This paper presents a comprehensive and critical analysis of the removal of pharmaceuticals (PhCs), the governing physicochemical properties, and removal mechanisms in constructed wetlands (CWs). The average removal efficiency of the most widely studied 34 PhCs ranges from 21% to 93%, with the exception of one PhC that exhibited negative removal. Moreover, CWs are effective in significantly reducing the environmental risk caused by many PhCs. Based on risk assessment, 12 PhCs were classified under high risk category (oxytetracycline > ofloxacin > sulfamethoxazole > erythromycin > sulfadiazine > gemfibrozil > ibuprofen > acetaminophen > salicylic acid > sulfamethazine > naproxen > clarithromycin), which could be considered for regular monitoring, water quality standard formulation and control purposes. Biodegradation (aerobic and anaerobic) is responsible for the removal of the majority of PhCs, often in conjunction with other mechanisms (e.g., adsorption/sorption, plant uptake, and photodegradation). The physicochemical properties of molecules play a pivotal role in the elimination processes, and could serve as important predictors of removal. The correlation and multiple linear regression analysis suggest that organic carbon sorption coefficient (Log Koc), octanol-water distribution coefficient (Log Dow), and molecular weight form a good predictive linear regression model for the removal efficiency of PhCs (R² = 0.65, P-value <0.05).

本文介绍了对人工去除湿地（CW）中的药物（PhC），控制理化性质以及去除机理的全面而严格的分析。研究最广泛的34种PhC的平均去除效率在21％到93％之间，只有一种具有负去除效果的PhC除外。此外，化武能有效地减少许多药业造成的环境风险。根据风险评估，将12种药分类为高风险类别（土霉素，氧氟沙星>磺胺甲恶唑>红霉素>磺胺嘧啶>吉非贝齐>布洛芬>对乙酰氨基酚>水杨酸>磺胺二甲嘧啶>萘普生>克拉霉素）标准制定和控制目的。生物降解（好氧和厌氧）通常与其他机制（例如，吸附/吸收，植物吸收和光降解）共同导致大部分PhC的去除。分子的物理化学性质在消除过程中起着关键作用，并且可以作为重要的去除预测指标。相关性和多元线性回归分析表明，有机碳吸附系数（Log Koc），辛醇-水分配系数（Log Dow）和分子量构成了对PhCs去除效率的良好预测线性回归模型（R 分子的物理化学性质在消除过程中起着关键作用，并且可以作为重要的去除预测指标。相关性和多元线性回归分析表明，有机碳吸附系数（Log Koc），辛醇-水分配系数（Log Dow）和分子量构成了对PhCs去除效率的良好预测线性回归模型（R 分子的物理化学性质在消除过程中起着关键作用，并且可以作为重要的去除预测指标。相关性和多元线性回归分析表明，有机碳吸附系数（Log Koc），辛醇-水分配系数（Log Dow）和分子量构成了对PhCs去除效率的良好预测线性回归模型（R² = 0.65，P值<0.05）。