To combat environmental challenges—such as the depletion of natural resources and a high carbon footprint—and contribute to the effort of achieving zero-waste technology and sustainable development, the use of agricultural and industrial wastes in the cement industry has created a research interest. This study explores the potential of two types of harvest residue ash (HRA) and three types of ceramic waste (CP) as supplementary cementitious materials (SCMs) through: (1) the characterization of raw materials and (2) examining the physical properties and mechanical performance of cement-based mortar samples prepared with 10%, 30% and 50%wt of the selected SCMs ground into powder form as cement replacement. Two main variables were the water-to-binder ratio (w/b) and the effect of different grinding procedures. Experimental results demonstrated that flexural and compressive strengths were not significantly impaired by SCM additions of up to 50%, but higher replacement levels led to an increased permeability and higher capillary water absorption due to the dilution effect. Also, a lower w/b was shown to effectively reduce the porosity of mortar and increase its mechanical properties, allowing for higher shares of SCMs to be utilized. This study verifies the technical feasibility of cob corn ash and ceramic powder application as SCMs in mortar formulations, further promoting the practice of incorporating industrial and agricultural by-products in greener cementitious composites.

During December 2009 snow was collected at twenty two locations across the urban area of Novi Sad, directly from roads and from traffic islands near crossroads. The total metal concentration was determined for each of ten metals (Al, Ca, Cu, Fe, K, Mn, Na, Ni, Pb, Zn) using the ICP-OES analytical technique. The metal found to have the lowest concentration was Ni (0.0265 mg dm-3). The metal with the highest concentration was Na (10786 mg dm-3), which is a consequence of sodium chloride being used as de-icing salt on the roads. The metal with the second highest concentration at all locations was Ca; this was most likely the result of soil dust. The Spearman's rank correlation coefficients between analyzed metals were calculated to determine how concentrations of metals were related. A cluster analysis was carried out on the obtained data sets, using both hierarchical and partitioning methods in order to identify associations among metals and/or locations. It was shown that traffic density was not the most important factor that caused differences between the concentrations of the metals in samples.