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.

Resource Footprints are Good Proxies of Environmental Damage.

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.

How Many Environmental Impact Indicators Are Needed in the Evaluation of Product Life Cycles?

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.

Including exposure variability in the life cycle impact assessment of indoor chemical emissions: the case of metal degreasing.

The present paper describes a method that accounts for variation in indoor chemical exposure settings and accompanying human toxicity in life cycle assessment (LCA). Metal degreasing with dichloromethane was used as a case study to show method in practice. We compared the human toxicity related to the degreasing of 1m(2) of metal surface in different exposure scenarios for industrial workers, professional users outside industrial settings, and home consumers.

How to address data gaps in life cycle inventories: a case study on estimating CO2 emissions from coal-fired electricity plants on a global scale.

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.

Parameter uncertainty in modeling bioaccumulation factors of fish.

We quantified the uncertainty due to biota-related parameters in estimated bioaccumulation factors (BAFs) of persistent organic pollutants for fish through Monte Carlo simulations. For this purpose, the bioaccumulation model OMEGA (Optimal Modeling for EcotoxicoloGical Applications) was parameterized based on data from the existing literature, analysis of allometric data, and maximum likelihood estimation. Lipid contents, fractions of food assimilated, the allometric rate exponent, normalized food intakes, respiration and growth dilution rates, and partial mass transfer resistances in water and lipid layers were included as uncertain parameters.

Modeled and monitored variation in space and time of PCB-153 concentrations in air, sediment, soil and aquatic biota on a European scale.

We evaluated various modeling options for estimating concentrations of PCB-153 in the environment and in biota across Europe, using a nested multimedia fate model coupled with a bioaccumulation model. The most detailed model set up estimates concentrations in air, soil, fresh water sediment and fresh water biota with spatially explicit environmental characteristics and spatially explicit emissions to air and water in the period 1930-2005. Model performance was evaluated with the root mean square error (RMSE(log)), based on the difference between estimated and measured concentrations.

Modelling bioaccumulation of semi-volatile organic compounds (SOCs) from air in plants based on allometric principles.

A model was developed for gaseous plant-air exchange of semi-volatile organic compounds. Based on previous soil-plant modelling, uptake and elimination kinetics were scaled as a function of plant mass and octanol-air partition ratios. Exchange of chemicals was assumed to be limited by resistances encountered during diffusion through a laminar boundary layer of air and permeation through the cuticle of the leaf.

Model and input uncertainty in multi-media fate modeling: benzo[a]pyrene concentrations in Europe.

This paper evaluates the contribution of (i) uncertainty in substance properties, (ii) lack of spatial variability, (iii) intermodel differences and (iv) neglecting sorption to black carbon (BC) to the uncertainty of Benzo[a]pyrene (BaP) concentrations in European air, soil and fresh water predicted by the multi-media fate model Simplebox. Uncertainty in substance properties was quantified using probabilistic modeling. The influence of spatial variability was quantified by estimating variation in predicted concentrations with three spatially explicit fate models (Impact 2002, EVn BETR and BETR Global).

Empirical evaluation of spatial and non-spatial European-scale multimedia fate models: results and implications for chemical risk assessment.

Multimedia environmental fate models are commonly-applied tools for assessing the fate and distribution of contaminants in the environment. Owing to the large number of chemicals in use and the paucity of monitoring data, such models are often adopted as part of decision-support systems for chemical risk assessment. The purpose of this study was to evaluate the performance of three multimedia environmental fate models (spatially- and non-spatially-explicit) at a European scale.

Including sorption to black carbon in modeling bioaccumulation of polycyclic aromatic hydrocarbons: uncertainty analysis and comparison to field data.

Model estimations of bioaccumulation of polycyclic aromatic hydrocarbons (PAHs) have been higher than field or laboratory data. This has been explained by strong sorption to black carbon (BC). In this paper, eight previously published bioaccumulation datasets were reinterpreted in terms of additional BC sorption.