Taking the spatio-temporal effects of climate change into account for Life Cycle Assessment of prospective scenarios to secure water supplies in agricultural areas.

To cope with climate change, agricultural territories are forced to implement adaptation strategies, including the implementation of irrigation infrastructures. These strategies are deployed over a long term, and their environmental performance may vary in time and space due to climate change. Environmental assessment methods that include spatio-temporal dynamics must be developed to identify long term "no-regret" scenarios. This study proposes an innovative approach based on the coupling between a crop model, i.e. AquaCrop, and the Territorial-Life Cycle Assessment (T-LCA) framework. Results are exemplified and discussed, with comparison of scenarios with or without irrigation, between 1981 and 2099, at six contrasting locations in terms of climate and soil conditions for the Shared Socioeconomic Pathways 5-8.5 scenario developed by the Intergovernmental Panel on Climate Change. The assessments report that climate change can affect the eco-efficiency of irrigated perimeters over time. Moreover, climate change may alter the conclusions of the comparison of scenarios with or without irrigation infrastructure at a given location. Additionally, a sensitivity analysis is performed on key parameters of the study highlighting the importance of the electricity mix. Finally, spatio-temporal dynamics need to be considered to assess the environmental performance of long-term land planning scenarios and account for environmental effects such as climate change.

Impact assessment of a large panel of organic and inorganic micropollutants released by wastewater treatment plants at the scale of France.

Micropollutants emitted by Human activities represent a potential threat to our health and aquatic environment. Thousands of active substances are used and go to WWTP through wastewaters. During water treatment, incomplete elimination occurs. Effluents released to the environment still contain part of the micropollutants present in the influents. Here, we studied the potential impacts on Human health and aquatic environment of the release of 261 organic micropollutants and 25 inorganic micropollutants at the scale of France. Data were gathered from national surveys, reports, papers and PhD works. The USEtox ® model was used to assess potential impacts. The impacts on Human health were estimated for 94 organic and 15 inorganic micropollutants and on aquatic environment for 88 organic and 19 inorganic micropollutants highlighting lack of concentration and toxicological data in literature. Some Polycyclic Aromatic Hydrocarbons and pesticides as well as As and Zn showed highest potential impacts on Human health. Some pesticides, PCB 101, ßE2, Al, Fe and Cu showed highest potential impacts on aquatic environment.

Wastewater treatment using oxygenic photogranule-based process has lower environmental impact than conventional activated sludge process.

The Life Cycle Assessment (LCA) methodology was applied to assess the environmental feasibility of a novel wastewater treatment technology based on oxygenic photogranules (OPG) biomass in comparison to a conventional activated sludge (CAS) system. LCA using laboratory scale experimental data allowed for eco-design of the process during the early stage of process development at laboratory scale. Electricity consumption related to artificial lighting, the fate of the generated biomass (renewable energy and replacement of mineral fertilizer), and the nitrogen flows in the OPG system were identified as major contributors to the potential environmental impact of the OPG treatment system. These factors require optimization in order to reduce the environmental impact of the overall OPG system. Nonetheless, the environmental impact of a non-optimized OPG scenario was generally lower than for a CAS reference system. With an optimization of the artificial lighting system, an energy neutral treatment system may be within reach.

Addressing temporal considerations in life cycle assessment.

In life cycle assessment (LCA), temporal considerations are usually lost during the life cycle inventory calculation, resulting in an aggregated "snapshot" of potential impacts. Disregarding such temporal considerations has previously been underlined as an important source of uncertainty, but a growing number of approaches have been developed to tackle this issue. Nevertheless, their adoption by LCA practitioners is still uncommon, which raises concerns about the representativeness of current LCA results. Furthermore, a lack of consistency can be observed in the used terms for discussions on temporal considerations. The purpose of this review is thus to search for common ground and to identify the current implementation challenges while also proposing development pathways. This paper introduces a glossary of the most frequently used terms related to temporal considerations in LCA to build a common understanding of key concepts and to facilitate discussions. A review is also performed on current solutions for temporal considerations in different LCA phases (goal and scope definition, life cycle inventory analysis and life cycle impact assessment), analysing each temporal consideration for its relevant conceptual developments in LCA and its level of operationalisation. We then present a potential stepwise approach and development pathways to address the current challenges of implementation for dynamic LCA (DLCA). Three key focal areas for integrating temporal considerations within the LCA framework are discussed: i) define the temporal scope over which temporal distributions of emissions are occurring, ii) use calendar-specific information to model systems and associated impacts, and iii) select the appropriate level of temporal resolution to describe the variations of flows and characterisation factors. Addressing more temporal considerations within a DLCA framework is expected to reduce uncertainties and increase the representativeness of results, but possible trade-offs between additional data collection efforts and the increased value of results from DLCAs should be kept in mind.

Modelling dynamic soil organic carbon flows of annual and perennial energy crops to inform energy-transport policy scenarios in France.

Low carbon strategies recently focus on soil organic carbon (SOC) sequestration potentials from agriculture and forestry, while Life Cycle Assessment (LCA) increasingly becomes the framework of choice to estimate the environmental impacts of these activities. Classic LCA is limited to static carbon neutral approaches, disregarding dynamic SOC flows and their time-dependent GHG contributions. To overcome such limitation, the purpose of this study is to model SOC flows associated with agricultural land use (LU) and the provision of agricultural substrates to transport biofuels, thus generating dynamic inventories and comparatively assessing energy policy scenarios and their climate consequences in the context of dynamic LCA. The proposed framework allows computing SOC from annual and perennial species under specific management practices (e.g. residue removal rates, organic fertiliser use). The results associated with the implementation of three energy policies and two accounting philosophies (C-neutral and C-complete) show that shifting energy pathways towards advanced biofuels reduces overall resource consumption, LU and GHG emissions. The French 2015 Energy Transition for Green Growth Act (LTECV) leads towards higher mitigation targets compared with business-as-usual (BAU) and intermediate (15BIO) policy constraints. C-neutral results show reduced radiative forcing effects by 10% and 34% for 15BIO and LTECV respectively, with respect to BAU. C-complete (i.e. dynamic assessment of all biogenic- and fossil-sourced C flows) results reveal further mitigation potentials across policies, whereof 50%-65% can be attributed to temporal C sequestration in perennial rhizomes. A sensitivity analysis suggests important SOC variations due to temperature increase (+2°C) and changes in residue removal rates. Both parameters affect mitigation and the latter also LU, by a factor of -0.56 to + 5. This article highlights the importance of SOC modelling in the context of LU in LCA, which is usually disregarded, as SOC is considered only in the context of land use change (LUC).

Consistent normalization approach for Life Cycle Assessment based on inventory databases.

The process-based life cycle assessments (LCA) of goods and services are calculated using a bottom-up approach related to a functional unit. However, this does not provide any information regarding the scale of the environmental impacts. Therefore, the normalization allows to relate the impacts to a reference system (specific countries, regions or even the whole world). These references are usually obtained from top-down approach. The different data sources introduce inconsistencies on results and raise doubts on their adequacy and representativity. This paper proposes a novel approach for determining the data for the reference in order to ensure consistency about boundaries, data sources and modelling hypotheses describing the system. For this purpose, normalization is applied as an expression of the result relative to the average component of the reference system, instead of the sum of all the components. The reference values are determined from the geometric means of the datasets of the inventory database, used for assessing the studied systems. The exemplary application to the ecoinvent databases provides normalization references for 878 versions of the impacts categories listed by ecoinvent and for the 2077 involved substances. For eight impact assessment methods, the results are compared with 16 normalization sets from the literature and point out highly significant correlations.

Comments on the international consensus model for the water scarcity footprint (AWARE) and proposal for an improvement.

Life Cycle Assessment (LCA) provides a structured framework, addressing environmental impacts of human activities. LCA requires consensual and scientifically sound characterisation factors to quantify impacts and allow comparisons. This is the objective of the AWARE model, recently published by an international consortium, which is now the reference for water impact in LCA. Looking back at the shape of the equation, linking human water use and water impact, we discuss the limits of the AWARE model and the associated cut-offs. They imply that all regions in a less than fair ecosystem condition are treated at the same level of severity, regardless of the extent of degradation. From this statement, we propose to define the impact by the ratio between the ecosystem demands and the remaining after human activities (DTR model). We use the marginal and average approaches, common approaches in LCA, to determine the corresponding characterisation factors. Through a sensitivity analysis with respect to parameters used (total water availability, ecosystem demand, human consumption and area of the region), we show that the DTR-based characterisation factors have the same properties than the AWARE-based ones between cut-offs. This article therefore provides a new alternative way of quantifying the impact of water use, in line with the AWARE model features, but without its validity limits and induced thresholds.

Optimal integration of microalgae production with photovoltaic panels: environmental impacts and energy balance.

BACKGROUND: Microalgae are 10 to 20 times more productive than the current agricultural biodiesel producing oleaginous crops. However, they require larger energy supplies, so that their environmental impacts remain uncertain, as illustrated by the contradictory results in the literature. Besides, solar radiation is often too high relative to the photosynthetic capacity of microalgae. This leads to photosaturation, photoinhibition, overheating and eventually induces mortality. Shadowing microalgae with solar panels would, therefore, be a promising solution for both increasing productivity during hotter periods and producing local electricity for the process. The main objective of this study is to measure, via LCA framework, the energy performance and environmental impact of microalgae biodiesel produced in a solar greenhouse, alternating optimal microalgae species and photovoltaic panel (PV) coverage. A mathematical model is simulated to investigate the microalgae productivity in raceways under meteorological conditions in Sophia Antipolis (south of France) at variable coverture percentages (0% to 90%) of CIGS solar panels on greenhouses constructed with low-emissivity (low-E) glass. RESULTS: A trade-off must be met between electricity and biomass production, as a larger photovoltaic coverture would limit microalgae production. From an energetic point of view, the optimal configuration lies between 10 and 20% of PV coverage. Nevertheless, from an environmental point of view, the best option is 50% PV coverage. However, the difference between impact assessments obtained for 20% and 50% PV is negligible, while the NER is 48% higher for 20% PV than for 50% PV coverage. Hence, a 20% coverture of photovoltaic panels is the best scenario from an energetic and environmental point of view. CONCLUSIONS: In comparison with the cultivation of microalgae without PV, the use of photovoltaic panels triggers a synergetic effect, sourcing local electricity and reducing climate change impacts. Considering an economic approach, low photovoltaic panel coverage would probably be more attractive. However, even with a 10% area of photovoltaic panels, the environmental footprint would already significantly decrease. It is expected that significant improvements in microalgae productivity or more advanced production processes should rapidly enhance these performances.

Data and non-linear models for the estimation of biomass growth and carbon fixation in managed forests.

The data and analyses presented support the research article entitled "Coupling partial-equilibrium and dynamic biogenic carbon models to assess future transport scenarios in France" (Albers et al., 2019). Carbon sequestration and storage in forestry products (e.g. transport fuels) is sought as a climate change mitigation option. The data presented support and inform dynamic modelling approaches to predict biomass growth and carbon fixation dynamics, of a tree or forest stand, over specific rotation lengths. Data consists of species-specific yield tables, parameters for non-linear growth models and allometric equations. Non-linear growth models and allometric equations are listed and described. National statistics and surveys of the wood supply chain serve to identify main tree species, standing wood volumes and distributions within specific geographies; here corresponding to managed forests in France. All necessary data and methods for the computation of the annual fixation flows are presented.

Resource depletion potentials from bottom-up models: Population dynamics and the Hubbert peak theory.

Life cycle impact assessment uses so-called characterization factors to address different types of environmental impact (e.g. climate change, particulate matter, land use…). For the topic of resource depletion, a series of proposals was based on heuristic and formal arguments, but without the use of expert-based models from relevant research areas. A recent study in using fish population models has confirmed the original proposal for characterization factors for biotic resources of the nineties. Here we trace the milestones of the arguments and the designs of resource depletion, delivering an ecological-based foundation for the biotic case, and extend it by a novel analysis of the Hubbert peak theory for the abiotic case. We show that the original abiotic depletion potential, used for two decades in life cycle assessment, estimates accurately a marginal depletion characterization factor obtained from a dynamic model of the available reserve. This is illustrated for 29 metal resources using published data.

A tool to guide the selection of impact categories for LCA studies by using the representativeness index.

Understanding the environmental profile of a product computed from the Life Cycle Assessment (LCA) framework is sometimes challenging due to the high number of environmental indicators involved. The objective here, in guiding interpretation of LCA results, is to highlight the importance of each impact category for each product alternative studied. For a given product, the proposed methodology identifies the impact categories that are worth focusing on, relatively to a whole set of products from the same cumulated database. The approach extends the analysis of Representativeness Indices (RI) developed by Esnouf et al. (2018). It proposes a new operational tool for calculating RIs at the level of impact categories for a Life Cycle Inventory (LCI) result. Impact categories and LCI results are defined as vectors within a standardized vector space and a procedure is proposed to treat issues coming from the correlation of impact category vectors belonging to the same Life Cycle Impact Assessment (LCIA) method. From the cumulated ecoinvent database, LCI results of the Chinese and the German electricity mixes illustrate the method. Relevant impact categories of the EU-standardized ILCD method are then identified. RI results from all products of a cumulated LCI database were therefore analysed to assess the main tendencies of the impact categories of the ILCD method. This operational approach can then significantly contribute to the interpretation of the LCA results by pointing to the specificities of the inventories analysed and for identifying the main representative impact categories.

Representativeness of environmental impact assessment methods regarding Life Cycle Inventories.

Life Cycle Assessment (LCA) characterises all the exchanges between human driven activities and the environment, thus representing a powerful approach for tackling the environmental impact of a production system. However, LCA practitioners must still choose the appropriate Life Cycle Impact Assessment (LCIA) method to use and are expected to justify this choice: impacts should be relevant facing the concerns of the study and misrepresentations should be avoided. This work aids practitioners in evaluating the adequacy between the assessed environmental issues and studied production system. Based on a geometrical standpoint of LCA framework, Life Cycle Inventories (LCIs) and LCIA methods were localized in the vector space spanned by elementary flows. A proximity measurement, the Representativeness Index (RI), is proposed to explore the relationship between those datasets (LCIs and LCIA methods) through an angular distance. RIs highlight LCIA methods that measure issues for which the LCI can be particularly harmful. A high RI indicates a close proximity between a LCI and a LCIA method, and highlights a better representation of the elementary flows by the LCIA method. To illustrate the benefits of the proposed approach, representativeness of LCIA methods regarding four electricity mix production LCIs from the ecoinvent database are presented. RIs for 18 LCIA methods (accounting for a total of 232 impact categories) were calculated on these LCIs and the relevance of the methods are discussed. RIs prove to be a criterion for distinguishing the different LCIA methods and could thus be employed by practitioners for deeper interpretations of LCIA results.

Environmental assessment of nutrient recycling from biological pig slurry treatment--impact of fertilizer substitution and field emissions.

Pig slurry treatment is an important means in reducing nitrogen loads applied to farmland. Solid phase separation prior to biological treatment further allows for recovering phosphorus with the solid phase. The organic residues from the pig slurry treatment can be applied as organic fertilizers to farmland replacing mineral fertilizers. The environmental impacts of nutrient recycling from aerobic, biological pig slurry treatment were evaluated applying the life cycle assessment (LCA) methodology. LCA results revealed that direct field emissions from organic fertilizer application and the amount of avoided mineral fertilizers dominated the environmental impacts. A modified plant available nitrogen calculation (PAN) was introduced taking into account calculated nitrogen emissions from organic fertilizer application. Additionally, an equation for calculating the quantity of avoided mineral fertilizers based on the modified PAN calculation was proposed, which accounted for nitrogen emissions from mineral fertilizer application.

Life-cycle assessment of microalgae culture coupled to biogas production.

Due to resource depletion and climate change, lipid-based algal biofuel has been pointed out as an interesting alternative because of the high productivity of algae per hectare and per year and its ability to recycle CO(2) from flue gas. Another option for taking advantage of the energy content of the microalgae is to directly carry out anaerobic digestion of raw algae in order to produce methane and recycle nutrients (N, P and K). In this study, a life-cycle assessment (LCA) of biogas production from the microalgae Chlorella vulgaris is performed and the results are compared to algal biodiesel and to first generation biodiesels. These results suggest that the impacts generated by the production of methane from microalgae are strongly correlated with the electric consumption. Progresses can be achieved by decreasing the mixing costs and circulation between different production steps, or by improving the efficiency of the anaerobic process under controlled conditions. This new bioenergy generating process strongly competes with others biofuel productions.

Life-cycle assessment of biodiesel production from microalgae.

This paper provides an analysis of the potential environmental impacts of biodiesel production from microalgae. High production yields of microalgae have called forth interest of economic and scientific actors but it is still unclear whether the production of biodiesel is environmentally interesting and which transformation steps need further adjustment and optimization. A comparative LCA study of a virtual facility has been undertaken to assessthe energetic balance and the potential environmental impacts of the whole process chain, from the biomass production to the biodiesel combustion. Two different culture conditions, nominal fertilizing or nitrogen starvation, as well as two different extraction options, dry or wet extraction, have been tested. The best scenario has been compared to first generation biodiesel and oil diesel. The outcome confirms the potential of microalgae as an energy source but highlights the imperative necessity of decreasing the energy and fertilizer consumption. Therefore control of nitrogen stress during the culture and optimization of wet extraction seem to be valuable options. This study also emphasizes the potential of anaerobic digestion of oilcakes as a way to reduce external energy demand and to recycle a part of the mineral fertilizers.

Microbial interactions within a cheese microbial community.

The interactions that occur during the ripening of smear cheeses are not well understood. Yeast-yeast interactions and yeast-bacterium interactions were investigated within a microbial community composed of three yeasts and six bacteria found in cheese. The growth dynamics of this community was precisely described during the ripening of a model cheese, and the Lotka-Volterra model was used to evaluate species interactions. Subsequently, the effects on ecosystem functioning of yeast omissions in the microbial community were evaluated. It was found both in the Lotka-Volterra model and in the omission study that negative interactions occurred between yeasts. Yarrowia lipolytica inhibited mycelial expansion of Geotrichum candidum, whereas Y. lipolytica and G. candidum inhibited Debaryomyces hansenii cell viability during the stationary phase. However, the mechanisms involved in these interactions remain unclear. It was also shown that yeast-bacterium interactions played a significant role in the establishment of this multispecies ecosystem on the cheese surface. Yeasts were key species in bacterial development, but their influences on the bacteria differed. It appeared that the growth of Arthrobacter arilaitensis or Hafnia alvei relied less on a specific yeast function because these species dominated the bacterial flora, regardless of which yeasts were present in the ecosystem. For other bacteria, such as Leucobacter sp. or Brevibacterium aurantiacum, growth relied on a specific yeast, i.e., G. candidum. Furthermore, B. aurantiacum, Corynebacterium casei, and Staphylococcus xylosus showed reduced colonization capacities in comparison with the other bacteria in this model cheese. Bacterium-bacterium interactions could not be clearly identified.