Radiocaesium derived from the TEPCO Fukushima accident in the North Pacific Ocean: Surface transport processes until 2017

2018 ◽  
Vol 189 ◽  
pp. 93-102 ◽  
Author(s):  
Michio Aoyama ◽  
Yasunori Hamajima ◽  
Yayoi Inomata ◽  
Yuichiro Kumamoto ◽  
Eitarou Oka ◽  
...  
Ocean Science ◽  
2018 ◽  
Vol 14 (4) ◽  
pp. 813-826 ◽  
Author(s):  
Yayoi Inomata ◽  
Michio Aoyama ◽  
Yasunori Hamajima ◽  
Masatoshi Yamada

Abstract. This study investigated the spatio-temporal variations in activity concentrations in the Sea of Japan (SOJ) of 137Cs and these transport process from the North Pacific Ocean to the SOJ through the East China Sea (ECS) during 2012–2016. The 137Cs activity concentrations in the SOJ have been increasing since 2012–2013 and reached a maximum in 2015–2016 of approximately 3.4 Bq m−3, more than twice the pre-Fukushima accident 137Cs activity concentration of ∼1.5 Bq m−3. The 134Cs ∕ 137Cs activity ratios ranged from 0.36 to 0.51 in 2016. After taking into account radioactive decay and ocean mixing, we concluded that these 134Cs ∕ 137Cs activity ratios were evidence that the Fukushima accident caused the increase in the 137Cs activity concentrations. In the North Pacific south of Japan (NPSJ), the highest 137Cs activities in 2012–2013 were observed in water from a depth of 300 m, the potential water density anomaly (σθ) of which corresponded to subtropical mode water (STMW). In the ECS, a clear increase in the 137Cs activity concentration started at a depth of 140 m (σθ= 25.2 kg m−3) in April 2013, propagated to the surface layers at depths of roughly 0–50 m, reached a maximum in 2015 and decreased in subsequent years. In the ECS, the Fukushima-derived radiocaesium activity concentration in surface water reached a maximum in 2014–2015, whereas the concentration in the SOJ reached a maximum in 2015–2016. The propagation of Fukushima-derived radiocaesium in surface seawater from the ECS into the SOJ therefore required approximately 1 year. These temporal changes in 137Cs activity concentrations and 134Cs ∕ 137Cs activity ratios indicated that part of the 137Cs and 134Cs derived from the Fukushima accident (FNPP1-derived 137Cs and134Cs) was transported within several years to the ECS and then to the SOJ via STMW from the NPSJ. The integrated amount of FNPP1-derived 137Cs that entered the SOJ before 2016 was estimated to be 0.21±0.01 PBq, 5.0 % of the estimated total amount of FNPP1-derived 137Cs in the STMW. The integrated amount of FNPP1-derived 137Cs that returned to the North Pacific Ocean through the Tsugaru Strait was estimated to be 0.09±0.01 Bq, 43 % of the total amount of FNPP1-derived 137Cs transported to the SOJ and 2.1 % of the estimated total amount of FNPP1-derived 137Cs in the STMW.


Water ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 388
Author(s):  
Hao Cheng ◽  
Liang Sun ◽  
Jiagen Li

The extraction of physical information about the subsurface ocean from surface information obtained from satellite measurements is both important and challenging. We introduce a back-propagation neural network (BPNN) method to determine the subsurface temperature of the North Pacific Ocean by selecting the optimum input combination of sea surface parameters obtained from satellite measurements. In addition to sea surface height (SSH), sea surface temperature (SST), sea surface salinity (SSS) and sea surface wind (SSW), we also included the sea surface velocity (SSV) as a new component in our study. This allowed us to partially resolve the non-linear subsurface dynamics associated with advection, which improved the estimated results, especially in regions with strong currents. The accuracy of the estimated results was verified with reprocessed observational datasets. Our results show that the BPNN model can accurately estimate the subsurface (upper 1000 m) temperature of the North Pacific Ocean. The corresponding mean square errors were 0.868 and 0.802 using four (SSH, SST, SSS and SSW) and five (SSH, SST, SSS, SSW and SSV) input parameters and the average coefficients of determination were 0.952 and 0.967, respectively. The input of the SSV in addition to the SSH, SST, SSS and SSW therefore has a positive impact on the BPNN model and helps to improve the accuracy of the estimation. This study provides important technical support for retrieving thermal information about the ocean interior from surface satellite remote sensing observations, which will help to expand the scope of satellite measurements of the ocean.


2021 ◽  
Author(s):  
R. J. David Wells ◽  
Veronica A. Quesnell ◽  
Robert L. Humphreys ◽  
Heidi Dewar ◽  
Jay R. Rooker ◽  
...  

2010 ◽  
Vol 37 (2) ◽  
pp. n/a-n/a ◽  
Author(s):  
Robert H. Byrne ◽  
Sabine Mecking ◽  
Richard A. Feely ◽  
Xuewu Liu

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