Hybrid Life Cycle Assessment Research Articles

Integrated hybrid life cycle assessment and contribution analysis for CO2 emission and energy consumption of a concentrated solar power plant in China

Concentrated solar power (CSP), a technology that provides electricity by concentrating solar energy into a single focal point, shows great potential for large-scale utilization. In this study, an integrated hybrid life cycle assessment (LCA) model for multiple regions of China is presented to evaluate the life cycle CO2 emission, energy consumption, and energy payback time of a 10-MW power tower CSP plant located in China. Over its life cycle of 25 years, the CSP plant is estimated to have CO2 emissions of 35 g/kWh, consume 514 kJ/kWh of energy, and have an energy payback time close to four years. Using the proposed hybrid model, a significant advantage is the ability to compare the life cycle impact sourced from each sector in input-output economic background. Based on the regionalization of economic background at the province level, the most noteworthy impact is from Hubei province; besides, the CO2 emission from the electricity sector in each province is the largest contributor. The majority (54%) of the life cycle CO2 emission of the CSP plant is contributed by the northern region of China due to the higher utilization of coal in the economy of that region, yet most of the energy consumption comes from the southern part of China because of the concentration of manufacturing there. For the life cycle impact of a CSP plant, thermal energy storage using molten salt, and solar collection demanding lots of steel are the two most significant contributors to CO2 emission and energy consumption.

Comparative Life-Cycle Assessment of Li-Ion Batteries through Process-Based and Integrated Hybrid Approaches

This paper analyzes and compares the life cycle environmental impacts of two major types of Li-ion batteries using process-based and integrated hybrid life-cycle assessment (LCA) approaches. The life cycle inventories (LCIs) of Li-ion battery contain component production, battery assembly, use phase, disposal and recycling and other related background processes. For process-based LCA, 17 ReCiPe midpoint environmental impact indicators and three end point environmental impact indicators are considered. As for the integrated hybrid LCA study, life cycle greenhouse gas (GHG) emissions and energy consumption are emphasized. Furthermore, we perform sensitivity analysis of life cycle GHG emissions with respect to the uncertainties in product prices, mass of BMS and cooling system, and production efficiency. The integrated hybrid LCA results show that battery cell production is the most significant contributor to the life cycle GHG emissions and the economic input-output (EIO) systems contribute the largest part...

The socio-economic impacts of introducing circular economy into Mediterranean rice production

Abstract: A novel bio-fertilizer technology that utilizing paddy rice residues (bran and husk) through composting was assessed in the context of life cycle assessment application to circular bio-economy. The bio-fertilizer can recycle the nutrients in residues to replace synthetic fertilizer within the rice production system. To evaluate the feasibility and potential benefits of this circular rice production system, a hybrid life cycle assessment model was developed to estimate social-economic impact. The model combined the multi-regional input-output database (Exiobase), with engineering process data of conventional and circular rice production systems from the Agrocycle project. The gross value added and employment in each system were compared at functional unit and sectoral level. The results indicated the efficiency of fertilizer application has a significant effect on social-economic impacts. The circular system has the potential to increase the gross value added and employment in conventional rice production, but the circular rice system could not improve both economic and social impacts at the same time. The results indicated the circular system did not necessarily achieve more positive social-economic impacts than the convention linear system. Considering the circularity and efficient use of resources, the bio-fertilizer technology should not be dismissed. To derive better social-economic performance from the circular rice supply chain, further developments are required, such as technology development to reduce unit production cost and infrastructure development to support bio-fertilizer production.

Greenhouse Gas Emission Analysis of Biomass Moving-bed Pyrolytic Polygeneration Systems based on Aspen Plus and Hybrid LCA in China

Under the existing scenario of greenhouse gas (GHG) emission reduction technologies, it is difficult to make the global temperature rise within 2°C in 2100. Thus, bio-energy with carbon capture and storage (BECCS) technology, as one of primary negative carbon emission methods, is urgent to deploy. In order to correctly recognize the development potential of bio-energy, the biomass pyrolytic polygeneration system, as the second novel bio-energy technology, should be carefully investigated in terms of GHG emission intensity and GHG emission reduction firstly. In this study, the material and energy flow in the process was carefully studied, and its environmental benefits was further researched. Based on the biomass pyrolysis mechanism and components pyrolysis property, the model of biomass pyrolytic polygeneration system was built on the Aspen Plus simulator, which is used to make an analysis of the life cycle greenhouse gas emission reduction. Results indicated that the agriculture process as the largest contributor to total GHG emissions with 86.03% of the total plant GHG emissions. In the entire pyrolysis temperature range, the intensity of GHG emissions from moving bed pyrolytic polygeneration system is from 4.15 to 6.12 g CO2-eq/MJ. Compared with other pyrolysis products, bio-char has a greater impact on the GHG emission reduction benefits of pyrolytic system. For the same system capacity, the system has the largest emissions reduction at a reaction temperature of 250°C, where also the bio-char yields is largest. If all of the bio-char returns to the field, the system can lead to negative carbon emission, which is 22 times larger than the system GHG emission when pyrolysis temperature is 250°C.

Life Cycle Assessment of the New Generation GT-MHR Nuclear Power Plant

This study describes a life cycle assessment (LCA) of a fourth generation (4G) nuclear power plant. A high temperature helium cooled reactor and gas turbine technology with modular helium reactor (GT-MHR) is used in this study as an example. This is currently one the safest design of a nuclear power plant. The study also takes into account impact of accidents and incidents (AI) which happened around the world at nuclear power generation facilities. The adopted method for the study is a hybrid LCA analysis. The analysis of each phase of the life cycle was done on the basis of process chain analysis (PCA). Where detailed data were not available, the Input/Output (I/O) databases was employed. The obtained results show that greenhouse gases (GHG) emissions and energy intensity per unit of electricity production are relatively low. In fact, these are even lower than emissions from a number of renewable energy sources. The results show considerably different greenhouse gases (GHG) emissions and energy intensity per unit of electricity production when effects of AI are taken into account.

Implementing hybrid LCA routines in an input\u2013output virtual laboratory

Hybrid life cycle assessment (LCA) has been developed for almost 40 years, but its applications are still limited to certain products/industries. This study endeavors to expand the accessibility of hybrid LCA from specialists to practitioners by developing a streamlined and semi-automated hybrid LCA data compilation routine in an input–output virtual laboratory. Data from the Australian Life Cycle Inventory Database (AusLCI) and the Australian Industrial Ecology Virtual Laboratory are used to demonstrate this routine. A hybridized AusLCI database is generated and used to calculate the hybrid carbon footprint intensities (CFIs) of all AusLCI processes. How different assumptions and settings on the hybridization influence the difference between process-based and hybrid results is further investigated and discussed intensively. Major inputs from the IO system are identified, and the sensitivity and uncertainty of hybrid results against unit price variations and EEIO table uncertainties are quantified via Monte Carlo simulations. On average, process-based CFIs are 21–32% lower than the corresponding hybrid CFIs, which is larger than the uncertainties resulting from either price variation, EEIO data uncertainty or scenarios on how the hybridization is conducted. Although the data are Australian specific, the underlying procedure is applicable to any country as long as suitable data are available.

A waste generation input output analysis: The case of Spain

In December 2015 the European Commission adopted the Circular Economy Package that includes legislative proposals on waste as well as long-term targets to reduce landfilling and increase recycling and reuse. A detailed and comprehensive accounting of waste arisings forms the quantitative basis for designing adequate policy instruments for a Circular Economy. The aim of this paper is to estimate total waste generation throughout the supply chain in Spain by applying an input-output based hybrid Life Cycle Assessment model. Both the waste generated by direct suppliers and indirect suppliers (that is, suppliers to suppliers) are estimated. The results show that there is high concentrations in total waste generation both in terms of sectors and waste types so the government should concentrate its waste prevention strategy on those sectors and types of waste that have a higher impact on total waste generation.

Both completing system boundaries and realistic modeling of the economy are of interest for life cycle assessment—a reply to “Moving from completing system boundaries to more realistic modeling of the economy in life cycle assessment” by Yang and Heijungs (2018)

As Yang and Heijungs (Int J Life Cycle Assess https://doi.org/10.1007/s11367-018-1532-y , 2018) bring forward, there is indeed a need for “more realistic modeling of the economy” in LCA. However, what I discuss in this letter is that this does not imply that research should be “moving from completing system boundaries to more realistic modeling” or that “hybrid LCA with further linear sophistication is a step forward in the wrong direction”, as Yang and Heijungs (2018) state. Five arguments are brought forward as to why not: (1) completing system boundaries is a fundamental aspect of LCA; (2) the approach that leads to a higher accuracy in LCA will in practice remain relative and case dependent; (3) the general argument of hybrid LCA is not that every economic activity is in theory connected; (4) hybrid LCA is applied for more reasons than just completing system boundaries; and (5) hybrid LCA is more a step forward in a pragmatic data-driven direction, which is not a wrong direction. Finally, I propose that a more broad empirical study is needed to pinpoint which type of adaptation might most probably lead to higher accuracy, keeping in mind that this still will never be completely generalizable.

Hybrid life-cycle assessment for robust, best-practice carbon accounting

In order to meet internationally agreed targets for avoiding dangerous anthropogenic climate change, an absolute priority for global society is to rapidly stabilise and then reduce carbon dioxide emissions into the atmosphere. Any entity, be it individual, company, or nation state, is more able to reduce its carbon dioxide (and other greenhouse gas) emissions if these can be quantified and attributed and the effects of interventions estimated. The current state of product and supply chain carbon accounting methods does not consistently meet the standards required to tackle this global challenge. This study therefore aims to identify key methodological practices affecting the accuracy of carbon accounting models and in particular to assess the effects of the system boundaries they employ. Models currently available for estimating carbon emissions are either input-output based (using macro-economic analysis), process-based (using specific carbon emissions attributes through the life-cycle of a product, service or event), or a hybrid of the two. Here, a detailed comparison has been made between various input-output and process-based models and the results compared with those from a hybrid model that was taken to represent ‘best practice’ in carbon accounting. Key factors affecting accuracy were found to lie in: the detail of methodological decisions for input-output models, the economic region or regions upon which the model is based, and the quality, disaggregation and, especially for price-volatile products, the temporal alignment of the data. The relative significance of these factors is explored. For copper wire, a system boundary gap analysis was conducted on an industry-leading process-based model (GREET.net) compared with a complete system as described by the best performing input-output model. GREET.net was found to suffer a 60% truncation error. The copper wire example demonstrates the practicality of substituting process-based analysis into input-output based supply chain emissions assessments.

Moving from completing system boundaries to more realistic modeling of the economy in life cycle assessment

Existing process-based life cycle assessment (LCA) models can be supplemented by input-output (IO) models to correct for the so-called truncation error resulting from an “incomplete” system boundary. The resulting hybrid LCA is not necessarily but probably a closer approximation to an ideally complete process model with a global all-inclusive system boundary. Here, we discuss whether such a complete process model is a goal worth pursuing and whether system boundary is the main limitation of process-based LCA. We argue that the results of the ideally complete process model, with every single economic activity on earth embodied within, have little to limited implications and relevance for the decisions which LCA seeks to support and which involve changes aimed at reducing environmental impacts through altering product systems or promoting alternatives. The main limitations of process-based LCA, as a supply chain based linear model, lie not in the “incomplete” system boundary but in the narrow focus on supply chain and the unrealistic assumptions, such as omission of price effects and constraints. These assumptions reflect poorly how the economy works. Hybrid LCA, through adding IO models, which are also supply chain and linearity based, doubles down on both the narrow focus on supply chain and the unrealistic assumptions, and thus is a step forward but in the wrong direction. Reflecting on advances in corn ethanol research, we show that pursuing a more complete system boundary by, for instance, covering Chinese stuffed animal production does not make the LCA results more accurate or relevant for determining if corn ethanol in the US should be promoted. Not only is the theoretical argument for including Chinese stuffed animal industry tenuous, but there is no evidence it has been affected by US corn ethanol expansion. And by worrying about processes far away up the supply chain could distract us from focusing on the actual market mechanisms, such as indirect land use change, that are more likely to occur and are essential to predicting whether promoting corn ethanol would reduce total carbon emissions. We suggest future studies shifting focus from “completing” system boundary within the conventional supply chain and linear framework towards more realistic modeling of our complicated human-environment system. Instead of trying to always include everything, we argue for a flexible and market-based system boundary tailored to the decision in question, particularly considering the scale of potential changes it may cause and how it may affect the economy. A change at larger scales is likely to have a broader impact, thus justifying the definition of a broader system boundary. But to cover a broad system boundary for a small change will likely result in overestimates. More is not necessarily better.

Hybrid life-cycle assessment for energy consumption and greenhouse gas emissions of a typical biomass gasification power plant in China

Among biomass energy technologies which are treated as the promising way to mitigate critical energy crisis and global climate change, biomass gasification plays a key role given to its gaseous fuels especially syngas for distributed power plant. However, a system analysis for the energy saving and greenhouse gas emissions abatement potentials of gasification system has been directed few attentions. This study presents a system analysis that combines process and input-output analyses of GHG emissions and energy costs throughout the full chain of activities associated with biomass gasification. Incorporating agricultural production, industrial process and wastewater treatment which is always ignored, the energy inputs in life cycle are accounted for the first commercial biomass gasification power plant in China. Results show that the non-renewable energy cost and GHG emission intensity of the biomass gasification system are 0.163 MJ/MJ and 0.137 kg CO2-eq/MJ respectively, which reaffirm its advantages over coal-fired power plants in clean energy and environmental terms. Compared with other biomass energy processes, gasification performs well as its non-renewable energy cost and CO2 intensity are in the central ranges of those for all of these technologies. Construction of the plant is an important factor in the process's non-renewable energy consumption, contributing about 44.48% of total energy use. Wastewater treatment is the main contributor to GHG emissions. The biomass gasification and associated wastewater treatment technologies have critical influence on the sustainability and renewability of biomass gasification. The results provide comprehensive analysis for biomass gasification performance and technology improvement potential in regulating biomass development policies for aiming to achieve sustainability globally.

A model for streamlining and automating path exchange hybrid life cycle assessment

Life cycle assessment (LCA) is inherently complex and time consuming. The compilation of life cycle inventories (LCI) using a traditional process analysis typically involves the collection of data for dozens to hundreds of individual processes. More comprehensive LCI methods, such as input-output analysis and hybrid analysis can include data for billions of individual transactions or transactions/processes, respectively. While these two methods are known to provide a much more comprehensive overview of a product’s supply chain and related environmental flows, they further compound the complex and time-consuming nature of an LCA. This has limited the uptake of more comprehensive LCI methods, potentially leading to ill-informed environmental decision-making. A more accessible approach for compiling a hybrid LCI is needed to facilitate its wider use. This study develops a model for streamlining a hybrid LCI by automating various components of the approach. The model is based on the path exchange hybrid analysis method and includes a series of inter-related modules developed using object-oriented programming in Python. Individual modules have been developed for each task involved in compiling a hybrid LCI, including data processing, structural path analysis and path exchange or hybridisation. The production of plasterboard is used as a case study to demonstrate the application of the automated hybrid model. Australian process and input-output data are used to determine a hybrid embodied greenhouse gas emissions value. Full automation of the node correspondence process, where nodes relating to identical processes across process and input-output data are identified, remains a challenge. This is due to varied dataset coverage, different levels of disaggregation between data sources and lack of detail of activities and coverage for specific processes. However, by automating other aspects of the compilation of a hybrid LCI, the comprehensive supply chain coverage afforded by hybrid analysis is able to be made more accessible to the broader LCA community. This study shows that it is possible to automate various aspects of a hybrid LCI in order to address traditional barriers to its uptake. The object-oriented approach used enables the data or other aspects of the model to be easily updated to contextualise an analysis in order to calculate hybrid values for any environmental flow for any variety of products in any region of the world. This will improve environmental decision-making, critical for addressing the pressing global environmental issues of our time.

Inequality across China's Staple Crops in Energy Consumption and Related GHG Emissions

It is significant to investigate the inequalities between energy consumption and related greenhouse gas emissions for sustainable crop production in China. We adopt a hybrid economic input-output and life cycle assessment model, in order to examine the crop-specific embodied energy intensity (EEI) and energy consumption related greenhouse gas intensity (ECR-GHGI) of 29 staple crops from 1990 to 2010. A sensitivity analysis is employed to investigate the relationship between ECR-GHGI and the different components of EEI. We further determine, via a structural path analysis, product-specific energy management priorities for each agricultural production input (API). Our findings indicate the following: (1) The EEI and ECR-GHGI of cash crops are greater than those of grain crops. (2) The EEI and ECR-GHGI of most grain crops increased during the sample period, while the EEI and ECR-GHGI of most cash crops decreased. (3) Energy consumption of synthetic fertilizers is the primary driver of ECR-GHGI across the full range of crops. Agricultural machinery and pesticides are also important factors. (4) Potential energy-savings practices in the API production processes should be taken seriously. (5) Different actions should be implemented to reduce energy consumption levels and ECR-GHG emissions in terms of the production processes of different APIs.

Decomposition of integrated hybrid life cycle inventories by origin and final-stage inputs

This note presents a method to decompose life cycle inventories derived from integrated and mixed-unit hybrid life cycle assessment. The approach extends the decomposition method described by Wiedmann (Econ Struct 6:11, 2017. https://doi.org/10.1186/s40008-017-0072-0) by differentiating between impacts from industries, products and processes. The method can be used to quantify the cradle-to-sale impacts of products and processes in the final stage of manufacturing a particular product. We present such a decomposition for the example of life cycle inventories for different types of concrete and compare it to one where the life cycle inventories have been decomposed by origin.

Using Data Mining To Assess Environmental Impacts of Household Consumption Behaviors.

Household consumption is a main driver of economy and might be regarded as ultimately responsible for environmental impacts occurring over the life cycle of products and services. Given that purchase decisions are made on household levels and are highly behavior-driven, the derivation of targeted environmental measures requires an understanding of household behavior patterns and the resulting environmental impacts. To provide an appropriate basis in support of effective environmental policymaking, we propose a new approach to capture the variability of lifestyle-induced environmental impacts. Lifestyle-archetypes representing prevailing consumption patterns are derived in a two-tiered clustering that applies a Ward-clustering on top of a preconditioning self-organizing map. The environmental impacts associated with specific archetypical behavior are then assessed in a hybrid life cycle assessment framework. The application of this approach to the Swiss Household Budget Survey reveals a global picture of consumption that is in line with previous studies, but also demonstrates that different archetypes can be found within similar socio-economic household types. The appearance of archetypes diverging from general macro-trends indicates that the proposed approach might be useful for an enhanced understanding of consumption patterns and for the future support of policymakers in devising effective environmental measures targeting specific consumer groups.

Carbon footprint assessment for the waste management sector: A comparative analysis of China and Japan

Waste management is becoming a crucial issue in modern society owing to rapid urbanization and the increasing generation of municipal solid waste (MSW). This paper evaluates the carbon footprint of the waste management sector to identify direct and indirect carbon emissions, waste recycling carbon emission using a hybrid life cycle assessment and input-output analysis. China and Japan was selected as case study areas to highlight the effects of different industries on waste management. The results show that the life cycle carbon footprints for waste treatment are 59.01 million tons in China and 7.01 million tons in Japan. The gap between these footprints is caused by the different waste management systems and treatment processes used in the two countries. For indirect carbon footprints, China’s material carbon footprint and depreciation carbon footprint are much higher than those of Japan, whereas the purchased electricity and heat carbon footprint in China is half that of Japan. China and Japan have similar direct energy consumption carbon footprints. However, CO2 emissions from MSW treatment processes in China (46.46 million tons) is significantly higher than that in Japan (2.72 million tons). The corresponding effects of waste recycling on CO2 emission reductions are considerable, up to 181.37 million tons for China and 96.76 million tons for Japan. Besides, measures were further proposed for optimizing waste management systems in the two countries. In addition, it is argued that the advanced experience that developed countries have in waste management issues can provide scientific support for waste treatment in developing countries such as China.

Mixed-unit hybrid life cycle assessment applied to the recycling of construction materials

The construction industry contributes around 18% of greenhouse gas emissions, 40% of depletion of natural resources, and 25% of wastes globally. To reduce these impacts, construction industries can adopt low-carbon alternatives for construction materials and waste minimisation strategies, including the recycling of construction and demolition waste. However, a comprehensive understanding of the full life cycle carbon profile of low-carbon and recyclable construction materials is required to accurately assess the efficacy of decarbonisation strategies in the built environment. Despite recent progress in hybrid life cycle assessment (hybrid LCA) methods, some weaknesses remain with respect to the inherent uncertainty relating to price variations and aggregated sectors that are unable to provide detailed waste-specific information in hybrid LCA. Furthermore, attributional, hybrid LCA for a functional unit does not reflect the actual, economy-wide physical flows of materials in a real economy. In this study, a mixed-unit hybrid LCA approach based on a combination of process life cycle inventory, input–output, and material flow data is used to model the economy-wide potential use of recycled construction materials in Australia. A comparison between methods of life cycle emissions of geopolymer concrete revealed that the mixed-unit hybrid LCA approach produced a more accurate and Australian-specific result. The usefulness of the proposed mixed-unit IO model is demonstrated through quantifying the cradle-to-gate embodied emissions of recycled construction materials and by-products utilised in concrete and steel sectors in Australia. The results yield a 1% reduction when recycled concrete aggregate completely replaces natural aggregate in both ordinary Portland cement and geopolymer concrete. Greenhouse gas emissions reduction of 30% is quantified for geopolymer concrete using recycled concrete aggregate compared with ordinary Portland cement concrete utilising natural aggregate and 43% is estimated for electric arc furnace route using iron and steel scrap compared with basic oxygen furnace route. The method merges physical and monetary units of industrial systems related to low-carbon alternatives and recycled construction materials to enable the calculations of embodied carbon with improved accuracy. The results of this study can help inform decarbonisation strategies in the built environment sector.

Quantifying uncertainties in greenhouse gas accounting of biomass power generation in China: System boundary and parameters

Systematically quantifying the greenhouse gas (GHG) emissions of biomass power generation is a prerequisite for robust decision-makings associated with the technology's scale deployment. This study compared the planting-to-wire GHG emissions of a typical corn-stover-based power generation system in China, estimated using one process-based and two hybrid life-cycle assessment (LCA) models. Results showed that emissions calculated by process-based LCA were 11% lower than that of hybrid models because of the truncations on services and accessory equipment. The two tiered hybrid approaches yielded total-supply-chain GHG footprints of material and equipment with a negligible difference (0.7%). The parameter settings varied by time and regions/countries resulted in temporal and spatial uncertainties of process-based LCA at 4%–10% and 0.1%–16% respectively. We proposed adopting hybrid LCA models for footprint calculation because of their strength in comprehensive accounting coverage, less dependence on data acquisition, and reduced temporal and spatial uncertainties. As the GHG footprint of biomass energy utilization is region-specific and determined by multiple factors, such as supply-chain configurations and landscape of power generation technology, results of this study help to understand the uncertainties and trade-offs associated with different LCA model deployments in China, and thus, contribute to advancing the country's biomass power sector moving forward.

Life cycle energy consumption and greenhouse gas emissions of urban residential buildings in Guangzhou city

Abstract Carbon emissions are derived mainly from the building, industrial, and transport sectors. Buildings are responsible for more than 40% of global energy use and for as much as 33% of global greenhouse gas emissions. By the end of 2016, 57.4% of the total population lived in urban areas in China, a dramatic increase from 26% in 1990. It is essential to study and analyze both energy consumption and carbon emissions of buildings. Taking Guangzhou city of China as an example, this study applied a hybrid life cycle assessment approach to quantify both the energy consumption and CO2 emissions throughout the life cycle of an urban residential building. The data was collected from the Guangzhou input–output (IO) table of 2012, Guangzhou Statistical Yearbook of 2013, China Electric Power Yearbook of 2013, and statistical data of the studied building. Results showed that the overall life cycle energy consumption and CO2 (eq.) emissions for the studied building, constructed in 2012, were approximately 72,591.98 GJ and 12,637.32 t, respectively. The largest CO2 (eq.) emission factor was oil and the smallest one was electricity. The CO2 emissions of steel, concrete, brick, and cement together accounted for 76.69% of the total emissions which are related to building materials in the preparation stage. This research not only promotes the construction of eco-cities or eco-communities, but also provides decision makers with comprehensive data on the energy consumption and environmental impacts of residential buildings. The findings are of considerable importance in terms of energy saving and emissions reductions for society as a whole.

Life cycle water use of a biomass-based pyrolysis polygeneration system in China

Water is essential for bioenergy production. Characterized as low carbon technology, crop-based bioenergy technology witnesses rapid development, inevitably putting pressure on global water resources. Therefore, it is crucial to carefully assess bioenergy technology’s overall impact on scarce water source for a sustainable bioenergy future. In this regard, this study aims to evaluate the life cycle water use of bioenergy from agricultural residues via the first pilot moving-bed pyrolysis polygeneration system in China. By using a tiered hybrid life cycle assessment, both direct and indirect water use are calculated. Results show life cycle water use is 3.89 L H2O/MJ and agricultural process dominates the total water use. Scenarios analysis shows different feedstock allocation ratios during agricultural production have striking influence on water use intensity. In addition, the choice of feedstock is another important influential factor. Under the 2020 Scenario in China’s 13th Five Year Plan, if all the bioenergy target could be met by polygeneration the estimated annual water use will be 6.6 billion m3, in magnitude up to around ten times the total water consumption in Denmark in 2013. In global scenario of potential feedstock available in 2060, the estimated water use for bioenergy produced by polygeneration will be 179–369 billion m3. Although the water use intensity of bioenergy production from agricultural residues by polygeneration is lower than that for other biomass conversion pathways, it is still higher than water intensity of conventional fossil energy products. Large-scale bioenergy production will have macroscopic effects on water demand. Finally, suggestions such as selecting high water-efficient biomass feedstock and reinforcing water-saving irrigation management to minimize water use in agriculture stage are proposed.