Abstract
Incinerator bottom ash (IBA) is a residual produced from incinerating municipal solid waste. In the past, IBA presented a big waste disposal problem; however, various recycling approaches have been adopted in recent years to mitigate this problem, as well as to provide a useful alternative to using primary aggregate resources. The use of IBA as an alternative to conventional aggregates in different civil engineering construction applications helps to conserve premium grade aggregate supplies; however, when IBA is in contact with water in the field, as a consequence of precipitation events or changes in water table, elements, such as salts and heavy metals, may be released to the soil and ground water. In this work, IBA waste was mixed with limestone aggregate to produce a blend with acceptable mechanical properties and minimum environmental risks for use as road foundation. The study focused on evaluating potential environmental impacts of some constituents, including sulphate, chloride, sodium, copper, zinc and lead in IBA blends using a lysimeter as a large scale leaching tool. Moreover, a specific scenario simulating field conditions was adopted in the lysimeter to assess the potential impact of changing conditions, such as IBA content in the blend, liquid to solid ratio (L/S) and pH value, on long-term release of heavy metals and salts. Then, numerical modelling was used to predict the release of the aforementioned constituents from IBA based on initial measurement of intrinsic material properties and the kinetic desorption process concept. Experimental results showed that zinc and lead were released in very low concentrations but sodium and sulphate were in high concentrations. The control limestone only blend also demonstrated low release concentrations of constituents in comparison to IBA blends, where constituent concentrations increased with increase in IBA content. Experimental results were compared with numerical results obtained using a non-equilibrium desorption model. Good agreement was found between the two sets of data. (C) 2010 Elsevier Ltd. All rights reserved.