Decomposition Analyses for COD Discharges in China’s Industrial Sub-Sectors: Which is the Superior Method?

Abstract

Numerous index decomposition analysis approaches have been reported in the past 30 years. However, the selection of different methods appears to be arbitrary, and little consensus has been reached on which is the superior method. Between 2001 and 2009, 10 different methods have been used to identify the factors (i.e. production effect, structural effect and intensity effect) influencing on China’s industrial wastewater pollutant (Chemical Oxygen Demand, COD) discharges. From the aspect of theoretical foundation, adaptability, ease of use, and ease of result interpretation, these methods are compared. Results show that: (1) LMDI 1 is a superior approach because of zero residual error in decomposition, no zero values problem in data set, simplicity in formula, and wide range in usage situations. (2) the average effect changes of industrial wastewater changes of COD discharges in China is 14.89 ×104 t with production effect, structural effect, and intensity effect were 72.97×104 t, -6.93×104 t and -80.94×104 t, respectively. (3) production effect was the major factor responsible for the rise of COD discharges, accounting for 45% of the total contribution. (4) structural effect contributed to the decrease of COD discharges with a small effect of 4% in total contribution. (5) intensity effect had an dominant decremental effect in COD discharges.

The Driving Forces of Point Source Wastewater Emission: Case Study of COD and NH4-N Discharges in Mainland China

“…At the same time, it is worth noting that an increasing trend in the emissions of COD and NH 4 -N was observed from 2004 to 2005 and 2010 to 2011. The possible explanation is the implementation of macroeconomic policies like the increase in investment, which had encouraged a large number of projects such as infrastructure construction and industrial projects [35,37]. For instance, in 2005, a serious water pollution incidents occurred in the Songhua river of Northeast China where about 100 tons of benzene were directly discharged, leading to a sharp increase in water pollution levels that year [47].…”

“…Moreover, LMDI can process the zero value in data which doesn’t affect the final result [31,32,33]. Hence, the LMDI method has been applied to identify key driving factors of wastewater discharge in China at the provincial level [19], industrial wastewater emissions [34,35], household wastewater emissions [36] and the COD discharge in China’s industrial sub-sectors [37,38]. These studies explore the driving factors of China’s wastewater emission change under different time scales, including economic scale, industrial structure, technological progress, and population size, and proposing industry or regional emission reduction strategies.…”