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A response surface model allowing nitrogen concentration to affect organic waste-derived compost

Abstract:

Differing human activities which have lead to different nations' economic development (excellent scientific, technological consequences and innovation) and caused changes which have not seemed to be the most suited for preserving the resources necessary for sustaining the lives of human beings living in the present or for those of future generations. The wasteful use of different power resources is leading to their exhaustion and substances and waste are being generated leading to environmental contamination. On the other hand, inadequate sanitary conditions are also being produced which can cause difficulties in the field of public health. The Central University of Venezuela has thus proposed dealing with and satisfactorily resolving solid-waste management by exploiting the organic fraction of the waste produced by the university's dining room for making compost. This requires implementing the composting and ensuring that the quality of the materials produced is reproducible. A useful tool for achieving the latter lies in producing a statistical design for composting, leading to a mathematical equation determining factors (independent variables) influence on response (dependent variable) (i.e. the likely power which initially mixed waste may have on nitrogen quality). This methodology leads to obtaining an equation allowing a response surface to be generated. This information would make it possible to control the quality of the product obtained (compost) according to the conditions laid down. This study was aimed at applying the Box-Behnken experimental design in drawing up a response surface model allowing conditions in producing compost to be considered where nitrogen contribution is reproducible. This statistical tool uses four factors or independent variables at three levels; they were: added waste portions (D), amount of sawdust (C) and added humidity (A), as well as aeration period (B). Response measured as nutrient input indicator was nitrogen (N). This design was based on 29 different trials combining the factors being considered. The surface model led to obtaining a quadratic function, as shown in the following equation: Y = β0 + Σi=1k βi X i + Σi=1k βii X i2 + Σi=1k-1 Σj=1k βij Xi X j + ε i where Y corresponded to analysed response, X1, X 2⋯.X4 corresponded to the four selected factors and ε was random error. The following equation was thus obtained: Ln(N-ammoniac) = Lny2 = - 2,17 - 0.069 A -0.24 B - 0.48 C + 0.15 D. The maximum point for the amount of nitrogen on the response surface was located by using the estimated equation. The model so obtained was verified by making more compost according to the maximum conditions indicated by the response surface model, finding that the quantity of nitrogen was that expected according to the model. This led to setting the optimum conditions for preparing compost from university dining room waste; its nitrogen contribution was reproducible.