ALBERT

Description: 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 combining 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 and 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 sulfur modelling for the models LOTOS and EUROS, the application areas were gradually extended with persistent organic pollutants, 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. The increasing interaction with emission experts has also 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 a good balance in the level of detail of process description and accuracy of input and output, and to keep a good record 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, and 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 the 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.

Description: 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.

Description: The accurate representation of bidirectional ammonia (NH3) biosphere-atmosphere exchange is an important part of modern air quality models. However, the cuticular (or external leaf surface) pathway, as well as other non-stomatal ecosystem surfaces, still pose a major challenge of translating our knowledge into models. Dynamic mechanistic models including complex leaf surface chemistry have been able to accurately reproduce measured bidirectional fluxes in the past, but their computational expense and challenging implementation into existing air quality models call for steady-state simplifications. We here qualitatively compare two semi-empirical state-of-the-art parameterizations of a unidirectional non-stomatal resistance (Rw) model after Massad et al. (2010), and a quasi-bidirectional non-stomatal compensation point (χw) model after Wichink Kruit et al. (2010), with NH3 flux measurements from five European sites. In addition, we tested the feasibility of using backward-looking moving averages of air NH3 concentrations as a proxy for prior NH3 uptake and driver of an alternative parameterization of non-stomatal emission potentials (Γw) for bidirectional non-stomatal exchange models. Results indicate that the Rw-only model has a tendency to underestimate fluxes, while the χw model mainly overestimates fluxes, although systematic underestimations can occur under certain conditions, depending on temperature and ambient NH3 concentrations at the site. The proposed Γw parameterization appears to have potential for improvement, but cannot be recommended for use in large scale simulations in its present state due to large uncertainties. As an interim solution for improving flux predictions, we recommend to reduce the minimum allowed Rw and the temperature response parameter in the unidirectional model and to revisit the temperature dependent Γw parameterization of the bidirectional model.

Description: Global distributions of atmospheric ammonia (NH3) measured with satellite instruments such as the Infrared Atmospheric Sounding Interferometer (IASI) contain valuable information on NH3 concentrations and variability in regions not yet covered by ground based instruments. Due to their large spatial coverage and daily observations, the satellite observations have the potential to increase our knowledge of the distribution of NH3 emissions, and associated seasonal cycles. However the observations remain poorly validated, with only a handful of available studies often using only surface observations without any vertical information. In this study, we present the first validation of the IASI-NH3 product using ground-based Fourier Transform InfraRed (FTIR) observations. Using a recently developed consistent retrieval strategy, NH3 concentration profiles have been retrieved using observations from nine Network for the Detection of Atmospheric Composition Change (NDACC) stations around the world between 2008–2015. We demonstrate the importance of strict spatio-temporal collocation criteria for the comparison. Large differences in the regression results are observed for changing intervals of spatial criteria, mostly due to terrain characteristics and the short lifetime of NH3 in the atmosphere. The seasonal variations of both datasets are consistent for most sites. Correlations are found to be high at sites in areas with considerable NH3 levels, whereas correlations are lower at sites with low atmospheric NH3 levels close to the detection limit of the IASI instrument. A combination of the observations from all sites (Nobs = 547) give a MRD of −32.4 ± (56.3) %, a correlation r of 0.8 with a slope of 0.73. These results indicate that the IASI-NH3 product performs better than previous upper bound estimates (-50% – +100 %).

Description: Global distributions of atmospheric ammonia (NH3) measured with satellite instruments such as the Infrared Atmospheric Sounding Interferometer (IASI) contain valuable information on NH3 concentrations and variability in regions not yet covered by ground-based instruments. Due to their large spatial coverage and (bi-)daily overpasses, the satellite observations have the potential to increase our knowledge of the distribution of NH3 emissions and associated seasonal cycles. However the observations remain poorly validated, with only a handful of available studies often using only surface measurements without any vertical information. In this study, we present the first validation of the IASI-NH3 product using ground-based Fourier transform infrared spectroscopy (FTIR) observations. Using a recently developed consistent retrieval strategy, NH3 concentration profiles have been retrieved using observations from nine Network for the Detection of Atmospheric Composition Change (NDACC) stations around the world between 2008 and 2015. We demonstrate the importance of strict spatio-temporal collocation criteria for the comparison. Large differences in the regression results are observed for changing intervals of spatial criteria, mostly due to terrain characteristics and the short lifetime of NH3 in the atmosphere. The seasonal variations of both datasets are consistent for most sites. Correlations are found to be high at sites in areas with considerable NH3 levels, whereas correlations are lower at sites with low atmospheric NH3 levels close to the detection limit of the IASI instrument. A combination of the observations from all sites (Nobs = 547) give a mean relative difference of −32.4 ± (56.3) %, a correlation r of 0.8 with a slope of 0.73. These results give an improved estimate of the IASI-NH3 product performance compared to the previous upper-bound estimates (−50 to +100 %).

Description: The accurate representation of bidirectional ammonia (NH3) biosphere–atmosphere exchange is an important part of modern air quality models. However, the cuticular (or external leaf surface) pathway, as well as other non-stomatal ecosystem surfaces, still pose a major challenge to translating our knowledge into models. Dynamic mechanistic models including complex leaf surface chemistry have been able to accurately reproduce measured bidirectional fluxes in the past, but their computational expense and challenging implementation into existing air quality models call for steady-state simplifications. Here we qualitatively compare two semi-empirical state-of-the-art parameterizations of a unidirectional non-stomatal resistance (Rw) model after Massad et al. (2010), and a quasi-bidirectional non-stomatal compensation-point (χw) model after Wichink Kruit et al. (2010), with NH3 flux measurements from five European sites. In addition, we tested the feasibility of using backward-looking moving averages of air NH3 concentrations as a proxy for prior NH3 uptake and as a driver of an alternative parameterization of non-stomatal emission potentials (Γw) for bidirectional non-stomatal exchange models. Results indicate that the Rw-only model has a tendency to underestimate fluxes, while the χw model mainly overestimates fluxes, although systematic underestimations can occur under certain conditions, depending on temperature and ambient NH3 concentrations at the site. The proposed Γw parameterization revealed a clear functional relationship between backward-looking moving averages of air NH3 concentrations and non-stomatal emission potentials, but further reduction of uncertainty is needed for it to be useful across different sites. As an interim solution for improving flux predictions, we recommend reducing the minimum allowed Rw and the temperature response parameter in the unidirectional model and revisiting the temperature-dependent Γw parameterization of the bidirectional model.