Comparing Environmental Impacts of Single-Junction Silicon and Silicon/Perovskite Tandem Photovoltaics-A Prospective Life Cycle Assessment.

Tandem photovoltaics applying perovskite on silicon are considered to be a possible route to sustaining continuous efficiency improvements and price reductions. A meaningful market share for such tandems is, however, at least a decade away. Herein, a comprehensive prospective life cycle assessment was conducted, comparing the full life cycle of monofacial and bifacial silicon/perovskite tandem panels with single-junction silicon panels produced up to 2050. The end-of-life included the recovery of silicon and silver. Climate change impacts per kilowatt hour were projected to decrease by two-thirds over time. Tandem panels are expected to reach impacts of 8-10 g CO2-eq/kWh in 2050, while single-junction panels may reach 11-13 g CO2-eq/kWh in 2050. Other midpoint impact categories with substantial contributions to damaging human health and ecosystem quality were toxicity, particulate matter formation, and acidification, with tandems having lower impacts in each category. Reductions in impacts over time are mainly the result of grid mix decarbonization and panel efficiency improvements. Balance-of-system and recycling were found to contribute substantially to these impact categories. To ensure that tandem panels provide environmental benefits, annual degradation rates should not exceed 1% for monofacial or 3% for bifacial tandems, and refurbishment of panels with advanced degradation is crucial.

Evaluating the Environmental Sustainability of Alternative Ways to Produce Benzene, Toluene, and Xylene.

The petrochemical industry can reduce its environmental impacts by moving from fossil resources to alternative carbon feedstocks. Biomass and plastic waste-based production pathways have recently been developed for benzene, toluene, and xylene (BTX). This study evaluates the environmental impacts of these novel BTX pathways at a commercial and future (2050) scale, combining traditional life cycle assessment with absolute environmental sustainability assessment using the planetary boundary concept. We show that plastic waste-based BTX has lower environmental impacts than fossil BTX, including a 12% decrease in greenhouse gas (GHG) emissions. Biomass-based BTX shows greater GHG emission reductions (42%), but it causes increased freshwater consumption and eutrophication. Toward 2050, GHG emission reductions become 75 and 107% for plastic waste and biobased production, respectively, compared to current fossil-BTX production. When comparing alternative uses of plastic waste, BTX production has larger climate benefits than waste incineration with energy recovery with a GHG benefit of 1.1 kg CO2-equiv/kg plastic waste. For biomass (glycerol)-based BTX production, other uses of glycerol are favorable over BTX production. While alternative BTX production pathways can decrease environmental impacts, they still transgress multiple planetary boundaries. Further impact reduction efforts are thus required, such as using other types of (waste) biomass, increasing carbon recycling, and abatement of end-of-life emissions.

Environmental Impact Prediction of a New Tire Vulcanization Activator.

Zinc oxide (ZnO) is the most common curing activator used to manufacture tires. To minimize environmental impacts by decreasing the zinc content and rolling resistance of tires, ZnO nanoparticles (NPs) anchored on SiO2 NPs (ZnO@SiO2) are currently under development as new activators at the pilot scale. Here, we applied prospective life cycle assessment to predict the impacts on human health, ecosystem quality, and resource scarcity of synthesizing ZnO@SiO2 for the production of passenger car tires at an industrial scale. We found that the life cycle impacts of the synthesis are expected to decrease by 89 to 96% between the pilot and industrial scale. The largest contributors to the synthesis of ZnO@SiO2 were electricity consumption and waste treatment of the solvent. Using the new activator for tire production led to potential reductions of 9 to 12% in life cycle impacts compared to tires that are currently in use. Those reductions were due to the expected decrease in rolling resistance, leading to lower fuel consumption, which outweighed the additional environmental impacts of the synthesis, as well as the potential decrease in lifetime. Our work highlights an opportunity for manufacturers to mitigate their impacts over the full life cycle of the tire.

The potential of emerging bio-based products to reduce environmental impacts.

The current debate on the sustainability of bio-based products questions the environmental benefits of replacing fossil- by bio-resources. Here, we analyze the environmental trade-offs of 98 emerging bio-based materials compared to their fossil counterparts, reported in 130 studies. Although greenhouse gas life cycle emissions for emerging bio-based products are on average 45% lower (-52 to -37%; 95% confidence interval), we found a large variation between individual bio-based products with none of them reaching net-zero emissions. Grouped in product categories, reductions in greenhouse gas emissions ranged from 19% (-52 to 35%) for bioadhesives to 73% (-84 to -54%) for biorefinery products. In terms of other environmental impacts, we found evidence for an increase in eutrophication (369%; 163 to 737%), indicating that environmental trade-offs should not be overlooked. Our findings imply that the environmental sustainability of bio-based products should be evaluated on an individual product basis and that more radical product developments are required to reach climate-neutral targets.

Predicting and improving the microbial removal of organic micropollutants during wastewater treatment: A review.

Organic micropollutants (OMPs) consist of widely used chemicals such as pharmaceuticals and pesticides that can persist in surface and groundwaters at low concentrations (ng/L to µg/L) for a long time. The presence of OMPs in water can disrupt aquatic ecosystems and threaten the quality of drinking water sources. Wastewater treatment plants (WWTPs) rely on microorganisms to remove major nutrients from water, but their effectiveness at removing OMPs varies. Low removal efficiency might be the result of low concentrations, inherent stable chemical structures of OMPs, or suboptimal conditions in WWTPs. In this review, we discuss these factors, with special emphasis on the ongoing adaptation of microorganisms to degrade OMPs. Finally, recommendations are drawn to improve the prediction of OMP removal in WWTPs and to optimize the design of new microbial treatment strategies. OMP removal seems to be concentration-, compound-, and process-dependent, which poses a great complexity to develop accurate prediction models and effective microbial processes targeting all OMPs.

The many greenhouse gas footprints of green hydrogen.

Green hydrogen could contribute to climate change mitigation, but its greenhouse gas footprint varies with electricity source and allocation choices. Using life-cycle assessment we conclude that if electricity comes from additional renewable capacity, green hydrogen outperforms fossil-based hydrogen. In the short run, alternative uses of renewable electricity likely achieve greater emission reductions.

Do initial concentration and activated sludge seasonality affect pharmaceutical biotransformation rate constants?

Pharmaceuticals find their way to the aquatic environment via wastewater treatment plants (WWTPs). Biotransformation plays an important role in mitigating environmental risks; however, a mechanistic understanding of involved processes is limited. The aim of this study was to evaluate potential relationships between first-order biotransformation rate constants (kb) of nine pharmaceuticals and initial concentration of the selected compounds, and sampling season of the used activated sludge inocula. Four-day bottle experiments were performed with activated sludge from WWTP Groesbeek (The Netherlands) of two different seasons, summer and winter, spiked with two environmentally relevant concentrations (3 and 30 nM) of pharmaceuticals. Concentrations of the compounds were measured by LC-MS/MS, microbial community composition was assessed by 16S rRNA gene amplicon sequencing, and kb values were calculated. The biodegradable pharmaceuticals were acetaminophen, metformin, metoprolol, terbutaline, and phenazone (ranked from high to low biotransformation rates). Carbamazepine, diatrizoic acid, diclofenac, and fluoxetine were not converted. Summer and winter inocula did not show significant differences in microbial community composition, but resulted in a slightly different kb for some pharmaceuticals. Likely microbial activity was responsible instead of community composition. In the same inoculum, different kb values were measured, depending on initial concentration. In general, biodegradable compounds had a higher kb when the initial concentration was higher. This demonstrates that Michealis-Menten kinetic theory has shortcomings for some pharmaceuticals at low, environmentally relevant concentrations and that the pharmaceutical concentration should be taken into account when measuring the kb in order to reliably predict the fate of pharmaceuticals in the WWTP. KEY POINTS: • Biotransformation and sorption of pharmaceuticals were assessed in activated sludge. • Higher initial concentrations resulted in higher biotransformation rate constants for biodegradable pharmaceuticals. • Summer and winter inocula produced slightly different biotransformation rate constants although microbial community composition did not significantly change.

Ammonia and chromate interaction explains unresolved Hyalella azteca mortality in Flanders' sediment bioassays.

Agricultural, industrial and household chemicals are emitted in large rivers along populated areas, transported by water and deposited in sediments, posing (eco)toxicological risks. Sediments have received less attention than surface waters, likely because of the intrinsic complexity of interactions between sediment constituents complicating correct framing of exposures. Sadly, thorough assessment of the in situ behavior of sediment constituents in bioassays is often not practical. Alternatively, we related physicochemical properties of sediments from field testing to results from bioassays. The case study covers Flemish sediment (incl. Scheldt and Meuse) and mortality of Hyalella azteca, a sensitive bio-indicator. Though variable across Flanders' main water bodies, heavy metals and ammoniacal nitrogen dominate the observed toxicity according to toxic unit (TU) assessments. Depending on the water body we explain between 50 and 90% of the variance in the observed H. azteca mortality, substantially more than previous ecotoxicity studies. We attribute the remaining variance to potential incoherently documented biophysicochemical sediment properties and concentrations of non-target biocides, testing conditions/set-ups and/or species variabilities. We discuss the relative influence of heavy metals/metaloxides, nitrogen (e.g. fertilizer), polycyclic aromatics and organochlorides. We highlight both direct and indirect mortality mechanisms. We note potential synergetic mixture effects between ammoniacal nitrogen and chromium. Such synergy may be phenomenological of 'standard' aerobic bioassays, and prove a complementary method alongside the 'acid-volatile sulfide test' to more effectively link concentration to toxicity. Future study ought to include variation in biophysicochemical properties between sampling locations and batch bioassays. Our approach enables water managers to interpret their monitoring data by converting sediment concentrations to H. azteca mortality and prioritize substances that contribute most.

Simulating behavior of petroleum compounds during refinery effluent treatment using the SimpleTreat model.

Distribution and elimination of petroleum products can be predicted in aerobic wastewater treatment plants (WWTPs) using models such as multimedia fate model SimpleTreat. An advantage of the SimpleTreat model is that it only requires a few basic properties of a chemical in wastewater to calculate partitioning, biodegradation and ultimately emissions to air, surface water and produced sludge. The SimpleTreat model structure reflects a WWTP scheme. However, refinery WWTPs typically incorporate more advanced treatment processes such as dissolved air flotation (DAF), a process that clarifies wastewaters by the removal of suspended matter such as oil or solids. The objective of this work was to develop a WWTP removal model that includes DAF treatment. To understand how including a DAF in the model affects the predicted concentrations of petroleum constituents in effluent, we replaced the primary sedimentation module in SimpleTreat with a module simulating DAF. Subsequently, we compared results from the WWTP-DAF model with results obtained with the original SimpleTreat model for a library of over 1500 representative hydrocarbon constituents. The increased air-water exchange in a WWTP-DAF unit resulted in higher predicted removal of volatile constituents. Predicted removal with DAF was on average 17% larger than removal with primary sedimentation. We compared modelled results with measured removal data from the literature, which supported that this model refinement continues to improve the technical basis of assessment of petroleum products.

Impact of energy flow optimization on the mitigation of environmental consequences and costs in greenhouse cucumber production.

Cucumber, as a major cultivated plant in Iran, takes up more than 80% of greenhouse production. So, improving the production efficiency can save energy, reduce the environmental consequences and production costs, and also create a lot of job opportunities. The present study aimed to investigate the impact of energy flow optimization on the environmental impacts and costs in greenhouse cucumber production by data envelopment analysis (DEA) and life cycle assessment (LCA) methods. For environmental assessment, human health damage, ecosystem damage, and resource scarcity were considered and analyzed in the form of 8, 12, and 2 impact categories, respectively, using the ReCiPe2016 (H) method on endpoint level. Required data were collected through questionnaire from 30 cucumber growers. The results of the current status of environmental impacts showed the major contribution of fuels (natural gas and diesel) in all three main impact categories. Based on DEA analysis, 19 greenhouses (63%) were identified as inefficient units with a mean efficiency score of 0.70 (TE = 0.7). The highest inefficiency was related to the manure (72%), electricity (71.7%), and fuel (59%), respectively. Electricity and manure showed the highest saving potential, while the highest contribution to total energy saving was related to fuel (87%). Environmental analysis of optimized greenhouses showed that efficient use of inputs can reduce all environmental impacts between 7 and 80%, which highlights the importance of efficient resource management in this study. Also, production costs were decreased by about 67 $ tonne-1 (196 to 129 $) after the optimization of the units.

Chemical footprint of pesticides used in citrus orchards based on canopy deposition and off-target losses.

The application of chemical pesticides is one of the main practices in citrus orchards. But during this operation, a considerable amount of sprayed volume is emitted to off-target areas using air-blast sprayers. The present study aimed to investigate pesticides' toxicological impacts in citrus orchards through determining the proportion of pesticides in different areas (air, soil, and canopy), which facilitate toxicity assessment of pesticides in citrus orchards. In this study, human toxicity and freshwater ecotoxicity impacts were assessed using USEtox 2.1 modeling approach for five active ingredients used in citrus orchards in the south of Iran. Different spraying scenarios were defined based on two types of nozzles (Hallow-cone and Teejet full-cone) and three levels of pressure (30, 40, and 50 bar) in two orchards with different row spacing. Results showed that only 26-37% of spray solution is deposited on the target with much loss to areas between tree canopies on the row. Scenario 1 (Hallow-cone nozzle with spraying pressure as 30 bar) shows the highest spraying efficiency in the both orchards (37% and 34% for Tangerine and Lemon orchards, respectively). Air emissions were obtained around 17 and 18% for hollow-cone and Teejet full-cone nozzles, respectively. The final inventory was obtained considering evaporation rate of active ingredients from soil surface and leaves. Based on the results obtained from toxicological impact assessment, Thiacloprid and Carbendazim had the highest negative environmental impacts on human health and freshwater aquatic ecosystem, respectively. Based on the results, soil emissions were identified as more critical than air emissions in terms of environmental consequences. It can be attributed to the higher characterization factor and deposition on the soil in comparison to the air. The present study provided well-founded information on the environmental performance of production systems by estimating the relevant emissions of pesticides to different compartments and determined the human and freshwater toxicity impact profiles, which assist decision-makers and LCA-practitioners to have a better perspective about pesticides behavior in receiving compartment.

Reliable and representative in silico predictions of freshwater ecotoxicological hazardous concentrations.

A reliable quantification of the potential effects of chemicals on freshwater ecosystems requires ecotoxicological response data for a large set of species which is typically not available in practice. In this study, we propose a method to estimate hazardous concentrations (HCs) of chemicals on freshwater ecosystems by combining two in silico approaches: quantitative structure activity relationships (QSARs) and interspecies correlation estimation (ICE) models. We illustrate the principle of our QSAR-ICE method by quantifying the HCs of 51 chemicals at which 50% and 5% of all species are exposed above the concentration causing acute effects. We assessed the bias of the HCs, defined as the ratio of the HC based on measured ecotoxicity data and the HC based on in silico data, as well as the statistical uncertainty, defined as the ratio of the 95th and 5th percentile of the HC. Our QSAR-ICE method resulted in a bias that was comparable to the use of measured data for three species, as commonly used in effect assessments: the average bias of the QSAR-ICE HC50 was 1.2 and of the HC5 2.3 compared to 1.2 when measured data for three species were used for both HCs. We also found that extreme statistical uncertainties (>105) are commonly avoided in the HCs derived with the QSAR-ICE method compared to the use of three measurements with statistical uncertainties up to 1012. We demonstrated the applicability of our QSAR-ICE approach by deriving HC50s for 1,223 out of the 3,077 organic chemicals of the USEtox database. We conclude that our QSAR-ICE method can be used to determine HCs without the need for additional in vivo testing to help prioritise which chemicals with no or few ecotoxicity data require more thorough assessment.

Global relative species loss due to first-generation biofuel production for the transport sector.

The global demand for biofuels in the transport sector may lead to significant biodiversity impacts via multiple human pressures. Biodiversity assessments of biofuels, however, seldom simultaneously address several impact pathways, which can lead to biased comparisons with fossil fuels. The goal of the present study was to quantify the direct influence of habitat loss, water consumption and greenhouse gas (GHG) emissions on potential global species richness loss due to the current production of first-generation biodiesel from soybean and rapeseed and bioethanol from sugarcane and corn. We found that the global relative species loss due to biofuel production exceeded that of fossil petrol and diesel production in more than 90% of the locations considered. Habitat loss was the dominating stressor with Chinese corn, Brazilian soybean and Brazilian sugarcane having a particularly large biodiversity impact. Spatial variation within countries was high, with 90th percentiles differing by a factor of 9 to 22 between locations. We conclude that displacing fossil fuels with first-generation biofuels will likely negatively affect global biodiversity, no matter which feedstock is used or where it is produced. Environmental policy may therefore focus on the introduction of other renewable options in the transport sector.

Confronting variability with uncertainty in the ecotoxicological impact assessment of down-the-drain products.

The use of down-the-drain products and the resultant release of chemicals may lead to pressures on the freshwater environment. Ecotoxicological impact assessment is a commonly used approach to assess chemical products but is still influenced by several uncertainty and variability sources. As a result, the robustness and reliability of such assessments can be questioned. A comprehensive and systematic assessment of these sources is, therefore, needed to increase their utility and credibility. In this study, we present a method to systematically analyse the uncertainty and variability of the potential ecotoxicological impact (PEI) of chemicals using a portfolio of 54 shampoo products. We separately quantified the influence of the statistical uncertainty in the prediction of physicochemical properties and freshwater toxicity as predicted from Quantitative Structure-Property Relationships (QSPRs) and Quantitative Structure-Activity Relationships (QSARs) respectively, and of various sources of spatial and technological variability as well as variability in consumer habits via 2D Monte Carlo simulations. Overall, the variation in the PEIs of shampoo use was mainly the result of uncertainty due to the use of toxicity data from three species only. All uncertainty sources combined resulted in PEIs ranging on average over seven orders of magnitude (ratio of the 90th to the 10th percentile) so that an absolute quantification of the ecological risk would not be meaningful. In comparison, variation in shampoo composition was the most influential source of variability, although less than compared to uncertainty, leading to PEIs ranging over three orders of magnitude. Increasing the number of toxicity data by increasing the number of species, either through additional measurements or ecotoxicological modelling (e.g. using Interspecies Correlation Equations), should get priority to improve the reliability of PEIs. These conclusions are not limited to shampoos but are applicable more generally to the down-the-drain products since they all have similar data limitations and associated uncertainties relating to the availability of ecotoxicity data and variability in consumer habits and use.

Quantifying variability in removal efficiencies of chemicals in activated sludge wastewater treatment plants - a meta-analytical approach.

Large variations in removal efficiencies (REs) of chemicals have been reported for monitoring studies of activated sludge wastewater treatment plants (WWTPs). In this work, we conducted a meta-analysis on REs (1539 data points) for a set of 209 chemicals consisting of fragrances, surfactants, and pharmaceuticals in order to assess the drivers of the variability relating to inherent properties of the chemicals and operational parameters of activated sludge WWTPs. For a reduced dataset (n = 542), we developed a mixed-effect model (meta-regression) to explore the observed variability in REs for the chemicals using three chemical specific factors and four WWTP-related parameters. The overall removal efficiency of the set of chemicals was 82.1% (95% CI 75.2-87.1%, N = 1539). Our model accounted for 17% of the total variability in REs, while the process-based model SimpleTreat did not perform better than the average of the measured REs. We identified that, after accounting for other factors potentially influencing RE, readily biodegradable compounds were better removed than non-readily biodegradable ones. Further, we showed that REs increased with increasing sludge retention times (SRTs), especially for non-readily biodegradable compounds. Finally, our model highlighted a decrease in RE with increasing KOC. The counterintuitive relationship to KOC stresses the need for a better understanding of electrochemical interactions influencing the RE of ionisable chemicals. In addition, we highlighted the need to improve the modelling of chemicals that undergo deconjugation when predicting RE. Our meta-analysis represents a first step in better explaining the observed variability in measured REs of chemicals. It can be of particular help to prioritize the improvements required in existing process-based models to predict removal efficiencies of chemicals in WWTPs.

Variability of Greenhouse Gas Footprints of Field Tomatoes Grown for Processing: Interyear and Intercountry Assessment.

Our study provides an integrated analysis of the variability of greenhouse gas (GHG) footprints of field-grown tomatoes for processing. The global farm-specific data set of 890 observations across 14 countries over a three-year period (2013-2015) was obtained from farms grown under Unilever's sustainable agricultural code. It represents on average 3% of the annual global production of processing tomatoes: insights can be used to help inform corporate sourcing strategies and certification schemes. The median GHG footprint ranged from 18 in Chile to 61 kg CO2-equiv per tonne of tomatoes in India, lower than results reported in other studies. We found that footprints are more consistent within countries than between them. Using linear mixed effect models, we quantified the relative influence of environmental conditions and farm management factors. Key variables were area of production and the method of fertilizer application. GHG footprints decreased with increasing area of production to a threshold of 17.4 ha. Farms using single fertilizer application methods in general had a larger GHG footprint than those using a combination of methods. We conclude that farm management factors should be prioritized for future data collection, and more stringent guidance on acceptable practices is required if greater comparability of outcomes is needed either within a scheme, such as the Unilever's sustainable agriculture code, or between schemes.

Estimation of chemical emissions from down-the-drain consumer products using consumer survey data at a country and wastewater treatment plant level.

Deriving reliable estimates of chemical emissions to the environment is a key challenge for impact and risk assessment methods and typically the associated uncertainty is not characterised. We have developed an approach to spatially quantify annual chemical emission loads to the aquatic environment together with their associated uncertainty using consumer survey data and publicly accessible and non-confidential data sources. The approach is applicable for chemicals widely used across a product sector. Product usage data from consumer survey studies in France, the Netherlands, South Korea and the USA were combined with information on typical product formulations, wastewater removal rates, and the spatial distribution of populations and wastewater treatment plants (WWTPs) in the four countries. Results are presented for three chemicals common to three types of personal care products (shampoo, conditioner, and bodywash) at WWTP and national levels. Uncertainty in WWTP-specific emission estimates was characterised with a 95% confidence interval and ranged up to a factor of 4.8 around the mean, mainly due to uncertainty associated with removal efficiency. Estimates of whole country product usage were comparable to total market estimates derived from sectorial market sales data with differences ranging from a factor 0.8 (for the Netherlands) to 5 (for the USA). The proposed approach is suitable where measured data on chemical emissions is missing and is applicable for use in risk assessments and chemical footprinting methods when applied to specific product categories.

Life cycle energy use, costs, and greenhouse gas emission of broiler farms in different production systems in Iran-a case study of Alborz province.

In order to achieve sustainable development in agriculture, it is necessary to quantify and compare the energy, economic, and environmental aspects of products. This paper studied the energy, economic, and greenhouse gas (GHG) emission patterns in broiler chicken farms in the Alborz province of Iran. We studied the effect of the broiler farm size as different production systems on the energy, economic, and environmental indices. Energy use efficiency (EUE) and benefit-cost ratio (BCR) were 0.16 and 1.11, respectively. Diesel fuel and feed contributed the most in total energy inputs, while feed and chicks were the most important inputs in economic analysis. GHG emission calculations showed that production of 1000 birds produces 19.13 t CO2-eq and feed had the highest share in total GHG emission. Total GHG emissions based on different functional units were 8.5 t CO2-eq per t of carcass and 6.83 kg CO2-eq per kg live weight. Results of farm size effect on EUE revealed that large farms had better energy management. For BCR, there was no significant difference between farms. Lower total GHG emissions were reported for large farms, caused by better management of inputs and fewer bird losses. Large farms with more investment had more efficient equipment, resulting in a decrease of the input consumption. In view of our study, it is recommended to support the small-scale broiler industry by providing subsidies to promote the use of high-efficiency equipment. To decrease the amount of energy usage and GHG emissions, replacing heaters (which use diesel fuel) with natural gas heaters can be considered. In addition to the above recommendations, the use of energy saving light bulbs may reduce broiler farm electricity consumption.

Spatial variability versus parameter uncertainty in freshwater fate and exposure factors of chemicals.

We compared the influence of spatial variability in environmental characteristics and the uncertainty in measured substance properties of seven chemicals on freshwater fate factors (FFs), representing the residence time in the freshwater environment, and on exposure factors (XFs), representing the dissolved fraction of a chemical. The influence of spatial variability was quantified using the SimpleBox model in which Europe was divided in 100 × 100 km regions, nested in a regional (300 × 300 km) and supra-regional (500 × 500 km) scale. Uncertainty in substance properties was quantified by means of probabilistic modelling. Spatial variability and parameter uncertainty were expressed by the ratio k of the 95%ile and 5%ile of the FF and XF. Our analysis shows that spatial variability ranges in FFs of persistent chemicals that partition predominantly into one environmental compartment was up to 2 orders of magnitude larger compared to uncertainty. For the other (less persistent) chemicals, uncertainty in the FF was up to 1 order of magnitude larger than spatial variability. Variability and uncertainty in freshwater XFs of the seven chemicals was negligible (k < 1.5). We found that, depending on the chemical and emission scenario, accounting for region-specific environmental characteristics in multimedia fate modelling, as well as accounting for parameter uncertainty, can have a significant influence on freshwater fate factor predictions. Therefore, we conclude that it is important that fate factors should not only account for parameter uncertainty, but for spatial variability as well, as this further increases the reliability of ecotoxicological impacts in LCA.

Global spatially explicit CO2 emission metrics for forest bioenergy.

Emission metrics aggregate climate impacts of greenhouse gases to common units such as CO2-equivalents (CO2-eq.). Examples include the global warming potential (GWP), the global temperature change potential (GTP) and the absolute sustained emission temperature (aSET). Despite the importance of biomass as a primary energy supplier in existing and future scenarios, emission metrics for CO2 from forest bioenergy are only available on a case-specific basis. Here, we produce global spatially explicit emission metrics for CO2 emissions from forest bioenergy and illustrate their applications to global emissions in 2015 and until 2100 under the RCP8.5 scenario. We obtain global average values of 0.49 ± 0.03 kgCO2-eq. kgCO2(-1) (mean ± standard deviation) for GWP, 0.05 ± 0.05 kgCO2-eq. kgCO2(-1) for GTP, and 2.14·10(-14) ± 0.11·10(-14) °C (kg yr(-1))(-1) for aSET. We explore metric dependencies on temperature, precipitation, biomass turnover times and extraction rates of forest residues. We find relatively high emission metrics with low precipitation, long rotation times and low residue extraction rates. Our results provide a basis for assessing CO2 emissions from forest bioenergy under different indicators and across various spatial and temporal scales.