Politecnico di Milano, Dipartimento di Ingegneria Idraulica, Ambientale, Infrastrutture Viarie e Rilevamento, Piazza L. Da Vinci, 32-20133 Milano, Italy.
Sci Total Environ. 2012 May 15;425:9-19. doi: 10.1016/j.scitotenv.2012.03.015. Epub 2012 Apr 5.
We analyze natural background levels (NBLs) and threshold values (TVs) of spatially distributed chemical species (NH(4), B and As) which may be a potential pressure and concern in three large scale alluvial and fluvio-deltaic aquifers at different depths of the Apennines and Po river plains in Emilia-Romagna, Northern Italy. Our results are based on statistical methodologies designed to separate the natural and anthropogenic contributions in monitored concentrations by modeling the empirical distribution of the detected concentration with a mixture of probability density functions. Available chemical observations are taken over a 20 years period and are associated with different depths and cover planar investigation scales of the order of hundreds of kilometers. High concentration values detected for NH(4) and B appear to be related to high natural background levels. Due to interaction with the host rock in different geochemical environments we observed that concentration vary in time and space (including in depth) consistently with the hydrogeochemical features and the occurrence of natural attenuation mechanisms in the analyzed reservoirs. Conversely, estimated As NBLs are not consistent with the conceptual model of the hydrogeochemical behavior of the systems analyzed and experimental evidences of As content in aquifer cores. This is due to the inability of these techniques to incorporate the complex dynamics of the processes associated with the specific hydrogeochemical setting. Statistical analyses performed upon aggregating the concentration data according to different time observation windows allow identifying temporal dynamics of NBLs and TVs of target compounds within the observation time frame. Our results highlight the benefit of a dynamic monitoring process and analysis of well demarcated groundwater bodies to update the associated NBLs as a function of the temporal dependence of natural processes occurring in the subsurface. Monitoring protocols could also include the detailed evaluation of the geochemistry (redox) of the aquifers.
我们分析了空间分布的化学物质（NH(4)、B 和 As）的自然背景水平（NBL）和阈值（TV），这些物质可能是意大利北部艾米利亚-罗马涅地区阿彭尼恩山脉和波河平原三个大型冲积和河流三角洲含水层在不同深度下的潜在压力和关注点。我们的结果基于统计方法，旨在通过用概率密度函数混合物对检测到的浓度的经验分布进行建模，从而分离监测浓度中的自然和人为贡献。可用的化学观测值是在 20 年的时间内获得的，并与不同的深度和数百公里的平面调查范围相关联。检测到的 NH(4)和 B 的高浓度值似乎与高自然背景水平有关。由于在不同地球化学环境中与母岩相互作用，我们观察到浓度随时间和空间（包括深度）变化，与分析储层中的水文地球化学特征和自然衰减机制的发生一致。相反，估计的 As NBL 与所分析系统的水文地球化学行为的概念模型以及含水层岩芯中 As 含量的实验证据不一致。这是由于这些技术无法纳入与特定水文地球化学环境相关的过程的复杂动力学。根据不同的时间观测窗口对浓度数据进行聚合的统计分析允许在观测时间范围内识别目标化合物的 NBL 和 TV 的时间动态。我们的结果强调了动态监测过程和对明确界定的地下水体进行分析的好处，以便根据地下发生的自然过程的时间依赖性更新相关的 NBL。监测协议还可以包括对含水层地球化学（氧化还原）的详细评估。
