4.7 Article Proceedings Paper

Long-term assessment of nitrogen deposition at remote EANET sites in Japan

期刊

ATMOSPHERIC ENVIRONMENT
卷 146, 期 -, 页码 70-78

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.atmosenv.2016.04.015

关键词

Reactive nitrogen; Oxidized nitrogen; Reduced nitrogen; Dry deposition; Inferential method; East Asia

资金

  1. Grants-in-Aid for Scientific Research [25502005] Funding Source: KAKEN

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Atmospheric emissions of reactive nitrogen have increased significantly on a global scale due to increases of the use of artificial fertilizer and the burning of fossil fuels. The Asian region has been identified as a high-risk area for nitrogen deposition effects on ecosystems. This paper describes a measurement-based assessment of nitrogen deposition carried out in cooperation with the Acid Deposition Monitoring Network in East Asia (EANET). The investigation aimed to understand the status and variability of dry, wet and total deposition of oxidized and reduced nitrogen over a 10-year period (2003-2012) at 8 remote sites in Japan (Rishiri, Tappi, Sado-seki, Happo, Oki, Yusuhara, Ogasawara and Hedo). Dry deposition amounts were estimated by the inferential method. All of the sites except Rishiri and Ogasawara had high mean annual total nitrogen deposition amounts of approximately 10 kg N ha(-1) year(-1) or more, over the 10-year period. The high contribution of oxidized nitrogen deposition in the central area is mainly caused by domestic emissions, especially for dry deposition processes. An increase in reduced nitrogen deposition originating from regional emissions was found, and is likely to result in a subsequent increase in the total nitrogen deposition in Japan. Since neither a clear increasing nor decreasing trend in total nitrogen deposition was found at any site during the 10-year period, the nitrogen deposition amounts remained high thorough the long period in Japanese remote area. The spatial distribution of nitrogen deposition was found to be significant when uncertainties were accounted for. (C) 2016 Elsevier Ltd. All rights reserved.

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