Battisti Sabrina, Caminiti Antonino, Ciotoli Giancarlo, Panetta Valentina, Rombolà Pasquale, Sala Marcello, Ubaldi Alessandro, Scaramozzino Paola
Geospat Health. 2013 Nov;8(1):77-86. doi: 10.4081/gh.2013.56.
In May 2005, beta-hexachlorocyclohexane (β-HCH) was found in a sample of bovine bulk milk from a farm in the Sacco River valley (Latium region, central Italy). The primary source of contamination was suspected to be industrial discharge into the environment with the Sacco River as the main mean of dispersion. Since then, a surveillance programme on bulk milk of the local farms was carried out by the veterinary services. In order to estimate the spatial probability of β- HCH contamination of milk produced in the Sacco River valley and draw probability maps of contamination, probability maps of β-HCH values in milk were estimated by indicator kriging (IK), a geo-statistical estimator, and traditional logistic regression (LR) combined with a geographical information systems approach. The former technique produces a spatial view of probabilities above a specific threshold at non-sampled locations on the basis of observed values in the area, while LR gives the probabilities in specific locations on the basis of certain environmental predictors, namely the distance from the river, the distance from the pollution site, the elevation above the river level and the intrinsic vulnerability of hydro-geological formations. Based on the β-HCH data from 2005 in the Sacco River valley, the two techniques resulted in similar maps of high risk of milk contamination. However, unlike the IK method, the LR model was capable of estimating coefficients that could be used in case of future pollution episodes. The approach presented produces probability maps and define high-risk areas already in the early stages of an emergency before sampling operations have been carried out.
2005年5月，在意大利中部拉齐奥地区萨科河谷一个农场的牛群散装牛奶样本中发现了β-六氯环己烷（β-HCH）。污染的主要来源被怀疑是工业排放到环境中，萨科河是主要的扩散途径。从那时起，兽医服务部门对当地农场的散装牛奶开展了一项监测计划。为了估计萨科河谷生产的牛奶受β-HCH污染的空间概率并绘制污染概率图，通过指示克里金法（IK，一种地质统计学估计方法）以及传统逻辑回归（LR）并结合地理信息系统方法，估计了牛奶中β-HCH值的概率图。前一种技术基于该地区的观测值，给出了非采样地点高于特定阈值的概率的空间视图，而LR则根据某些环境预测因子，即距河流的距离、距污染地点的距离、河流水位以上的海拔高度以及水文地质层的固有脆弱性，给出特定地点的概率。根据2005年萨科河谷的β-HCH数据，这两种技术得出了类似的牛奶污染高风险地图。然而，与IK方法不同，LR模型能够估计在未来污染事件发生时可使用的系数。所提出的方法在尚未开展采样作业的紧急情况早期阶段就能生成概率图并确定高风险区域。
