3. In wastewater treatment, bacteria are often grown to clean up the pollutants
ID: 3323041 • Letter: 3
Question
3. In wastewater treatment, bacteria are often grown to clean up the pollutants in water. In one of Dr. Lin's early projects, he attempted to observe the growth of a group of wastewater treatment bacteria after feeding them with beef broth for 48 hours. He recorded the initial biomass concentration before the feeding, final biomass concentration after the feeding and the amount of organics in beef broth digested by the bacteria. The data and analysis are shown below. Based on the results, answer the following: (50 points) a) From the scattered plots, do you see any correlation between the parameters? Do you b) Two regression analyses were performed with the data (see output below), which one c) Predict the final biomass concentration (mg/L) at an initial biomass concentration of d) In the ANOVA table of Regression #2, what are the values of x, y, z, p, and q? think it is a good idea to use an empirical model to study the bacteria growth? Why? is a better model and why? 80 and a digested organics of 150 mg/L Regression #1 the regression equation is: (Final Bioms ss-Ini. Bionsss13.7-0.242 Digested Org Residual Plots for (Final-Ini) Biomass Predietor Constan Digested Org. 0.24120 0.04459 5.41 0.002 Coef SE Coef -13.70 10.93-1.250.246 S-5.64353 R-Sq-78.58 R-Sq tady) -75.8 Analysis of Variance D MS Source Regression altrer 1 273.23 999:25 2%26 o.001 Total 9 1272.40 Regression #2 tion is: Final Biomass 23.0 1.40 tni. Biomass 0.216 DEgested org The Residual Plats for Final Biomass Predictor Constant Ini. Biomass 1.39570.5825 2.40 0.048 Coef SE Coef P -22.99 17.76 -1.29 0.237 Digested org 0.217610.05777 3.77 0.007 Analysis of Variance DF SS NSE 35 x 1764.22 Source Regression Residual Error y 256.28 Total 9 0.001 9 2020.50Explanation / Answer
(a) There is no scatter plot given in the diagram between the parameters.
Yes, it is a good idea to build an empirical model to predict bacterial growth as it is easy to use and easier to interpret. Also, it predicts the growth of bacteria to a good accuracy.
(b) Regression #2 model is a better model as adjusted R2 value is higher in this case which means it is predicting the final biomass value to a higher level of accuracy. Also, both the input variables i.e. initial biomass and digested organics are coming out to be significant which means both are impacting the final biomass value.
(c) Initial biomass = 80
Digested organics = 150 mg/L
From the Regrssion #2 model, the equation is:
FInal biomass = -23 + 1.40*Initial biomass +0.218*Digested organics
= -23 + 1.40*80 + 0.218*150
= -23 + 112 + 32.7
= 121.7
Hence, final biomass = 121.7
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