Analysis of meteorology-chemistry interactions during air pollution episodes using online coupled models within AQMEII Phase-2

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).This study reviews the top ranked meteorology and chemistry interactions in online coupled models recommended by an experts’ survey conducted in COST Action EuMetChem and examines the sensitivity of those interactions during two pollution episodes: the Russian forest fires 25 Jul -15 Aug 2010 and a Saharan dust transport event from 1 Oct -31 Oct 2010 as a part of the AQMEII phase-2 exercise. Three WRF-Chem model simulations were performed for the forest fire case for a baseline without any aerosol feedback on meteorology, a simulation with aerosol direct effects only and a simulation including both direct and indirect effects. For the dust case study, eight WRF-Chem and one WRF-CMAQ simulations were selected from the set of simulations conducted in the framework of AQMEII. Of these two simulations considered no feedbacks, two included direct effects only and five simulations included both direct and indirect effects. The results from both episodes demonstrate that it is important to include the meteorology and chemistry interactions in online-coupled models. Model evaluations using routine observations collected in AQMEII phase-2 and observations from a station in Moscow show that for the fire case the simulation including only aerosol direct effects has better performance than the simulations with no aerosol feedbacks or including both direct and indirect effects. The normalized mean biases are significantly reduced by 10-20% for PM10 when including aerosol direct effects. The analysis for the dust case confirms that models perform better when including aerosol direct effects, but worse when including both aerosol direct and indirect effects, which suggests that the representation of aerosol indirect effects needs to be improved in the model.Peer reviewedFinal Published versio

Emission fluxes and atmospheric degradation of monoterpenes above a boreal forest: Field measurements and modelling

The contribution of monoterpenes to aerosol formation processes within and above forests is not well understood. This is also true for the particle formation events observed during the BIOFOR campaigns in Hyytiälä, Finland. Therefore, the diurnal variation of the concentrations of several biogenic volatile organic compounds (BVOCs) and selected oxidation products in the gas and particle phase were measured on selected days during the campaigns in Hyytiälä, Finland. α-pinene and Δ3-carene were found to represent the most important monoterpenes above the boreal forest. A clear vertical gradient of their concentrations was observed together with a change of the relative monoterpene composition with height. Based on concentration profile measurements of monoterpenes, their fluxes above the forest canopy were calculated using the gradient approach. Most of the time, the BVOC fluxes show a clear diurnal variation with a maximum around noon. The highest fluxes were observed for α-pinene with values up to 20 ng m−2 s−1 in summer time and almost 100 ng m−2 s−1 during the spring campaign. Furthermore, the main oxidation products from α-pinene, pinonaldehyde, and from β-pinene, nopinone, were detected in the atmosphere above the forest. In addition to these more volatile oxidation products, pinic and pinonic acid were identified in the particle phase in a concentration range between 1 and 4 ng m−3. Beside these direct measurement of known oxidation products, the chemical sink term in the flux calculations was used to estimate the amount of product formation of the major terpenes (α-pinene, β-pinene, Δ3-carene). A production rate of very low volatile oxidation products (e.g., multifunctional carboxylic) from ·OH- and O3-reaction of monoterpenes of about 1.3·104 molecules cm−3 s−1 was estimated for daylight conditions during summer time. Additionally, model calculations with the one-dimensional multilayer model CACHE were carried out to investigate the diurnal course of BVOC fluxes and chemical degradation of terpenes

Model evaluation and ensemble modelling of surface-level ozone in Europe and North America in the context of AQMEII

More than ten state-of-the-art regional air quality models have been applied as part of the Air Quality Model Evaluation International Initiative (AQMEII). These models were run by twenty independent groups in Europe and North America. Standardised modelling outputs over a full year (2006) from each group have been shared on the web-distributed ENSEMBLE system, which allows for statistical and ensemble analyses to be performed by each group. The estimated ground-level ozone mixing ratios from the models are collectively examined in an ensemble fashion and evaluated against a large set of observations from both continents. The scale of the exercise is unprecedented and offers a unique opportunity to investigate methodologies for generating skilful ensembles of regional air quality models outputs. Despite the remarkable progress of ensemble air quality modelling over the past decade, there are still outstanding questions regarding this technique. Among them, what is the best and most beneficial way to build an ensemble of members? And how should the optimum size of the ensemble be determined in order to capture data variability as well as keeping the error low? These questions are addressed here by looking at optimal ensemble size and quality of the members. The analysis carried out is based on systematic minimization of the model error and is important for performing diagnostic/probabilistic model evaluation. It is shown that the most commonly used multi-model approach, namely the average over all available members, can be outperformed by subsets of members optimally selected in terms of bias, error, and correlation. More importantly, this result does not strictly depend on the skill of the individual members, but may require the inclusion of low-ranking skill-score members. A clustering methodology is applied to discern among members and to build a skilful ensemble based on model association and data clustering, which makes no use of priori knowledge of model skill. Results show that, while the methodology needs further refinement, by optimally selecting the cluster distance and association criteria, this approach can be useful for model applications beyond those strictly related to model evaluation, such as air quality forecasting. (C) 2012 Elsevier Ltd. All rights reserved.Peer reviewe

An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating

This article presents an enhanced emission module for the PALM model system, which collects discrete emission sources from different emission sectors and assigns them dynamically to the prognostic equations for specific pollutant species as volumetric source terms. Bidirectional lookups between each source location and cell index are maintained by using a hash key approach, while allowing all emission source modules to be conceived, developed, and operated in a homogeneous and mutually independent manner. An additional generic emission mode has also been implemented to allow for the use of external emission data in simulation runs. Results from benchmark runs indicate a high level of performance and scalability. Subsequently, a module for modeling parametrized emissions from domestic heating is implemented under this framework, using the approach of building energy usage and temperature deficit as a generalized form of heating degree days. A model run has been executed under idealized conditions by solely considering dispersion of PM10 from domestic heating sources. The results demonstrate a strong overall dependence on the strength and clustering of individual sources, diurnal variation in domestic heat usage, and the temperature deficit between the ambient temperature and the user-defined target temperature. Vertical transport additionally contributes to a rapid attenuation of daytime PM10. Although urban topology plays a minor role on the pollutant concentrations at ground level, it has a relevant contribution to the vertical pollutant distribution

An enhanced emission module for the PALM model system 23.10 with application for PM 10 emission from urban domestic heating

This article presents an enhanced emission module for the PALM model system, which collects discrete emission sources from different emission sectors and assigns them dynamically to the prognostic equations for specific pollutant species as volumetric source terms. Bidirectional lookups between each source location and cell index are maintained by using a hash key approach, while allowing all emission source modules to be conceived, developed, and operated in a homogeneous and mutually independent manner. An additional generic emission mode has also been implemented to allow for the use of external emission data in simulation runs. Results from benchmark runs indicate a high level of performance and scalability. Subsequently, a module for modeling parametrized emissions from domestic heating is implemented under this framework, using the approach of building energy usage and temperature deficit as a generalized form of heating degree days. A model run has been executed under idealized conditions by solely considering dispersion of PM$_{10}$ from domestic heating sources. The results demonstrate a strong overall dependence on the strength and clustering of individual sources, diurnal variation in domestic heat usage, and the temperature deficit between the ambient temperature and the user-defined target temperature. Vertical transport additionally contributes to a rapid attenuation of daytime PM$_{10}$. Although urban topology plays a minor role on the pollutant concentrations at ground level, it has a relevant contribution to the vertical pollutant distribution