Improving the deterministic skill of air quality ensembles

<p><strong>Abstract.</strong> Forecasts from chemical weather models are subject to uncertainties in the input data (e.g. emission inventory, initial and boundary conditions) as well as the model itself (e.g. physical parameterization, chemical mechanism). Multi-model ensemble forecasts can improve the forecast skill provided that certain mathematical conditions are fulfilled. We demonstrate through an intercomparison of two dissimilar air quality ensembles that unconditional raw forecast averaging, although generally successful, is far from optimum. One way to achieve an optimum ensemble is also presented. The basic idea is to either add optimum weights to members or constrain the ensemble to those members that meet certain conditions in time or frequency domain. The methods are evaluated against ground level observations collected from the EMEP and Airbase databases.<br><br> The two ensembles were created for the first and second phase of the Air Quality Model Evaluation International Initiative (AQMEII). Verification statistics shows that the deterministic models simulate better O<sub>3</sub> than NO<sub>2</sub> and PM<sub>10</sub>, linked to different levels of complexity in the represented processes. The ensemble mean achieves higher skill compared to each station's best deterministic model at 39 %–63 % of the sites. The skill gained from the favourable ensemble averaging has at least double the forecast skill compared to using the full ensemble. The method proved robust for the 3-monthly examined time-series if the training phase comprises 60 days. Further development of the method is discussed in the conclusion.</p&gt

Sulfur and Nitrogen Depositions in BULGARIA—Model Results and Observations

Atmospheric deposition processes are of primary importance for human health, forests, agricultural lands, aquatic bodies, and ecosystems. South-East Europe is still characterized by numerous hot spots of elevated sulfur deposition, despite the reduction in European emission sources. The purpose of this study is to discuss the results from two chemical transport models and observations for wet and dry depositions of sulfur (S), reduced nitrogen (RDN) and oxidized nitrogen (OXN) in Bulgaria in 2016–2017. The spatial distribution and the domain main deposition values by EMEP MSC-W (model of the MSC-W Centre of the Co-operative Programme for Monitoring and Evaluation of the Long-range Transmissions of Air Pollutants in Europe) and BgCWFS (Bulgarian Chemical Weather Forecast System) demonstrated S wet depositions to be higher than N depositions, and identified a rural area in south-east Bulgaria as a possible hot-spot. The chemical analysis of deposition samples at three sites showed a prevalence of sulfate in the western part of the country, and prevalence of Cl and Na at a coastal site. The comparison between modeled and observed depositions demonstrated that both models captured the prevalence of S wet depositions at all sites. Better performance of BgCWFS with an average absolute value of the normalized mean bias of 16% was found

Sulfur and Nitrogen Depositions in BULGARIA—Model Results and Observations

Atmospheric deposition processes are of primary importance for human health, forests, agricultural lands, aquatic bodies, and ecosystems. South-East Europe is still characterized by numerous hot spots of elevated sulfur deposition, despite the reduction in European emission sources. The purpose of this study is to discuss the results from two chemical transport models and observations for wet and dry depositions of sulfur (S), reduced nitrogen (RDN) and oxidized nitrogen (OXN) in Bulgaria in 2016–2017. The spatial distribution and the domain main deposition values by EMEP MSC-W (model of the MSC-W Centre of the Co-operative Programme for Monitoring and Evaluation of the Long-range Transmissions of Air Pollutants in Europe) and BgCWFS (Bulgarian Chemical Weather Forecast System) demonstrated S wet depositions to be higher than N depositions, and identified a rural area in south-east Bulgaria as a possible hot-spot. The chemical analysis of deposition samples at three sites showed a prevalence of sulfate in the western part of the country, and prevalence of Cl and Na at a coastal site. The comparison between modeled and observed depositions demonstrated that both models captured the prevalence of S wet depositions at all sites. Better performance of BgCWFS with an average absolute value of the normalized mean bias of 16% was found

Meteorology and air pollution at a coastal site - Experiment and modeling

Here we presents results of an experimental campaign performed in October 2016 in Ahtopol (Bulgaria) in the context of Exchange program between ISAC-CNR and NIHM-BAS research centers. The aim of the campaign is to collect aerosols in the coastal area, together with physical parameters; to consider air-masses circulation from meteorological output and to demonstrate that for some period Ahtopol and Lamezia Terme sites are in the same system. Evidence of aerosols circulation is also given by using HYSPLIT model for a better understanding of pollution sources also by chemical analysis form wet and dry deposition and filters from impactor