What are the determinants of wastewater discharge reduction in China? Decomposition analysis by LMDI

Drivers and Decoupling Effects of PM2.5 Emissions in China: An Application of the Generalized Divisia Index

“…Specifically, the reduced level of PM 2.5 emissions due to emission intensity (∆PMG) is 51,253,335 Mg per year on average, implying that reducing emission intensity (∆PMG) can effectively improve air quality. In addition, the emission coefficient (∆PME) is another significant driver of PM 2.5 emission reduction, in line with the findings in the literature [35]. It is observed that the emission coefficient (∆PME) reduced PM 2.5 emissions for this entire term by an average of 354,372.4 Mg a year, except for 2012-2013.…”

“…With increasing R&D expenditure, the technology innovations of enterprises have been improved, in turn increasing the efficiency of factor utilization and reducing PM 2.5 emissions [44,45]. In line with previous studies, emission intensity (∆PMG) also has a negative impact on PM 2.5 emissions [30,35,53]. Specifically, the reduced level of PM 2.5 emissions due to emission intensity (∆PMG) is 51,253,335 Mg per year on average, implying that reducing emission intensity (∆PMG) can effectively improve air quality.…”

“…The logarithmic mean Divisia index (LMDI), which uses the log mean weight function and shows perfect performance in factor decomposition, has been shown preference in the literature [31,32]. For example, by applying the LMDI technique, Raza and Lin investigated the drivers of transport CO 2 emissions in the case of Pakistan from 1984 to 2018 [33]; Lyu et al identified the determinants of PM 2.5 , NOx, and SO 2 emissions in China from 1997 to 2012 [34]; and Tian et al measured the contributions of factors governing wastewater discharge in China at the provincial level from 2011 to 2017 [35]. However, the LMDI method is unable to reveal the effects of multiple absolute indicators [22], and contradictory results may occur when the LMDI decomposition forms are different [36].…”