Evaluating the energy efficiency of wastewater treatment plants in the Yangtze River Delta: Perspectives on regional discrepancies

Novel Machine Learning-Based Energy Consumption Model of Wastewater Treatment Plants

“…However, the low importance is reflected on the ordinate of BOD and NH 3 −N. In general, the trends of COD and BOD are generally in line with Huang et al, 34 trend of NH 3 −N is a little conflict with the common sense, and we are going to explain it in the following discussion. When the independent variable was too large, a flat response occurred in this region of the predictive model due to the lack of data; in other words, when BOD i /BOD e or NH 3 −N i /NH 3 − N e was too large, there will be insufficient data in the database to train the model at this level and the prediction will be the average of these data; therefore, these regions are not discussed in the following analysis.…”

“…The overall trend is consistent with the finding of previous studies. 33,34 What is more, this finding also follows the scale economy of WWTPs. 46 The construction scale of WWTPs in China can be divided into five categories [according to the Ministry of Construction of China (2001).…”

“…However, as overload may damage the instruments and equipment, a load rate between 60 and 100% should be maintained in the design and operation of WWTPs. The trend in this study corresponds well the results of Huang et al, 34 and it also follows the rule of extensive models of different factory managements. 47 This finding indicates that it will be better to do more studies on the amount of wastewater needed to be treated in one area before designing the treatment capacity of the WWTP.…”

“…RF has also been applied to environmental engineering, such as for mapping canopy nitrogen and in environmental assessment . However, RF is rarely used to analyze and predict energy consumption of WWTPs. , Data envelopment analysis , and multiple linear regression are commonly used methods to analyze the energy efficiency of WWTPs. The main principle of data envelopment analysis is using the method of linear programming, and multiple linear regression is a kind of generalized linear model.…”

A modified dynamic DEA model to assess the wastewater treatment efficiency: perspective from Yangtze River and Non-Yangtze River Basin

“…Urbanization level has a significantly positive impact on wastewater output efficiency in each region Water pollution disease efficiency and the total efficiency of the eastern, western, and central regions all show a decreasing trend COD; urbanization rate water diseases; wastewater treatment capacity; COD Sun et al 14 Sun et al 15 Dynamic exogenous variable SBM-DEA Dynamic network SBM-DEA Wastewater treatment plants GHG; COD; climate type eco-efficiency; carbon footprint; CO 2; techno-economic efficiency; technological gap ratios; concentration of pollutants Zhang et al 16 ; Dong et al 17 ; Gémar et al 18 WRDDM. ; Combining DEA with uncertainty assessment The operational costs and greenhouse gas emissions are the main drivers reducing eco-productivity WWTPs in eastern and western China significantly outperform those in the central region in terms of mean efficiency and performance stability An et al 26 ESDA model; super-efficiency DEA; Malmquist index From 2011 to 2015, urban wastewater discharge showed a spatial agglomeration trend Both technological upgrade and scale-up efficiency are negative, leading to low overall efficiency Zhang et al 27 Statistical data analysis Unbalanced population distribution and economic development led to differences in the efficiency of wastewater treatment plants between regions Hernández-Sancho et al 28 ; Hernández-Sancho et al 29 Non-radial DEA The efficiency levels for the studied sample of WWTPs are low Plant size, quantity of eliminated organic matter, and bioreactor aeration type are significant variables affecting the energy efficiency of WWTPs Huang et al 30 Applied energy The study evaluated the energy efficiency of wastewater treatment plants in the Yangtze River Delta and gave perspectives on regional discrepancies Jiang et al 31 SBM-DEA Large WWTPs operate more efficiently than small ones. Of these, 170 wastewater treatment plants are relatively efficient, with a score of 1; 691 low-efficiency samples have different degrees of excess input or insufficie...…”