http://scholars.ntou.edu.tw/handle/123456789/26545| Title: | Biogenic CO₂, CH₄, and N₂O emissions from abalone culture in tidal ponds | Authors: | Chen, Yi-Jung Chou, Wen-Chen Tseng, Hsiao-Chun Shiu, Ruei-Feng Lee, Meng-Chou Nan, Fan-Hua Yeh, Han-Yang |
Keywords: | abalone;carbon dioxide;greenhouse gases;methane;nitrous oxide | Issue Date: | 2025 | Publisher: | MDPI | Journal Volume: | 12 | Journal Issue: | 9 | Source: | MATERIALS TODAY BIO | Abstract: | Abalone is among the most highly prized seafoods, valued for its delicate flavor and texture. As abalone aquaculture continues to expand, addressing its environmental impacts has become increasingly important. Although aquaculture is recognized as a contributor to greenhouse gas (GHG) emissions, the specific mechanisms and pathways of GHG emissions-particularly in abalone farming-remain poorly understood. To clarify the patterns and drivers of GHG emissions in abalone (Haliotis discus) culture systems, this study was conducted in three aquaculture ponds located in Gongliao District, New Taipei City, Taiwan. We measured CO2, CH4, and N2O fluxes along with key environmental parameters to assess variation across sampling locations, times, and seasons. The results showed that sampling time had no significant effect on GHG flux variations, whereas seasonal changes influenced all three gases, and sampling location significantly affected N2O flux only. During the culture period, average fluxes were 2.19 +/- 10.83 mmol m-2 day-1 for CO2, 2.11 +/- 2.81 mu mol m-2 day-1 for CH4, and 1.65 +/- 2.73 mu mol m-2 day-1 for N2O, indicating that the abalone ponds served as net sources of these GHGs. When converted to CO2-equivalents (CO2-eq), the total average CO2-eq flux from the ponds was 0.02 +/- 0.09 mg CO2-eq m-2 day-1, calculated using global warming potential (GWP20 and GWP100) metrics. This study provides the first comprehensive assessment of GHG emissions in abalone pond systems and offers valuable insights into their emission dynamics. The findings contribute to the scientific basis needed to improve aquaculture GHG inventories. |
URI: | http://scholars.ntou.edu.tw/handle/123456789/26545 | ISSN: | 2076-3298 | DOI: | 10.3390/environments12090313 |
| Appears in Collections: | 水產養殖學系 海洋環境與生態研究所 |
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