Morten Birkved

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

PurposeThe 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.MethodsPestLCI 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.ResultsCompared 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.ConclusionsPestLCI 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.

Quantification of urban metabolism through coupling with the life cycle assessment framework: concept development and case study

Cities now consume resources and produce waste in amounts that are incommensurate with the populations they contain. Quantifying and benchmarking the environmental impacts of cities is essential if urbanization of the world’s growing population is to occur sustainably. Urban metabolism (UM) is a promising assessment form in that it provides the annual sum material and energy inputs, and the resultant emissions of the emergent infrastructural needs of a city’s sociotechnical subsystems. By fusing UM and life cycle assessment (UM‐LCA) this study advances the ability to quantify environmental impacts of cities by modeling pressures embedded in the flows upstream (entering) and downstream (leaving) of the actual urban systems studied, and by introducing an advanced suite of indicators. Applied to five global cities, the developed UM‐LCA model provided enhanced quantification of mass and energy flows through cities over earlier UM methods. The hybrid model approach also enabled the dominant sources of a city’s different environmental footprints to be identified, making UM‐LCA a novel and potentially powerful tool for policy makers in developing and monitoring urban development policies. Combining outputs with socioeconomic data hinted at how these forces influenced the footprints of the case cities, with wealthier ones more associated with personal consumption related impacts and poorer ones more affected by local burdens from archaic infrastructure.

Chemical footprint method for improved communication of freshwater ecotoxicity impacts in the context of ecological limits.

The ecological footprint method has been successful in communicating environmental impacts of anthropogenic activities in the context of ecological limits. We introduce a chemical footprint method that expresses ecotoxicity impacts from anthropogenic chemical emissions as the dilution needed to avoid freshwater ecosystem damage. The indicator is based on USEtox characterization factors with a modified toxicity reference point. Chemical footprint results can be compared to the actual dilution capacity within the geographic vicinity receiving the emissions to estimate whether its ecological limit has been exceeded and hence whether emissions can be expected to be environmentally sustainable. The footprint method was illustrated using two case studies. The first was all inventoried emissions from European countries and selected metropolitan areas in 2004, which indicated that the dilution capacity was likely exceeded for most European countries and all landlocked metropolitan areas. The second case study indicated that peak application of pesticides alone was likely to exceed Denmarks freshwater dilution capacity in 1999-2011. The uncertainty assessment showed that better spatially differentiated fate factors would be useful and pointed out other major sources of uncertainty and some opportunities to reduce these.

Beyond safe operating space: finding chemical footprinting feasible.

Feasible Leo Posthuma,*,† Anders Bjorn,‡ Michiel C. Zijp,†,∥ Morten Birkved,‡ Miriam L. Diamond, Michael Z. Hauschild,‡ Mark A. J. Huijbregts, Christian Mulder,† and Dik Van de Meent†,∥ †RIVM, Centre for Sustainability, Environment and Health, P.O. Box 1, 3720BA Bilthoven, The Netherlands ‡DTU Management Engineering, Quantitative Sustainability Assessment, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark Dept Earth Sciences, 22 Russell Street, University of Toronto, Toronto, M5S 3B1, Canada Dept Environmental Science, Institute for Water and Wetland Research, Radboud University, 6525AJ Nijmegen, The Netherlands

Choosing co-substrates to supplement biogas production from animal slurry - a life cycle assessment of the environmental consequences.

Biogas production from animal slurry can provide substantial contributions to reach renewable energy targets, yet due to the low methane potential of slurry, biogas plants depend on the addition of co-substrates to make operations profitable. The environmental performance of three underexploited co-substrates, straw, organic household waste and the solid fraction of separated slurry, were assessed against slurry management without biogas production, using LCA methodology. The analysis showed straw, which would have been left on arable fields, to be an environmentally superior co-substrate. Due to its low nutrient content and high methane potential, straw yields the lowest impacts for eutrophication and the highest climate change and fossil depletion savings. Co-substrates diverted from incineration to biogas production had fewer environmental benefits, due to the loss of energy production, which is then produced from conventional fossil fuels. The scenarios can often provide benefits for one impact category while causing impacts in another.

Environmental life cycle assessment of producing willow, alfalfa and straw from spring barley as feedstocks for bioenergy or biorefinery systems

The current study aimed at evaluating potential environmental impacts for the production of willow, alfalfa and straw from spring barley as feedstocks for bioenergy or biorefinery systems. A method of Life Cycle Assessment was used to evaluate based on the following impact categories: Global Warming Potential (GWP100), Eutrophication Potential (EP), Non-Renewable Energy (NRE) use, Agricultural Land Occupation (ALO), Potential Freshwater Ecotoxicity (PFWTox) and Soil quality. With regard to the methods, soil organic carbon (SOC) change related to the land occupation was calculated based on the net carbon input to the soil. Freshwater ecotoxicity was calculated using the comparative toxicity units of the active ingredients and their average emission distribution fractions to air and freshwater. Soil quality was based on the change in the SOC stock estimated during the land use transformation and land occupation. Environmental impacts for straw were economically allocated from the impacts obtained for spring barley. The results obtained per ton dry matter showed a lower carbon footprint for willow and alfalfa compared to straw. It was due to higher soil carbon sequestration and lower N2O emissions. Likewise, willow and alfalfa had lower EP than straw. Straw had lowest NRE use compared to other biomasses. PFWTox was lower in willow and alfalfa compared to straw. A critical negative effect on soil quality was found with the spring barley production and hence for straw. Based on the energy output to input ratio, willow performed better than other biomasses. On the basis of carbohydrate content of straw, the equivalent dry matter of alfalfa and willow would be requiring higher. The environmental impacts of the selected biomasses in biorefinery therefore would differ based on the conversion efficiency, e.g. of the carbohydrates in the related biorefinery processes.

Urban versus conventional agriculture, taxonomy of resource profiles: a review

Urban agriculture appears to be a means to combat the environmental pressure of increasing urbanization and food demand. However, there is hitherto limited knowledge of the efficiency and scaling up of practices of urban farming. Here, we review the claims on urban agriculture’s comparative performance relative to conventional food production. Our main findings are as follows: (1) benefits, such as reduced embodied greenhouse gases, urban heat island reduction, and storm water mitigation, have strong support in current literature. (2) Other benefits such as food waste minimization and ecological footprint reduction require further exploration. (3) Urban agriculture benefits to both food supply chains and urban ecosystems vary considerably with system type. To facilitate the comparison of urban agriculture systems we propose a classification based on (1) conditioning of the growing space and (2) the level of integration with buildings. Lastly, we compare the predicted environmental performance of the four main types of urban agriculture that arise through the application of the taxonomy. The findings show how taxonomy can aid future research on the intersection of urban food production and the larger material and energy regimes of cities (the “urban metabolism”).

Evaluation of selection methods for toxicological impacts in LCA recommendations for OMNIITOX

Goal, Scope and BackgroundThe aim of this study has been to come up with recommendations on how to develop a selection method (SM) within the method development research of the OMNHTOX project. An SM is a method for prioritization of chemical emissions to be included in a Life Cycle Impact Assessment (LCIA) characterisation, in particular for (eco)toxicological impacts. It is therefore designed for pre-screening to support a characterisation method. The main reason why SMs are needed in the context of LCIA is the high number of chemical emissions that potentially contribute to the impacts on ecosystems and human health. It will often not be feasible to cover all emissions with characterisation factors and, therefore, there exists a need to focus the effort on the most significant chemical emissions in the characterisation step. Until now not all LCA studies include tox-icity-related impact categories, and when they do there are typically many gaps. This study covers the only existing methods explicitly designed as SMs (EDIP-selection, Priofactor and CPM-selection), the dominating Chemical Ranking and Scoring (CRS) method in Europe (EURAM) and in the USA (WMPT) that can be adapted for this purpose, as well as methods presenting novel approaches which could be valuable in the development of improved SMs (CART analysis and Hasse diagram technique).MethodsThe included methods are described. General guidance principles established for CRS systems are applied to SMs and a set of criteria for good performance of SMs is developed. The included methods are finally evaluated against these criteria.Results and DiscussionTwo of the most important performance criteria include providing consistent results relative to the more detailed, associated characterisation methods and the degree of data availability to ensure broader chemical coverage. Applicability to different chemical groups, user friendliness, and transparency are also listed amongst the important criteria. None of the evaluated methods currently fulfil all of the proposed criteria to a degree that excludes the need for development of improved selection methods.Conclusion and RecommendationsFor the development of SMs it is recommended that the general principles for CRS systems are taken into account. Furthermore, special attention should be paid to some specific issues, i.e. the emitted amount should be included, data availability should enable broad chemical coverage, and when identifying priority chemicals for the characterisation, the developed SM should generate few false positives (chemical emissions classified wrongly as being of high concern) and no (significant) false negatives (classified wrongly as being of low concern) as compared to the associated characterisation method. These recommendations are not only relevant for a stand alone SM, but also valuable when dealing with simple characterisation methods associated with a more detailed characterisation method.OutlookThere are several questions that need to be answered before an optimal SM can be developed, inter alia: Is it optimal to just use simple measured data with high availability or are QSAR estimates of more complex, relevant data better? Which key parameters to include and how? Is a statistical approach, like linear regression of characterisation factors or CART analysis, the best solution?

Pesticide emission modelling and freshwater ecotoxicity assessment for Grapevine LCA: adaptation of PestLCI 2.0 to viticulture

PurposeConsumption of high quantities of pesticides in viticulture emphasizes the importance of including pesticide emissions and impacts hereof in viticulture LCAs. This paper addresses the lack of inventory models and characterization factors suited for the quantification of emissions and ecotoxicological impacts of pesticides applied to viticulture. The paper presents (i) a tailored version of PestLCI 2.0, (ii) corresponding characterization factors for freshwater ecotoxicity characterization and (iii) result comparison with other inventory approaches. The purpose of this paper is hence to present a viticulture customized version of PestLCI 2.0 and illustrate the application of this customized version on a viticulture case study.MethodsThe customization of the PestLCI 2.0 model for viticulture includes (i) addition of 29 pesticide active ingredients commonly used in vineyards, (ii) addition of 9 viticulture type specific spraying equipment and accounting the number of rows treated in one pass, and (iii) accounting for mixed canopy (vine/cover crop) pesticide interception. Applying USEtox™, the PestLCI 2.0 customization is further supported by the calculation of freshwater ecotoxicity characterization factors for active ingredients relevant for viticulture. Case studies on three different vineyard technical management routes illustrate the application of the inventory model. The inventory and freshwater ecotoxicity results are compared to two existing simplified emission modelling approaches.Results and discussionThe assessment results show considerably different emission fractions, quantities emitted and freshwater ecotoxicity impacts between the different active ingredient applications. Three out of 21 active ingredients dominate the overall freshwater ecotoxicity: Aclonifen, Fluopicolide and Cymoxanil. The comparison with two simplified emission modelling approaches, considering field soil and air as part of the ecosphere, shows that PestLCI 2.0 yields considerable lower emissions and, consequently, lower freshwater ecotoxicity. The sensitivity analyses reveal the importance of soil and climate characteristics, canopies (vine and cover crop) development and sprayer type on the emission results. These parameters should therefore be obtained with site-specific data, while literature or generic data that are acceptable inputs for parameters whose uncertainties have less influence on the result.ConclusionsImportant specificities of viticulture have been added to the state-of-the-art inventory model PestLCI 2.0. They cover vertically trained vineyards, the most common vineyard training form; they are relevant for other perennial or bush crops provided equipment, shape of the canopy and pesticide active ingredients stay in the range of available options. A similar and compatible model is needed for inorganic pesticide active ingredients emission quantification, especially for organic viticulture impacts accounting.

Weighting and Aggregation in Life Cycle Assessment: Do Present Aggregated Single Scores Provide Correct Decision Support?

This study investigates the prevailing practice of obtaining single scores in life cycle assessment (LCA) and identifies potential lacunas in impact assessment methodology related to the results of aggregation into endpoints and single scores. In order to conduct this investigation, a detailed approach was adopted to facilitate identification of three main problems related to the single†score calculation approach. The prevailing ReCiPe single†score calculation method does not account for either the effect of so†called dominating alternatives (i.e., alternatives having high values across all endpoints) or the interdependency of the indicators being aggregated. It was also found that the simple linear weighted sum method, presently used for obtaining single scores, is not capable of accounting for the effect of weighting schemes and thus cannot realistically represent stakeholders’ perspectives. Finally, we propose a distance†based multiple attribute decision†making method for use in obtaining single scores. This method was found to be more suitable, given that it takes into account the weighting schemes and types of indicators in the process of estimating single scores. The new single†score calculation method proposed here is considered ideal for environmental decision†making problems in the context of life cycle sustainability assessment. Thus, it is also ideal for situations in which more†complex decision†making situations will emerge by combining LCA indicators (midpoints or endpoints) with other indicators representing the performance of a system from economic and social perspectives.