Water footprints and crop water use of 175 individual crops for 1990-2019 simulated with a global crop model

The water footprint of a crop (WF) is a common metric for assessing agricultural water consumption and productivity. To provide an update and methodological enhancement of existing WF datasets, we apply a global process-based crop model to quantify consumptive WFs of 175 individual crops at a 5 arcminute resolution over the 1990-2019 period. This model simulates the daily crop growth and vertical water balance considering local environmental conditions, crop characteristics, and farm management. We partition WFs into green (water from precipitation) and blue (from irrigation or capillary rise), and differentiate between rainfed and irrigated production systems. The outputs include gridded datasets and national averages for unit water footprints (expressed in m3 t-1 yr-1), water footprints of production (m3 yr-1), and crop water use (mm yr-1). We compare our estimates to other global studies covering different historical periods and methodological approaches. Provided outputs can offer insights into spatial and temporal patterns of agricultural water consumption and serve as inputs for further virtual water trade studies, life cycle and water footprint assessments.

Water pollution from pharmaceutical use in livestock farming: Assessing differences between livestock types and production systems

Livestock production is a major source of pharmaceutical emissions to the environment. The current scientific discourse focuses on measuring and modeling emissions as well as assessing their risks. Although several studies corroborate the severity of pharmaceutical pollution resulting from livestock farming, differences in pollution between livestock types and production systems are largely unknown. In fact, there is no comprehensive analysis of factors influencing pharmaceutical use-the emission's source-in the diverse production systems. To address these knowledge gaps, we developed a framework to investigate pharmaceutical pollution from different livestock production systems and applied it in a first pilot assessment to compare pollution from organic and conventional cattle, pig, and chicken production systems on selected indicator substances, covering antibiotics, antiparasitics, hormones, and nonsteroidal anti-inflammatory drugs (NSAIDs). Given the lack of statistics, for this article we retrieved novel qualitative information about influential factors for pharmaceutical use and pollution from expert interviews and combined this with quantitative data on, among other factors, the environmental behavior of specific substances from the literature. Our analysis reveals that factors across a pharmaceutical's entire life cycle influence pollution. However, not all factors are livestock type or production-system dependent. The pilot assessment furthermore reveals that differences in pollution potential between conventional and organic production exist, but for antibiotics, NSAIDs, and partially for antiparasitics, some factors lead to greater pollution potential in conventional systems, and others in organic systems. For hormones, we identified a comparatively greater pollution potential from conventional systems. Among the indicator substances, the assessment over the entire pharmaceutical life cycle illustrates that flubendazole in broiler production has the greatest per unit impact. The framework and its application in the pilot assessment generated insights useful to identifying which substances, livestock types, production systems, or the combination thereof have great or little pollution potential, informing more sustainable agricultural management practices. Integr Environ Assess Manag 2023;19:1495-1509. © 2023 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

The role of context in identifying linkages between SDG 2 (food) and SDG 6 (water)

The Sustainable Development Goals (SDGs) of the United Nation's Agenda 2030 are formulated to promote the development of integrated, multisectoral policies that explicitly consider linkages across SDGs. Although multiple recent studies have tried to identify linkages across SDGs, the role of contextual factors in identifying SDG linkages is neither well described nor understood. For the case of SDG 2 and SDG 6, this study aims to (i) identify linkages-at country and SDG target level-through the application of various quantitative and qualitative identification methods, and (ii) explore contextual factors to explain the differences across identified linkages. Hereto, we first conducted a text analysis of 195 Voluntary National Reviews (VNRs) reported by 159 countries from 2016 to 2020. Next, we synthesized linkages reported by previous qualitative studies and conducted a quantitative (correlation) analysis on the UN's SDG database. Last, we compared identified linkages across methods, paying special attention to the role of context. From the text analysis, we identified 221 country-specific linkages between 25 SDG target pairs and observed that countries increasingly report SDG linkages in their VNRs over time. Comparing text analysis, existing qualitative studies, and our quantitative correlation analysis, we found substantial differences between the number and nature of linkages identified. These differences can be explained in part by methodological considerations, but to a significant extent also by contextual factors, such as project design, technology application, phase of interventions, and project scale. We conclude by discussing the strengths and limitations of the methods involved, and suggestions for future studies.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11625-022-01158-3.

An integrated modelling approach to derive the grey water footprint of veterinary antibiotics

Water pollution by veterinary antibiotics (VAs) resulting from livestock production is associated with severe environmental and human health risks. While upward trends in global animal product consumption signal that these risks might exacerbate toward the future, VA related water pollution is currently insufficiently understood. To increase this understanding, the present research assesses processes influencing VA pollution from VA administration to their discharge into freshwater bodies, using an integrated modelling approach (IMA). For the VAs amoxicillin, doxycycline, oxytetracycline, sulfamethazine, and tetracycline we estimate loads administered to livestock, excretion, degradation during manure storage, fate in soil and transport to surface water. Fate and transport are modelled using the VA transport model (VANTOM), which is fed with estimates from the Pan-European Soil Erosion Risk Assessment (PESERA). The grey water footprint (GWF) is used to indicate the severity of water pollution in volumetric terms by combining VA loads and predicted no effect concentrations. We apply our approach to the German-Dutch Vecht river catchment, which is characterized by high livestock densities. Results show a VA mass load decrease larger than 99% for all substances under investigation, from their administration to surface water emission. Due to metabolization in the body, degradation during manure storage and degradation in soil, VA loads are reduced by 45%, 80% and 90% on average, respectively. While amoxicillin and sulfamethazine dissipate quickly after field application, significant fractions of doxycycline, oxytetracycline and tetracycline accumulate in the soil. The overall Vecht catchment's GWF is estimated at 250,000 m³ yr^-1, resulting from doxycycline (81% and 19% contribution from the German and Dutch catchment part respectively). Uncertainty ranges of several orders of magnitude, as well as several remaining limitations to the presented IMA, underscore the importance to further develop and refine the approach.