A rough set-based game theoretical approach for environmental decision-making: A case of offshore oil and gas operations

Environmental decision-making in offshore oil and gas (OOG) operations can be extremely complex due to conflicting objectives or criteria, availability of vague and uncertain information, and interdependency among multiple decision-makers. Most existing studies ignore conflicting preferences and strategic interactions among decision-makers. This paper presents a game theoretical approach to solve multi-criteria conflict resolution problem under constrained and uncertain environments. Uncertainties in the quantification of imprecise data are expressed using rough numbers. A multi-criteria game is developed to model a decision problem in which three groups of decision-makers (i.e., operators, regulators and service engineers) are involved. This game is solved using the generalized maximin solution concept. With the solution (i.e., optimal weights of the criteria), the rough numbers can be aggregated to an expected payoff for each alternative. Finally, the weights of upper and lower limits of a rough number are employed to transform the expected payoff into a crisp score, based on which all alternatives are ranked to identify the best one. A numerical example is outlined to demonstrate the application of the proposed method to the selection of management scenarios of drilling wastes.     

Effects of NO2 and SO2 on selective catalytic reduction of nitrogen oxides by ammonia

The selective catalytic reduction (SCR) characteristics of NO and NO(2) over V(2)O(5)-WO(3)-MnO(2)/TiO(2) catalyst using ammonia as a reducing agent have been determined in a fixed-bed reactor at 200-400 degrees C. The presence of NO(2) enhances the SCR activity at lower temperatures and the optimum ratio of NO(2)/NO(x) is found to be 0.5. During the SCR reactions, there are some side reactions occurred such as ammonia oxidation and N(2)O formation. At higher temperatures, the selective catalytic oxidation of ammonia and the nitrous oxide formation compete with the SCR reactions. The denitrification (DeNO(x)) conversion decreases at lower temperatures but it increases at higher temperatures with increasing SO(2) concentration. The presence of SO(2) in the feeds inhibits N(2)O formation.     

Perspectives of using fungi as bioresource for bioremediation of pesticides in the environment: a critical review

Pesticides are used for controlling the development of various pests in agricultural crops worldwide. Despite their agricultural benefits, pesticides are often considered a serious threat to the environment because of their persistent nature and the anomalies they create. Hence removal of such pesticides from the environment is a topic of interest for the researchers nowadays. During the recent years, use of biological resources to degrade or remove pesticides has emerged as a powerful tool for their in situ degradation and remediation. Fungi are among such bioresources that have been widely characterized and applied for biodegradation and bioremediation of pesticides. This review article presents the perspectives of using fungi for biodegradation and bioremediation of pesticides in liquid and soil media. This review clearly indicates that fungal isolates are an effective bioresource to degrade different pesticides including lindane, methamidophos, endosulfan, chlorpyrifos, atrazine, cypermethrin, dieldrin, methyl parathion, heptachlor, etc. However, rate of fungal degradation of pesticides depends on soil moisture content, nutrient availability, pH, temperature, oxygen level, etc. Fungal strains were found to harbor different processes including hydroxylation, demethylation, dechlorination, dioxygenation, esterification, dehydrochlorination, oxidation, etc during the biodegradation of different pesticides having varying functional groups. Moreover, the biodegradation of different pesticides was found to be mediated by involvement of different enzymes including laccase, hydrolase, peroxidase, esterase, dehydrogenase, manganese peroxidase, lignin peroxidase, etc. The recent advances in understanding the fungal biodegradation of pesticides focusing on the processes, pathways, genes/enzymes and factors affecting the biodegradation have also been presented in this review article.     

Attenuation of Gaseous Pollutants by Greenbelts

The article draws attention towards the importance ofgreenbelts in attenuating gaseous pollutants andpresents the meteorological, physico-chemical,biological, and horticultural dimensions associatedwith effective greenbelt design.We have presented the gist of a system ofmethodologies, developed by us, for greenbelt design. A case study demonstrating the applicability of thesystem has been presented.     

A spatial econometric analysis of convergence in global environmental performance

Environmental Science and Pollution Research - This study intends to test the presence of β-convergence in the global Environmental Performance (EP). For this purpose, spatial Green Solow...     

Ag nanoparticle-decorated chitosan/SrSnO3 nanocomposite for ultrafast elimination of antibiotic linezolid and methylene blue

Environmental Science and Pollution Research - Effective design of ultrafast new-generation photocatalysts is a challenging task that requires highly dedicated efforts. This research focused on the...     

Dynamic risk assessment using failure assessment and Bayesian theory

To ensure the safety of a process system, engineers use different methods to identify the potential hazards that may cause severe consequences. One of the most popular methods used is quantitative risk assessment (QRA) which quantifies the risk associated with a particular process activity. One of QRA's major disadvantages is its inability to update risk during the life of a process. As the process operates, abnormal events will result in incidents and near misses. These events are often called accident precursors. A conventional QRA process is unable to use the accident precursor information to revise the risk profile. To overcome this, a methodology has been proposed based on the work of Meel and Seider (2006). Similar to Meel and Seider (2006) work, this methodology uses Bayesian theory to update the likelihood of the event occurrence and also failure probability of the safety system. In this paper the proposed methodology is outlined and its application is demonstrated using a simple case study. First, potential accident scenarios are identified and represented in terms of an event tree, next, using the event tree and available failure data end-state probabilities are estimated. Subsequently, using the available accident precursor data, safety system failure likelihood and event tree end-state probabilities are revised. The methodology has been simulated using deterministic (point value) as well as probabilistic approach. This Methodology is applied to a case study demonstrating a storage tank containing highly hazardous chemicals. The comparison between conventional QRA and the results from dynamic failure assessment approach shows the significant deviation in system failure frequency throughout the life time of the process unit.     

Revised fire consequence models for offshore quantitative risk assessment

Offshore oil and gas platforms are well known for their compact geometry, high degree of congestion, limited ventilation and difficult escape routes. A small mishap under such conditions can quickly escalate into a catastrophe. Among all the accidental process-related events occurring offshore, fire is the most frequently reported. It is, therefore, necessary to study the behavior of fires and quantity the hazards posed by them in order to complete a detailed quantitative risk assessment. While there are many consequence models available to predict fire hazards-varying from point source models to highly complex computational fluid dynamic models—only a few have been validated for the unique conditions found offshore.

In this paper, we have considered fire consequence modeling as a suite of sub-models such as individual fire models, radiation model, overpressure model, smoke and toxicity models and human impact models. This comprehensive suite of models was then revised by making the following modifications: (i) fire models: existing fire models have been reviewed and the ones most suitable for offshore conditions were selected; (ii) overpressure impact model: a model has been developed to quantify the overpressure effects from fires to investigate the possible damage from the hot combustion gases released in highly confined compartments; (iii) radiation model: instead of a point/area model, a multipoint grid-based model has been adopted for better modeling and analysis of radiation heat flux consequences. A comparison of the performance of the revised models with the ones used in a commercial software package for offshore risk assessment was also carried out and is discussed in the paper.     

Effect of CO on NO oxidation over platinum based catalysts for hybrid fast SCR process

The oxidation characteristics of NO over Pt/TiO2 (anatase, rutile) catalysts have been determined in a fixed bed reactor as a function of O2, CO and SO2 concentrations in the presence of 8% water. The conversion of NO to NO2 increases with increasing O2 concentration up to 12% and it levels off. This saturation effect is more pronounced over rutile-Pt/TiO2 (r-Pt/TiO2) than that of anatase-Pt/TiO2 (a-Pt/TiO2). The presence of CO increases NO oxidation significantly and this enhanced effect is more pronounced on a-Pt/TiO2 than that on r-Pt/TiO2 with increasing CO concentration at lower temperatures. The same effect is also observed on the catalysts with different Pt and tungsten oxide (WO3) loadings. With increasing Pt and WO3 loadings on TiO2 support (Pt-WO3/TiO2), formation of NO2 is high even at lower temperatures. The presence of SO2 significantly suppresses the oxidation of NO over both r-Pt/TiO2 and a-Pt/TiO2 catalysts but it is less pronounced due to low stability of sulfate on a-Pt/TiO2.     

Integrated groundwater resource management in Indus Basin using satellite gravimetry and physical modeling tools

Reliable and frequent information on groundwater behavior and dynamics is very important for effective groundwater resource management at appropriate spatial scales. This information is rarely available in developing countries and thus poses a challenge for groundwater managers. The in situ data and groundwater modeling tools are limited in their ability to cover large domains. Remote sensing technology can now be used to continuously collect information on hydrological cycle in a cost-effective way. This study evaluates the effectiveness of a remote sensing integrated physical modeling approach for groundwater management in Indus Basin. The Gravity Recovery and Climate Experiment Satellite (GRACE)-based gravity anomalies from 2003 to 2010 were processed to generate monthly groundwater storage changes using the Variable Infiltration Capacity (VIC) hydrologic model. The groundwater storage is the key parameter of interest for groundwater resource management. The spatial and temporal patterns in groundwater storage (GWS) are useful for devising the appropriate groundwater management strategies. GRACE-estimated GWS information with large-scale coverage is valuable for basin-scale monitoring and decision making. This frequently available information is found useful for the identification of groundwater recharge areas, groundwater storage depletion, and pinpointing of the areas where groundwater sustainability is at risk. The GWS anomalies were found to favorably agree with groundwater model simulations from Visual MODFLOW and in situ data. Mostly, a moderate to severe GWS depletion is observed causing a vulnerable situation to the sustainability of this groundwater resource. For the sustainable groundwater management, the region needs to implement groundwater policies and adopt water conservation techniques.