Effects of species and geo-information on the 137Cs concentrations in edible wild mushrooms and plants collected by residents after the Fukushima nuclear accident

Site information

We collected radioactivity data of wild mushrooms and wild edible plants from inspection results of specimens brought in by residents in Kawauchi Village, which is located 12–30 km away from the FDNPP (Fig. 1). Kawauchi Village is considered small, with an area of 197.4 km², and a population of about 2500 (2820 in 2010 and 2518 in 2021)⁴⁸. It is located in the middle of the Abukuma Highlands, where the elevation ranges from 270 to 1,192 m above the sea level. It has a forest coverage of 89.0%, which is higher than the average for Fukushima Prefecture (71%) and Japan as a whole (69%)⁴⁹. ¹³⁷Cs deposition in the village ranged from 42 to 960 kBq/m² in 2011, estimated from an aircraft monitoring²⁸. Before the accident, its residents were accustomed to gathering wild foods, such as wild edible mushrooms, plants, mammals, and wild honey⁵⁰; many have been brought in for inspection. Information on collection areas of sub-village levels, called “Ko-aza” in Japanese, is also recorded. For these reasons, we thought that the data of the brought in inspection in Kawauchi Village would possess high value as data for inter-species and inter-region analysis on the wild mushrooms and edible plants’ radioactivity concentrations.

Radioactivity data of mushrooms and wild plants

Fukushima Prefecture sets up a system for each municipality to inspect radioactivity in vegetables and mushrooms consumed by residents, and Kawauchi Village started its inspection program in May 2012. Simple inspection machines are set up at public facilities, and inspections are conducted upon application by residents. In Kawauchi Village, the location of samples inspected was requested at the sub-village level. The inspection results were regularly reported in the village newsletter, along with the inspection date, inspected food, and collection location. The data compiled from May 2012 to March 2020 was provided to us through the village officials. Orita et al. analyzed the same inspection data of agricultural products in Kawauchi Village²⁴. They used 7668 food data from April 2013 to December 2014, including 1986 wild plants and mushrooms data for internal radiation exposure assessment. Some of their data overlap with the data used in our analyses.

System of monitoring radioactivity in Kawauchi Village

Kawauchi Village started the brought in inspection in May 2012, and there is a maximum of eight inspection stations and currently three stations managed by residents. In the inspection sites, there are four types of NaI (Tl) or CsI (Tl) scintillation detectors. The machine names are Triathler Becquerel Finder (Hidex, Oy, Finland), Captus-3000A (Capintec, NJ), CAN-OSP-NAI (Hitachi Aloka, Tokyo, Japan), and FD-08Cs1000-1 (X-Ray Technology, Osaka, Japan). Table S4 shows the specifications of the machines^51,52,53. All instruments have been confirmed to meet the radiocesium screening method requirements for food⁵³. Among these machines, FD-08Cs1000-1 can measure radioactivity non-destructively, and the others conduct destructive measurements. The sample weight is approximately 500 g, and the counting time is 30 min. FD-08Cs1000-1 outputs the summed concentration of the two radiocesium nuclides (¹³⁴Cs and ¹³⁷Cs), and its detection limit is 10 Bq/kg (for total ¹³⁴Cs + ¹³⁷Cs). Each of the other three machines separately outputs the concentrations of ¹³⁴Cs and ¹³⁷Cs, and the detection limit is 10 Bq/kg for each radionuclide. Energy calibrations and background checks were performed daily, and the accuracy was periodically verified with brown rice whose radiocesium concentration was verified by calibrated high-purity Germanium (HPGe) detectors installed in the Fukushima Nuclear Center⁴⁹. Table S4 shows the results of quality control using brown rice.

Data preparation of radioactivity of samples

From the radioactivity data of wild mushrooms and plants, we picked up data that met the following criteria;

• Data have information of sampling location at sub-village levels

• Items that are not confirmed to be cooked products such as “boiled” or “dried.”

• Species with more than ten samples in which radiocesium was detected.

In cases where mushrooms and wild plants were given in dialects, we confirmed the species’ names with residents. The names of the species were determined from the Japanese names of the items, but in some cases, it was not possible to distinguish between Cortinarius salor (“Murasakiaburashimejimodoki” in Japanese) and C. iodes (“Murasakiaburashimeji”), considered to be closely related species, so the two were mixed for analysis. The leaf stalk and scape of Petasites japonicus (Japanese butterbur) are called “Fuki” and “Fukinotou” in Japanese, respectively, and are registered separately. Therefore, despite being the same species, they were distinguished in the analysis. In this data, there were not sampling date but measurement date. Therefore, the date of measurement and sample collection were assumed to be the same.

The ¹³⁷Cs concentration results were used in the model analysis. The reason for not using the¹³⁴Cs concentration among the measured values is explained in the subsection of “Bayesian estimation”. ¹³⁷Cs concentrations were decay-corrected to March 11th, 2011 for comparison with Komatsu et al. (2019). Based on the assumption that the ¹³⁴Cs/¹³⁷Cs ratio at the time of the accident was one⁵⁴, the summed concentration of ¹³⁴Cs and ¹³⁷Cs concentration taken by FD08-Cs1000-1 was converted to a ¹³⁷Cs concentration, which was decay-corrected to March 11th, 2011, using the following equation;

In this equation, dy indicates the period from March 11th, 2011, to the date of measuring, and it is expressed by decimal years.

Sub-village (“Ko-aza”) boundary map of Kawauchi Village

Kawauchi Village comprises eight administrative communities (called “Oh-aza” in Japanese), which are further subdivided into small administrative units known as “Ko-aza”. Here, we refer to these small administrative units as sub-villages. We obtained a sub-village map from the administrative office. The printed map was originally drawn by hand and had been used for village administration. To create a polygon shapefile of the map, we digitized it by scanning, geo-rectifying, and digitizing using GIS software in TNTmips v2014 (MicroImages, Inc, NE) and ArcGIS 10.3 (Esri, Inc, CA). We used this map to associate land names with monthly radioactivity data from samples and to estimate sample collection locations.

Deposition data

For the ¹³⁷Cs deposition data of this area, we used 250 m grid deposition data measured by the Ministry of Education, Culture, Sports, Science and Technology^28,55 and then corrected by Kato and Onda²⁶. We computed the geometric mean value of ¹³⁷Cs deposition within each sub-village polygon. The ¹³⁷Cs deposition is also decay-corrected to March 11th, 2011.

Bayesian estimation

We constructed a Bayesian model partially modified from Komatsu et al.²² to estimate ¹³⁷Cs concentration (¹³⁷Cs_sample). The model is based on the Gonze and Calmon’s concept of normalized concentration (NC) as expressed by:

where D indicates the radiocesium deposition amount based on the aircraft monitoring. Then the above equation is transformed and logarithmized to yield;

In this expression of the model equation, we further assumed that the logartihm of NC encompassed the summed effects of species identity, collection date, and collection site, and that the logarithm of NC was normally distributed around the estimated mean as per the following equations;

where NC_sp, λ_sp, D_loc and r_loc indicate characteristics of concentration of species, temporal trends of species, ¹³⁷Cs deposition of each sub-village area and effects of sub-village on concentration, respectively. r_loc is a parameter with zero mean that represents the deviation of the concentration effect from the expected value based on the deposition (D_loc) value at the point of collection. These parameters except D_loc were obtained from hierarchically sampled from normal distribution with hierarchical parameters (μ_sp, σ_sp, μ_λsp, σ_λsp, σ_loc). Additionally, r_loc was sampled using the Intrinsic Conditional Auto-Regressive (Intrinsic CAR) model⁵⁶, which is one of the models considering spatial auto-correlation. For samples whose measured radiocesium concentrations were below the detection limit, radiocesium concentration values were estimated by a censoring distribution in which the detection limit was treated as the upper bound⁵⁷. This model was defined as the “sub-village model” for this research. This model is similar to model 6 in Komatsu et al.²² but differs in that their previous model takes into account ¹³⁴Cs values and differences between ¹³⁴ and ¹³⁷Cs values. Komatsu et al. evaluated the regional trend in the difference between¹³⁴Cs and ¹³⁷Cs concentrations across eastern Japan because ¹³⁷Cs originating from nuclear bomb tests before the FDNPP accident was detected in wild mushrooms sampled in the northern and southern parts of eastern Japan, which are far from the FDNPP and received less deposition from the accident (< 10 Bq/m² according to aircraft monitoring). However, in Kawauchi Village, the amount of ¹³⁷Cs deposition because of the FDNPP accident (42–960 Bq/m² in Kawauchi Village²⁶) was larger than the amount of ¹³⁷Cs deposition from nuclear tests (< 10 kBq/m² in Japan⁵⁸), and it is difficult to evaluate differences between ¹³⁷Cs and ¹³⁴Cs concentrations of each specimen. Therefore, our analysis used only ¹³⁷Cs values given the longer half-life of that isotope.

Alternatively, for the comparison, we also used the “whole village model,” in which r_loc was not taken into account and the geometric mean of the ¹³⁷Cs deposition in the village (D_village) was used for the calculation.

For the Bayesian estimation, we used WinBUGS ver 1.4.3⁵⁷. In the calculation, we set burn-in, burn-out, chain, and thin as 10,000, 20,000, 3, and 10, respectively. As a result, we gained 3000 posterior results for each parameter.

The effective annual change ratio according to species (R_{eff_sp}) was calculated based on the radiological decay of ¹³⁷Cs (half-life: 30.17 years) and using λ_sp as follows:

Limitation

The date of collection of each sample was not registered, and the substitution of the measurement date for the collection date may cause uncertainty in the analysis of temporal trends. However, the measurement dates were reported in a concentrated manner for each species (Fig. S5), and we assume that the collection and measurement dates were generally close. Considering the small annual rate of change (< 20%) and the length of the sampling period, it is unlikely that a substantial bias affected the conclusions.

It has been pointed out that non-destructive testing machines cannot fill samples homogeneously and can sometimes introduce a bias of > 20% vs. HPGe measurements⁵². However, in the case of wild mushrooms and plants, the variation among species and samples is substantial, on the one to two orders of magnitude. Therefore, we consider the influence of errors because of the measurement equipment to be dwarfed by other factors.

Source: Ecology - nature.com