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Estimating the Nitrous Oxide Emission Rate from the Soil Surface by Means of a Diffusion Model

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  • Asger Roer Pedersen

Abstract

Soil cover methods are probably the most widely used methods for measuring the nitrous oxide emission rate from the soil surface. The methodology involves estimation of the emission rate from repeated measurements of the nitrous oxide concentration beneath a soil cover. Based on a deterministic model proposed by Hutchinson & Mosier (1981) we propose to use a diffusion process as a stochastic model for the evolution of the nitrous oxide concentrations beneath a soil cover. From this model we derive methods for statistical inference about the emission rate that significantly extend the method proposed by Hutchinson & Mosier (1981). In particular, the derived methods provide solutions to important problems with the method proposed by Hutchinson & Mosier (1981).

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  • Asger Roer Pedersen, 2000. "Estimating the Nitrous Oxide Emission Rate from the Soil Surface by Means of a Diffusion Model," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 27(3), pages 385-403, September.
  • Handle: RePEc:bla:scjsta:v:27:y:2000:i:3:p:385-403
    DOI: 10.1111/1467-9469.00196
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    Cited by:

    1. Jean Jacod & Michael Sørensen, 2018. "A review of asymptotic theory of estimating functions," Statistical Inference for Stochastic Processes, Springer, vol. 21(2), pages 415-434, July.
    2. Vinicius P. Israel & H�lio S. Migon, 2012. "Stochastic models for greenhouse gas emission rate estimation from hydroelectric reservoirs: a Bayesian hierarchical approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(5), pages 1069-1086, October.
    3. Nina Munkholt Jakobsen & Michael Sørensen, 2015. "Efficient Estimation for Diffusions Sampled at High Frequency Over a Fixed Time Interval," CREATES Research Papers 2015-33, Department of Economics and Business Economics, Aarhus University.
    4. Michael Sørensen, 2008. "Efficient estimation for ergodic diffusions sampled at high frequency," CREATES Research Papers 2007-46, Department of Economics and Business Economics, Aarhus University.
    5. Mathieu Kessler & Michael Sørensen, 2005. "On Time-Reversibility and Estimating Functions for Markov Processes," Statistical Inference for Stochastic Processes, Springer, vol. 8(1), pages 95-107, January.

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