Evaluation of foods, drinks and diets in the Netherlands according to the degree of processing for nutritional quality, environmental impact and food costs.

OBJECTIVE: This study investigates nutritional quality, environmental impact and costs of foods and drinks and their consumption in daily diets according to the degree of processing across the Dutch population. DESIGN: The NOVA classification was used to classify the degree of processing (ultra-processed foods (UPF) and ultra-processed drinks (UPD)). Food consumption data were derived from the Dutch National Food Consumption Survey 2012-2016. Indicators assessed were nutritional quality (saturated fatty acids (SFA), sodium, mono and disaccharides (sugar), fibre and protein), environmental impact (greenhouse gas (GHG) emissions and blue water use) and food costs. SETTING: The Netherlands. PARTICIPANTS: Four thousand three hundred thirteen Dutch participants aged 1 to 79 years. RESULTS: Per 100 g, UPF were more energy-dense and less healthy than unprocessed or minimally processed foods (MPF); UPF were associated with higher GHG emissions and lower blue water use, and were cheaper. The energy and sugar content of UPD were similar to those of unprocessed or minimally processed drinks (MPD); associated with similar GHG emissions but blue water use was less, and they were also more expensive. In the average Dutch diet, per 2000 kcal, ultra-processed foods and drinks (UPFD) covered 29% (456 g UPF and 437 g UPD) of daily consumption and 61% of energy intake. UPFD consumption was higher among children than adults, especially for UPD. UPFD consumption determined 45% of GHG emissions, 23% of blue water use and 39% of expenses for daily food consumption. UPFD consumption contributed 54% to 72% to daily sodium, sugar and SFA intake. CONCLUSIONS: Compared with unprocessed or minimally processed foods and drinks, UPF and UPD were found to be less healthy considering their high energy, SFA, sugar and sodium content. However, UPF were associated higher GHG emissions and with less blue water use and food costs. Therefore daily blue water use and food costs might increase if UPF are replaced by those unprocessed or minimally processed. As nutritional quality, environmental impacts and food costs relate differently to the NOVA classification, the classification is not directly applicable to identify win-win-wins of nutritional quality, environmental impact and costs of diets.

Effects of Dutch livestock production on human health and the environment.

Observed multiple adverse effects of livestock production have led to increasing calls for more sustainable livestock production. Quantitative analysis of adverse effects, which can guide public debate and policy development in this area, is limited and generally scattered across environmental, human health, and other science domains. The aim of this study was to bring together and, where possible, quantify and aggregate the effects of national-scale livestock production on 17 impact categories, ranging from impacts of particulate matter, emerging infectious diseases and odor annoyance to airborne nitrogen deposition on terrestrial nature areas and greenhouse gas emissions. Effects were estimated and scaled to total Dutch livestock production, with system boundaries including feed production, manure management and transport, but excluding slaughtering, retail and consumption. Effects were expressed using eight indicators that directly express Impact in the sense of the Drivers-Pressures-State-Impact-Response framework, while the remaining 14 express Pressures or States. Results show that livestock production may contribute both positively and negatively to human health with a human disease burden (expressed in disability-adjusted life years) of up to 4% for three different health effects: those related to particulate matter, zoonoses, and occupational accidents. The contribution to environmental impact ranges from 2% for consumptive water use in the Netherlands to 95% for phosphorus transfer to soils, and extends beyond Dutch borders. While some aggregation across impact categories was possible, notably for burden of disease estimates, further aggregation of disparate indicators would require normative value judgement. Despite difficulty of aggregation, the assessment shows that impacts receive a different contribution of different animal sectors. While some of our results are country-specific, the overall approach is generic and can be adapted and tuned according to specific contexts and information needs in other regions, to allow informed decision making across a broad range of impact categories.

Healthy diets with reduced environmental impact? - The greenhouse gas emissions of various diets adhering to the Dutch food based dietary guidelines.

OBJECTIVE: To determine the differences in environmental impact and nutrient content of the current Dutch diet and four healthy diets aimed at lowering greenhouse gas (GHG) emissions. METHODS: GHG emissions (as proxy for environmental impact) and nutrient content of the current Dutch diet and four diets adhering to the Dutch food based dietary guidelines (Wheel of Five), were compared in a scenario study. Scenarios included a healthy diet with or without meat, and the same diets in which only foods with relatively low GHG emissions are chosen. For the current diet, data from the Dutch National Food Consumption Survey 2007-2010 were used. GHG emissions (in kg CO2-equivalents) were based on life cycle assessments. Results are reported for men and women aged 19-30years and 31-50years. RESULTS: The effect on GHG emissions of changing the current Dutch diet to a diet according to the Wheel of Five (corresponding with the current diet as close as possible), ranged from -13% for men aged 31-50years to +5% for women aged 19-30years. Replacing meat in this diet and/or consuming only foods with relatively low GHG emissions resulted in average GHG emission reductions varying from 28-46%. In the scenarios in which only foods with relatively low GHG emissions are consumed, fewer dietary reference intakes (DRIs) were met than in the other healthy diet scenarios. However, in all healthy diet scenarios the number of DRIs being met was equal to or higher than that in the current diet. CONCLUSIONS: Diets adhering to food based dietary guidelines did not substantially reduce GHG emissions compared to the current Dutch diet, when these diets stayed as close to the current diet as possible. Omitting meat from these healthy diets or consuming only foods with relatively low associated GHG emissions both resulted in GHG emission reductions of around a third. These findings may be used to expand food based dietary guidelines with information on how to reduce the environmental impact of healthy diets.

SimpleBox 4.0: Improving the model while keeping it simple .

Chemical behavior in the environment is often modeled with multimedia fate models. SimpleBox is one often-used multimedia fate model, firstly developed in 1986. Since then, two updated versions were published. Based on recent scientific developments and experience with SimpleBox 3.0, a new version of SimpleBox was developed and is made public here: SimpleBox 4.0. In this new model, eight major changes were implemented: removal of the local scale and vegetation compartments, addition of lake compartments and deep ocean compartments (including the thermohaline circulation), implementation of intermittent rain instead of drizzle and of depth dependent soil concentrations, adjustment of the partitioning behavior for organic acids and bases as well as of the value for enthalpy of vaporization. In this paper, the effects of the model changes in SimpleBox 4.0 on the predicted steady-state concentrations of chemical substances were explored for different substance groups (neutral organic substances, acids, bases, metals) in a standard emission scenario. In general, the largest differences between the predicted concentrations in the new and the old model are caused by the implementation of layered ocean compartments. Undesirable high model complexity caused by vegetation compartments and a local scale were removed to enlarge the simplicity and user friendliness of the model.

The Flash Environmental Assessment Tool: worldwide first aid for chemical accidents response, pro action, prevention and preparedness.

The United Nations response mechanism to environmental emergencies requested a tool to support disaster assessment and coordination actions by United Nations Disaster Assessment and Coordination (UNDAC) teams. The tool should support on-site decision making when substantial chemical emissions affect human health directly or via the environment and should be suitable for prioritizing impact reduction management options under challenging conditions worldwide. To answer this need, the Flash Environmental Assessment Tool (FEAT) was developed and the scientific and practical underpinning and application of this tool are described in this paper. FEAT consists of a printed decision framework and lookup tables, generated by combining the scientific data on chemicals, exposure pathways and vulnerabilities with the pragmatic needs of emergency field teams. Application of the tool yields information that can help prioritize impact reduction measures. The first years of use illustrated the usefulness of the tool as well as suggesting additional uses and improvements. An additional use is application of the back-office tool (Hazard Identification Tool, HIT), the results of which aid decision-making by the authorities of affected countries and the preparation of field teams for on-site deployment. Another extra use is in disaster pro action and prevention. In this case, the application of the tool supports safe land-use planning and improved technical design of chemical facilities. UNDAC teams are trained to use the tool after large-scale sudden onset natural disasters.

Environmental impact assessment of pharmaceutical prescriptions: Does location matter?

A methodology was developed for the assessment and comparison of the environmental impact of two alternative pharmaceutical prescriptions. This methodology provides physicians with the opportunity to include environmental considerations in their choice of prescription. A case study with the two antibiotics ciprofloxacin and levofloxacin at three locations throughout Europe showed that the preference for a pharmaceutical might show spatial variation, i.e. comparison of two pharmaceuticals might yield different results when prescribed at different locations. This holds when the comparison is based on both the impact on the aquatic environment and the impact on human health. The relative impacts of ciprofloxacin and levofloxacin on human health were largely determined by the local handling of secondary sludge, agricultural disposal practices, the extent of secondary sewage treatment, and local food consumption patterns. The relative impacts of ciprofloxacin and levofloxacin on the aquatic environment were mostly explained by the presence of specific sewage treatment techniques, as effluents from sewage treatment plants (STPs) are the most relevant emission pathway for the aquatic environment.

Spatially explicit prioritization of human antibiotics and antineoplastics in Europe.

This paper presents a screening tool for the location-specific prioritization of human pharmaceutical emissions in Europe, based on risk quotients for the aquatic environment and human health. The tool provides direction towards either monitoring activities or additional research. Its application is illustrated for a set of 11 human antibiotics and 7 antineoplastics. Risk quotients for the aquatic environment were highest for levofloxacin, doxycycline and ciprofloxacin, located in Northern Italy (Milan region; particularly levofloxacin) and other densely populated areas in Europe (e.g. London, Krakow and the Ruhr area). Risk quotients for human health not only depend on pharmaceutical and location, but also on behavioral characteristics, such as consumption patterns. Infants in eastern Spain that consume locally produced food and conventionally treated drinking water were predicted to run the highest risks. A limited comparison with measured concentrations in surface water showed that predicted and measured concentrations are approximately within one order of magnitude.

Environmental fate factors and human intake fractions for risk assessment of petroleum products.

Petroleum products may contain up to thousands of individual hydrocarbon compounds, which vary widely in environmental behavior and ecotoxicity. Environmental risk assessment of these complex substances is facilitated by use of the hydrocarbon block method (HBM). The HBM assigns similarly behaving hydrocarbons to the same blocks and then relates release rates of petroleum products to environmental concentrations and human intake rates by means of so-called environmental fate factors and human intake fractions of the hydrocarbon blocks. We have derived such fate factors and intake fractions and associated uncertainties with a library of representative hydrocarbon structures. Fate factors and intake fractions of over 1500 individual representative hydrocarbons have been modeled according to the EU Technical Guidance Documents. Fate factors and intake fractions for the chosen hydrocarbon blocks are then estimated from average values obtained for the individual compounds in the blocks. Fate factors and intake fractions of the hydrocarbon blocks vary by up to 10 orders of magnitude for the different emission scenarios and compartments/spatial scales. The highest fate factors are obtained for the exposure scenarios with the highest emission intensity (the local emission scenarios) and for the most direct exposure chain. Uncertainties introduced by the "blocking" method are typically smaller than 30% and rarely larger than a factor of 3. Various hydrocarbon blocking schemes of different resolution were tested, and all schemes investigated appeared to perform satisfactorily. The use of the library-based HBM was illustrated by assessing the aquatic ecological risk of gas oil, emitted to water. The aquatic risk characterization ratio of gas oil hydrocarbons in regional freshwater is estimated to be 6 × 10(−5) per unit of emission (1 kg/d released 1:10:100 to local, regional, and continental scales, respectively), with an uncertainty of 32%. In view of other uncertainties in environmental risk assessment, the precision achieved with the procedure presented here is judged to be reasonable.

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. The RMSE(log) was 5.4 for air, 5.6-6.3 for sediment and biota, and 5.5 for soil in the most detailed model scenario. Generally, model estimations tended to underestimate observed values for all compartments, except air. The decline in observed concentrations was also slightly underestimated by the model for the period where measurements were available (1989-2002). Applying a generic model setup with averaged emissions and averaged environmental characteristics, the RMSE(log) increased to 21 for air and 49 for sediment. For soil the RMSE(log) decreased to 3.5. We found that including spatial variation in emissions was most relevant for all compartments, except soil, while including spatial variation in environmental characteristics was less influential. For improving predictions of concentrations in sediment and aquatic biota, including emissions to water was found to be relevant as well.

Substance or space? The relative importance of substance properties and environmental characteristics in modeling the fate of chemicals in Europe.

The relative influence of substance properties and of environmental characteristics on the variation in the environmental fate of chemicals was studied systematically and comprehensively. This was done by modeling environmental concentrations for 200 sets of substance properties, representative of organic chemicals used, and 137 sets of environmental characteristics, representative of regions in Europe of 250 x 250 km. Since it was expected that the model scale has an influence on the predicted concentration variations, the calculations were repeated for regions with a 100 x 100 km and 50 x 50 km area. Stepwise multiple regression analysis was performed to determine the contribution of each of the individual input parameters on the total concentration variation. Depending on the scenario, the range in predicted environmental concentrations spreads from two up to nine orders of magnitude. In accord with earlier studies, variation in the fate of chemicals in the environment appeared to depend mainly on substance-specific partition coefficients and degradation rates. For the estimation of soil and water concentrations with direct emissions to these compartments, however, the influence of spatial variation in environmental characteristics can mount up to two orders of magnitude, a range that can be significant to account for in certain model applications. Concentration differences in water and soil are predicted to be larger if a smaller region is applied in the model calculations, and the relative influence of environmental characteristics on the total variation increases on a more detailed spatial scale. It is argued that the influence of environmental characteristics as predictors of exposure concentrations of chemicals deserves better attention in comparative risk assessment with conventional nonspatial multimedia box models.

Spatial variance in multimedia mass balance models: comparison of LOTOS-EUROS and SimpleBox for PCB-153.

The aim of this study was to determine whether nested generic box models can be used to predict spatial variance. An inter-comparison study was performed for the nested box model SimpleBox, and the spatially resolved model LOTOS-EUROS, using PCB-153 emissions in Europe as an example. We compared the two models concerning (1) average environmental concentrations, (2) spatial concentration variances, (3) spatial concentration patterns (maps), and (4) agreement with measured concentrations for the air and soil compartments. In SimpleBox, the spatial concentration variances and patterns were calculated subsequently for each separate grid cell surrounded by a regional and a continental shell with homogeneous, averaged circumstances. Average European PCB-153 concentrations calculated by LOTOS-EUROS and SimpleBox for the period 1981-2000 agree well for the air and soil compartments. Moreover, the predicted concentrations of both models are in line with the measured PCB-153 concentrations in Europe during that period. For PCB-153, the prediction of spatial concentration variances with the nested multimedia fate model SimpleBox performs adequately in most cases, except for the lower concentration boundary in the air compartment. It is concluded that SimpleBox can be used to predict the spatial maximum and average concentrations of PCB-153 in the air and soil compartments. The proposed method has to be tested systematically for different types of compounds, emission scenarios, environmental compartments and spatial scales in order to allow conclusions about the general applicability of the method.

Validation of predicted exponential concentration profiles of chemicals in soils.

Multimedia mass balance models assume well-mixed homogeneous compartments. Particularly for soils, this does not correspond to reality, which results in potentially large uncertainties in estimates of transport fluxes from soils. A theoretically expected exponential decrease model of chemical concentrations with depth has been proposed, but hardly tested against empirical data. In this paper, we explored the correspondence between theoretically predicted soil concentration profiles and 84 field measured profiles. In most cases, chemical concentrations in soils appear to decline exponentially with depth, and values for the chemical specific soil penetration depth (d(p)) are predicted within one order of magnitude. Over all, the reliability of multimedia models will improve when they account for depth-dependent soil concentrations, so we recommend to take into account the described theoretical exponential decrease model of chemical concentrations with depth in chemical fate studies. In this model the d(p)-values should estimated be either based on local conditions or on a fixed d(p)-value, which we recommend to be 10cm for chemicals with a log K(ow)>3.