Evaluating the Distribution of Perfluoroalkyl Substances in Rice Paddy Lysimeter with an Andosol.

The properties of potential emerging persistent contaminants, perfluoroalkyl substances (PFAS), in an andosol rice paddy lysimeter were analyzed to determine their mobility and leaching behavior regarding carbon chain length and functional groups. For this purpose, simulated contaminated water (ΣPFAS = 1,185,719 ng/L) was used in the lysimeter. The results showed that PFAS distribution in the paddy soil lysimeter was influenced by the migration of these substances into irrigation water and their adsorption into the soil. PFHxS (C6) and PFOS (C8), which are the main components of the simulated contaminated water, were mostly captured in the soil layers of the low-humic andosol layer (0-35 cm). PFAS distribution may depend on soil properties, such as total carbon (TC) content. Compared with perfluoroalkane sulfonic acids (PFSAs), the distribution of perfluoroalkyl carboxylic acids (PFCAs) in soil showed significant variation. The remaining PFCAs were distributed across all layers of the lysimeter, except for the longer-chain PFCAs. Moreover, the PFSA distribution was directly correlated with the carbon chain number, whereby longer- and shorter-chain PFSAs accumulated in the top and bottom soil layers, respectively. This study provides detailed information on the distribution, leaching, uptake, and accumulation of individual PFAS in andosol paddy fields in Japan.

Accumulation of perfluoroalkyl substances in lysimeter-grown rice in Japan using tap water and simulated contaminated water.

Perfluoroalkyl substances (PFASs) are a group of contaminants of concern in agricultural crops, but little is known of their accumulation or behavior in grains. We grew Japanese rice (Oryza sativa subsp. indica) in lysimeters irrigated with tap water or tap water plus simulated contaminated water for 2 years, then analyzed the roots, straw, unhulled rice, white rice, bran, soil, and water for PFASs residues. Total fluorine was measured by combustion ion chromatography. Estimated per-plant residue levels were 3.0 pg perfluorooctanesulfonic acid (PFOS) (bran: 0.5%, hull: 99.5%), 0.54 pg N-ethylperfluorooctanesulfonamide (N-EtFOSA) (white rice: 67%, hull: 33%), 1.2 pg perfluorobutanoic acid (PFBA) (white rice: 13%, bran: 7%, hull: 79%), 0.68 pg perfluoropentanoic acid (hull: 100%), 0.50 pg perfluorohexanoic acid (PFHxA) (white rice: 65%, bran: 16%, hull: 19%), 0.21 pg perfluoroheptanoic acid (hull: 100%), 0.25 pg perfluorooctanoic acid (PFOA) (hull: 100%), and 0.12 pg perfluorodecanoic acid (PFNA) (white rice: 81%, bran: 19%). Estimated daily PFASs intakes were <1-3 ng perfluorooctanesulfonamide, <1-7 ng N-EtFOSA, 1-2 ng PFBA, <3-4 ng PFHxA, and 1-2 ng PFNA. Estimated PFOS, PFOA, and total PFASs in straw feed were 0.4, 0.1, and 2 kg yr-1 and 0.7, 0.4, and 8 kg yr-1 in 2015 and 2016, respectively. Estimated PFOS, PFOA, and total PFASs in straw fertilizer were 4, 1, and 23 kg yr-1 and 7, 4, and 86 kg yr-1 in 2015 and 2016, respectively. PFASs accumulation may cause longer residence time in agricultural systems owing to straw being used as animal feed and organic fertilizer.

Estimating Soil Moisture Distributions across Small Farm Fields with ALOS/PALSAR.

The ALOS (advanced land observing satellite) has an active microwave sensor, PALSAR (phased array L-band synthetic aperture radar), which has a fine resolution of 6.5 m. Because of the fine resolution, PALSAR provides the possibility of estimating soil moisture distributions in small farmlands. Making such small-scale estimates has not been available with traditional satellite remote sensing techniques. In this study, the relationship between microwave backscattering coefficient (σ) measured with PALSAR and ground-based soil moisture was determined to investigate the performance of PALSAR for estimating soil moisture distribution in a small-scale farmland. On the ground at a cabbage field in Japan in 2008, the soil moisture distribution of multiple soil layers was measured using time domain reflectometry when the ALOS flew over the field. Soil moisture in the 0-20 cm soil layer showed the largest correlation coefficient with σ (r = 0.403). The σ values also showed a strong correlation with the ground surface coverage ratio by cabbage plants. Our results suggested that PALSAR could estimate soil moisture distribution of the 0-20 cm soil layer across a bare field and a crop coverage ratio when crops were planted.

Screening of plants for phytoremediation of oil-contaminated soil.

Several species of ornamental flowering plants were evaluated regarding their phytoremediation ability for the cleanup of oil-contaminated soil in Japanese environmental conditions. Thirty-three species of plants were grown in oil-contaminated soil, and Mimosa, Zinnia, Gazania, and cypress vine were selected for further assessment on the basis of their favorable initial growth. No significant difference was observed in the above-ground and under-ground dry matter weight of Gazania 180 days after sowing between contaminated and non-contaminated plots. However, the other 3 species of plants died by the 180th day, indicating that Gazania has an especially strong tolerance for oil-contaminated soil. The total petroleum hydrocarbon concentration of the soils in which the 4 species of plants were grown decreased by 45-49% by the 180th day. Compared to an irrigated plot, the dehydrogenase activity of the contaminated soil also increased significantly, indicating a phytoremediation effect by the 4 tested plants. Mimosa, Zinnia, and cypress vine all died by the 180th day after seeding, but the roots themselves became a source of nutrients for the soil microorganisms, which led to a phytoremediation effect by increase in the oil degradation activity. It has been indicated that Gazania is most appropriate for phytoremediation of oil-contaminated soil.

Contribution of Ebullition to Methane and Carbon Dioxide Emission from Water between Plant Rows in a Tropical Rice Paddy Field.

Although bubble ebullition through water in rice paddy fields dominates direct methane (CH4) emissions from paddy soil to the atmosphere in tropical regions, the temporal changes and regulating factors of this ebullition are poorly understood. Bubbles in a submerged paddy soil also contain high concentrations of carbon dioxide (CO2), implying that CO2 ebullition may occur in addition to CH4 ebullition. We investigated the dynamics of CH4 and CO2 ebullition in tropical rice paddy fields using an automated closed chamber installed between rice plants. Abrupt increases in CH4 concentrations occurred by bubble ebullition. The CO2 concentration in the chamber air suddenly increased at the same time, which indicated that CO2 ebullition was also occurring. The CH4 and CO2 emissions by bubble ebullition were correlated with falling atmospheric pressure and increasing soil surface temperature. The relative contribution of CH4 and CO2 ebullitions to the daily total emissions was 95-97% and 13-35%, respectively.

Sensitivity Analysis and Validation for Numerical Simulation of Water Infiltration into Unsaturated Soil.

A FORTRAN code for liquid water flow in unsaturated soil under the isothermal condition was developed to simulate water infiltration into Yolo light clay. The governing equation, that is, Richards' equation, was approximated by the finite-difference method. A normalized sensitivity coefficient was used in the sensitivity analysis of Richards' equation. Normalized sensitivity coefficient was calculated using one-at-a-time (OAT) method and elementary effects (EE) method based on hydraulic functions for matric suction and hydraulic conductivity. Results from EE method provided additional insight into model input parameters, such as input parameter linearity and oscillating sign effect. Boundary volumetric water content (θ L (upper bound)) and saturated volumetric water content (θ s ) were consistently found to be the most sensitive parameters corresponding to positive and negative relations, as given by the hydraulic functions. In addition, although initial volumetric water content (θ L (initial cond)) and time-step size (Δt), respectively, possessed a great amount of sensitivity coefficient and uncertainty value, they did not exhibit significant influence on model output as demonstrated by spatial discretization size (Δz). The input multiplication of parameters sensitivity coefficient and uncertainty value was found to affect the outcome of model simulation, in which parameter with the highest value was found to be Δz.