Q- Q plot (Zn)
4.7 Artificial Neural Network
4.7.3 Error Histogram
138 Regression Coefficient of Nickel, Lead and Zinc
The R-values of training, validation, testing and the whole datasets were found to be 1, which directly represented the observed values of Ni was predicted accurately (Figure 4.33). From Figure 4.34, the R-values acquired as 1, 1, 0.99992 and 0.99996 from training, validation, testing and the whole datasets, respectively, for the metal element of Pb. As the R-value was closed to 1 (0.99996), the prediction was considered to be precise. Moreover, based on the above statement, it can be decided that there was a close relationship between observed and predicted data in case of Zn (Figure 4.35). In addition, the error histogram plotted by ANN for metal elements of Al, As, Ba, Ca, Co, Cr, Cu, Fe, Hg, K, Mn, Na, Sb, Sc, Sr, Ti, and V provided in Figure G.18 to Figure G. 34 in the Annex-G.
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Figure 4.37, the error was reported as -6.3*10-5, which indicated smaller error, tends to zero which indicate perfect prediction.
Figure 4.36: Histogram plot of Cd. Figure 4.37: Histogram plot of Ni.
Figure 4.38: Histogram plot of Pb. Figure 4.39: Histogram plot of Zn.
Metal element of Pb showed that most data fall on zero error line which provided an idea to check the outliers to indicate those data points were similar to the rest of the data set (Figure 4.38). The error was reported as -0.0205, which indicated smaller error, tends to zero which indicate perfect prediction. Furthermore, Zn also showed negligible value of error (0.0029), which indicate prediction of the concentration of metal element of Zn was faithfully perfect (Figure 4.39). In addition, the error histogram plotted by ANN for metal elements of Al, As, Ba, Ca, Co, Cr, Cu, Fe, Hg, K, Mn, Na, Sb, Sc, Sr, Ti, and V provided in Figure G.35 to Figure G.51 in the Annex-G.
140 4.8 Concluding Remarks
The term ―landfill‖ is a unit, designed and operated for the disposal of municipal solid waste (MSW) to protect the environmental components (water, soil, air, etc.) and all the living beings from the contaminants like metal elements presence in MSW stream (Alamgir et al., 2005). MSW can be disposed either in form of open dumping or disposal in sanitary landfill. In developing countries like Bangladesh, open dumping has become a traditional practice to dispose MSW. Due to long retention of MSW on dumping site, MSW decomposes and produces three components of solid, liquid and landfill gas. In addition, leachate and contaminated soil creates vulnerable effects to the environmental components and nearby inhabitants. There has long been concern about the issue of contamination of soil by metal elements because of their toxicity for plant, animal and human beings as well as their lack of biodegradability (Li et al., 2006; Zhuang et al., 2009). Soil is a multi-phase system contaminated with the presence of xenobiotic (human- made) chemicals or other alteration in the natural soil environment due to improper disposal of MSW, industrial activity and agricultural chemicals. Soil contamination occurs when the presence of toxic chemicals, pollutants or contaminants with high concentrations in soil and it has great risk to plants, wildlife, humans and of course for the soil itself (Jia et al., 2010). The concentration of metal elements in soil and their impact on ecosystems can be influenced by many factors such as the parent rock, climate and anthropogenic activities (Jia et al., 2010).
In Khulna city, most of the MSWs are collected from door-to-door without any sorting and dumped in open disposal site at Rajbandh. Due to inadequate management practices of MSW, necessities arise to take steps for the proper disposal of MSW as well as maintenance of disposal site at Rajbandh, Khulna, Bangladesh. Moreover, to date, there is no comprehensive study to examine how the metal elements are correlated to each other as well as their possible sources of contamination such as anthropogenic or human activities and natural parent materials. In addition, there is no ready manual or guidebook related to this research from where one can easily get the information about quantitative distribution of metal elements spatially as well as the level of contamination of soil due to presence of metal elements in soil. Thus unplanned disposal, irregular unloading and improper maintenance of MSW in waste disposal site consequent of contamination of pollutants
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such as metal elements in soil and environment of waste disposal site as well as in surrounding areas. This random disposal of MSW also consequences health effects on all living being near the waste disposal site
The main purpose of this study was to find out the possible sources of contamination of metal elements and the distribution of metal elements spatially in soil of waste disposal site. To these endeavors, total sixty soil samples were collected at a depth of 0-30 cm from the existing ground surface from different selected locations within the waste disposal site.
These study periods covered both the dry season (March to May, 2016) and rainy season (June to August, 2016). In the laboratory, the concentration of metal elements such as Al, As, Ba, Ca, Fe, Hg, K, Mn, Na, Na, Pb, Sb, Sc, Sr, Ti, V and Zn in soil were measured through standard test methods. To evaluate the nature of measured concentration of all the studied metal elements, the normality test was performed through K-S test and S-W test categorized distinctly for both the dry and rainy season. For more accurate result, normal QQ plot was also plotted to check the distribution of metal elements either normally or not.
Conventional statistics, based on mathematical indices such as mean, median, maximum, minimum, CV, SD, skewness and kurtosis were evaluated to show the variability of metal elements in soil for both the dry and rainy season. Moreover, multivariate statistics including pearson correlation was accomplished to measure the linear correlation between metal elements in soil. In addition, The PCA was implemented to explain the major generation sources of metal elements to exploit the soil of waste disposal site.
Furthermore, the AHC was also performed to classify the metal elements on the basis of dissimilarity between sets of observations. Perfect prediction of metal elements using different interpolation techniques of IDW, LP, RBF’s and ordinary kriging exhibited better field condition of spread out of metal elements in soil of waste disposal site. Moreover, the accuracy of these interpolation techniques were checked based several indices such as MAPE, RI and G-value. In this study, a network model was developed by ANN to predict and depict the validity based MSE and R-value of the observed data of metal elements obtained from laboratory. It was found that the predicted values from ANN were almost same as obtained from laboratory. The main outcome of this study was to know the correlation of metal elements with each other in soil, possible sources of their contamination, distribution of metal elements spatially and the level of contamination of soil due to presence of metal elements in soil.
142 CHAPTER V
COMPARISON AND VALIDATION