Skip to main content

Advertisement

SpringerLink
Log in

Exploring wind direction and SO2 concentration by circular–linear density estimation

  • Original Paper
  • Published:
Stochastic Environmental Research and Risk Assessment Aims and scope Submit manuscript

Abstract

The study of environmental problems usually requires the description of variables with different nature and the assessment of relations between them. In this work, an algorithm for flexible estimation of the joint density for a circular–linear variable is proposed. The method is applied for exploring the relation between wind direction and SO2 concentration in a monitoring station close to a power plant located in Galicia (NW–Spain), in order to compare the effectiveness of precautionary measures for pollutants reduction in two different years.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  • Agostinelli C, Lund U (2011) Circular: circular statistics. R package version 0.4-3. https://r-forge.r-project.org/projects/circular/. Accessed 23 July 2011

  • Azzalini A (1981) A note on the estimation of a distribution function and quantiles by a kernel method. Biometrika 68: 326–328

    Article  Google Scholar 

  • Bayraktar H, Turalioğlu FS, Tuncel G (2010) Average mass concentrations of TSP, PM10 and PM2.5 in Erzurum urban atmosphere, Turkey. Stoch Environ Res Risk Assess 24:57–65

    Article  Google Scholar 

  • Chen C-C, Wu K-Y, Chang-Chien G-P (2011) Point source identification using a simple permutation test: a case study of elevated PCDD/F levels in ambient air and soil and their relation to the distance to a local municipal solid waste incinerator. Stoch Environ Res Risk Assess 26:225–233

    Article  Google Scholar 

  • Deschepper E, Thas O, Ottoy JP (2008) Tests and diagnostic plots for detecting lack-of-fit for circular–linear regression models. Biometrics 64:912–920

    Article  CAS  Google Scholar 

  • Duong T, Hazelton ML (2003) Plug-in bandwidth matrices for bivariate kernel density estimation. Nonparametr Stat 15:17–30

    Google Scholar 

  • Fernández-Durán JJ (2004) Circular distributions based on nonnegative trigonometric sums. Biometrics 60:499–503

    Article  Google Scholar 

  • Fernández-Durán JJ (2007) Models for circular–linear and circular–circular data constructed from circular distributions based on nonnegative trigonometric sums. Biometrics 63:579–585

    Article  Google Scholar 

  • Gijbels I, Mielniczuk J (1990) Estimating the density of a copula function. Communications in statistics. Theory Methods 19:445–464

    Article  Google Scholar 

  • Hall P, Watson GS, Cabrera J (1987) Kernel density estimation with spherical data. Biometrika 74:751–762

    Article  Google Scholar 

  • Jammalamadaka SR, Lund UJ (2006) The effect of wind direction on ozone levels: a case study. Environ Ecol Stat 13:287–298

    Article  CAS  Google Scholar 

  • Jammalamadaka SR, SenGupta A (2001) Topics in circular statistics. World Scientific Press. Singapore

  • Johnson ME (1987) Multivariate statistical simulation. Wiley series in probability and mathematical statistics. Wiley, New York

  • Johnson RA, Wehrly T (1978) Some angular–linear distributions and related regression models. J Am Stat Assoc 73:602–606

    Article  Google Scholar 

  • Mardia KV, Jupp PE, (2000) Directional statistics. Wiley series in probability and statistics. Wiley, Chichester

  • Nazemi A, Elshorbagy A (2012) Application of copula modelling to the performance assessment of reconstructed watersheds. Stoch Environ Res Risk Assess 26:189–205.

    Google Scholar 

  • Nelsen RB (2006) An introduction to Copulas. Springer series in statistics. Springer, New York

  • Omelka M, Gijbels I, Veraverbeke N (2009) Improved kernel estimation of copulas: weak convergence and goodness-of-fit testing. Ann Statist 37:3023–3058

    Google Scholar 

  • R Development Core Team (2011) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Austria

  • Ruppert D, Wand MP (1994) Multivariate locally weighted least squares regression. Ann Stat 22:1346–1370

    Article  Google Scholar 

  • Sheather SJ, Jones MC (1991) A reliable data-based bandwidth selection method for kernel density estimation. J R Stat Soc B 53:683–690

    Google Scholar 

  • Shih DC–F (2008) Wind characterization and potential assessment using spectral analysis. Stoch Environ Res Risk Assess 22:247–256

    Article  Google Scholar 

  • Taylor CC (2008) Automatic bandwidth selection for circular density estimation. Comput Stat Data Anal 52:3493–3500

    Article  Google Scholar 

  • Wand MP, Jones MC (1995) Kernel smoothing. Chapman and Hall, London

  • Wehrly T, Johnson RA (1979) Bivariate models for dependence of angular observations and a related Markov process. Biometrika 67:255–256

    Article  Google Scholar 

Download references

Acknowledgements

The authors acknowledge the support of Project MTM2008–03010, from the Spanish Ministry of Science and Innovation and Project 10MDS207015PR from Dirección Xeral de I+D, Xunta de Galicia. Work of E. García-Portugués has been supported by FPU grant AP2010–0957 from the Spanish Ministry of Education. We also thank the referee and the Associate Editor for providing constructive comments and help in improving this paper.

Author information

Authors and Affiliations

  1. Department of Statistics and Operations Research, Faculty of Mathematics, University of Santiago de Compostela, Santiago de Compostela, Spain

    E. García-Portugués, R. M. Crujeiras & W. González-Manteiga

Authors
  1. E. García-Portugués
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. R. M. Crujeiras
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. W. González-Manteiga
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to E. García-Portugués.

Rights and permissions

Reprints and permissions

About this article

Cite this article

García-Portugués, E., Crujeiras, R.M. & González-Manteiga, W. Exploring wind direction and SO2 concentration by circular–linear density estimation. Stoch Environ Res Risk Assess 27, 1055–1067 (2013). https://doi.org/10.1007/s00477-012-0642-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00477-012-0642-5

Keywords

Search

Navigation