High biochemical oxygen demand (BOD) concentrations in water minimize oxygen availability, damage ecosystem biodiversity, impair water quality, and spoil freshwater. The increased level of BOD is an indication of severe organic pollution of freshwater. Thus, this study aims to establish empirical correlations between the 5-day biochemical oxygen demand (BOD₅) and organic decomposition time to control organic pollution in various wastewater effluents. Ultimate biochemical oxygen demand (UBOD) and minimum and average BOD_t data sets along with their reaction rates were collected from earlier sampling analyses in the plants used for industrial, domestic (sanitary), and storm (surface) wastewater treatment. Average BOD₅/COD ratios were then utilized to calculate existing 5-day dissolved oxygen (DO₅) concentration for the estimation of experimental dilution factors (dfs) as a good start in sampling analysis to reach an optimum DO₅ concentration. Moreover, the relationships between average BOD₅ vs. COD, and BOD₅ vs. DO₅, were obtained based on the literature with 60–70% oxygen consumption rates required for organic decomposition. Results showed that such BOD₅ relationships with time (power equations) or with COD (linear correlations) are helpful for wastewater engineers to generate valuable and accurate results for quality control, without the need to conduct laboratory experiments. The proposed regression equations would facilitate effluent quality assessment, allowing selection of optimal processes to control microbiological contamination or organic constituents in wastewaters.

中文翻译：

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预测 BOD 采样的最佳稀释因子和所需溶解氧以控制各种废水中的有机污染

水中的高生化需氧量 (BOD) 浓度会最大限度地减少氧气的可用性，破坏生态系统的生物多样性，损害水质并破坏淡水。BOD 水平升高表明淡水存在严重的有机污染。因此，本研究旨在建立 5 天生化需氧量 (BOD ₅ ) 与有机物分解时间之间的经验相关性，以控制各种废水流出物中的有机物污染。最终生化需氧量 (UBOD) 和最小和平均 BOD _t数据集及其反应速率是从用于工业、生活（卫生）和暴雨（地表）废水处理的工厂的早期采样分析中收集的。平均BOD ₅然后使用 /COD 比率来计算现有的 5 天溶解氧 (DO ₅ ) 浓度，以估计实验稀释因子 (dfs) 作为采样分析的良好开端，以达到最佳 DO ₅浓度。此外，平均BOD ₅与COD 和BOD ₅与DO ₅之间的关系是根据文献获得的，有机分解所需的氧气消耗率为60-70%。结果表明，这样的 BOD ₅与时间（功率方程）或与 COD（线性相关）的关系有助于废水工程师生成有价值且准确的质量控制结果，而无需进行实验室实验。所提出的回归方程将有助于废水质量评估，允许选择最佳工艺来控制废水中的微生物污染或有机成分。