Cropland contamination by toxic trace metal (loid)s (TTMs) has attracted increasing attention due to the serious consequential threat to crop quality and human health. Mitigation of plant TTM stress by silica amendment has been proposed recently. However, the relationship between the siliceous structure of phytoliths and TTMs in plants, and the environmental implications of phytolith-occluded trace metal (loid)s (PhytTMs) remain unclear. This study assessed the accumulation of five metal (loid)s, including lead (Pb), zinc (Zn), cadmium (Cd), copper (Cu) and arsenic (As), in the organic tissues and phytoliths of wheat grown in a mixed-TTM contaminated soil under both lightly and heavily contaminated conditions. The results show that the concentrations of plant TTMs and PhytTMs were significantly (p < 0.05) positively correlated, and higher in heavily contaminated wheats than those in lightly contaminated ones. The bio-enrichment factors between phytoliths and organic tissues were higher for As (1.83), Pb (0.27) and Zn (0.30) than for Cd (0.03) and Cu (0.14), implying that As, Pb and Zn were more readily co-precipitated with silicon (Si) in phytolith structures than Cd and Cu. Network analysis of the relationship between soil and plant elements with PhytTMs showed that severe contamination could impact the homeostasis of elements in plants by altering the translocation of TTMs between soils, plants, and phytoliths. The accumulation of TTMs in phytoliths was affected by the capacity of Si deposition in tissues and chelation of TTMs with silica, which could impact the role of PhytTMs in global biogeochemical TTM cycles.

The most prominent source of Cu contamination in soils is metal mining and processing, partly since the Middle Age. However, coal mining and combustion can also cause (some) Cu contamination. We studied the distribution of Cu concentrations and isotope ratios in soils of the Huaibei coal mining area. The contribution of the coal mining and combustion to total Cu concentrations in soil was determined with a two-end-member mixing model based on the distinct δ⁶⁵Cu values of the Cu emitted from coal mining and combustion and in native soil. The mean Cu concentration of 75 mg kg⁻¹ exceeded the local soil background value (round to 22.13 mg kg⁻¹). The similar δ⁶⁵Cu value of grass near the coal mining and combustion operation as in gangue and flying ash indicated a superficial Cu contamination. Mining input was the dominant source of Cu in the contaminated soils, contributing up to 95% and on average 72% of the total Cu in the topsoils. The mining-derived Cu was leached to a depth of 65 cm, where still 29% of the Cu could be attributed to the mining emissions. Grasses showed lower δ⁶⁵Cu values than the topsoils, because of the preferential uptake of light Cu isotopes. However, the Δ⁶⁵Cugᵣₐₛₛ₋ₛₒᵢₗ was lower in the contaminated than the uncontaminated area because of superficial adsorption of isotopically heavy Cu from the mining emissions. Overall, in this study the distinct δ⁶⁵Cu values of the mining-derived Cu emissions and the native soil allowed for the quantification of the mining-derived Cu and had already reached the subsoil and contaminated the grass by superficial adsorption in only 60 years of mining operation.

The properties and metal-binding abilities of dissolved organic matter (DOM) rely on its molecular weight (MW) structure. In this study, the spatial differences of DOM in compositions, MW structures, and binding mechanisms with copper (Cu²⁺) in Dongping Lake were investigated by applying excitation-emission matrix combining parallel factor analysis (EEM-PARAFAC), synchronous fluorescence (SF) spectra, two-dimensional correlation spectra (2D-COS), and Fourier transform infrared (FTIR) spectra. The EDOM for the entrance of the Dawen River and PDOM for the macrophyte-dominated region were divided from DOM of Dongping Lake based on hierarchical clustering analysis (HCA) and principal component analysis (PCA) and were size-fractioned into MW < 500 kDa and <100 kDa fractions. According to EEM-PARAFAC, Dongping Lake was dominated by tryptophan-like substances with MW < 500 kDa. The concentration of PDOM was higher than that of EDOM (p < 0.05). 2D-COS showed that protein-like components preceded humic-like components binding to Cu²⁺ regardless of sample type (215 nm > 285 nm > 310–360 nm). The Cu²⁺ binding capacity of DOM exhibited specific differences in space, components, and molecular weights. The humic-like component 1 (C1) and tryptophan-like component 4 (C4) of PDOM showed stronger binding abilities than those of EDOM. Endogenous tryptophan-like component 4 (C4) had a higher binding affinity for Cu²⁺ than humic-like components (logKₐ: C4 > C1 > C2) in PDOM irrespective of MW. Humic-like components with MW < 500 kDa displayed higher binding potentials for Cu²⁺. FTIR spectra showed that the main participants of DOM-Cu complexation included aromatic hydrocarbons, aliphatic groups, amide Ⅰ bands, and carboxyl functional groups. This study provides spatial-scale insights into the molecular weight structure of DOM in influencing the behavior, fate, and bioavailability of heavy metals in lakes.

Copper has become one of the most important heavy metal pollutants in the environment because of its wide application and high toxicity, but research on water quality criteria (WQCs) on copper is limited, especially the derivation of seawater WQC. In addition, the toxicity of copper in the seawater system is affected by various environmental factors. Therefore, establishing a WQC that meets the characteristics of the regional environment is a top priority. The correlations between four factors of temperature, salinity, pH, dissolved organic carbon (DOC) and the toxic effect values of copper were analyzed in this study, and the temperature was determined as the most influential factor among the four factors in the Bohai Sea. A specific correlation between temperature and the toxic effects of copper was identified, and WQCs were derived based on the identified correlation and the variations of the Bohai Sea's temperature in different seasons by species sensitivity distribution (SSD) method. Under the condition of the winter, spring, autumn, and summer with an average water temperature of 0.09, 15.96, 17.83, and 24.87 °C, the obtained short-term water quality criteria (SWQCs) were 44.29, 4.70, 4.31, and 3.33 μg/L; the long-term water quality criteria (LWQCs) were 18.14, 1.93, 1.77 and 1.36 μg/L. The findings indicated the importance of introducing specific environmental conditions during the derivation process. This work could provide valuable information for pollution prevention and aquatic life protection in the Bohai Sea and provide a valuable reference for the derivation of criteria in other regions alike.