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Renewable biogas from anaerobic digestion of biomass: influence factors in life cycle assessment

Based on the current generation rate of 1 kg−1 person−1, the production of organic waste in Malaysia is estimated to reach 9 metric tons per year by the year 2020. Components of these wastes, however, can be used to generate biogas, not only to decrease waste-related issues, but also to produce renewable energy. There is a growing interest in resource recovery and waste/energy integration through biogas generation from organic waste through anaerobic digestion method. However, due to the anaerobic digestion process varies in different facilities, thus proactive assessment on the status of biogas production and its effect on the environment through life cycle assessment is vital. The objective of this review is to assess factors that affect environmental performance results such as the system boundaries setting, the databases used and the life cycle impact assessment methods applied. This review underscores the fact that goal definition and scope, functional units, system boundaries setting, characterization and life cycle impact assessment methodology, as well as types of software and databases used influence and affects the life cycle assessment results. It suggests that for future cross study comparisons, all assessment guidelines should be addressed to avoid biased comparisons on climate performance between different alternatives.


Introduction
Biomass is classified as a renewable source that comprises of water and carbon dioxide, utilizing daylight as a source of energy. This contains food, harvested crop, trees, farm and forestry residues, aquatic plants, animal and municipal waste [1,2]. The environmental benefits of using biomass are derived from its cycle of life. Output source on biomass could, in theory, biodegrade into carbon dioxide and water toward their finish cycle, preferably generating no "additional" carbon dioxide. Renewable biomass feed stocks are grains, oils, fats, proteins, and lignin's from a chemical perspective [3].
Food waste (FW) is a source of biomass. It is the largest element of municipal solid waste (MSW) that comprises restaurants and canteen waste, households, as well as food processing plants. These large generations of FW brings about a wide range of environmental and sanitary problems, and this should not be ignored. It is expected that by 2025, FW volume in Asian countries will increase to 4.16 billion tons compared to the current 2.78 billion tons [4]. Every year, as stated by Xiao et al. [5], the foods  3 In correlation with different biofuels, biogas is progressively adaptable, since it tends to be created from hydrocarbons, proteins, and fats, including wet and secondary materials [14,15]. Generally, biogas is generated from FW, sewage sludge and manure, but the biogas production method and arrangement is differed between regions, with various feedstocks, production, and use [16]. Thailand, Indonesia, Brazil, China, the United States of America and European countries for instance, deployed their accessible local timber and biomass resources to substitute coal and oil [17]. In Malaysia, biomass energy sources are acquired from timber waste and several cultivations i.e. palm oil, rubber, coconut, sugarcane, cocoa, rice paddy, animal waste and urban waste [18]. However, the biggest biomass energy is contributed by the palm oil industry due to its enormous plantation in Malaysia. Bruijstens et al. [19] stated that FW has higher methane content, which can reach nearly 85% compared to other wastes. A study conducted by Naesko Environment's Association [20], has shown percentage variation on the biogas yielded based on four types of waste. Compared to household waste (50-60%), all other wastes have a higher methane percentage (food waste 68%; agricultural waste 60-75%; wastewater treatment sludge 60-75%).
AD has numerous processes involving methanogenic archaea and bacterial actions. To assist the degradation of organic matter, four stages would be involved sequentially such as hydrolysis, acidogenesis, acetogenisis, and methanogenisis. During the treatment, macromolecular organic component is degraded into liquefy monomers which then to tinier molecules of short group fatty acid, pyruvic acid, amino acid, acetic acid and others. These eventually ingested into hydrogen and acetic acids and converted by methanogenic archaea into methane [4]. FW is highly considered suitable for AD bio methane potentiality approximated at range 200 to 670ml CH4/g added Volatile Solids (VS).
During the AD process, organic waste might be altered into burnable biogas (principally methane, as well as gases variation, such as, hydrogen sulphide and hydrogen [5]. Parameters, for instance, volatile solids reduction and methane yield or so were employed to evaluate investigation efficiency. In the procedure to improve the quality of methane production, various aspects of AD are investigated such as additional supplementation, functional alternations, optimization of parameters and microbial behaviour. Besides biogas, the anaerobic digestion process transfers secondary products-bio fertilizer also known as digestate. As a large share of the source of nourishment content of the feedstock ends up in digestate, it can be used as bio compost contributing to improved soil nutrient management [21,22]. However, as biomass transformation to bioenergy increases ecological issues, the subject on ecological sustainability assessment of bioenergy pathways has been extensively conducted. Consequently, a life cycle assessment (LCA) as a comprehensive method is used to determine and guarantee the environmental sustainability of the biogas. LCA is a holistic approach for surveying a system's environmental burdens by characterizing the fuel, materials utilized, and contamination discharged into the ecological system. As stated by Aziz et al. [23], particularly in Malaysia's biogas production there are less LCA studies have been conducted. This study aims to assess the biogas generation from biomass towards environmental impacts through LCA. This review highlights the influence factors that affect the life cycle assessment results, for example, goal determination and scope, functional units, boundary systems setting, characterization, assessment methodology on life cycle impact, impacts categories, finally the selection of software and databases.

LCA for biogas generation from anaerobic digestion of biomass
There is expanding attention in the assessment of the ecological impacts of biogas as a cleaner and more sustainable power source utilising approach of LCA. This reviewed paper discussed the investigations on LCA biogas generation from several countries with various characteristic points of view. The studies depended on the described LCA approach that stated in ISO 14040 and 14044. The consideration of the exhaustion of non-renewable energy source and the ecological issue, for instance, an a worldwide temperature alteration identified with ozone harming substance releases has incited an extension in examining at organic wastes biogas creation for a more feasible energy production.
Biogas processing from biomass products is highly cost saving for the creation of sustainable energy. This is because the abundance of ready feedstocks such as MSW, wastewater discharges, horticultural  4 and animal waste can be exploited to generate energy. Reusing of natural wastes is likewise a better and more practical ecological expenditure that be able profit residents and the environment simultaneously. However, effect of feedstocks to lower ecological burden need to be defined; for example the use of straw, corn silage, or co generation between energy crop-agricultural residues with MSW food residue feedstock mixture [24]. Table 2 indicates 20 of the studies evaluated, 13 of which involved European countries such as Luxembourg, Germany, Italy, the United Kingdom, Switzerland, and Sweden. One study was from the African nation, Ethiopia and the other six were conducted in Asian nations (three in China, and one each in Vietnam, Singapore, Indonesia). Recently, the LCA research on biogas production has increases especially in Asian and North America regions. The developing concern for ecological assessment related to the generation and application of biogas utilizing LCA was to evaluate the environmental performance and the sustainability of the energy pathways [25]. Table 2 shows the summarized of 20 LCA biogas studies with different study context, the methodology used, and feedstock type, use of biogas and bio fertilizer, and the categories of environmental impacts. Referring to Table 2, the studies on life cycle assessment for AD plants in this review could have conducted out quite differently. Researchers found a number of importance influences in the way biogas by AD plants conducted. For example, the life cycle impact assessment method applied still play an important role in affecting the LCA results. The LCA results can be obtained much better, but there is stillroom for improvement especially complex systems that include assumptions and plenty of records. Many LCA results can be improved with appropriate system boundaries setting, the used of measurable functional unit (FU) as well as the robust databases selected. Difficulties can arise when there is more than one crucial element to be perceived. Thus, it is important to identify which elements have a larger influence on some of the other viable elements; and these may be described qualitatively. The following section addresses components and aspects such as goal definition and scopes, functional unit, system boundaries, use of biogas, use of bio fertilizers and categories of impacts that have been covered in the reviewed studies. As the LCA usage is likely to increase in the future, relevant LCA establishments were needed with the detailed guidelines provided. This is important for future potentiality on cross study comparisons and increasing the general quality in assessment.

Defining the Goal and scope of reviewed studies
The conducted LCA study is intended for its certain utility, the target audiences or for info dissemination. The utmost intention of using LCA on the biogas from AD is to assess on the environmental existence cycle effects of managing organic waste as they are achieved in those cases. In this segment, the plans of the LCA researches need to be described as clearly as possible. The classified scopes were ecological performance, ecological and economic performance, ecological and energy performance as well as resource efficiency. Fiez et al. [22] has assessed on environmental performance of FW biogas digesters that has carried out in Xiaoguwei Island, Guangzhou, China. The study was comparing the impacts on environmental of different waste treatment such as FW to biogas production (with upgrading to fuel, and with electricity production), incineration, landfill, and pig farms. The results indicated that the FW to biogas plant provides about 0.3MNm 3 bio methane and a reduction of greenhouse gas emissions of about 1780 tons of CO2-eq each year.  [44] a multi-criteria method applied to evaluate the right quality of biogas feedstocks and the production of bio fertilizer was assessed. The study examined aspects of efficient costing, feasible technology, energy and ecological performance, accessibility, policy, competition and other relevant issues. The importance of the finding is to structure information relevancy for facilitating strategic overviews, informed decision making and communicating its result.

Functional units
FU has to be defined as the type of function or service the products' system delivers. The FU reason is to have a reference to which the inputs and outputs are related. The FU is essential to enable the similar cross study comparability between the LCA studies. Therefore, the FU itself needs to be measurable. Gradually, the options of the FU in biogas structures refer on power, distance, mass, volume or a hectare for land used. As shown in Table 2 the LCA studies of biogas manufacturing were having variation FU, for examples; ton [22,24,[27][28]31,34,[41][42][43], kg [30,35,36], Mg [32], m 3 , MJ [26,33,39], kWh [37][38], MWh [40], ha and km.

Boundaries Setting
According to Fiez et al. [22] the effects of environmental and energy assessment are very dependent on the choice of system boundaries, assumptions and include effect categories. The boundaries setting indicate the system or process as well as the inputs and outputs of the system that to be included under the consideration for LCA evaluation purposes. There are 13 studies from total 20 reviewed LCA-studies took into consideration the system boundaries from cradle-to-gate [22,[26][27][28][29][30][31][32][34][35][38][39]40], 3 studies from cradle to grave [36][37]42], 3 studies from gate to gate [33,41,43], and a biogas production and usage respectively [24]. The cradle-to-gate method consists of the complement of feedstock until the biogas production, and in a certain case focused effectively on unique stages within the system boundaries. In the general system, as illustrated in Figure 1, the dotted traces are the flows of energy and the solid traces are the flows of material. Definition system in Figure 1 is inclusion of feedstocks transportation, different processes waste, and the bio fertilizer product. In an extra correct system, biofertilizer products must also be covered in addition to the transportation of these flows and in a few cases, the fuel that is produced. Dependent on the substrate and/or the intended first-class of the products the need for different processes will vary. Five principal processes, AE, have been defined: -A: sorting-B: pre-treatment-C: anaerobic digestion-D: bio residual treatment -E: biogas usage and upgrading.
Bernstad et al. [45] discussed how variation in process parameters and boundary setting may influence the result of the LCA and made suggestions to improve interior equivalence within treatment options in a comparable LCA as well as among various LCAs. For example as reported by Chen [12] AD requires huge energy consumption (diesel provision) using larger trucks due to the process of collection, transporting collection to the waste treatment facility (electricity provision) and labourers' cost. The journey from the collection sites or small transfer station will release emission to air. Emission to air in AD process especially in collecting and transporting even in low concentration is considered as environmental burden.

Characterization method and life cycle impact assessment
Life cycle impact assessments (LCIA) transform the life cycle inventory (LCI) results in a limited number of indicator scores, which are useful in defining the scores of indicators that show relative magnitude of impacts on the environment. As stated in Table 3, the LCA practitioners in biogas plants might have conducted the LCIA in a different way. The selection of the LCIA approach used can have a major impact on the outcome; however, no clear information or recommendations are available for general users to choose reasonable LCIA methods. Therefore, there is a need to understand each LCIA method or combination of methods used for purposes of comparisons. Furthermore, the findings can be used to elaborate the literature in future studies. These could be very useful when it is used in biogas plants with similar features. In addition, this analysis may also be part of future research on comparing biogas plants with other organic fractions treatments of AD from LCA perspectives.
The LCIA method is consists of two elements, midpoint and endpoint. Midpoint has lower uncertainties because the impacts that can be modelled are considered. Midpoint impact assessment has indicators that concentrate on a single environmental issue e.g. climate change or acidification. This will give a more concise overview of the system's impacts on the environment. The environmental impact results obtained using different LCIA midpoint approaches are identical for comparable categories. Moreover, the LCIA techniques such as ReCiPe, EDIP and Impact 2002+ offer greater assessment and comparative categories than CML and TRACI (as shown in Table 3) [46].
With respect to the definitions of global warming (called "Global Warming" in CML, TRACI, EDIP, and Impact 2002+ and "Climate Change" in ReCiPe Midpoint), expressed as kilograms of carbon dioxide equivalent (kg CO2 eq); it can be noted that there is almost the same relative result because the same reference was derived from the IPCC. Referring to Table 3, the midpoint studies using CML approaches conducted by Grosso [28][29][32][33]40], the results showed the best indication related to the potential for global warming reduction and improvement. Another type of environmental impact that can be correlated with different methods is the degradation of the ozone layer (called "Ozone Depletion" in ReciPe, TRACI and EDIP and "Ozone Layer Depletion" in CML and Impact 2002+, expressed as kilograms of chlorofluorocarbons equivalent (kg CFC-11 eq). Such quantitative analysis is not feasible for impacts such as eutrophication and toxicity that have different indicators of specific ecological compartments depending on the method selection. For acidifications, the findings are not convergent due to differences in spatially similar characterization variables and different models characteristics adopted according to each approach. An example of the differences in CML (acidification, as kg SO2 eq), in ReCiPe (terrestrial acidification, as kg SO2eq), EDIP (acidification as square meter) in TRACI (acidification as H + moles eq) and in Impact  [24,26,28]. Meanwhile, the GEMIS (Global Emissions Model for Integrated Systems) calculations have established the standard for contemporary assessments of the life cycle. GEMIS is a free lifecycle and material flow analysis tool for the public domain, which also provides a comprehensive database on energy carriers, materials energy, and material processes. Midpoint have robust model and data, which is recognized as a problem oriented LCIA method. It may lead to reliable interpretation and open possibilities for comparisons between different studies. However midpoint can also be harder to interpret because it has too many abstract meanings e.g. radiative forcing -acidification. Besides, such features are not the only environmental effects of the emissions listed on LCI, but there are measures of the potential impact. Therefore, endpoint as damage oriented LCIA method is an alternative for simplification on the LCIA interpretation. For instance endpoint (e.g. ReCiPe 3 points and Eco Indicator 99) were indicators that showed the impact of the environment on three higher aggregations level on the effect on human health, biodiversity, and finally resource scarcity [24,26,27].
With regard to the single score, the relative contribution of the respiratory categories in organics in IMPACT 2002+ and Eco-Indicator 99 (H) methods and particulate matter formation in the ReCiPe endpoint (H) method can be compared [26,24,31]. Both categories are related to emissions of particulate, sulphur oxides, ammonia, and nitrogen oxides with some little differences in characterization steps and all of them are expressed in Disability Adjusted Life Years (DALY), at endpoint level. Another comparison can be made between the relative weight of land use in Eco indicator 99 (H) and Impact 2002+ methods [26,27]. The Ecological Scarcity method presents no specific environmental impact category related to land [27]. The categories of Energy Resources in Ecological Scarcity, Fossil Fuels in Eco Indicator 99 (H) and Non-renewable energy in Impact 2002+ generally showed similar results, as exemplified by a comparison study conducted by Jury et al. and Stucki et al. [26,27]. Poeschl et al. [24] indicated that single scores using ReCiPe methods could show the most significant outcomes when comparing variation on technologies of small scale and large-scale biogas plant, and identifying the 'hot spot' potential where it is possible to achieve further reduction of environmental impacts. The outcome indicates preference for small plants. Tri-generation would be the most promising path for sustainable biogas use; compared to the generation of electricity only. Tri-generation combined  11 heat and power (CHP) could be reduced the overall impact on the environment by almost 200%. Cavalett et al. [46] extended the debate whether and to what degree the efficiency of the system is influenced by using of the various Life Cycle Impact Assessment (LCIA) presented throughout the research study of the Brazilian environmental impact analysis of bio refinery. The assessment considered the following LCIA methods: CML 2001, Impact 2002+, EDIP 2003, Eco-indicator 99, TRACI 2, ReCiPe, and Ecological Scarcity 2006. Although there is a consensus on the outcomes of similar categories of environmental impact using different midpoint LCIA measures, when considering singlescore metrics, the use of various techniques of LCIA could results in different interpretations. However, ReCiPe was indicated as the best endpoint method to evaluate environmental impact as shown in the summarized framework in Figure 2.

Life cycle assessment (LCA ReCiPe) Life cycle inventory (LCI)
Life cycle impact assessment (LCIA) Product processes

Impact categories
Some research that focused mainly on greenhouse gases and energy balance assessed greenhouse gas emissions, potential for global warming (GWP), and greenhouse gas mitigation potential (GMP), Cumulative energy demand (CED), cumulative exergy demand (CExD), net energy gain (NEG) and primary energy demand (PED). In several studies, these metrics were calculated to assess the energy efficiency of biogas production. Based on Bosch et al. [47], CED and CExD offered a reliable energy efficiency evaluation of the production of biogas system compared to the method of natural gas. Many biogas production studies have shown that biogas-generated energy contributes to greenhouse emissions reductions compared to fossil fuel [26, 48, and 49].
Bacenetti et al. [50] explained that the using of cogenerated heat effectively and reduce methane emissions at the side of strength self-consumption have been the primary factors to enhance the results of the CED and GHG emissions. In the LCA conducted by Seldal et al. [42], the GWP had the point of interest. It was observed that biogas plant from the AD value chain had an overall impact on GWP of 455kg CO2-eq/FU. By the defined processes, the household waste collection had the greatest effect. When adopting the value chain compared to using alternative options such as chemical fertilizer and diesel, a burden of 747 396 kg CO2-eq can be averted.
AD treatment releases emissions that direct from the digestive process or indirect from transient emissions of valve malfunction or transitory and this concept has developed by Gentil et al. [51] occurs during the upstream-operation-downstream, which all relevant processes were accounted for. Besides, the produced biogas is necessary to be enhanced, compressed/liquefied and transferred. The fugitive emissions from anaerobic digestion plants may emit CH4 during treatment and upgrading which may largely affect the general Global Warming Potential (GWP) from the treatment chain. Such discharges change between different technologies and, as stated by Eggleston et al. [52], range from 0 to 10 vol. percent of the biogas generated, but close to 0 percent in plants with unexpected discharges. According to Börjesson and Berglund [53] and Møller et al. [54], both studies noted that the outlawed discharge of methane is a key parameter in connection with Greenhouse Gas (GHG)-outflows from AD systems (in both cases allowing discharges equal to 0-3 vol. percent of methane delivered). While others [55 -58] do not consider these discharges at all in their assessments, Bjarnadottir et al. [59] and Ia Cour Jansen et al. [60] consider fugitive methane discharges compulsory.
In the meantime, Lantz et al. [61] and Pertl et al. [62] indicate that during the technology upgrade decision and the consequent fear of CH4-outflows, the total treatment chain GWP may be significantly affected. As stated in the IPCC rules, the ignition of recovered biogas is minimum in connection to a worldwide temperature alteration since CO2 emissions are of biogenic starting point (and along these lines GWP neutral) and the outflows of CH4 and N2O are insignificant (IPCC, 2006), whereas Ia Cour Jansen et al. [60] states that biogas discharges is necessary be considered. Biogas outflows from ignition rely upon the kind of gas engine, and lean-burn gas engines, commonly utilized at AD plants, often produce higher CH4 in contrast with different gas engines [63]. While the use of LCA is likely to increase in this area in the near future, it is rather important to develop up more standards that are comprehensive in order to improve the overall consistency of assessments as well as the possibility of cross-study comparisons.

Software's/databases
Software is also one of the influencing factors in the LCA results. The AD system may look simple at one glance, of reality; however, any technology must be carefully modelled. The version of the waste management program requires a substantial amount of information that includes characteristics of waste, system of collection, different choices for treatment, background structures, and so forth. Such changes were introduced for future trends update, offering future portions of waste, fuel expenses, electricity mixes, and lots of others. Since used software varies for example SimaPro, Gabi, ORWARE, EaseTech etc. the most important of software selection is its databases. GaBi for instance has more than 20,000 accessible databases and this will provide very good visualization to represent assessment results compared to other software which only used common database provider i.e. Eco Invent (13,300 databases) [64]. There is an extensive division among popular LCA applications as with SimaPro, GaBi, Team, Umberto and the programs specifically designed for use in a particular area. In waste treatment schemes, for example: ORWARE (organic waste research), IWM-2 (integrated waste management II), WISARD (waste -integrated systems for assessment of recovery and disposal), WRATE (waste resources assessment tool for the environment), and EASEWASTE (environmental assessment of solid waste systems and technologies). GEMIS (Global Emissions Model for Integrated Systems) is a free lifecycle and material flow analysis tool for the public domain, which also provides a comprehensive database on energy carriers, resources, energy and material processes. Such software will be used to assess the present and further to version-new waste management systems. Figure 3 showed the databases used for LCA reviewed studies in biogas plant by AD. Kulczycka et al. [65] stated that differences among the research in the assessment are associated to technical assumptions with input data, form of technology, used inventories and data production. It is also determined that the models are subject to special assumptions are especially associated with various times after the information system has been developed (e.g. assumptions for the time horizons for landfill emissions). Further optimization of these tools to geographical situations will have an extra impact on the consequences. Nevertheless, each of the LCA programs can display a few benefits and downsides if assessed strictly from the waste management perspectives. The common LCA programs frequently encompass complete databases; however, they are now not continually specific for the waste treatment systems and suitable for national/regional situations [65].
Nonetheless, compared to a standard LCA model, the concept of ORWARE is designed to capture the waste characteristics control applying an SFA method and additionally include estimates of the economy. The use of a version unlike ORWARE, the concept of the district heating system has been popular and is in addition defined by Eriksson et al. [29], ORWARE is to an excessive volume feasible to adapt to the system studied precisely. ORWARE is beneficial due to (1) its potential to each treatment of environmental and biological wastes efficiently and (2) the potential of the new model procedures.

Recommendations
It is recommended that the modelling performed on to biogas plants from AD treatment be improved to give better results such as by defining a system with more processes to produce more equal results, thus more processes and more reliable inputs and outputs are needed to be included. So, the result with much lesser uncertainty will be generated by a system. Secondly, is by comparison of the value chain with relevant literature studies. It is strongly suggested to LCA practitioners to perform both a Material Flow Analysis and LCA for robust analysis [42]. Finally, a selection of suitable database to model the study system on, for example by using GaBi which has 20,000 accessible data plus Eco invent databases 13,300 data for the foreground processes to reduce uncertainties. This means the impacts that can be modelled are will be considered to have with robust model and data, and finally could lead to accurate analysis and open comparability between different studies [64,65]. Regarding the AD alternatives for organic waste treatment the single stage dry continuous as well as single stage wet high rate digestion system can effectively handle organic waste. Both technologies are capable of significantly reducing the water consumption and energy expense. However, in high generation of organic waste in urban area with fewer spaces available, dry continuous system is more preferable because it has a small reactor, cheap pre-treatment, very little wastewater production, composting waste well applied and less heat needed. This is supported by Poeschl et al. [24] which indicated that small scale AD technologies is the promising approach to reduce impact on the environmental. The two-stage AD systems with separation of hydrolysis and methanogenesis in separate reactors could have shorter processing times and higher organic loading levels (up to 50 kg-COD/m3/d) than the single-stage systems, but their Total Solid > 20%, the dilution of the waste stream causes a substantial increase in the energy needed for heating, pumping and expanding reactors. Meanwhile, the performance of the three-stage digestion systems has more complex operation, more costly investment, more maintenance and operating resources compared to two-stage AD systems, and the large-scale three-stage system is not currently a good option [66].