systems that occur when there is a reorganization of the dominant feedbacks in the system. Monitoring information on changes in the system state, controlling variables, and feedbacks is a crucial contributor to applying sustainability and ecosystem resilience at an operational level. To better understand the factors driving salinization of the lower Salinas River on the central coast of California, we examined a 27-year record of concentrations of major salinity constituents in the river. Although limited in providing an understanding of solute flux behavior during storm events, long-term “grab sampling” datasets with accompanying stream discharges can be used to estimate the actual history of concentrations and fluxes. We developed new concentration–discharge relationships to evaluate the dynamics of chemical weathering, hydrological processes, and agricultural practices in the watershed. Examinations of long-term records of surface water and groundwater salinity are required to provide both understanding and perspective towards managing salinity in arid and semi-arid regions while also enabling determination of the influence of external climatic variability and internal drivers in the system. We found that rock weathering is the main source of Ca, Mg, Na, HCO₃, and SO₄ in the river that further enables ion exchange between Ca, Mg, and Na. River concentrations of K, NO₃, and Cl were associated with human activities while agricultural practices were the major source of K and NO₃. A more direct anthropogenic positive trend in NO₃ that has persisted since the mid-1990s is associated with the lag or memory effects of field cropping and use of flood irrigation. Event to inter-year scale patterns in the lower Salinas River salinity are further controlled by antecedent hydrologic conditions. This study underscores the importance of obtaining long-term monitoring records towards understanding watershed changes-of-state and time constants on the range of driving processes.

     

Use of solvent extraction for the removal of heavy metals from liquid wastes

Solvent extraction is recommended as a suitable method for the removal of heavy metals from the waste waters of the chemical and electronic industries. Common extractants are organic compounds with molecular mass 200–450, almost insoluble in water (5–50 ppm), that selectively extract metals from aqueous solutions. On the basis of data from the literature, the extraction conditions are reviewed for the metals that cause problems in waste waters. The extraction conditions are understood to mean the type of extractant, anion present in the aqueous phase, and pH. As far as the data permit, the metals are ordered according to their extractability by given extractants. Special attention is paid to the main source of contamination of waste waters by heavy metals, namely electroplating plants. Two examples of the design of mixer-settler batteries are presented, which demonstrate continuous removal of heavy metals from the waste waters of electroplating plants to levels below the permissible limits. The first example illustrates removal of cadmium using triisooctylamine in a mixer-settler battery with the pertraction flow-arrangement; the second, removal of zinc and lead from rinse waters using the organophosphoric acid DEHPA (bis (2-ethylhexyl) phosphoric acid) in a battery with counter-current flow and reflux. The extraction equilibrium data were obtained in laboratory experiments using chloride solutions in concentrations close to those in the rinse waters of electroplating plants (erná and Volaufová, 1991).     

The occurrence and hydrochemistry of fluoride and boron in carbonate aquifer system, central and western Estonia

Silurian–Ordovician (S–O) aquifer system is an important drinking water source of central and western Estonia. The fluoride and boron contents of groundwater in aquifer system vary considerably. The fluoride concentration in 60 collected groundwater samples ranged from 0.1 to 6.1 mg/l with a mean of 1.95 mg/l in the study area. Boron content in groundwater varied from 0.05 mg/l to 2.1 mg/l with a mean value of 0.66 mg/l. Considering the requirements of EU Directive 98/83/EC and the Estonian requirements for drinking water quality, the limit value for fluoride (1.5 mg/l) and for boron (1.0 mg/l) is exceeded in 47 and 28 % of wells, respectively. Groundwater with high fluoride and boron concentrations is found mainly in western Estonia and deeper portion of aquifer system, where groundwater chemical type is HCO₃–Cl–Na–Mg–Ca, water is alkaline, and its Ca²⁺ content is low. Groundwater of the study area is undersaturated with respect to fluorite and near to equilibrium phase with respect to calcite. The comparison of TDS versus Na/(Na?+?Ca) and Cl/(Cl?+?HCO₃) points to the dominance of rock weathering as the main process, which promotes the availability of fluoride and boron in the groundwater. The geological sources of B in S–O aquifer system have not been studied so far, but the dissolution of fluorides from carbonate rocks (F?=?100–400 mg/kg) and K-bentonites (F?=?2,800–4,500 mg/kg) contributes to the formation of F-rich groundwater.     

A Computational Fluid Dynamic Model for Prediction of Organic Dyes Adsorption from Aqueous Solutions

Modelling of the removal of synthetic dyes from aqueous solutions by adsorbents is important to develop an appropriate treatment plan using adsorption process. This paper presents a computational fluid dynamic model incorporating the Langmuir isotherm scheme and second-order kinetic expression to describe the adsorption process. The governing equation of the model was numerically solved using PHOENICS software to simulate synthetic dyes adsorption from the aqueous system. The experimental results presented in this study and taken from the literature for the removal of synthetic dyes were compared with those results predicted by the numerical model. The predicted outputs of the model match the experimental measurements satisfactory. A sensitivity analysis of the major parameters that influence the percent of dye removal from solution phase has been carried out. Three of the main parameters taken into account were the kinetic rate constant, amount of dye adsorbed at equilibrium and the Langmuir isotherm constant. It was found that the model is most sensitive to the amount of dye adsorbed at equilibrium. This effect is most obvious at the early stages of the adsorption process when the rate of dye removal is very fast. Quantification of the reaction mechanism allows developing an appropriate remediation strategy based on the adsorption process.     

Grain-size analysis of volcanic ash for the rapid assessment of respiratory health hazard

Volcanic ash has the potential to cause acute and chronic respiratory diseases if the particles are sufficiently fine to enter the respiratory system. Characterization of the grain-size distribution (GSD) of volcanic ash is, therefore, a critical first step in assessing its health hazard. Quantification of health-relevant size fractions is challenging without state-of-the-art technology, such as the laser diffractometer. Here, several methods for GSD characterization for health assessment are considered, the potential for low-cost measurements is investigated and the first database of health-pertinent GSD data is presented for a suite of ash samples from around the world. Methodologies for accurate measurement of the GSD of volcanic ash by laser diffraction are presented by experimental analysis of optimal refractive indices for different magmatic compositions. Techniques for representative sampling of small quantities of ash are also experimentally investigated. GSD results for health-pertinent fractions for a suite of 63 ash samples show that the fraction of respirable (<4 microm) material ranges from 0-17 vol%, with the variation reflecting factors such as the style of the eruption and the distance from the source. A strong correlation between the amount of <4 and <10 microm material is observed for all ash types. This relationship is stable at all distances from the volcano and with all eruption styles and can be applied to volcanic plume and ash fallout models. A weaker relationship between the <4 and <63 microm fractions provides a novel means of estimating the quantity of respirable material from data obtained by sieving.     

Opportunities for Improved Risk Assessments of Exotic Species in Canada Using Bioclimatic Modeling

This paper briefly reviews the process of exotic pest risk assessments and presents some examples of emerging opportunities for spatial bioclimatic modeling of exotic species in Canada. This type of analysis can support risk assessments but does not replace the need for on-going high quality field-based observations to validate and update models. Bioclimatic analysis of several exotic pests is provided to illustrate both opportunities and limits. A link is demonstrated to the National Forest Inventory to characterize timber volumes at risk for one exotic species. Challenges' are both scientific and administrative. More accessible and current field survey data are required to improve models. Our experience is that for many exotic species, historical, and even current, data are not always digital or quality controlled for taxonomic identity and accurate geo-referencing. This inhibits their use for integrated spatial modeling applications.