Optimizing safety-constrained solvent selection for process systems with economic uncertainties

Solvents are very commonly used in industrial facilities for a multitude of reasons. Traditionally, solvent selection has been based on minimizing the process operating cost while satisfying a set of operational requirements. Regrettably, safety considerations have typically been overlooked during the design phase. In this paper, a systematic approach is introduced to integrate safety issues into solvent selection and provides a computationally effective method for establishing tradeoffs between the economic and safety objectives. In order to quantify the risk associated with the solvent, we focus on the potential spillage of the solvent and introduce a risk index that is a function of the amount of solvent used and stored, as well as the Permissible Exposure Limit (PEL) dictated by regulatory directives. An optimization formulation is developed and the associated mathematical program solved to select optimal solvents and blends while incorporating economic, technical, and safety considerations. Tradeoff (Pareto) curves are developed to represent the multi-objective optimization results and tradeoffs. Furthermore, economic-data uncertainty and variability over expected ranges are included in the optimization formulation to conduct an insightful sensitivity analysis. Finally, an illustrative case study is considered via increasing levels of complexity in order to evaluate the proposed optimization method which considers both operating cost and safety risk implications in the presence of economic uncertainties.     

Multiple dimensions of work-related risk factors and their relationship to work ability among industrial workers in Iran

Objectives. The present study was designed to investigate the simultaneous effects of physical, psychosocial and other work-related risk factors on the work ability index (WAI) score among industrial workers. Methods. This study used a cross-sectional design with a questionnaire survey. A total of 280 workers were included in the study. Data were collected using three questionnaires including the Persian version of the WAI, the Persian version of the job content questionnaire and an author-developed measure (to assess work-related factors, health-related factors and socio-demographic characteristics). Results. The majority of the participants were young, but they had poor WAI scores (mean 37.3?±?6.4) and 44.3% of them had poor or moderate work ability. Occupational accidents and injuries were found to be the strongest predictors of WAI scores. Additionally, there was a strong association between WAI scores and supervisor support, skill discretion, occupational training, sleep quality, work nature and educational level. Conclusions. Intervention programs should focus on improving supervisor support, sleep quality, job skills and knowledge and on decreasing physical and mental work demands. Additionally, implementing a comprehensive occupational health and ergonomics program for controlling and reducing hazardous working environments and occupational injury rates should be considered.     

Public preferences for production of local and global ecosystem services

Many regulating ecosystem services exhibit non-excludability and non-rivalry characteristics akin to public goods. This makes it unlikely that such regulating ecosystem services will attract a price in the marketplace. Policymakers, therefore, find difficulties in determining a correct economic valuation for regulating ecosystem services, with potentially severe consequences for aligning policy for ecosystem service provision with public preferences for service delivery. This research used a choice modelling approach to estimate public preferences for delivery of two regulating ecosystem services; reductions in the flood risk to the British city of York (implemented by filling in drainage ditches in peat moorland further up the catchment), and a reduction in CO₂ emissions (implemented by planting Poplar trees for biomass either locally in the study area or elsewhere in the UK). The choice experiment presented respondents with options providing different levels of CO₂ reduction, implemented locally or nationally, and different levels of flood risk reduction, at a range of different prices, with a tax as the payment vehicle. Subsequent analysis with latent class (LC) models showed considerable heterogeneity of preference among respondents, particularly with regard to the location of tree planting for CO₂ reduction. One LC segment showed a significant preference for achieving a high level CO₂ reduction through national, as opposed to local tree planting, potentially indicating the existence of NIMBYism. The same LC segment displayed a preference for moderate reductions in the flood risk to York, even though this would deliver no personal benefit for a substantial proportion of the segment. This could, therefore, indicate altruistic behaviour towards geographically proximate beneficiaries.     

Modeling sediment and nitrogen export from a rural watershed in eastern Canada using the soil and water assessment tool

Watershed simulation models can be used to assess agricultural nonpoint-source pollution and for environmental planning and improvement projects. However, before application of any process-based watershed model, the model performance and reliability must be tested with measured data. The Soil and Water Assessment Tool version 2005 (SWAT2005) was used to model sediment and nitrogen loads from the Thomas Brook Watershed, which drains a 7.84 km rural landscape in the Annapolis Valley of Nova Scotia, Canada. The Thomas Brook SWAT model was comprised of 28 subbasins and 265 hydrologic response units, most of them containing agricultural land use, which is the main nonpoint nitrogen source in the watershed. Crop rotation schedules were incorporated into the model using field data collected within Agriculture and Agri-Food Canada's Watershed Evaluation of Beneficial Management Practices program. Model calibration (2004-2006) and validation (2007-2008) were performed on a monthly basis using continuous stream flow, sediment, and nitrogen export measurements. Model performance was evaluated using the coefficient of determination, Nash-Sutcliff efficiency (NSE), and percent bias (PBIAS) statistics. Study results show that the model performance was satisfactory (NSE > 0.4; > 0.5) for stream flow, sediment, nitrate-nitrogen, and total nitrogen simulations. Annual corn, barley, and wheat yields were also simulated well, with PBIAS values ranging from 0.3 to 7.2%. This evaluation of SWAT demonstrated that the model has the potential to be used as a decision support tool for agricultural watershed management in Nova Scotia.     

Electrocoagulation of palm oil mill effluent as wastewater treatment and hydrogen production using electrode aluminum

Palm oil mill effluent (POME) is highly polluting wastewater generated from the palm oil milling process. Palm oil mill effluent was used as an electrolyte without any additive or pretreatment to perform electrocoagulation (EC) using electricity (direct current) ranging from 2 to 4 volts in the presence of aluminum electrodes with a reactor volume of 20 L. The production of hydrogen gas, removal of chemical oxygen demand (COD), and turbidity as a result of electrocoagulation of POME were determined. The results show that EC can reduce the COD and turbidity of POME by 57 and 62%, respectively, in addition to the 42% hydrogen production. Hydrogen production was also helpful to remove the lighter suspended solids toward the surface. The production of Al(OH)XHO at the aluminum electrode (anode) was responsible for the flocculation-coagulation process of suspended solids followed by sedimentation under gravity. The production of hydrogen gas from POME during EC was also compared with hydrogen gas production by electrolysis of tap water at pH 4 and tap water without pH adjustment under the same conditions. The main advantage of this study is to produce hydrogen gas while treating POME with EC to reduce COD and turbidity effectively.     

Performance improvement potential of sensor embedded products in environmental supply chains

Environmental supply chain is a desirable alternative to traditional supply chain due to new and stricter environmental regulations by local governments and increasing consumer awareness towards environmental issues. The two most common types of environmental supply chains are reverse supply chains and closed-loop supply chains. In reverse or closed-loop supply chains, collected used products are subjected to one of four recovery options, viz., reuse, recycling, remanufacturing or disposal. Regardless of the chosen recovery option, all products are disassembled up to some level. However, there is a high level of uncertainty associated with the disassembly yield due to non-functional and/or missing components. Sensor embedded products (SEPs) is a viable approach to cope with this uncertainty since they involve sensors which can detect non-functional and/or missing components prior to disassembly. This study presents a quantitative assessment of the impact of SEPs on the various performance measures of a kanban-controlled disassembly line. First, separate design of experiments studies based on Orthogonal Arrays are carried out for conventional products and SEPs. Then, the results of paired t-tests comparing the two cases based on different performance measures are presented.     

Sustainable options of post treatment of UASB effluent treating sewage: A review

The upflow anaerobic sludge blanket (UASB) process is reported to be a sustainable technology for domestic wastewaters treatment in developing countries and for small communities. However, the inability of UASB process to meet the desired disposal standards has given enough impetus for subsequent post treatment. In order to upgrade the UASB based sewage treatment plants (STPs) to achieve desired effluent quality for disposal or for reuse, various technological options are available and broadly differentiated as primary post-treatment for the removal of organic and inorganic compounds and suspended matter; secondary post-treatment for the removal of hardly degradable soluble matter, colloidal and nutrients; and polishing systems for removals of pathogens. Hence, this paper discusses the different systems for the treatment of UASB reactor effluent treating sewage. Additionally, a comparative review, an economic evaluation of some of the emerging options was conducted and based on the extensive review of different integrated combination, i.e. UASB-different aerobic systems, a treatment concept based on natural biological mineralization route recognized as an advanced technology to meet all practical aspects to make it a sustainable for environmental protection, resource preservation and recovering maximum resources.     

Designing a mixed performance measurement system for environmental supply chain management using evolutionary game theory and balanced scorecard: A case study of an auto industry supply chain

This paper proposes a mixed performance measurement system using a combination of evolutionary game theory and the balanced scorecard (BSC) in environmental supply chain management (ESCM) that measures and evaluates business operations using the four different perspectives of finance, customer, internal business process, and learning and growth. ESCM plays an important role in the supply chain which leads to the reduction, reuse and recycling of resources involved in both upstream and downstream activities. This paper presents guidance for practical managers in evaluating and measuring ESCM by developing a knowledge-based BSC and evolutionary game theory. The primary purpose of this paper is to apply the proposed method in a case study to one of Iran's biggest auto industry supply chain SAIPA Company. The results of this study indicate that the adoption of ESCM, in the absence of regulatory pressures and cost-saving measures is triggered by public pressures and its implementation is limited by organizational factors and strategic myopia.     

Screening and detection of biomarkers in chickpea plants exposed to chromium and cadmium

A broad screening protocol, covering the most general phytochemical groups of compounds, was developed on the basis of high performance thin layer chromatography (HPTLC). A total of six TLC systems, comprising three derivatization reagents, two stationary phases and two mobile phases, were included. The screening method was applied for the identification of biomarkers in the chickpea plant exposed to cadmium and chromium. The biomarkers were selected on the basis of significant changes (0.26-4.6 fold) in concentration levels of phytochemicals. Totally, five different amino acids, three organic acids, one sulphur containing compound and one sugar were identified as biomarkers in chickpea exposed heavy metal.