Interregional Air Pollutant Transport: The Linearity Question

This report contains extended abstracts from an international meeting held in Budapest, Hungary. Its main subject is the question of proportionality and linearity between emissions and deposition/airborne concentration of air pollutants including sulfur, nitrogen, oxidants, and acidity. Session topics (which serve here as section headings) included analysis of measurements, ammonia and its implications for linearity, modeling with emphasis on chemistry, simplified approaches to the linearity issue, and results from long-range transport models. Linearity was found to be strongly dependent on the distance between emitters and receptors, the averaging time of pollutants, and the form of deposition

SMOKE for Europe – adaptation, modification and evaluation of a comprehensive emission model for Europe

The US EPA regional emission model SMOKE was adopted and modified to create temporally and spatially distributed emission for Europe and surrounding countries based on official reports and public domain data only. The aim is to develop a flexible model capable of creating consistent high resolution emission data for long-term runs of Chemical Transport Models (CTMs). This modified version of SMOKE, called SMOKE for EUROPE (SMOKE-EU) was successfully used to create hourly gridded emissions for the timespan 1970–2010. <br><br> In this paper the SMOKE-EU model and the underlying European datasets are introduced. Emission data created by SMOKE-EU for the year 2000 are evaluated by comparison to data of three different state-of-the-art emission models. SMOKE-EU produced a range of values comparable to the other three datasets. Further, concentrations of criteria pollutants calculated by the CTM CMAQ using the four different emission datasets were compared against EMEP measurements with hourly and daily resolution. Using SMOKE-EU gave the most reliable modelling of O<sub>3</sub>, NO<sub>2</sub> and SO<sub>4</sub><sup>2−</sup>. The amount of simulated concentrations within a factor of 2 (F2) of the observations for these species are: O<sub>3</sub> (F2 = 0.79, <i>N</i> = 329 197), NO<sub>2</sub> (F2 = 0.55, <i>N</i> = 11 465) and SO<sub>4</sub><sup>2−</sup> (F2 = 0.62, <i>N</i> = 17 536). The lowest values were found for NH<sub>4</sub><sup>+</sup> (F2 = 0.34, <i>N</i> = 7400) and NO<sub>3</sub><sup>−</sup> (F2 = 0.25, <i>N</i> = 6184). NH<sub>4</sub><sup>+</sup> concentrations were generally overestimated, leading to a fractional bias (FB) averaged over 22 measurement stations of (FB = 0.83 ± 0.41) while better agreements with observations were found for SO<sub>4</sub><sup>2−</sup> (FB = 0.06 ± 0.38, 51 stations) and NO<sub>3</sub><sup>−</sup> (FB = 0.13 ± 0.75, 18 stations). <br><br> CMAQ simulations using the three other emission datasets were similar to those modelled using SMOKE-EU emissions. Highest differences where found for NH<sub>4</sub><sup>+</sup> while O<sub>3</sub> concentrations were almost identical

Retrieval methods of effective cloud cover from the GOME instrument: an intercomparison

The radiative scattering by clouds leads to errors in the retrieval of column densities and concentration profiles of atmospheric trace gas species from satellites. Moreover, the presence of clouds changes the UV actinic flux and the photo-dissociation rates of various species significantly. The Global Ozone Monitoring Experiment (GOME) instrument on the ERS-2 satellite, principally designed to retrieve trace gases in the atmosphere, is also capable of detecting clouds. Four cloud fraction retrieval methods for GOME data that have been developed are discussed in this paper (the Initial Cloud Fitting Algorithm, the PMD Cloud Recognition Algorithm, the Optical Cloud Recognition Algorithm (an in-house version and the official implementation) and the Fast Retrieval Scheme for Clouds from the Oxygen A-band). Their results of cloud fraction retrieval are compared to each-other and also to synoptic surface observations. It is shown that all studied retrieval methods calculate an effective cloud fraction that is related to a cloud with a high optical thickness. Generally, we found ICFA to produce the lowest cloud fractions, followed by our in-house OCRA implementation, FRESCO, PC2K and finally the official OCRA implementation along four processed tracks (+2%, +10%, +15% and +25% compared to ICFA respectively). Synoptical surface observations gave the highest absolute cloud fraction when compared with individual PMD sub-pixels of roughly the same size

Retrieval methods of effective cloud cover for the GOME instrument: an intercomparison

International audienceThe radiative scattering by clouds leads to errors in the retrieval of column densities and concentration profiles of atmospheric trace gas species from satellites. Moreover, the presence of clouds changes the UV actinic flux and the photo-dissociation rates of various species significantly. The Global Ozone Monitoring Experiment (GOME) instrument on the ERS-2 satellite, principally designed to retrieve trace gases in the atmosphere is also capable of detecting clouds. Four cloud fraction retrieval methods for GOME data that have been developed are discussed in this paper (the Initial Cloud Fitting Algorithm, the PMD Cloud Retrieval Algorithm, the Optical Cloud Recognition Algorithm and the Fast Retrieval Scheme for Cloud Observables). Their results of cloud fraction retrieval are compared to each-other and also to synoptic surface observations. It is shown that all studied retrieval methods calculate an effective cloud fraction that is related to a cloud with a high optical thickness. Generally, we found ICFA to produce the lowest cloud fractions, followed by OCRA, then FRESCO and PC2K along four processed tracks (+2%, +10% and +15% compared to ICFA respectively). Synoptical surface observations gave the highest absolute cloud fraction when compared with individual PMD sub-pixels of roughly the same size

Spatial variation of aerosol properties over Europe derived from satellite observations and comparison with model calculations

International audienceAerosol optical depths (AOD) and Angström coefficients over Europe were retrieved using data from the ATSR-2 radiometer on board the ESA satellite ERS-2, for August 1997. Taking advantage of the nadir and forward view of the ATSR-2, the dual view algorithm was used over land to eliminate the influence of the surface reflection. Over sea the AOD was retrieved using only the forward observations. Retrieved aerosol optical properties are in good agreement with those from ground-based sunphotometers. The AOD and Angström coefficients together yield information on the column integrated effective aerosol distribution. Observed regional variations of the AOD and Angström coefficient are related to anthropogenic emissions of aerosol precursors such as SO2 and NOx in the major European industrial and urban areas, and their subsequent transformation into the aerosol phase. The influence of anthropogenic aerosols such as ammonium sulphate and ammonium nitrate on the total AOD is estimated using a regional chemistry transport model. Sulphate is estimated to contribute from 15% in very clean areas to 70% in polluted areas, the contribution of nitrate is between 5% and 25% over most of Europe. This paper shows the great importance of nitrate in summer over The Netherlands

The nitrate aerosol field over Europe: simulations with an atmospheric chemistry-transport model of intermediate complexity

International audienceNitrate is an important component of fine aerosols in Europe. We present a model simulation for the year 1995 in which we account for the formation of the ammonium nitrate, a semi volatile component. For this purpose, LOTOS, a chemistry-transport model of intermediate complexity, was extended with a thermodynamic equilibrium module and additional relevant processes to account for aerosol formation and deposition. Our earlier analysis of data on (ammonium) nitrate in Europe was used for model evaluation. During winter, fall and especially spring high nitrate levels are projected over north western, central and eastern Europe. During winter nitrate concentrations are highest in the Po valley, Italy. This is in accordance with the field that was constructed from the data. In winter nitric acid, the precursor for aerosol nitrate, is formed through heterogeneous reactions on the surface of aerosols. Appreciable ammonium nitrate concentrations in summer are limited to those areas with high ammonia emissions, e.g. The Netherlands, since high ammonia concentrations are necessary to stabilise this aerosol component at high temperatures. Averaged over all stations the model reproduces the measured concentrations for NO3, SO4, NH4, TNO3, TNH4 and SO2 within 20%. The daily variation is captured well, albeit that the model does not always represents the amplitude of single events. The model underestimates wet deposition which was attributed to the crude representation of cloud processes. The treatment of ammonia was found to be the major source for uncertainties in the model representation of secondary aerosols. Also, inclusion of sea salt is necessary to properly assess the nitrate and nitric acid levels in marine areas. Over Europe the annual forcing by nitrate is calculated to be 25% of that by sulphate. In summer nitrate is found to be regionally important, e.g. in The Netherlands, where the forcing of nitrate and sulphate are calculated to be equal. In winter, spring and fall the nitrate forcing over Europe is about half that by sulphate. Over north western Europe and the alpine region the forcing by nitrate was calculated to be similar to that of sulphate. Overall, nitrate forcing is significant and should be taken into account to estimate the impact of regional climate change in Europe

Spatial variation of aerosol properties derived from satellite observations

International audienceAerosol optical depths (AOD) and Angström coefficients over Europe were retrieved using data from the ATSR-2 radiometer on board the ESA satellite ERS-2, for August 1997. Taking advantage of the nadir and forward view of the ATSR-2, the dual view algorithm was used over land to eliminate the influence of the surface reflection. Over sea the AOD was retrieved using only the forward observations. Retrieved aerosol optical properties are in good agreement with those from ground-based sunphotometers. The AOD and Angström coefficients together yield information on the column integrated effective aerosol distribution. Observed regional variations of the AOD and Angström coefficient are related to anthropogenic emissions of aerosol precursors such as SO2 and NOx in the major European industrial and urban areas, and their subsequent transformation into the aerosol phase. The influence of anthropogenic aerosols such as ammonium sulphate and ammonium nitrate on the total AOD is estimated using a regional chemistry transport model. Sulphate is estimated to contribute from 15% in very clean areas to 70% in polluted areas, the contribution of nitrate is between 5% and 25% over most of Europe. This paper shows the great importance of nitrate in summer over The Netherlands

The ACCENT-protocol: a framework for benchmarking and model evaluation

We summarise results from a workshop on “Model Benchmarking and Quality Assurance” of the EU-Network of Excellence ACCENT, including results from other activities (e.g. COST Action 732) and publications. A formalised evaluation protocol is presented, i.e. a generic formalism describing the procedure of how to perform a model evaluation. This includes eight steps and examples from global model applications which are given for illustration. The first and important step is concerning the purpose of the model application, i.e. the addressed underlying scientific or political question. We give examples to demonstrate that there is no model evaluation per se, i.e. without a focused purpose. Model evaluation is testing, whether a model is fit for its purpose. The following steps are deduced from the purpose and include model requirements, input data, key processes and quantities, benchmark data, quality indicators, sensitivities, as well as benchmarking and grading. We define “benchmarking” as the process of comparing the model output against either observational data or high fidelity model data, i.e. benchmark data. Special focus is given to the uncertainties, e.g. in observational data, which have the potential to lead to wrong conclusions in the model evaluation if not considered carefully.publishe

Secondary inorganic aerosol simulations for Europe with special attention to nitrate

International audienceNitrate is an important component of (secondary inorganic) fine aerosols in Europe. We present a model simulation for the year 1995 in which we account for the formation of secondary inorganic aerosols including ammonium sulphate and ammonium nitrate, a semi volatile component. For this purpose, the chemistry-transport model LOTOS was extended with a thermodynamic equilibrium module and additional relevant processes to account for secondary aerosol formation and deposition. During winter, fall and especially spring high nitrate levels are projected over north western, central and eastern Europe. During winter nitrate concentrations are highest in Italy, in accordance with observed data. In winter nitric acid, the precursor for aerosol nitrate is formed through heterogeneous reactions on the surface of aerosols. Modelled and observed sulphate concentrations show little seasonal variation. Compared to sulphate levels, appreciable ammonium nitrate concentrations in summer are limited to those areas with high ammonia emissions, e.g. the Netherlands, since high ammonia concentrations are necessary to stabilise this aerosol component at high temperatures. As a consequence of the strong seasonal variation in nitrate levels the AOD depth of nitrate over Europe is especially significant compared to that of sulphate in winter and spring when equal AOD values are calculated over large parts of Europe. Averaged over all stations the model reproduces the measured concentrations for NO3, SO4, NH4, TNO3 (HNO3+NO3), TNH4 (NH3+NH4) and SO2 within 20%. The daily variation is captured well, albeit that the model does not always represent the amplitude of single events. The model underestimates wet deposition which was attributed to the crude representation of cloud processes. Comparison of retrieved and computed aerosol optical depth (AOD) showed that the model underestimates AOD significantly, which was expected due to the lack of carbonaceous aerosols, sea salt and dust in the model. The treatment of ammonia was found to be a major source for uncertainties in the model representation of secondary aerosols. Also, inclusion of sea salt is necessary to properly assess the nitrate and nitric acid levels in marine areas

Combining data from the distributed GRUAN site Lauder–Invercargill, New Zealand, to provide a site atmospheric state best estimate of temperature

A site atmospheric state best estimate (SASBE) of the temperature profile above the GCOS (Global Climate Observing System) Reference Upper-Air Network (GRUAN) site at Lauder, New Zealand, has been developed. Data from multiple sources are combined within the SASBE to generate a high temporal resolution data set that includes an estimate of the uncertainty on every value.The SASBE has been developed to enhance the value of measurements made at the distributed GRUAN site at Lauder and Invercargill (about 180&thinsp;km apart), and to demonstrate a methodology which can be adapted to other distributed sites. Within GRUAN, a distributed site consists of a cluster of instruments at different locations.The temperature SASBE combines measurements from radiosondes and automatic weather stations at Lauder and Invercargill, and ERA5 reanalysis, which is used to calculate a diurnal temperature cycle to which the SASBE converges in the absence of any measurements.The SASBE provides hourly temperature profiles at 16 pressure levels between the surface and 10&thinsp;hPa for the years 1997 to 2012. Every temperature value has an associated uncertainty which is calculated by propagating the measurement uncertainties, the ERA5 ensemble standard deviations, and the ERA5 representativeness uncertainty through the retrieval chain. The SASBE has been long-term archived and is identified using the digital object identifier https://doi.org/10.5281/zenodo.1195779.The study demonstrates a method to combine data collected at distributed sites. The resulting best-estimate temperature data product for Lauder is expected to be valuable for satellite and model validation as measurements of atmospheric essential climate variables are sparse in the Southern Hemisphere. The SASBE could, for example, be used to constrain a radiative transfer model to provide top-of-the-atmosphere radiances with traceable uncertainty estimates.</p