Nielsen Lars Peter

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Nielsen
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Lars Peter
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  • Preprint
    Methods for measuring denitrification : diverse approaches to a difficult problem
    ( 2005-07-15) Groffman, Peter M. ; Altabet, Mark A. ; Bohlke, John K. ; Butterbach-Bahl, Klaus ; David, Mark B. ; Firestone, Mary K. ; Giblin, Anne E. ; Kana, Todd M. ; Nielsen, Lars Peter ; Voytek, Mary A.
    Denitrification, the reduction of the nitrogen (N) oxides, nitrate (NO3-) and nitrite (NO2-), to the gases nitric oxide (NO), nitrous oxide (N2O) and dinitrogen (N2), is important to primary production, water quality and the chemistry and physics of the atmosphere at ecosystem, landscape, regional and global scales. Unfortunately, this process is very difficult to measure, and existing methods are problematic for different reasons in different places at different times. In this paper, we review the major approaches that have been taken to measure denitrification in terrestrial and aquatic environments and discuss the strengths, weaknesses and future prospects for the different methods. Methodological approaches covered include; 1) acetylene-based methods, 2) 15N tracers, 3) direct N2 quantification, 4) N2/Ar ratio quantification, 5) mass balance approaches, 6) stoichiometric approaches, 7) methods based on stable isotopes, 8) in situ gradients with atmospheric environmental tracers and 9) molecular approaches. Our review makes it clear that the prospects for improved quantification of denitrification vary greatly in different environments and at different scales. While current methodology allows for the production of accurate estimates of denitrification at scales relevant to water and air quality and ecosystem fertility questions in some systems (e.g., aquatic sediments, well defined aquifers), methodology for other systems, especially upland terrestrial areas, still needs development. Comparison of mass balance and stoichiometric approaches that constrain estimates of denitrification at large scales with point measurements (made using multiple methods), in multiple systems, is likely to propel more improvement in denitrification methods over the next few years.
  • Article
    Megameter propagation and correlation of T-waves from Kermadec Trench and Islands
    (Frontiers Media, 2022-11-15) Oliveira, Tiago C. A. ; Nielsen, Peter ; Lin, Ying-Tsong ; Kushida, Noriyuki ; Jesus, Sérgio M.
    On 18 June 2020 and 4 March 2021, very energetic low-frequency underwater T-wave signals (2 to 25 Hz) were recorded at the Comprehensive Nuclear-Test-Ban Treaty (CTBT) International Monitoring System (IMS) hydrophone stations in the Pacific Ocean (Stations HA11 and HA03) and the South Atlantic Ocean (Station HA10). This work investigates the long-range (megameters) propagation of these T-waves. Their sources were three powerful submarine earthquakes in the Kermadec Trench and Islands, located at approximately 6000, 8800, and 15100 km from Stations HA11, HA03, and HA10, respectively. Arrival time and back azimuth of the recorded T-waves were estimated using the Progressive Multi-Channel Correlation algorithm installed on the CTBT Organization (CTBTO) virtual Data Exploitation Centre (vDEC). Different arrivals within the duration of the earthquake signals were identified, and their correlations were also analyzed. The data analysis at HA03 and HA10 revealed intriguing T-wave propagation paths reflecting, refracting, or even transmitting through continents, as well as T-wave excitation along a chain of seamounts. The analysis also showed much higher transmission loss (TL) in the propagation paths to HA11 than to HA03 and HA10. Moreover, strong discrepancies between expected and measured back azimuths were observed for HA11, and a three-dimensional (3D) parabolic equation model was utilized to identify the cause of these differences. Numerical results revealed the importance of 3D effects induced by the Kermadec Ridge, Fiji archipelago, and Marshall Islands on T-wave propagation to HA11. This analysis can guide future improvements in underwater event localization using the CTBT-IMS hydroacoustic sensor network.