Life Cycle Inventory Research Articles

Swiss Agricultural Life Cycle Assessment: A method to assess the emissions and environmental impacts of agricultural systems and products

PurposeAgricultural production, which dominates the environmental impacts of the food sector, has specific characteristics that need to be considered in life cycle assessment (LCA) studies. Agricultural systems are open, difficult to manage and control, strongly depend on natural resources and their impacts are highly variable and influenced by soil, climate and farm management. A specific framework, efficient methods and tools are thus needed to adequately assess the environmental impacts of agricultural systems.MethodsWe present the Swiss Agricultural Life Cycle Assessment (SALCA) concept and method, developed for a detailed and specific analysis of agricultural systems. It comprises rules for the definition of system boundaries, functional unit and allocation, emission models, a life cycle inventory (LCI) database, calculation tools, impact assessment methods and concepts for analysis, interpretation and communication. This paper focuses on emission models for gaseous N, nitrate leaching, P emissions to water, soil erosion, pesticides, heavy metals, emissions from animal production and impact assessment methods for soil quality and biodiversity. The models are calculated at the crop, field, animal group and farm levels and are integrated in a consistent and harmonised framework, which is ensured by exchanging intermediate results between models.Results and discussionThe SALCA concept has been applied in numerous LCA studies for crops and crop products, cropping systems, animal husbandry systems and animal products, food and feed products, farms and product groups, the agrifood sector and food systems. The SALCA methodology has also been a backbone of the LCI databases ecoinvent, AGRIBALYSE and the World Food LCA database. The strengths of SALCA lie in its comprehensiveness, specificity to agriculture, harmonisation, broad applicability, consistency, comparability, flexibility and modularity. The extensive data demand and the high complexity, however, limit the application of SALCA to experts. The geographical scope is limited to Central and Western Europe, with a special focus on Switzerland. However, due to the modular and flexible design, an adaptation to other contexts is feasible with reasonable effort.ConclusionsSALCA enables answering a wide range of research questions related to environmental assessment and is applicable to various goals and scopes. A further development would be the inclusion of the social and economic dimensions to perform a full sustainability analysis in the SALCAsustain framework.

Life cycle energy and greenhouse gas emissions of a traditional and a smart HVAC control system for Australian office buildings

In recent years, many novel smart technologies have been proposed to reduce the energy consumption and greenhouse gas (GHG) emissions attributed to the building sector. One such application of these technologies is the reduction of the Heating, Ventilation and Air Conditioning (HVAC) energy needs and GHG emissions using smart control systems. The environmental benefits of smart control systems during building operation have been explored in many studies, however, their embodied effects, associated with the extraction of raw materials, manufacturing and replacement are often overlooked. Accordingly, this study quantifies the life cycle energy needs and GHG emissions of a smart HVAC control system and assesses its potential for reducing the HVAC operational energy and GHG emissions in an Australian office building. A comparative assessment is performed, considering a traditional HVAC control system and an equivalent smart HVAC control system. The components of both the traditional and smart control systems are specified based on the characteristics of these systems as well as the layout of the serviced spaces in the reference building. The embodied energy and GHG emissions of both the traditional and smart control systems are quantified through a hybrid life cycle inventory (LCI) approach. To evaluate the effects of these control systems on the building HVAC operational energy, a building energy simulation is performed by applying the control logics of both systems. The results show that energy and GHG emissions savings in the HVAC operational offset the additional energy needs and GHG emissions of deploying the smart HVAC control system.

Environmental and economic assessments of industry-level medical waste disposal technologies – A case study of ten Chinese megacities

Medical waste (MW) is exploding due to the COVID-19 pandemic, posing a significant environmental threat, and leading to the urgent requirement for affordable and environmentally friendly MW disposal technologies. Prior research on individual MW disposal plants is region-specific, applying these results to other regions may introduce bias. In this study, major MW disposal technologies in China, i.e., incineration technologies (pyrolysis incineration and rotary kiln incineration), and sterilization technologies (steam sterilization, microwave sterilization, and chemical disinfection) with residue landfill or incineration were analyzed from an industry-level perspective via life cycle assessment (LCA), life cycle costing (LCC) and net present value (NPV) methods. Life cycle inventories and economic cost data for 4–5 typical companies were selected from 128 distinct enterprises and academic sources for each technology. LCA results show that microwave sterilization with residue incineration has the lowest environmental impact, emitting only 480 kg CO2 eq. LCC and NPV analyses indicate that steam sterilization with landfilling is the most economical, yielding revenues of 1,210 CNY/t and breaking even in the first year. Conversely, pyrolysis and rotary kiln incineration break even between the 4th and 5th years. Greenhouse gas emissions from the MW disposal in ten cities with the largest MW production in 2020 increased by 7% over 2019 to 43,800 tons and other pollutants increased by 6% to 12%. Economically, Shanghai exhibits the highest cost-effectiveness, while Nanjing delivers the lowest. It can be observed that the adoption of optimal environmental technologies has resulted in a diminution of greenhouse gas emissions by 279,000 tons and energy conservation of 1.76 billion MJ.

Broccoli Leaves (Brassica oleracea var. Italica) as a Source of Bioactive Compounds and Chemical Building Blocks: Optimal Extraction Using Dynamic Maceration and Life Cycle Assessment

Bioactive compounds (BACs) and chemical building blocks (CBBs) play a pivotal role in driving economic growth. These compounds, known for their diverse applications in pharmaceuticals, agriculture, and manufacturing, have become integral to meeting the increasing demand for sustainable and innovative products. In this research, we used and characterized dynamic maceration to extract BACs and CBBs from broccoli leaves (BLs). A central composite design (CCD) was selected to evaluate the effect of temperature (from 4 °C to 70 °C), ethanol concentration (from 30% to 70% (v/v)), and exposition time (15 to 60 min) on total phenolic content (TPC) (mg of gallic acid equivalents (GAEs) per 100 g of dry biomass (db)). A confirmation experiment (CE) was performed to reproduce the optimal conditions (50 °C, 36.92 min, and 30% (v/v)) for BAC extraction. Results indicated a GAE concentration of 112.95 ± 0.92 mg/100 g db, while the statistical model predicted a value of 111.87 mg of GAEs/100 g db (error of 0.95%) with a rate constant (k) value of 0.0154 mg/g·min (R2 of 0.9894). BACs and CBBs were identified with gas chromatography–electron impact mass spectrometry detecting l-isoleucine, l-leucine, malonic acid, and succinic acid, among others. Finally, a life cycle inventory (LCI) was developed to determine global warming (GW) and water consumption (WC), among others, for 10 g of BL extract. Findings reported herein prove the sustainability of eco-friendly extraction of BACs and CBBs for the effective use of agricultural by-products.

The PROPER program evaluation to support the development of a national life cycle inventory database: recommendations

The quality and quantity of unit process datasets in the Life Cycle Inventory (LCI) database directly affect the reliability and accuracy of Life Cycle Assessment (LCA) study results where the data is used. Research has shown that data inventory management takes up 70-80% of LCA work. Using available datasets can improve efficiency in carrying out inventory. However, the availability of datasets for the Indonesia region still needs to be improved. Since 2021, the government has issued the revision of regulations related to corporate environmental performance known as PROPER. This research aims to recommend which industrial sectors should be prioritized for a national LCI database development based on an analysis of PROPER 2022 ratings, which company submitted LCA reports. This research concludes that the priority for developing the national LCI database is the oil and gas, electricity, mining, chemical, cement, food & beverages, and plantation sectors. This adds a new perspective to the development of the national database as it allows available resources through the implementation of the PROPER program.

Life cycle assessment of kerbside waste material for an open-looped and closed-loop production– towards circular economy designs

Urbanization growth has increased the generation of municipal solid waste (MSW) and has the potential for recycling and reuse. However, it is frequently limited to a linear lifecycle mode which end up in landfills. A novel attributional lifecycle inventory model for lifecycle assessment based on value retention process (VRP) model of circular economy was developed to quantify the lifecycle inventory and measure the environmental impacts of multiple lifecycle stages, from in-community separation to the end-of-use/life stage and subsequent lifecycles. This investigation focused on assessing the environmental impacts of two distinct in-community waste glass separation methods - separate kerbside glass recycling bin (SKGRB) and mixed kerbside recycling bin (MKRB) - in combination with two recycling approaches - open-loop (asphalt) and closed-loop (glass container). The goal of the study was to make a comparative evaluation of the environmental impacts of these methods. Results showed that the SKGRB method had better environmental performance (40–60% reduction compared to the MKRB method) for both materials. Closed-loop recycling of glass container production had higher environmental impacts due to higher energy consumption in production in one lifecycle, while the open-loop recycling method of asphalt had higher environmental impacts despite fewer circulations, due to higher production volume in 21 years. The results of the sensitivity/uncertainty analysis showed that environmental impacts decreased as the allocation coefficient decreased, reaching stability when the coefficient reached the waste materials percentage in the new product's mixed design.

Harmonized Life-Cycle Inventories of Nanocellulose and Its Application in Composites.

Cellulose nanocrystals (CNC) and nanofibers (CNF) have been broadly studied as renewable nanomaterials for various applications, including additives in cement and plastics composites. Herein, life cycle inventories for 18 previously examined processes are harmonized, and the impacts of CNC and CNF production are compared with a particular focus on GHG emissions. Findings show wide variations in GHG emissions between process designs, from 1.8-1100 kg CO2-eq/kg nanocellulose. Mechanical and enzymatic processes are identified as the lowest GHG emission methods to produce CNCs and CNFs. For most processes, energy consumption and chemical use are the primary sources of emissions. However, on a mass basis, for all examined production methods and impact categories (except CO emissions), CNC and CNF production emissions are higher than Portland cement and, in most cases, are higher than polylactic acid. This work highlights the need to carefully consider process design to prevent potential high emissions from CNCs and CNF production despite their renewable feedstock, and results show the magnitude of conventional material that must be offset through improved performance for these materials to be environmentally favorable.

Comparison of Primary Energy Consumption Between Additive Manufacturing Processes and CNC Machining Applied to Components in the Oil and Gas Sector

This work elucidates the environmental impact on the production of components in the oil and gas sector by analyzing two different production routes. To this end, a life cycle assessment of the CNC machining process and additive manufacturing (AM) was carried out using Multi Jet Fusion (MJF) technology. Life cycle inventories were prepared for both processes, using the Open LCA software and information from the Ecoinvent database to develop the life cycle, with Cumulative Energy Demand (CED) being considered as the impact method. From the analysis, it was found that the machining process presented an energy demand of 7177 MJ. In contrast, the MJF presented 3214 MJ, less than half of the primary energy required to produce one unit of the studied component, thus indicating that manufacturing by MJF presents greater environmental sustainability than the Oil and Gasconventional machining process.

4 Hands-On I: Building an Agent-Based Model in Anylogic

Abstract Livestock farming systems (LFS) have detrimental effects on the environment, associated mainly with feed production, enteric methane and emissions from manure. LFS are complex because they are structured by multiple interactions between biological and human-controlled processes, at various organizational levels. Their behavior and the extent to which feeding strategies can mitigate this environmental burden is not always easily predictable. Dynamic mechanistic models of LFS can simulate the effects of feeding strategies on both animal performance and the associated excretion of nutrients. These models are useful tools to produce the life cycle inventories needed in the second step of a life cycle assessment. In the pig-fattening unit, the effects of multiphase group feeding depend largely on the variability of growth potential among pigs and the farmer has decisions that can target either the group of pigs or each individual (e.g., when choosing pigs to deliver to slaughterhouse). Therefore, simulating the growth trajectory of each individual pig and events like deliveries to slaughterhouse makes it possible to estimate the response of the pig population rather than the average pig to feeding strategies. Individual-based models (IBM) are particularly adequate because they make it possible to simulate each individual and to build the response of the population from the aggregation of individuals. Agent-based models are IBM that rely on self-governing agents made of properties, behavioral rules and resources that allow each agent to make decisions upon the occurrence of an event, which can be triggered randomly or not. This hands-on will focus on a specific example dedicated to the simulation of the response (growth, nitrogen excretion and subsequent gaseous emissions from manure) of a population of fattening pigs to a multiphase feeding strategy. In a first step, we will develop a simplified individual-based model of a pig-fattening pen including pigs and the farmer as agents. In a second step, we will improve this model by introducing interactions between these agents. For both steps, we will work with python language using pre-developed jupyter notebooks.

Gadjah Mada University drinking water supply system TOYAGAMA life cycle inventory

TOYAGAMA is the drinking water supply system (DWSS) of Gadjah Mada University. Acknowledging that its production operations have potential environmental and ecological impacts is essential. To ensure sustainable operations, comprehension of these impacts is necessary. The Life Cycle Assessment (LCA) has been reported to be an ideal method, but it has never been carried out, Life Cycle Inventory (LCI) is a vital preliminary step. Therefore, this study aims to construct an LCI database for the production of drinking water in TOYAGAMA DWSS, covering the process of raw water intake to treatment. This database could serve as a reference for future LCA studies involving similar technologies and as an overview of its potential impacts. The data collection methods included observation, literature review, and interviews. The collected data focus was carried out from September 26 to November 3, 2022. Organizing and processing were performed using Microsoft Excel and OpenLCA 2.0 Beta. The results showed that TOYAGAMA DWSS consisted of 15 unit processes and an additional 1 non-TOYAGAMA DWSS unit process was included in the LCI. Flows recapitulation showed that 15 environmental flows were involved. Evaluation using Life Cycle Impact Assessment (LCIA) method Environmental Footprint 3.0 indicated that the production of 1 m3 drinking water contributed to 12 of 28 potential impact categories. Based on the results, to produce 1 m3 of drinking water, 3.35293 MJ of electrical energy and 1.22723 m3 groundwater were required. Furthermore, plastic waste had the highest potential impact, with a total of 5 impacts.

The ILCIDAF project for the development of an Italian Life Cycle Inventory Database of agri-food products: the bread production phase

The Project of Significant National Interest (PRIN, 2017) entitled: "Italian Life Cycle Inventory Database of Agri-Food Products" (ILCIDAF), financed by the Ministry of University and Research, aims to promote the sustainability of the agri-food sector through the development of a database on a national and regional scale for some food chains that are significant for the Italian economy The objective is to create datasets for the Italian agri-food sector which current existing databases do not provide. Specifically, datasets that are geographically, temporally and technologically representative of the Italian national territory were developed. The selected supply chains are: bread and pasta, wine, olive oil and citrus fruits respectively studied by four scientific units: the Universities of Bari, Chieti-Pescara, Messina and Reggio Calabria respectively. The database is constructed considering the entire supply chain of the indicated foodstuffs. The University of Bari, to which the authors of this work belong to, has previously provided contributions on the agricultural phase of wheat, the milling phase and the pasta-making phase. In this work, on the other hand, the phases of the bread-making process of durum and soft wheat bread are described. The aim of this study is to construct datasets relating to the transformation phase of the indicated end products. In particular, 5 datasets were constructed: two relating to bread made from soft wheat flour, 2 with durum wheat semolina and 1 with wholemeal durum wheat semolina. The data was acquired through information provided by the companies in the sector (field data) through the completion of appropriately drafted questionnaires and company reports. In addition, the same analysed and processed were compared with data available in scientific literature.

Life cycle assessment of prospective trajectories: A parametric approach for tailor‐made inventories and its computational implementation

AbstractLife cycle assessment (LCA) is a standardized, holistic, and multi‐criteria approach to estimate the environmental impacts of a system over its entire lifecycle. Modeling the environmental impacts of future scenarios and evolving systems in LCA is challenging due to lack of knowledge around technological evolutions and changing backgrounds influencing the foreground system. The method proposed here tackles these issues by combining parameterized life cycle inventories (LCIs) of foreground and background systems to assess how background changes, for example in the energy sector, affect the environmental impacts of the foreground. First, parameterized LCIs for the heating and energy sector were developed to flexibly estimate the environmental impacts of heating, gas, and electricity trajectories. Assessing their environmental impacts is essential to avoid any burden shifting to other impacts. Thanks to their parameterization, these models can represent different geographical, temporal, or technological contexts. Second, the combination of these parameterized LCIs was implemented using the Python library lca_algebraic, designed to enhance computational efficiency and calculation speed of LCAs. lca_algebraic’s features were extended to link parameters to specific LCIs and, hence, ease their import and export and facilitate teamwork. In a final step, the developed LCIs and lca_algebraic library were used to estimate the environmental impacts of French heating scenarios from 2018 until 2050, as a test of the approach. The parameterized models developed within this work are available on a Git together with published reference datasets for comparison, so that the method can be adapted to evaluate similar energy trajectories for other countries or regions. This article met the requirements for a gold–gold JIE data openness badge described at http://jie.click/badges.

Life cycle assessment of a decoupled biofloc aquaponics facility across seasons

Aquaponics promises a more sustainable approach to food production by repurposing waste from aquaculture for the production of crop plants. Previous life cycle assessments have been published on the environmental impacts of coupled aquaponics using recirculating aquaculture systems, however, impacts from decoupled biofloc aquaponics systems remain unknown. Decoupled systems offer many operational advantages over coupled systems, and the objective of this study was to use life cycle assessment to quantify their environmental impacts. Data from a multi-greenhouse aquaponics system was collected over a one-year period to generate a life cycle inventory. A previously published mass balance model was also used to analyze alterative operational scenarios. Both avoided burden and mass allocation approaches were considered given the high sensitivity of the model toward the former. Results showed that electricity, heating fuel, and feed made up 40%, 22%, and 24% of global warming potential (GWP), similar to other aquaponics studies. These inputs similarly dominated cumulative energy demand. A switch to renewable electricity sources could reduce GWP by over 40% in scenario analysis. Eutrophication impacts of the decoupled biofloc aquaponics system ranged from 8.93 × 10−3 to 5.27 × 10−2 kg N-eq per kg fish depending on the scenario. While at least 10% lower than aquaculture alone, these rates were over four times higher than coupled aquaponics due to discharge of nutrient-containing waters after plant production. Efforts to balance fish and plant production are especially critical in decoupled systems, as is re-use of post-plant effluent. These results show that careful consideration of operational decisions is important when trying to minimize the environmental footprint of decoupled aquaponics systems.

Remarkable Spatial Disparity of Life Cycle Inventory for Coal Production in China.

Coal is the primary energy source in China, and its life cycle inventory (LCI) is widely used as background data for life cycle assessment studies. Previous research indicates that the inventory of coal production varies regionally. However, the development of complete regionalized LCIs for coal production is quite limited. Here, we establish the first provincial-level LCIs of local coal production and market for coal in China, based on a database of 6,122 coal mines and developed models. In the inventory results of local coal production, the coefficients of variation (CVs) of nine indicators exceed 0.5, especially SO2 and particulate matter emission factors (CVs > 1). Compared with that, the interprovincial coal trade homogenizes the provincial production inventory of market for coal relatively, despite four indicators with CVs exceeding 0.5. Therefore, the regionalized inventory with remarkable spatial differentiation can provide more accurate fundamental data for future research such as electricity production. Furthermore, CH4 emissions from coal production account for 24% of China's total methane emissions, highlighting its significance in mitigating global warming. Moreover, through the increasing coal trade, the significant and implicit plunder of water resources from the three coal net-exporting provinces, located in water-scarce areas, should be noted.

Technical innovation of Autoclaved Aerated Concrete preparation from Desulfurization Wastewater and Sludge and its Life Cycle Assessment

ABSTRACT The article presents an innovative technique for the production of autoclaved-aerated concrete using desulfurization wastewater. The experiments were conducted to explore the optimal formula that meets the requirements of high compressive strength(≥5MPa) and low oven-dry density (≤600 kg m−3). Combined with specific production cases, the environmental assessment within the scope of the total life cycle assessment and circular economy assessment were carried out. Using compressive strength and maximum dry density as indicators, the optimal formulation was found to be 73%:16%:11%:30%:45% for fly ash: cement: lime: desulfurization wastewater: recycled water (process water). And the optimum ratio was 72%: 14%: 12%: 45%: 30% for fly ash: cement: lime: nanofiltration water: recycled water. The life cycle assessment contains a total life-cycle inventory and willing to pay was 61.1CNY. In addition, the GWP = 144.83 kg per cubic meter of autoclaved aerated concrete, the carbon emission reduction efficiency is 72.4%, the water saving is 0.195CNY for one ton of water, and the water saving rate is 40%. The technology is also a low-cost solution for clean production and circular economy model, promoting green and low-carbon development and meeting the requirements of “waste-free cities” popular worldwide.

Multilevel life cycle assessment to evaluate prospective agricultural development scenarios in a semi-arid irrigated region of Tunisia

CONTEXTTo design policies for sustainable irrigation planning, public decision-makers need knowledge about the potential environmental impacts of irrigated farming systems. In a previous paper, we proposed to couple Life Cycle Assessment (LCA) and Agrarian System Diagnosis (ASD) to build the Life Cycle Inventory (LCI) of a farming region in a context of data scarcity and farming system diversity. This method was applied to the semi-arid irrigated plain of Kairouan (Tunisia). OBJECTIVESThe aim of the present paper is to demonstrate how this new ASD-based LCA method is used to conduct the impact assessment of this farming region, under current conditions and for two prospective scenarios. METHODSTwo functional units (FU) were used: the area and the gross product generated. Life Cycle Impact Assessment (LCIA) was conducted based on a multilevel process, by converting LCI data collected for each cropping/ livestock system into LCIA outputs, which were then consolidated at the farming system (FS) and at the regional scales. Two scenarios, based on observed trends, were assessed: the “agrarian” scenario (driven by a shift from family to corporate farming) and the “hydrological” scenario (driven by a water table drawdown). RESULTSEnvironmental hotspots were identified at each scale: the most impactful FS was the “mixed family farming” (intermediate access to water), because of its large share of land at the regional scale (45%). In this FS, the most harmful cropping system was input-intensive olive groves intercropped with a melon-pepper/ cereal/ tomato rotation, in which most impacts (35%) were attributable to the input-intensive “melon” crop, and more particularly to “manufacture and transport of fertilizer”, including farmyard manure. Globally, the most harmful processes were water and fertilizer use (fertilizer manufacturing and transportation). This downscaling is very useful to inform public policies on the most harmful productions. The impacts in human, ecosystem and resource endpoints increased by 11%, 2%, 9% and 23%, 27% and 40%, for the agrarian and hydrological scenarios respectively. SIGNIFICANCEThese results show that observed trends in farming practices evolution (more irrigation) should be stopped. Our method has three main strengths: i) inter-farms synergies are accounted for in the LCIA, which is essential to promote circularity; ii) thanks to the innovative and multilevel approach, the origins of environmental hotspots can be investigated and later mitigated by future policies; iii) ASD helps to design sustainable scenarios by identifying current trends and regional thresholds (resources, pollution and workforce) that cannot be overcome.

Problematic consequences of the inclusion of capital goods inventory data in Environmental Product Declarations

PurposeA recent update to the Product Category Rules (PCRs) for Construction Products (of the International EPD System) has triggered a methodological issue for owners and users of Environmental Product Declarations (EPDs). The updated PCR has led to capital goods data being implicitly included in the Life Cycle Inventory (LCI) of EPDs. This paper critically examines the role of capital goods in EPDs and establishes major shortcomings in the current methodology, LCI datasets and interpretation.MethodsTo evaluate the role of capital goods in EPDs, this paper provides a discourse on the fundamentals of Life Cycle Assessment (LCA) methodology, scope, available LCI data and the impact of capital goods on EPD outcomes. Using the ecoinvent database, we analyse the impact of the inclusion and exclusion of capital goods in selected 38 construction products based on the EN 15804+A2 (2019) Standard. Finally, we estimate the relative contribution of capital goods to a suite of Life Cycle Impact Assessment (LCIA) indicators based on the archetypes of capital goods available in ecoinvent and apply Monte Carlo simulation to establish the range of uncertainties in the capital goods data for the selected construction products.Results and discussionOur research confirms that when capital goods are included based on currently available background LCI data, they mostly have a low effect (<10% increase) on climate change, but they can have an enormous effect (>100% increase) on abiotic depletion (minerals and metals), land use and/or human toxicity indicators. Interestingly, when looking further into the ecoinvent capital goods LCI datasets, it becomes clear that there are inaccuracies, inconsistencies, and possibly incorrect estimates of capital goods and infrastructure data. These findings raise questions about the suitability of the underlying LCI background data and whether non-attributable capital goods should be allowed to define EPD outcomes.ConclusionThe requirement for the inclusion of capital goods leads to a major conundrum for LCA practitioners. It is suggested that capital goods be excluded until there is better refinement and improvement of the quality of LCI datasets and EPD programs provide clearer guidance on dealing with capital goods. Alternatively, EPDs could document transparently the inclusion or exclusion of capital goods, so that there is a clear separation of the effects of capital goods on LCIA indicators.

Life‐Cycle‐Assessment of purlin systems: the influence of the low carbon high strength steels in CO2eq. emissions

AbstractDue to the decarbonization of the energy sector, embodied carbon has been recognized as the dominant climate impact driver. In response, countries are currently accelerating their efforts to comply with climate change commitments and regulations, pressure grows for the construction sector to reduce its impact rapidly.In the present paper, the life cycle assessments (LCA) of purlin roof systems, used as secondary structural elements on single‐story industrial buildings, are compared. Three structural materials are considered: metallic‐coated structural steel, reinforced concrete, and structural timber. In addition, different steel grades are compared to highlight the environmental benefits of using high‐strength steels (HSS) allowing weight‐optimized design.The LCA focuses on the product stage (modules A1‐A3), transport (module A4), end‐of‐life (module C), and the benefits and loads beyond the system boundary (module D). The life cycle inventory (LCI) is composed of construction environmental product declarations (EPD) published according to EN 15804. All the LCA evaluations are performed using the commercial software One Click LCA following the recommendations of EN 15978.

Life‐Cycle‐Assessment of a wildlife bridge: influence of the structural design on the carbon emissions

AbstractIn 2020, 37% of the global share of CO2eq. emissions were attributed to the construction sector. More recently, awareness has been raised on embodied carbon, where emissions from materials and products must be urgently addressed to ensure sustainable constructions. To assess the environmental impacts of a project, a Life‐Cycle‐Assessment (LCA) can be applied: it is a science‐based standardized methodology for quantifying the environmental impacts. It can be used to measure and provide insights to reduce the embodied carbon of constructions over their life.The present publication details the LCA of a wildlife bridge built in France. In addition to the original bridge structure, other structural systems are considered including different materials such as steel and reinforced concrete. The boundary of the LCA is a cradle‐to‐cradle analysis. The life cycle inventory (LCI) is composed of environmental product declarations (EPD) according to EN 15804.The influence of the structural design on the bridge's global warming potential (GWP) emissions and the influence of LCA assumptions (for example, EOL scenarios) are analyzed. This publication aims to support a holistic approach for bridge LCA and help identify the opportunities that can result from implementing sustainable construction strategies.

Life Cycle Inventory of the Italian citrus fruit supply chain: Modelling the agricultural phase inventory through statistical data processing

Life Cycle Inventory of the Italian citrus fruit supply chain: Modelling the agricultural phase inventory through statistical data processing