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| Effects of observation period selection on annual CH4 emission from freshwater aquaculture ponds |
| Received:November 02, 2021 |
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| KeyWord:freshwater aquaculture pond;eddy covariance method;methane flux;observation period selection |
| Author Name | Affiliation | E-mail | | ZHAO Jiayu | NUIST Center on Atmospheric Environment, Nanjing University of Information Science and Technology, Nanjing 210044, China
Key Laboratory of Meteorology and Ecological Environmental of Hebei Province, Shijiazhuang 050021, China
School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China | | | ZHANG Mi | NUIST Center on Atmospheric Environment, Nanjing University of Information Science and Technology, Nanjing 210044, China
School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China | zhangm.80@nuist.edu.cn | | SHI Lixin | Key Laboratory of Meteorology and Ecological Environmental of Hebei Province, Shijiazhuang 050021, China | | | XIAO Wei | NUIST Center on Atmospheric Environment, Nanjing University of Information Science and Technology, Nanjing 210044, China
School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China | | | XIE Yanhong | NUIST Center on Atmospheric Environment, Nanjing University of Information Science and Technology, Nanjing 210044, China
School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China | | | PU Yini | NUIST Center on Atmospheric Environment, Nanjing University of Information Science and Technology, Nanjing 210044, China
School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China | | | JIA Lei | NUIST Center on Atmospheric Environment, Nanjing University of Information Science and Technology, Nanjing 210044, China
School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China | | | ZHEN Xiaoju | Key Laboratory of Meteorology and Ecological Environmental of Hebei Province, Shijiazhuang 050021, China | | | FENG Zhaozhong | School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China | |
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| Abstract: |
| Freshwater aquaculture ponds are hot spots of methane（CH4）emission, and large challenges remain in accurate observations of annual CH4 emissions, especially those based on low-frequency observation methods. In this study, high-frequency CH4 flux was measured continuously for five years, from 2016 to 2020, with the eddy covariance（EC）method in typical freshwater aquaculture ponds in the subtropical Yangtze River Delta, China. Using these data, optimal flux observation schemes, including the observation time in a day and the number of sampling days in a year, for the low-frequency observation method were developed. The results follow. For the daily observation time, observations should be conducted from 14：30 to 16：30 in spring, from 6：30 to 8：30 in summer and autumn, and from 11：30 to 13： 30 in winter. The averaged results during the above time periods in the different seasons could be used to represent the daily value. By comparison with seasonal daily value obtained by EC continuous observation, this method contained much smaller uncertainty, ranging from 0.1% to 4%. For the number of sampling days, on the basis of accurate estimation of the daily average, we recommend that measurements of CH4 flux were made over at least 80 days（observational frequency：six to seven days evenly scattered throughout one month）scattered throughout the whole year to cover the seasonal pattern of CH4 flux as well as achieve high-accuracy estimation（defined as within ±20% of the annual mean value derived from EC observation）. Fewer than 20 sampling days yielded uncertainties in annual CH4 emission estimation as high as 50%. The results in this study provide a scientific basis and reference for designing an observational period scheme for CH4 flux from ponds when high-frequency and continuous observations are lacking and for the reduction of uncertainties in the estimation of the inland water carbon budget. |
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