Division of Geosciences and Environmental Engineering, Luleå University of Technology, SE-971 87 Luleå, Sweden.
Sci Total Environ. 2011 Oct 1;409(21):4585-95. doi: 10.1016/j.scitotenv.2011.07.024. Epub 2011 Aug 3.
This paper presents a biogeochemical model developed for a clarification pond receiving ammonium nitrogen rich discharge water from the Boliden concentration plant located in northern Sweden. Present knowledge about nitrogen (N) transformations in lakes is compiled in a dynamic model that calculates concentrations of the six N species (state variables) ammonium-N (N(am)), nitrate-N (N(ox)), dissolved organic N in water (N(org)), N in phytoplankton (N(pp)), in macrophytes (N(mp)) and in sediment (N(sed)). It also simulates the rate of 16 N transformation processes occurring in the water column and sediment as well as water-sediment and water-atmosphere interactions. The model was programmed in the software Powersim using 2008 data, whilst validation was performed using data from 2006 to 2007. The sensitivity analysis showed that the state variables are most sensitive to changes in the coefficients related to the temperature dependence of the transformation processes. A six-year simulation of N(am) showed stable behaviour over time. The calibrated model rendered coefficients of determination (R(2)) of 0.93, 0.79 and 0.86 for N(am), N(ox) and N(org), respectively. Performance measures quantitatively expressing the deviation between modelled and measured data resulted in values close to zero, indicating a stable model structure. The simulated denitrification rate was on average five times higher than the ammonia volatilisation rate and about three times higher than the permanent burial of N(sed) and, hence, the most important process for the permanent removal of N. The model can be used to simulate possible measures to reduce the nitrogen load and, after some modification and recalibration, it can be applied at other mine sites affected by N rich effluents.
本文提出了一个生物地球化学模型,该模型是为一个澄清池开发的,该澄清池接收来自瑞典北部博利登选矿厂富含铵氮的排放水。目前关于湖泊中氮(N)转化的知识被编译到一个动态模型中,该模型计算六种 N 物种(状态变量)的浓度:铵-N(N(am))、硝酸盐-N(N(ox))、水中溶解的有机 N(N(org))、浮游植物中的 N(N(pp))、大型植物中的 N(N(mp))和沉积物中的 N(N(sed))。它还模拟了水柱状和沉积物中以及水-沉积物和水-大气相互作用中发生的 16N 转化过程的速率。该模型使用 2008 年的数据在 Powersim 软件中进行编程,而验证则使用 2006 年至 2007 年的数据进行。敏感性分析表明,状态变量对与转化过程温度依赖性相关的系数变化最敏感。对 N(am)进行的六年模拟显示随时间稳定。经过校准的模型对 N(am)、N(ox)和 N(org)的决定系数(R(2))分别为 0.93、0.79 和 0.86。定量表达模型数据与实测数据之间偏差的性能指标接近零,表明模型结构稳定。模拟的反硝化速率平均比氨挥发速率高五倍,比 N(sed)的永久埋藏率高约三倍,因此是永久去除 N 的最重要过程。该模型可用于模拟减少氮负荷的可能措施,并且经过一些修改和重新校准后,可应用于其他受富氮废水影响的矿山。