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The basis for modelling greenhouse gases and air pollutants is an explicit spatially and temporally resolved specification of the anthropogenic emissions. Although a lot effort has been put in to improve the spatial allocation for emission inventories, the temporal variability for many sectors is not aligned with real-world conditions and often prescribed using static or constant time profiles. We have been developing a modelling system to predict the spatial-temporal behaviour of anthropogenic emissions of air pollutants and greenhouse gases in which we aim to also include the influence of e.g. meteorological conditions on activities and emission factors. As such, we are replacing the static emission profiles with parametrizations one by one. Here, we present the approaches we are taking for 3 sectors. First, for large power plants the point source metadata of the CAMS-REG inventory have been matched to those from the ENTSO-E database to link the hourly production statistics to the emission inventory. Next, we tried to group the production time series of the different kinds of power plants, but this turned out not to be possible as they show very specific profiles. It was affordable to include for each power plant its individual emission time profile into the emission model. Second, for small stationary combustion the temporal variability is calculated for two building types, i.e. office and residential buildings, using the heating degree day method for oil and gas. For residential wood and coal combustion additional constraints with respect to heating behaviour have been applied. Third, for methane emissions from landfills we based our parametrization on investigations showing a significant pressure dependency of the emission flux. The original (constant) emission profile is exchanged with a profile which is spatially and temporally dependent on the change of atmospheric pressure, which leads to a variability of a factor 4 around the annual mean flux. Given the impact of synoptic variability the behaviour shows comparable patterns across large regions. At the meeting we will also show our planned approach to detail the emission variability of methane and PM from the agricultural sector (enteric fermentation, livestock housing and land management).

The exposure to ambient particulate matter in metropolitan areas is a major health problem. A prerequisite for formulating effective mitigation strategies it to understand the origin of particulate matter in terms of source regions and sectors. We performed a source attribution of particulate matter (PM) for the Berlin agglomeration area covering the period from 2016 to 2018 using the LOTOS-EUROS chemistry transport model. The (3 year-) mean modelled urban background PM2.5 concentration (10.4 μg/m³) is largely explained by households (3.2 μg/m³) and industry & energy (2.0 μg/m³), while the remaining source sectors contribute the other half. The modelled annual mean urban increment for PM2.5 is mainly attributed to households (1.6 μg/m³) and traffic (0.5 μg/m³). With respect to its relative shares the PM10 source attribution looks similar to that of PM2.5 throughout the year, but with enhanced natural contributions. From a geographical perspective the main source area for the PM2.5 in Berlin is Germany (5.1 μg/m³) itself, followed by the contributions from transboundary transport (3.4 μg/m³). The German sources could be further split into Berlin (2.6 μg/m³), Brandenburg (0.7 μg/m³) and remaining states of Germany (1.8 μg/m³). About one third of the foreign shares can be attributed to Germany's neighbouring countries Poland and Czech Republic. During episodes these contributions can significantly differ, e.g. in February 2017 the Polish contribution is about 1/3rd. The sectoral contributions agree with previous findings except that our study indicates lower contributions for traffic. The model's underestimation of total PM is largely caused by an underestimation of the coarse mode PM. Both the coarse mode urban increment as well as the regional background concentrations are underestimated by the model, especially during summer. We suggest that the enhanced coarse material (in the city) during warm seasons is predominated by (road) resuspension processes which need more of our attention to further improve our models.

Air Quality in Berlin is a particular problem during winter episodes. During this episodes, local emissions are only one factor contributing to the high concentrations. The other factors are the lowered height of the planetary boundary layer and the advection of pollutants, some of which are produced in Eastern Europe. To trace the share of total pollution in Berlin for 2016-18 back to its origins, the Chemistry Transport Model (CTM) LOTOS-EUROS v2.1 (LOng Term Ozone Simulation EURopean Operational Smog, invented by TNO, Netherlands) is used, which also provides a labelling approach. Some specifications were made for the emission datasets used to drive the model, including emission dependencies on temperature (e.g. cold engine starts and heating degree-days for households).The model results are evaluated using the German AirBase monitoring sites. An incremental approach (Lenschow et al., 2001) is used for the evaluation and estimation of the urban share of Berlin. The focus is on Particulate Matter (PM): PM10, PM2.5, and the coarse-mode fraction (PM10-PM2.5). Due to the seasonal variability of PM and its composition, seasonal differentiation is investigated. The labelling approach provided in LOTOS-EUROS allows to distinguish between the sources relevant for Berlin’s PM pollution, with the focus of this work on local contributions such as households and traffic on the one hand and regional contributions from Berlin itself and Germany’s Eastern European neighbors (Poland and the Czech Republic) on the other hand.This study is in relation to the “Berliner Luftreinhalteplan” (Berlin Clean Air Plan).

In this article we describe the implementation of an online-coupled gas-phase chemistry model in the turbulence-resolving PALM model system 6.0 (formerly an abbreviation for Parallelized Large-eddy Simulation Model and now an independent name). The new chemistry model is implemented in the PALM model as part of the PALM-4U (PALM for urban applications) components, which are designed for application of the PALM model in the urban environment (Maronga et al., 2020). The latest version of the Kinetic PreProcessor (KPP, 2.2.3) has been utilized for the numerical integration of gas-phase chemical reactions. A number of tropospheric gas-phase chemistry mechanisms of different complexity have been implemented ranging from the photostationary state (PHSTAT) to mechanisms with a strongly simplified volatile organic compound (VOC) chemistry (e.g. the SMOG mechanism from KPP) and the Carbon Bond Mechanism 4 (CBM4; Gery et al., 1989), which includes a more comprehensive, but still simplified VOC chemistry. Further mechanisms can also be easily added by the user. In this work, we provide a detailed description of the chemistry model, its structure and input requirements along with its various features and limitations. A case study is presented to demonstrate the application of the new chemistry model in the urban environment. The computation domain of the case study comprises part of Berlin, Germany. Emissions are considered using street-type-dependent emission factors from traffic sources. Three chemical mechanisms of varying complexity and one no-reaction (passive) case have been applied, and results are compared with observations from two permanent air quality stations in Berlin that fall within the computation domain. Even though the feedback of the model's aerosol concentrations on meteorology is not yet considered in the current version of the model, the results show the importance of online photochemistry and dispersion of air pollutants in the urban boundary layer for high spatial and temporal resolutions. The simulated NOx and O3 species show reasonable agreement with observations. The agreement is better during midday and poorest during the evening transition hours and at night. The CBM4 and SMOG mechanisms show better agreement with observations than the steady-state PHSTAT mechanism. © 2021 Copernicus GmbH. All rights reserved.

Large-Eddy Simulation (LES) allow to simulate pollutant dispersion at a fine-scale turbulence-resolving scale with explicitly resolved turbulent transport around building structures and in street canyons. The microscale urban climate model with atmospheric chemistry PALM-4U (i.e. PALM for Urban applications; Maronga et al., 2019, Met. Z., https://doi.org/10.1127/metz/2019/0909) has been developed within the collaborative project MOSAIK (Model-based city planning and application in climate change). With such a large-eddy simulation (LES) model, pollutant dispersion around buildings and within street canyons can be simulated, with explicitly resolving the turbulent transport in urban environments.Cyclic boundaries are frequently applied in LES in order to obtain lateral boundary conditions for the turbulent quantities. In addition to the default cyclic boundary conditions, PALM-4U allows also time-dependent boundary conditions from regional models to account for variable weather conditions and regional scale pollutant transport. Turbulent fluctuations, which are not included in the boundary conditions from the regional simulation but are needed as additional boundary conditions for the LES model are produced by a turbulence generator (Maronga et al, 2019, GMDD, https://doi.org/10.5194/gmd-2019-103).PALM-4U simulations with and without time dependent boundary conditions from regional simulations with WRF-Chem are performed for different setups in order to test the impact of the domain configuration. The simulations indicate that cyclic boundary conditions can lead to unrealistic accumulation of pollutants over urban areas with strong sources, which is not the case when time-dependent boundary conditions are applied. However, even though a turbulence generator is applied, explicit setting of time-dependent boundary conditions requires large model domains, in order to obtain fully developed turbulence within the domain of interest, increasing the computational demand of the simulation.

Large-Eddy Simulation (LES) models are so far barely applied to dispersion and chemical transformation of pollutants in urban air quality studies. Within the joint project MOSAIK (Modellbasierte Stadtplanung und Anwendung im Klimawandel/Model-based city planning and application in climate change) a new LES based state-of-the-art microscale urban climate model PALM-4U, has been developed. The new model includes both gas phase and aerosol chemistry. For practical applications, our approach is to go beyond the simulation of single street canyons to chemical transformation, advection and deposition of air pollutants in the larger urban canopy. First LES results of a test case for an urban quarter of Berlin (Germany) are presented.

In this article we outline the model development planned within the joint project Model-based city planning and application in climate change (MOSAIK). The MOSAIK project is funded by the German Federal Ministry of Education and Research (BMBF) within the framework Urban Climate Under Change ([UC]2) since 2016. The aim of MOSAIK is to develop a highly-efficient, modern, and high-resolution urban climate model that allows to be applied for building-resolving simulations of large cities such as Berlin (Germany). The new urban climate model will be based on the well-established large-eddy simulation code PALM, which already has numerous features related to this goal, such as an option for prescribing Cartesian obstacles. In this article we will outline those components that will be added or modified in the framework of MOSAIK. Moreover, we will discuss the everlasting issue of acquisition of suitable geographical information as input data and the underlying requirements from the model's perspective. publishedVersion

Biodiversity is strongly affected by the deposition of nitrogen and sulfur on terrestrial ecosystems. In this paper we present new quantitative estimates of the deposition of atmospheric nitrogen to ecosystems across Germany. The methodology combines prognostic and empirical modelling to establish wet deposition fluxes and land use dependent dry and occult deposition fluxes. On average, the nitrogen deposition in Germany was estimated to be 1057 eq ha−1 yr−1. The deposition maps show considerable variability across the German territory with highest deposition on forest ecosystems in or near the main agricultural and industrial areas. The accumulated deposition over Germany of this study is systematically lower (27 %) than provided in earlier studies. The main reasons are an improved wet deposition estimation and the consolidation of improved process descriptions in the LOTOS-EUROS chemistry transport model. The presented deposition estimates show a better agreement with results obtained by integrated monitoring and deposition modelling by EMEP than the earlier results. Through comparison of the new deposition distributions with critical load maps it is estimated that 70 % of the ecosystems in Germany receive too much nitrogen.

In this study we present a dynamic model evaluation of chemistry transport model LOTOS-EUROS (LOng Term Ozone Simulation – EURopean Operational Smog) to analyse the ability of the model to reproduce observed non-linear responses to emission changes and interannual variability of secondary inorganic aerosol (SIA) and its precursors over Europe from 1990 to 2009. The 20 year simulation was performed using a consistent set of meteorological data provided by RACMO2 (Regional Atmospheric Climate MOdel). Observations at European rural background sites have been used as a reference for the model evaluation. To ensure the consistency of the used observational data, stringent selection criteria were applied, including a comprehensive visual screening to remove suspicious data from the analysis. The LOTOS-EUROS model was able to capture a large part of the seasonal and interannual variability of SIA and its precursors' concentrations. The dynamic evaluation has shown that the model is able to simulate the declining trends observed for all considered sulfur and nitrogen components following the implementation of emission abatement strategies for SIA precursors over Europe. Both the observations and the model show the largest part of the decline in the 1990s, while smaller concentration changes and an increasing number of non-significant trends are observed and modelled between 2000 and 2009. Furthermore, the results confirm former studies showing that the observed trends in sulfate and total nitrate concentrations from 1990 to 2009 are lower than the trends in precursor emissions and precursor concentrations. The model captured well these non-linear responses to the emission changes. Using the LOTOS-EUROS source apportionment module, trends in the formation efficiency of SIA have been quantified for four European regions. The exercise has revealed a 20–50% more efficient sulfate formation in 2009 compared to 1990 and an up to 20% more efficient nitrate formation per unit nitrogen oxide emission, which added to the explanation of the non-linear responses. However, we have also identified some weaknesses in the model and the input data. LOTOS-EUROS underestimates the observed nitrogen dioxide concentrations throughout the whole time period, while it overestimates the observed nitrogen dioxide concentration trends. Moreover, model results suggest that the emission information of the early 1990s used in this study needs to be improved concerning magnitude and spatial distribution.

To accurately simulate dispersion, chemical transformation and removal of air pollutants in the urban canopy layer, fine-scale turbulence-resolving simulations are required that can explicitly resolve building structures and street canyons. Large-Eddy Simulation (LES) models explicitly resolve the dominant scales of turbulence in the atmospheric boundary layer and therefore, have the potential to capture the turbulent motion within street canyons as well as the observed short term fluctuations of pollutant concentrations. LES models including chemical transformation of pollutants are so far barely applied for urban air quality studies. Within the joint project MOSAIK (Model-based city planning and application in climate change) a new urban microscale model including gas Phase chemistry and aerosols, PALM-4U, has been developed. The state-of-the-art LES model PALM (Maronga et al, 2015, Geosci. Model Dev., 8, doi:10.5194/gmd-8-2515-2015) is used as core model for PALM-4U. In order to obtain the necessary flexibility in the choice of the chemistry mechanisms the gas-phase chemistry was implemented using the Kinetic PreProcessor KPP. Due to the very high computational demands of an LES-based model, compromises are required with respect to the degree of detail of the gas-phase chemistry mechanisms. A number of chemical mechanisms with varying complexity and detail that ranges from a strongly reduced mechanism which includes only a simple O3-NO2-NO-VOC-HOx chemistry and a small number of products to large mechanisms which are typically used in regional air quality models were implemented into PALM-4U. The performance of different gas-phase chemistry schemes of different complexity within the LES model PALM-4U is tested and compared.

The development and application of chemistry transport models has a long tradition. Within the Netherlands the LOTOS-EUROS model has been developed by a consortium of institutes, after combination of its independently developed predecessors in 2005. Recently, version 2.0 of the model was released as an open source version. This paper presents the curriculum vitae of the model system, describing the model’s history, model philosophy, basic features, a validation with EMEP stations for the new benchmark year 2012, and presents cases with the model's most recent and key developments. By setting the model developments in context and providing an outlook for directions for further development, the paper goes beyond the common model description. With an origin in ozone and sulphur modelling for the models LOTOS and EUROS, the application areas were gradually extended with POPs, reactive nitrogen and primary and secondary particulate matter. After the combination of the models to LOTOS-EUROS in 2005, the model was further developed to include new source parametrizations (e.g. road resuspension, desert dust, wildfires), applied for operational smog forecasts in the Netherlands and Europe, and has been used for emission scenarios, source apportionment and long-term hindcast and climate change scenarios. LOTOS-EUROS has been a front-runner in data assimilation of ground-based and satellite observations and has participated in many model intercomparison studies. The model is no longer confined to applications over Europe but is also applied to other regions of the world, e.g. China. Also the increasing interaction with emission experts has contributed to the improvement of the model’s performance. The philosophy for model development has always been to use knowledge that is state of the art and proven, to keep good balance in the level of detail of process description and accuracy of input and output, and to keep a good track on the effect of model changes using benchmarking and validation. The performance of v2.0 with respect to EMEP observations is good, with spatial correlations around 0.8 or higher for concentrations and wet deposition. Temporal correlations are around 0.5 or higher. Recent innovative applications include source apportionment and data assimilation, particle number modelling, energy transition scenarios including corresponding land use changes as well as Saharan dust forecasting. Future developments would enable more flexibility with respect to model horizontal and vertical resolution and further detailing of model input data. This includes use of different sources of land use characterization (roughness length and vegetation), detailing of emissions in space and time, and efficient coupling to meteorology from different meteorological models.

In this study, the chemistry transport model (CTM) LOTOS-EUROS is used to calculate the deposition fluxes of eutrophying and acidifying reactive nitrogen (Nr) to ecosystems in Germany. In the last years important developments have been made for the modelling of the budget of Nr. The new model version has changed the spatial explicit budget calculations across Germany and was thoroughly evaluated with respect to pollutants concentrations and deposition fluxes. The results revealed that the balance between dry and wet deposition is sensitive to the updates in the process descriptions impacting the pollutants transport distances. A comparison to observations showed an improvement of the new model version compared to the pre-developments model version.

In this study we investigate the ability of the Chemistry Transport Model (CTM) LOTOS-EUROS to explain the observed decrease in secondary inorganic aerosol (SIA) and its precursors between 1990 and 2009 over Europe. The model explicitly accounts for cloud chemistry and aerosol thermodynamics. The results have shown that the model largely captures the observed trends in SIA and its precursors’ concentrations while it underestimates the interannual variability. Using a source-apportionment module the amount of SIA formed per unit emission was traced for a number of regions. The results show 20–50 % more efficient SO4 2− formation in 2009 compared to 1990, whereas the change in NO3 − formation per unit NOx emission is lower (−10 % to +20 %) for the same time period.

In this study, the response of secondary inorganic aerosol (SIA) concentrations to changes in precursor emissions during high PM10 episodes over Central Europe in spring 2009 was investigated with the Eulerian Chemistry Transport Model (CTM) REM-Calgrid (RCG). The model performed well in capturing the temporal variation of PM10 and SIA concentrations and was used to analyse the different origin, development and characteristics of the selected high PM10 episodes. SIA concentrations, which attribute to about 50% of the PM10 concentration in north-western Europe, have been studied by means of several emission scenarios varying SO2, NOx and NH3 emissions within a domain covering Germany and within a domain covering Europe. It was confirmed that the response of sulphate, nitrate and ammonium concentrations and deposition fluxes of S and N to SO2, NOx and NH3 emission changes is non-linear. The deviation from linearity was found to be lower for total deposition fluxes of S and N than for SIA concentrations. Furthermore, the study has shown that incorporating explicit cloud chemistry in the model adds non-linear responses to the system and significantly modifies the response of modelled SIA concentrations and S and N deposition fluxes to changes in precursor emissions. The analysis of emission reduction scenarios demonstrates that next to European wide emission reductions additional national NH3 measures in Germany are more effective in reducing SIA concentrations and deposition fluxes than additional national measures on SO2 and NOx.

The Chemistry Transport Model (CTM) REM-Calgrid (RCG) has been applied to investigate the non-linear relationship between emission changes and modelled SIA (=SO4 + NO3 + NH4) concentrations for a high PM10 episode in spring 2009. Emissions were reduced for the model domain only and the model domain including Boundary Conditions. It was found that the effectiveness of emission reductions increases with increasing emission reduction area whereas results were least dependent on the size of emission reduction area for ammonia emission changes.

In this study, the response of secondary inorganic aerosol (SIA) concentrations to changes in precursor emissions during high PM10 episodes over central Europe in spring 2009 was investigated with the Eulerian Chemistry Transport Model (CTM) REM-Calgrid (RCG). The model performed well in capturing the temporal variation of PM10 and SIA concentrations and was used to analyse the different origin, development and characteristics of the selected high PM10 episodes. SIA concentrations, which contribute to about 50% of the PM10 concentration in northwestern Europe, have been studied by means of several model runs for different emission scenarios. SO2, NOx and NH3 emissions have been varied within a domain covering Germany and within a domain covering Europe. It was confirmed that the response of sulfate, nitrate and ammonium concentrations and deposition fluxes of S and N to SO2, NOx and NH3 emission changes is non-linear. The deviation from linearity was found to be lower for total deposition fluxes of S and N than for SIA concentrations. Furthermore, the study has shown that incorporating explicit cloud chemistry in the model adds non-linear responses to the system. It significantly modifies the response of modelled SIA concentrations and S and N deposition fluxes to changes in precursor emissions. The analysis of emission reduction scenario runs demonstrates that next to European-wide emission reductions additional national NH3 measures in Germany are more effective in reducing SIA concentrations and deposition fluxes than additional national measures on SO2 and NOx.

The Chemistry Transport Model REM-Calgrid (RCG) has been improved by implementing an enhanced description of aqueous-phase chemistry and wet deposition processes including droplet pH. A sensitivity study on cloud and rain droplet pH has been performed to investigate its impact on model sulphate production and gas wet scavenging. Air concentrations and wet deposition fluxes of the model sensitivity runs have been analysed and compared to observations. It was found that droplet pH variation within atmospheric ranges affects modelled air concentrations and wet deposition fluxes significantly. Applying a droplet pH of 5.5 for July 2005, mean sulphate air concentrations increased by up to 10% compared to using a droplet pH of 5 while SO 2 domain wet deposition sum increased by 110%. Moreover, model results using modelled droplet pH for January and July 2005 have been compared to model results applying a constant pH of 5 and to observations. The comparison to observations has shown that using a variable droplet pH improves the model performance concerning air concentrations and wet deposition fluxes of the investigated sulphur and nitrogen compounds. For SO x wet deposition fluxes the Root Mean Square Error (RMSE) decreased by 16% for July 2005 when using a variable droplet pH instead of a constant pH of 5. Concerning sulphate and SO 2 air concentrations the RMSE was reduced by 8% and 16% for July 2005, respectively. The results have revealed that applying a variable droplet pH is preferable to using a constant pH leading to better consistency concerning air concentrations and wet deposition fluxes. © 2011 Elsevier Ltd.

The Dutch National Precipitation Chemistry Monitoring Network measures the wet deposition fluxes of acidifying and eutrophying compounds and heavy metals over the Netherlands since 1978. Recent measurements of sulfate, ammonium and nitrate of this precipitation network are used to validate the outcome of the new wet deposition module implemented into the regional air quality model LOTOS-EUROS. The old wet deposition module only included below-cloud scavenging, whereas the new wet deposition module takes into account below-cloud and in-cloud scavenging. Both processes are implemented such that the effect of the saturation of rain droplets on the scavenging efficiency is included. A simple parameterization, based on the liquid water content data from ECMWF, is used to distinguish between regions in which respectively below-cloud or in-cloud scavenging occurs. In general, it is found that the combination of below-cloud and in-cloud scavenging increases the net scavenging process in the LOTOS-EUROS model simulations; hence the wet deposition fluxes are increased. These increased wet deposition fluxes in the model simulations are evaluated at the sites of the precipitation network in the Netherlands and show a better agreement as compared to results of simulations performed with the old wet deposition module. Finally the wet deposition fluxes are also evaluated at the sites of the European EMEP monitoring stations: a similar improvement is found again between the measurements and model results.

The Chemistry Transport Model REM-Calgrid (RCG) has been improved by implementing a more detailed description of aqueous-phase chemistry and wet deposition processes including droplet pH. A sensitivity study on cloud and rain droplet pH has been performed to investigate its impact on model sulphate production and gas wet scavenging. Air concentrations and wet deposition fluxes of model runs applying differing droplet pH have been analysed and compared to observations. It was found that droplet pH variation within atmospheric ranges affects modelled air concentrations and wet deposition fluxes significantly.