本文提出了一种整合三个方面的方法 用于评估颗粒活性炭（GAC）在水处理过程中的性能的工具，以便以最小的成本和精力从中获得最大的效益。它们包括数学模型、台架试验和中试柱试验。这 在亚利桑那州斯科茨代尔市进行的一项为期12个月的研究中采用了这种方法 为拟建的30 mgd地表水处理厂制定GAC设计标准。 甲基异龙脑（MIB）和DBP前体去除是GAC的主要处理方法 客观的试验台和中试规模试验以及计算机建模一起使用 跟随: 进行快速小规模柱试验（RSSCT），以确定基线中试试验条件和不同的GAC 对类型（沥青和褐煤）和品牌进行筛选，以选择GAC作为试点 空床接触时间（EBCT）和水力负荷的研究、中试条件 根据RSSCT结果选择比率（HLR）； 在为期6个月的试验中，对沥青和褐煤GAC（有臭氧和无臭氧）进行了测试 确定GAC性能的试点研究，用于季节性气候变化的全面应用 水质变化和生物降解； 进行模拟分配系统（SDS）测试，以确定季节性TOC 基于TTHM和HAA5形成的出水目标； 进行回归分析，以使一般逻辑函数模型与 该数学模型用于评估一系列设计 测试条件两侧的参数，以找到成本最低的设计。包括7个参考文献、图表。

This paper presents a methodology for integrating three tools for evaluating the performance of granular activated carbon (GAC) in the water treatment process in order to obtain the maximum benefit from each with the least cost and effort. They include mathematical models, bench-scale tests, and pilot column tests. This approach was applied in a 12-month study conducted for the City of Scottsdale, Arizona to develop GAC design criteria for a proposed 30-mgd surface water treatment plant. Methylisoborneol (MIB) and DBP precursor removal were the primary GAC treatment objective. Bench- and pilot-scale testing and computer modeling were used together as follows: rapid small-scale column tests (RSSCTs) were conducted to establish baseline pilot testing conditions and different GAC types (bituminous and lignite), and brands, were screened to select GACs for the pilot study, pilot test conditions for empty bed contact time (EBCT) and hydraulic loading rates (HLR) were selected based on RSSCT results; both bituminous and lignite GACs were tested (with and without ozone) in a 6-month pilot study to determine GAC performance for full-scale application with seasonal water quality changes and biodegradation; simulated distribution system (SDS) tests were conducted to establish seasonal TOC effluent targets based on TTHM and HAA5 formation; regression analyses were performed to fit the General Logistic Function model to the pilot-column data, and this mathematical model was used to evaluate a range of design parameters on either side of the test conditions to find the least cost design. Includes 7 references, figures.