A Statistical Approach to Estimate Spatial Distributions of Wet Deposition in Germany

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A Statistical Approach to Estimate Spatial Distributions of Wet Deposition in Germany. / Vautz, W.; Busch, A. Ulrike; Urfer, Wolfgang et al.
In: Water, Air, and Soil Pollution, Vol. 145, No. 1-4, 05.2003, p. 215-238.

Research output: Journal contributionsJournal articlesResearchpeer-review

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Vautz W, Busch AU, Urfer W, Klockow D. A Statistical Approach to Estimate Spatial Distributions of Wet Deposition in Germany. Water, Air, and Soil Pollution. 2003 May;145(1-4):215-238. doi: 10.1023/A:1023676011565

Bibtex

@article{795da28f49fb4053ac3f65bee353b1bb,
title = "A Statistical Approach to Estimate Spatial Distributions of Wet Deposition in Germany",
abstract = "The correct spatial interpolation from a few available point measurements of wet deposition - which contributes a major part to total deposition - is very important for the determination of a possible exceeding of critical loads: A wide spatial variability is a property of both deposition and critical loads. For this purpose, the meteorological variables having relevant influence on wet deposition and being available from routine measurements were used as input data for a statistical model for the estimation of wet deposition. Those variables are precipitation amount, preceding dry period, wind direction and season. The results obtained from the developed model were validated using measurements from routine monitoring stations in Germany for daily wet deposition rates of the major anions and cations. After description of model development and verification, the application of the model is presented exemplarily for sulfate, chloride and nitrate. Therefore daily precipitation data from a few representative monitoring stations and additional information about wind direction from meteorological maps were used as model input. As a result, reliable point estimates for wet deposition were available in addition to the measured data, thus allowing spatial interpolation with higher accuracy. The resulting wet deposition maps reveal that the critical loads for the investigated substances are already exceeded in some areas of Germany, particularly when the additional input from dry and occult (fog and cloud) deposition is taken into account. Using all available daily precipitation data in an annual routine, deposition maps could be available with high spatial resolution (<10 km).",
keywords = "Economics, empirical/statistics, penalized regression, Non-linear model, Regression mit Strafterm, Nichtlineare Modelle, Ecosystems Research, wet deposition, monitoring, nasse Deposition, Monitoring",
author = "W. Vautz and Busch, {A. Ulrike} and Wolfgang Urfer and D. Klockow",
note = "Funding Information: Financial support for this project by the German Federal Environmental Agency, Berlin, is gratefully acknowledged. Additional financial support has been given by the German Federal Ministry of Education, Science, Research and Technology, the Ministry of Science and Research of the State of Northrhine-Westfalia and the Deutsche Forschungsgemeinschaft (DFG).",
year = "2003",
month = may,
doi = "10.1023/A:1023676011565",
language = "English",
volume = "145",
pages = "215--238",
journal = "Water, Air, and Soil Pollution",
issn = "0049-6979",
publisher = "Springer Nature",
number = "1-4",

}

RIS

TY - JOUR

T1 - A Statistical Approach to Estimate Spatial Distributions of Wet Deposition in Germany

AU - Vautz, W.

AU - Busch, A. Ulrike

AU - Urfer, Wolfgang

AU - Klockow, D.

N1 - Funding Information: Financial support for this project by the German Federal Environmental Agency, Berlin, is gratefully acknowledged. Additional financial support has been given by the German Federal Ministry of Education, Science, Research and Technology, the Ministry of Science and Research of the State of Northrhine-Westfalia and the Deutsche Forschungsgemeinschaft (DFG).

PY - 2003/5

Y1 - 2003/5

N2 - The correct spatial interpolation from a few available point measurements of wet deposition - which contributes a major part to total deposition - is very important for the determination of a possible exceeding of critical loads: A wide spatial variability is a property of both deposition and critical loads. For this purpose, the meteorological variables having relevant influence on wet deposition and being available from routine measurements were used as input data for a statistical model for the estimation of wet deposition. Those variables are precipitation amount, preceding dry period, wind direction and season. The results obtained from the developed model were validated using measurements from routine monitoring stations in Germany for daily wet deposition rates of the major anions and cations. After description of model development and verification, the application of the model is presented exemplarily for sulfate, chloride and nitrate. Therefore daily precipitation data from a few representative monitoring stations and additional information about wind direction from meteorological maps were used as model input. As a result, reliable point estimates for wet deposition were available in addition to the measured data, thus allowing spatial interpolation with higher accuracy. The resulting wet deposition maps reveal that the critical loads for the investigated substances are already exceeded in some areas of Germany, particularly when the additional input from dry and occult (fog and cloud) deposition is taken into account. Using all available daily precipitation data in an annual routine, deposition maps could be available with high spatial resolution (<10 km).

AB - The correct spatial interpolation from a few available point measurements of wet deposition - which contributes a major part to total deposition - is very important for the determination of a possible exceeding of critical loads: A wide spatial variability is a property of both deposition and critical loads. For this purpose, the meteorological variables having relevant influence on wet deposition and being available from routine measurements were used as input data for a statistical model for the estimation of wet deposition. Those variables are precipitation amount, preceding dry period, wind direction and season. The results obtained from the developed model were validated using measurements from routine monitoring stations in Germany for daily wet deposition rates of the major anions and cations. After description of model development and verification, the application of the model is presented exemplarily for sulfate, chloride and nitrate. Therefore daily precipitation data from a few representative monitoring stations and additional information about wind direction from meteorological maps were used as model input. As a result, reliable point estimates for wet deposition were available in addition to the measured data, thus allowing spatial interpolation with higher accuracy. The resulting wet deposition maps reveal that the critical loads for the investigated substances are already exceeded in some areas of Germany, particularly when the additional input from dry and occult (fog and cloud) deposition is taken into account. Using all available daily precipitation data in an annual routine, deposition maps could be available with high spatial resolution (<10 km).

KW - Economics, empirical/statistics

KW - penalized regression

KW - Non-linear model

KW - Regression mit Strafterm

KW - Nichtlineare Modelle

KW - Ecosystems Research

KW - wet deposition

KW - monitoring

KW - nasse Deposition

KW - Monitoring

UR - http://www.scopus.com/inward/record.url?scp=0038813934&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/e7311e44-b14f-3db5-88ac-7ab942581bf6/

U2 - 10.1023/A:1023676011565

DO - 10.1023/A:1023676011565

M3 - Journal articles

VL - 145

SP - 215

EP - 238

JO - Water, Air, and Soil Pollution

JF - Water, Air, and Soil Pollution

SN - 0049-6979

IS - 1-4

ER -

DOI

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