Evaluation of Solidified Wastewater Treatment Sludge as a Potential SCM in Pervious Concrete Pavements.

Waste and recycled materials have recently been used in the construction industry to comply with the principles of circular economy and sustainable development. The aim of this paper is to examine the potentials of solidified wastewater treatment sludge (SWWTS) as a supplementary cementitious material (SCM) in the production of lightweight pervious concrete pavers (LWPCP) suitable for pedestrian trails and rooftops (green) that comply with EU standards. Detailed characterization of SWWTS was performed, in order to understand its properties related to application as SCM, which led to the conclusion that it may be applied only as a filler, having 89.5% of Ca(OH)2. After thorough characterization, LWPCP samples were prepared and testing of physical and mechanical properties was conducted. The research showed that partial replacement of cement with SWWTS led to the decrease of all mechanical properties, ranging between 3.91 and 5.81 MPa for compressive strength and 0.97 to 1.23 MPa for flexural strength. However, all of the investigated mixtures showed a value higher than 3.5 MPa, which was defined as the lowest compressive strength in the range of pervious concrete properties. The addition of SWWTS led to a slight decrease in bulk density of the mixtures and an increase in water absorption. This could be explained by the reduction in hydration products that would fill in the micropores of the matrix, since SWWTS showed no pozzolanic reactivity. Pore sizes that prevail in the tested binder matrices are in accordance with the results measured on ordinary pervious concrete (the largest fraction of pores had a diameter between 0.02 and 0.2 µm). Low thermal conductivity nominates produced pavers as potential rooftop elements.

Build-up and characterisation of pollutants on urban impervious surfaces.

This paper presents the results of the investigation of pollutant build-up on impervious surfaces of a parking lot in Belgrade, Serbia during the summer months. Contaminant build-up was found to be greater on asphalt surfaces directly exposed to vehicular traffic than on concrete walkways. The difference in the amounts of accumulated pollutants between asphalt and concrete were significant: for total solids (TS), total suspended solids (TSS), chemical oxygen demand (COD), heavy metals and total phosphorus (TP) accumulations were two to three times higher, while only 30% higher for total nitrogen (TN) and anions. Build-up of most of the measured parameters was best described by power functions. The highest surface loads were found for solids, COD, iron and zinc. A strong correlation was found between turbidity, TS, TSS, COD, heavy metals and phosphorus, while conductivity, nitrates and nitrites were weakly correlated to other parameters.

Further insight into the mechanism of heavy metals partitioning in stormwater runoff.

Various particles and materials, including pollutants, deposited on urban surfaces are washed off by stormwater runoff during rain events. The interactions between the solid and dissolved compounds in stormwater runoff are phenomena of importance for the selection and improvement of optimal stormwater management practices aimed at minimizing pollutant input to receiving waters. The objective of this research was to further investigate the mechanisms responsible for the partitioning of heavy metals (HM) between the solid and liquid phases in urban stormwater runoff. The research involved the collection of samples from urban asphalt surfaces, chemical characterization of the bulk liquid samples, solids separation, particle size distribution fractionation and chemical and physico-chemical characterization of the solid phase particles. The results revealed that a negligible fraction of HM was present in the liquid phase (less than 3% by weight), while there was a strong correlation between the total content of heavy metals and total suspended solids. Examinations of surface morphology and mineralogy revealed that the solid phase particles consist predominantly of natural macroporous materials: alpha quartz (80%), magnetite (11.4%) and silicon diphosphate (8.9%). These materials have a low surface area and do not have significant adsorptive capacity. These materials have a low surface area and do not have significant adsorptive capacity. The presence of HM on the surface of solid particles was not confirmed by scanning electron microscopy and energy dispersive X-ray microanalyses. These findings, along with the results of the liquid phase sample characterization, indicate that the partitioning of HM between the liquid and solid phases in the analyzed samples may be attributed to precipitation processes.

A new approach in regression analysis for modeling adsorption isotherms.

Numerous regression approaches to isotherm parameters estimation appear in the literature. The real insight into the proper modeling pattern can be achieved only by testing methods on a very big number of cases. Experimentally, it cannot be done in a reasonable time, so the Monte Carlo simulation method was applied. The objective of this paper is to introduce and compare numerical approaches that involve different levels of knowledge about the noise structure of the analytical method used for initial and equilibrium concentration determination. Six levels of homoscedastic noise and five types of heteroscedastic noise precision models were considered. Performance of the methods was statistically evaluated based on median percentage error and mean absolute relative error in parameter estimates. The present study showed a clear distinction between two cases. When equilibrium experiments are performed only once, for the homoscedastic case, the winning error function is ordinary least squares, while for the case of heteroscedastic noise the use of orthogonal distance regression or Margart's percent standard deviation is suggested. It was found that in case when experiments are repeated three times the simple method of weighted least squares performed as well as more complicated orthogonal distance regression method.