Park Daeryong, Park Byungtae, Mendinsky Justin J, Paksuchon Benjaphon, Suhataikul Ratda, Dempsey Brian A, Cho Yunchul
Department of Civil and Environmental System Engineering, 120 Neungdong-ro, Gwangjin-gu, Seoul, 143-701, Republic of Korea.
Environ Monit Assess. 2015 Jan;187(1):4095. doi: 10.1007/s10661-014-4095-9. Epub 2014 Nov 16.
Eighteen sites impacted by abandoned mine drainage (AMD) in Pennsylvania were sampled and measured for pH, acidity, alkalinity, metal ions, and sulfate. This study compared the accuracy of four acidity calculation methods with measured hot peroxide acidity and identified the most accurate calculation method for each site as a function of pH and sulfate concentration. Method E1 was the sum of proton and acidity based on total metal concentrations; method E2 added alkalinity; method E3 also accounted for aluminum speciation and temperature effects; and method E4 accounted for sulfate speciation. To evaluate errors between measured and predicted acidity, the Nash-Sutcliffe efficiency (NSE), the coefficient of determination (R (2)), and the root mean square error to standard deviation ratio (RSR) methods were applied. The error evaluation results show that E1, E2, E3, and E4 sites were most accurate at 0, 9, 4, and 5 of the sites, respectively. Sites where E2 was most accurate had pH greater than 4.0 and less than 400 mg/L of sulfate. Sites where E3 was most accurate had pH greater than 4.0 and sulfate greater than 400 mg/L with two exceptions. Sites where E4 was most accurate had pH less than 4.0 and more than 400 mg/L sulfate with one exception. The results indicate that acidity in AMD-affected streams can be accurately predicted by using pH, alkalinity, sulfate, Fe(II), Mn(II), and Al(III) concentrations in one or more of the identified equations, and that the appropriate equation for prediction can be selected based on pH and sulfate concentration.
对宾夕法尼亚州18个受废弃矿井排水(AMD)影响的地点进行了采样,并测量了其pH值、酸度、碱度、金属离子和硫酸盐含量。本研究将四种酸度计算方法的准确性与实测热过氧化物酸度进行了比较,并根据pH值和硫酸盐浓度确定了每个地点最准确的计算方法。方法E1是基于总金属浓度的质子和酸度之和;方法E2增加了碱度;方法E3还考虑了铝的形态和温度影响;方法E4考虑了硫酸盐的形态。为了评估实测酸度与预测酸度之间的误差,应用了纳什-萨特克利夫效率(NSE)、决定系数(R²)和均方根误差与标准差之比(RSR)方法。误差评估结果表明,E1、E2、E3和E4方法分别在0个、9个、4个和5个地点最为准确。E2方法最准确的地点pH值大于4.0且硫酸盐含量小于400mg/L。E3方法最准确的地点pH值大于4.0且硫酸盐含量大于400mg/L,但有两个例外。E4方法最准确的地点pH值小于4.0且硫酸盐含量大于400mg/L,但有一个例外。结果表明,利用一个或多个已确定方程中的pH值、碱度、硫酸盐、Fe(II)、Mn(II)和Al(III)浓度,可以准确预测受AMD影响溪流中的酸度,并且可以根据pH值和硫酸盐浓度选择合适的预测方程。