Disaster coordination preparedness of soft-target organisations

This paper introduces a network‐enabled model to examine the disaster coordination preparedness of soft‐target organisations (STOs). Little attention is devoted to this matter in recent research. This study places emphasis on such organisations and the proposed model tests hypotheses related to network relation and coordination preparedness. It analyses the data set entitled ‘Preparedness of large retail malls to prevent and respond to terrorist attack, 2004′, which contains 120 completed surveys of security directors of retail malls in the United States. ¹ 1 See http://www.icpsr.umich.edu/icpsrweb/TPDRC/studies/21140 .
The following questions form the basis of this study: ‘What do STOs need to be better prepared to respond to a disaster?’; ‘How does network relationship between STOs and emergency agencies affect the coordination preparedness of STOs for disaster recovery?’; and ‘Which centrality measure needs to be followed to measure network variables in order to analyse coordination preparedness?’ The results show that STOs with a high level of connectedness and strong ties to other emergency agencies are better prepared for disaster response.     

Stagnant surface water bodies (SSWBs) as an alternative water resource for the Chittagong metropolitan area of Bangladesh: physicochemical characterization in terms of water quality indices

The concern over ensuing freshwater scarcity has forced the developing countries to delve for alternative water resources. In this study, we examined the potential of stagnant surface water bodies (SSWBs) as alternative freshwater resources in the densely populated Chittagong metropolitan area (CMPA) of Bangladesh??where there is an acute shortage of urban freshwater supply. Water samples were collected at 1-month intervals for a period of 1 year from 12 stations distributed over the whole metropolis. Samples were analyzed for pH, water temperature (WTemp), turbidity, electrical conductivity (EC), total dissolved solids, total solids, total hardness, dissolved oxygen (DO), chloride, orthophosphates, ammonia, total coliforms (TC), and trace metal (Cd, Cr, Cu, Pb, As, and Fe) concentrations. Based on these parameters, different types of water quality indices (WQIs) were deduced. WQIs showed most of CMPA-SSWBs as good or medium quality water bodies, while none were categorized as bad. Moreover, it was observed that the minimal water quality index (WQI_m), computed using five parameters: WTemp, pH, DO, EC, and turbidity, gave a reliable estimate of water quality. The WQI_m gave similar results in 72% of the cases compared with other WQIs that were based on larger set of parameters. Based on our finding, we suggest the wider use WQI_m in developing countries for assessing health of SSWBs, as it will minimize the analytical cost to overcome the budget constraints involved in this kind of evaluations. It was observed that except turbidity and TC content, all other quality parameters fluctuated within the limit of the World Health Organization suggested standards for drinking water. From our findings, we concluded that if the turbidity and TC content of water from SSWBs in CMPA are taken care of, they will become good candidates as alternative water resources all round the year.     

Explosibility of micron- and nano-size titanium powders

Explosibility of micron- and nano-titanium was determined and compared according to explosion severity and likelihood using standard dust explosion equipment. ASTM methods were followed using a Siwek 20-L explosion chamber, MIKE 3 apparatus and BAM oven. The explosibility parameters investigated for both size ranges of titanium include explosion severity (maximum explosion pressure (P_max) and size-normalized maximum rate of pressure rise (K_St)) and explosion likelihood (minimum explosible concentration (MEC), minimum ignition energy (MIE) and minimum ignition temperature (MIT)). Titanium particle sizes were ?100 mesh (<150 μm), ?325 mesh (<45 μm), ≤20 μm, 150 nm, 60–80 nm, and 40–60 nm. The results show a significant increase in explosion severity as the particle size decreases from ?100 mesh with an apparent plateau being reached at ?325 mesh and ≤20 μm. Micron-size explosion severity could not be compared with that for nano-titanium due to pre-ignition of the nano-powder in the 20-L chamber. The likelihood of an explosion increases significantly as the particle size decreases into the nano range. Nano-titanium is very sensitive and can self-ignite under the appropriate conditions. The explosive properties of the nano-titanium can be suppressed by adding nano-titanium dioxide to the dust mixture. Safety precautions and procedures for the nano-titanium are also discussed.     

Quantifying the effect of strong ignition sources on particle preconditioning and distribution in the 20-L chamber

Computational fluid dynamics is used to investigate the preconditioning aspect of overdriving in dust explosion testing. The results show that preconditioning alters both the particle temperature and distribution prior to flame propagation in the 20-L chamber. A parametric study gives the fluid pressure and temperature, and particle temperature and concentration at an assumed flame kernel development time (10 ms) for varying ignitor size and particle diameter. For the 10 kJ ignitor with 50% efficiency, polyethylene particles under 50 μm reach 400 K and may melt prior to flame propagation. Gases from the ignitor detonation displace the dust from the center of the chamber and may increase local particle concentration up to two times the nominal value being tested. These effects have important implications for explosive testing of dusts in the 20-L chamber and comparing to larger 1-m³ testing, where these effects may be negligible.     

Dynamic safety analysis of process systems by mapping bow-tie into Bayesian network

Among the various techniques used for safety analysis of process systems, bow-tie (BT) analysis is becoming a popular technique as it represents an accident scenario from causes to effects. However, the BT application in the dynamic safety analysis is limited due to the static nature of its components, i.e. fault tree and event tree. It is therefore difficult in BT to take accident precursors into account to update the probability of events and the consequent risk. Also, BT is unable to represent conditional dependency. Event dependency is common among primary events and safety barriers. The current paper illustrates how Bayesian network (BN) helps to overcome these limitations. It has also been shown that BN can be used in dynamic safety analysis of a wide range of accident scenarios due to its flexible structure. This paper also introduces the application of probability adapting in dynamic safety analysis rather than probability updating. A case study from the U.S. Chemical Safety Board has been used to illustrate the application of both BT and BN techniques, with a comparison of the results from each technique.     

Precursor-based hierarchical Bayesian approach for rare event frequency estimation: A case of oil spill accidents

Due to a scarcity of data, the estimate of the frequency of a rare event is a consistently challenging problem in probabilistic risk assessment (PRA). However, the use of precursor data has been shown to help in obtaining more accurate estimates. Moreover, the use of hyper-priors to represent prior parameters in the hierarchical Bayesian approach (HBA) generates more consistent results in comparison to the conventional Bayesian method. This study proposes a framework that uses a precursor-based HBA for rare event frequency estimation. The proposed method is demonstrated using the recent BP Deepwater Horizon accident in the Gulf of Mexico. The conventional Bayesian method is also applied to the same case study. The results show that the proposed approach is more effective with regards to the following perspectives: (a) using the HBA in the proposed framework provides an opportunity to take full advantage of the sparse data available and add information from indirect but relevant data; (b) the HBA is more sensitive to changes in precursor data than the conventional Bayesian method; and (c) using hyper-priors to represent prior parameters, the HBA is able to model the variability that can exist among different sources of data.     

A systematic review of the utilization of waste materials as aggregate replacement in stone matrix asphalt mixes

Environmental Science and Pollution Research - The daily utilization of a large amount of raw materials is causing a rapid depletion of natural resources. The growth of the human population is...     

Multivariate statistics and entropy theory for irrigation water quality and entropy-weighted index development in a subtropical urban river,Bangladesh

Environmental Science and Pollution Research - Currently, a well-developed combination of irrigation water quality index (IWQIs) and entropy water quality index (EWQIs) for surface water appraisal...     

An assessment of contamination and ecological risk of metals in sediments of the Guaracara,Caparo and Couva rivers in Trinidad,West Indies

The presence of metals in an aquatic environment can serve as a biomarker for pollution and can be used to evaluate its contamination status. Rapid industrialisation in recent decades has propelled Trinidad and Tobago to be one of the most developed nations within the Caribbean region and has stimulated the awareness of potential ecological risks from various industrial activities affecting the rivers of Trinidad. Sediment samples from three rivers along the West coast of Trinidad were analysed for Cd, Cr, Cu, Mn, Ni, Pb and Zn. For all three rivers, the metal concentrations in sediments were in the range of 0.40–2.31?μg/g, 12.77–33.04?μg/g, 14.51–72.89?μg/g, 224.90–4472.83?μg/g, 8.20–43.08?μg/g, 22.63–38.34?μg/g and 92.0–5462.60?μg/g for Cd, Cr, Cu, Mn, Ni, Pb and Zn, respectively. Assessment of the pollution status indicated that all three rivers were considered polluted, with significant contributions from Cr, Cu, Mn, Ni and Zn. The potential ecological risk for all three rivers, however, was low and multivariate statistics revealed that mainly anthropogenic sources contributed to the metal concentrations in sediments of all three rivers.