Biowaste-to-biomethane or biowaste-to-energy? An LCA study on anaerobic digestion of organic waste

Accepted Manuscript Biowaste-to-biomethane or biowaste-to-energy? An LCA study on anaerobic digestion of organic waste Filomena Ardolino, Francesco Parrillo, Umberto Arena PII:

S0959-6526(17)32624-0

DOI:

10.1016/j.jclepro.2017.10.320

Reference:

JCLP 11112

To appear in:

Journal of Cleaner Production

Received Date: 14 July 2017 Revised Date:

27 October 2017

Accepted Date: 29 October 2017

Please cite this article as: Ardolino F, Parrillo F, Arena U, Biowaste-to-biomethane or biowaste-toenergy? An LCA study on anaerobic digestion of organic waste, Journal of Cleaner Production (2017), doi: 10.1016/j.jclepro.2017.10.320. 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.

ACCEPTED MANUSCRIPT Word count: 7280

Biowaste-to-Biomethane or Biowaste-to-Energy? An LCA

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study on Anaerobic Digestion of Organic Waste Filomena Ardolino , Francesco Parrillo and Umberto Arena1

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Department of Environmental, Biological, Pharmaceutical Sciences and Technologies – University of Campania Luigi Vanvitelli, Via Vivaldi, 43, 81100 Caserta, ITALY

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ABSTRACT

The study aims to demonstrate the overall environmental sustainability of biomethane production by anaerobic digestion of the separately collected organic fraction of municipal solid waste. There is a great interest in the utilisation of biofuels produced from biowaste in the

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transport sector, due to the benefits of reduced pollutant emissions and diversified transport fuel supplies. An attributional, process-based life cycle assessment study quantifies and compares the potential environmental impacts of an anaerobic digestion plant, where the produced biogas is

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upgraded to biomethane for the transport sector instead that directly burned in a combined heat

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and power unit. The avoided impacts related to the utilisation of biomethane instead of diesel, petrol or natural gas have been evaluated with reference to a vehicle fleet made of passenger cars and small rigid trucks. They appear large enough to make the biomethane production the cleanest option for the management of biowaste. The global warming and non-renewable energy

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Author to whom correspondence should be addressed. Phone +39-0823-274414; Fax +39-0823-274592; email: [email protected]

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ACCEPTED MANUSCRIPT potentials of the Biowaste-to-Biomethane scenario improve of 79% and 36%, respectively, with reference to the Biowaste-to-Energy scenario. A sensitivity analysis evaluates the effect of several key parameters. Some of them are peculiar for the analysed application, such as the composition of the vehicle fleet, specific biomethane consumptions of these vehicles, and methane slip in the

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biogas upgrading unit. Some other parameters are more general, and mainly related to the biological process, such as the final destination of solid digestate, gas engine efficiency, national electric energy mix. The results of the analysis provide data and information to policy-makers,

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planners and operators that would like or have to approach the management of the separately

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collected organic fraction of municipal solid waste. They also inform on the environmental advantages connected with the utilisation for road transportation of biomethane produced from this waste fraction.

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KEYWORDS

Biomethane; Biowaste; Anaerobic digestion; Biogas Upgrading; Life Cycle Assessment; Biofuels.

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LIST OF ACRONYMS

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AD, Anaerobic Digestion; CHP, Combined Heat and Power; EWC, European Waste Catalogue; GHG, Greenhouse Gas; GWP, Global Warming Potential; ISO, International Organisation for Standardisation; LCA, Life Cycle Assessment; LCI, Life Cycle Inventory; LCIA, Life Cycle Impact Assessment; LOP, Land Occupation Potential; MFA, Material Flow Analysis; MSW, Municipal Solid Waste; NCP, Non Carcinogens Potential; NREP, Non-Renewable Energy Potential; OECD, Organisation for Economic Co-operation and Development; OFMSW, Organic Fraction of 2

ACCEPTED MANUSCRIPT Municipal Solid Waste; PSA, Pressure Swing Adsorption; RINP, Respiratory INorganics Potential; SFA, Substance Flow Analysis; SR, Sensitivity Ratio; TECP, Terrestrial ECotoxicity Potential; VF, Variation Factor; WWTP, Waste Water Treatment Process.

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1. INTRODUCTION Biowaste typically includes food and kitchen waste from households and restaurants, waste from food processing plants, and biodegradable garden and park waste (ISWA, 2015). It is an

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important fraction of total solid waste, and a crucial part of municipal solid waste (MSW). In the 35 OECD countries, which generate 44% of the total MSW of the world, this fraction varies

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significantly, from 14% to 56% of total MSW in 2013, with an average of 27% and a yearly generation rate of about 177 million tonnes (OECD, 2015). Only a limited part of this amount (37% in OECD countries, i.e. 66 million tonnes) is currently sent to biological (ISWA, 2015). This indicates a huge potential of resource recovery from this biowaste: assuming an overall capture rate of 70%,

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it can be estimated that an additional amount of about 58 million tonnes/year could be sent to resource recovery, generating added value products with various levels of appealing. Essential taxonomy incudes (ISWA, 2015):

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− Bio-based fine and specialty chemicals, generally used in limited quantities for high-

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technology applications, which can be classified as high value (and low volume) products (Fava et al., 2015).

− Biofuels (such as biogas and biomethane), bioplastics, cellulose, and commodity chemicals, which can be classified as medium value (and medium volume) products (Tuck et al., 2012); − Compost and solid digestate, produced through aerobic and anaerobic digestion processes, respectively, which are considered as low value (and high volume) products (IEA Bioenergy, 3

ACCEPTED MANUSCRIPT 2010). These simple observations give an idea of the importance of the global market for these products, when obtained by a clean and economically feasible production process (Tock, 2017). The technoscientific literature indicates that anaerobic digestion (AD) has the best environmental and

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economic performances among the biological treatments of the organic fraction of MSW (MataAlvarez, 2003; Hermann et al., 2011; Lombardi et al., 2015; Tock, 2017). It allows a minimisation of greenhouse gas (GHG) generation (Møller et al., 2009; Yoshida et al., 2012), absence of emissions

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of bio-aerosols and bad odours (Mata-Alvarez, 2000), a reduced land surface use (Zhang et al.,

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2007), and recovery of energy (Khalid et al. 2011; Evangelisti et al., 2014) or fuels (Pertl et al., 2010; Bauer et al., 2013) from a low cost biogas. There are more than 17,000 biogas plants in Europe, mainly in Germany (with more than 50% of the total production), and in UK and Italy (with 14% each). About 1,000 of these plants are fed with biowaste from MSW (Torrijos, 2016). The

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produced biogas is often cleaned to be used as gaseous fuel in generators and combined heat and power (CHP) systems, producing heat and electricity for internal consumptions of the AD plant and injecting the excess of electricity in the national grid. Alternatively, it is treated to remove the non-

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methane components and to be upgraded to biomethane for different applications, mainly for

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cooking, domestic heating and fuel for shipping and road transport sectors (Patterson et al., 2011; Ricardo-AEA, 2016). There is a great interest in the utilisation of biomethane in the transport sector, due to the potential benefits related to the diversification of transport fuel supplies and the reduced emissions of GHGs and other pollutants into the atmosphere (Ricardo-AEA, 2015; 2016). This study aims to compare the environmental sustainability of an anaerobic treatment of 4

ACCEPTED MANUSCRIPT separately collected organic fractions of municipal solid waste, where the produced biogas is upgraded to biomethane for the road transport sector instead that directly burned in a combined heat and power unit. The analysis quantifies the related avoided burdens and potential environmental impacts from a life cycle perspective. Some studies recently investigated this kind

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of biogas utilisation. Pertl et al. (2010) focused their analysis on the quantification of the global warming potential (GWP), assuming the substitution of natural gas with the produced biomethane, without any indication about its specific utilisation. They took into account four upgrading

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technologies, and data for membrane separation units derive from the available literature, and

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appear only partially in agreement with recent data (Chen et al., 2017; Munoz et al., 2015). The study carried out by Adelt et al. (2011) made a quantification of GWP and cumulative energy demand, with reference to biomethane production starting from energetic crops and upgrading the biogas by amine absorption. Patterson et al. (2011) developed an analysis on a regional scale

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by taking into account the utilisation of biomethane for domestic use and transport sector, with inventory data almost completely derived from Ecoinvent databases. The study by Starr et al. (2014) developed an LCA to compare and identify possible improvements of two carbon

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mineralization technologies for biogas upgrading (alkaline with regeneration and bottom ash

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upgrading), which so far have a limited utilisation on the market. The study carried out by Ravina and Genon (2015) and that by Xu et al. (2015) did not utilise an LCA approach. The first adopted a dispersion model to estimate on a local scale the emissions of particulates and NOx in a biomethane plant equipped with a water scrubbing technology for biogas upgrading, and estimated the related carbon footprint. Xu et al. (2015) analysed the energetic aspects and the environmental impacts of a biomethane plants equipped with three different upgrading 5

ACCEPTED MANUSCRIPT technologies: pressured water scrubbing, monoethanolamine aqueous scrubbing and ionic liquid scrubbing. Leonzio et al. (2016) utilised an LCA to compare upgrading units fed with different chemical solvents. The LCA developed by Di Maria et al. (2016) compared three biological treatments of organic fraction of MSW: composting; AD with a final composting of digestate; and

with data derived from Ecoinvent databank.

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AD with final composting of digestate and upgrading of biogas by pressure swing adsorption (PSA),

A comparative analysis of the studies mentioned above suggests that most of them utilise the

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Ecoinvent databases to assess the performances of the biogas conditioning section. They often

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refer to PSA upgrading technology (Sircar, 2002) and do not provide indications about the specific utilisation of biomethane. Moreover, they generally adopt simple allocation procedures or substitution factors. At the authors’ knowledge, the scientific literature does not report any detailed LCA study comparing anaerobic digestion plants for organic fraction of MSW, aimed at

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producing energy or a transportation fuel. A further peculiarity of the study presented here is that most of input data have been collected from existing plants (Piancatelli, 2017; Barbato, 2017), so obtaining a reliable and exhaustive inventory table. The study estimates the avoided

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environmental burdens by following a new approach (Vadenbo et al., 2017) and using the results

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of a recent research project focused on biomethane utilisation in transport sector (Ricardo-AEA, 2016). The structure of the paper differs from that of a conventional scientific paper in order to provide an appropriate description of the case study and to follow the different phases of a standardised life cycle assessment (ISO, 2006). The next paragraph reports all the information necessary to define the goal and scope of the study. The successive two paragraphs report the life cycle inventory and impact assessment of each of the alternative configurations of the anaerobic 6

ACCEPTED MANUSCRIPT digestion plant under analysis, by identifying and quantifying the environmental burdens and potential impact categories of each of them. The final paragraph describes a sensitivity analysis involving a number of crucial parameters and assumptions that could affect the results of the

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study.

2. GOAL AND SCOPE DEFINITION

This process-based LCA follows the guidelines of the ISO standards (ISO, 2006) and utilises an

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attributional approach, which focuses on describing the environmentally relevant physical flows

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to/from a life cycle system under analysis and its subunits. It is mainly used for estimating environmental impacts of different systems and comparing alternative scenarios (Royal Academy of Engineering, 2017). The intended application of the analysis is a reliable assessment of the environmental sustainability of an AD plant, equipped with a membrane separation unit able to

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upgrade the raw syngas to biomethane for injection into the national grid and utilisation as transport fuel. The plant performances have been compared in a life cycle perspective with those of some alternative configurations, able to satisfy the same functional unit. The main reason for

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carrying out the study is to demonstrate the overall environmental sustainability of the

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biomethane production by anaerobic digestion of separately collected MSW organic fraction, and to quantify the related potential environmental impacts, with the support of an exhaustive and objective tool. In defining the scope of the study, the following aspects have been pointed out, with reference to the base case scenario. The analysed system is a biomethane plant that includes: a wet anaerobic digester operating continuously under mesophilic regime at 37-39°C, and producing 583 m3N/h of raw biogas from 100 t/d of organic waste; a CHP unit, providing the 7

ACCEPTED MANUSCRIPT energy for most of internal consumptions from the combustion of a limited part of the produced biogas; and a membrane separation unit (Scholz et al., 2015), upgrading the remaining flow rate of raw biogas (400 m3N/h) and injecting 207 m3N/h of biomethane into the natural gas grid. The study estimates mass and energy flows for the base case and some alternative plant configurations, and

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identified and quantified all the direct, indirect and avoided burdens. Figure 1 reports the

quantified flow sheet related to the base case configuration, together with the codes of the European Waste Catalogue (EWC) for the different waste streams. The functional unit coincides

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with the service provided by the plant, i.e. the treatment of 100 t/d of waste organic fraction

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obtained by MSW separate collection. It has the composition (Table1) specifically adopted for the waste management planning in the area of interest (Arena and Di Gregorio, 2014), which is in the range of those generally utilised for biowaste-to-biomethane production (Campuzano and Gonzalez-Martinez, 2016). The system boundaries, sketched in Figure 2 highlighting the

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foreground and background systems (Clift et al., 2000), include all the activities from the delivery of the biowaste at the plant entry gate until to the management of all process products (e.g., biomethane as transportation fuel) and residues. The analysis excludes the capital goods, since no

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reliable data are available and they do not affect the comparative analysis. The allocation problem

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of the analysed systems has been avoided by utilising the system expansion methodology (known as "avoided burden method"), by identifying which products are replaced on the markets by the obtained co-products and including their replacement in the model (Clift et al., 2000). The avoided impacts related to the utilisation of biomethane instead of diesel have been evaluated based on data of a recent report about the role of biomethane in the transport sector (Ricardo-AEA, 2016). The adopted procedure is that proposed by Vadenbo et al. (2017), which quantifies the 8

ACCEPTED MANUSCRIPT substitution potential of an available market product (diesel) with a secondary resource (biomethane), as the product of four parameters. These are the potential physical amount of the secondary resource (Ubiomethane); the related recovery efficiency of this resource (ηbiomethane), which depends on the upgrading unit and raw biogas composition; the substitutability (αbiomethane: diesel);

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and the market response (πdiesel). The substitutability represents the functionality provided by biomethane compared to that of diesel per automotive use, i.e. the biomethane and diesel amount necessary to cover the same distance, together with the related emissions into the

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atmosphere. The market response parameter is the share of secondary resource that can

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effectively displace the available product on the market. It has been assumed that the produced biomethane fed a vehicle fleet including 50% of passenger cars and 50% of small rigid trucks moving on urban roads. The analysis does not consider the heavy, long-distance trucks that rarely utilise methane as transportation fuel, since the distribution grid has still a limited extension

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(Ricardo-AEA, 2015). The quality of data is high since all those related to the processes affected directly by decisions based on the study (i.e., the foreground system) derive from official information or measurements related to an existing AD plant, located in Italy and equipped with a

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CHP engine (Piancatelli, 2017), and to a biogas upgrading unit, utilising a membrane separation

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technology (Barbato, 2017). Data related to the remaining, mainly indirect and avoided, burdens derive from the Ecoinvent 3.2 databank and technical reports and studies recently published on scientific literature (Ricardo-AEA, 2016; Anderson, 2015). Data related to the avoided electricity production have been based on the Italian electric energy mix, provided by International Energy Agency statistics (IEA, 2017). The study assesses the life cycle environmental impacts by means of the methodology Impact 2002+, v2.11 (Jolliet et al., 2003), specifically developed to enable 9

ACCEPTED MANUSCRIPT comparative assessments (JRC, 2010). Accordingly to the ISO standard (ISO, 2006), the study normalises the obtained results with the aim of identifying the significant impact categories to compare the environmental performances of different AD plant configurations. These include that of the described AD plant for biomethane production (base case), and those of three alternatives,

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described by the quantitative flow sheets of Figure 3. These alternative scenarios refer to

configurations of the same anaerobic digestion process, characterised by a different fate of the flow rate of produced biogas. In the scenario 1, “only energy”, the total flow rate is sent to the CHP

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unit for energy generation, while in the scenario 2, “only biomethane”, this total flow rate is sent

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to the upgrading unit for biomethane production (with the internal consumptions satisfied by external sources, that is the electricity grid and a boiler fed with methane). Finally, in the scenario 3, “no energy from grid”, the amount of biogas sent to upgrading is just that in excess to the flow rate necessary to satisfy the internal consumptions. The software package utilised for the study is

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SimaPro© 8.2.

3. LIFE CYCLE INVENTORY

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The study collected all the data, whether measured, calculated or estimated, necessary to quantify

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the inputs and outputs of each unit process included within the system boundaries. Table 2 summarises specific values of the main parameters utilised, together with those of flowsheets reported in Figures 1 and 3, to estimate the environmental burdens of all the analysed plant configurations. An essential but exhaustive description of the unit processes included in the base case is reported in the following, with reference to the flow sheet of Figure 1. The biowaste-tobiomethane plant is made-up of three main process units: pre-treatment, wet anaerobic digestion 10

ACCEPTED MANUSCRIPT (with a Continuous-flow Stirred-Tank Reactor), and raw biogas upgrading unit. The pre-treatment is a mechanical sorting process that removes the out-of-target material, making the organic fraction of MSW (OFMSW) a substrate suitable for the anaerobic digestion process. The generated solid residues, which are 15.3% of the total waste inlet flow rate, are mainly made of dirty plastics

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(EWC 19.12.12), and are disposed in a close landfill. The wet anaerobic digester, which operates under mesophilic regime at 37-39°C, produces a digestate and a biogas. The raw digestate is sent to a dehydration and dewatering process that separates the liquid fraction from the solid residues.

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The liquid digestate (EWC 19.06.03) is treated on-site by using 0.5 t/d of sulfuric acid, and then

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discharged: the treated water mass flow rate is 13,000 tonnes/y with the average pollutant concentrations reported in Table 2. All these values are below the limits imposed by Italian legislation (D. Lgs 152, 2006). The dried solid digestate (EWC 19.06.04) is not suitable for agronomic utilisation, according to the Italian legislation (DM 5046, 2016), and it is disposed in a

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close landfill as stabilised material (DM 270910, 2010; Cavinato et al., 2013). The produced raw biogas, composed of 50.8% of methane and 44.6% of carbon dioxide (Table 3), amounts to 140 m3N/twaste, i.e. 513 m3N/tVS with a degradation rate of the volatile solids of 63%, in agreement with

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data from scientific literature (Evangelisti et al. 2014; Møller et al. 2009). In the biowaste-to-

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biomethane base case scenario, a flow rate of 400 m3N/h of raw biogas is sent to the membrane upgrading unit. A combined heat and power (CHP) system burns the remaining part of raw biogas, 183 m3N/h, with an electric energy conversion efficiency of 38% and a production of 80.3 kWh/twaste. Self-consumptions of the plant are about 129 kWh/twaste, which are used for the operations of pre-treatment, anaerobic digestion and wastewater treatment (101 kWh/twaste), and for the operations of raw biogas upgrading (0.29 kWh for each normal cubic meter of raw biogas 11

ACCEPTED MANUSCRIPT sent to upgrading, i.e. 28 kWh/twaste). The electricity from the Italian grid satisfies the remaining energy consumption. The recovered heat is completely utilised for the internal necessities of the plant. The biogas upgrading unit includes preliminary stages of biogas drying and compression, which is responsible of most of electrical consumptions, and hydrogen sulphide removal, which

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requires 3.4 t/y of activated carbon (i.e., about 1 g for each normal cubic meter of treated raw biogas). The upgrading unit (Figure 4) is equipped with a high-efficiency three-stage membrane separation system made of polyimide hollow fibres (Chen et al., 2017), which provides a CO2

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removal of 98.0% and a methane slip limited to 0.69% (Barbato, 2017). The base case

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configuration has three sources of emissions into atmosphere (Table 4): CHP system, biofilter, and upgrading unit. Air emissions from CHP system have been quantified based on the measured flow rate and average pollutant concentrations of the flue gas at the engine stack, also reported in Table 2. The biofilter receives the gas stream coming from the areas of biowaste stock and pre-

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treatment, and digestate processing, which is preliminary treated in a water scrubber, designed to operate in an environment with a low level of acidity, and able to remove dust, limit the picks of pollutant load, and moisturize the gas stream. Air emissions from the biofilter source derive from

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the values reported in the BREF document of European Union (JRC_EC, 2015). The emissions from

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biogas upgrading unit (Figure 4) are the off-gases, composed mainly of the carbon neutral biogenic CO2 (98.9%), and only for a small part (0.79%) of CH4. Table 4 summarises all the data reported above in terms of direct and avoided burdens, and it is the main part of the life cycle inventory table. As mentioned, the impacts related to the utilisation of biomethane instead of diesel have been quantified on the basis of fuel consumptions and specific air emissions of the assumed vehicle fleet (Table 5). For the analysed biowaste-to-biomethane plant, the Ubiomethane is equal to 12

ACCEPTED MANUSCRIPT 96.0 m3N/twaste in the base case scenario, considering the specific biogas production (140 m3N/twaste) and the fraction of raw biogas (0.686) sent to upgrading. The recovery efficiency ηbiomethane has been set equal to 0.518, taking into account the slip of methane and the removal of carbon dioxide and other impurities, during upgrading stage. The substitutability αbiomethane: diesel

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has been evaluated based on data of Table 5, which includes 50% of passenger cars (having a consumption of 4.56 m3N of biomethane or 2.62 kg of diesel for 100 km) and 50% of small rigid trucks (having a consumption of 22.2 m3N of biomethane or 13.1 kg of diesel 100 km). The

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obtained biomethane can be assumed all marketable (πdiesel equal to 1) since the Italian legislation

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will provide economic incentives only for a demonstrated utilisation as transportation fuel of the produced biomethane. Then, the product (Ubiomethane*ηbiomethane*αbiomethane: diesel* πdiesel) provides the distances (in km) covered by the assumed vehicle fleet by using biomethane, and not more by diesel. In the base scenario, these distances are 54,500 km for passenger cars and 11,200 km for

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small trucks (with reference to the functional unit), as it is reported in Table 4. In other words, a tonne of separately collected organic fraction of MSW leads to 49.7 m3N of biomethane, which in turn allow covering 112 km by small truck/bus and 545 km by passenger cars. The influence of the

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composition of vehicle fleet has been investigated in the sensitivity analysis included in the

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interpretation stage of the LCA.

4. LIFE CYCLE IMPACT ASSESSMENT The normalised results of LCIA reported in Figure 5 indicate that the impact categories that play a key role in the environmental performance of the system under analysis are those of GWP, NREP (non-renewable energy potential), RINP (respiratory inorganics potential), and, to a lesser extent, TECP (terrestrial ecotoxicity potential). All the total values for each impact category are negative 13

ACCEPTED MANUSCRIPT (for GWP and NREP) or about zero, highlighting that the examined biowaste-to-biomethane plant implies a substantial reduction of the overall environmental impact. In other words, the avoided burdens related to the biomethane production and utilisation are larger than the direct and indirect burdens. The same figure quantifies the specific contributions of the different stages of

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the life cycle. Large part of the avoided impacts derives from the missed production of diesel (“from crude oil to diesel”) and avoided “tank-to-wheels” emissions for its utilisation in passenger cars and small rigid trucks (E4Tech, 2014; Ricardo-AEA, 2016). On the other hand, the

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corresponding contributions for the biowaste-to-biomethane production and biomethane

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utilisation in the same types of vehicles appear comparatively limited. The first are mainly related to the electricity consumptions (for the AD process and biogas upgrading) and to air emissions from the CHP. The contributions related to the utilisation of biomethane as transportation fuel are limited, and mainly related to the emissions of particulates and nitrous oxide, as shown for the

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main impact categories by the contribution analyses reported in the Appendix. Figure 6 shows the result of the comparative analyses between the four scenarios described in the Goal and Scope Definition, which are synthetically identified by the data listed in the first rows

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of Table 4. The plant configurations aimed to biomethane production (base scenario and scenario

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2 and 3) have the best environmental performances. GWP and NREP values in the base scenario are better than they are in scenario 1 (“only energy”), with an improvement up to 79% and 36%, respectively. The results related to the impact category of Respiratory inorganics are enough close to each other, even though the specific contributions have a different origin, as shown in Figure 7. Therefore, they answer differently to the variation of some parameters, such as the composition of the national electric energy mix and that of vehicle fleet of interest, as discussed in the 14

ACCEPTED MANUSCRIPT Interpretation stage. The scenario 1, “only energy”, shows a crucial role of exported electricity, for the avoided impacts related to the specific national mix, and of gas engine emissions, for the direct impacts related to the overall efficiency of the CHP unit. The scenario 2, “only biomethane”, has an environmental behaviour slightly worse than that of base case, with the avoided impacts reduced

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of 2.41% for GWP and 20.6% for NREP, as shown in Fig. 6. This means that the higher avoided impacts related to a larger biomethane production are partially balanced by direct and indirect

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impacts related to the internal energy consumptions satisfied by external energy sources (Fig. 7).

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INTERPRETATION

In this stage, a sensitivity analysis investigates how the variation of some key parameters affects the results of the LCIA. Some of the parameters taken into account are peculiar for the analysed application, such as the composition of the vehicle fleet (percentage of passenger cars and small

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rigid trucks), utilisation of another transportation fuel instead of diesel as reference fuel in the comparative analysis, specific biomethane consumptions, and methane slip in the upgrading unit.

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The other considered parameters are more general, such as final destination of solid digestate, gas engine efficiency, and national electric energy mix.

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Figure 8 shows the normalised results for the three main impact categories as a function of different compositions of the vehicle fleet (from “100% passenger cars and 0% small trucks” to “0% passenger cars and 100% small trucks”). The examined variation of this parameter confirms that the scenarios with biomethane production are always better than that of “only energy” production, mainly in terms of GWP and NREP. The parameter affects to a limited extent the Nonrenewable energy but remarkably more the categories of Global warming and Respiratory 15

ACCEPTED MANUSCRIPT inorganics. In particular, the RINP remains in a range of low values, even though it improves (i.e. its value decreases) when more passenger cars compose the vehicle fleet, reaching the minimum value when no small trucks are in the fleet. This indicates that RINP is affected by the longer distances (and related avoided emissions) covered by biomethane cars, which are 1091 km/twaste in

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the case of 100% passenger cars, instead of 657 km/twaste in the base case (545 km/twaste by cars and 112 km/twaste by trucks). On the other hand, GWP improves when more small trucks are present in the vehicle fleet, due to the avoided greenhouse gas emissions (Table 5), which in the

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diesel small trucks are strongly higher than in diesel passenger cars (600 g/km vs 107 g/km).

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Table 6 lists the values of all the other parameters of the sensitivity analysis and reports the characterisation values for RINP, GWP and NREP. The results that determined a larger sensitivity on these three impact categories are also shown in Figure 9, but in terms of a variation factor VF. The latter has been defined as the ratio between the result for the specific scenario investigated by

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the sensitivity analysis and that for the base case. There are limited effects for some parameters, such as the variation of distances covered by passenger cars and small trucks (+/-10%), methane slip from the upgrading unit (varied from 0.69% to 1%, with the related lower biomethane

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production), lower electric energy conversion efficiency of the CHP unit (varied from 38% to 30%),

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and the fate of solid digestate (sent to composting instead of landfilling). The latter considers an on-site treatment in bio cells, producing a compost that substitutes peat in horticulture and/or hobby gardening, but requires about 69 kWh for each tonne of treated solid digestate (JRC_EC, 2014; 2015). A lower efficiency of the CHP unit implies higher energy requirements from external sources for biomethane scenarios and a lower amount of exported electricity for the scenario “only energy”: these variations negatively affect all the results and particularly those of RINP for 16

ACCEPTED MANUSCRIPT scenario 1. The utilisation of a fuel different from diesel in the comparative analysis shows various effects. When biomethane replaces fossil natural gas as transportation fuel for cars and trucks, the biomethane scenarios show no variation of GWP, an improvement of NREP, and a worsening of RINP (the latter being anyway small in terms of person*year). On the contrary, when biomethane

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replaces petrol, the biomethane scenarios greatly improve their performances, thanks to the higher avoided impacts related to the petrol production and utilisation, with VF in the range 1.53.3 for GWP and NREP (Figure 9).

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The variation of the national electric energy mix strongly affects all the scenarios with the

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exclusion of scenario 3 “no energy from grid”. The base case refers to the Italian electricity production, which is made of a rather balanced mix of 61% of non-renewable sources (oil 5%, coal 16%, and natural gas 40%) and 39% of renewable sources (hydroelectric 16%, biofuels and waste 8%, solar, wind and geothermal 15%), as reported by the International Energy Agency (IEA, 2017).

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The analysis considers two completely different mixes, those of Sweden and France (Table 7), which imply a lower utilisation of non-renewable sources and a predominant role of nuclear source, respectively. Anyway, both have a lower utilisation of fossil energy sources (1% for Sweden

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and 6% for France, against 61% for Italy): this implies lower avoided burdens related to the

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exported electric energy. Scenario 1 (“only energy”) is negatively affected by this variation, with results particularly worse for RINP (from 0.18 kg PM2.5 to more than 4 kg PM2.5, with VF up to 24). For the same scenario, NREP improves up to a VF=2 with the French energy mix (from 9.72E+04 MJ primary to -18.2E+04 MJ primary), due to larger avoided burdens, and worsens with the Swedish mix (from -9.72E+04 MJ primary to -7.75E+04 MJ primary), due to smaller avoided burdens. The two scenarios of biomethane that utilise electricity from grid show improved RINP 17

ACCEPTED MANUSCRIPT (for instance, in the base case, from 0.11 to about -1.20 kg PM2.5, with a VF of about -11) and GWP (for instance, in the base case, from -1.1E+04 kg CO2 eq. to about -1.3E+04 kg CO2 eq., with a VF of 1.2), as a direct consequence of the lower utilisation of fossil fuels. NREP varies slightly but differently for the two alternatives, showing an improvement with the Swedish mix (due to the

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larger utilisation of renewable sources) and a worsening with the French mix (due to the huge utilisation of nuclear source).

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5. CONCLUSIONS

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The study assesses the environmental sustainability of an anaerobic digestion process of a separately collected organic fraction of municipal solid waste, where the produced biogas is upgraded to biomethane for the road transport sector by means of a membrane separation unit instead that directly burned in a combined heat and power unit for energy generation.

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An attributional, process-based life cycle assessment compares in detail some alternative configurations of the plant, based on data almost completely collected on the field or from official reports. The results indicate that the production of biomethane for road transport is always

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cleaner than the production of energy. The quantification of the (generally large) avoided impacts

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related to the utilisation of biomethane instead of diesel, petrol or fossil natural gas has been referred to a vehicle fleet, made of passenger cars and small rigid trucks, in different percentages.

Large part of the avoided impacts derives from the missed production of diesel and avoided “tank-to-wheels” emissions for its utilisation, while the corresponding contributions for the biowaste-to-biomethane production and biomethane utilisation in the same types of vehicles are

18

ACCEPTED MANUSCRIPT rather limited. In particular, the biomethane scenarios largely improve the impact categories of global warming and non-renewable energy, with reference to the scenario with only energy production from the biogas, with variation in the ranges 58-79% and 8-36%, respectively. Some parameters could affect the results of the life cycle impact assessment. A different

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composition of the vehicle fleet does not change the assessed better sustainability of the

configurations with biomethane production. The utilisation of a fuel different from diesel in the comparative analysis shows various effects. When the substituted fuel is the fossil natural gas, the

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biomethane scenarios show an improvement in the impact category of non-renewable energy, and

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a worsening in the (anyway low) values of respiratory inorganics. On the contrary, when biomethane replaces petrol, the biomethane scenarios have better performances, with large improvement of global warming and non-renewable energy potentials (up to 170%), thanks to the higher avoided impacts related to the petrol production and utilisation.

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The analysis provides a detailed inventory of useful information and data, which can help policy-makers, planners and operators for a correct definition of a sustainable management of the separately collected organic fraction of municipal solid waste. The quantification of potential

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impacts in a life cycle perspective emphasises the environmental advantages connected to the

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utilisation of biomethane as road transport fuel in substitution of fossil fuels.

APPENDIX

Supplementary data associated with this article can be found in the online version of the journal.

19

ACCEPTED MANUSCRIPT ACKNOWLEDGMENTS The authors gratefully acknowledge Foglia Umberto s.r.l. and, in particular, Marco Piancatelli, which supported the study by providing the official measurements related to the anaerobic

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digestion plant and the technical information of all the components of the facility.

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ACCEPTED MANUSCRIPT LIST OF CAPTIONS Table 1. Composition on mass basis of the wet organic fraction of municipal solid waste, entering all the systems under analysis. (Data obtained following the standards ASTM D3173, D3174, D3175, D3176, D1542)

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Table 2. Specific data and parameters utilised together with those of quantified flow sheets to estimate the environmental burdens of the scenarios under analysis.

Table 3. Main characteristics of the raw biogas sent to upgrading and biomethane injected in

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the grid (base case scenario).

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Table 4. Direct and avoided burdens for the scenarios under analysis. All the data refer to the functional unit.

Table 5. Fuel consumptions of passenger cars and small rigid trucks with the specific air emissions utilised for the life cycle assessment. (Sources: Ricardo, 2016; Anderson, 2015;

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Ecoinvent, 2016)

Table 6. Sensitivity analysis for all the considered scenarios as a function of some parameters. Table 7. National electricity production mixes utilised in the sensitivity analysis. (Source: IEA,

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2017)

Figure 1. Quantified flow sheet of the biowaste-to-biomethane plant under analysis (base case), together with the EWC codes. Data are expressed in t/d and refer to the functional unit. I=import flow; E=export flow.

Figure 2. System boundaries for all the plant configurations under analysis, together with the indication of the foreground and background systems and the codes of European Waste Catalogue 26

ACCEPTED MANUSCRIPT (EWC). Dashed lines refer to the solid streams or the avoided burdens that are present only in some of the analysed configurations. Figure 3. Quantified flow sheets of the alternative AD plant configurations: scenario 1, “only energy” (top), scenario 2, “only biomethane” (middle), and scenario 3, “no energy from grid”

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(bottom), together with the EWC codes. Data are expressed in t/d and refer to the functional unit. I=import flow; E=export flow.

Figure 4. Sketch of the three-stage membrane separation unit (redrawn from Barbato, 2017)

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Figure 5. Normalised results of impact assessment for the biowaste-to-biomethane plant under

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analysis (base case scenario). The shaded rhombus indicates the total value for each impact category.

Figure 6. Normalised results of impact assessment for the four scenarios. Figure 7. Comparison between the normalised results of life cycle impact assessment for the

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base scenario, scenario 1 (“only energy”) and scenario 2 (“only biomethane”). The shaded rhombus indicates the total normalised value for each impact category. Figure 8. Normalised results of life cycle assessment as a function of different compositions of

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the vehicle fleet (percentage of passenger cars and small rigid trucks) for the base case scenario,

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scenario 1 (“only energy”), scenario 2 (“only biomethane”) and scenario 3 (“no energy from grid”). Figure 9. Sensitivity analysis for all the considered scenarios, in terms of a variation factor VF, which transforms the base case value in that related to the modified parameter: VF = 1 indicates no variation; some variations occur when VF is < 1 or VF > 1; and a negative value of VF changes the potential impact from positive to negative or viceversa.

27

ACCEPTED MANUSCRIPT

% 15.49 2.51 0.76 0.20 0.03 13.62 62.50 4.89 100.00

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Carbon Hydrogen Nitrogen Chlorine Sulphur Oxygen (by diff.) Moisture Ash

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Table 1. Composition on mass basis of the wet organic fraction of municipal solid waste, entering all the systems under analysis. (Data obtained following the standards ASTM D3173, D3174, D3175, D3176, D1542)

ACCEPTED MANUSCRIPT Table 2. Specific data and parameters utilised together with those of quantified flow sheets to estimate the environmental burdens of the scenarios under analysis. Plant treatment capacity, t/y

35,000

Pre-treatment Solid residues to landfill, %input

15.3%

Anaerobic digestion 3

140 513 583 0.62 101 338

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Produced raw biogas, m N/twaste 3 Produced raw biogas, m N/tVS 3 Produced raw biogas, m N/h Degradation rate of volatile solids, % Electric energy for AD and waste water treatment, kWh/twaste Thermal energy for AD and waste water treatment, MJ/twaste Pollutants concentrations in discharged water, mg/kg CODmax BOD5 Suspended solids NH4 CHP Electric energy conversion efficiency, % Thermal energy conversion efficiency, % 3 Pollutants concentrations in CHP flue gases, mg/m N NOx CO COT PM SO2 HCl Hg HF NH3 Cd + Tl PCDD + PCDF IPA Sb As Co Cr Mn Ni Pb Cu Vn Biofilter 3 Biofilter flow rate, m N/h 3 NH3 concentration in biofilter flow rate, mg/m N Membrane upgrading unit 3 Electric energy for biogas upgrading, kWh/m N raw biogas 3 Activated carbon, g/m N raw biogas CO2 removal, % CH4 slip, % Off gas composition, %vol CH4 CO2 O2 N2 H2O

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127 40 8 5

0.38 0.45

248 205 27.75 2.3 30.45 4.73 0.007 0.43 1.83 0.019 2.7E-09 0.067 0.033 0.033 0.033 0.031 0.05 0.055 0.033 0.033 0.033 55,000 0.46 0.29 1 98.0% 0.69% 0.79% 98.93% 0.09% 0.04% 0.14%

ACCEPTED MANUSCRIPT Table 3. Main characteristics of the raw biogas sent to upgrading and biomethane injected in the grid (base case scenario).

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50.83 44.59 0.01 0.38 0.10 <0.01 4.09

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CH4 CO2 H2S N2 O2 NH3 H2O

Biomethane 207 153 12,000 26.1 34.9

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Raw biogas 400 511 5 37-39 18.2

Volumetric flow rate, m3N/h Mass flow rate, kg/h Pressure, mbarg Temperature, °C Low Heating Value, MJ/m3N Composition, %vol

97.47 1.72 < 0.0004 0.70 0.11 <0.0002 0

ACCEPTED MANUSCRIPT Table 4. Direct and avoided burdens for the scenarios under analysis. All the data refer to the functional unit.

TOC (kg)

Scenario 3

Only energy

183 (31) 400 (69)

583 (100) -

Only biomethane 583 (100)

No energy from grid 283 (49) 300 (51)

1 30 2,157 15.31 15.60 5.6 10.6 8.7

1 30 15.31 15.60 17.9 33.6 27.8

1 30 10,100 33,760 15.31 15.60 -

1 30 15.31 15.60 8.7 16.3 13.5

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Scenario 2

1.2

3.8

-

1.8

0.1 1.3 0.20

0.3 4.1 0.6

-

0.2 2.0 0.3

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PM (kg) SO2 (kg) HCl (kg)

Scenario 1

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Biogas sent to CHP, m3N/h (%) Biogas sent to upgrading, m3N/h (%) DIRECT BURDENS Pre-treatment and anaerobic digestion phases Water (t) Diesel (L) Electric energy from the grid (kWh) Thermal energy from natural gas boiler (MJ) Solid residues to landfill, EWC 19.12.12 (t) Solid digestate to landfill, EWC 19.06.04 (t) CHP air emissions, tbiogas/d NOx (kg) CO (kg)

Base Scenario Case study

0.0003

0.001

HF (kg)

0.02

0.06

-

0.03

NH3 (kg)

0.08

0.25

-

0.12

Cd (g)

0.8267

2.6

-

1.28

PCDD (mg)

0.0001

0.0004

-

0.0002

PAH (g)

2.9

9.1

-

4.4

Sb (g)

1.4

4.4

-

2.1

As (g)

1.4

4.4

-

2.1

Co (g)

1.4

4.4

-

2.1

Cr (g)

1.3

4.2

-

2.0

Mn (g)

2.1

6.8

-

3.3

Ni (g)

2.3

7.5

-

3.6

Pb (g)

1.4

4.4

-

2.1

Cu (g)

1.4

4.4

-

2.1

Vn (g)

1.4

4.4

-

2.1

CO2 biogenic (t)

8.2

26.2

-

12.7

607.2

607.2

607.2

607.2

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Hg (kg)

0.0005

Biofilter air emissions NH3 (g) Water emissions from liquid digestate

ACCEPTED MANUSCRIPT treatment 4.7 1.5

4.7 1.5

4.7 1.5

4.7 1.5

Suspended solids (kg)

0.30

0.30

0.30

0.30

NH4 (kg)

0.18

0.18

0.18

0.18

Biogas upgrading unit, ttreated biogas/d

12.3

-

17.9

9.2

Activated carbon consumption (kg) Activated carbon disposal (kg) Electric energy from the grid (kWh) Air emissions (off-gas) CH4, biogenic (kg) CO2, biogenic (kg) Biomethane utilisation Biomethane utilisation in passenger car (km) Biomethane utilisation in small rigid truck (km) AVOIDED BURDENS Electric energy exported to the grid (kWh) Diesel production and utilisation in passenger car (km) Diesel production and utilisation in small rigid truck (km)

9.71 11.43 2,784

-

14.2 16.7 4,060

7.29 8.57 -

24 8,235

-

35 12,009

18 6,176

54,500 11,200

-

79,500 16,330

40,900 8,400

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15,400 -

79,500

40,900

11,200

-

16,330

8,400

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CODmax (kg) BOD5 (kg)

ACCEPTED MANUSCRIPT Table 5. Fuel consumptions of passenger cars and small rigid trucks with the specific air emissions utilised for the life cycle assessment. (Sources: Ricardo, 2016; Anderson, 2015; Ecoinvent, 2016)

Biomethane Small truck

m3N/100 km 4.56

mg/km

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Ricardo, 2016; Anderson, 2015; 3 Anderson, 2015; Ecoinvent, 2016. 4 Ecoinvent, 2016.

350 1,250 109

2.62

13.1

1.07E+05 0.60 4.0 13.2 1.34 210 0.46 1.5 0.16 6.83

6.00E+05 3.0 4.0 17.5 1.66 291 1.91 16.1 0.20 8.95

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1,290 27.6 0.64 50 440 59 0 0.3 -

1 2

22.2

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Fuel consumption1 Air emissions from fuel utilisation CO2 fossil1 CO biogenic2 CH4 fossil1 CH4 biogenic1 N2O1 NMVOC3 Hydrocarbons3 NOx1 SO21 PM2.51 Heavy metals4 Aldehydes and ketones4

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Passenger car

Diesel Passenger Small car truck kg/100 km

-

4,840 291 0 1.6 -

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Table 6. Sensitivity analysis for all the considered scenarios as a function of some parameters.

French electric energy mix

Base case -1.08E+04

GWP, kg CO2 eq. Scen. 1 Scen. 2 -6.03E+03 -1.05E+04

Scen. 3 -9.51E+03

Base case -1.32E+05

NREP, MJ primary Scen. 1 Scen. 2 -9.72E+04 -1.05E+05

Scen. 3 -1.23E+05

0.36

0.17

-1.12E+04

-

-1.15E+04

-1.00E+04

-1.38E+05

-

-1.17E+05

-1.29E+05

-

0.96

0.47

-9.93E+03

-

-9.55E+03

-9.02E+03

-1.22E+05

-

-9.33E+04

-1.16E+05

-

0.50

0.24

-1.13E+04

-

-1.00E+04

-1.38E+05

-

-1.17E+05

-1.29E+05

-

0.82

0.40

-9.86E+03

-

-9.46E+03

-8.98E+03

-1.21E+05

-

-9.30E+04

-1.16E+05

-

0.53

0.33

-1.07E+04

-

-1.06E+04

-9.44E+03

-1.32E+05

-

-1.08E+05

-1.22E+05

0.97

-

1.77

0.89

-1.02E+04

-

-9.95E+03

-9.23E+03

-1.92E+05

-

-1.96E+05

-1.69E+05

-0.51

-

-0.38

-0.21

-1.83E+04

-

-2.18E+04

-1.53E+04

-2.92E+05

-

-3.42E+05

-2.45E+05

0.93

1.32

0.75

1.91

-1.26

4.46

-1.20

4.29

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-

-1.15E+04

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General sensitivity parameters Solid digestate to postcomposting 0.86 Lower CHP electric energy conversion efficiency (30%) Swedish electric energy mix

Scen. 3 0.32

1.02

-1.01E+04

-5.57E+03

-1.00E+04

-8.98E+03

-1.24E+05

-9.12E+04

-9.90E+04

-1.15E+05

-

1.15

-9.84E+03

-1.52E+02

-

-8.34E+03

-1.19E+05

-1.82E+05

-

-1.06E+05

-3.42

-

-1.28E+04

4.03E+02

-1.67E+04

-

-1.39E+05

-7.75E+04

-1.27E+05

-

-3.26

-

-1.26E+04

-1.52E+02

-1.62E+04

-

-1.05E+05

-1.82E+05

-3.07E+04

-

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Biomethane replaces fossil methane as transportation fuel Biomethane replaces petrol as pass. car fuel

RINP, kg PM2.5 Scen. 1 Scen. 2 0.18 0.66

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Base case Reference Value 0.11 Specific sensitivity parameters +10% travelled km by pass. cars with 0.003 biomethane as fuel -10% travelled km by pass. cars with 0.41 biomethane as fuel +10% travelled km by small trucks with 0.10 biomethane as fuel -10% travelled km by small trucks with 0.32 biomethane as fuel Higher methane slip in the upgrading (1%) 0.12

ACCEPTED MANUSCRIPT Table 7. National electricity production mixes utilised in the sensitivity analysis. (Source: IEA, 2017)

Oil Coal Natural gas Nuclear Renewable sources, %

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Hydroelectric Biofuel and waste Solar, wind and geothermal

Sweden 36 1 35 64 47 7 10

France 84 2 4 78 16 10 1 5

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Non-renewable sources; %

Italy 61 5 16 40 0 39 16 8 15

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Figure 1. Quantified flow sheet of the biowaste-to-biomethane plant under analysis (base case), together with the EWC codes. Data are expressed in t/d and refer to the functional unit. I=import flow; E=export flow.

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BACKGROUND

ORGANIC WET FRACTION of MSW EWC 20.01.08 FOREGROUND

Anaerobic Digestion

Energy Chemicals

Water and air emissions Solid residues EWC 19.12.12

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Water

Landfill disposal

Solid digestate Biogas EWC 19.06.99

Biogas upgrading unit

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CHP unit

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EWC 19.06.04

Biomethane

Electricity

Production and utilisation as automotive fuel

Electricity from grid

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Figure 2. System boundaries for all the AD configurations under analysis, together with the indication of the foreground and background systems and the codes of European Waste Catalogue (EWC). Dashed lines refer to the solid streams or the avoided burdens that are present only in some of the analysed configurations.

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Figure 3. Quantified flow sheets of the alternative AD plant configurations: scenario 1, “only energy” (top), scenario 2, “only biomethane” (middle), and scenario 3, “no energy from grid” (bottom), together with the EWC codes. Data are expressed in t/d and refer to the functional unit. I=import flow; E=export flow.

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Compressor FIRST STAGE OF MEMBRANES

Biomethane (> 97% CH4 )

THIRD STAGE OF MEMBRANES

Permeate 3rd stage

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Permeate 2nd stage

Permeate 1st stage

Retentate 3rd stage

SECOND STAGE OF MEMBRANES

Off-gas

(< 1% CH4)

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Retentate 1st stage

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Figure 4. Sketch of the three-stage membrane separation unit (redrawn from Barbato, 2017)

ACCEPTED MANUSCRIPT 1.0 Diesel production and utilisation in "small truck" Diesel production and utilisation in "passenger car"

0.5

Biomethane utilisation in "small truck" Biomethane utilisation in "passenger car"

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person·year

0.0

Biogas upgrading phase

-0.5

AD electricity consumptions

Biofilter air emissions

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-1.0

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WWTP water emissions

CHP air emissions

Solid digestate disposal

Pre-treatment phase

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Figure 5. Normalised results of impact assessment for the biowaste-to-biomethane plant under analysis (base case scenario). The shaded rhombus indicates the total value for each impact category.

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0.00

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-0.20

person · year

-0.40

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-0.80 Base scenario "case study"

Scenario 2 "only biomethane" Scenario 3 "no energy from grid" -1.20

Respiratory inorganics

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Figure 6. Normalised results of impact assessment for the four scenarios.

Non-renewable energy

ACCEPTED MANUSCRIPT 1.0 Diesel production and utilisation in "small truck" Diesel production and utilisation in "passenger car"

0.5

Biomethane utilisation in "small truck"

0.0

Biomethane utilisation in "passenger car"

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person·year

Biogas upgrading phase

-0.5 AD electricity consumptions

Exported electricity

-1.0

Biofilter air emissions

-1.5

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WWTP water emissions

-2.5

Terrestrial ecotoxicity

Global warming

CHP air emissions

Solid digestate disposal

Pre-treatment phase

Total

Non-renewable energy

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Figure 7. Comparison between the normalised results of life cycle impact assessment for the base scenario, scenario 1 (“only energy”) and scenario 2 (“only biomethane”). The shaded rhombus indicates the total normalised value for each impact category.

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0.4

100% PassCar 0%SmallTruck

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70% PassCar 30% SmallTruck

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50% PassCar 50% SmallTruck

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30% PassCar 70% SmallTruck

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-1.2 -1.4 Scenario Scenario Scenario 1 2 3

Base Case

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Scenario Scenario Scenario 1 2 3

Base Case

Scenario Scenario Scenario 1 2 3

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Non-renewable energy

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Figure 8. Normalised results of life cycle assessment as a function of different compositions of the vehicle fleet (percentage of passenger cars and small rigid trucks) for the base case scenario, scenario 1 (“only energy”), scenario 2 (“only biomethane”) and scenario 3 (“no energy from grid”).

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20.0 Solid digestate to postcomposting stage

10.0 0.0

Biomethane replaces petrol as pass. car fuel

Solid digestate to postcomposting stage

-10.0 -20.0

Lower CHP electric energy conversion efficiency (30%)

Swedish electric energy mix Base case Scenario 1

Lower CHP electric energy conversion efficiency (30%)

GWP

Biomethane replaces petrol as pass. car fuel

Swedish electric energy mix Base case

Solid digestate to postcomposting stage

Biomethane replaces fossil methane as transportation fuel 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0 -0.5

Lower CHP electric energy conversion efficiency (30%)

Scenario 3

No variation

Biomethane replaces petrol as pass. car fuel

Scenario 1

Scenario 2

French electric energy mix

NREP

Swedish electric energy mix Base case

Scenario 1

Scenario 2 Scenario 3 No variation

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French electric energy mix

Biomethane replaces fossil methane as transportation fuel 3.0 2.5 2.0 1.5 1.0 0.5 0.0 -0.5

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Biomethane replaces fossil methane as transportation fuel 30.0

Scenario 2 French electric energy mix

Scenario 3 No variation

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Figure 9. Sensitivity analysis for all the considered scenarios, in terms of a variation factor VF, which transforms the base case value in that related to the modified parameter: VF = 1 indicates no variation; some variations occur when VF is < 1 or VF > 1; and a negative value of VF changes the potential impact from positive to negative or viceversa.

ACCEPTED MANUSCRIPT HIGHLIGHTS

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The production of biomethane or energy by anaerobic digestion of MSW organic fraction is compared An attributional LCA is utilised to quantify environmental burdens and potential impacts The biogas upgrading unit utilises a membrane separation unit made of polymide hollow fibres Reliable data provide an exhaustive LCI table for all the configurations and sub-units Production of biomethane for road transport is always cleaner than the production of energy. Biomethane as transport fuel reduces GHG emissions and non-renewable energy consumptions

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