Simulation study of the Lower Cretaceous geothermal reservoir for aquifer thermal energy storage

Environmental Geochemistry and Health - The aquifer thermal energy storage (ATES) has gained attention in several countries as an installation for increasing the energy efficiency of geothermal...     

Measuring the association of environmental,corporate, financial,and social CSR: evidence from fuzzy TOPSIS nexus in emerging economies

Environmental Science and Pollution Research - The purpose of this research is to measure the combing impact of corporate social responsibility on company performance and to conduct a comparative...     

Energy and environment - An introduction

Environmental Science and Pollution Research -     

Using individual-based movement information to identify spatial conservation priorities for mobile species

The optimal design of reserve networks and fisheries closures depends on species occurrence information and knowledge of how anthropogenic impacts interact with the species concerned. However, challenges in surveying mobile and cryptic species over adequate spatial and temporal scales can mask the importance of particular habitats, leading to uncertainty about which areas to protect to optimize conservation efforts. We investigated how telemetry-derived locations can help guide the scale and timing of fisheries closures with the aim of reducing threatened species bycatch. Forty juvenile speartooth sharks (Glyphis glyphis) were monitored over 22 months with implanted acoustic transmitters and an array of hydrophone receivers. Using the decision-support tool Marxan, we formulated a permanent fisheries closure that prioritized areas used more frequently by tagged sharks and considered areas perceived as having high value to fisheries. To explore how the size of the permanent closure compared with an alternative set of time-area closures (i.e., where different areas were closed to fishing at different times of year), we used a cluster analysis to group months that had similar arrangements of selected planning units (informed by shark movements during that month) into 2 time-area closures. Sharks were consistent in their timing and direction of migratory movements, but the number of tagged sharks made a big difference in the placement of the permanent closure; 30 individuals were needed to capture behavioral heterogeneity. The dry-season (May–January) and wet-season (February–April) time-area closures opened 20% and 25% more planning units to fishing, respectively, compared with the permanent closure with boundaries fixed in space and time. Our results show that telemetry has the potential to inform and improve spatial management of mobile species and that the temporal component of tracking data can be incorporated into prioritizations to reduce possible impacts of spatial closures on established fisheries.     

Contamination by arsenic and other trace elements in tube-well water and its risk assessment to humans in Hanoi, Vietnam

Concentrations of As and other trace elements and their association were examined in groundwater (n = 25) and human hair (n = 59) collected at Gia Lam District and Thanh Tri District, suburban areas of Hanoi, Vietnam, in September 2001. Concentrations of As in the groundwater ranged from <0.10 to 330 microg/l, with about 40% of these exceeding WHO drinking water guideline of 10 microg/l. Also, 76% and 12% of groundwater samples had higher concentrations of Mn and Ba than WHO drinking water guidelines, respectively. Arsenic concentrations in hair of residents in Gia Lam and Thanh Tri Districts (range 0.088-2.77 microg/g dry wt.) were lower than those in other As-contaminated areas of the world, but were higher than those of people in non-contaminated areas. Concentrations of As and Mn in hair of some individuals from the Gia Lam and Thanh Tri Districts exceeded the level associated with their toxicity and, therefore, a potential health risk of As and Mn is a concern for the people consuming the contaminated water in this area. Cumulative As exposure was estimated to be lower than the threshold levels at the present, which might explain the absence of manifestations of chronic As poisoning and arsenicosis in the residents of Gia Lam and Thanh Tri Districts. To our knowledge, this study revealed for the first time that the residents are exposed not only to As but also Mn and Ba from groundwater in the Red River Delta, Vietnam.     

Application of soft computing to predict water quality in wetland

Prediction of water quality is a critical issue because of its significant impact on human and ecosystem health. This research aims to predict water quality index (WQI) for the free surface wetland using three soft computing techniques namely, adaptive neuro-fuzzy system (ANFIS), artificial neural networks (ANNs), and group method of data handling (GMDH). Seventeen wetland points for a period of 14 months were considered for monitoring water quality parameters including conductivity, suspended solid (SS), biochemical oxygen demand (BOD), ammoniacal nitrogen (AN), chemical oxygen demand (COD), dissolved oxygen (DO), temperature, pH, phosphate nitrite, and nitrate. The sensitivity analysis performed by ANFIS indicates that the significant parameters to predict WQI are pH, COD, AN, and SS. The results indicated that ANFIS with Nash-Sutcliffe Efficiency (NSE = 0.9634) and mean absolute error (MAE = 0.0219) has better performance to predict the WQI comparing with ANNs (NSE = 0.9617 and MAE = 0.0222) and GMDH (NSE = 0.9594 and MAE = 0.0245) models. However, ANNs provided a comparable prediction and the GMDH can be considered as a technique with an acceptable prediction for practical purposes. The findings of this study could be used as an effective reference for policy makers in the field of water resource management. Decreasing variables, reduction of running time, and high speed of these approaches are the most important reasons to employ them in any aquatic environment worldwide.

     

Assessing and selecting interventions for river water quality improvement within the context of population growth and urbanization: a case study of the Cau River basin in Vietnam

In this study, a multi-criteria methodology is proposed to identify and prioritize interventions for water quality improvement with the aid of computer simulation models. The methodology can be used to elaborate and compare future socio-economic development scenarios to select the best interventions based on three criteria: (1) ideas of experts and stakeholders about the importance of scenarios, (2) impacts of each scenario on surface water quality in watershed, and (3) benefit–cost analysis for each scenario. A score is computed for each scenario based on a weighted sum technique which enables to take into consideration different level of importance for the three criteria. The methodology is applied to Cau River basin in Vietnam, with the aid of a computer tool, to assess interventions for river water quality improvement within the context of population growth and urbanization. The results show that fast future population growth in upstream has significant impacts. In 2020, an increase of 116 % of the population in Bac Kan town can lead to an increase of 120 and 135 % in BOD₅ and NH₄ ⁺ median concentrations, respectively, with the implementation of a treatment plant for 10,000 people in Bac Kan town. Therefore, the increase of the domestic wastewater treatment plant’s capacity in Bac Kan town, at least twice as the projection of local government, is necessary. These results will help decision makers to select the best interventions for Cau River basin management.     

Determining contamination level of heavy metals in road dust from busy traffic areas with different characteristics

This study identified the levels and sources of heavy metal contamination in road dust from busy traffic areas in a typical industrial city in Korea. This study compared the total concentrations, as determined by aqua regia digestions and atomic absorption spectroscopy, of cadmium (Cd), copper (Cu), lead (Pb), zinc (Zn) and nickel (Ni) in the road dust from areas with different characteristics such as traffic rotaries, downtown areas, circulation roads, and asphalt and concrete highways. The contamination levels of the heavy metals in the road dust were evaluated using the contamination factor and the degree of contamination. The contamination levels of the heavy metals in the road dust were highly dependent on traffic volume and atmospheric dispersion from traffic rotaries. Industrial emissions and the frequency of brake use and vehicles coming to a complete stop were additional factors that affected the contamination levels in downtown areas. The concrete highway had higher contamination levels of the heavy metals than the asphalt highway. Vehicle speed was also a strong contributing factor to the degree of contamination of heavy metals in the road dust from the circulation roads and highways.     

CREAM-based communication error analysis method (CEAM) for nuclear power plant operators’ communication

Communication error has been considered a primary cause of many incidents and accidents in the nuclear industry. In order to prevent these accidents, a method for the analysis of such communication errors is proposed here. This paper presents a qualitative and a quantitative method to analyze communication errors. The qualitative method focuses on finding a root cause of the communication error and predicting the type of communication error which could happen in nuclear power plants. We develop context conditions and antecedent-consequent links of influential factors related to communication errors. The quantitative analysis method focuses on estimating the probability of communication errors. To accomplish the quantification of communication errors, the Cognitive Speaking Process (CSP) is defined and a method to estimate the weighting factors and the probability is suggested. Finally, case studies conducted to validate the applicability of the proposed methods are detailed. From the results, we can foresee the effects of given plant conditions on communication errors and reduce the error occurrences.     

Actuarial risk assessment of expected fatalities attributable to carbon capture and storage in 2050

This study estimates the human cost of failures in the CCS industry in 2050, using the actuarial approach. The range of expected fatalities is assessed integrating all steps of the CCS chain: additional coal production, coal transportation, carbon capture, transport, injection and storage, based on empirical evidence from technical or social analogues. The main finding is that a few hundred fatalities per year should be expected if the technology is used to avoid emitting 3.67 GtCO₂ year⁻¹ in 2050 at baseload coal power plants. The large majority of fatalities are attributable to mining and delivering more coal. These risks compare to today's industrial hazards: technical, knowable and occupational dangers for which there are socially acceptable non-zero risk levels. Some contemporary European societies tolerate about one fatality per thousand years around industrial installations. If storage sites perform like that, then expected fatalities per year due to leakage should have a minor contribution in the total expected fatalities per year: less than one. But to statistically validate such a safety level, reliability theory and the technology roadmap suggest that CO₂ storage demonstration projects over the next 20 years have to cause exactly zero fatality.