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Quantification of the Greenhouse Gas Emissions from the Pre-Disposal Stage of Municipal Solid Waste Management Chuanbin Zhou, Daqian Jiang, and Zhilan Zhao Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b05180 • Publication Date (Web): 12 Dec 2016 Downloaded from http://pubs.acs.org on December 13, 2016
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Quantification of the Greenhouse Gas Emissions from the Pre-Disposal Stage of
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Municipal Solid Waste Management
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Chuanbin Zhou,*,1,2, Daqian Jiang2, Zhilan Zhao1
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1
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Environmental Science, Chinese Academy of Sciences, 18 Shuangqing Road, Haidian District,
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Beijing100085, China. 2School of Forest and Environmental Studies, Yale University, 195
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Prospect Street, New Haven, Connecticut 06511, USA.
State Key Laboratory of Urban and Region Ecology, Research Center for Eco-
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ABSTRACT
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Municipal solid waste (MSW) disposal represents one of the largest sources of anthropogenic
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greenhouse gas (GHG) emissions. However, the biogenic GHG emissions in the pre-disposal
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stage of MSW management (i.e., the time from waste being dropped off in community or
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household garbage bins to being transported to disposal sites) are excluded from the IPCC
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inventory methodology and rarely discussed in academic literature. Herein, we quantify the
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effluxes of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) from garbage bins
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in five communities along the urban-rural gradient in Beijing in four seasons. We find that the
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annual average CO2, CH4 and N2O effluxes in the pre-disposal stage were (1.6±0.9)103,
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0.049±0.016 and 0.94±0.54 mg kg-1h-1 (dry matter basis) and had significant seasonal
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differences (24- to 159-fold) that were strongly correlated with temperature. According to our
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estimate, the N2O emission in the MSW pre-disposal stage amounts to 20% of that in the
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disposal stage in Beijing, making the pre-disposal stage a non-trivial source of waste-induced
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N2O emissions. Furthermore, the CO2 and CH4 emission in the MSW pre-disposal account for
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5% (maximum 10% in summer) of the total carbon contents in Beijing’s household food
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waste stream, which has significance in the assessment of MSW-related renewable energy
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potential and urban carbon cycles.
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TOC
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1. INTRODUCTION
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Municipal solid waste (MSW) management is not only crucial to urban environmental
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quality and material recycling, but also one of the largest sources of greenhouse gas (GHG)
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emissions from human settlements 1, 2. According to the Intergovernmental Panel on Climate
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Change (IPCC), global waste disposal is responsible for 1446 million tons of GHG emissions
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in 2010, and has seen an increase of 13% between 2000 and 20103. In 2005, GHG emissions
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from the waste sector amounted to 112 and 178 million tons CO2eq in China and in the U.S.
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respectively, which shows the significant GHG impact of the waste sector in both developing
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and developed countries 2, 4. In addition, waste disposal is often one of the largest sources of
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anthropogenic methane emissions, which is the second largest category of GHGs and
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25-times more potent than CO2 2, 3.
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A breadth of studies has examined the GHG emissions from MSW management at
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different scales. At the regional and national scales, GHG emissions from MSW disposal sites
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in Africa, U.S, Europe and China were calculated to provide scientific evidence for setting
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GHG reduction targets1, 5-8. Similar efforts were made at the city scale to help understand the
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environmental impacts of MSW9, 10, or choose mitigation technologies and strategies10-12. At
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the site scale, experimental studies have been conducted to quantify the amounts and trends of
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GHG emissions from centralized disposal sites13-16 and decentralized organic waste treatment
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facilities (e.g., home composting of source-separated organics17-22) to understand the
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mechanisms or obtain high-resolution emissions data.
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Most of these studies have adopted the widely-followed IPCC inventory methodology,
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which focuses on the GHG emissions from disposal sites and under-emphasizes the
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pre-disposal stage (i.e., the time from when the waste being dropped off in community or
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household garbage bins to the time it is being transported to disposal sites)23. Literature
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pertaining to the pre-disposal stage of MSW management only examined the GHG emissions
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from the fossil fuel consumption in the MSW collection and transportation9, 12, 24, 25, without
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paying attention to the direct, biogenic GHG effluxes. However, in the pre-disposal stage,
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MSW is often dropped off and stored in garbage bins in households and communities for a 3
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considerable amount of time before being collected and transported to waste disposal sites
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(i.e., landfills and incinerators)26. In China, this pre-disposal stage can take up to two days in
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urban areas, and much longer in rural areas with no regular clearing service27. In the U.S., the
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curbside collection service for MSW and separated organic waste is normally offered weekly
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or biweekly for cost considerations28-30. During this time, the garbage bins provide an ideal
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environment for biogenic GHG emissions given the moderate temperature, and the presence
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of oxygen, active microorganisms and large quantities of biodegradable matters (e.g.,
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biodegradable food waste accounts for 40.0 to73.7% of the total MSW in China)27, 31, 32. The
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conditions of the pre-disposal stage are somewhat similar to home composting, in which
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significant amounts of methane and nitrous oxide emissions were found18, 22. Despite the
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favorable conditions, the biogenic GHG emissions of MSW in the pre-disposal stage have not
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been systemically studied.
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In this study, we attempt to fill this knowledge gap by monitoring the biogenic GHG
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emissions from MSW in the pre-disposal stage. Using the chamber method 16, 20, 21, we did a
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high-resolution profiling of the GHG effluxes from 50 households in five communities along
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the urban-rural gradient of the Beijing metropolitan area. We found that the biogenic GHG
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emissions in the pre-disposal stage was non-trivial, and had potentially significant seasonal
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and cross-community differences. Our results call attention to the potential climate change
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impact of this overlooked MSW management stage that may be worthy of further studies.
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2. MATERIAL AND METHODS
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2.1 Description of the study sites
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The study was done in Beijing, which has a population around 21.15 million and
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generated a total of 6.72 million tons of MSW in 2013 33. A large proportion of Beijing’s
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MSW is biodegradable food waste (64-67%) that can potentially result in high biogenic GHG
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effluxes 34.
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Five communities along the urban-rural gradient of the Beijing metropolitan area were
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selected for this study, which were representative of the location (old city, new built city,
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suburbs and village), the type and age of the buildings (story and built year), the 4
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socio-economic status, and the demographics of typical residential communities in Beijing.
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For each community, 10 households were randomly selected. A questionnaire was given to
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each household to collect background information on demographics, income, food
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expenditures, MSW drop-off habits, and source separation behaviors. The location and the
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socio-economic profiles of the five communities are shown in Figure 1. Generally, the
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Jinmaoyue community (in new built city) has the highest average income; the Shaojiu and
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Huangtugang community have middle income; the Zhuxinzhuang (suburb) and Shuiyuzui
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(rural village) community have the lowest income, largest family population and highest
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percentage of income spent on food. More details of the communities could be found in
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Supporting Information, Table S1.
No.
Community
District
Location
Type of building
1
Huangtugang
Xicheng Dist.
Old city
Single-storey house (Hutong), 1950s
2
Shaojiu
Xicheng Dist.
Old city
Low-rise apartment (7-storey), 1980s
3
Jinmaoyue
Chaoyang Dist.
New city
High-rise apartment (18-storey), 2010s
4
Zhuxinzhuang
Changping Dist.
Suburbs
Low-rise apartment (7-storey), 2000s
5
Shuiyuzui
Mentougou Dist.
Village
Two-storey village house, 2000s
4
5
3 1 2
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Figure 1 Locations of the studied communities along an urban-rural gradient in Beijing, China.
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The questionnaire results indicated that on average, MSW stayed inside the households
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for one day before being dropped off in the community garbage bins. The Regulation of
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Beijing Municipality on City Appearance and Environmental Sanitation requests a daily
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collection and clearance of MSW in urban area. Therefore, in this work, we assumed that the
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duration of the pre-disposal stage was two days in Beijing.
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2.2 Sampling and waste composition characterization 5
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MSW from each community was sampled once in each season. The five communities
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were sampled sequentially in each season and the entire sampling and monitoring was
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completed in two weeks. The sampling dates were: spring, from April 12th to April 26th in
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2015; summer, from July 7th to July 28th in 2015; autumn, from October 19th to November 7th
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in 2015; winter, from January 8th to January 23th in 2016. Given the relatively short timeframe
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of the pre-disposal stage (around 2 days in Beijing), only MSW that can be rapidly
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biodegraded was collected. The selection of biodegradable MSW was based on previous
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studies30, 35, and included five main categories, namely rice & wheat, vegetable, fruit, meat
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waste and other biodegradable fraction.
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In each experiment, around 15-20 kg biodegradable fraction of MSW was collected from
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10 households in each community. The collected waste was thoroughly mixed, and two 3kg
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mixtures were taken by using coning and quartering method for further analysis: one mixture
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was used for GHG emission quantification; the other mixture was used for quantifying the
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composition and the moisture content, which was used to calculate the dry mass basis weight.
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The dry mass basis weight of each component was then used to calculate the total organic
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carbon contents (TOC) and the total nitrogen contents (TN) using a previously established
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database, which had detailed statistics on the organic contents of each waste category.
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Methane yield potential (L0) and carbon sequestration factor (CSF) were selected as indicators
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for the biodegradability of waste. The values of L0 and CSF were taken from a recent study on
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the biodegradability of organic waste in China35. Data used here were listed in Supporting
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Information, Table S2.
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2.3 GHG efflux quantification
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The chamber method was applied to quantify the GHG effluxes16-18. The diagram of the
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chamber is shown in Figure 2. The size of the chamber is 65cm×65cm×40cm (length, width
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and height). A garbage bin (20cm×20cm×20cm) similar to the ones used in households is
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placed in the chamber. An electric fan is placed inside the chamber to mix the gases
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thoroughly. The fan is run during the gases sampling period in order to ensure the samples
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were representative of the average gas mixture in the chamber36-38. A base with water-filled 6
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grooves is used to seal the chamber in order to prevent leakage. Syringe used for sampling
Pipe for baro-pressure balance
Pipe for sampling gases
Chamber for testing gas effluxes
Garbage bin with the waste sampled from different communities Fan for mixing the inside air
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Chamber bottom with water seal
Figure 2 Diagram of chamber method.
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The rain proofed chamber and the simulated garbage bin (with waste collected from
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households) were placed outdoors for GHG emission monitoring. To simulate the length of
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the pre-disposal stage, each chamber experiment lasted for 2 days. The GHG effluxes were
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sampled in the following hours each day: 06:00-07:00, 10:00-11:00, 14:00-15:00,
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18:00-19:00, and 22:00-23:00. Four samples were taken at 0 min, 20min, 40min and 60 min
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in each of the hours, and an average GHG efflux was calculated and reported for that hour. In
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each sampling, 50mL of air was drawn using a syringe, which was then split into 2×25mL as
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technical duplicates. The ambient temperature was recorded during the monitoring, which
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varied from -12.4 to 35.8 ℃, with the seasonal average being 23.9, 31.3, 10.0 and -3.9 ℃ for
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spring, summer, autumn and winter, respectively.
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The concentrations of CO2, CH4 and N2O of each sample were analyzed using a gas
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chromatography (GC) (Agilent 7890A, U.S.) equipped with a flame ionized detector (FID)
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for CO2 and CH4, an electron capture detector (µECD) for N2O.
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The effluxes CO = of + 2, CH 4 and N2O were determined by Equation (1). 2
4
F = 0 × 273273 + × 0.1013 × × × − 0 × 0 × 0 ×
!
×
10 6 #
公式 (1)
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Where F is the GHG effluxes (mg·kg-1·h-1); ρ0 is the density of CO2, CH4 and N2O
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under the standard temperature and pressure (STP), ρCO2 is 1.977 kg·m-3, ρCH4 is 0.717 kg·m-3, 7
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ρN2O is 2.982 kg·m-3; P is barometric absolute pressure; T is thermodynamic temperature (K);
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H, L,W are the height, length and width of the chamber, 0.4m, 0.65m, 0.65m; L0 and W0 are
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the length and width of the garbage bin, 0.20 m, 0.20 m; H0 is the height of the waste placed
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in the garbage bin; dc/dt is the increment rate of the CO2, CH4 and N2O concentrations
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(ppm·h-1); m is the dry weight of the testing waste.
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To compare the differences of GHG emission along the urban-rural gradient, the per
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capita GHG emission were calculated for different communities using Equation (2). CO2
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emission was excluded according to IPCC GHG inventory methodology23. $ $%#&''&( =
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∑&=1,2,3,4 ∙ 4 &- + . ∙ /2 &- ∙ 24 ∙ 0 ∙ &- ∙ 1 − 1&- /- ∙ 365 4
(2)
Where GHGEmission is the per capita annual GHG emission of one community (g CO2eq
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capita-1 year-1); F is the daily average efflux of CH4 and N2O (g·kg-1·h-1); W is the total weight
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of the food waste collected from each community; M is the moisture content of the collected
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food waste from each community; P is the total number of residents covered by our waste
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sampling in each community; a and b are GWP100 of CH4 and N2O, 25 and 298 respectively3;
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D is the length of the pre-disposal stage (D=2 in this work); i designates the four seasons; and
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j is the five communities studied.
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2.4 Statistical Analysis
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SPSS 16.0 was used for the statistical analysis. One-way ANOVA was used to analyze
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whether there are statistically significant differences in the GHG effluxes in different seasons.
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Spearman’s correlation test (2-tail) was used to analyze the monotonic correlation between
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GHG effluxes and potentially influential factors, including ambient temperature, moisture,
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TOC, TN, C:N ratio, L0 and CSF. Regression analysis was done for GHG effluxes and
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temperature given the strong spearman correlation coefficient. Adjusted R2 and the Akaike
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information criterion for small sample size (AICc) were used for model comparison.
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3. RESULTS AND DISCUSSION
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3.1 Annual total GHG emissions in the pre-disposal stage
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The annual average CO2, CH4 and N2O effluxes in the pre-disposal stage were 8
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(1.6±0.9)103, 0.049±0.016 and 0.94±0.54 mg kg-1h-1 (dry matter basis) respectively in the five
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communities in Beijing. After excluding CO2 from the GHG accounting due to assuming
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carbon-neutrality in biogenic waste, the annual per capita GHG emissions in the pre-disposal
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stage was 240±140 g CO2eq capita-1 year-1, and was predominantly N2O emission (0.81 g N2O
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capita-1 year-1 or 240g CO2eq capita-1 year-1). There are two other interesting features. First,
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the CO2 and N2O effluxes in the pre-disposal stage measured in this study are higher than the
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effluxes reported for home composting and full-scale composting. For example, hourly CO2
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and N2O efflux in pre-disposal stage are 38-52 times and 2-13 times larger than corresponding
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fluxes in home composting (Table 1). Second, the N2O efflux was much larger than CH4 in
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the pre-disposal stage, which was very different from landfills but somewhat similar to
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composting. The percentages of CO2, CH4 and N2O in the pre-disposal stage were
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85.40±7.15%, 0.06±0.60% and 14.54±7.49% respectively on a CO2eq basis.
193 194
Table 1 Comparison of the GHG effluxes from pre-disposal stage and other MSW facilities. Stages
Source
Pre-disposal Home composting Full scale composting Landfill
195 196 197 198 199
MC (%)
GHG effluxes (mg kg (dm)-1 h-1) CO2
CH4 3
N2O
This work
73.7–82.1
(1.6±0.9)10
0.049±0.016
0.94±0.54
Andersen et al., 201017 a
63.8–78.9
39–42d
0.09–0.13d
0.07d
Martínez-Blanco et al., 201018
43.6
n/a
0.12d
0.50d
Adhikari et al., 201320 b
75.9
31d
n/d
0.22d
Colón et al., 201219
n/a
n/a
0.34–4.37
0.035–0.251
Rinne et al., 200539
n/a
5640c
1660c
4.2c
Note: a. the no mixing experimental group; b. the plastic bin experimental group; c. unit is mg m-2 h-1; d. calculated based on the original data, moisture contents and the composting duration days; n/d – not detected; n/a – not applicable.
Our findings are somewhat supported by mechanism studies. For instance, the methane
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emissions are facilitated by low oxygen conditions and the lag-phase time of CH4 yield (5-25
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days) 30, 35, 40, which is not available in the simulated pre-disposal stage. In contrast, N2O
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emission is a consequence of richness in nitrogen and frequently alternating aerobic and
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anaerobic conditions41, and possibly more intense in the first 3 days42, which is similar to the
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conditions in the pre-disposal stage. The overall larger GHG effluxes from the pre-disposal
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stage may be related to the short duration of the monitoring. When monitored over periods of
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2 month to 2 years, GHG effluxes from home and full-scale composting have been shown to
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decline overtime17-22.
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3.2 Seasonal GHG emissions in the pre-disposal stage
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Different GHG showed different seasonal trends. Seasonal CO2 effluxes varied from
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0.13±0.16 to (3.2±0.9)103 mg kg-1 h-1 and showed statistically significant differences in each
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season (summer > spring > autumn > winter, p
