Publications by authors named "Zoran J N Steinmann"

Bioenergy with carbon capture and storage (BECCS) based on purpose-grown lignocellulosic crops can provide CO emissions to mitigate climate change, but its land requirements present a threat to biodiversity. Here, we analyse the implications of crop-based BECCS for global terrestrial vertebrate species richness, considering both the land-use change (LUC) required BECCS and the climate change prevented BECCS. LUC impacts are determined using global-equivalent, species-area relationship-based loss factors.

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In the twenty-first century, modern bioenergy could become one of the largest sources of energy, partially replacing fossil fuels and contributing to climate change mitigation. Agricultural and forestry biomass residues form an inexpensive bioenergy feedstock with low greenhouse gas (GHG) emissions, if harvested sustainably. We analysed quantities of biomass residues supplied for energy and their sensitivities in harmonised bioenergy demand scenarios across eight integrated assessment models (IAMs) and compared them with literature-estimated residue availability.

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Variability in consumer practices and choices is typically not addressed in comparisons of environmental impacts of traditional shopping and e-commerce. Here, we developed a stochastic model to quantify the variability in the greenhouse gas (GHG) footprints of product distribution and purchase of fast-moving consumer goods (FMCGs) via three prevalent retail channels in the United Kingdom (U.K.

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The net greenhouse gas benefits of wind turbines compared to their fossil energy counterparts depend on location-specific wind climatology and the turbines' technological characteristics. Assessing the environmental impact of individual wind parks requires a universal but location-dependent method. Here, the greenhouse gas payback time for 4161 wind turbine locations in northwestern Europe was determined as a function of (i) turbine size and (ii) spatial and temporal variability in wind speed.

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Environmental footprints are increasingly used to quantify and compare environmental impacts of for example products, technologies, households, or nations. This has resulted in a multitude of footprint indicators, ranging from relatively simple measures of resource use (water, energy, materials) to integrated measures of eventual damage (for example, extinction of species). Yet, the possible redundancies among these different footprints have not yet been quantified.

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Although it is generally recognized that global biodiversity is declining, few studies have examined long-term changes in multiple biodiversity dimensions simultaneously. In this study, we quantified and compared temporal changes in the abundance, taxonomic diversity, functional diversity, and phylogenetic diversity of bird assemblages, using roadside monitoring data of the North American Breeding Bird Survey from 1971 to 2010. We calculated 12 abundance and diversity metrics based on 5-year average abundances of 519 species for each of 768 monitoring routes.

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Numerous indicators are currently available for environmental impact assessments, especially in the field of Life Cycle Impact Assessment (LCIA). Because decision-making on the basis of hundreds of indicators simultaneously is unfeasible, a nonredundant key set of indicators representative of the overall environmental impact is needed. We aimed to find such a nonredundant set of indicators based on their mutual correlations.

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It is unknown whether metal absorption efficiencies in terrestrial soft-bodied species can be predicted with the same metal properties as for aquatic species. Here, we developed models for metal absorption efficiency from the dissolved phase for terrestrial worms and several aquatic species, based on 23 metal physicochemical properties. For the worms, the absorption efficiency was successfully related to 7 properties, and is best predicted with the ionic potential.

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One of the major challenges in life cycle assessment (LCA) is the availability and quality of data used to develop models and to make appropriate recommendations. Approximations and assumptions are often made if appropriate data are not readily available. However, these proxies may introduce uncertainty into the results.

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