Including metal atmospheric fate and speciation in soils for terrestrial ecotoxicity in life cycle impact assessment

Purpose

The aim of the study is to calculate regionalized characterization factors for the atmospheric emissions of metals transferred to soil for zinc, copper, and nickel taking into account the atmospheric fate and speciation.

Methods

In order to calculate characterization factors for all possible atmospheric emission locations around the world, the link between atmospheric deposition with regionalized soil fate factors and bioavailability factors accounting for the metal’s speciation was established. The methodology to develop the regionalized fate factors and characterization factors is threefold. First, the emitted metal fraction that is deposited on soils is calculated from atmospheric source-receptor matrices providing for each emission location the fraction of an emission that is deposited on each worldwide receiving cell (2°?×?2.5° resolution). Second, the fraction of metal deposited in different soil types is determined by overlapping the deposition map with a soil map, based on the 4513 different soil types from the Harmonized World Soil Database. Third, bioavailability factors are calculated for each soil type, which allows determining the bioavailable fraction of the deposited metal depending on the soil properties. Combining these steps with the effect factors results in a series of terrestrial ecotoxicological characterization factors. These characterization factors are then applied in an illustrative example and compared to results obtained with generic characterization factors. The case study focuses on the electricity production process in Québec, whose ecosystem impacts are currently dominated by metal ecotoxicity impacts. The uncertainty due to the spatial variability of the impact is quantified.

Results and discussion

Our results show that regionalized characterization factors are over three orders of magnitude lower than generic characterization factors. They are presented on maps and their spatial variability was evaluated at different regional scales (region, country, world). The use of regionalized characterization factors with their spatial variability at different geographic resolution scales in the case study gives a result more or less precise depending on the level of resolution of the characterization factor applied (country or global-default). The impact scores of the three metals in the case study are three orders of magnitude lower when compared to the scores obtained with generic characterization factors.

Conclusions

The development of those regionalized characterization factors improves the terrestrial ecotoxicity assessment in life cycle impact assessment by taking into account the atmospheric fate and the speciation of the metal for new 3 metals for the different soil types in the world and by documenting their spatial variability.

     

Spatially explicit fate factors of phosphorous emissions to freshwater at the global scale

Purpose

The location of a phosphorus emission can strongly affect its expected fate in freshwater. To date, in Life Cycle Assessment (LCA), fate factors for phosphorus emissions have been derived for continents or large countries and had limited spatial resolution. These fate factors do not account sufficiently for local variations and are not applicable globally. In this paper, fate factors for freshwater eutrophication are derived for phosphorus emissions to freshwater on a global scale with a half-degree resolution.

Methods

For this purpose, a new global fate model for phosphorus has been developed on a half-degree resolution. The removal processes taken into account are grid-specific advection, phosphorus retention and water use. Aggregated fate factors based on archetypes and on administrative units are presented.

Results and discussion

The derived fate factors represent the persistence of phosphorus in the freshwater environment. The typical fate factor of phosphorus emissions to freshwater is 10?days and can vary more than 2 orders of magnitude among the grid cells (the 5th and 95th percentile are 0.8 and 310?days, respectively). Advection is the dominant removal process of phosphorus in freshwater (67.5%), followed by retention (27.6%) and water use (4.9%).

Conclusions

The results demonstrate inclusion of information on the location of phosphorus emissions to freshwater can improve the comparative power of the fate factor implementation in LCAs. The fate factors enable consistent assessment and comparison of freshwater eutrophication impacts at different locations across the globe.     

Freshwater ecotoxicity characterization factors for aluminum

Purpose

Aluminum (Al) is an abundant, non-essential element with complex geochemistry and aquatic toxicity. Considering its complex environmental behavior is critical for providing a reasonable estimate of its potential freshwater aquatic ecotoxicity in the context of Life Cycle Impact Assessment (LCIA).

Methods

Al characterization factors (CFs) are calculated using the following: (1) USEtox^? model version 2.1 for environmental fate, (2) MINEQL+ to estimate the distribution of Al between the solid phase precipitate and total dissolved Al, (3) WHAM 7 for Al speciation within the total dissolved phase, and (4) Biotic Ligand Model (BLM) and Free Ion Activity Model (FIAM) for ecotoxicity estimation for seven freshwater archetypes and default landscape properties for the European continent. The sensitivity of the CFs to aquatic chemistry parameters is calculated. New CFs are compared with Dong et al. (Chemosphere 112:26–33, 2014) and default CF calculated by USEtox 2.1.

Results and discussion

Al CFs vary over 5 orders of magnitude between the seven archetypes, with an arithmetic average CF_ave of 0.04 eq 1,4-DCB (recommended for use), geometric mean CF_geo of 0.0014 eq 1,4-DCB, and weighted average CF_wt of 0.026 eq 1,4-DCB. These values are lower (less toxic) than those for Cu, Ni, Zn, and Pb (with one exception). The effect factor (EF) contributed most to this variability followed by the bioavailability factor (BF), varying over 8 and 4 orders of magnitude, respectively. These revised CFs are 2–6 orders of magnitude lower than those presented by Dong et al. (Chemosphere 112:26–33, 2014) mainly because of consideration of Al precipitation.

Conclusions

Freshwater archetype-specific Al CFs for freshwater ecotoxicity that address the effect of Al speciation on bioavailability (BF) and ecotoxicity (EF) have been calculated, and a CF of 0.04 eq 1,4-DCB is recommended for use in generic LCA. For site-specific LCA, the choice of water chemistry and, in particular, pH, and consideration of metal precipitation could significantly influence results.

Practical implications

Incorporating estimates of metal speciation and its effect on aquatic toxicity is essential when conducting LCIA. Along with metal speciation estimates, the values derived from the definition of water chemistry parameters must also be included into LCIA. For site-generic assessments, we recommend using the arithmetic average of metal CFs. We also recommend using FIAM as a suitable alternative to BLM to estimate EF if the latter is not available. Consideration of metal speciation is essential for providing more realistic estimates of Al freshwater ecotoxicity in the context of LCIA.

     

Deriving characterization factors on freshwater ecotoxicity of graphene oxide nanomaterial for life cycle impact assessment

Purpose

Graphene oxide (GO) nanomaterial has found wide potential industrial applications, but its life cycle environmental impact is not fully understood mainly because of lack of characterization factors (CFs) for the life cycle impact assessment. In this paper, we report the derivation of CF for freshwater ecotoxicity of GO based on the USEtox method.

Methods

The CF is derived based on the toxic effect factor, fate factor, and exposure factor of GO in the aquatic environment. The toxic effect factor is extracted from mechanistic toxicity studies available in the literature. The fate factor is derived with the colloidal method, and the exposure factor is determined through Langmuir adsorption isotherm for interactions between GO and dissolve organic carbon. Additionally, both fate factor and exposure factor are re-calculated through the default mass-balanced model in USEtox. The apparent octanol-water partition coefficient (K _ow) required in the mass balanced model is determined via experiment. Other parameters are calculated according to the apparent K _ow.

Results and discussion

The study derives a CF of 777.5 potentially affected species (PAF) day m³ kg^?1 for GO with a fate factor of 27.2 days and an exposure factor of 0.93. Sensitivity analysis suggests that variability from the effect factor is the dominant source leading changes in CF. The uncertainty of CF value can vary between ～1 and 10³ PAF day m³ kg^?1. Comparison between the colloidal and the mass-balanced models indicates that heteroaggregation may be underestimated by using the apparent partition coefficient, and thus, a much higher estimate of fate factor is obtained from the mass-balanced model. Additionally, empirical formulae in the USEtox to correlate other coefficients with K _ow are not proper to calculate bioaccumulation and adsorption with dissolved organic carbon since a virtually a unit exposure factor is obtained.

Conclusion

The derived CFs can be readily incorporated into future toxicity assessment on GO. The fate factor is calculated in the colloidal model while adsorption of dissolved organic carbon onto GO surface should be derived from the Langmuir isotherm. Compared to the colloidal-based method, the conventional mass-balanced method may not be well applicable to GO due to the significant uncertainties in fate and exposure factors from applying the apparent partition coefficients. As three orders of magnitude variations in CF are caused by effect factor due to limited toxicity tests available for GO, more toxicological studies of GO on various species are needed in the future.

     

Development of a dynamic LCA approach for the freshwater ecotoxicity impact of metals and application to a case study regarding zinc fertilization

Purpose

Temporal variability is a major source of uncertainty in current life cycle assessment (LCA) practice. In this paper, the recently developed dynamic LCA approach is adapted to assess freshwater ecotoxicity impacts of metals. The objective is to provide relevant information regarding the distribution and magnitude of metal impacts over time and to show whether the dynamic approach significantly influences the conclusions of an LCA. An LCA of zinc fertilization in agriculture was therefore carried out.

Methods

Dynamic LCA is based on the temporal disaggregation of the inventory, which is then assessed using time-horizon-dependent characterization factors. The USEtox multimedia fate model is used to develop time-horizon-dependent characterization factors for the freshwater ecotoxicity impact of 18 metals. Mass balance equations are solved dynamically to obtain fate factors as a function of time, providing both instantaneous (impact at time t following a pulse emission) and cumulative (total time-integrated impact following a pulse emission) characterization factors (CFs).

Results and discussion

Time-horizon-dependent CFs for freshwater ecotoxicity depend on the emission compartment and the metal itself. The two variables clearly influence metal fate aspects such as the maximum mass loading reaching freshwater and the persistence time of metals into this compartment. The time needed to reach the total impact for each metal may exceed thousands of years, so the time horizon used in the analysis constitutes a determining factor. The case study reveals that the results of a classical LCA are always higher than those obtained from a dynamic LCA, especially for short time horizons. For instance, at the end of a 100-year fertilization treatment, only 25 % of the impacts obtained through traditional LCA occurred.

Conclusions

Results show that dynamic LCA enables assessing freshwater ecotoxicity impacts of metals over time, allowing decision makers to test the sensitivity of their results to the choice of a time horizon. For the particular case study of zinc fertilization over a period of 20 years, the use of time-horizon-dependent CFs is more important in determining the dynamics of impacts than the timing of emission.     

The influence of value choices in life cycle impact assessment of stressors causing human health damage

Purpose

This study analyzes the influence of value choices in impact assessment models for human health, such as the choice of time horizon, on life cycle assessment outcomes.

Methods

For 756 products, the human health damage score is calculated using three sets of characterization factors (CFs). The CFs represent seven human health impact assessment categories: water scarcity, tropospheric ozone formation, particulate matter formation, human toxicity, ionizing radiation, stratospheric ozone depletion, and climate change. Each set of CFs embeds a combination of value choices following the Cultural Theory, and reflects the individualist, hierarchist, or egalitarian perspective.

Results

We found that the average difference in human health damage score goes from 1 order of magnitude between the individualist and hierarchist perspectives to 2.5 orders of magnitude between the individualist and egalitarian perspectives. The difference in damage score of individual materials among perspectives depends on the combination of emissions driving the impact of both perspectives and can rise up to 5 orders of magnitude.

Conclusions

The value choices mainly responsible for the differences in results among perspectives are the choice of time horizon and inclusion of highly uncertain effects. A product comparison can be affected when the human health damage score of two products differ less than a factor of 5, or the comparing products largely differ in their emitted substances. Overall, our study implies that value choices in impact assessment modeling can modify the outcomes of a life cycle assessment (LCA) and thus the practical implication of decisions based on the results of an LCA.     

Exploring variability in methods and data sensitivity in carbon footprints of feed ingredients

Purpose

Production of feed is an important contributor to life cycle greenhouse gas emissions, or carbon footprints (CFPs), of livestock products. Consequences of methodological choices and data sensitivity on CFPs of feed ingredients were explored to improve comparison and interpretation of CFP studies. Methods and data for emissions from cultivation and processing, land use (LU), and land use change (LUC) were analyzed.

Method

For six ingredients (maize, wheat, palm kernel expeller, rapeseed meal, soybean meal, and beet pulp), CFPs resulting from a single change in methods and data were compared with a reference CFP, i.e., based on IPCC Tier 1 methods, and data from literature.

Results and discussion

Results show that using more detailed methods to compute N₂O emissions from cultivation hardly affected reference CFPs, except for methods to determine $ \mathrm{NO}_3^{-} $ leaching (contributing to indirect N₂O emissions) in which the influence is about ?7 to +12 %. Overall, CFPs appeared most sensitive to changes in crop yield and applied synthetic fertilizer N. The inclusion of LULUC emissions can change CFPs considerably, i.e., up to 877 %. The level of LUC emissions per feed ingredient highly depends on the method chosen, as well as on assumptions on area of LUC, C stock levels (mainly aboveground C and soil C), and amortization period.

Conclusions

We concluded that variability in methods and data can significantly affect CFPs of feed ingredients and hence CFPs of livestock products. Transparency in methods and data is therefore required. For harmonization, focus should be on methods to calculate $ \mathrm{NO}_3^{-} $ leaching and emissions from LULUC. It is important to consider LUC in CFP studies of food, feed, and bioenergy products.     

Metal toxicity characterization factors for marine ecosystems—considering the importance of the estuary for freshwater emissions

Purpose

The study develops site-dependent characterization factors (CFs) for marine ecotoxicity of metals emitted to freshwater, taking their passage of the estuary into account. To serve life cycle assessment (LCA) studies where emission location is often unknown, site-generic marine CFs were developed for metal emissions to freshwater and coastal seawater, respectively. The new CFs were applied to calculate endpoint impact scores for the same amount of metal emission to each compartment, to compare the relative ecotoxicity damages in freshwater and marine ecosystems in LCA.

Methods

Site-dependent marine CFs for emission to freshwater were calculated for 64 comparatively independent seas (large marine ecosystems, LMEs). The site-dependent CF was calculated as the product of fate factor (FF), bioavailability factor (BF), and effect factor (EF). USEtox modified with site-dependent parameters was extended with an estuary removal process to calculate FF. BF and EF were taken from Dong et al. Environ Sci Technol 50:269–278 (2016). Site-generic marine CFs were derived from site-dependent marine CFs. Different averaging principles were tested, and the approach representing estuary discharge rate was identified as the best one. Endpoint marine and freshwater metals CFs were developed to calculate endpoint ecotoxicity impact scores.

Results and discussion

Marine ecotoxicity CFs are 1.5 orders of magnitude lower for emission to freshwater than for emission to seawater for Cr, Cu, and Pb, due to notable removal fractions both in freshwater and estuary. For the other metals, the difference is less than half an order of magnitude, mainly due to removal in freshwater. The site-dependent CFs generally vary within two orders of magnitude around the site-generic CF. Compared to USES-LCA 2.0 CFs (egalitarian perspective), the new site-generic marine CFs for emission to seawater are 1–4 orders of magnitude lower except for Pb. The new site-generic marine CFs for emission to freshwater lie within two orders of magnitude difference from USES-LCA 2.0 CFs. The comparative contribution share analysis shows a poor agreement of metal toxicity ranking between both methods.

Conclusions

Accounting for estuary removal particularly influences marine ecotoxicity CFs for emission to freshwater of metals that have a strong tendency to complex-bind to particles. It indicates the importance of including estuary in the characterization modelling when dealing with those metals. The resulting endpoint ecotoxicity impact scores are 1–3 orders of magnitude lower in seawater than in freshwater for most metals except Pb, illustrating the higher sensitivity of freshwater ecosystems to metal emissions, largely due to the higher species density there.

     

A methodology for separating uncertainty and variability in the life cycle greenhouse gas emissions of coal-fueled power generation in the USA

Purpose

Results of life cycle assessments (LCAs) of power generation technologies are increasingly reported in terms of typical values and possible ranges. Extents of these ranges result from both variability and uncertainty. Uncertainty may be reduced via additional research. However, variability is a characteristic of supply chains as they exist; as such, it cannot be reduced without modifying existing systems. The goal of this study is to separately quantify uncertainty and variability in LCA.

Methods

In this paper, we present a novel method for differentiating uncertainty from variability in life cycle assessments of coal-fueled power generation, with a specific focus on greenhouse gas emissions. Individual coal supply chains were analyzed for 364 US coal power plants. Uncertainty in CO₂ and CH₄ emissions throughout these supply chains was quantified via Monte Carlo simulation. The method may be used to identify key factors that drive the range of life cycle emissions as well as the limits of precision of an LCA.

Results and discussion

Using this method, we statistically characterized the carbon footprint of coal power in the USA in 2009. Our method reveals that the average carbon footprint of coal power (100 year time horizon) ranges from 0.97 to 1.69 kg CO₂eq/kWh of generated electricity (95 % confidence interval), primarily due to variability in plant efficiency. Uncertainty in the carbon footprints of individual plants spans a factor of 1.04 for the least uncertain plant footprint to a factor of 1.2 for the most uncertain plant footprint (95 % uncertainty intervals). The uncertainty in the total carbon footprint of all US coal power plants spans a factor of 1.05.

Conclusions

We have developed and successfully implemented a framework for separating uncertainty and variability in the carbon footprint of coal-fired power plants. Reduction of uncertainty will not substantially reduce the range of predicted emissions. The range can only be reduced via substantial changes to the US coal power infrastructure. The finding that variability is larger than uncertainty can obviously not be generalized to other product systems and impact categories. Our framework can, however, be used to assess the relative influence of uncertainty and variability for a whole range of product systems and environmental impacts.     

Estimating the impact of changing fertilizer application rate, land use, and climate on nitrous oxide emissions in Irish grasslands

Aim

This study examines the impact of changing nitrogen (N) fertilizer application rates, land use and climate on N fertilizer-derived direct nitrous oxide (N₂O) emissions in Irish grasslands.

Methods

A set of N fertilizer application rates, land use and climate change scenarios were developed for the baseline year 2000 and then for the years 2020 and 2050. Direct N₂O emissions under the different scenarios were estimated using three different types of emission factors and a newly developed Irish grassland N₂O emissions empirical model.

Results

There were large differences in the predicted N₂O emissions between the methodologies, however, all methods predicted that the overall N₂O emissions from Irish grasslands would decrease by 2050 (by 40–60 %) relative to the year 2000. Reduced N fertilizer application rate and land-use changes resulted in decreases of 19–34 % and 11–60 % in N₂O emission respectively, while climate change led to an increase of 5–80 % in N₂O emission by 2050.

Conclusions

It was observed in the study that a reduction in N fertilizer and a reduction in the land used for agriculture could mitigate emissions of N₂O, however, future changes in climate may be responsible for increases in emissions causing the positive feedback of climate on emissions of N₂O.      

Characterization model to assess ocean acidification within life cycle assessment

Purpose

Ocean acidification due to the absorption of increasing amounts of atmospheric carbon dioxide has become a severe problem in the recent years as more and more marine species are influenced by the decreasing pH value as well as by the reduced carbonate ion concentration. So far, no characterization model exists for ocean acidification. This paper aims to establish such a characterization model to allow for the necessary future inclusion of ocean acidification in life cycle assessment (LCA) case studies.

Methods

Based on a cause-effect chain for ocean acidification, the substances carbon monoxide, carbon dioxide, and methane were identified as relevant for this impact category. In a next step, the fate factor representing the substances’ share absorbed by the ocean due to conversion, distribution, and dissolution is determined. Then, the fate sensitivity factor is established reflecting the changes in the marine environment due to the amount of released hydrogen ions per gram of substance (category indicator). Finally, fate and fate sensitivity factors of each substance are multiplied and set in relation to the reference substance, carbon dioxide, thereby delivering the respective characterization factors (in kg CO₂ eq) at midpoint level.

Results and discussion

Characterization factors are provided for carbon monoxide (0.87 kg CO₂ eq), carbon dioxide (1 kg CO₂ eq), and methane (0.84 kg CO₂ eq), which allow conversion of inventory results of these substances into category indicator results for ocean acidification. Inventory data of these substances is available in common LCA databases and software. Hence, the developed method is directly applicable. In a subsequent contribution analysis, the relative contribution of the three selected substances, along with other known acidifying substances, to the ocean acidification potential of 100 different materials was studied. The contribution analysis confirmed carbon dioxide as the predominant substance responsible for more than 97 % of the total ocean acidification potential. However, the influence of other acidifying substances, e.g., sulfur dioxide, should not be neglected.

Conclusions

Evaluation of substances contributing to ocean acidification is of growing importance since the acidity of oceans has been increasing steadily over the last decades. The introduced approach can be applied to evaluate product system related impacts of ocean acidification and include those into current LCA practice.

     

Spatial and technological variability in the carbon footprint of durum wheat production in Iran

Purpose

The purpose of this study was to quantify the spatial and technological variability in life cycle greenhouse gas (GHG) emissions, also called the carbon footprint, of durum wheat production in Iran.

Methods

The calculations were based on information gathered from 90 farms, each with an area ranging from 1 to 150 ha (average 16 ha). The carbon footprint of durum wheat was calculated by quantifying the biogenic GHG emissions of carbon loss from soil and biomass, as well as the GHG emissions from fertilizer application and machinery use, irrigation, transportation, and production of inputs (e.g., fertilizers, seeds, and pesticides). We used Spearman’s rank correlation to quantify the relative influence of technological variability (in crop yields, fossil GHG emissions, and N₂O emissions from fertilizer application) and spatial variability (in biogenic GHG emissions) on the variation of the carbon footprint of durum wheat.

Results and discussion

The average carbon footprint of 1 kg of durum wheat produced was 1.6 kg CO₂-equivalents with a minimum of 0.8 kg and a maximum of 3.0 kg CO₂-equivalents. The correlation analysis showed that variation in crop yield and fertilizer application, representing technological variability, accounted for the majority of the variation in the carbon footprint, respectively 76 and 21%. Spatial variation in biogenic GHG emissions, mainly resulting from differences in natural soil carbon stocks, accounted for 3% of the variation in the carbon footprint. We also observed a non-linear relationship between the carbon footprint and the yield of durum wheat that featured a scaling factor of ?2/3. This indicates that the carbon footprint of durum wheat production (in kg CO₂-eq kg^?1) typically decreases by 67% with a 100% increase in yield (in kg ha^?1 year^?1).

Conclusions

Various sources of variability, including variation between locations and technologies, can influence the results of life cycle assessments. We demonstrated that technological variability exerts a relatively large influence on the carbon footprint of durum wheat produced in Iran with respect to spatial variability. To increase the durum wheat yield at farms with relatively large carbon footprints, technologies such as site-specific nutrient application, combined tillage, and mechanized irrigation techniques should be promoted.

     

Climate change impacts on life cycle greenhouse gas (GHG) emissions savings of biomethanol from corn and soybean

Purpose

The purpose of this study is to assess and calculate the potential impacts of climate change on the greenhouse gas (GHG) emissions reduction potentials of combined production of whole corn bioethanol and stover biomethanol, and whole soybean biodiesel and stalk biomethanol. Both fuels are used as substitutes to conventional fossil-based fuels. The product system includes energy crop (feedstock) production and transportation, biofuels processing, and biofuels distribution to service station.

Methods

The methodology is underpinned by life cycle thinking. Crop system model and life cycle assessment (LCA) model are linked in the analysis. The Decision Support System for Agrotechnology Transfer – crop system model (DSSAT-CSM) is used to simulate biomass and grain yield under different future climate scenarios generated using a combination of temperature, precipitation, and atmospheric CO₂. Historical weather data for Gainesville, Florida, are obtained for the baseline period (1981–1990). Daily minimum and maximum air temperatures are projected to increase by +2.0, +3.0, +4.0, and +5.0 °C, precipitation is projected to change by ±20, 10, and 5 %, and atmospheric CO₂ concentration is projected to increase by +70, +210, and +350 ppm. All projections are made throughout the growing season. GaBi 4.4 is used as primary LCA modelling software using crop yield data inputs from the DSSAT-CSM software. The models representation of the physical processes inventory (background unit processes) is constructed using the ecoinvent life cycle inventory database v2.0.

Results and discussion

Under current baseline climate condition, net greenhouse gas (GHG) emissions savings per hectare from corn-integrated biomethanol synthesis (CIBM) and soybean-integrated biomethanol synthesis (SIBM) were calculated as ?8,573.31 and ?3,441 kg CO₂-eq. ha^?1 yr^?1, respectively. However, models predictions suggest that these potential GHG emissions savings would be impacted by changing climate ranging from negative to positive depending on the crop and biofuel type, and climate scenario. Increased atmospheric level of CO₂ tends to minimise the negative impacts of increased temperature.

Conclusions

While policy measures are being put in place for the use of renewable biofuels driven by the desire to reduce GHG emissions from the use of conventional fossil fuels, climate change would also have impacts on the potential GHG emissions reductions resulting from the use of these renewable biofuels. However, the magnitude of the impact largely depends on the biofuel processing technology and the energy crop (feedstock) type.     

Assessment of urgent impacts of greenhouse gas emissions—the climate tipping potential (CTP)

Purpose

The impact of anthropogenic greenhouse gas (GHG) emissions on climate change receives much focus today. This impact is however often considered only in terms of global warming potential (GWP), which does not take into account the need for staying below climatic target levels, in order to avoid passing critical climate tipping points. Some suggestions to include a target level in climate change impact assessment have been made, but with the consequence of disregarding impacts beyond that target level. The aim of this paper is to introduce the climate tipping impact category, which represents the climate tipping potential (CTP) of GHG emissions relative to a climatic target level. The climate tipping impact category should be seen as complementary to the global warming impact category.

Methods

The CTP of a GHG emission is expressed as the emission’s impact divided by the ‘capacity’ of the atmosphere for absorbing the impact without exceeding the target level. The GHG emission impact is determined as its cumulative contribution to increase the total atmospheric GHG concentration (expressed in CO₂ equivalents) from the emission time to the point in time where the target level is expected to be reached, the target time.

Results and discussion

The CTP of all the assessed GHGs increases as the emission time approaches the target time, reflecting the rapid decrease in remaining atmospheric capacity and thus the increasing potential impact of the GHG emission. The CTP of a GHG depends on the properties of the GHG as well as on the chosen climatic target level and background scenario for atmospheric GHG concentration development. In order to enable direct application in life cycle assessment (LCA), CTP characterisation factors are presented for the three main anthropogenic GHGs, CO₂, CH₄ and N₂O.

Conclusions

The CTP metric distinguishes different GHG emission impacts in terms of their contribution to exceeding a short-term target and highlights their increasing importance when approaching a climatic target level, reflecting the increasing urgency of avoiding further GHG emissions in order to stay below the target level. Inclusion of the climate tipping impact category for assessing climate change impacts in LCA, complimentary to the global warming impact category which shall still represent the long-term climate change impacts, is considered to improve the value of LCA as a tool for decision support for climate change mitigation.     

Human health characterization factors of nano-TiO<Subscript>2</Subscript> for indoor and outdoor environments

Purpose

The increasing use of engineered nanomaterials (ENMs) in industrial applications and consumer products is leading to an inevitable release of these materials into the environment. This makes it necessary to assess the potential risks that these new materials pose to human health and the environment. Life cycle assessment (LCA) methodology has been recognized as a key tool for assessing the environmental performance of nanoproducts. Until now, the impacts of ENMs could not be included in LCA studies due to a lack of characterization factors (CFs). This paper provides a methodological framework for identifying human health CFs for ENMs.

Methods

The USEtox? model was used to identify CFs for assessing the potential carcinogenic and non-carcinogenic effects on human health caused by ENM emissions in both indoor (occupational settings) and outdoor environments. Nano-titanium dioxide (nano-TiO₂) was selected for defining the CFs in this study, as it is one of the most commonly used ENMs. For the carcinogenic effect assessment, a conservative approach was adopted; indeed, a critical dose estimate for pulmonary inflammation was assumed.

Results and discussion

We propose CFs for nano-TiO₂ from 5.5E?09 to 1.43E?02 cases/kg_emitted for both indoor and outdoor environments and for carcinogenic and non-carcinogenic effects.

Conclusions

These human health CFs for nano-TiO₂ are an important step toward the comprehensive application of LCA methodology in the field of nanomaterial technology.

     

Carbon footprint of a Cavendish banana supply chain

Purpose

Bananas are one of the highest selling fruits worldwide, and for several countries, bananas are an important export commodity. However, very little is known about banana’s contribution to global warming. The aims of this work were to study the greenhouse gas emissions of bananas from cradle to retail and cradle to grave and to assess the potential of reducing greenhouse gas (GHG) emissions along the value chain.

Methods

Carbon footprint methodology based on ISO-DIS 14067 was used to assess GHG emissions from 1 kg of bananas produced at two plantations in Costa Rica including transport by cargo ship to Norway. Several methodological issues are not clearly addressed in ISO 14067 or the LCA standards 14040 and ISO 14044 underpinning 14067. Examples are allocation, allocation in recycling, representativity and system borders. Methodological choices in this study have been made based on other standards, such as the GHG Protocol Products Standard.

Results and discussion

The results indicate that bananas had a carbon footprint (CF) on the same level as other tropical fruits and that the contribution from the primary production stage was low. However, the methodology used in this study and the other comparative studies was not necessarily identical; hence, no definitive conclusions can be drawn. Overseas transport and primary production were the main contributors to the total GHG emissions. Including the consumer stage resulted in a 34 % rise in CF, mainly due to high wastage. The main potential reductions of GHG emissions were identified at the primary production, within the overseas transport stage and at the consumer.

Conclusions

The carbon footprint of bananas from cradle to retail was 1.37 kg CO₂ per kilogram banana. GHG emissions from transport and primary production could be significantly reduced, which could theoretically give a reduction of as much as 44 % of the total cradle-to-retail CF. The methodology was important for the end result. The choice of system boundaries gives very different results depending on which life cycle stages and which unit processes are included. Allocation issues were also important, both in recycling and in other processes such as transport and storage. The main uncertainties of the CF result are connected to N₂O emissions from agriculture, methane emissions from landfills, use of secondary data and variability in the primary production data. Thus, there is a need for an internationally agreed calculation method for bananas and other food products if CFs are to be used for comparative purposes.     

Land use impacts on freshwater regulation, erosion regulation, and water purification: a spatial approach for a global scale level

Purpose

Rarely considered in environmental assessment methods, potential land use impacts on a series of ecosystem services must be accounted for in widely used decision-making tools such as life cycle assessment (LCA). The main goal of this study is to provide an operational life cycle impact assessment characterization method that addresses land use impacts at a global scale by developing spatially differentiated characterization factors (CFs) and assessing the extent of their spatial variability using different regionalization levels.

Methods

The proposed method follows the recommendations of previous work and falls within the framework and principles for land use impact assessment established by the United Nations Environment Programme/Society of Environmental Toxicology and Chemistry Life Cycle Initiative. Based on the spatial approach suggested by Saad et al. (Int J Life Cycle Assess 16: 198–211, 2011), the intended impact pathways that are modeled pertain to impacts on ecosystem services damage potential and focus on three major ecosystem services: (1) erosion regulation potential, (2) freshwater regulation potential, and (3) water purification potential. Spatially-differentiated CFs were calculated for each biogeographic region of all three regionalization scale (Holdridge life regions, Holdridge life zones, and terrestrial biomes) along with a nonspatial world average level. In addition, seven land use types were assessed considering both land occupation and land transformation interventions.

Results and discussion

A comprehensive analysis of the results indicates that, when compared to all resolution schemes, the world generic averaged CF can deviate for various ecosystem types. In the case of groundwater recharge potential impacts, this range varied up to factors of 7, 4.7, and 3 when using the Holdridge life zones, the Holdridge regions, and the terrestrial biomes regionalization levels, respectively. This validates the importance of introducing a regionalized assessment and highlights how a finer scale increases the level of detail and consequently the discriminating power across several biogeographic regions, which could not have been captured using a coarser scale. In practice, the implementation of such regionalized CFs suggests that an LCA practitioner must identify the ecosystem in which land occupation or transformation activities occur in addition to the traditional inventory data required—namely, the land use activity and the inventory flow.

Conclusions

The variability of CFs across all three regionalization levels provides an indication of the uncertainty linked to nonspatial CFs. Among other assumptions and value choices made throughout the study, the use of ecological borders over political boundaries was deemed more relevant to the interpretation of environmental issues related to specific functional ecosystem behaviors.     

PestLCI 2.0: a second generation model for estimating emissions of pesticides from arable land in LCA

Purpose

The spatial dependency of pesticide emissions to air, surface water and groundwater is illustrated and quantified using PestLCI 2.0, an updated and expanded version of PestLCI 1.0.

Methods

PestLCI is a model capable of estimating pesticide emissions to air, surface water and groundwater for use in life cycle inventory (LCI) modelling of field applications. After calculating the primary distribution of pesticides between crop and soil, specific modules calculate the pesticide??s fate, thus determining the pesticide emission pattern for the application. PestLCI 2.0 was developed to overcome the limitations of the first model version, replacement of fate calculation equations and introducing new modules for macropore flow and effects of tillage. The accompanying pesticide database was expanded, the meteorological and soil databases were extended to include a range of European climatic zones and soil profiles. Environmental emissions calculated by PestLCI 2.0 were compared to results from the risk assessment models SWASH (surface water emissions), FOCUSPEARL (groundwater via matrix leaching) and MACRO (groundwater including macropore flow, only one scenario available) to partially validate the updated model. A case study was carried out to demonstrate the spatial variation of pesticide emission patterns due to dependency on meteorological and soil conditions.

Results

Compared to PestLCI 1.0, PestLCI 2.0 calculated lower emissions to surface water and higher emissions to groundwater. Both changes were expected due to new pesticide fate calculation approaches and the inclusion of macropore flow. Differences between the SWASH and FOCUSPEARL and PestLCI 2.0 emission estimates were generally lower than 2 orders of magnitude, with PestLCI generally calculating lower emissions. This is attributed to the LCA approach to quantify average cases, contrasting with the worst-case risk assessment approach inherent to risk assessment. Compared to MACRO, the PestLCI 2.0 estimates for emissions to groundwater were higher, suggesting that PestLCI 2.0 estimates of fractions leached to groundwater may be slightly conservative as a consequence of the chosen macropore modelling approach. The case study showed that the distribution of pesticide emissions between environmental compartments strongly depends on local climate and soil characteristics.

Conclusions

PestLCI 2.0 is partly validated in this paper. Judging from the validation data and case study, PestLCI 2.0 is a pesticide emission model in acceptable accordance with both state-of-the-art pesticide risk assessment models. The case study underlines that the common pesticide emission estimation practice in LCI may lead to misestimating the toxicity impacts of pesticide use in LCA.     

Soil warming accelerates decomposition of fine woody debris

Aims

There is evidence that increased N inputs to boreal forests, via atmospheric deposition or intentional fertilization, may impact negatively on ectomycorrhizal (ECM) fungi leading to a reduced flux of plant-derived carbon (C) back to the atmosphere via ECM. Our aim was to investigate the impact of N fertilization of a Pinus sylvestris (L.) forest stand on the return of recently photoassimilated C via the ECM component of soil respiration.

Methods

We used an in situ, large-scale, ¹³C-CO₂ isotopic pulse labelling approach and monitored the ¹³C label return using soil gas efflux chambers placed over three different types of soil collar to distinguish between heterotrophic (R_H), autotrophic (R_A; partitioned further into contributions from ECM hyphae and total R_A) and total (R_S) soil respiration.

Results

The impact of N fertilization was to significantly reduce R_A, particularly respiration via extramatrical ECM hyphae. ECM hyphal flux in control plots showed substantial spatial variability, resulting in mean flux estimates exceeding estimates of total R_A, while ECM contributions to R_A in N treated plots were estimated at around 30%.

Conclusion

Significant impacts on soil C cycling may be caused by reduced plant C allocation to ECM fungi in response to increased N inputs to boreal forests; ecosystem models so far lack this detail.     

Impact of DOC trends resulting from changing climatic extremes and atmospheric deposition chemistry on periphyton community of a freshwater tropical lake of India

Recent measurements have demonstrated unprecedented increase in atmospheric deposition of nutrients in many parts of India. To determine whether atmospheric nutrient inputs would increase phytoplankton growth and catchment dissolved organic carbon (DOC) flushing to constrain benthic algae, we analyzed NO₃ ^? and PO ₄ ^?3 in atmospheric deposits; nutrients and DOC in runoff and lake water and standing crop biomass of phytoplankton and periphyton at Jaisamand Lake of Rajasthan, India. Atmospheric deposition of NO₃ ^? (7.18–29.95 kg ha^?1 year^?1) and PO ₄ ^?3 (0.56–2.15 kg ha^?1 year^?1) showed a consistently rising trend across the year. Microbial biomass and activity in catchment increased in response to atmospheric deposition. Lake DOC and nutrients showed strong coherence with their terrestrial and atmospheric fluxes. Phytoplankton development showed significant linearity with atmospheric input of nutrients. Air-driven input appeared to have compensated the nutrient constraints to phytoplankton during drought. The N:P stoichiometry of deposition and that of lake water indicated that, although there was a seasonal switchover to N- or P-limitation, phytoplankton were mainly co-limited by N and P due probably to the synergistic effects of combined N + P enrichment in the pelagic zone of the lake. Periphyton standing crop showed inverse relationship with phytoplankton and lake DOC. The study indicated that enhanced phytoplankton development and terrestrial DOC flushing in response to atmospheric nutrient input attenuated light penetration to constrain algal periphyton. We suggests that data on these issues may be considered in developing aquatic ecosystem models to establish future links between changing air–water–land interactions and associated shifts in lake ecosystem functioning for more accurately predicting climate change drivers and designing integrated lake basin management strategies.