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Life cycle environmental benefit and waste-to-energy potential of municipal solid waste management scenarios in Indonesia

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Abstract

Appropriate municipal solid waste management transition should be promoted for developing Asian countries. Thus, we established a life-cycle assessment model to assess the environmental impact of waste recycling, composting, incineration, and landfill with gas recovery (LFG) for 34 capital cities in Indonesia by 2025. Scenarios A (12.5% recycling + 12.5% composting + 37.5% incineration + 37.5% LFG), B (15% recycling + 10% composting + 50% incineration + 25% LFG), C (10% recycling + 15% composting + 25% incineration + 50% LFG), D (20% recycling + 5% composting + 75% incineration), and E (20% recycling + 5% composting + 75% LFG) are developed to quantify future environmental impacts and energy generation potential from waste-to-energy (WtE). Results show that Java contributes the highest environmental impacts, while Moluccas and Papua show the least impacts. Cumulative environmental benefits from scenarios A, E, D, B, and C were 98%, 97%, 92%, 91%, and 86%, respectively, compared to Business-as-Usual scenario. Incineration can provide more energy than LFG. Scenarios D and E generate the highest electricity from incineration and LFG, respectively. WtE electricity rate to social energy consumption is scenario B (5.34%) > D (5.22%) > A (4.81%) > C (4.27%) > E (1.49%). Scenario A is suggested considering its best environmental benefit, while scenario B is advised considering its highest electricity contribution rate. Finally, appropriate environmental mitigation schemes and WtE facilitation are proposed.

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Abbreviations

MSW:

Municipal solid waste

LFG:

Landfill gas

WtE:

Waste to energy

\({W}_{\mathrm{rate}}\) :

Daily waste generation per capita in the city (kg/capita/day)

\({W}_{\mathrm{Total}}\) :

Total amount of waste generation (collected) in the city (quantified as kg/day)

\({Q}_{\mathrm{pop}}\) :

Population numbers residing the city as MSW collection service

\({Q}_{{\mathrm{w}}_{2025}}\) :

Estimation of daily waste produced in 2025 (ton/day)

\({W}_{i}\) :

Quantity of waste category i (tons/day)

\({p}_{i}\) :

Percentage of waste category i in respective cities (%)

\({W}_{\mathrm{Total}}\) :

Daily amount of waste generation in respective cities (tons/day)

\({W}_{{\mathrm{Sc}}_{\mathrm{incineration}}}\) :

Quantity of waste available for incineration in respective scenario (tons/day)

\({\mathrm{MSW}}_{{\% \mathrm{sc}}_{\mathrm{incineration}}}\) :

Percentage of waste allocation in selected scenario (%)

\({\mathrm{Fw}}_{{\mathrm{Sc}}_{\mathrm{incineration}}}\) :

Adjusted fraction of incinerable waste in each scenario (%)

\(\mathrm{LCV}\) :

Lower calorific value (LVC) of the waste category (kcal/kg)

\({\mathrm{LCV}}_{{W}_{(i)}}\) :

LCV in each fraction of waste for MSW incineration (kJ/kg)

\({{\mathrm{LCV}}_{{W}_{(\mathrm{incineration})}}}_{i}\) :

LCV of waste category i incinerated (kJ/kg)

\({K}_{1}\) :

Constant value of a conversion from kcal/kg to kJ/kg (4.184)

\({\mathrm{LCV}}_{\mathrm{Total}}\) :

Cumulative LCV waste for incineration (kJ/kg)

\(P\) :

Amount of electric power (kW)

\(\gamma\) :

Thermal replacement achievable from incineration (0.316)

\({K}_{2}\) :

Adjustment constant for kW as electric power unit (0.001157)

\({\mathrm{Cap}}_{\mathrm{f}}\) :

Capacity factor of WtE incineration (0.7375)

\(\omega\) :

Total number of hours per annum (yearly equal as 8760)

\({E}_{\mathrm{Incineration}}\) :

Amount of electricity generated (kWh/year)

\({\alpha }\) :

Assumption of electricity usage for WtE power plant (6%)

\(\beta\) :

Assumption of heat loss (5%)

\({E}_{\mathrm{actual}}\) :

Net electricity produced (kWh/year)

\({Q\mathrm{waste}}_{\mathrm{daily} (t)}\) :

Total quantity of waste produced (ton/day) in year t

\({\mathrm{Pop}}_{\mathrm{year} \left(t\right)}\) :

Number of populations in year t

\({W}_{{t}_{\mathrm{rate}/\mathrm{capita}}}\) :

Waste generation rate per capita (kg/cap/day) in year t

\({N}_{{\mathrm{Days}}_{\mathrm{year} (t)}}\) :

Number of days in year t (adapted value: 365)

\({Q}_{{\mathrm{CH}}_{4}}\) :

Annual methane generation in the year of the calculation (m3/year)

\(t\) :

One year time increment

\(n\) :

Year of the calculation minus the initial year of waste acceptance

\(j\) :

0.1 Years of time increment

\(k\) :

Methane generation rate (year-1)

\({L}_{0}\) :

Potential CH4 generation capacity (m3/Mg)

\({M}_{t}\) :

Mass of waste accepted yth year (Mg)

\({A}_{t, j}\) :

Age of section j of the waste mass \({M}_{i}\) accepted in year t

\({\mathrm{Cap}}_{{\mathrm{CH}}_{4} (\mathrm{t})}\) :

CH4 captured from landfill in year t for power generation (m3/year)

\({\mathrm{eff}}_{{\mathrm{CH}}_{4}}\) :

Methane collection efficiency (0.75)

\({\mathrm{E}}_{{\mathrm{actual}}_{(\mathrm{LFG})}}\) :

Electricity potential produced from LFG (kWh/year)

\({\mathcalligra{v}}\) :

Methane heating value (37.2) in MJ/m3

\(\zeta\) :

Capacity factor (0.85)

\(\varphi\) :

Landfill oxidation factor (0.9)

\(\in\) :

Electrical conversion efficiency for internal combustion engine (35%)

\(\theta\) :

\(\mathrm{MJ to kWh}\) Conversion factor (3.6)

\({\mathcal{E}}_{y(2025){\mathrm{WtE}}_{\mathrm{Incineration}}}\) :

Incineration energy percentage to public energy consumption by 2025 in cities (%)

\({\mathcal{E}}_{y(2025){\mathrm{WtE}}_{\mathrm{LFG}}}\) :

LFG energy percentage to public energy consumption by 2025 in cities (%)

\({2025}_{{\mathrm{EP}}_{\mathrm{net}}{\mathrm{WtE}}_{\mathrm{Incineration}}}\) :

Total electricity production by 2025 from incineration (MWh/year)

\({2025}_{{\mathrm{EP}}_{{\mathrm{netWtE}}_{\mathrm{LFG}}}}\) :

Total electricity generation by 2025 from LFG (MWh/year)

\({2025}_{{\mathrm{EP}}_{\mathrm{capita}}}\) :

Total electricity consumption in cities by 2025 (MWh/year) considering Indonesian per capita energy consumption

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Acknowledgements

This study is supported by the National Natural Science Foundation of China (71974126, 72088101, 72061127004), the open fund of Shanghai Engineering Research Center of Solid Waste Treatment and Resource Recovery, and Shanghai Environmental Key Lab of Environmental Data and Intelligence.

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Authors and Affiliations

  1. School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, China

    Ade Brian Mustafa, Huijuan Dong & Chenyi Zhang

  2. Shanghai Engineering Research Center of Solid Waste Treatment and Resource Recovery, Shanghai Jiao Tong University, Shanghai, 200240, China

    Huijuan Dong

  3. Center for Social and Environmental Systems Research, National Institute for Environmental Studies, Tsukuba, 305-8506, Japan

    Minoru Fujii

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Contributions

Conceptualization, HD and ABM; methodology, ABM and HD; software, ABM; formal analysis, ABM and HD; writing—original draft preparation, ABM; writing—review and editing, ABM, CZ, and HD; visualization, ABM; supervision, HD and MF; funding acquisition, HD. All authors have read and agreed to the published version of the manuscript.

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Correspondence to Huijuan Dong.

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Mustafa, A.B., Dong, H., Zhang, C. et al. Life cycle environmental benefit and waste-to-energy potential of municipal solid waste management scenarios in Indonesia. J Mater Cycles Waste Manag 24, 1859–1877 (2022). https://doi.org/10.1007/s10163-022-01441-6

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