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Research Article

An evaluation of alternatives to energy recovery from municipal solid waste part 2: energy balance and carbon footprint

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Pages 4712-4723 | Received 21 Mar 2019, Accepted 09 Aug 2019, Published online: 25 Sep 2019
 

ABSTRACT

This two-part paper, which consists of Part 1: waste flow and energy potential, and Part 2: energy balance and carbon footprint, respectively, aims to evaluate alternatives to energy recovery from Municipal Solid Waste (MSW) in Pyongyang. This second part, as the ongoing research, focuses on an evaluation of the alternatives to energy recovery from MSW in terms of energy balance and carbon footprint. Based on an analysis of mass and energy balance in the alternatives, this study evaluates net electricity and energy-related carbon footprint from the alternatives in Pyongyang, respectively, regarding the energy consumption in each process and the transport of feedstock and residues (e.g., inerts and ash). The results show that alternative 1 could produce the largest net electricity, followed by alternative 3 and alternative 2, while net efficiency decreases by 25.3% in alternative 1, followed by alternative 3 and alternative 2, as 21.4% and 20.9%, respectively. In regard to the energy-related carbon footprint, alternative 3 has the largest carbon footprint as 13,222.7 CO2eq Mg, followed by alternative 2 and alternative 1, as 9,686.8 CO2eq Mg and 7,206.6 CO2eq Mg, respectively. In summary, the results reveal that alternative 1 could be the most favorable option in terms of the net electricity production, the net efficiency as well as the carbon footprint. Therefore, alternative 3 is highly recommended to the municipality. The research findings could make a valuable contribution to achievement of energy recovery from MSW in the municipality.

Nomenclature

Latin symbols

CFenergy in=

emissions by energy consumption in each process (CO2eq Mg)

CFtotal=

total GHG emissions (CO2eq Mg)

CFtransport=

emissions by transport in the alternatives (CO2eq Mg)

Dis=

total transport distance for each route (km)

EC=

electricity consumption in each process (kWh)

EFmix=

the weighted average CO2 emission factor per kWh of the national electricity mix (CO2 kg/kWh)

EFcoal=

CO2 emission factor per kWh from coal-fired power (CO2 kg/kWh)

EFhydro=

CO2 emission factor per kWh from hydro power (CO2 kg/kWh)

EFi=

CO2eq emission factor of ith GHG (i.e. CO2, CH4, and N2O) per kg of fuel (CO2eq kg/fuel kg)

Ein=

electricity consumption in each process of the alternatives (kWh)

Eout=

electricity output from each WtE process in the alternatives (kWh)

F=

fuel mass used per km in transport (fuel kg/km)

GWPi=

characterization factor of ith GHG

HVfuel=

average heating value of 1kg fuel used in transport (MJ/fuel kg)

LHVfeedstock/RDF=

Lower Heating Value (LHV) of feedstock/RDF to WtE processes (MJ/kg)

mfeedstock/RDF=

weight of feedstock/RDF to WtE processes (Mg)

M=

total weight considered in transport (kg)

V=

loading capacity of the vehicles used in transport (Mg)

Greek symbols

φ=

proportion of coal-fired power to the national electricity mix (%)

ω=

proportion of hydro power to the national electricity mix (%)

ηn=

a net efficiency of WtE process to electricity production (%)

μ=

the factor converting heating value into electricity (1MJ≈0.277 kWh)

δi=

emission factor of ith GHG per MJ of fuel (CO2eq kg/MJ)

Further research

Although the authors have conducted the additional analysis of energy potential in the municipality, further research is highly recommended to determine an economic feasibility, focusing on life cycle costing.

Additional information

Funding

This research was supported by the Ministry of Land and Environmental Protection, the Democratic People’s Republic of Korea.

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