Accepted Manuscript Eco-efficiency optimization for municipal solid waste management Zhifeng Yang, Xiaocui Zhou, Linyu Xu PII:
To appear in:
Journal of Cleaner Production
Received Date: 6 May 2014 Revised Date:
26 June 2014
Accepted Date: 27 September 2014
Please cite this article as: Yang Z, Zhou X, Xu L, Eco-efficiency optimization for municipal solid waste management, Journal of Cleaner Production (2014), doi: 10.1016/j.jclepro.2014.09.091. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Eco-efficiency optimization for municipal solid waste management
Zhifeng Yang1*, Xiaocui Zhou1,2, Linyu Xu1*
1.State Key Laboratory of Environment Simulation and Pollution Control, School of the
Environment, Beijing Normal University, Beijing 100875, PR China
2.Chongqing Planning Research Center. Chongqing 400011, PR China
*Corresponding author: Tel/fax: +86(0)10 58800618; [email protected]
; [email protected]
Carbon emission from municipal solid waste (MSW) treatment is one of the anthropogenic
sources to cause climate change, which accounts for 3-5% of global greenhouse gas
emissions according to the report of the United Nations Environment Programme (UNEP). At
the same time, the gases and liquid discharged from MSW treatment can also cause other
environmental impacts, such as climate change, photochemical ozone synthesis, and
acidification, especially in huge city with huge population as Beijing, China. This paper
proposed an eco-efficiency analysis method, which aimed to yield maximum overall
environmental improvement per unit investment cost during its life cycle processing. This
method took the overall reduction in the environmental impact of MSW treatment using
cost-effective techniques as the objective to optimize waste disposal systems. The separation
ratio during MSW collection and the proportion of techniques used for treatment were the
major indicators for optimization measures. For Beijing, an increase in the waste separation
ratio during collection proved to be the most effective measure, with an eco-efficiency score
of 0.144. Adjustment of the proportion of treatment techniques used was less eco-efficient,
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with an increase in the proportion of composting being the most effective approach. Based on
real needs, the objective should be to reduce the proportion of landfills used and increase the
amount of composting and incineration. This optimization measure had the lowest cost and an
eco-efficiency score of 0.0461, which is 60% higher than that for the measure with the lowest
Keywords: Climate change, municipal solid waste, cost–benefit analysis, eco-efficiency,
1.1 Importance of waste management
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At a global scale, the waste management sector makes a relatively minor contribution
to greenhouse gas (GHG) emissions, estimated at approximately 3-5% of total anthropogenic
emissions in 2005 (UNEP, 2010). Although minor levels of emissions are released through
waste treatment and disposal, the wastes management such as recovery of secondary
materials or energy has avoided emissions in all other sectors of the economy. A holistic
approach to waste management has positive consequences for GHG emissions from the
energy, forestry, agriculture, mining, transport, and manufacturing sectors (UNEP, 2010).
At the same time, management of municipal solid waste (MSW) is also an important urban
social issue that can provide environmental benefits for urban residents and reflects the level
of urban ecological sustainability (Li and Yang, 2004). China is facing increasing amounts of
MSW and a limited capacity for waste treatment (Zhao et al., 2009) owing to rapid economic
development and urbanization. Some advanced concepts, such as the recycle economy and 2
ecological cities, have provided guidelines and prerequisites for MSW management to reduce
environmental impacts while keeping costs as low as possible. These guidelines and
prerequisites would also guide the optimization of MSW solutions (Tan et al., 2010).
1.2 Eco-efficiency of waste management
Eco-efficiency analysis relates two pillars of sustainability, the pillar of economics and
the pillar of environmental protection, and links economic efficiency to environmental
efficiency (Cramer, 2000; Huppes and Ishikawa, 2005; Schmidheiny, 2000; Stigson, 2001;
Suh, 2005). The concept of eco-efficiency is increasingly being applied to judge the
combined environmental and economic performance of MSW management strategies, such as
waste collection, recycling and processing (Bohne et al., 2008; Eik et al., 2002; Kuosmanen
and Kortelainen, 2005; Meier, 1997; Morioka et al., 2005; Zhao et al., 2009). Eco-efficiency
is typically defined as the ratio of added economic value to environmental impact or the ratio
of added environmental benefits to the economic costs. However, this traditional definition is
not appropriate to evaluate end-of-pipe (EOP) treatment technologies because the aim of such
technologies is to improve environmental performance at the cost of economic savings.
Moreover, some of the technologies produce environmental pollutants as well and thus can
lead to both environmental and economic costs between three MSW treatment technologies,
namely landfill, composing, and incineration. Hellweg et al. (2005) proposed an indicator to
be used for the assessment of EOP technologies, termed environmental cost efficiency (ECE),
that is defined as the ratio of net environmental benefits to differences in costs. ECE
quantifies the environmental benefit of Technology A over Technology B per additional cost
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(ECEA,B); ECEA,C is calculated in the same way for Technologies A and C. By comparing
ECEA,B with ECEA,C, we can determine whether technology B or C is better by setting A as
the constant variable. However, this evaluation method can result in some uncertainty because
different objects (constant parameter) may be chosen for comparison.
1.3 Study area
In this study, we explored eco-efficiency analysis for MSW management to optimize
waste disposal systems with the dual aim of reducing the carbon emission of MSW
processing and improving the cost-effectiveness.
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Beijing is the capital of China and the political and cultural center of the country, and
generates a large amount of MSW and is experiencing rapid growth. In 2008, the amount of
MSW was as high as 18,411 tons per day, with an annual growth rate of nearly 8%. The MSW
composition in recent years has been 11.1% paper, 12.7% plastics, 2.46% fabric, 1.76% glass,
0.27% metal, 63.4% kitchen waste, 1.74% grass and wood, and 6.57% lime soil (BMAMC,
2009). This MSW has a lower heat value of 4627 kJ kg–1. 54% of the waste generated is
collected separately, of which 50% become recyclables; All of the left wastes are subject to
waste treatment, of which 93% is placed in a landfill, 4% is composted, and 3% is incinerated.
All above, Beijing will be a typical case study in this paper.
2.1 Framework of eco-efficiency assessment on waste management
We define environmental improvement per unit economic cost as an eco-efficiency
indicator to assess the improvements for each optimization measure. The higher the indicator 4
value, the better the effects of optimization are per unit cost. We set a reduction in
environmental impact as the overall optimization objective for each waste treatment process,
and the separation ratio during MSW collection and the utilization ratio of safe disposal
technologies as the means for optimizing the measures. These improvements were integrated
in an eco-efficiency index that relates the unit cost of investment to environmental
improvements. Values of the eco-efficiency index can be used as the basis for optimization.
Figure 1 shows flow diagram for the optimization concept.
This approach can be used to combine the environmental impacts of all processes to assess
environmental improvements for the whole system. When combined with the economic costs,
these improvements can be used to formulate an optimization plan for the entire disposal
system and to determine the appropriate MSW treatment technologies along with their
contributions to each optimization measure (equation 1). EE =
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EITcurrent - EITm Environmental improvement = , Economic costs Cm
m = 1,2, … , n ,
where EE is eco-efficiency, EITcurrent is the current environmental impact, EITm is the
environmental impact of measure m and Cm is the economic cost of measure m.
Figure 2 shows flow diagram for calculation. This approach solves the difficult trade-off
problem that arises when two EOP technologies have different environmental and economic
advantages and disadvantages.
2.2 Environmental Impact Assessment
We used environmental impact potential to represent the degree of environmental impact.
We obtained the environmental impact potential through identification of system scope,
resource and energy consumption and environmental discharge inventory, and environmental 5
impact potential calculation.
2.2.1 Goal and Scope The goal of this study was to evaluate the environmental impact of the existing MSW
management system in Beijing and to account for potential environmental impacts. The
functional unit used was 1 t MSW. The study scope was the system of MSW disposal,
including collection, transportation, and safe treatment processes. However, the processes for
MSW collection and sorting could be ignored when we calculated the environmental impact
potential, because these areas are dominated by human labor inputs, for which resource and
energy inputs are small compared with the other processes. But its economic cost should be
considered in the systematic eco-efficiency analysis. In this study, the means for optimizing
measures were the separation ratio during MSW collection and the utilization ratio of safe
disposal technologies, which were often used in the waste treatment planning and
management in China as important indicators. Separated collection could help for waste
rescued so as to reduce the amount of end-of-pipe treatment. Utilization ratio of safe disposal
technologies was the proportion taken by each treatment technology, including incineration,
composting and landfill. To compare landfill, incineration and composting treatments, we
assumed that these processes had the same transportation routes to the plant. Figure 3(A-E)
shows the scope of each measure, as well as the whole system studied.
2.2.2 Data collection and inventory
The aim of the inventory is to identify and quantify environmental interventions related to the
system. This process results in a list of environmental inputs and outputs (Anil, 2010). In the
MSW transportation process, pollutants arise mainly from vehicle exhaust emissions. Thus,
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data for transportation processes were obtained in terms of vehicle exhaust emission factors.
According to Huang et al. (2004), the energy consumption of MSW in Beijing during
transportation is 164.45MJ/(person·a·t), and the conversion unit of gasoline consumption is
28.16kg/t. So the vehicle exhaust emissions during the process of transportation could be
calculated (Xu, 2010). We also collected the relevant data for EOP treatment processes from
the environmental impact assessment reports of three case sites in Beijing, China. All of these
data could be found in Table S1and S2 from the Supplementary Materials, and the inventory
has been listed in Table 1(A-D).
2.2.3 Environmental impact potential calculation
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The environmental impact of each process could be calculated with equation 2. Once the
inventory was obtained, an environmental impact assessment was carried out that included
environmental impact categorization, data standardization, and normalization factor
assignment. EI =
[Q(j ) ⋅ PF(j )i ] ) = ∑ Wj ⋅ ∑ i , SEP(j )
i = 1,2, … ;
j = 1,2, …
where EI is the environmental impact of each process; EP(j) is the environmental impact
potential for environmental impact category j; Wj is the normalization factor denoting the
relative materiality of the selected environment impacts; Qi is the amount of emissions of
substance i (kg t-1); PF(j)i is the equivalence factor for substance i with an environmental
impact for category j; and SEP(j) is the data standardization baseline for the environmental
impact of category j.
Equation (3) quantifies the environmental impact of the entire disposal system, including collection, transportation and processing: 7
EIT = (1 − γ ⋅ L) ⋅ [EIT + PC ⋅ EIC + PI ⋅ EII + (0.3⋅ PC + 0.1⋅ PI + PL ) ⋅ EIL ]
where EIT is the environmental impact of the entire disposal system; γ is the separated
collection rate (the amount of MSW separatedly collected/the amount of MSW produced, %);
L is the resource sorting rate for raw MSW (the amount of MSW rescued/the amount of
MSW separately collected, %); γ ⋅ L can be considered as reduction rate of MSW. 1 − γ ⋅ L
is the amount of MSW to be processed that cannot be rescued before treatment. Considering
most MSW treatment plants are set in suburbs long distances from collection and sorting sites
in the city, the environmental impact produced during transportation is not negligible. P is the
proportion of MSW processed in different EOP treatment technologies (%) immediately upon
collection, which are the parameters usually established and used in planning in China, and EI
is the environmental impact of each process. The subscripts T, C, I and L denote
transportation, composting, incineration and landfill, respectively. After incineration and
composting, there is still a residue of 10% and 30%, respectively, to be placed in a landfill
(Zhou, 2010); therefore, the landfill proportion is 0.3 ⋅ PC + 0.1 ⋅ PI + PL .
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The inventory in table 1 indicated that the main resource inputs and the main emission
loads were as follows: leachate, acid gases such as NOx and SO2, odorous gases such as H2S,
NH3-N, and greenhouse gases. Generally, the toxic liquid from landfill would be disposed
directly according to the regulation, which will not be permitted to emission directly into
environment. So we chose four categories, which are climate change, acidification,
eutrophication, and photochemical ozone synthesis, to assess the environmental impact
potential. These four environmental impact categories are bound up with the main emission
load, and have significance in environmental protection, also are widely studied (Bani et al.,
2010; Cai, 2006; Huang et al., 2004; Ji, 2010; Kong, 2009; Paolo, 2009; Xu, 2009; Yang et al.,
2002). We used characterization factors for the characterization of the data according to
equation 2. Table 2 shows characterization factors for Environmental Impacts (Xu, 2009). The
data standardization baseline used for environmental impact assessment (Climate Change,
Acidification, Eutrophication and Photochemical Ozone Synthesis), built by the Research
Center for Eco-Environmental Sciences, Chinese Academy of Sciences, is the per capita
environmental impact in east China. The normalization factors of environmental impacts are
set on the basis of Chinese pollutant reduction targets for the year 2008 (table 3) (Kong,
2009). The data standardization baseline for depletion of potential natural resources
(petroleum and coal) is the per capita consumption of resources, with normalization factors
assigned according to resource scarcity (i.e., the reciprocal of the resource supply period).
According to Yang et al. (2002), China has petroleum reserves of 25,600 kg person–1. Thus,
with consumption of 592 kg person–1 yr–1, the resource supply period for petroleum is 43 yr
(the normalization factor is 1/43). Similarly, China has coal reserves of 98,570 kg person–1.
With consumption of 574 kg person–1 yr–1, the resource supply period for coal is 170 yr (the
normalization factor is 1/170).
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According to Beijing MSW management (stated above), then combined with the
environmental impact potential and of each process (Table 4), using equation 3 can get the
systematic environmental impact potential of 0.0773, which is the value before optimization
2.3 Economic Costs Analysis
Economic analysis for MSW disposal includes calculations of the economic costs and the 200 201
and processing: C Total = C Coll + C T + C P
benefits of each process. The total cost includes the costs of collection, sorting, transportation
In Beijing, mixed collected MSW are often directly transported to end-of-pipe plants, so
there is barely cost for mixed collection. Separated collection needs some devices and labor
sorting before being transported to end-of-pipe plants, so there would be cost. The unit cost
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′ ′ ′ ′ ′ ′ CTotal = γ ⋅ CS + (1− γ ⋅ L) ⋅ CT + PC ⋅ CC + PI ⋅ CI + (0.3⋅ PC + 0.1⋅ PI + PL ) ⋅ CL ,
where C is the cost of MSW disposal, and C ′ is the unit cost (the cost of disposal for 1 ton of
MSW); the subscripts Coll, S and P denote collection, sorting and processing, respectively.
Economic analysis for MSW disposal includes calculations of the economic investment
and benefits of each process (see equation 4), as well as calculations for collection and
transportation costs. Following the method of Huang et al. (2004) and considering a price
increase of 20%, we calculated costs for separated collection (including sorting) and
transportation as 1.20E+02 and 1.41E+02 CNY t–1, respectively. The process of turning
MSW to a resource prior to end-of-pipe treatment is out of the study scope. In this study
scope, we just sort out some recyclables to reduce the amount of end-of-pipe treatment, so
any benefits and environmental impacts associated with turning MSW to a resource prior to
end-of-pipe treatment are not considered here. Hence, there is no direct benefit considered in
the processes of collection and transportation. We summarize the benefits of MSW treatments in Table 5 (Ji, 2010). As for processing
costs, the construction and operation costs for MSW treatment plants have been combined to
calculate the overall benefit from each treatment, as shown in Table 6.
To consider a standard unit in keeping with environmental impact potential, we need to 224
standardize the cost data using GDP per capita. The per capita GDP was 63,029 CNY in
Beijing for 2008. The standardized results are presented in table 7. Although the construction 226
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and operating costs are high for incineration, this technology has good economic returns 227
becausea great potion of energy can be recovered. For composting, the benefits of fertilizer, 228
as calculated from theoretical considerations, means that costs are greatly reduced. Although 229
landfill treatment is simple, and construction costs are low, resource utilization is also low, 230
which makes the total cost higher than for the other treatment technologies. 3. Results and discussion
3.1 Eco-efficiency of each optimization measure
The environmental impact and economic assessment results for each MSW process reveal
that the current environmental impact could be reduced by increasing the rate of MSW
separation and increasing utilization of the treatment technology with the lowest
environmental impact. Thus, we used the MSW separation ratio and disposal utilization ratios
as the means for optimizing measures. The eco-efficiency of each optimization measure was
assessed, and the results are shown in Table 8.
We analyzed the environmental impact and economic cost–benefit for each step in MSW
disposal for Beijing. The results indicate that an increase in the waste separation rate was 11
most effective because the eco-efficiency of 0.144 was much higher than for the other
optimization measures. The reason could be that separated collection helps MSW rescued,
thereby reducing the amount of treatment needed and avoiding the end-of-pipe pollution;
however, the cost of separated collection is high. Adjusting the proportion of treatment
techniques used was less eco-efficient, with an increase in the proportion of composting
providing the most effective approach. Based on real needs, the objective should be to reduce
the proportion of landfill usage and increase the proportion of composting and incineration.
This optimization measure costs the least and has an eco-efficiency of 0.0461, which was
60% higher than for the measure with the lowest eco-efficiency.
3.2.1 Eco-efficiency analysis
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The results of the eco-efficiency analysis indicated that the most effective measure with the
greatest decrease in environmental impact per unit cost is to increase the separation ratio for
MSW collection. The eco-efficiency of measure I is 0.144; this value is 1-2 times higher than
for the other optimization measures. An increase in the separation rate can reduce the amount
of end treatment and thus reduce the overall environmental impact. Although the cost of
separate collection ranks second highest (just less than the cost of transportation) in the
processes, along with the cost of measure I, the greatest reduction in overall environmental
impact means that this option leads to the greatest environmental improvement per unit cost
of investment. Comparison of end optimization measures II1, II3, and II4 reveals that an
increase in PC is most effective because both its environmental impact and economic costs are
small compared to the other treatment technologies. A comparison of landfill use and
incineration demonstrates that the environmental impact is lower for landfill use and the
economic cost is lower for incineration; however, in terms of the contribution to overall
environmental improvement, a decrease in PI is more effective than a decrease in PL. For
measure II2, which involves a decrease in PL and increases in both PC and PI, the
eco-efficiency is of intermediate rank, but the cost is the lowest. However, the eco-efficiency
is approximately 60% higher than that for measure II1. The current proportion of MSW that is
placed in a landfill is too high at 93%, and Beijing has limited land resources that are
becoming increasingly valuable. Therefore, measure II2 is the most practical. Moreover,
according to MSW disposal experience in other countries with a similar population density
and land resources, promotion of incineration is the leading trend. Thus, over the next 10–15
years, an increase in the proportions of incineration and composting is feasible.
3.2.2 Discussion on environmental impact potential of MSW
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Because emissions from MSW processing are abated in treatment plants before discharge
and there is energy recovery, the whole environmental impact (including natural resource
depletion potential) of processing is less than that of transportation. The main environmental
impacts during transportation are on climate change and photochemical pollution. Less MSW
emission, improvement of transportation routes and clean transportation should be made to
reduce the impact on the environment.
Photochemical ozone synthesis (POS) and climate change are the greatest contributors to
environmental load from landfill use. This is because landfill gas contains large amounts of
CH4, N2O and CO, which are involved in POS and are the main greenhouse gases. CH4 can 13
be converted to CO2 by burning of landfill gas; this process can significantly reduce the
impact on climate change because the climate change equivalent of CH4 is 25 times that of
CO2. Therefore, collection and processing landfill gas is very important for reducing the
environmental impact of landfills. Exhaust emission from transportation vehicles is also a
major contributor to POS.
Acidification arises due to the generation of H2S, SO2 and other acidic gases during
composting. Large amounts of gases, such as CH4, CO and NOx, are also generated; these
gases not only have an impact on climate change but also participate in POS. However, the
overall environmental impact of composting is less than that of the other two technologies.
One reason is that at our case site, measures are taken to collect composting gas in a
subatmospheric pressure system, and odors are effectively removed by use of a biofilter.
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The greatest impact of incineration is acidification, followed by climate change and POS.
The environmental impacts of climate change and POS are slightly less than for landfill use,
but acidification is significantly higher. This is because incineration produces large amounts
of acid gases such as NOx, HCl and SO2. However, a relatively large amount of NOx leads to
the finding that the impact of eutrophication is greater following incineration than from
Composting is the worst strategy in terms of the potential depletion of natural resources
because there is no energy to recover; in fact, composting can consume much energy by
maintaining the temperature necessary for supporting subatmospheric pressure systems. The
resource depletion potential for landfill use and incineration is negative because much energy
can be recovered from the burning of landfill gases and MSW, which exceeds the 14
consumption during processing.
This paper improves the eco-efficiency analysis methodology for application to MSW
management. Firstly, it integrats the environmental impact and economic costs of each
process, from collection to treatment, into the entire disposal system and then it analyzes the
contribution of each process individually to determine the eco-effective optimization measure.
This approach not only reveals the best measure for maximum overall environmental
improvement per unit investment cost, but also identifies appropriate MSW treatment
technologies. However, in the research system scope which we defined, we excluded some
factors, including treatment technologies with variation, price fluctuation and transportation
route optimization, which could lead to some limitations; these factors will be examined in
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This research is supported by the Fund for Innovative Research Group of the National
Natural Science Foundation of China (Grant No. 51121003) and the National Natural Science
Foundation of China (No. 41271105).
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Figure Captions: Figure1. Diagram for the optimization concept. It shows diagram for the optimization concept. Figure 2. Calculation process. It shows flow diagram for calculation.
Figure 3. (A)System for Beijing MSW management (B) transportation process (C)
landfill process (D) incineration process (E) composting process. The pictures above
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show a flow diagram for the study system.
Table1. Resource and energy consumption and environmental discharge inventory Table 1(A) Resource consumption inventory Transportation
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Table 1(B) Waste gas discharge inventory Waste gas component
Table 1(C) Waste water discharge inventory Waste water component
Table 1(D) Energy recovery inventory Transportation
Table 2. Characterization factors of Environmental Impact Characteristic Substance
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Environmental Impact category
Table 3. Data standardization baseline and normalization factors for Environmental impact potential in China
Environmental Impact category
Data standardization baseline East
kg C2H4 0.76
Table 4. Systematic environmental impact potential of waste treatment (person yr) Systematic environmental
mental impact potential (output)
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ozone synthesis Depletion
–4.69E–04 4 5.89E–02
Following GB/T2589-2008 (General principles for calculation of comprehensive energy
consumption), we converted recovered energy (electricity and heat) into uniform coal
consumption and added the consumption of coal, electricity and heat used in processing to obtain the total coal consumption. A great deal of energy can be recovered from landfills and
incineration, so the coal consumption is negative.
Table 5. Analysis of MSW treatment benefits MSW disposal benefits
Calculation Every family in Beijing pays 3 CNY per month; therefore, the benefit from
Fees paid by residents
4.67 million families in 2008 is 33.4 CNY·t–1 If all waste heat from incineration is used to generate electricity, recovery is Electricity generation by
271.2 kWh for each ton of MSW processed; the pool purchase price is 0.51 incineration
CNY·kWh–1, and the benefit from incineration is 138 CNY t–1
Organic fertilizer costs 320 CNY·t–1 and ~0.368 t fertilizer can be produced
from 1 t waste, so the benefit from composting is 117.8 CNY·t–1
For our case site, 60% of landfill gas is collected, 50% of which is used to Electricity generation by
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generate electricity; the power generated is 0.026 kWh t–1, and the benefit is burning landfill gas
0.132 CNY t–1
Table 6. Summary of the benefit and cost for MSW treatments Benefit (CNY t–1)
Fees paid by
Table 7. Economic analysis for MSW processes Separate collection
Cost (CNY t–1)
Benefit (CNY t–1)
Total (CNY t–1)
Standardized result (person yr)
Table 8. Eco-efficiency analysis for each optimization measure Optimization measure*
same Increase PC by 1% and decrease PL by 1%; the other parameters remain II1 the same Increase both PI and PC by 1% and
parameters remain the same Increase PC by 1% and decrease PI by 1%; the other parameters remain II3 the same
by 1%; the other parameters remain II4 the same
Increase PL by 1% and decrease PI
*I: Front optimization; II: End optimization.
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decrease PL by 2%; the other II2
the other parameters remain the I
Increase the separation rate by 1%;
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Eco-efficiency links economic efficiency to environmental efficiency;
Improvement was made for eco-efficiency analysis methodology;
MSW measure for maximum overall environmental improvement per unit cost
It served for MSW management optimization and carbon reduction in MSW
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Supplementary Material Table S1.Automobile emission in municipal solid waste transportation Emission factor *
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*Data source Xu, L.N., 2009. The life cycle assessment of Wuhan municipal waste disposal system. Master’s
thesis, Wuhan University of Technology, Wuhan, China (in Chinese).
Table S2. Data for EOP treatment techniques Treatment
Energy Waste water recovery
(t day )
60% of landfill
gas collected, 50% Electricity of which is used
located in Yongfeng Township, Haidian
generation; the kWh yr–1 remaining 50% is discharged
Odors collected in
Leachate used as plant,
through a biofilter
back ejecta for the Composting
located in second
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High Town, Pinggu district, Beijing
Flue gas treated in
At the south
an NID system
carbon to adsorb
Note: All discharges meet standard requirements. Source: Landfill plant environmental impact assessment report of Liulitun, Beijing, China (in Chinese); Solid waste integrated treatment plant environmental impact assessment report of Pinggu, Beijing, China (in Chinese); Zhang, Y.F., Deng, N., Liu, X.Y., Tian, Q., Zhou, G.B., 2004. Municipal solid waste disposal methods and its benefit assessment. Nat. Sci. Prog. 14(8), 863-869 (in Chinese with English abstract); BSB (Beijing Statistics Bureau) (2009) Beijing statistical yearbook 2009 (in Chinese).