*4.1. Status in 2012 and 2017*

Table 3 lists sectoral solid waste production, solid waste production coefficients, and export/import of solid waste in Fujian. The total waste production approached 275.66 <sup>×</sup> <sup>10</sup><sup>6</sup> t in 2012, where the direct and indirect productions accounted for 34.82% and 65.18%, respectively. Total waste production decreased to 236.05 <sup>×</sup> <sup>10</sup><sup>6</sup> t in 2017, with direct and indirect productions decreasing by 23.23% and 9.63%, respectively. The amount of indirect waste production was more than that of direct waste production, implying the significance of the indirect production flow calculation. In 2012, PM, AM, and CON were the dominant contributors, occupying 27.73, 42.75 and 12.59% of the total solid waste production. In 2017, the proportions of the three sectors' production were 34.17, 34.50, and 11.59%, respectively. These results revealed that solid waste was mainly produced by primary manufacturing (PM) and advanced manufacturing (AM). In addition, PM was the biggest solid waste net exporter (23.982 <sup>×</sup> <sup>10</sup><sup>6</sup> t in 2012 and 22.019 <sup>×</sup> <sup>10</sup><sup>6</sup> t in 2017) and CON was the largest importer (13.627 <sup>×</sup> <sup>10</sup><sup>6</sup> t in 2012 and 10.229 <sup>×</sup> <sup>10</sup><sup>6</sup> t in 2017). Fujian highly relied on clothing, lithium cells, auto parts manufacturing and food processing, and large amounts of construction materials were purchased from other provinces. Therefore, a future reduction strategy should focus on cutting down waste from these sectors.


**Table 3.** Results gained from physical input-output table in Fujian in 2012 and 2017.

Figure 2 describes the direct and indirect solid waste flows among sectors in 2012 and 2017. Each sector has a specific color and the line between sectors indicates the direction of waste flows. The width of the line in each sector represents the amount of waste inflow and outflow. All direct waste flows are positive, while indirect waste flows have positive and negative values. A positive value means one sector receives waste from the other sector, whereas a negative value denotes one sector delivers waste to the other sector. It can be seen that direct waste mainly flowed to CON, while indirect waste flowed to all sectors. In Figure 2a,b, the largest contributor of direct waste flow was AM, which contributed 54.23% and 44.18 % of the total amount in 2012 and 2017, respectively. It contributed a large part of its direct waste flow to CON and PM (occupying 27.62% in 2012 and 23.67% in 2017) and itself (accounting for 60.50% in 2012 and 66.01% in 2017). In Figure 2c,d, AM was still the largest contributor of indirect waste flow, which contributed 73.29% and 57.62 % of the total amount in 2012 and 2017, respectively. The indirect waste of AM flowing to all other sectors was almost the same (occupying 20% to 30%). These results show the relationship of indirect waste flows is more complicate than that of direct flows.

**Figure 2.** Direct and indirect solid waste flows among sectors. (**a**) 2012\_direct; (**b**) 2017\_direct; (**c**) 2012\_indirect; (**d**) 2017\_indirect.

Figure 3a displays the sectoral DFW (driving force weight) and PFW (pulling force weight) in 2012 and 2017, representing the control and dependent degrees of a sector on the USWS. AM's DFW and PFW were the highest; the values of DFW were 71.34% in 2012 and 55.43% in 2017; the values of PFW were 16.90% in 2012 and 17.89 % in 2017. These results indicate that AM was the biggest control sector and dependent sector that affected upstream sectors (basic industries that provide raw materials and primary products) and downstream sectors (advanced industry that consumes products from upstream). The sectoral total weight equals the difference between sectoral DFW and sectoral PFW. The sector was a controller in the system when DFW was greater than PFW, whereas the sector was a dependent sector in the system when DFW was smaller than PFW. Thus, AM finally acted as a controller, since its DFW was greater than PFW (Sectoral total weight = DFW−PFW > 0). It was obvious that AM and PM were dominant sectors that controlled the other producers, while the seven sectors (i.e., AGR, MIN, ELE, CON, TRA, WHO, and OTH) depended on the other sectors' product supply. In 2017, the total weight of AM and PM decreased by 7.34% compared with 2012 due to reduced economic production scales. Generally, the ecological hierarchy structure was not healthy due to the high sectoral total weight value of AM. Carrying out reduction measures from the production side (especially from AM) could be helpful for adjusting hierarchy structure of the USWS.

**Figure 3.** Ecological network analysis. (**a1**) sectoral DFW and PFW in 2012; (**a2**) sectoral DFW and PFW in 2017; (**b1**) sectoral pairwise relationships in 2012; (**b2**) sectoral pairwise relationships in 2017.

Figure 3b shows the sectoral pairwise relationships related to solid waste production in 2012 and 2017, with a total of 45 pairs of relationships in each year. Exploitation relationships contributed 54.77% and 68.89% to all pairs of relationships in 2012 and 2017. The proportions of mutualism relationships were 13.33% in 2012 and 6.67% in 2017. High value of *SI* (i.e., *SI* = 8.96 > 0 in 2012, *SI* = 9.65 > 0 in 2017) indicated the synergistic effect of the USWS. A high value of *MI* (i.e., *MI* = 1.38 > 1 in 2012, *MI* = 1.31 > 1 in 2017) showed that the USWS was mutualistic. Results of sectoral pairwise relationships were acceptable for decision makers. However, the number of mutualism relationships in 2017 was less than that in 2012. In order to make the USWS more beneficial, exploitation relationships needed to be transformed to mutualism relationships, as much as possible, through adjusting strategies. It was also found that the production structure of Fujian had little changes.
