The increase in food demand and limited opportunities to expand agricultural land pose a threat to local and global food security. Producing food in urban areas such as green roofs can help satisfy... Show moreThe increase in food demand and limited opportunities to expand agricultural land pose a threat to local and global food security. Producing food in urban areas such as green roofs can help satisfy urban food demand and thus alleviate pressure on agricultural land. However, a modeling framework that simulates crop growth and production potential on green roofs at a city scale is missing. Here, we adapt the Aquacrop model to explore the growth potential of various types of crops on green roofs and apply it to suitable roof areas in the city of Amsterdam. Our modeling framework includes irrigation methods for water use on green roofs that are optimized according to various climate-driven scenarios of water availability. We find that cabbage has the maximum achievable crop yields ranging from 30.8 to 75.9 t ha-1 yr-1, while pea has the minimum achievable crop yields ranging from 1.7 to 6.4 t ha-1 yr-1. The potential suitable green roof area (i.e., roofs with a certain slope and bearing capacity) for Amsterdam is roughly 400 ha for crop production. This represents 16 % of the total rooftop areas of Amsterdam and can produce up to a total of 28 kt of crops on an annual basis. Our modeling framework can be easily applied to other cities to identify the crop growth potential of green roofs. Our results can help policymakers and urban planners find optimal planting strategies and contribute to shorter food supply chains. Show less
Reduced river discharge and flow regulation are significant threats to freshwater biodiversity. An accurate representation of potential damage of water consumption on freshwater biodiversity is... Show moreReduced river discharge and flow regulation are significant threats to freshwater biodiversity. An accurate representation of potential damage of water consumption on freshwater biodiversity is required to quantify and compare the environmental impacts of global value chains. The effect of discharge reduction on fish species richness was previously modeled in life cycle impact assessment, but models were limited by the restricted geographical scope of underlying species-discharge relationships and the small number of species data. Here, we propose a model based on a novel regionalized species-discharge relationship (SDR). Our SDR-based model covers 88 % of the global landmass (2320 river basins worldwide excluding deserts and permanently frozen areas) and is based on a global dataset of 11,450 riverine fish species, simulated river discharge, elevation, and climate zones. We performed 10-fold cross-validation to select the best set of predictors and validated the obtained SDRs based on observed discharge data. Our model performed better than previous SDRs employed in life cycle impact assessment (Kling-Gupta efficiency coefficient about 4 times larger). We provide both marginal and average models with their uncertainty ranges for assessing scenarios of small and large-scale water consumption, respectively, and include regional and global species loss. We conducted an illustrative case study to showcase the method's applicability and highlight the differences with the currently used approach. Our models are useful for supporting sustainable water consumption and riverine fish biodiversity conservation decisions. They enable a more specific, reliable, and complete impact assessment by differentiating impacts Show less
Ligtvoet, W.; Bouwman, A.; Bakkenes, M.; Beusen, A.; van Bemmel, B.; de Blois, F.; ... ; Righart, A. 2023
Plastic food packaging is a cost-effective tool to minimize food waste. However, plastic food packaging rapidly generates waste and if mismanaged can leak to the environment adversely affecting... Show morePlastic food packaging is a cost-effective tool to minimize food waste. However, plastic food packaging rapidly generates waste and if mismanaged can leak to the environment adversely affecting ecosystems. We quantified the plastic waste leaked to the marine environment due to food consumption in the Netherlands. Combining food consumption patterns, food waste estimates, and plastic packaging data, we estimated the plastic packaging intensity of the Dutch diet. We then mapped the fate of the plastic food packaging waste generated using Dutch plastic waste management patterns. We estimate that a total of 296 kt/yr of plastic food packaging is required in the Netherlands. We model that 6.5 kt/yr is leaked to the marine environment, with 75% of this leakage resulting from the exportation of plastic waste to nations in Asia, 3% from all other nations, and 22% due to littering. We conclude that despite being a high-income nation with a post-consumer plastic packaging waste network reporting a 78% recycle rate, Dutch plastic food packaging waste is leaked to the marine environment at a globally average rate, raising questions about plastic recycle rate metrics and Dutch/EU plastic waste export policies. Show less
Li, D.; Dorber, M.; Barbarossa, V.; Verones, F. 2022
Water temperature is an abiotic master variable for the survival of aquatic organisms. Global warming alters the thermal regimes of rivers and, thus, poses a threat to freshwater biodiversity. To... Show moreWater temperature is an abiotic master variable for the survival of aquatic organisms. Global warming alters the thermal regimes of rivers and, thus, poses a threat to freshwater biodiversity. To address the impacts of water temperature changes related to global warming on freshwater fish species in life cycle assessment (LCA), we developed spatially explicit characterization factors (CFs) for 207 greenhouse gases under four representative concentration pathways. We calculated fate factors by using the output of a global hydrological model fully coupled with a dynamic water temperature model. We developed six species sensitivity distribution curves for two thermal effects (i.e., lethal and sub-lethal) to derive effect factors, which take the differences in sensitivity between climate regions into account. The regional CFs for CO2 ranged from 2.91 x 10(-22) to 6.53 x 10(-18) PAF.yr/kg for sub-lethal effects and from 1.98 x 10(-22) to 4.58 x 10(-18) PDF.yr/kg for lethal effects, depending on the river watersheds and future climate scenarios. To identify the contribution of regional impacts on freshwater fish to their potential global extinction, the regional CFs were converted into global CFs. The largest CFs always occur in the tropical watersheds. The regional impacts in the Amazon watershed contribute the most to the global freshwater fish species extinction. This study contributes to assessing the potential impacts on freshwater biodiversity from global warming from a new cause-effect pathway in LCA. Show less
Verones, F.; Kuipers, K.; Núnez, M.; Rosa, F.; Scherer, L.; Marques, A.; ... ; Dorber, M. 2022
Human activities put pressure on the natural environmental and the Life Cycle Assessment methodology (LCA) is becoming a more prevalent tool to assess the relevant environmental impacts from... Show moreHuman activities put pressure on the natural environmental and the Life Cycle Assessment methodology (LCA) is becoming a more prevalent tool to assess the relevant environmental impacts from products and processes on terrestrial, marine and freshwater ecosystems. The Global Life Cycle Impact Assessment Method (GLAM) project of the Life Cycle Initiative hosted by the UN Environment Programme aims at making recommendations for new impact assessment models (such as for land use, water consumption and eutrophication) and improving the consistency and comparability across impact categories. An important aspect to ensure the comparability of these categories across geographic regions is to identify and quantify the scale of impacts, i.e., distinguish if an impact to an area results in local species losses or global species extinctions. This distinction is of high relevance because a species lost at a local level may still exist in other regions of the world and could potentially reestablish in that area, whereas global extinctions are irreversible. A consistent approach to scale impacts from local to global scales is currently not implemented within the LCIA framework, but is crucial to appropriately consider potential biodiversity impacts across impact categories. Here we present an updated approach for calculating a scaling factor, called the Global Extinction Probability (GEP), and calculate it for more than 98 000 species in 20 species groups across marine, terrestrial and freshwater ecosystems. We also provide the GEPs for different spatial scales, such as grid cells, ecoregions or watersheds and country averages. We found that GEP varies over orders of magnitude across the world, emphasizing the relevance of considering the spatial dimension of such extinction probabilities. We recommend quantifying global extinctions based on local species loss by multiplying local species loss within a certain spatial unit with the GEP corresponding to the same spatial unit. GEPs harmonize the quantification of biodiversity impacts across impact categories, improving information to support environmental decision-making. Show less
There is growing evidence that climate change impacts ecosystems and socio-economic activities in freshwater environments. Consistent global data of projected streamflow and water temperature are... Show moreThere is growing evidence that climate change impacts ecosystems and socio-economic activities in freshwater environments. Consistent global data of projected streamflow and water temperature are key to global impact assessments, but such a dataset is currently lacking. Here we present FutureStreams, the first global dataset of projected future streamflow and water temperature for multiple climate scenarios (up to 2099) gridded at a 5 arcminute spatial resolution (similar to 10 km at the equator), including recent past data (1976-2005) for comparison. We generated the data using global hydrological and water temperature models (PCR-GLOBWB, DynWat) forced with climate data from five general circulation models. We included four representative concentration pathways to cover multiple future greenhouse gas emission trajectories and associated changes in climate. Our dataset includes weekly streamflow and water temperature for each year as well as a set of derived indicators that are particularly relevant from an ecological perspective. FutureStreams provides a crucial starting point for large-scale assessments of the implications of changes in streamflow and water temperature for society and freshwater ecosystems. Show less
Aim Discharge is a key determinant of biodiversity in rivers. Positive relationships between riverine biodiversity and discharge, also called species-discharge relationships (SDRs), have been... Show moreAim Discharge is a key determinant of biodiversity in rivers. Positive relationships between riverine biodiversity and discharge, also called species-discharge relationships (SDRs), have been widely documented. However, potential human influences on these relationships are typically not considered. We aimed to fill this gap by exploring whether and how the slopes and intercepts of global riverine fish SDRs might be affected by human pressure on the environment. Location Global. Time period Current. Major taxa studied Riverine fishes. Methods We first quantified native riverine fish species richness of 4,430 catchments of >500 km(2) in size with available discharge measurements, using a novel dataset of the global distributions of 11,425 riverine fish species. We then established mixed effects models relating fish species richness to discharge and to two aggregated human pressure variables: the human footprint index (HFI) and the fragmentation status index (FSI). We tested for possible interactions between discharge and the human pressure variables, while accounting for other relevant covariates of large-scale gradients in riverine fish diversity. Results Against our expectations, we found positive coefficients for both HFI and FSI, in addition to a positive interaction between FSI and discharge. We found this consistently for different discharge variables (annual mean, maximum weekly and minimum weekly discharge). These findings suggest that riverine fish species richness tends to be higher in catchments characterized by more anthropogenic alterations of the natural environment. Main conclusions The global congruence between riverine fish species richness and human presence might reflect a commonality of drivers as well as biodiversity data gaps in the most pristine and species-rich catchments. Irrespectively, our results indicate that conflicts between human development and conservation are not easily avoided and highlight the challenges involved in safeguarding global freshwater biodiversity. Show less
Climate change poses a significant threat to global biodiversity, but freshwater fishes have been largely ignored in climate change assessments. Here, we assess threats of future flow and water... Show moreClimate change poses a significant threat to global biodiversity, but freshwater fishes have been largely ignored in climate change assessments. Here, we assess threats of future flow and water temperature extremes to similar to 11,500 riverine fish species. In a 3.2 degrees C warmer world (no further emission cuts after current governments' pledges for 2030), 36% of the species have over half of their present-day geographic range exposed to climatic extremes beyond current levels. Threats are largest in tropical and sub-arid regions and increases in maximum water temperature are more threatening than changes in flow extremes. In comparison, 9% of the species are projected to have more than half of their present-day geographic range threatened in a 2 degrees C warmer world, which further reduces to 4% of the species if warming is limited to 1.5 degrees C. Our results highlight the need to intensify (inter)national commitments to limit global warming if freshwater biodiversity is to be safeguarded. Show less
Existing methods for applying the planetary boundary concept in life cycle assessment are not sufficiently spatially and temporally resolved. Here, we develop a new method for freshwater use based... Show moreExisting methods for applying the planetary boundary concept in life cycle assessment are not sufficiently spatially and temporally resolved. Here, we develop a new method for freshwater use based on the safe operating space (SOS) at watershed-level. The SOS is based on the concept of environmental flow requirements, which is the share of mean monthly flow that should be reserved to achieve or maintain "fair conditions" of aquatic ecosystems. The method is composed of two steps. First, water consumption is multiplied by a characterization factor, which converts it to an environmental impact, expressed as an area-equivalent of a watershed's mean monthly flow. Second, the environmental impact is compared to an assigned share of SOS to determine if the activity causing it can be considered environmentally sustainable, with respect to a chosen principle for sharing the SOS.The method is demonstrated for a case study on water consumed for irrigation in open-field tomato production in 27 watersheds, spanning 10 countries and 5 continents, based on data for 316 farms in the year 2014. Water consumption was modelled from crop characteristics, climatic data and the assumed type of irrigation system. Two principles, "status quo" and "gross value added", were illustratively applied for the assignment of SOS to 1 tonne of tomatoes.The characterization factors developed span two orders of magnitude from 10th to 90th percentile, which shows the relevance of a spatially and temporally explicit assessment. In the case study, the characterization factors largely determine the high variability in the resulting environmental impacts between watersheds, which ranged from 400 m(2) to 50,000 m(2) per tonne of tomatoes. The analysis would suggest that the freshwater use by current tomato farming is environmentally sustainable in all months in a maximum of 2 of the 27 watersheds with respect to the two principles applied for sharing the SOS.The method can be used as a basis to identify potential "planetary boundary hotspots" in the life cycle of products and to inform appropriate interventions. Two key challenges are the lack of appropriate spatial and temporal data in current life cycle inventories and the choice of sharing principle for assigning the SOS. Show less
Dams contribute to water security, energy supply, and flood protection but also fragment habitats of freshwater species. Yet, a global species-level assessment of dam-induced fragmentation is... Show moreDams contribute to water security, energy supply, and flood protection but also fragment habitats of freshwater species. Yet, a global species-level assessment of dam-induced fragmentation is lacking. Here, we assessed the degree of fragmentation of the occurrence ranges of similar to 10,000 lotic fish species worldwide due to similar to 40,000 existing large dams and similar to 3,700 additional future large hydropower dams. Per river basin, we quantified a connectivity index (CI) for each fish species by combining its occurrence range with a high-resolution hydrography and the locations of the dams. Ranges of nondiadromous fish species were more fragmented (less connected) (CI = 73 +/- 28%; mean +/- SD) than ranges of di-adromous species (CI = 86 +/- 19%). Current levels of fragmentation were highest in the United States, Europe, South Africa, India, and China. Increases in fragmentation due to future dams were especially high in the tropics, with declines in CI of similar to 20 to 40 percentage points on average across the species in the Amazon, Niger, Congo, Salween, and Mekong basins. Our assessment can guide river management at multiple scales and in various domains, including strategic hydropower planning, identification of species and basins at risk, and prioritization of restoration measures, such as dam removal and construction of fish bypasses. Show less
Environmental risk assessment of pharmaceuticals requires the determination of their environmental exposure concentrations. Existing exposure modeling approaches are often computationally demanding... Show moreEnvironmental risk assessment of pharmaceuticals requires the determination of their environmental exposure concentrations. Existing exposure modeling approaches are often computationally demanding, require extensive data collection and processing efforts, have a limited spatial resolution, and have undergone limited evaluation against monitoring data. Here, we present ePiE (exposure to Pharmaceuticals in the Environment), a spatially explicit model calculating concentrations of active pharmaceutical ingredients (APIs) in surface waters across Europe at similar to 1 km resolution. ePiE strikes a balance between generating data on exposure at high spatial resolution while having limited computational and data requirements. Comparison of model predictions with measured concentrations of a diverse set of 35 APIs in the river Ouse (UK) and Rhine basins (North West Europe), showed around 95% were within an order of magnitude. Improved predictions were obtained for the river Ouse basin (95% within a factor of 6; 55% within a factor of 2), where reliable consumption data were available and the monitoring study design was coherent with the model outputs. Application of ePiE in a prioritisation exercise for the Ouse basin identified metformin, gabapentin, and acetaminophen as priority when based on predicted exposure concentrations. After incorporation of toxic potency, this changed to desvenlafaxine, loratadine, and hydrocodone. Show less
Streamflow data is highly relevant for a variety of socio-economic as well as ecological analyses or applications, but a high-resolution global streamflow dataset is yet lacking. We created FLO1K,... Show moreStreamflow data is highly relevant for a variety of socio-economic as well as ecological analyses or applications, but a high-resolution global streamflow dataset is yet lacking. We created FLO1K, a consistent streamflow dataset at a resolution of 30 arc seconds (-1 km) and global coverage. FLO1K comprises mean, maximum and minimum annual flow for each year in the period 1960-2015, provided as spatially continuous gridded layers. We mapped streamflow by means of artificial neural networks (ANNs) regression. An ensemble of ANNs were fitted on monthly streamflow observations from 6600 monitoring stations worldwide, i.e., minimum and maximum annual flows represent the lowest and highest mean monthly flows for a given year. As covariates we used the upstream-catchment physiography (area, surface slope, elevation) and year-specific climatic variables (precipitation, temperature, potential evapotranspiration, aridity index and seasonality indices). Confronting the maps with independent data indicated good agreement (R-2 values up to 91%). FLO1K delivers essential data for freshwater ecology and water resources analyses at a global scale and yet high spatial resolution.[GRAPHICS]. Show less
Quantifying mean annual flow of rivers (MAF) at ungauged sites is essential for assessments of global water supply, ecosystem integrity and water footprints. MAF can be quantified with spatially... Show moreQuantifying mean annual flow of rivers (MAF) at ungauged sites is essential for assessments of global water supply, ecosystem integrity and water footprints. MAF can be quantified with spatially explicit process-based models, which might be overly time-consuming and data-intensive for this purpose, or with empirical regression models that predict MAF based on climate and catchment characteristics. Yet, regression models have mostly been developed at a regional scale and the extent to which they can be extrapolated to other regions is not known. In this study, we developed a global-scale regression model for MAF based on a dataset unprecedented in size, using observations of discharge and catchment characteristics from 1885 catchments worldwide, measuring between 2 and 10(6) km(2). In addition, we compared the performance of the regression model with the predictive ability of the spatially explicit global hydrological model PCR-GLOBWB by comparing results from both models to independent measurements. We obtained a regression model explaining 89% of the variance in MAF based on catchment area and catchment averaged mean annual precipitation and air temperature, slope and elevation. The regression model performed better than PCR-GLOBWB for the prediction of MAF, as root-mean-square error (RMSE) values were lower (0.29-0.38 compared to 0.49-0.57) and the modified index of agreement (d) was higher (0.80-0.83 compared to 0.72-0.75). Our regression model can be applied globally to estimate MAF at any point of the river network, thus providing a feasible alternative to spatially explicit process based global hydrological models. (C) 2016 Elsevier B.V. All rights reserved. Show less
