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JH
Verified CAS / Academic Author2 Decoded Studies

Prof. JIA Hexue

Hengshui University, Center for Wetland Conservation and Research

Co-Affiliations:Hengshui University, Center for Wetland Conservation and Research, Hengshui, China

Research Publications & English Decoded Briefs

Showing 2 publications
Environmental Chemistry2026DOI: 10.7524/j.issn.0254-6108.2025020603

Screening and Identification of High Cellulase-Producing Strain Bacillus cereus and Optimization of Enzyme Production Conditions

The high cellulase-producing strains were screened and the enzyme production conditions were optimized, providing strain resources for the effective utilization of agricultural solid waste. A promising cellulolytic strain S3 was isolated from the soil of Hengshui Lake Wetland Park. The isolation process employed Congo red plate staining method for primary screening, followed by secondary screening through cellulase activity determination and straw degradation experiments. Through morphological observation and molecular biology identification, the strain S3 was identified to be Bacillus cereus. The ratio of transparent circle to colony diameter of strain S3 was 4.01±0.17. The filter paper enzyme activity of strain S3 was 42.09 U·mL−1, and the degradation rate of corn stover reached 19.29% after 10 days of fermentation. It was found that the optimum carbon source of strain S3 was the mixture of microcrystalline cellulose and wheat bran with the addition amount of 4%, and the optimum nitrogen source was soybean powder with the addition amount of 2%. Single factor experiment and response surface methodology were used to optimize the enzyme production conditions of the strain S3. The optimal conditions were fermentation time of 76 h, fermentation temperature of 36℃, initial pH of 6, and inoculation volume of 4%. Under these conditions, the filter paper enzyme activity reached 60.13 U·mL−1, which was 1.43 times higher than that before optimization. The strain S3 showed the high cellulase-producing capability, demonstrating its potential as an efficient microbial candidate for the degradation and utilization of agricultural solid waste.

Environmental Chemistry2026DOI: 10.7524/j.issn.0254-6108.2026021002

Model-Averaging Species Sensitivity Distribution for Phthalate Esters and Ecological Risk Assessment in Typical Freshwater Basins of China

The construction of species sensitivity distribution (SSD) models using a single function requires optimization to reduce subjectivity. To minimize model selection uncertainty and align with Chinese freshwater organism effect criteria, this study integrated native freshwater species toxicity data, including experimental and predicted values from interspecies correlation estimation (ICE) and acute-chronic ratio (ACR) methods, and applied a model-averaging approach to construct SSD models for seven representative phthalate esters (PAEs): dimethyl phthalate (DMP), diethyl phthalate (DEP), dibutyl phthalate (DnBP), butyl benzyl phthalate (BBP), bis(2-ethylhexyl) phthalate (DEHP), diisodecyl phthalate (DIDP), and dihexyl phthalate (DnHP). The derived short-term predicted no-effect concentrations (PNECacute) for DMP, DEP, DnBP, BBP, DEHP, DIDP, and DnHP were 16.796, 4.984, 9.064×10⁻², 2.490×10⁻¹, 1.898×10⁻², 1.386×10⁻¹, and 7.428×10⁻² μg·L⁻¹, respectively. Long-term PNECs (PNECchronic) were 3.245×10², 36.500, 1.149, 4.018, 8.949×10⁻², 1.637, and 4.073×10⁻¹ μg·L⁻¹, respectively. These PNECs, based on native species toxicity data and more stringent than existing standards, are recommended as potential references for water quality criteria based on Chinese freshwater organism effects. Ecological risk assessment using the hazard quotient (HQ) method on exposure concentrations from typical Chinese freshwater basins revealed that DEHP and DnBP posed high short-term risks, BBP mainly medium risk, while DMP, DEP, and DnHP showed low or no risk. Long-term risks indicated DEHP at medium to high risk, DnBP mainly medium to low, BBP low or no risk, and DMP, DEP, and DnHP no risk. The overall ecological risk ranking was DEHP > DnBP > BBP > DEP > DMP ≈ DnHP.