Decomposing the Influencing Factors of China’s Industrial Wastewater Discharges Using LMDI I Method

Abstract

China’s industry accounts for 46.8% of the national gross domestic product (GDP) and plays an important strategic role to its economic growth, but it is also the main water pollution sources. In order to identify the relationship between the underlying driving forces and various environmental indicators, two critical industrial wastewater pollutant discharges over 2001-2009, including Chemical Oxygen Demand (COD) and ammonia nitrogen (NH4-N), were decomposed into three factors, i.e., production effect (caused by change in the scale of economic activity), structural effect (caused by change in economic structure) and intensity effect (caused by change in technological level of the sector), using a logarithmic mean Divisia index I (LMDI I) decomposition method. Results showed that: (1) the average annual effect changes of industrial wastewater changes of COD discharges in China is -2.99% with the production effect, structural effect, and intensity effect as 14.64%, -1.39%, and -16.24%, respectively. Similarly, the average effect changes of industrial wastewater changes of NH4-N discharges is -4.03% with production effect, structural effect, and intensity effect as 16.18%, -2.88%, and -17.33%, respectively. (2) production effect was the major factor responsible for the rise of COD and NH4-N discharges, accounting for 45% and 44% of the total contribution. (3) structural effect contributed to the decrease of COD and NH4-N discharges with a small effect of 4% and 8% in total contribution. (4) intensity effect had an dominant decremental effect in COD and NH4-N discharges, accounting for 50% and 48% of the total contribution; intensity effect could be further decomposed in cleaner production effect and pollution abatement effect, and cleaner production effect of COD and NH4-N accounts for 60% and 55% in pollution reduction. (5) the main contributors to incremental COD and NH4-N discharges among industrial sub-sectors were manufacture of paper and paper products, processing of food from agricultural products, manufacture of textile and so on. These sectors should be the top priorities for policy makers to reduce pollutants discharges, and the potential measures are industrial restructuring and related regulation.

Sustainable Development Goal 6 Assessment and Attribution Analysis of Underdeveloped Small Regions Using Integrated Multisource Data

“…In terms of assessing the action degree of influence variables, this study is consistent with previous findings, with results indicating that the contribution of economic scale and technological level is significant [24,40], while the impact of population size and industrial structure is minimal [40,41]. Technical level and industrial structure are the influencing aspects that were found to be most consistent with previous studies in terms of action orientation, and improvements in technical level and industrial structure have a positive impact on the SDG 6 composite index [21,[23][24][25]. Existing research differs in terms of economic scale and population size.…”

Analysis of anthropogenic nitrogen and its influencing factors in Beijing

“…In addition, most studies suggested that technological effects (Ding et al, 2017) and intensity effects (Lei et al, 2012) inhibited the growth of nitrogen consumption and emission, whereas the material intensity factor in the present study also showed high inhibition, accounting for more than 20% of the total. The direction of structural effects in previous research was usually divided into phases in which the change either promoted or inhibited consumption of reactive nitrogen (Wang, 2017), whereas the industrial structural effect observed in the present study consistently inhibited the growth of Beijing's anthropogenic reactive nitrogen consumption.…”

“…In the context of nitrogen, the LMDI method has mainly been applied to nitrogen pollutant emission, with the goal of decomposing the factors that drive nitrogen emission in terms of their structure, scale, efficiency, and intensity, while also accounting for social and technological improvements. The structural effects used in previous studies always included factors related to the economic and energy structure of the system being studied (Wang, 2017) and its industrial structure (Lei et al, 2012).…”

Measuring the incremental impact of Payments for Watershed Services on water quality in a transboundary river basin in China

“…Factors identified in the Chinese literature as affecting industrial pollution include urbanization, regional economic development, industrialization, capital investments, human capital and government expenditures, including for environmental protection (e.g. He et al, 2014;Lei et al, 2012;Xiao et al, 2011). Besides the size of industrial output, also the composition of the industry sector is expected to play an important role in industry pollution.…”