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Effect of composting process on phytotoxicity and speciation of copper, zinc and lead in sewage sludge and swine manure
Authors:Miaomiao He  Wenhong Li  Xinqiang Liang  Donglei Wu  Guangming Tian
Affiliation:Department of Environmental Engineering, College of Environment and Resources Science, Zhejiang University, Hangzhou 310029, China.
Abstract:The concentration and bioavailability of heavy metals in composted organic wastes have negative environmental impacts following land application. Aerobic composting procedures were conducted to investigate the influences of selected parameters on heavy metal speciation and phytotoxicity. Results showed that both of sewage sludge (SSC) and swine manure (SMC) composting systems decreased the pH, the content of organic matter (OM) and dissolved organic carbon (DOC), and total amounts of Cu, Zn and Pb. Sequential extraction showed that readily extractible fractions of exchangeable and carbonate in Cu and Zn increased during SSC composting but decreased during SMC composting, thus their bioavailability factors (BF) enhanced in SSC but declined in SMC. The fraction of reducible iron and manganese (FeMnOX) of Cu and Zn in SSC and FeMnOX-Cu in SMC decreased, but FeMnOX-Zn in SMC gradually increased in the process of compost. In contrast, the changes of Pb distributions were similar in two organic wastes. Pb was preferentially bound to the residual fraction and its BF decreased. The evolution of heavy metal distributions and BF depended on not only total metal concentrations but also the other properties, such as pH, decomposition of OM and decline of DOC. The germination rate (RSG), root growth (RRG) and germination index (GI) of pakchoi (Brassica Chinensis L.) increased during the composting process. Linear regression analysis demonstrated that GI, which could represent phytotoxic behavior to the plants, could be poorly predicted by BF or total amount of metals, i.e., BF-Zn, T-Cu. However, the inclusion of other physicochemical parameters (pH, OM and DOC) could enhance the linear regression significances (R).
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