Table 2 Variables and equations of Shanghai green transformation system.
Variables | Unit | Properties | Equations |
|---|---|---|---|
GDP | billion | L | = INTEG(Incremental GDP,25269.8) |
Forestry areas | km2 | L | = INTEG(Incremental forestry areas,1033.6) |
Total carbon trading quota | billion tons | R | = INTEG(The change in carbon trading quota, 1.6) |
Technology investment ratio | % | A | = (((Time-2013)*0.1048 + 3.1802)*0.01)*100 |
Emission efficiency | % | A | = Technology Investment*0.009 + 52.1023 |
Excessive carbon dioxide emissions | million tons | A | = Carbon emissions - Total carbon trading quota*10000 |
Carbon sink | million tons | A | = Forestry areas * Forestry carbon sink coefficient/10000 |
Punishment price | RMB/ton | A | = Carbon trading price *3 |
Maximum fine | billion | A | = Total carbon trading quota * Punishment price |
Industrial energy consumption | million tons of standard coal | A | = Secondary industry output value*(−0.1883) + 7346.71 |
Non-industrial energy consumption | million tons of standard coal | A | = Tertiary industry output value *0.133908–2.67798* Primary industry output value + 3012.24 |
Total energy consumption | million tons of standard coal | A | = Production energy consumption + Domestic energy consumption |
Production energy consumption | million tons of standard coal | A | = Non-industrial energy consumption + Industrial energy consumption |
Domestic energy consumption | million tons of standard coal | A | = Per capita domestic energy consumption * Total population*0.001 |
Fines | billion | A | = IFTHENELSE (Excessive carbon dioxide emissions <0, 0, IFTHENELSE (Excessive carbon dioxide emissions < (Maximum fine/Punishment price*10000), Punishment price* Excessive carbon dioxide emissions *0.0001, Maximum fine)) |
Birth rate | ‰ | A | = WITHLOOKUP (Time, ([(2014,0) -(2025,0.01)], (2014,0.00835), (2015,0.00752), (2016,0.009), (2017,0.0081), (2018,0.0072), (2019,0.007), (2022,0.008), (2025,0.0068))) |
In-migration population | million people | A | = WITHLOOKUP (Time, ([(2014,0) -(2025,15)], (2014,11.55), (2015,11.61), (2016,11.25), (2017,11.85), (2018,13.75), (2019,13.69),(2025,15))) |
The proportion of secondary industry output value in GDP | – | A | = WITHLOOKUP (Time, ([(2014,0) -(2025,0.5)], (2014,0.330), (2015,0.317), (2016,0.304), (2017,0.292), (2018,0.280), (2019,0.276), (2020,0.270), (2021,0.266), (2022,0.262), (2023,0.258), (2025,0.252))) |
The proportion of non-fossil fuel energy consumption | – | A | = WITHLOOKUP (Time, ([(0,0) -(3000,10)], (2014,0.11), (2015,0.12), (2016,0.13), (2017,0.14), (2018,0.15), (2019,0.16), (2025,0.18))) |
Per capita domestic energy consumption | tons of standard coal/person | A | = WITHLOOKUP (Time, ([(2014,0) -(2025,600)], (2014,474.16), (2015,505.7), (2016,489.27), (2017,500.54), (2018,529.65), (2019,528.92), (2025,524.2))) |
Carbon trading price | RMB/ton | exogenous | = WITHLOOKUP (Time, ([(2014,0) -(2025,60)], (2014,39.9997), (2015,20.7483), (2016,5.2343), (2017,23.2841), (2018,28.9083), (2019,41.4464), (2025,87))) |
