Eco-efficiency and entropy generation evaluation based on emergy analysis: Application to two small biogas plants

Accepted Manuscript Eco-efficiency and entropy generation evaluation based on emergy analysis: Application to two small biogas plants G. Merlin, H. Boileau PII:

S0959-6526(16)32181-3

DOI:

10.1016/j.jclepro.2016.12.117

Reference:

JCLP 8692

To appear in:

Journal of Cleaner Production

Received Date: 26 June 2016 Revised Date:

19 December 2016

Accepted Date: 21 December 2016

Please cite this article as: Merlin G, Boileau H, Eco-efficiency and entropy generation evaluation based on emergy analysis: Application to two small biogas plants, Journal of Cleaner Production (2017), doi: 10.1016/j.jclepro.2016.12.117. 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.

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ACCEPTED MANUSCRIPT ECO-EFFICIENCY AND ENTROPY GENERATION EVALUATION BASED ON EMERGY ANALYSIS: APPLICATION TO TWO SMALL BIOGAS PLANTS.

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G. MERLINa,b*, H. BOILEAUa a LOCIE UMR CNRS 5271, Université Savoie-Mont Blanc 73376 Le Bourget du Lac, France

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b

LEPMI UMR CNRS 5276, Université Grenoble-Alpes, 38402 Saint Martin d’Hères, France. *Corresponding author [email protected] 33 (0) 4 79 75 86 21

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Abstract: The research presented in this paper demonstrates how emergy analysis can be used to measure the ecoefficiency of unit operation processes (UOP). To illustrate this, two small biogas plants in France were analyzed, both with a nominal biogas production of almost 300 Nm3/d. One plant is an Upflow Anaerobic Sludge Blanket (UASB) digester treating dairy effluents while the other is a Continuous Stirred Tank Reactor (CSTR) farm biogas plant with a cogeneration of a nominal power of 45 kWe. The objectives of the study were to show: (a) the long-term sustainability of both UASB and CSTR biogas plants by assessing the respective eco-efficiencies using emergy analysis; (b) whether emergy analysis can holistically account for the true benefits of biogas plants; (c) how energy change or transformation is generated in any UOP systems. Energy analysis revealed some dysfunctions for both systems. The results show that it is possible to improve anaerobic digestion and efficiency of the process working on heat supply and insulation for the UASB-AD (anaerobic digester) plant and on insulation for the CSTRAD plant. Emergy analysis of the UASB-AD plant through emergy ratios and indices confirm that ecoefficiency was not optimal due to a low biogas production and high sodium hydroxide consumption. For the CSTR, emergy indices show a better eco-efficiency than for the UASB with a biogas transformity close to 4x105 sej/Jbiogas in the same range as literature values. However, digester operation and maintenance should be upgraded as well as the use of digestate in order to improve the eco-efficiency of this kind of energy conversion system. The discussion chapter explores the applicability of emergy analysis to improve sustainability of UOP taking into account relationships between emergy, entropy generation and information theory. Entropy generation decreases after improving efficiency and sustainability, in accordance with the maximum empower principle.

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Keywords: embodied energy, anaerobic digestion, entropy generation, emergy

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1. INTRODUCTION

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Eco-efficiency grounds on the concept of creating more goods and services while using fewer resources and creating less waste and pollution (WBCSD, 2000). The concept of sustainability was defined in 1987 (Bruntland, 1987) as: “development that meets the needs of the present without compromising the ability of future generations to meet their own needs”. In order to preserve resources, eco-efficiency has been proposed to promote sustainable development. Eco-efficiency indices based on emergy analysis can be used to evaluate sustainability of human systems such as industry, business, buildings or agricultural systems (Zhou et al., 2010). After research and discussions, seven conditions were defined as compulsory to consider a process as eco-efficient (WBCSD, 2000). They are: (1) a reduction in the material intensity of goods or services;(2) a reduction in the energy intensity of goods or services; (3) maximized use of renewable resources; (4) reduced dispersion of toxic materials; (5) increased service intensity; (6) improved recyclability; (7) greater durability of product. From a scientific stand of view, the question is how to quantify sustainability and thus ecoefficiency on a physical level. This is a subject of debate in the scientific community (Liao et al., 2013; Gaggioli et al., 2014). In a recent review of the 48 available methods that can be used by industries to strengthen the assessment of their environmental sustainability, the main conclusion is that every method has strengths and weaknesses and it is in the eye of the beholder to decide which method fits to his goal. (Angelakoglou and Gaidajis, 2015). Among these numerous methods, emergy analysis belongs to the category of material and energy flow analysis and is an interesting approach to sustainability quantification. Emergy evaluation is a method based on thermodynamic principles providing indicators used to assess the sustainability of a given system (Bastianoni et al., 2007). These kinds of indicators provide an assessment of sustainability rate consistent with the principle of sustainability stating that resources should be used at a rate that allows their re-formation (Daly, 1990). Emergy approach is based on the theory that any system (ecological, social or economic) is centered on the transformation of available energy (Xue et al., 2015). The emergy evaluation method is acknowledged to be a holistic approach to account for the primary (solar) energy that generates the renewable and non-renewable resource flows used by human activities (Arbault et al., 2013) and more generally by all biophysical processes on planet Earth. In a previous study (Merlin and Lissolo, 2010), energy and emergy analysis have been used to assess sustainability of two types of small wastewater treatment facilities, a constructed wetland and an activated sludge sequential batch reactor. Emergy indices derived from emergy analysis were in favor of the constructed wetland process and thus confirmed its eco-efficiency. The present study focuses on Anaerobic Digestion (AD) plants as simple systems called Unit Operation and Processes (UOP). Anaerobic digestion for biogas production is a promising renewable energy technology among other alternative processes that could be used to convert energy either through gasification and or combustion. Anaerobic digestion can turn organic matter partly into biogas as renewable energy and the final residues (called “digestate”) into fertilizers or organic amendment. Furthermore, performance and efficiency of biogas plants can be improved and particularly concerning eco-efficiency. As promoted in France, the standard anaerobic digestion plant is located on or nearby a farm, and transforms agricultural waste such as manure, slurry or cheese whey with other co-substrate such as activated sludge coming from wastewater treatment plant, into biogas and digestate. Biogas goes to a combined heat power (CHP) unit for electricity production and heat supply, or now, turned into biomethane (CO2 removed) used as natural gas substitute injected in the network. Digestate can be recycled in a wastewater treatment plant or separated into fibers digestate and liquid digestate reused in agriculture as nitrogen amendment. This standard AD plant is generally a small unit producing from few hundreds to few thousand cubic meters of biogas per day, and with an electric power installed from 50 to 200 kWe. As part of its 2015 energy transition law, France committed to building 1,500 units over the next three years (Law 2015-992, August 17 2015). A recent report (ATEE, 2016) conducted in France on 44 agricultural AD plants and 10 territorial AD plants (using food waste and other organic residues) shows that 44% have digestion process dysfunctions and 31% cogeneration dysfunctions. Only 31%

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ACCEPTED reach the nominal biogas and electricity production.MANUSCRIPT This deficiency seems due to heterogeneity of feeding systems and lack of adequately adapted equipment. This paper shows the application of energy and emergy analysis to assess the sustainability of French AD systems by using two types of biogas plants treating agricultural wastes with or without cogeneration and having a nominal biogas production of about 300 Nm3/d. These biogas plants are in the range of standard AD plant as promoted in France. One biogas plant was an Upflow Anaerobic Sludge Blanket (UASB) treating dairy effluents and the other was a Continuously Stirred Tank Reactor (CSTR) farm biogas plant with cogeneration using various substrates. The objectives of the study are to determine: (a) the long-term sustainability of both UASB and CSTR biogas plants by assessing the respective eco-efficiencies using emergy analysis; (b) whether emergy analysis can holistically account for the true benefits of biogas plants; (c) how energy change or transformation is generated in any UOP systems. Relationships between energy, entropy, information and emergy are discussed based on the results obtained in this study. Biological UOP like biogas plants are considered as specific ecological systems where human control is more or less significant and more or less far-from-equilibrium thermodynamics. In this case, thermodynamic extremization principles can be used like in an ecological context. These principles hypothesize that entropy production will be maximized or minimized which can constrain the dynamics and structure of far-from-equilibrium systems (Kleidon et al. 2010; Yen et al., 2014). The Human role is to maintain the UOP system in a steady-state far from thermodynamic equilibrium in order to perform work. The idea is to have the most relevant UOP system in respect with thermodynamic principles. In this case, it could be useful to have the better self-organized and dissipative structure for the process. As thermodynamics is connected to information theory and more specifically entropy (Shannon, 1948; Jaynes 1957; Avery, 2012), the discussion section explores the potential applicability of emergy analysis to improve sustainability of UOP such as AD-plants taking into account the relationships between emergy, entropy generation and information theory.

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2. MATERIALS AND METHODS 2.1Biogas plants description Two types of small biogas plants treating agricultural wastes with or without cogeneration were studied for emergy analysis application. Both biogas plants are located in the French Pre-Alps at a distance in a straight line of 16 km (45°27’N, 5°52’E and 45°35’, 5°51’E, respectively). Table 1 summarizes main operation parameters. Both systems have a daily potential biogas production of about 300 cubic meters. One digester is an upflow anaerobic sludge blanket digester (UASB), the other being a continuous stirred tank reactor anaerobic digester (CSTR). Detailed technical flow charts of both biogas plants are shown in Figure 1. The UASB-AD plant treats only dairy effluent and the CSTR-AD plant treats diverse solid and liquid agricultural waste. For the CSTR-AD plant, the biogas is used to generate electricity first, and then heat is used on site. Climatic conditions are quite similar for both units (Table 1).

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Table 1: Main operation parameters for both types of anaerobic digestion plants.

Type (AD)

UASB

CSTR

Biogas production Nm3/d

≈ 170(≈300)*

≈300

Cogeneration

-

+ (44kWe)

Inputs /Year

Dairy effluent

Various agricultural waste

11500T

solids: 1500T; liquids: 2700T

Elevation

820 m

350 m

°C [min ; max]

[-10 ; 28]

[-5 ; 32]

*300 was the nominal biogas production and 170 the average measured production 4

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A Mixer

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4

Flarestack

Inflow hardtop

Biogas

2

Flexible top (membrane)

Liquids

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Outflow

Storage tank 3

Storage tanks Heat exchanger

cogenerator

Digestate out 5

B

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2.2. UOP energy and emergy analysis

UOP systems are open systems, transferring mass and energy to and from their environment. These two features can be measured by energy flux and the changes in entropy amount. Energy flux is the sum of all energy inputs and outputs (mechanical, chemical, electrical, thermal, etc.). If the "quality of energy" is to be considered, exergy may be used and/or also emergy as in this study. Hermanowicz (Hermanowicz, 2008) proposes to use in the sustainability assessment only the part of the total energy flux that changes its form in association with the changes of entropy, with combined criterion omega (Ω): Ω = ∆E + T ∆S (1) Where ∆S is the change of entropy, ∆E is the associated energy flux, and T is the absolute temperature. Processes that result in large positive entropy changes or use large amounts of energy flux are deemed less sustainable and are characterized by Ω>0. For some systems, energy flux may be sufficient for a complete description without considering the entropy but depends on the definition of spatiotemporal boundaries of the system. The concept of sustainability implies to take into account the time and it is therefore necessary to use a time dependent method of analysis. The emergy method developed by H.T. Odum (Odum, 1996), corresponds to the energy hierarchy principle, which states that energy quality can be measured by the energy used in the transformations from one type of energy to the next. Emergy accounts for past available energy throughout history of a product or service for its formation. On a spatial scale, emergy is the aggregate of energy demanded for direct/indirect supports. The primary energy is the solar energy (Odum, 1988; Brown et al., 2004). Emergy accounting uses the thermodynamic basis of any form of energy resources and human services and converts them into solar energy’s equivalent. Thus, solar emergy Joule (sej) is the common unit for any product or service. In comparison to other environmental accounting methods (e.g. exergy,

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Figure 1: Technical flow-charts of the biogas AD plants. A: UASB-AD plant; B: CSTR-AD plant. Numbers represent the different sectors and devices of the wastewater treatment plant where the heat transfer was modeled.

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ACCEPTED MANUSCRIPT embodied energy or Input-Output analysis, LCA), the emergy analytical window is less limited (Yi et al., 2015) and can offer a holistic solution for sustainability evaluation. To determine the energy flux, an energy balance has been applied to our UOP systems according to the basic equation of conservation of energy (Merlin et al., 2012). The anaerobic digestion unit is considered as a thermodynamic open system and making different assumptions: (1) kinetic energy and potential energy are negligible and variations are time independent; (2) pseudo steady-state heat transfer within the system; (3) change of phase is negligible for calculation of enthalpy. The boundary of the spatial scale defined in this study is the UOP and its proximal environment. UOP requires a great deal of energy concentration and transformation for its construction its operation and its maintenance. The system diagram takes into account these considerations. We have chosen to restrict the study to UOP systems and their immediate environment because a good analysis requires to get reliable and sufficient data.

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Raw data on flows and storage tanks are converted into emergy units, and then summed for a total emergy flow to the system. Emergy is calculated from equation 2: (2) Emi=Ei ×Tri Where Emi is solar emergy of energetic flow, Ei is energy or mass input, and Tri is the transformity that refers to specific emergy value of the input. A unit emergy value (UEV) is assigned to each input to calculate its corresponding emergy value. Previous literature studies refer to different baselines (i.e. the sum of annual independent emergy inputs to the geobiosphere, i.e. solar radiation, tidal energy and geothermal heat, which are used as the reference to quantify the transformity of natural resources). In the present study, inputs and results are expressed with respect to the 1.2x1025 sej/year baseline (Campbell, 2016). Emergy values from another baseline in their original publications were converted using a simple ratio. Most of the UEVs were retrieved from the recently developed UEVs database (Tilley et al., 2012) and were corrected to be expressed on the adopted baseline (1.2x1025 sej/year). For this study, the total emergetic flow is computed as the summation of emergy input for each material or component divided into two distinct categories: (a) emergy of AD plants building (“building immobilization”) and (b) operational emergy for the UOP (equation 3). =∑ +∑ (3)

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The emergy “building“ is composed of the flow emergy for the building’s material production (Emmaterial) and emergy onsite construction work including onsite renewable inputs, human labor (Hi), and transportation (Emconstruction) (equation 4). In order to aggregate the annual running energy, the global construction emergy is divided by its expected life span over twenty years in the present case.

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∑

=∑

+∑

=∑

!

+

(4)

where: Ti: expected life span; Tri: transformity; ρiVi: mass used

The emergetic flow for UOP operation and maintenance is computed as the summation of (a) energy demand for operation and maintenance (EDj ) including human labor (Hj) and (b) energy content of inputs (Elk : sun, organic matter, electricity …) (equation 5). All inputs considered in the production systems are converted into annual flows based on the expected useful life and operation period. ∑

= ∑$ !" #$ %&$ ' +

$

+ ∑)

!

() %&)

(5)

A renewability factor is introduced to divide each purchased resource into renewable and non-renewable fractions. Emergy algebra is used to combine the emergy from upstream flows (Odum, 1996; Le Corre and Truffet, 2012). 6

ACCEPTED MANUSCRIPT The final step involves the quantitative interpretation of the results using diverse indices or ratios. The details of emergy accounting and transformities estimation for the products and services can be referred to the works of Odum (1996 and 2000); Brown and Ulgiati (2004), Tilley et al. (2012) and Wu et al. (2015). Details of the different calculations for energy and emergy analysis are presented as supplementary material in addition to this article.

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2.3 Exergy, entropy generation, information and emergy A fundamental question for this type of analysis is how information “embedded in the system” used to build it and to maintain its operation should be valued in terms of energy and emergy. Entropy seems an interesting parameter to take into consideration due to the equivalence between thermodynamic entropy and information entropy. Thermodynamic entropy is equivalent to the information entropy of a given distribution (Jaynes, 1957 a and b). The relevance of entropy for living systems and ecosystems has been demonstrated (Lesne, 2011). Non-equilibrium thermodynamic systems are organized in steady state such that the rate of entropy production is maximized (Kleidon et al.., 2010). It has also been shown that ecological systems maximize their emergy storage (Odum, 1996) and the residence time of energy (Fath et al., 2001). Ecological and living systems evolve such that energy becomes more accessible through time. Open systems, in a state far from equilibrium, become stabilized when entropy production is maximized by the emergence of dissipative structures (Serizawa et al., 2014). Dissipative structures with access to free energy will reduce internal entropy and become more organized (ordered) by externalizing entropy to their environment (Skene, 2015). This principle states that energy flow should become easier (lower resistance) as time increases, allowing energy dissipation to increase (Bejan and Lorente, 2010). This principle is consistent with maximum entropy generation (Yen et al., 2014). The improvement of an industrial process is similar to the evolution according to Darwin and must follow the physical laws that govern it.

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Shannon introduced statistical entropy as a basic concept in information theory, measuring the average missing information on a random source (Shannon, 1948). Entropy and relative entropy have a central position in statistical laws describing generic collective behaviors (Lesne, 2014), providing insights into the notions of randomness, typicality and disorder. Knowledge (useful information) is the capacity to change the organization (design of the process) to facilitate flow (Bejan and Lorente, 2013).

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Let us take as an example of knowledge, a physical law: the Constructal law. A system governed by this law has reached the highest reachable level of order. In the absence of this knowledge leading to have the best organization, the system has a greater entropy generation and a lower dissipation of energy throughout the system due to the increasing resistance to flow. Therefore, the entropy corresponds to missing useful information.

More knowledge leads to improved (optimized) flow. Useful and relevant information for the system is high quality information. The organization and development of natural and living systems follow this principle of acquiring a more and more relevant knowledge (Dewar, 2003; Harte and Newman, 2014; Skene, 2015). Therefore, the flow of materials, energy and knowledge are linked together (Bejan and Lorente, 2013). Thus, a fundamental question in energy or emergy analysis is: how information should be valued in terms of energy and emergy? Another question concerns the dependence on human intervention and/or external information for the process. How does information contribute to optimize the sustainability? What is the price (cost) in terms of energy of the needed information for a better system’s sustainability? In other terms, the entropy generation rate (J.s-1.K-1) seems a universal metric to examine how any system like an UOP for example is organized (i.e., how information flows) to respect the maximum entropy production principle or the minimum entropy generation (within the system).

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With UOP based on biological processes such as AD plant it would be relevant to measure or estimate the part of technology due to human design and the part due to the self-organization activity in terms of 7

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ACCEPTED emergy because it is the self-regulating processes MANUSCRIPT of nature that make ecological self-design with low energy consumption and high sustainability (Odum and Odum, 2003).

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As exergy is the useful energy, and emergy is the embodied useful energy, the corresponding value in information could be the useful information (the knowledge) of the system. Assuming that emergy (Em) is linked to useful work (or available exergy Exa) by transformity (equation 6): = *r ∙ (6) with *r : transformity in sej/J; - : available exergy of the output. Some authors argue that each methodology assumes specific assumptions and paradigms, although both cumulatively account for inputs/outputs of a system to represent its behavior (Amaral et al., 2016). According to Bastianoni (Bastianoni et al., 2007), when each input is converted into solar energy, the transformity is 1 sej/J and only expressed in terms of exergy (1sej=1J) thus, emergy can be reformulated as a function of exergy and therefore its physical and mathematical validity is the same as exergy’s one.

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Assuming that, without pressure variation and when the temperature of the system (T) is equal to the temperature of the environment (To), the lost exergy ( -. in open system at stationary state is linked to the generation of entropy (equation 7): 7 -. = %/ ∙ 01 = 2. = 3/ 46 5 − 46 9: (7) 5 with Sg: entropy generated by the system; 4 :exergy rate ; 4 : exergy rate for a reversible process and * the lifetime of the process. This relation is the Gouy-Stodola theorem (Lucia, 2013).

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Thus, it is possible to link emergy and entropy generation by combining equations 6 and 7: ! -. = − - = %/ ∙ 01 = ∙ ;1 − * = (8) If the information theory is applied (Shannon, 1948), the Boltzmann’s equation for entropy can be used to define entropy S (equation 9) and more specifically Sg for information linked to entropy’s generation considering that the destroyed exergy ( -. corresponds to a lost or a lack of information. 01 = ?@ ∙ AB2 ∙ (

(9)

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With I, representing information in bits (binary units). A bit is equal to the amount of information provided by the selection of a choice between two equal probabilities. Any information can be expressed as a binary choice defining the number of observations (questions, relationships) needed to describe the system. The average amount of information associated with each event is the entropy of the information, H.

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Finally, we can combine equations 8 and 9: -. = %/ ∙ ?@ ∙ AB2 ∙ ( =

!

∙ ;1 − * =

(10)

The Landauer's principle (Landauer, 1990) asserts that there is a minimum possible amount of energy required to erase one bit of information. Thus, there is a correspondence between information in bit and energy (equation 11) (Jaynes, 1957a, b ; Avery, 2012). kB . ln 2= 1 bit = 0.95697x10-23 J/K (11) 23 Therefore 1 J/K = 1.04496x10 bits. If -. or Em is known, it is possible to convert exergy lost into equivalent information (equation 12).

(=

-D

%0 ∙?F ∙AB2

=%

1

∙;1− = *&

0 ∙?F ∙AB2

(12) 8

N

=

P

L ∙)M ∙

N

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P

I L ∙;!O =OI P ∙;!O = *QL *QP

(14)

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∆( =

∆IJK

2.4 data sources and analysis

We collected data on sites from 2006 to 2009 for the UASB-AD plant and from 2012 to 2014 for the CSTR-AD plant. We obtained weather data from measurements with various types of temperature, humidity or radiation sensors or from data collected from the local unit of the French weather forecast agency. The external air and wall temperatures were measured and recorded every 10 min in diverse places defined for each UOP (20 points on average) using data logger (CR1000, Campbell Scientific, France) with thermocouples. The circulating effluent temperatures in each sector were measured and recorded every 10 min using waterproof battery-operated data logger immersed in pipes, tanks and digesters (ELUSB-TC, LASCAR, GB). The data were converted into hourly and daily average values. For the effluents, we recorded the physico-chemical data (COD, pH ...) by standard methods (APHA, 1995). Effluent samples were taken on a weekly or monthly basis. Biogas production was determined using volumetric flow meters originally installed or deducted from COD mass balance. Building data (materials, transport, labor ...) have been collected on the basis of information provided by the different companies involved in the implementation of the facilities. Operating data have been provided by the operators or collected on site over the years of monitoring. Solid inputs were identified by frequent weighing of samples and estimation of the volume.

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And so, from equation 12:

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We will apply equations 8 and 12 to the two systems we studied. Now we can compare different situations to the system considered such as before and after changes generating improvements. Then we can define: Initial baseline (state 0): / = *r/ ∙ -/ Improved situation (state 1): ! = *r! ∙ -! The difference of emergy between the two situations is then defined from equation 6 as: Δ = (13) /− !

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3. RESULTS AND DISCUSSION

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3.1. Emergy diagrams First, emergy diagrams were built for both systems (Figure 2), according to basic rules (Le Corre, 2016). In these diagrams, we have chosen to represent emergy building immobilizations calculated from equation 4 as a tank with an annual emergy flow based on the expected useful life. Thus, we consider emergy due to immobilizations as a local non-renewable resource within the system. advantage is to consider building immobilizations as a unique resource with emergy flow depending only from the expected lifespan. There are two co-products out coming from the anaerobic digester: biogas and digestate. The main differences between the two emergy diagrams concern cogeneration and digestate reused as fertilizers and organic amendment for CSTR-AD plant versus UASB-AD plant. Another difference is the heat reused to maintain internal temperature of the digester close to 35°C for the CSTR-AD Plant.

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Electricity

ACCEPTED MANUSCRIPT Labor A: UASB-AD Plant

Materials, Transport

Reagents

Immobilized

Dairy effluent

$

Anaerobic Digester Microbes

Boiler

Biogas

Effluent + Sludge

Activated Sludge Treatment

Digestate

Market

Heat

Environment

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Sun, Rain

Legend

Materials, Transport

Waste

Labor

B: CSTR-AD Plant

SC

Electricity

$

Immobilized

Anaerobic Digester

Sun, Rain

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Biogas Microbes

9

Environment

3.2. Energy analysis

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Digestate

Figure 2: Emergy system diagrams for UASB-AD plant (A) and CSTR-AD plant (B).

We performed yearly energy balance for both UOPs (Table 2 and Figure 3) based on data collected from 2006 to 2009 for the UASB-AD plant and from 2012 to 2014 for the CSTR-AD plant.

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Spreading

Heat

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Digestate

Co-generation

Market

Table 2: Energy fluxes for both UOP UASB-AD

CSTR-AD 9

x10 J/year

Inlets

2160

5780

Biogas

1270

3318

Outlets (digestate or effluent)

803

2231

Biomass

87

231

10

10

ACCEPTED MANUSCRIPT * 109J/year 3000

2500

UASB CSTR

2000

1000

500

0 heat valorized

1 2

power generation

sludge

effluent

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Figure 3: Energy fluxes for both UOP.

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For the UASB-AD plant and the CSTR-AD plant about 15% of the energy fluxes corresponded to heat losses through flare stack or heat transfer with ambient air. For the CSTR up to 40% of the energy coming from produced biogas and cogeneration were used to heat the digester and for mixing. This autoconsumption is higher than average values observed in France, equal to 15-25%. With the CSTR-AD plant, about 40% of input energy remained in the digestate due to a poor digestibility of agricultural waste used. This was not the case for dairy effluent. Electricity generation represented about 20% of the input energy and 36% of the biogas energy content.

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With the UASB-AD plant, energy analysis showed that mesophilic conditions were not respected during cold periods when ambient air and wastewater temperatures were low with a low biogas production as a result (Figure 4A). Biogas production was lower than 60% of the potential production in cold period (Merlin et al., 2012). With the CSTR-AD plant, energy analysis showed that mesophilic conditions were respected (Figure 4B), but digester heat losses were significant: higher than 10 W/m2 through the digester’s wall and up to more than 100 W/m2 through the roof, in winter. So, heat is primarily lost through the roof, because it is not insulated. Per year, total heat losses have been estimated to about 140 x103 kWh (5.04 x1011 J) and about 33% of biogas produced are consumed to heat the digester.

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heat loss

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1500

These energy analysis show that it is possible to improve anaerobic digestion and efficiency of the process acting on heat supply and insulation for UASB-AD plant and acting on insulation for CSTR-AD plant. For example, a simulation of heat transfer (using EES® software) shows that for non-insulated roof, the internal roof temperature is only 18°C in winter time with an air temperature of -8°C. The consequence is the creation of convection rolls in the headspace between the inner wall and the digestate which accelerates heat losses. When the roof is insulated with 0.15 m of wheat straw (λ= 0.07 W m-1 K-1) and under same external temperature conditions, the temperature of the roof inside is close to 35 °C. This confirms the interest of the roof insulation.

11

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

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ACCEPTED MANUSCRIPT

Figure 4: Example of temperature changes in different parts of UASB-AD plant (A) and CSTR-AD plant (B). 3.3. Emergy analysis

The energy system diagram of an agricultural biogas plants (Figure 2) illustrates emergy flow. The emergy values associated to each resource, were calculated using the emergy specific unit (sej/year) or transformity coefficient from energy quantities (sej/J), mass quantities (sej/g) or monetary values (sej/$). Emergy values are reported in Table 3 for the UASB-AD plant and Table 5 for the CSTR-AD plant. All the products including biogas, residues and power generation are called system yield (Y). Input resource is divided into three main categories: renewable resources (R); non-renewable purchased resources (F); and renewable purchased resources (RF) including human labor. Table 3: Emergy accounting for the UASB-AD plant. 12

ACCEPTED Quantity Unit MANUSCRIPT Transformity Reference

Item

Types

Emergy (x1015sej/y)

(sej/J or sej/g or sej/€) Renewable resources 3.8x1011

J

1

Odum, 1996

R

0.0004

Dairy wastewater

1.26x1012

J

4.83x105*

Zhou et al., 2009

R

608.8

Chemical reaction (anaerobic digestion)

7.5x1010

J

4.06x104*

Tilley et al.,2012

R

3.037

Structure assimilated to fiberglass

3.9x107

g

7.46x109*

Tilley et al.,2012

F

14

Structures and concrete slabs

1.8x108

g

2.3x109*

Tilley et al.,2012

F

50.2

Steel structures

2.8x106

g

5.27x109*

Tilley et al.,2012

F

0.74

Stainless steel

5.0x108

PCV (piping)

3.1x108

Material transport

4.1x109

SC Tilley et al.,2012

F

132.2

g

7.46x109*

Tilley et al.,2012

F

115.7

J

8.4x104*

Tilley et al.,2012

F

0.013

J

6.23x104*

Arbault et al, 2013

F

0.0005

3.5x103

€

3.66x1012

This study

60%RF 40%F

12.84

3.4x103

€

3.66x1012

This study

60%RF 40%F

12.58

7.3x1010

J

8.39x104*

Tilley et al.,2012

F

6.1

Sodium hydroxide

5,3x107

g

2.4x109*

Raugei et al., 2007

F

128.4

Sodium hydroxide transport

9.1x109

J

8.39x104*

Tilley et al.,2012

F

0.966

Biogas

6.3x1011

J

1.68x106

This study

Y

1055

Effluent

0.122x1012

J

4.83x105*

Zhou et al., 2009

Y

59.1

Service technician

EP

Service engineer

Outputs

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Transport

4

5.27x109*

8.0x106

Power consumption

1 2 3

g

TE D

Operation and maintenance

M AN U

Immobilization (building)

RI PT

Sun

Only significant contributions have been reported in this table (> 0.0001% of total emergy). *: The emergy unit values were corrected to be expressed on the adopted baseline. Table 4: Emergy analysis for the UASB-AD plant. 13

ACCEPTED MANUSCRIPT Emergy (x1017sej/year)

RF F F

6.1 1.36

R F

10.55 0.6

Y Y

6

SC

The Table 4 summarizes the emergy accounting for the UASB-AD plant. Sodium hydroxide represents a significant purchased emergy used to maintain pH when mesophilic conditions are not respected and when only hydrolysis and acidification of organic matter occur. Table 5: Emergy accounting for the CSTR-AD plant. Quantity

Unit

Transformity

Emergy (sej)

sej/J or sej/kg or sej/$

15

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Items

Renewable ressources 5.2x109

Sun

J 9

Rain

7.30x10

Manure/slurry

2736x103

Crops residues

0.55x10

12

J

Food residues*

1.60x1012

J

643x10

Immobilizations (building)

Asphalt Steel

1.94x10 176000

(x10 sej/y)

0.0000052

Tilley et al., 2012

R

0.139

Tilley et al., 2012

R

kg

12.32x107*

337

Tilley et al., 2012

R

1.9x10 *

104.5

Tilley et al., 2012

R

2.59x105**

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Gravel

Type

1.90x10 *

kg

5

reference

J

kg

2.79x105

Concrete

4

5

414.4

This study

R

11

1.9x10 *

122.2

This study

R

TOTAL

978.3

EP

Cheese whey

3

1

TE D

1 2 3 4 5

0.25 2.03 2.83

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Immobilized and service Maintenance Power consumption Construction Inlets influent Sodium hydroxide Outlets biogas Effluent + sludge

Type

2.3x1012*

641.7

Tilley et al., 2012

F

12

kg

1.69x10 *

327,9

Tilley et al., 2012

F

kg

6.02x1011*

106

Tilley et al., 2012

F

12

6400

kg

8.86x10 *

56.7

Tilley et al., 2012

F

Plastic piping

265.8

kg

12.53x1012*

3.33

Tilley et al., 2012

F

Waterproofing

26.98

kg

12.53x1012 *

0.338

Tilley et al., 2012

F

PEHD

252

kg

11.25x1011*

0.283

Tilley et al., 2012

F

10

Steel piping

628

kg

12.2x10 *

0.0766

Tilley et al., 2012

F

Polyane

4.4

kg

3.44x1012*

0.0152

Tilley et al., 2012

F

Excavator

15.05x10

6

J

143620*

0.0022

Tilley et al., 2012

F

Bull

17.61x106

J

143620*

0.0025

Tilley et al., 2012

F

6

J

143620*

0.00406

Tilley et al., 2012

F

Mechanical compactor

28.14x10

14

ACCEPTED MANUSCRIPT 143620* 0.000966 Tilley et al., 2012

Truck 6*4

6.72x106

J

Truck 8*4

7.44x10

6

J

143620*

0.00106

Tilley et al., 2012

F

Mobile crane

7.2x106

143620*

0.00103

Tilley et al., 2012

F

Perforator

0.285x10

J

254200*

0.000038

Tilley et al., 2012

F

Vibrator

0.148x106

J

254200*

0.000021

Tilley et al., 2012

F

J

254200*

0.00015

Tilley et al., 2012

F

J

254200*

0.00008

Tilley et al., 2012

F

282.6

This study

60%RF 40%F

6

Air compressor

1.02x10

Mobile saw

0.554x106 77222

$

3.66x10

12

Total

RI PT

J 6

Labor

1419.2

Per year (on 20 years life time)

Operation and maintenance

SC

71

Power cogenerator

25000

$

2.45x1012*

61.3

Power

473.8x109

J

6.23x104*

29.5

Arbault et al, 2013

F

M AN U

Tilley et al., 2012

Oil

30.38x10

J

8.39x10 *

2.55

Tilley et al., 2012

F

Spreading

1.055x109

J

8.39x104*

88.6

Tilley et al., 2012

F

12

Maintenance cogeneration

1544

$

3.38x10 *

5.22

Tilley et al., 2012

F

Maintenance

36944

$

3.38x1012*

125.8

Tilley et al., 2012

RF

3.32x1012

J

3.98x105

1321.4

This study

Y

Power generation

1.21x10

12

J

1.55x10

6

1876

This study

Y

Heat valorized

1.26x1012

TE D

4

F

9

J

6.76x104

85.1

This study

Y

Outputs biogas

*: The emergy unit values were corrected to be expressed on the adopted baseline.

2 3 4

**average value:cf. supplementary data for explanation;

EP

1

Only significant contributions have been reported in this table (> 0.0001% of total emergy).

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F

The total emergy input represents about 11.2x1017 sej/year for UASB-AD plant and 13.3 1017 sej/year for CSTR-AD plant without cogeneration or close to 19x1017 sej/year including cogeneration (Tables 4 and 6). These values are in the same order of magnitude than other biogas systems (Wang et al., 2013).

9

Table 6: Emergy analysis for CSTR-AD plant. Biogas system +Cogeneration system 17 Emergy (x10 sej/year) Immobilized and service Maintenance Power consumption Construction

1.69 1.19 0.74

1.70 1.19 1.36

Type RF F F

Inlets 15

ACCEPTED MANUSCRIPT 9.8

inlets

9.8

R

biogas Electricity

13.2

Y Y

Outlets 18.8

1

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For the CSTR-AD plant construction and services, emergies are higher than for an UASB-AD plant due to power consumption used to mix solid and liquid waste (Table 6) and due to more infrastructures and maintenance for the cogeneration unit. 3.4 Eco-efficiency indices.

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By omparing the transformities we evaluate the total emergy involved in the product formation giving some information about the sustainability of the system. A higher relative transformity requires the input of more emergy to produce the same amount of product. But this is not enough to have a good evaluation of the sustainability. The aggregation of emergy inputs in different categories (R, F, RF, Y) can enable the calculation of eco-efficiency indices (Liu et al., 2013), Renewable Fraction, Emergy Yield Ratio, Environmental Loading Ratio, Emergy Sustainability Index (Table 7). In the long run, only processes with a high renewable fraction (defined as the ratio of renewable emergy to the total emergy used) are sustainable. The Emergy Yield Ratio, defined as the ratio of the emergy yield from a process to the emergy costs, measures how much a process will contribute to the economy and it is used to evaluate the level of dependence. The ratio of nonrenewable and imported emergy used to renewable emergy used (Environmental Loading Ratio) is an indicator of the pressure of a transformation process on the environment. We can consider it as a measure of the ecosystem stress due to a production. The environmental impact is low if the environmental loading ratio is lower than 2 and high if higher than 10. The ratio of the Emergy Yield Ratio to the Environmental Loading Ratio (Emergy Sustainability Index) measures the contribution of a resource or process to the economy per unit of the environmental loading. If the ratio is lower than 1 the process is unsustainable in long term and sustainable if higher than 5.

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Table 7: Emergy ratios and indices for production of biogas.

Fraction renewable

EP

Calculation

UASB

CSTR

CSTR +cogeneration

R/(R+RF+F)

0.6

0.74

0.71

Y/F

2.5

3.85

3.41

Environmental loading ratio

(F+RF)/R

0.67

0.35

0.42

Emergy sustainability index

(Y/F)/((F+RF)/R)

3.76

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Emergy yield ratio

Biogas or electricity transformity (sej/J)

(R+RF+F)/Jproduct

1.68x10

11 6

3.98x10

8.12 5

9.41x105

28

Sej: Solar emjoules = Solar exergy required (directly or indirectly) to make a product.

29 30 31 32 33 34 35 36 37

Emergy analysis through emergy ratios and indices confirms that the eco-efficiency was not optimal for the UASB-AD plant due to low biogas production and high sodium hydroxide consumption (Table 3). For the CSTR-AD plant, emergy indices showed a better eco-efficiency with a biogas transformity close to 4x105 sej/Jbiogas and in the same range as literature values (Zhou et al., 2010; Wang et al., 2013; Chen and Chen, 2014). Taking into account the cogeneration for the CSTR-AD plant due to specific investment, the maintenance and the yield of conversion of heat into electricity, we notice that all the ratios or indices are lower than for a CSTR-AD plant without cogeneration (Table 7). The conversion of biogas into 16

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ACCEPTED MANUSCRIPT electricity resulted in a reduction in the relative sustainability of the system as observed by other studies (Ciotola et al., 2011). This is due to the greater amount of purchased inputs required to build and maintain the generator and the energy lost when the biogas is converted into electricity (30-35% according classical efficiency of a stroke engine). The benefit of transforming the biogas into electricity is the production of a higher transformity and a higher quality energy source, as electricity is more useful than biogas from a human perspective (Ciotola et al., 2011). Moreover, this kind of valorisation is compulsory in a French regulation context : electricty first, then possibly, heat. Concerning electricity production from biogas, emergy analysis of wastewater treatment plant in a town with about 9,500 inhabitants in the southern part of Sweden gave interesting information. The resource requirements from the economy in the production of electricity by the digestion of sewage sludge was about two times the total resource used for the generation of an average mix of electricity used in the town (Bjorklund et al., 2001). In this case, it would be more resourceefficient to purchase the electricity on the Swedish distribution net because the part of renewable sourced electricity in Sweden is 52%. In France, the part of renewable electric energy is only 19.5%.

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The renewable fraction of resource is very high for both systems (Table 7) and specifically for the CSTR-AD plant. Values are in the same order as those determined in other studies (Wei et al., 2009; Zhou et al., 2010; Wang et al., 2013). This is because all organic inputs (manure, food residues…) have been classified as a renewable resource. Even if the separation of these inputs into renewable and purchased resources seems more accurate (Ciotola et al., 2011), this separation was not made in our study where the boundary defined is the UOP and its proximal environment. Emergy yield ratio shows that the systems have low dependency even for a system with cogeneration because energy transformation is essentially due to living organisms without intensive technology. Only mesophilic and anaerobic conditions have to be maintained to produce biogas but the infrastructure has to be designed for this purpose. Environmental loading ratio is very low because these AD plants are not intensive processes. The emergy sustainability indices are high (>3) measuring a long-term sustainability in terms of emergy. For the CSTR-AD plant, a biogas transformity close to 4x105 solar emjoule per joule of biogas, can be calculated and is in the same range as literature values (Ciotola et al., 2011; Zhou et al., 2013). For the UASB-AD plant, if mesophilic conditions are respected with biogas production close to 300 cubic meters of biogas per day, the transformity will reach the expected value.

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UASB-AD plant: The balance is carried out on the assumption of an ideal system: no consumption of soda and maximum production of biogas. For this, a portion of the gas consumed is used to heat the effluent up to the ideal temperature of 35°C. The evolution of the indices demonstrates the environmental benefits of the proposed improvements (Table 8). Indeed, the contribution of renewable emergy changes from 60 to 68%, which shows a lower use of non-renewable energy. In addition, the installation becomes emergetically more efficient, as the emergy yield ratio increases from 2.5 to 3.13. The environmental loading ratio and the emergy yield ratio both consider the ratio of energy purchased on renewable emergies. The fact that they are in any case less than 1 shows the importance of renewable resources in this type of process. The decrease of these indices from 0.67 to 0.47 shows a lower dependency on non-renewable resources in the second case. Finally, an emergy sustainability index of 6.65 indicates a long-term sustainability of the process. 17

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ACCEPTED MANUSCRIPT CSTR-AD plant: Emergy analysis simulation is made taking into account insulation for the roof and pipes of the digester. Biogas production is the same but there is less electricity used to heat the digester. Table 8: Emergy ratios and indices for production of biogas simulated after improvement. Calculation

UASB

CSTR

CSTR +cogeneration

R/(R+N+F)

0.68

Emergy yield ratio

Y/F

3.13

Environmental loading ratio

(F+N)/R

0.47

Emergy sustainability index

(Y/F)/((F+N)/R)

6.65

4.08

3.57

0.32

0.39

12.75

5

4.58 x10

9.15

5

3.90 x10

7.55 x105

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Insulating the roof helps to produce more electricity with cogeneration because 15% of biogas is no longer needed to maintain the temperature of the digester, which results in an improvement of the different indices (Table 8). 3.5 Entropy generation, information and emergy in UOP-AD systems:

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Even if emergy is an estimation of embedded exergy this cannot be measured directly and with more or less uncertainties (Ingwersen, 2010), this method is an attractive tool to perform sustainability evaluation of all sorts of systems (Amaral et al., 2016) such as for AD plants in this present study. The results confirm that emergy analysis can be used for the improvement of actions regarding environmental sustainability issues such as material and energy efficiency that may be critical for specific types of industries (Angelakoglou and Gaidajis, 2015). It remains that emergy analysis is not scientifically and technically sufficiently consolidated, particularly concerning relationship between exergy, emergy and information on thermodynamic basis. Applying equation 8, Sg was around 3.4 1021 J/K for the UASB-AD plant and around 8.8 1019 J/K for the CSTR-AD plant including cogeneration. These values are very high, illustrating that the higher the transformity of a product is, the lower is its efficiency to convert direct and indirect solar energy into final output. Applying equation 8 for the UASB-AD plant improvement simulation, the value of Sg decreases to 8.58 1019 J/K ie 40 times lower than initial value.

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(R+N+F)/biogas

0.72

SC

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0.75

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Fraction renewable

Applying equation 14 to compare “before” and “after” improvement for UASB-AD, the equivalent information not lost by the system (∆( is equal to 1.1 x1038 bits and around 2.51 x1037 bits for CSTRAD. This information (∆I) in bits expressed from determinate emergy values could be the self-design expressed in “equivalent bits”. In this case, it is a useful information because this information represents the “needed information” for process maintenance and building (organization, structure). This emergy analysis provides the interest to evaluate the time evolution of complex systems and measures their sustainability through a thermodynamic approach by comparing various situations, such as initial and final situation. Useful information is fundamentally a product of the self-organization of a system (Odum, 1996). The question is how to create this required information in order to improve efficiency and sustainability for the system. As self-organization is argued to be a fundamental phenomenon of nature, we can reasonably think that a bio-inspired process including the principle of evolution according to the laws of thermodynamics and particularly the principle of maximum empower would be more sustainable. We can consider that this equivalent information is a cultural information. This cultural information leads to 18

42 43 44 45 46 47 48 49 50 51 52 53

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a cultural evolution of engineering, ACCEPTED guided by the MANUSCRIPT need for sustainability. For instance, one difficulty is to determine the value of the transformity between solar emergy joule and information and more specifically cultural information. It is argued that culture is shared in a hierarchy of distinct ‘scales’ of information production (including memory, conversation, media, ritual, education, research, and legal codes). These scales differ in a number of critical dimensions, such as how quickly they degrade, how widely they are shared, how much work is required for their construction, energy and material inputs, feedback impact, fidelity of intermediate carriers, and in the number of production events (Abel, 2013). For example, the value has been evaluated to 1.12 x108 sej/J for external information or 3.4 sej x1015/page of publication (Meillaud et al., 2005) or 1.6 x1018 sej/J to develop a new conversation cultural variant (Abel, 2013). There still exists a lack of theoretical relations establishing the principle of quality for information related to the energy required.

4. CONCLUSION

ACKNOWLEDGMENTS

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Energy analysis, especially heat balance, shows that these small biogas production plants were not working at expected efficiency and that design errors were responsible of this situation. These results are indicative of major problems noted in this sector as in France for instance. The various indices calculated from emergy analysis nevertheless show the sustainability of such systems. Therefore, with proper design of the plant, a good implementation of the new design and an appropriate operating procedure for the digester, the performances for the biogas plants could be improved. Simulations of emergetic analysis taking into account the required improvements show their appropriateness. Particularly, digester operation and maintenance should be modified and the digestate used as organic fertilizer in order to improve the eco-efficiency of this type of energy conversion system. Irrespective of the delicacy and complexity of computing emergy transformity, the method shows to be a very good accounting tool for the evaluation of the evolution of complex systems and the measurement of sustainability. Particularly, the emergy analysis provides the interest to evaluate the evolution in time of complex systems and measures their sustainability through a thermodynamic approach by comparing various situations, such as initial and final situation. The use of original equations linking emergy and information developed in this study can contribute to evaluate the self-organization needed to improve sustainability of UOPs in terms of energy. This has to be checked, applying this method to more cases and diverse types of UOP in future works.

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We gratefully acknowledge discussions with, and manuscript edits from, Dr Julien Ramousse and Dr Thierry Lissolo. APPENDIX A. SUPPLEMENTARY DATA

Supplementary data for emergy calculations, associated with this article can be found, in the online version.

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ACCEPTED Landauer, R., 1990. in Maxwell’s Demon: Entropy,MANUSCRIPT Information, Computing (Princeton University Press, Princeton, NJ. Le Corre, O., Truffet, L. 2012. Exact computation of emergy based on a mathematical reinterpretation of the rules of emergy algebra. Ecol. Model., 230, 101-113. Le Corre, O, 2016. Emergie, approche holistique pour l’éco-conception. ISTE editions Ltd, London, UK. Lesne A., 2014. Statistical entropy: at the crossroads between probability, information theory, dynamical systems and statistical physics. Mathematical Structures in Computer Science 24, e240311. Liao, W., Reinout H., Gjalt H., 2013. Thermodynamic analysis of human-environment systems: A review focused on industrial ecology. Ecol. Model., 228, 76-88. Liu, G., Yang, Z. Chen, B. Zhang, L., 2013. Modelling a thermodynamic-based comparative framework for urban sustainability: Incorporating economic and ecological losses into emergy analysis. Ecol. Model., 252, 280–287. Lucia U., 2013. Stationary open systems: A brief review on contemporary theories on irreversibility. Physica A, 392, 1051-1062. Meillaud F., Gay J.B., Brown M.T., 2005. Evaluation of a building using the emergy method. Solar Energy, 79, 204.212. Merlin, G., Lissolo, T., 2010. Energy and emergy analysis to evaluate sustainability of small wastewater treatment plants: application to a reed bed and a sequencing batch reactor. J. Water Resource and Protection, 2, 997-1009. Merlin, G., Kohler, F., Bouvier, M. Lissolo, T., Boileau, H., 2012. Importance of heat transfer in an anaerobic digestion plant in a continental climate context. Bioresource Technol., 124, 59-67. Odum, HT., 1988. Self-organization, transformity, and information. Science, 242, 1132-1139. Odum, H.T., 1996. Environmental Accounting, Emergy and Decision Making. John Wiley, NY. Odum H.T., 2000. Handbook of emergy evaluation: A compedium of data for emergy computation issued in a series of folios. Folio # 2 - emergy of global processes. Center for environmental policy, environmental engineering sciences, University of Florida, Gainesville, Floride, 28pp. Available in: http://www.cep.ees.ufl.edu/emergy/publications/folios.shtml Odum, H.T., Odum, B., 2003. Concepts and methods of ecological engineering. Ecol. Eng., 20, 339–36. Raugei, M., Bargigli, S., Ulgiati, S., 2007. Life cycle assessment and energy pay-back time of advanced photovoltaic modules: CdTe and CIS compared to poly-Si., Energy, 32, 1310-1318. Shannon E.C., 1948. A Mathematical Theory of Communication. Bell System Tech. Journal, 27, pp. 379-423 and 623-656. Serizawa, H.; Amemiya, T.; Itoh, K., 2014. Tree network formation in Poisson equation models and the implications for the maximum entropy production principle. Nat. Sci., 6, 514. 
 Skene K.R. 2015. Life’s a gas: A thermodynamic theory of biological evolution. Entropy, 17, 55225548. Tilley, D.R., Agostinho, F., Campbell, E., Ingwersen, W., Lomas, P., Winfrey, B., Zucaro, A., Zhang. P., 2012. The ISAER transformity database. International Society for Advancement of Emergy Research. Available at www.emergydatabase.org. WBCSD, World Business Council for Sustainable Development., 2000. Eco-efficiency: Creating more value with less impact. From http://www.wbcsd.org/web/publications/eco_efficiency_creating_more_value.pdf. Wang, Y., Lin, C., Li, J., Duan, N., Li, X., Fu, Y., 2013. Emergy Analysis of Biogas Systems Based on Different Raw Materials. The Scientific World Journal, 415812. http://doi.org/10.1155/2013/415812. Wei, X.M., Chen, B., Qu, Y.H., Lin, C., Chen, G.Q., 2009. Emergy analysis of ‘four in one’ peach production system in Beijing. Commun. Nonlinear Sci. Numer. Simulat. 14, 946–958. Wu, X., Wu, F., Tong, X., Wu, J., Sun, L., Peng, X., 2015. Emergy and greenhouse gas assessment of a sustainable, integrated agricultural model (SIAM) for plant, animal and biogas production: Analysis of the ecological recycle of wastes. Resources, Conservation and Recycling, 96, 40–50. Xue, X., Schoen, M. E., Hawkins, T. R., Ashbolt, J. C., Garland, J., 2015. Critical insights for a sustainability framework to address integrated community water services: Technical metrics and approaches. Wat. Res., 77, 155-169.

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ACCEPTED MANUSCRIPT Yen, J. D. L., Paganin, D.M., Thomson, J.R. Mac Nally, R., 2014. Thermodynamic extremization principles and their relevance to ecology. Austral Ecology, 39, 619–632. Yi, H. Srinivasan R.S., Braham W.W., 2015. An integrated energy emergy approach to building form optimization: Use of EnergyPlus, emergy analysis and Taguchi-regression method. Building and Environment, 84, 89-104. Zhou, S.Y., Zhang, B., Cai, Z.F., 2010. Emergy analysis of a farm biogas project in China : a biophysical perspective of agricultural ecological engineering. Commun Nonlinear Numer. Simulat., 1408-141.

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Figure 3: Energy fluxes for both UOP.

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Figure 4: Example of temperature changes in different parts of UASB-AD plant (A) and CSTR-AD plant (B).

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Figure 2: Emergy system diagrams for UASB-AD plant(A) and CSTR-AD plant (B).

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ACCEPTED MANUSCRIPT Figure 1: Technical flow charts of biogas AD plants. A: UASB-AD plant; B: CSTR-AD plant. Numbers represent the different sectors and devices of the wastewater treatment plant in which the heat transfer was modeled.

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ACCEPTED MANUSCRIPT Energy and emergy analyzes of farm biogas plant are indicative of problems noted in this sector. Simulations taking into account the required improvements show their appropriateness. Emergy analysis provides the interest to evaluate the evolution in time of complex systems.

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Entropy generation decreases after improving efficiency and sustainability.