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Significance China has undergone unprecedented increases in material development and by 2010 drove 30% of the global material footprint (MF). Understanding China’s MF distribution and development is critical for resource efficiency and circular economy ambitions globally. We combine a provincial input–output table (IOT), province-specific import–export statistics, a global IOT, and detailed extraction data to assess sector-specific and province-specific MFs in China. Capital investment—crucial to China’s development—is up to 4 times more resource-intensive than consumption and comprises 49 to 86% of provincial MF. We find large differences in MF per capita across provinces, even among those with similar development characteristics. Findings indicate the need for improved understanding of material developments in other emerging countries in the 21st century., High-income countries often outsource material demands to poorer countries along with the associated environmental damage. This phenomenon can also occur within (large) countries, such as China, which was responsible for 24 to 30% of the global material footprint (MF) between 2007 and 2010. Understanding the distribution and development of China’s MF is hence critical for resource efficiency and circular economy ambitions globally. Here we present a comprehensive analysis of China’s MF at the provincial and sectoral levels. We combine provincial-level input–output data with sector- and province-specific trade data, detailed material extraction data, and the global input–output database EXIOBASE. We find that some provinces have MFs equivalent to medium-sized, high-income countries and limited evidence of material decoupling. Lower-income regions with high levels of material extraction can have an MF per capita as large as developed provinces due to much higher material intensities. The higher-income south-coastal provinces have lower MF per capita than equally developed provinces. This finding relates partly to differences in economic structure but indicates the potential for improvement across provinces. Investment via capital formation is up to 4 times more resource-intensive than consumption and drives 49 to 86% of provincial-level MFs (the Organisation for Economic Co-operation and Development average is 37%). Resource-efficient production, efficient use of capital goods/infrastructure, and circular design are essential for reductions in China’s MF. Policy efforts to shift to a high-quality development model may reduce material intensities, preferably while avoiding the further outsourcing of high-intensity activities to other provinces or lower-income countries.

More than 5% of any population suffers from asthma, and there are indications that these individuals are more sensitive to nanoparticle aerosols than the healthy population. We used an air-liquid interface model of inhalation exposure to investigate global transcriptomic responses in reconstituted three-dimensional airway epithelia of healthy and asthmatic subjects exposed to pristine (nCuO) and carboxylated (nCuO(COOH)) copper oxide nanoparticle aerosols. A dose-dependent increase in cytotoxicity (highest in asthmatic donor cells) and pro-inflammatory signaling within 24 h confirmed the reliability and sensitivity of the system to detect acute inhalation toxicity. Gene expression changes between nanoparticle-exposed versus air-exposed cells were investigated. Hierarchical clustering based on the expression profiles of all differentially expressed genes (DEGs), cell-death-associated DEGs (567 genes), or a subset of 48 highly overlapping DEGs categorized all samples according to "exposure severity", wherein nanoparticle surface chemistry and asthma are incorporated into the dose-response axis. For example, asthmatics exposed to low and medium dose nCuO clustered with healthy donor cells exposed to medium and high dose nCuO, respectively. Of note, a set of genes with high relevance to mucociliary clearance were observed to distinctly differentiate asthmatic and healthy donor cells. These genes also responded differently to nCuO and nCuO(COOH) nanoparticles. Additionally, because response to transition-metal nanoparticles was a highly enriched Gene Ontology term (FDR 8 X 10(-13)) from the subset of 48 highly overlapping DEGs, these genes may represent biomarkers to a potentially large variety of metal/metal oxide nanoparticles.

L'Union européenne (UE) a acquis au cours des deux dernières décennies une position de leader dans la lutte contre le changement climatique. Cependant, malgré les progrès significatifs réalisés en matière de réduction des émissions de gaz à effet de serre (GES) au cours de cette période, l'efficacité du pilotage de la politique climatique et énergétique au niveau de l'UE demeure insatisfaisante. Dans cet article, nous nous efforçons d'identifier le rôle que l'UE peut jouer pour faciliter la mise en œuvre de politiques de transition énergétique ambitieuses. Tout d'abord, si la gestion des projets liés à la transition énergétique est généralement mieux adaptée au niveau local ou national, le niveau européen reste le plus approprié pour collecter des fonds ou piloter des infrastructures transnationales de réseaux d'énergie et de transport. Ceci est mis en évidence par une analyse des projets financés par le Fonds européen pour les investissements stratégiques (EFSI). Deuxièmement, au-delà des objectifs au niveau de l'UE, la coordination entre les États membres sur la définition de leurs infrastructures énergétiques est essentielle. Un déploiement réussi des énergies renouvelables nécessite un haut niveau d'intégration pour surmonter les difficultés liées à l'intermittence. Des stratégies opposées peuvent avoir des effets négatifs, ralentir la tendance actuelle des investissements dans les capacités renouvelables et empêcher ainsi l'UE de respecter les engagements déterminés par ses États membres au niveau national (Intended Nationally Determined Contributions, INDC). La coordination entre les politiques énergétiques nationales devrait être assurée au niveau de l'UE, qui pourrait associer plus efficacement les différentes sources de financement, constituer un marché de capacité et même définir une politique commune de la taxe carbone à côté du système d'échange de quotas d'émissions (Emissions Trading System, ETS). Enfin, la conception des politiques d'atténuation du changement climatique devrait mettre davantage l'accent sur les bénéfices commerciaux potentiels que l'UE peut tirer de sa position de leader dans ce domaine. La quasidisparition de l'industrie photovoltaïque européenne face à leurs concurrents chinois devrait faire prendre conscience aux autorités européennes que l'avantage actuel est fragile. Malgré une position significative de leader dans de nombreux domaines de lutte contre le changement climatique, les dividendes économiques dont l'UE pourrait profiter ne sont pas assurés par les politiques actuellement mises en œuvre. Il s'agit notamment d'aller au-delà de la recherche en R&D en consacrant davantage d'efforts à la commercialisation de produits et technologies innovants liés à la transition énergétique.

To a large extent, environmental macroeconomics is developing outside of the theoretical debates taking place in other fields of research in applied macroeconomics. This is evidenced by the low representation of environmental issues in mainstream economics journals and in advanced macroeconomics textbooks. While the environment has not up to now been considered as a subject in itself for advancing knowledge in macroeconomics, since the 1990s it has at least been an important topic for applying macroeconomic models. These models have been used in particular to analyse and quantify the economic effects of the transition to a sustainable system of production and consumption. We propose to shed light on the state of the art in applied environmental macroeconomics. More specifically, we will endeavour to identify the specific features of this area of research that explain the theoretical and empirical choices made. A© OFCE. Tous droits reserves pour tous pays.

A Lagrangian particle dispersion model, the FLEXible PARTicle dispersion chemical transport model (FLEXPART CTM), is used to simulate global three-dimensional fields of trace gas abundance. These fields are constrained with surface observation data through nudging, a data assimilation method, which relaxes model fields to observed values. Such fields are of interest to a variety of applications, such as inverse modelling, satellite retrievals, radiative forcing models and estimating global growth rates of greenhouse gases. Here, we apply this method to methane using 6 million model particles filling the global model domain. For each particle, methane mass tendencies due to emissions (based on several inventories) and loss by reaction with OH, Cl and O(1D), as well as observation data nudging were calculated. Model particles were transported by mean, turbulent and convective transport driven by 1∘×1∘ ERA-Interim meteorology. Nudging is applied at 79 surface stations, which are mostly included in the World Data Centre for Greenhouse Gases (WDCGG) database or the Japan–Russia Siberian Tall Tower Inland Observation Network (JR-STATION) in Siberia. For simulations of 1 year (2013), we perform a sensitivity analysis to show how nudging settings affect modelled concentration fields. These are evaluated with a set of independent surface observations and with vertical profiles in North America from the National Oceanic and Atmospheric Administration (NOAA) Earth System Research Laboratory (ESRL), and in Siberia from the Airborne Extensive Regional Observations in SIBeria (YAK-AEROSIB) and the National Institute for Environmental Studies (NIES). FLEXPART CTM results are also compared to simulations from the global Eulerian chemistry Transport Model version 5 (TM5) based on optimized fluxes. Results show that nudging strongly improves modelled methane near the surface, not only at the nudging locations but also at independent stations. Mean bias at all surface locations could be reduced from over 20 to less than 5 ppb through nudging. Near the surface, FLEXPART CTM, including nudging, appears better able to capture methane molar mixing ratios than TM5 with optimized fluxes, based on a larger bias of over 13 ppb in TM5 simulations. The vertical profiles indicate that nudging affects model methane at high altitudes, yet leads to little improvement in the model results there. Averaged from 19 aircraft profile locations in North America and Siberia, root mean square error (RMSE) changes only from 16.3 to 15.7 ppb through nudging, while the mean absolute bias increases from 5.3 to 8.2 ppb. The performance for vertical profiles is thereby similar to TM5 simulations based on TM5 optimized fluxes where we found a bias of 5 ppb and RMSE of 15.9 ppb. With this rather simple model setup, we thus provide three-dimensional methane fields suitable for use as boundary conditions in regional inverse modelling as a priori information for satellite retrievals and for more accurate estimation of mean mixing ratios and growth rates. The method is also applicable to other long-lived trace gases.

A data assimilation system for the LOTOS-EUROS chemical transport model has been implemented to improve the simulation and forecast of PM10 and PM2.5 in a densely populated urban valley of the tropical Andes. The Aburrá Valley in Colombia was used as a case study, given data availability and current environmental issues related to population expansion. The data assimilation system is an Ensemble Kalman filter with covariance localization based on specification of uncertainties in the emissions. Observations assimilated were obtained from a surface network for the period March–April of 2016, a period of one of the worst air quality crisis in recent history of the region. In a first series of experiments, the spatial length scale of the covariance localization and the temporal length scale of the stochastic model for the emission uncertainty were calibrated to optimize the assimilation system. The calibrated system was then used in a series of assimilation experiments, where simulation of particulate matter concentrations was strongly improved during the assimilation period, which also improved the ability to accurately forecast PM10 and PM2.5 concentrations over a period of several days. © 2020 Elsevier Ltd

A large fraction of the urban population in Europe is exposed to particulate matter levels above the WHO guideline value. To make more effective mitigation strategies, it is important to understand the influence on particulate matter (PM) from pollutants emitted in different European nations. In this study, we evaluate a country source contribution forecasting system aimed at assessing the domestic and transboundary contributions to PM in major European cities for an episode in December 2016. The system is composed of two models (EMEP/MSC-W rv4.15 and LOTOS-EUROS v2.0), which allows the consideration of differences in the source attribution. We also compared the PM10 concentrations, and both models present satisfactory agreement in the 4 d forecasts of the surface concentrations, since the hourly concentrations can be highly correlated with in situ observations. The correlation coefficients reach values of up to 0.58 for LOTOS-EUROS and 0.50 for EMEP for the urban stations; the values are 0.58 for LOTOS-EUROS and 0.72 for EMEP for the rural stations. However, the models underpredict the highest hourly concentrations measured by the urban stations (mean underestimation of 36 %), which is to be expected given the relatively coarse model resolution used (0.25∘ longitude × 0.125∘ latitude). For the source attribution calculations, LOTOS-EUROS uses a labelling technique, while the EMEP/MSC-W model uses a scenario having reduced anthropogenic emissions, and then it is compared to a reference run where no changes are applied. Different percentages (5 %, 15 %, and 50 %) for the reduced emissions in the EMEP/MSC-W model were used to test the robustness of the methodology. The impact of the different ways to define the urban area for the studied cities was also investigated (i.e. one model grid cell, nine grid cells, and grid cells covering the definition given by the Global Administrative Areas – GADM). We found that the combination of a 15 % emission reduction and a larger domain (nine grid cells or GADM) helps to preserve the linearity between emission and concentrations changes. The nonlinearity, related to the emission reduction scenario used, is suggested by the nature of the mismatch between the total concentration and the sum of the concentrations from different calculated sources. Even limited, this nonlinearity is observed in the NO3-, NH4+, and H2O concentrations, which is related to gas–aerosol partitioning of the species. The use of a 15 % emission reduction and of a larger city domain also causes better agreement on the determination of the main country contributors between both country source calculations. Over the 34 European cities investigated, PM10 was dominated by domestic emissions for the studied episode (1–9 December 2016). The two models generally agree on the dominant external country contributor (68 % on an hourly basis) to PM10 concentrations. Overall, 75 % of the hourly predicted PM10 concentrations of both models have the same top five main country contributors. Better agreement on the dominant country contributor for primary (emitted) species (70 % is found for primary organic matter (POM) and 80 % for elemental carbon – EC) than for the inorganic secondary component of the aerosol (50 %), which is predictable due to the conceptual differences in the source attribution used by both models. The country contribution calculated by the scenario approach depends on the chemical regime, which largely impacts the secondary components, unlike the calculation using the labelling approach.

Satellite observes large methane emissions from the Permian Basin in the United States., Using new satellite observations and atmospheric inverse modeling, we report methane emissions from the Permian Basin, which is among the world’s most prolific oil-producing regions and accounts for >30% of total U.S. oil production. Based on satellite measurements from May 2018 to March 2019, Permian methane emissions from oil and natural gas production are estimated to be 2.7 ± 0.5 Tg a−1, representing the largest methane flux ever reported from a U.S. oil/gas-producing region and are more than two times higher than bottom-up inventory-based estimates. This magnitude of emissions is 3.7% of the gross gas extracted in the Permian, i.e., ~60% higher than the national average leakage rate. The high methane leakage rate is likely contributed by extensive venting and flaring, resulting from insufficient infrastructure to process and transport natural gas. This work demonstrates a high-resolution satellite data–based atmospheric inversion framework, providing a robust top-down analytical tool for quantifying and evaluating subregional methane emissions.

In 2006, public and private parties parties (municipality of Ameland, GasTerra, NAM, Eneco) agreed to jointly and individually invest in projects to contribute to the energy transition of Ameland and to stimulate sustainable economic growth and social entrepreneurship with the formalization of convenant Duurzaam Ameland. Between 2006 and 2018 the covenant expanded (Phillips, Alliander, EnTrance, TNO) and 8 large, innovative energy projects were realized. However, to achieve the goal to be ahead of the Dutch energy transition by 10-15 years the parties have to reconsider the current collaboration and project realization in the covenant. At the same time, the lessons learned and experiences of the parties on Ameland in the past 12 years are valuable for other transition regions. This moment was taken as an opportunity to look back at the process in an evaluation study. The evaluation study is carried out by TNO and the Hanze University of Applied Sciences, within the research program ESTRAC Transforming Regions. In ESTRAC the aim is to develop a practice based methodology to support the most important stakeholders in decision making on regional energy transition. The methodology is developed based on several cases in the built environment and the industrial environment. This research serves as an input case for the built environment This research evaluates the transition process as it has developed on Ameland in the last 10 years. The research focuses on the collaboration between parties, the results achieved and the participation process with the people of Ameland. In 20 interviews and a collective workshop with the key stakeholders the different experiences and perspectives on the transition of Ameland and the collaboration in the covenant Duurzaam Ameland are collected

Quantification of greenhouse gas emissions is receiving a lot of attention because of its relevance for climate mitigation. Complementary to official reported bottomup emission inventories, quantification can be done with an inverse modelling framework, combining atmospheric transport models, prior gridded emission inventories and a network of atmospheric observations to optimize the emission inventories. An important aspect of such a method is a correct quantification of the uncertainties in all aspects of the modelling framework. The uncertainties in gridded emission inventories are, however, not systematically analysed. In this work, a statistically coherent method is used to quantify the uncertainties in a high-resolution gridded emission inventory of CO2 and CO for Europe. We perform a range of Monte Carlo simulations to determine the effect of uncertainties in different inventory components, including the spatial and temporal distribution, on the uncertainty in total emissions and the resulting atmospheric mixing ratios. We find that the uncertainties in the total emissions for the selected domain are 1 % for CO2 and 6 % for CO. Introducing spatial disaggregation causes a significant increase in the uncertainty of up to 40 % for CO2 and 70 % for CO for specific grid cells. Using gridded uncertainties, specific regions can be defined that have the largest uncertainty in emissions and are thus an interesting target for inverse modellers. However, the largest sectors are usually the best-constrained ones (low relative uncertainty), so the absolute uncertainty is the bes indicator for this. With this knowledge, areas can be identified that are most sensitive to the largest emission uncertainties, which supports network design.

We present a modelling framework for fossil fuel CO2 emissions in an urban environment, which allows constraints from emission inventories to be combined with atmospheric observations of CO2 and its co-emitted species CO, NOx , and SO2. Rather than a static assignment of average emission rates to each unit area of the urban domain, the fossil fuel emissions we use are dynamic: they vary in time and space in relation to data that describe or approximate the activity within a sector, such as traffic density, power demand, 2 m temperature (as proxy for heating demand), and sunlight and wind speed (as proxies for renewable energy supply). Through inverse modelling, we optimize the relationships between these activity data and the resulting emissions of all species within the dynamic fossil fuel emission model, based on atmospheric mole fraction observations. The advantage of this novel approach is that the optimized parameters (emission factors and emission ratios, N = 44) in this dynamic emission model (a) vary much less over space and time, (b) allow for a physical interpretation of mean and uncertainty, and (c) have better defined uncertainties and covariance structure. This makes them more suited to extrapolate, optimize, and interpret than the gridded emissions themselves. The merits of this approach are investigated using a pseudo-observation-based ensemble Kalman filter inversion set-up for the Dutch Rijnmond area at 1 km×1 km resolution. We find that the fossil fuel emission model approximates the gridded emissions well (annual mean differences < 2 %, hourly temporal r 2 = 0.21–0.95), while reported errors in the underlying parameters allow a full covariance structure to be created readily. Propagating this error structure into atmospheric mole fractions shows a strong dominance of a few large sectors and a few dominant uncertainties, most notably the emission ratios of the various gases considered. If the prior emission ratios are either sufficiently well-known or well constrained from a dense observation network, we find that including observations of co-emitted species improves our ability to estimate emissions per sector relative to usingCO2 mole fractions only. Nevertheless, the total CO2 emissions can be well constrained with CO2 as the only tracer in the inversion. Because some sectors are sampled only sparsely over a day, we find that propagating solutions from day-to-day leads to largest uncertainty reduction and smallest CO2 residuals over the 14 consecutive days considered. Although we can technically estimate the temporal distribution of some emission categories like shipping separate from their total magnitude, the controlling parameters are difficult to distinguish. Overall, we conclude that our new system looks promising for application in verification studies, provided that reliable urban atmospheric transport fields and reasonable a priori emission ratios for CO2 and its co-emitted species can be produced.

De uitstoot van ammoniak in Nederland is in 2018 met 0,6 kiloton is afgenomen ten opzichte van 2017. Dit komt vooral door ontwikkelingen in de landbouw, waar minder runderen worden gehouden en er steeds meer varkensstallen komen die minder ammoniak uitstoten. Toch ligt de uitstoot van ammoniak in 2018 met 129,3 kiloton boven het maximum van 128 kiloton dat vanuit Europa voor Nederland is bepaald. De uitstoot van stikstofoxiden en zwaveldioxide is in 2018 licht gedaald, met respectievelijk 8,6 en 1,6 kiloton. Minder stikstofoxiden komt onder andere door de strengere eisen voor de uitstoot door personenauto’s en vrachtverkeer, en doordat energiecentrales minder steenkool gebruiken. Minder zwaveloxiden komt vooral doordat raffinaderijen niet meer op olie maar op gas stoken, met een betere rookgasreiniging. De uitstoot van beide stoffen blijft onder de vastgestelde maxima. Ook de emissies van fijnstof zijn iets gedaald. Dat komt door aanpassingen in productie processen en toenemend gebruik van stoffilters in de industrie, en door strengere eisen voor de uitstoot door wegverkeer. De uitstoot van vluchtige organische stoffen is in 2018 met 13,1 kiloton afgenomen tot 241,6 kiloton, maar ligt wel boven het maximum van 185 kiloton. De afname wordt vooral veroorzaakt doordat in de landbouw minder kuilvoer nodig is. Een andere reden zijn extra milieumaatregelen bij de energieproductie en in de industrie

De uitstoot van ammoniak in Nederland is in 2018 met 0,6 kiloton is afgenomen ten opzichte van 2017. Dit komt vooral door ontwikkelingen in de landbouw, waar minder runderen worden gehouden en er steeds meer varkensstallen komen die minder ammoniak uitstoten. Toch ligt de uitstoot van ammoniak in 2018 met 129,3 kiloton boven het maximum van 128 kiloton dat vanuit Europa voor Nederland is bepaald. De uitstoot van stikstofoxiden en zwaveldioxide is in 2018 licht gedaald, met respectievelijk 8,6 en 1,6 kiloton. Minder stikstofoxiden komt onder andere door de strengere eisen voor de uitstoot door personenauto’s en vrachtverkeer, en doordat energiecentrales minder steenkool gebruiken. Minder zwaveloxiden komt vooral doordat raffinaderijen niet meer op olie maar op gas stoken, met een betere rookgasreiniging. De uitstoot van beide stoffen blijft onder de vastgestelde maxima. Ook de emissies van fijnstof zijn iets gedaald. Dat komt door aanpassingen in productie processen en toenemend gebruik van stoffilters in de industrie, en door strengere eisen voor de uitstoot door wegverkeer. De uitstoot van vluchtige organische stoffen is in 2018 met 13,1 kiloton afgenomen tot 241,6 kiloton, maar ligt wel boven het maximum van 185 kiloton. De afname wordt vooral veroorzaakt doordat in de landbouw minder kuilvoer nodig is. Een andere reden zijn extra milieumaatregelen bij de energieproductie en in de industrie

Total greenhouse gas (GHG) emissions in the Netherlands in 2018 decreased by approximately 2.7 percent, in comparison with 2017 emissions. This decrease was mainly the result of decreased coal combustion for energy and heat production.In 2018, total GHG emissions (including indirect CO2 emissions and excluding emissions from Land use, land use change and forestry (LULUCF)) in the Netherlands amounted to 188.2 Tg CO2 eq. This is approximately 15.1 percent below the emissions in the base year 1990 (221.7 Tg CO2 eq.).CO2 emissions in 2018 were 1.6 percent below the level in the base year. The total of the emissions of methane, nitrous oxide and fluorinated gases (CH4, N2O and F-gases) was reduced by more than 50% over this period.This report documents the Netherlands’ annual submission for 2020 of its GHG emissions inventory in accordance with the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC, 2006) prescribed by the United Nations Framework Convention on Climate Change (UNFCCC), the Kyoto Protocol (KP) and the European Union’s Greenhouse Gas Monitoring Mechanism.This report includes explanations of observed trends in emissions, an assessment of the sources with the highest contribution to total national emissions (key sources) and a description of the uncertainty in the emissions es timates. Estimation methods, data sources and emission factors (EFs) are described for each source category, and there is also a description of the quality assurance system and the verification activities performed on the data. The report also describes changes in methodologies since the previous submission (NIR 2019), the results of recalculations and planned improvements.

The diversity and increasing prevalence of products derived from engineered nanomaterials (ENM), warrants implementation of non-animal approaches to health hazard assessment for ethical and practical reasons. Although non-animal approaches are becoming increasingly popular, there are almost no studies of side-by-side comparisons with traditional in vivo assays. Here, transcriptomics is used to investigate mechanistic similarities between healthy/asthmatic models of 3D air–liquid interface (ALI) cultures of donor-derived human bronchial epithelia cells, and mouse lung tissue, following exposure to copper oxide ENM. Only 19% of mouse lung genes with human orthologues are not expressed in the human 3D ALI model. Despite differences in taxonomy and cellular complexity between the systems, a core subset of matching genes cluster mouse and human samples strictly based on ENM dose (exposure severity). Overlapping gene orthologue pairs are highly enriched for innate immune functions, suggesting an important and maybe underestimated role of epithelial cells. In conclusion, 3D ALI models based on epithelial cells, are primed to bridge the gap between traditional 2D in vitro assays and animal models of airway exposure, and transcriptomics appears to be a unifying dose metric that links in vivo and in vitro test systems. © 2020 The Authors. Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

Dit rapport is een achtergronddocument bij de analyse van PBL van maatregelen voorgesteld door het Kabinet om kosteneffectief de stikstofdepositie te verlagen. In dit rapport worden in aparte factsheets de effecten en kosten voor vijf maatregelen voor de sector mobiliteit gepresenteerd (hoofdstuk 6 uit de koepelnotitie van PBL). De analyse is gebaseerd op de omschrijving van deze maatregelen zoals die in fiches door het Ministerie van Infrastructuur en Waterstaat (IenW) zijn aangeleverd op 19 februari 2020. De maatregelen zijn, voor zover de huidige kennis dat toelaat, beoordeeld op kosten en effecten door PBL, TNO en CE Delft. Voor sommige beleidsopties zijn meerdere varianten onderzocht. Dit rapport is de bundeling van de analyses van de vijf opties voor mobiliteit die door het kabinet zijn opgenomen in het voorgestelde pakket stikstofmaatregelen. De maatvoering van deze maatregelen, zoals die door het kabinet is voorgesteld eind april 2020, wijkt in sommige gevallen af van de opties zoals deze zijn onderzocht op basis van de op 19 februari 2020 door het Ministerie aangeleverde fiches. Waar dit van toepassing is, staat dit beschreven in de koepelnotitie van PBL

A circular economy is an industrial system that is restorative or regenerative by intention or design. During the last decade, the circular economy became an attractive paradigm to increase global welfare while minimizing the environmental impacts of economic activities. Although several studies concerning the potential benefits and drawbacks of policies that implement the new paradigm have been performed, there is currently no standardized theoretical model or software to execute such assessment. In order to fill this gap, in the present paper we show how to perform these analyses using Environmentally Extended Input-Output Analysis. We also describe a python package (pycirk) for modeling Circular Economy scenarios in the context of the Environmentally Extended Multi-Regional Input-Output database EXIOBASE V3.3, for the year 2011. We exemplify the methods and software through a what-if zero-cost case study on two circular economy strategies (Resource Efficiency and Product Lifetime Extension), four environmental pressures and two socio-economic factors. © 2019 The Authors

In 2006, public and private parties parties (municipality of Ameland, GasTerra, NAM, Eneco) agreed to jointly and individually invest in projects to contribute to the energy transition of Ameland and to stimulate sustainable economic growth and social entrepreneurship with the formalization of convenant Duurzaam Ameland. Between 2006 and 2018 the covenant expanded (Phillips, Alliander, EnTrance, TNO) and 8 large, innovative energy projects were realized. However, to achieve the goal to be ahead of the Dutch energy transition by 10-15 years the parties have to reconsider the current collaboration and project realization in the covenant. At the same time, the lessons learned and experiences of the parties on Ameland in the past 12 years are valuable for other transition regions. This moment was taken as an opportunity to look back at the process in an evaluation study. The evaluation study is carried out by TNO and the Hanze University of Applied Sciences, within the research program ESTRAC Transforming Regions. In ESTRAC the aim is to develop a practice based methodology to support the most important stakeholders in decision making on regional energy transition. The methodology is developed based on several cases in the built environment and the industrial environment. This research serves as an input case for the built environment This research evaluates the transition process as it has developed on Ameland in the last 10 years. The research focuses on the collaboration between parties, the results achieved and the participation process with the people of Ameland. In 20 interviews and a collective workshop with the key stakeholders the different experiences and perspectives on the transition of Ameland and the collaboration in the covenant Duurzaam Ameland are collected

This study presents the first investigation of the methane (CH4) emissions of a big festival. In 2018 we measured the CH4 emissions of Munich Oktoberfest, the world's largest folk festival, using in-situ measurements combined with a Gaussian plume dispersion model. Oktoberfest is a potential source for CH4 as a high amount of natural gas for cooking and heating is used. Measurements were performed by walking and biking around the perimeter of the Oktoberfest premises (Theresienwiese) at different times of the day, during the week and at the weekend. The measurements show enhancements of up to 100 ppb compared to background values and measurements performed after Oktoberfest. The average emission flux of Oktoberfest is determined as 6.7 ± 0.6 μg/(m2s). Additional analyses, including the daily emission cycle and comparisons between emissions and the number of visitors, suggest that CH4 emissions of Oktoberfest are not only due to the human biogenic emissions; it is likely that fossil fuel CH4 emissions, such as incomplete combustion or loss in the gas appliances, are the major contributors to Oktoberfest emissions. Our results can help to develop CH4 reduction policies and measures to reduce emissions at festivals and other major events in cities. Furthermore, events with a limited duration have not yet been included in the state-of-the-art emission inventories, such as TNO-MACC, EDGAR or IER. Our investigations show that these emissions are not negligible. Therefore, these events should be included in future emission inventories.

Silicon dioxide (silica, SiO2, SAS) and titanium dioxide (TiO2) are produced in high volumes and applied in many consumer and food products. As a consequence, there is a potential human exposure and subsequent systemic uptake of these particles. In this study we show the characterization and quantification of both total silicon (Si) and titanium (Ti), and particulate SiO2 and TiO2 in postmortem tissue samples from 15 deceased persons. Included tissues are liver, spleen, kidney and the intestinal tissues jejunum and ileum. Low-level analysis was enabled by the use of fully validated sample digestion methods combined with (single particle) inductively coupled plasma high resolution mass spectrometry techniques (spICP-HRMS). The results show a total-Si concentration ranging from

Since the industrial revolution we have relied heavily on fossil fuels as feedstock and energy source. A major drawback in using fossil fuels is the emission of anthropogenic greenhouse gases. Deep reductions in these greenhouse gas emissions are needed if climate change is to be limited to 1.5-2°C above pre-industrial levels. These reductions will require a drastic transformation of the energy system as indicated by scenario studies which have evaluated possible roadmaps for this transformation. There is no straightforward solution to make a transition from a fossil-driven energy system to one based on renewables. There are many technological options to consider and which options work best depends to a great extent on local and regional circumstances. Therefore, it is increasingly recognized that the energy transition will take place at the local and regional level. This is where major decisions will have to be made.

In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants for a period of 17 d during the Second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) that took place at Cabauw, the Netherlands (51.97-N, 4.93-E). We report on the outcome of the formal semi-blind intercomparison exercise, which was held under the umbrella of the Network for the Detection of Atmospheric Composition Change (NDACC) and the European Space Agency (ESA). The three major goals of CINDI-2 were (1) to characterise and better understand the differences between a large number of multi-axis differential optical absorption spectroscopy (MAX-DOAS) and zenith-sky DOAS instruments and analysis methods, (2) to define a robust methodology for performance assessment of all participating instruments, and (3) to contribute to a harmonisation of the measurement settings and retrieval methods. This, in turn, creates the capability to produce consistent high-quality ground-based data sets, which are an essential requirement to generate reliable long-term measurement time series suitable for trend analysis and satellite data validation. The data products investigated during the semi-blind intercomparison are slant columns of nitrogen dioxide (NO2), the oxygen collision complex (O4) and ozone (O3) measured in the UV and visible wavelength region, formaldehyde (HCHO) in the UV spectral region, and NO2 in an additional (smaller) wavelength range in the visible region. The campaign design and implementation processes are discussed in detail including the measurement protocol, calibration procedures and slant column retrieval settings. Strong emphasis was put on the careful alignment and synchronisation of the measurement systems, resulting in a unique set of measurements made under highly comparable air mass conditions. The CINDI-2 data sets were investigated using a regression analysis of the slant columns measured by each instrument and for each of the target data products. The slope and intercept of the regression analysis respectively quantify the mean systematic bias and offset of the individual data sets against the selected reference (which is obtained from the median of either all data sets or a subset), and the rms error provides an estimate of the measurement noise or dispersion. These three criteria are examined and for each of the parameters and each of the data products, performance thresholds are set and applied to all the measurements. The approach presented here has been developed based on heritage from previous intercomparison exercises. It introduces a quantitative assessment of the consistency between all the participating instruments for the MAX-DOAS and zenith-sky DOAS techniques. ©Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License.

Natural sea-salt aerosols, when interacting with anthropogenic emissions, can enhance the formation of particulate nitrate. This enhancement has been suggested to increase the direct radiative forcing of nitrate, called the "massenhancement effect". Through a size-resolved dynamic mass transfer modeling approach, we show that interactions with sea salt shift the nitrate from sub-to super-micron-sized particles ("redistribution effect"), and hence this lowers its efficiency for light extinction and reduces its lifetime. The redistribution effect overwhelms the mass-enhancement effect and significantly moderates nitrate cooling; e.g., the nitrateassociated aerosol optical depth can be reduced by 10 %-20% over European polluted regions during a typical seasalt event, in contrast to an increase by ∼ 10% when only accounting for the mass-enhancement effect. Global model simulations indicate significant redistribution over coastal and offshore regions worldwide. Our study suggests a strong buffering by natural sea-salt aerosols that reduces the climate forcing of anthropogenic nitrate, which had been expected to dominate the aerosol cooling by the end of the century. Comprehensive considerations of this redistribution effect foster better understandings of climate change and nitrogen deposition. © Author(s) 2020.

De directie Bouwen en Energie van het ministerie van Binnenlandse Zaken en Koninkrijksrelaties (BZK) heeft in het kader van de toekomststrategie energiebesparing utiliteitsbouw behoefte aan een korte Kentallennotitie waarin de best beschikbare voorraad- en energieverbruiksgegevens voor de utiliteitsbouw op een toegankelijke manier worden gepresenteerd en voorzien van enige uitleg. In deze notitie schetst ECN part of TNO deze voorraad en energieverbruiksgegevens voor de utiliteitsbouw, en daarbinnen de dienstensector

The nitrogen cycle has been continuously disrupted by human activity over the past century, resulting in almost a tripling of the total reactive nitrogen fixation in Europe. Consequently, excessive amounts of reactive nitrogen (Nr) have manifested in the environment, leading to a cascade of adverse effects, such as acidification and eutrophication of terrestrial and aquatic ecosystems, and particulate matter formation. Chemistry transport models (CTMs) are frequently used as tools to simulate the complex chain of processes that determine atmospheric Nr flows. In these models, the parameterization of the atmosphere–biosphere exchange of Nr is largely based on few surface exchange measurement and is therefore known to be highly uncertain. In addition to this, the input parameters that are used here are often fixed values, only linked to specific land use classes. In an attempt to improve this, a combination of multiple satellite products is used to derive updated,time-variant leaf area index (LAI) and roughness length (z0) input maps. As LAI, we use the Moderate Resolution Imaging Spectroradiometer (MODIS) MCD15A2H product. The monthly z0 input maps presented in this paper are a function of satellite derived normalized difference vegetation index (NDVI) values (MYD13A3 product) for short vegetation types (such as grass and arable land) and a combination of satellite-derived forest canopy height and LAI for forests. The use of these growth-dependent satellite products allows us to represent the growing season more realistically. For urban areas, the z0 values are updated,too, and linked to a population density map. The approach to derive these dynamic z0 estimates can be linked to any land use map and is as such transferable to othermodels.We evaluated the sensitivity of the modelled Nr deposition fields in LOng Term Ozone Simulation – EURopean Operational Smog (LOTOS-EUROS)v2.0to the above mentioned changes in LAI and z0 inputs, focusing on Germany, the Netherlands and Belgium. We computed z0 values from FLUXNET sites and compared these to the default and updated z0 values in LOTOS-EUROS.The root mean square difference (RMSD) for both short vegetation and forest sites improved. Comparing all sites, the RMSD decreased from 0.76 (default z0) to 0.60 (updated z0). The implementation of these updated LAI and z0 input maps led to local changes in the total Nr deposition of up to∼30% and a general shift from wet to dry deposition. The most distinct changes are observed in land-use-specific deposition fluxes. These fluxes may show relatively large deviations, locally affecting estimated critical load exceedances for specific natural ecosystems

In 2018 is de totale uitstoot van broeikasgassen in Nederland met 2,7 procent gedaald ten opzichte van 2017. Deze daling komt vooral doordat er minder kolen zijn gebruikt om elektriciteit te produceren. De totale uitstoot van broeikasgassen naar de lucht wordt uitgedrukt in CO2-equivalenten en bedroeg in 2018 188,2 miljard kilogram. Het jaar 1990 geldt als referentiejaar (het zogeheten Kyoto-basisjaar) voor de te halen doelstellingen. De uitstoot in 1990 bedroeg 221,7 miljard kilogram CO2-equivalenten. Ten opzichte van het basisjaar is de uitstoot gedaald met 15,1 procent. De uitstoot van CO2 alleen ligt 1,6 procent onder het niveau van het basisjaar. De uitstoot van de andere broeikasgassen (methaan, distikstofoxide en gefluoreerde gassen) is sinds 1990 met meer dan 50 procent gedaald. Dit blijkt uit de inventarisatie van broeikasgasemissies die het RIVM jaarlijks op verzoek van het Ministerie van Economische Zaken en Klimaat (EZK) opstelt. Met deze inventarisatie voldoet Nederland aan de nationale rapportageverplichtingen voor 2020 van het Klimaatverdrag van de Verenigde Naties (UNFCCC), van het Kyoto Protocol en van het Bewakingsmechanisme Broeikasgassen van de Europese Unie

Urban mining from construction and demolition waste (CDW) is highly relevant for the circular economy ambitions of the European Union (EU). Given the large volumes involved, end-of-life (EoL) concrete is identified as one of the priority streams for CDW recycling in most EU countries, but it is currently largely downcycled or even landfilled. The European projects C2CA and VEEP have proposed several cost-effective technologies to recover EoL concrete for new concrete manufacturing. To understand the potential effects of large-scale implementation of those recycling technologies on the circular construction, this study deployed static material flow analysis (MFA) for a set of EoL concrete management scenarios in the Netherlands constructed by considering the development factors in two, technological and temporal dimensions. On the technological dimension, three treatment systems for EoL concrete management, namely: business-as-usual treatment, C2CA technological system and VEEP technological system were investigated. On the temporal dimension, 2015 was selected as the reference year, representing the current situation, and 2025 as the future year for the prospective analysis. The results show that the development of cost-effective technologies has the potential to improve the share of recycling (as opposed to downcycling) in the Netherlands from around 5% in 2015 up to 22%–32% in 2025. From the academic aspect, the presented work illustrates how the temporal dimension can be included in the static MFA study to explore the potential effects in the future.

Dit rapport is een achtergronddocument bij de analyse van PBL van maatregelen voorgesteld door het Kabinet om kosteneffectief de stikstofdepositie te verlagen. In dit rapport worden in aparte factsheets de effecten en kosten voor vijf maatregelen voor de sector mobiliteit gepresenteerd (hoofdstuk 6 uit de koepelnotitie van PBL). De analyse is gebaseerd op de omschrijving van deze maatregelen zoals die in fiches door het Ministerie van Infrastructuur en Waterstaat (IenW) zijn aangeleverd op 19 februari 2020. De maatregelen zijn, voor zover de huidige kennis dat toelaat, beoordeeld op kosten en effecten door PBL, TNO en CE Delft. Voor sommige beleidsopties zijn meerdere varianten onderzocht. Dit rapport is de bundeling van de analyses van de vijf opties voor mobiliteit die door het kabinet zijn opgenomen in het voorgestelde pakket stikstofmaatregelen. De maatvoering van deze maatregelen, zoals die door het kabinet is voorgesteld eind april 2020, wijkt in sommige gevallen af van de opties zoals deze zijn onderzocht op basis van de op 19 februari 2020 door het Ministerie aangeleverde fiches. Waar dit van toepassing is, staat dit beschreven in de koepelnotitie van PBL

In dit TNO-rapport, opgesteld voor het Planbureau voor de Leefomgeving (PBL), beschrijven en duiden we de meest recente ontwikkelingen in de sector mobiliteit voor zes deelgebieden. Hierbij geven we per deelgebied een inschatting van de gevolgen van deze ontwikkelingen op de toekomstige uitstoot van CO2- en/of luchtverontreinigende stoffen. Het eerste deel van dit rapport (de hoofdstukken 2 en 3) richt zich op de verwachte CO2-uitstoot door het wegverkeer en de inzet van biobrandstoffen tussen nu en 2030. Het PBL heeft deze inzichten en cijfers (mede) gebruikt ter onderbouwing van het hoofdstuk Mobiliteit in de Klimaat- en Energieverkenning 2019 (KEV 2019; Schoots en Hammingh, 2019). De KEV-2019 geeft een projectie van het te verwachten energieverbruik en de emissies van broeikasgassen tot en met 2030 voor alle sectoren, waar mobiliteit er één van is. Het tweede deel van dit rapport (de hoofdstukken 4, 5 en 6) richt zich vooral op de verwachte emissies van luchtverontreinigende stoffen door het niet-wegverkeer (NRMM1, Binnenvaart, Zeevaart). Voor ieder van deze drie laatstgenoemde subsectoren zijn ook de onderliggende modellen geactualiseerd die gebruikt worden om de (toekomstige) emissies van luchtverontreinigende stoffen te kwantificeren. Het PBL heeft deze inzichten, cijfers en geactualiseerde modellen (mede) gebruikt ter onderbouwing van het KEV onderdeel “Emissieramingen luchtverontreinigende stoffen”, dat in het voorjaar van 2020 wordt gepubliceerd. De KEV 2019 is gebaseerd op de (beleids)situatie op 1 mei 2019. Ook in ons rapport hebben wij dit ijkpunt aangehouden. Dit betekent dat het Klimaatakkoord2 van 28 juni 2019 en de lopende nationale doorvertaling van Herziene Europese Richtlijn Hernieuwbare Energie (RED- II)3, niet zijn meegenomen in dit rapport (tenzij anders aangegeven in de tekst).

The diversity and increasing prevalence of products derived from engineered nanomaterials (ENM), warrants implementation of non-animal approaches to health hazard assessment for ethical and practical reasons. Although non-animal approaches are becoming increasingly popular, there are almost no studies of side-by-side comparisons with traditional in vivo assays. Here, transcriptomics is used to investigate mechanistic similarities between healthy/asthmatic models of 3D air–liquid interface (ALI) cultures of donor-derived human bronchial epithelia cells, and mouse lung tissue, following exposure to copper oxide ENM. Only 19% of mouse lung genes with human orthologues are not expressed in the human 3D ALI model. Despite differences in taxonomy and cellular complexity between the systems, a core subset of matching genes cluster mouse and human samples strictly based on ENM dose (exposure severity). Overlapping gene orthologue pairs are highly enriched for innate immune functions, suggesting an important and maybe underestimated role of epithelial cells. In conclusion, 3D ALI models based on epithelial cells, are primed to bridge the gap between traditional 2D in vitro assays and animal models of airway exposure, and transcriptomics appears to be a unifying dose metric that links in vivo and in vitro test systems. © 2020 The Authors. Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

Ammonia emissions into the atmosphere have increased substantially in Europe since 1960, primarily due to the intensification of agriculture, as illustrated by enhanced livestock and the use of fertilizers. These associated emissions of reactive nitrogen, particulate matter, and acid deposition have contributed to negative societal impacts on human health and terrestrial ecosystems. Due to the limited availability of reliable measurements, emission inventories are used to assess large-scale ammonia emissions from agriculture by creating gridded annual emission maps and emission time profiles globally and regionally. The modeled emissions are subsequently utilized in chemistry transport models to obtain ammonia concentrations and depositions. However, current emission inventories usually have relatively low spatial resolutions and coarse categorizations that do not distinguish between fertilization on various crops, grazing, animal housing, and manure storage in its spatial allocation. Furthermore, in assessing the seasonal variation of ammonia emissions, they do not consider local climatology and agricultural management, which limits the capability to reproduce observed spatial and seasonal variations in the ammonia concentrations. This paper describes a novel ammonia emission model that quantifies agricultural emissions with improved spatial details and temporal dynamics in 2010 in Germany and Benelux. The spatial allocation was achieved by embedding the agricultural emission model Integrated Nitrogen Tool across Europe for Greenhouse gases and Ammonia Targeted to Operational Responses (INTEGRATOR) into the air pollution inventory Monitoring Atmospheric Composition and Climate-III (MACC-III), thus accounting for differentiation in ammonia emissions from manure and fertilizer application, grazing, animal houses and manure storage systems. The more detailed temporal distribution came from the integration of TIMELINES, which provided predictions of the timing of key agricultural operations, including the day of fertilization across Europe. The emission maps and time profiles were imported into LOTOS-EUROS to obtain surface concentrations and total columns for validation. The comparison of surface concentration between modeled output and in situ measurements illustrated that the updated model had been improved significantly with respect to the temporal variation of ammonia emission, and its performance was more stable and robust. The comparison of total columns between remote sensing observations and model simulations showed that some spatial characteristics were smoothened. Also, there was an overestimation in southern Germany and underestimation in northern Germany. The results suggested that updating ammonia emission fractions and accounting for manure transport are the direction for further improvement, and detailed land use is needed to increase the spatial resolution of spatial allocation in ammonia emission modeling.

In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants for a period of 17 d during the Second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) that took place at Cabauw, the Netherlands (51.97-N, 4.93-E). We report on the outcome of the formal semi-blind intercomparison exercise, which was held under the umbrella of the Network for the Detection of Atmospheric Composition Change (NDACC) and the European Space Agency (ESA). The three major goals of CINDI-2 were (1) to characterise and better understand the differences between a large number of multi-axis differential optical absorption spectroscopy (MAX-DOAS) and zenith-sky DOAS instruments and analysis methods, (2) to define a robust methodology for performance assessment of all participating instruments, and (3) to contribute to a harmonisation of the measurement settings and retrieval methods. This, in turn, creates the capability to produce consistent high-quality ground-based data sets, which are an essential requirement to generate reliable long-term measurement time series suitable for trend analysis and satellite data validation. The data products investigated during the semi-blind intercomparison are slant columns of nitrogen dioxide (NO2), the oxygen collision complex (O4) and ozone (O3) measured in the UV and visible wavelength region, formaldehyde (HCHO) in the UV spectral region, and NO2 in an additional (smaller) wavelength range in the visible region. The campaign design and implementation processes are discussed in detail including the measurement protocol, calibration procedures and slant column retrieval settings. Strong emphasis was put on the careful alignment and synchronisation of the measurement systems, resulting in a unique set of measurements made under highly comparable air mass conditions. The CINDI-2 data sets were investigated using a regression analysis of the slant columns measured by each instrument and for each of the target data products. The slope and intercept of the regression analysis respectively quantify the mean systematic bias and offset of the individual data sets against the selected reference (which is obtained from the median of either all data sets or a subset), and the rms error provides an estimate of the measurement noise or dispersion. These three criteria are examined and for each of the parameters and each of the data products, performance thresholds are set and applied to all the measurements. The approach presented here has been developed based on heritage from previous intercomparison exercises. It introduces a quantitative assessment of the consistency between all the participating instruments for the MAX-DOAS and zenith-sky DOAS techniques. ©Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License.

This study presents the first investigation of the methane (CH4) emissions of a large festival. Munich Oktoberfest, the world’s largest folk festival, is a potential source of CH4 as a large amount of natural gas for cooking and heating is used. In 2018 we measured the CH4 emissions of Oktoberfest using in situ measurements combined with a Gaussian plume dispersion model. Measurements were taken while walking and biking around the perimeter of the Oktoberfest premises (Theresienwiese) at different times of the day, during the week and at the weekend. The measurements showed enhancements of up to 100 ppb compared to background values and measurements after Oktoberfest. The average emission flux of Oktoberfest is determined as (6.7 ± 0.6) µg(m2 s) −1. Additional analyses, including the daily emission cycle and comparisons between emissions and the number of visitors, suggest that CH4 emissions of Oktoberfest are not due solely to the human biogenic emissions. Instead, fossil fuel CH4 emissions, such as incomplete combustion or loss in the gas appliances, appear to be the major contributors to Oktoberfest emissions. Our results can help to develop CH4 reduction policies and measures to reduce emissions at festivals and other major events in cities. Furthermore, events with a limited duration have not yet been included in the state-of-the-art emission inventories, such as TNO-MACC, EDGAR or IER. Our investigations show that these emissions are not negligible. Therefore, these events should be included in future emission inventories.

Ammonia emissions to the atmosphere have increased substantially in Europe since 1960, largely due to the intensification of agriculture as illustrated by enhanced livestock and use of fertilizers. These associated emissions of reactive nitrogen, particulate matter and acid deposition have contributed to negative societal impacts on human health and terrestrial ecosystems. Due to the limited availability of measurements, emission inventories are used to assess large-scale ammonia emissions from agriculture, creating gridded annual emission maps as well as emission time profiles, both globally and regionally. The modeled emissions are in turn used in chemistry transport models to obtain ammonia concentrations and depositions. However, current emission inventories usually have relatively low spatial resolutions and coarse categorizations that do not distinguish between fertilization on various crops, grazing, animal housing, and manure storage in its spatial allocation. Furthermore, in assessing the seasonal variation of ammonia emissions, they do not take into account local climatology and agricultural management, which limits the capability to reproduce observed spatial and seasonal variations in the ammonia concentrations. This paper describes a novel ammonia emission model that quantifies agricultural emissions with improved spatial details and temporal dynamics over the year of 2010, in Germany and Benelux. The spatial allocation was achieved by embedding the agricultural emission model INTEGRATOR into MACC-III, thus accounting for differences in manure and fertilizer application on croplands and grassland, grazing, animal houses and manure storage systems. The more detailed temporal distribution comes from the integration of the TIMELINES model, which provided predictions of the timing of key agricultural operations including the day of fertilization across Europe. The emission maps and time profiles were imported into LOTOSEUROS to obtain surface concentrations and total columns for validation. The comparison of surface concentration between modeled output and in-situ measurements illustrated that the updated model has been improved significantly with respect to the temporal variation of ammonia emission, and its performance was more stable and robust. The comparison between ammonia total columns from remote sensing and simulations showed that there is an overestimation in Southern Germany and underestimation in Northern Germany, which suggested that updating ammonia emission fractions and accounting for manure transport is the direction for further improvement.

The nitrogen cycle has been continuously disrupted by human activity over the past century, resulting in almost a tripling of the total reactive nitrogen fixation in Europe. Consequently, excessive amounts of reactive nitrogen (Nr) have manifested in the environment, leading to a cascade of adverse effects, such as acidification and eutrophication of terrestrial and aquatic ecosystems, and particulate matter formation. Chemistry transport models (CTMs) are frequently used as tools to simulate the complex chain of processes that determine atmospheric Nr flows. In these models, the parameterization of the atmosphere–biosphere exchange of Nr is largely based on few surface exchange measurement and is therefore known to be highly uncertain. In addition to this, the input parameters that are used here are often fixed values, only linked to specific land use classes. In an attempt to improve this, a combination of multiple satellite products is used to derive updated,time-variant leaf area index (LAI) and roughness length (z0) input maps. As LAI, we use the Moderate Resolution Imaging Spectroradiometer (MODIS) MCD15A2H product. The monthly z0 input maps presented in this paper are a function of satellite derived normalized difference vegetation index (NDVI) values (MYD13A3 product) for short vegetation types (such as grass and arable land) and a combination of satellite-derived forest canopy height and LAI for forests. The use of these growth-dependent satellite products allows us to represent the growing season more realistically. For urban areas, the z0 values are updated,too, and linked to a population density map. The approach to derive these dynamic z0 estimates can be linked to any land use map and is as such transferable to othermodels.We evaluated the sensitivity of the modelled Nr deposition fields in LOng Term Ozone Simulation – EURopean Operational Smog (LOTOS-EUROS)v2.0to the above mentioned changes in LAI and z0 inputs, focusing on Germany, the Netherlands and Belgium. We computed z0 values from FLUXNET sites and compared these to the default and updated z0 values in LOTOS-EUROS.The root mean square difference (RMSD) for both short vegetation and forest sites improved. Comparing all sites, the RMSD decreased from 0.76 (default z0) to 0.60 (updated z0). The implementation of these updated LAI and z0 input maps led to local changes in the total Nr deposition of up to∼30% and a general shift from wet to dry deposition. The most distinct changes are observed in land-use-specific deposition fluxes. These fluxes may show relatively large deviations, locally affecting estimated critical load exceedances for specific natural ecosystems

A data assimilation system for the LOTOS-EUROS chemical transport model has been implemented to improve the simulation and forecast of PM10 and PM2.5 in a densely populated urban valley of the tropical Andes. The Aburrá Valley in Colombia was used as a case study, given data availability and current environmental issues related to population expansion. The data assimilation system is an Ensemble Kalman filter with covariance localization based on specification of uncertainties in the emissions. Observations assimilated were obtained from a surface network for the period March–April of 2016, a period of one of the worst air quality crisis in recent history of the region. In a first series of experiments, the spatial length scale of the covariance localization and the temporal length scale of the stochastic model for the emission uncertainty were calibrated to optimize the assimilation system. The calibrated system was then used in a series of assimilation experiments, where simulation of particulate matter concentrations was strongly improved during the assimilation period, which also improved the ability to accurately forecast PM10 and PM2.5 concentrations over a period of several days. © 2020 Elsevier Ltd

In Eastern Germany winter episodes with PM10 exceedances of EU limit values are often connected to continental air masses, combining polluted air from Eastern Europe with air pollution from local urban sources. The EU air quality legislation requires the analysis of the contribution of such cross-boundary transport to exceedances for development of effective policy measures. To this end we have performed a source apportionment study to establish the main sources of particulate matter during high PM episodes in Eastern Germany. We have run the LOTOS-EUROS model with its labelling based source apportionment tool and found that the contribution from cross boundary transport becomes more dominant during the episodes. The results from the model are currently compared to a measurement based source attribution (PMF) and a more detailed evaluation of episodes with exceedances is being performed. The modelled concentrations have been evaluated against PM composition observations which revealed that especially the modelling of carbonaceous aerosol is challenging and lead to a large underestimation of modelled PM10 levels in winter. The use of an updated bottom-up inventory in combination with temperature dependent temporal variability for residential combustion emissions leads to an increase of carbonaceous aerosols and reduction of PM biases. Another improvement was realised through an update of the deposition routine over snow that leads to a strong reduction of the underestimation during cold PM episodes with snow conditions. © Springer Nature Switzerland AG 2020.

We present a modelling framework for fossil fuel CO2 emissions in an urban environment, which allows constraints from emission inventories to be combined with atmospheric observations of CO2 and its co-emitted species CO, NOx , and SO2. Rather than a static assignment of average emission rates to each unit area of the urban domain, the fossil fuel emissions we use are dynamic: they vary in time and space in relation to data that describe or approximate the activity within a sector, such as traffic density, power demand, 2 m temperature (as proxy for heating demand), and sunlight and wind speed (as proxies for renewable energy supply). Through inverse modelling, we optimize the relationships between these activity data and the resulting emissions of all species within the dynamic fossil fuel emission model, based on atmospheric mole fraction observations. The advantage of this novel approach is that the optimized parameters (emission factors and emission ratios, N = 44) in this dynamic emission model (a) vary much less over space and time, (b) allow for a physical interpretation of mean and uncertainty, and (c) have better defined uncertainties and covariance structure. This makes them more suited to extrapolate, optimize, and interpret than the gridded emissions themselves. The merits of this approach are investigated using a pseudo-observation-based ensemble Kalman filter inversion set-up for the Dutch Rijnmond area at 1 km×1 km resolution. We find that the fossil fuel emission model approximates the gridded emissions well (annual mean differences < 2 %, hourly temporal r 2 = 0.21–0.95), while reported errors in the underlying parameters allow a full covariance structure to be created readily. Propagating this error structure into atmospheric mole fractions shows a strong dominance of a few large sectors and a few dominant uncertainties, most notably the emission ratios of the various gases considered. If the prior emission ratios are either sufficiently well-known or well constrained from a dense observation network, we find that including observations of co-emitted species improves our ability to estimate emissions per sector relative to usingCO2 mole fractions only. Nevertheless, the total CO2 emissions can be well constrained with CO2 as the only tracer in the inversion. Because some sectors are sampled only sparsely over a day, we find that propagating solutions from day-to-day leads to largest uncertainty reduction and smallest CO2 residuals over the 14 consecutive days considered. Although we can technically estimate the temporal distribution of some emission categories like shipping separate from their total magnitude, the controlling parameters are difficult to distinguish. Overall, we conclude that our new system looks promising for application in verification studies, provided that reliable urban atmospheric transport fields and reasonable a priori emission ratios for CO2 and its co-emitted species can be produced.

Since the industrial revolution we have relied heavily on fossil fuels as feedstock and energy source. A major drawback in using fossil fuels is the emission of anthropogenic greenhouse gases. Deep reductions in these greenhouse gas emissions are needed if climate change is to be limited to 1.5-2°C above pre-industrial levels. These reductions will require a drastic transformation of the energy system as indicated by scenario studies which have evaluated possible roadmaps for this transformation. There is no straightforward solution to make a transition from a fossil-driven energy system to one based on renewables. There are many technological options to consider and which options work best depends to a great extent on local and regional circumstances. Therefore, it is increasingly recognized that the energy transition will take place at the local and regional level. This is where major decisions will have to be made.

We present an observing simulated system experiment (OSSE) dedicated to evaluate the potential added value from the Sentinel-4 and the Sentinel-5P observations on tropospheric ozone composition. For this purpose, the ozone data of Sentinel-4 (Ultraviolet Visible Near-infrared) and Sentinel-5P (TROPOspheric Monitoring Instrument) on board a geostationary (GEO) and a low-Earth-orbit (LEO) platform, respectively, have been simulated using the DISAMAR inversion package for the summer 2003. To ensure the robustness of the results, the OSSE has been configured with conservative assumptions. We simulate the reality by combining two chemistry transport models (CTMs): the LOng Term Ozone Simulation – EURopean Operational Smog (LOTOS-EUROS) and the Transport Model version 5 (TM5). The assimilation system is based on a different CTM, the MOdèle de Chimie Atmosphérique à Grande Echelle (MOCAGE), combined with the 3-D variational technique. The background error covariance matrix does not evolve in time and its variance is proportional to the field values. The simulated data are formed of six eigenvectors to minimize the size of the dataset by removing the noise-dominated part of the observations. The results show that the satellite data clearly bring direct added value around 200 hPa for the whole assimilation period and for the whole European domain, while a likely indirect added value is identified but not for the whole period and domain at 500 hPa, and to a lower extent at 700 hPa. In addition, the ozone added value from Sentinel-5P (LEO) appears close to that from Sentinel-4 (GEO) in the free troposphere (200–500 hPa) in our OSSE. The outcome of our study is a result of the OSSE design and the choice within each of the components of the system.

Using new satellite observations and atmospheric inverse modeling, we report methane emissions from the Permian Basin, which is among the world's most prolific oil-producing regions and accounts for >30% of total U.S. oil production. Based on satellite measurements from May 2018 to March 2019, Permian methane emissions from oil and natural gas production are estimated to be 2.7 ± 0.5 Tg a−1, representing the largest methane flux ever reported from a U.S. oil/gas-producing region and are more than two times higher than bottom-up inventory-based estimates. This magnitude of emissions is 3.7% of the gross gas extracted in the Permian, i.e., 60% higher than the national average leakage rate. The high methane leakage rate is likely contributed by extensive venting and flaring, resulting from insufficient infrastructure to process and transport natural gas. This work demonstrates a high-resolution satellite data-based atmospheric inversion framework, providing a robust top-down analytical tool for quantifying and evaluating subregional methane emissions. © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).

Chemical transport model (CTM) simulation of organic aerosol (OA) is always challenged by numerous sources and complicated formation processes of secondary organic aerosol. In this study, we conducted a source-specific, whole-year (2011) simulation of organic aerosol in Europe using the air quality model CAMx v6.3 with volatility basis set (VBS) scheme after implementing new findings from experimental studies. The VBS module was parameterized based on the latest data for gasoline and diesel vehicles and wood combustion from the smog-chamber experiments. The model performance was evaluated using OA measurements from the ACSM (Aerodyne Chemical Speciation Monitor) and AMS (Aerodyne Aerosol Mass Spectrometer) network and contributions from 6 different anthropogenic (gasoline and diesel vehicles with old or new technologies, biomass burning, and other sources (OP)) and biogenic sources were estimated. The modified VBS scheme improved the model performance on OA simulation during the whole period by reducing the bias between model and measurements by up to 52%. The OA concentrations were dominated by biomass burning in winter, while biogenic emissions were the main sources in summer. The contribution of road traffic was relatively lower compared to studies in the USA. The contribution of new gasoline and diesel vehicles (after Euro IV emission standards or equipped with diesel particle filters) to the total OA was negligible. © Springer Nature Switzerland AG 2020.

In Eastern Germany winter episodes with PM10 exceedances of EU limit values are often connected to continental air masses, combining polluted air from Eastern Europe with air pollution from local urban sources. The EU air quality legislation requires the analysis of the contribution of such cross-boundary transport to exceedances for development of effective policy measures. To this end we have performed a source apportionment study to establish the main sources of particulate matter during high PM episodes in Eastern Germany. We have run the LOTOS-EUROS model with its labelling based source apportionment tool and found that the contribution from cross boundary transport becomes more dominant during the episodes. The results from the model are currently compared to a measurement based source attribution (PMF) and a more detailed evaluation of episodes with exceedances is being performed. The modelled concentrations have been evaluated against PM composition observations which revealed that especially the modelling of carbonaceous aerosol is challenging and lead to a large underestimation of modelled PM10 levels in winter. The use of an updated bottom-up inventory in combination with temperature dependent temporal variability for residential combustion emissions leads to an increase of carbonaceous aerosols and reduction of PM biases. Another improvement was realised through an update of the deposition routine over snow that leads to a strong reduction of the underestimation during cold PM episodes with snow conditions. © Springer Nature Switzerland AG 2020.

Quantification of greenhouse gas emissions is receiving a lot of attention because of its relevance for climate mitigation. Complementary to official reported bottomup emission inventories, quantification can be done with an inverse modelling framework, combining atmospheric transport models, prior gridded emission inventories and a network of atmospheric observations to optimize the emission inventories. An important aspect of such a method is a correct quantification of the uncertainties in all aspects of the modelling framework. The uncertainties in gridded emission inventories are, however, not systematically analysed. In this work, a statistically coherent method is used to quantify the uncertainties in a high-resolution gridded emission inventory of CO2 and CO for Europe. We perform a range of Monte Carlo simulations to determine the effect of uncertainties in different inventory components, including the spatial and temporal distribution, on the uncertainty in total emissions and the resulting atmospheric mixing ratios. We find that the uncertainties in the total emissions for the selected domain are 1 % for CO2 and 6 % for CO. Introducing spatial disaggregation causes a significant increase in the uncertainty of up to 40 % for CO2 and 70 % for CO for specific grid cells. Using gridded uncertainties, specific regions can be defined that have the largest uncertainty in emissions and are thus an interesting target for inverse modellers. However, the largest sectors are usually the best-constrained ones (low relative uncertainty), so the absolute uncertainty is the bes indicator for this. With this knowledge, areas can be identified that are most sensitive to the largest emission uncertainties, which supports network design.

We present an observing simulated system experiment (OSSE) dedicated to evaluate the potential added value from the Sentinel-4 and the Sentinel-5P observations on tropospheric ozone composition. For this purpose, the ozone data of Sentinel-4 (Ultraviolet Visible Near-infrared) and Sentinel-5P (TROPOspheric Monitoring Instrument) on board a geostationary (GEO) and a low-Earth-orbit (LEO) platform, respectively, have been simulated using the DISAMAR inversion package for the summer 2003. To ensure the robustness of the results, the OSSE has been configured with conservative assumptions. We simulate the reality by combining two chemistry transport models (CTMs): the LOng Term Ozone Simulation – EURopean Operational Smog (LOTOS-EUROS) and the Transport Model version 5 (TM5). The assimilation system is based on a different CTM, the MOdèle de Chimie Atmosphérique à Grande Echelle (MOCAGE), combined with the 3-D variational technique. The background error covariance matrix does not evolve in time and its variance is proportional to the field values. The simulated data are formed of six eigenvectors to minimize the size of the dataset by removing the noise-dominated part of the observations. The results show that the satellite data clearly bring direct added value around 200 hPa for the whole assimilation period and for the whole European domain, while a likely indirect added value is identified but not for the whole period and domain at 500 hPa, and to a lower extent at 700 hPa. In addition, the ozone added value from Sentinel-5P (LEO) appears close to that from Sentinel- 4 (GEO) in the free troposphere (200–500 hPa) in our OSSE. The outcome of our study is a result of the OSSE design and the choice within each of the components of the system.

Urban mining from construction and demolition waste (CDW) is highly relevant for the circular economy ambitions of the European Union (EU). Given the large volumes involved, end-of-life (EoL) concrete is identified as one of the priority streams for CDW recycling in most EU countries, but it is currently largely downcycled or even landfilled. The European projects C2CA and VEEP have proposed several cost-effective technologies to recover EoL concrete for new concrete manufacturing. To understand the potential effects of large-scale implementation of those recycling technologies on the circular construction, this study deployed static material flow analysis (MFA) for a set of EoL concrete management scenarios in the Netherlands constructed by considering the development factors in two, technological and temporal dimensions. On the technological dimension, three treatment systems for EoL concrete management, namely: business-as-usual treatment, C2CA technological system and VEEP technological system were investigated. On the temporal dimension, 2015 was selected as the reference year, representing the current situation, and 2025 as the future year for the prospective analysis. The results show that the development of cost-effective technologies has the potential to improve the share of recycling (as opposed to downcycling) in the Netherlands from around 5% in 2015 up to 22%–32% in 2025. From the academic aspect, the presented work illustrates how the temporal dimension can be included in the static MFA study to explore the potential effects in the future. © 2020

In 2018 is de totale uitstoot van broeikasgassen in Nederland met 2,7 procent gedaald ten opzichte van 2017. Deze daling komt vooral doordat er minder kolen zijn gebruikt om elektriciteit te produceren. De totale uitstoot van broeikasgassen naar de lucht wordt uitgedrukt in CO2-equivalenten en bedroeg in 2018 188,2 miljard kilogram. Het jaar 1990 geldt als referentiejaar (het zogeheten Kyoto-basisjaar) voor de te halen doelstellingen. De uitstoot in 1990 bedroeg 221,7 miljard kilogram CO2-equivalenten. Ten opzichte van het basisjaar is de uitstoot gedaald met 15,1 procent. De uitstoot van CO2 alleen ligt 1,6 procent onder het niveau van het basisjaar. De uitstoot van de andere broeikasgassen (methaan, distikstofoxide en gefluoreerde gassen) is sinds 1990 met meer dan 50 procent gedaald. Dit blijkt uit de inventarisatie van broeikasgasemissies die het RIVM jaarlijks op verzoek van het Ministerie van Economische Zaken en Klimaat (EZK) opstelt. Met deze inventarisatie voldoet Nederland aan de nationale rapportageverplichtingen voor 2020 van het Klimaatverdrag van de Verenigde Naties (UNFCCC), van het Kyoto Protocol en van het Bewakingsmechanisme Broeikasgassen van de Europese Unie