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ZG
Verified CAS / Academic Author2 Decoded Studies

Prof. ZHANG Guangming

State Key Laboratory of Efficient Utilization of Agricultural Water Resources, China Agricultural University, Beijing 100083, China

Co-Affiliations:Tianjin Research Institute for Water Transport Engineering, Ministry of Transport, Tianjin 300456, China; School of Energy and Environmental Engineering, Hebei University of Technology, Tianjin 300401, China

Research Publications & English Decoded Briefs

Showing 2 publications
Chinese Journal of Environmental Engineering2026DOI: 10.12030/j.cjee.202511051

Mechanistic Study on Photosynthetic Bacteria Granulation under Synergistic Hydraulic and Organic Loading

Photosynthetic bacteria (PSB) wastewater treatment technology is promising for simultaneous pollutant removal and resource recovery (e.g., single-cell protein, hydrogen). However, poor cell hydrophobicity and aggregation lead to low biomass retention and short sludge retention time, hindering engineering application. This study investigated the driving role and mechanism of upflow velocity as a key hydraulic selection pressure on PSB granulation under stepwise increasing organic loading rate (OLR). In laboratory up-flow photobioreactors (UPBR), comparative experiments were conducted with macro-index monitoring and micro-mechanism analysis. Results showed that under high upflow velocities of 3.00–6.30 m·h−1, PSB granular sludge with an average diameter of 285.58 μm and excellent settleability (sludge volume index, SVI = 22.73 mL·g−1) was successfully formed within approximately 60 days. Compared to the control, the granules in the experimental group were larger, with clear boundaries and compact structure, and significant enrichment of filamentous bacteria was observed. Mechanism analysis indicated that OLR provided nutritional driving force for microbial growth, while upflow velocity supplied high hydraulic shear force, physically screening and enriching settleable aggregates, and specifically inducing secretion of hydrophobic tryptophan-like proteins and humic acids (key extracellular polymeric substances, EPS). Additionally, core genera such as Xanthobacteraceae, possessing stress tolerance and EPS secretion functions, were enriched. This study reveals a chain mechanism of 'physical selection–biological response' centered on hydraulic selection, demonstrating that upflow velocity is a key controllable factor for PSB granulation, providing theoretical basis and technical pathway for solving PSB biomass washout and promoting resource-oriented treatment of high-strength organic wastewater.

Chinese Journal of Environmental Engineering2026DOI: 10.12030/j.cjee.202509072

Precision Source Parameter Inversion for Typical Air Pollutant Emissions at Microscale: An Integrated PSO-NM Algorithm and Gaussian Dispersion Model Approach

Accurate identification of pollutant emission source parameters is critical for effective pollution response. This study evaluates the performance of genetic algorithm (GA), Nelder-Mead simplex (NM), particle swarm optimization (PSO), and their coupled variants on multi-dimensional, multi-extremum benchmark functions, and develops a source parameter inversion technique integrating PSO-NM with a Gaussian dispersion model. Validation via sulfur hexafluoride (SF6) single-point and multi-point release experiments demonstrates that PSO-NM achieves mean values closest to theoretical optima on Shubert, Hartmann, and Shekel functions, with superior stability and precision. In single-point source experiments, the relative deviation of source strength (Q) inversion ranges from -27.1% to 38.5%, with positional errors below 10 m, indicating robust convergence and repeatability. Multi-point source inversion exhibits stability across two scenarios but with reduced accuracy compared to single-point cases. When source strength is unknown, inversion accuracy for low-release sources (relative deviation 37.3%-70.4%) surpasses that for high-release sources; when position is unknown, positional deviations generally remain below 50 m, with low-release sources yielding better x0 deviations (-1.6 to 8.2 m) but slightly worse y0, z0, and distance parameters. Inversion errors primarily stem from meteorological non-stationarity, inter-source interference, algorithmic local optima, low-concentration measurement noise, and model assumptions. Future improvements may incorporate real-time meteorological correction and source-specific constraints to enhance accuracy and robustness in complex scenarios. The findings provide technical support for precise source tracing, monitoring, and refined management of pollutant emissions at microscale in industrial parks and enterprises.