Wet extraction of heavy metals and chloride from MSWI and straw combustion fly ashes

Fly ash residues from combustion often do not meet the criteria neither for reuse as construction materials nor landfilling as non-hazardous waste, mainly because of the high concentration of heavy metals and chlorides. This work aimed to technically evaluate an innovative wet treatment process for the extraction of chloride (Cl^?), cadmium (Cd), copper (Cu), lead (Pb) and zinc (Zn) from fly ashes from a municipal solid waste incineration (MSWI) plant and from a straw combustion (SC) facility. Factors investigated were liquid/solid (L/S) ratio, full carbonation (CO₂ treatment), influence of pH and leaching time, using a two-level full factorial design. The most significant factor for all responses was low pH, followed by L/S ratio. Multiple linear regression models describing the variation in extraction data had R² values ranging from 58% to 98%. An optimization of the element extraction models was performed and a set of treatment conditions is suggested.     

Reuse of Stormwater for Watering Gardens and Plants Using Green Gully: A New Stormwater Quality Improvement Device (SQID)

This paper introduces a new stormwater quality improvement device, called the "Green Gully" that collects, purifies, and reuses stormwater throughout an automated system. The working principal of the Green Gully is divided into two parts. Firstly, diverting stormwater from roadways to the diverter channel by filtering litter and secondly, watering the gardens and roadside plants with the stormwater that is collected from diverter channel. Stormwater treatment is an important step before reusing the water for gardening purpose. Different treatment levels (primary, secondary, and tertiary) are applied depending on the application to make water suitable for long-term storage and watering purposes. In this study, stormwater samples from three sites of Rockhampton City have been tested and analyzed to determine the quality of water for reuse. The parameters tested were electrical conductivity, pH, salinity, concentration of oil and grease, total suspended solid, turbidity, alkalinity, sodium, and chloride. The results of on-site stormwater quality tests are compared with the Australian and New Zealand Environment Conservation Council (ANZECC) standards and quality data available in the literature for each parameter suitable for irrigating roadside plants and gardening. Although, the results of this study is comparable with the literature data, a significantly different quality data are found compared to ANZECC standards. However, the samples collected for this study gave a basic understanding of stormwater quality issues for potential inflows to the Green Gully. Further study is recommended in order to establish mathematical link between raw stormwater quality and water quality required for gardening and irrigating roadside plants and for adopting required level of treatment facility with Green Gully for purifying and reusing water through an automated network system.     

A Bayesian network analysis of workplace accidents caused by falls from a height

This article analyses, using Bayesian networks, the circumstances surrounding workplace tasks performed using auxiliary equipment (ladders, scaffolding, etc.) that may result in falls. The information source was a survey of employees working at a height. We were able to determine the usefulness of this approach – innovative in the accident research field – in identifying the causes that have the greatest bearing on accidents involving auxiliary equipment: in these cases, the adoption of incorrect postures during work and a worker’s inadequate knowledge of safety regulations. Likewise, the duration of tasks was also associated with both these variables, and therefore, with the accident rate. Bayesian networks also enable dependency relationships to be established between the different causes of accidents. This information – which is not usually furnished by conventional statistical methods applied in the field of labour risk prevention – allow a causality model to be defined for workplace accidents in a more realistic way. With this statistic tool, the expert is also provided with useful information that can be input to a management model for labour risk prevention.     

Determination of the optimal escape routes of underground mine networks in emergency cases

Escaping is natural in the case of accidents in underground mines. Determining the optimal escape route is one of the most important factors for relief of miners in the emergency cases. This paper aims at developing a mathematical method to determine the shortest escape time from a given point to alternative points of an underground mine network. It also aims to find the shortest routes between each pair of the given points. The first point refers to the place of the accident where some miners may exist, and the alternative points show the safe places that the miners can escape to. After determining the shortest escape time and its corresponding route between each pair of mine work junctions, it is possible to set an electronic board that shows the access route to the nearest safe location by an arrow sign in each mine work. In this paper, Floyd–Warshall and π algorithms are used to determine the shortest escape time between the place of accident and safe places as well as their corresponding routes. Those algorithms are rigorous since they are supported by mathematical proof. Finally, the algorithms are implemented on the network of a certain underground coal mine and the results are presented.     

Agent-based analysis and support for incident management

This paper presents an agent-based approach for error detection in incident management organizations. The approach consists of several parts. First, a formal approach for the specification and hierarchical verification of both traces and properties. Incomplete traces are enriched by enrichment rules. Furthermore, a classification mechanism is presented for the different properties in incident management that is based on psychological literature. Classification of errors provides insight in the functioning of the agents involved with respect to their roles. This insight enables the provision of dedicated training sessions and allows software support to give appropriate warning messages during incident management.