simulation analysis of policy for waste treatment toward a

Journal of Sustainable Development; Vol. 10, No. 4; 2017 ISSN 1913-9063 E-ISSN 1913-9071

Published by Canadian Center of Science and Education

65

Simulation Analysis of Policy for Waste Treatment toward a Sound Material-cycle Society in Tokyo

Noriko Nozaki1, Keyu Lu2, Rajeev Kumar Singh3, Takeshi Mizunoya4, Helmut Yabar4 & Yoshiro Higano4 1 Graduate School of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Ibaraki, Japan 2 Science & Research Department, Chinese Society for Urban Studies, Beijing, China 3 Sustainable Consumption and Production (SCP), Institute for Global Environmental Strategies (IGES), Hayama, Kanagawa, Japan 4 Faculty of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Ibaraki, Japan

Correspondence: Noriko Nozaki, Graduate School of Life and Environmental Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8572, Japan. Tel: 81-29-853-7255. E-mail: [email protected]

Received: May 16, 2017 Accepted: July 12, 2017 Online Published: July 30, 2017

doi:10.5539/jsd.v10n4p65 URL: https://doi.org/10.5539/jsd.v10n4p65

Abstract Enhancing resource productivity is effective to improve trade-off between the environment and economy. For minimizing consumption of natural resources required for economic activities, it is necessary to strengthen both material recycling and energy utilization, which reduce final disposal amount and return waste to economic activities as resource.

This study seeks to clarify environmental economic policy for promoting establishment of sound material-cycle society subject to keeping or expanding the regional economic scale, and enhancing the amount of material recycling and reducing greenhouse gas (GHG) emissions. Study area is Tokyo metropolitan area. To reduce GHG emissions and final disposal amount, we consider promoting both material recycling and energy utilization thoroughly. Under these circumstances, we construct an expanded input-output model. The model includes the flows of waste and energy, and emissions of GHG. With restrictions on GHG emissions, Gross Regional Product (GRP) is maximized as the objective function. We quantitatively analyze how much tax and subsidy on discharging waste is required for sound material-cycle society along with analysis on effects of the policy by model simulation.

The results show that, with 10 yen/kg tax on discharging waste, final disposal amount per GRP was 11% lower than the baseline case.

Keywords: energy utilization, input-output model, material recycling, policy evaluation, waste

1. Introduction In the 1960s, during so-called high-growth period, economic activities in Japan were based on mass-production, mass-consumption and mass-disposal. This social structure initiated many environmental issues such as depletion of natural resources, shortage of landfill site and excessive emission of pollutants including GHG along with outbreak of four major environmental pollutions in Japanese history. The fundamental problem with this society is existence of trade-off between the environment and economic growth. To improve the trade-off and shift the society with a sustainable economic system, it is effective to enhance resource productivity with the idea of a sound material-cycle society.

In Japan, legal systems to establish a sound material-cycle society has already implemented around 2000 (Bureau of Environment, 2014). However, in Tokyo, majority of waste is simply incinerated and the ash goes to landfill site (Bureau of Environment, 2014). When we consider only biomass in waste, potential energy corresponds to 14.1% of the energy consumption in Tokyo whereas the actual use in 2011 is only about 5.2% of the potential energy per our estimation (see Figure 1 and Table 1). Moreover, biomass is mostly used for generating power through incineration. There are more efficient methods for biomass such as methane fermentation and conversion into biodiesel fuel (BDF). If we use these methods, we can achieve higher resource productivity.

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69

= (4)

where

: Endogenous column vectors of energy demand amount of j industries

: Exogenous column vectors of energy demand coefficients of j industries

: Endogenous values of total energy demand of households

: Endogenous values of households’ consumption of each energy

: An exogenous value of energy demand coefficients of households

: Diagonal matrices whose diagonal elements are the elements of

subscript e=2,8

2.3.2 Demand of Each Energy

This equation holds for both ‘Tokyo metropolitan city’ and ‘Other region’. = ∑ + ∑ + ∑ + ∑ + ∑ + ∑ + ∑ + ∑ + ∑ +∑ + ∑ + ∑ (5) = (1) + (2) + (3) + (4) + (5) + (6) + (7) + (8) + (9) + (10) + (11) + (12) (6)

where

, , , , , , , , , , , , , , , ,

, , , , , , ,

: Endogenous column vectors of energy demand for each energy by each industry in sector j

: Coal mining, : Crude petroleum, : Natural gas, : Gasoline,

: Kerosene, : Diesel oil, : Miscellaneous petroleum refinery products,

: Coal products, : Electricity, : Private power generation, : Gas supply,

: Steam and hot water supply

, , , , , , , , , , ,

: Endogenous values of energy demand for each energy by households

subscript c: Households

2.3.3 Total Energy Supply

Equation (7) represents that coal mining sector supply more than their total demand. Similar equations hold for each energy. For energy in ‘Other region’, left sides are all singular. (1) (1) + (1) (1) ≥ ∑ + + (7)

where

: Exogenous row vectors of energy supply coefficient of i industries

l: A row vector for summation

2.4 Balance of Waste Flow

The total waste discharged amount consists of discharged waste by production of each industry and by household consumption. Similar equation holds for ‘Other region’. = + + + + ( + + + + ) (8)

where

subscript w: Waste

: Endogenous column vectors of total disposal amount of waste

2.5 Amount of Emission of GHG

The amount of GHG emitted is calculated by multiplying GHG emission coefficient to products of each industry


70

and household’s consumption amount respectively. = + + + + + + ( + ) (9)

where

subscript z: Greenhouse gas

: An endogenous variable of total emission of GHG

2.6 Value Balances

2.6.1 Value Balances of Usual Industries

The left side represents income due to selling goods, and the right side represents expenditure needed for production. As we assume perfect competitive market, income should not exceed expenditure because firms produce until there is no excess profit. The last entity in right side represents waste discharging tax imposed on industries in Tokyo by multiplying the amount of waste discharged by production of goods and waste discharging tax rate. ≤ + + + + + + + + + + t (10) where

: Exogenous row vectors of households’ income of each industry in j industries

: Exogenous row vectors of depreciation of each industry in j industries

: Exogenous row vectors of indirect tax of each industry in j industries

: An exogenous value of tax rate on discharging waste, operating variable

Similar equations hold for ‘Material recycled goods utilizing industries in Tokyo’, ‘Usual industries in other region’, energy industries and waste treatment industries.

Expenditure on energy needed for production is equivalent to purchase of demanded amount which is determined by balance of energy mentioned above. Hence, instead of input-output coefficient, equation (11) is used for expenditure on energy which is in right side of value balance of each industry. = (1)t + (2)t + (3)t + (4)t + (5)t + (6)t + (7)t + (8)t + (9)t + (10)t + (11)t + (12)t (11)

where

: Endogenous row vectors of expenses for energy required for production of j industries

: Endogenous row vectors of price rates of goods i

2.6.2 Value Balances of New Waste Treatment Industries in Tokyo (material recycling)

The last entity in left side represents subsidy for introducing new waste treatment industries and extending their activities. The subsidy comes from waste discharging tax which is the last entity of equation (10). Similar equation holds for ‘New Waste Treatment Industries in Tokyo (energy utilization)’. + = + + + + + + + (12)

where

: Endogenous row vectors of subsidy for industries

2.7 Disposal Income

Disposal income of household is given by national income minus direct tax. Similar equation holds for ‘Other region’. = (1 − )( + + + + + ) (13)

where

: Endogenous values of disposal income of households

: An exogenous value of direct tax rate

2.8 Consumption and Saving of Households

Disposal income is divided into consumption and savings of every goods by certain proportion. The sum of


71

proportion of consumption and saving is 1. Similar equations hold for ‘Other region’. + t = (14) = (15) + = 1 (16)

where

: Exogenous row vectors of consumption ratio with goods i of households

: Exogenous values of saving ratio of households

: Endogenous values of saving of households

2.9 Objective Function

We set GRP as objective function and maximized it under constraints of 87 equations. = + + + + + + + + + + + + + + + + + (17) (18)

2.10 Case Setting

We set three cases as shown in Table 2. Case0 is the baseline case. In case1, new waste treatment industries are introduced but there is no tax-subsidy policy. In case2, waste discharging tax is implemented. The tax is a specific duty which is imposed on discharged amount of waste. All the money collected by the tax is spent as subsidy to Waste treatment industries in Tokyo and New waste treatment industries in Tokyo.

Table 2. Case setting

New industries Tax-subsidy

case0 ✕ ✕

case1 ✓ ✕

case2 ✓ ✓

In the next chapter, with GHG emissions restriction at the 2011 level in case0 is referred to as case0 (0%), and we analyze the results with case0 (0%) as the standard.

3. Simulation Results 3.1 Effect of Introducing New Industries

Figure 5 shows changes in GRP and Gross Domestic Product (GDP) along with GHG emissions restriction. In case0 (0%) which is baseline case and GHG emissions amount is 2011 level, GRP is 99 008 680 million yen and GDP is 553 089 100 million yen while the actual value in 2011 is 100 868 188 million yen for GRP and 548 754 636 million yen for GDP. Differences between value of simulation result and actual value for GRP and GDP are 1.84% and 0.79%, respectively. Therefore, we consider that the simulation model used in the research and the results are valid. In case0, we got result only with restriction on GHG emissions till -6% of that of 2011. Meanwhile we got till -14.5% for case1 which is case with new industries. In both cases, GRP and GDP fell down as we tighten up GHG emissions restriction. However in case1, economic level was kept higher than case0 (0%) till -8% GHG emissions restriction. These indicate that deterioration in economic scale was suppressed by introduction of new industries. Here -8% GHG emissions restriction equals to only 3.5% GHG emissions reduction from 2000 level, which cannot fulfill the GHG reduction target of -25% from 2000 level.

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simulation analysis of policy for waste treatment toward a

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