Aerosol measurements in the Dutch National Air Quality Monitoring Network

Elzakker, B.G. van; Meulen, A. van der

doi:10.1016/s0021-8502(99)80031-7

Cited by 4 publications

(4 citation statements)

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“…To improve the estimation of the assimilated concentrations of ozone and to reduce the uncertainties in the emissions, the model is combined with available measurements. Time series of measurements at surface level were obtained from the Netherlands Air quality Monitoring Network, LML [ Elzakker , 2001], from the EMEP (A. G. Hjellbrekke, Ozone measurements 1996, EMEP/CCC 3/98, 1998, available from the EMEP Web site at http://www.emep.int/) and Airbase (ETC‐ACC, Airbase from the European Topic Centre on Air Quality and Climate Change, 2003, available at http://air-climate.eionet.eu.int/databases/airbase.html) databases. Airbase, a Web‐based database of information and data on air quality across Europe, is managed by the European Topic Centre on Air Quality and Climate Change of the European Environment Agency.…”

Section: State Space Representationmentioning

confidence: 99%

Data assimilation of ground‐level ozone in Europe with a Kalman filter and chemistry transport model

2004

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[1] A Kalman filter coupled to the atmospheric chemistry transport model EUROS has been used to estimate the ozone concentrations in the boundary layer above Europe. Two Kalman filter algorithms, the reduced rank square root (RRSQRT) and the ensemble Kalman filter (ENKF), were implemented in this study. Both required, in general, a large number of EUROS model simulations for an assimilation. The observations consisted of hourly ozone data in a set of 135 ground-based stations in Europe for the period, June 1996. Half of these stations were used for the assimilation and the other half only for validation of the results. The combination between data assimilation (Kalman filter) and the atmospheric chemistry transport model, EUROS, gave more accurate results for boundary layer ozone than the EUROS model or measurements used separately. The average difference between assimilated and measured ozone concentrations decreased from 27.4 to 20.5 mg m À3 for the average of the stations used for validation in Europe. Both algorithms tend to converge to about the same accuracy, with an increasing number of EUROS model runs. About 10-20 EUROS model calculations were found sufficient for a good assimilation. The results are supported by a number of simulations that also reveal a local character for the assimilation process.

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Section: State Space Representationmentioning

confidence: 99%

Data assimilation of ground‐level ozone in Europe with a Kalman filter and chemistry transport model

2004

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“…The purpose of the Dutch air quality monitoring network is to monitor air quality in the Netherlands on a continual basis (Van Elzakker 2001). Measurements from this network provide a general description of national, regional and local air quality, along with information on smog episodes; measurements are also tested against international air quality standards.…”

Section: Introductionmentioning

confidence: 99%

External drift kriging of NOx concentrations with dispersion model output in a reduced air quality monitoring network

et al. 2007

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In the mid nineteen eighties the Dutch NO x air quality monitoring network was reduced from 73 to 32 rural and city background stations, leading to higher spatial uncertainties. In this study, several other sources of information are being used to help reduce uncertainties in parameter estimation and spatial mapping. For parameter estimation, we used Bayesian inference. For mapping, we used kriging with external drift (KED) including secondary information from a dispersion model. The methods were applied to atmospheric NO x concentrations on rural and urban scales. We compared Bayesian estimation with restricted maximum likelihood estimation and KED with universal kriging. As a reference we also included ordinary least squares (OLS). Comparison of several parameter estimation and spatial interpolation methods was done by cross-validation. Bayesian analysis resulted in an error reduction of 10 to 20% as compared to restricted maximum likelihood, whereas KED resulted in an error reduction of 50% as compared to universal kriging. Where observations were sparse, the predictions were substantially improved by inclusion of the dispersion model output and by using available prior information. No major improvement was observed as compared to OLS, the cause presumably being that much good information is contained in the dispersion model output, so that no additional spatial residual random field is required to explain the data. In all, we conclude that reduction in the monitoring network could be compensated by modern geostatistical methods, and that a traditional simple statistical model is of an almost equal quality.

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“…PM 10 and PM 2.5 , using an FAG-type β-dust monitor (Van Elzakker, 2000). The sampling air is heated (to 50 • C) in order to remove water from aerosol particles (Buringh and Opperhuizen, 2002).…”

Section: Methodsmentioning

confidence: 99%

Physical and optical aerosol properties at the Dutch North Sea coast based on AERONET observations

Kuśmierczyk-Michulec

Leeuw²,

Moerman³

2007

Atmos. Chem. Phys.

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Abstract. Sun photometer measurements at the AERONET station at the North Sea coast in The Hague (The Netherlands) provide a climatology of optical and physical aerosol properties for the area. Results are presented from the period January 2002 to July 2003. For the analysis and interpretation these data are coupled to chemical aerosol data from a nearby station of the Dutch National Air Quality Network. This network provides PM 10 and black carbon concentrations. Meteorological conditions and air mass trajectories are also used. Due to the location close to the coast, the results are strongly dependent on wind direction, i.e. air mass trajectory. In general the aerosol optical properties are governed by industrial aerosol emitted form various industrial, agricultural and urban areas surrounding the site in almost all directions over land. For maritime air masses industrial aerosols are transported from over the North Sea, whereas very clean air is transported from the NW in clean polar air masses from the North Atlantic. In the winter the effect of the production of sea salt aerosol at high wind speeds is visible in the optical and physical aerosol data. In these cases fine and coarse mode radii are similar to those reported in the literature for marine aerosol. Relations are derived between theÅngström coefficients with both the fine/coarse mode fraction and the ratio of black carbon and PM 10 .

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Aerosol measurements in the Dutch National Air Quality Monitoring Network

Cited by 4 publications

References 0 publications

Data assimilation of ground‐level ozone in Europe with a Kalman filter and chemistry transport model

Data assimilation of ground‐level ozone in Europe with a Kalman filter and chemistry transport model

External drift kriging of NOx concentrations with dispersion model output in a reduced air quality monitoring network

Physical and optical aerosol properties at the Dutch North Sea coast based on AERONET observations

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