Ferretti Marco, Andrei Sara, Caldini Gabriella, Grechi Daniele, Mazzali Cristina, Galanti Emilio, Pellegrini Marco
Linnaeambiente Ricerca Applicata Srl, Via G. Sirtori 37, I-50137 Firenze, Italy.
Sci Total Environ. 2008 Jun 25;396(2-3):180-92. doi: 10.1016/j.scitotenv.2008.02.019. Epub 2008 Apr 2.
Prior to 2000 a network of conventional ozone (O3) analysers existed in the Province of Firenze (Tuscany, central Italy). Between 2000 and 2004 the network was extended to incorporate a newly designed bioindicator network of tobacco plants (Nicotiana tabacum Bel W3). The objective was to set-up an integrated monitoring system to obtain estimates of ground-level O3 concentrations over the whole study area (3513 km2) in order to fill data gaps and cover reporting requirements. The existing conventional monitors were purposefully located mainly in urban areas. A total of 45 biomonitoring sites were selected using a systematic design to cover the target area. Two to five additional biomonitoring sites were co-located with conventional O3 analysers for calibration purposes, and five more sites for independent validation of modelled O3 concentrations. Visible Leaf Injury Index (LII) on the tobacco plants was significantly correlated (P: 0.018/0.0014) with a series of O3 exposure variables (mean of weekly 1-hour maxima, M1; mean of 7-hour means, M7; 24-hour mean, M24; and weekly AOT40). LII was found to be a significant predictor of weekly means of the O3 exposure variables with a standard error of estimates between 13.6 and 24.3 microg m(-3) (absolute values). LII was mapped with an ad-hoc spatial model over the study area at a 22 km grid resolution, and mapped values were used to predict O3 concentrations by means of a first order linear model. Results showed that high estimates of O3 (up to 188 microg m(-3) as mean of weekly maxima, M1) occurred more frequently in hilly and mountainous areas, with a spatial pattern changing on an annual basis. Predicted O3 concentrations were not significantly different from the measured concentrations (P: 0.34), although marked differences were observed for individual sites and years. The study provided evidence that integration of monitoring networks using different methods can be a viable option to obtain estimates of O3 concentrations over large areas.
2000年以前,佛罗伦萨省(意大利中部托斯卡纳)存在一个传统臭氧(O₃)分析仪网络。在2000年至2004年期间,该网络进行了扩展,纳入了一个新设计的烟草植物(烟草品种Bel W3)生物指示物网络。目的是建立一个综合监测系统,以获取整个研究区域(3513平方公里)地面臭氧浓度的估计值,以填补数据空白并满足报告要求。现有的传统监测仪主要有意设置在城市地区。使用系统设计选择了总共45个生物监测站点以覆盖目标区域。为了校准目的,另外两到五个生物监测站点与传统臭氧分析仪共址,还有五个站点用于对模拟臭氧浓度进行独立验证。烟草植物上的可见叶损伤指数(LII)与一系列臭氧暴露变量(每周1小时最大值的平均值,M1;7小时平均值的平均值,M7;24小时平均值,M24;以及每周累积光化学臭氧暴露量,AOT40)显著相关(P值分别为0.018/0.0014)。发现LII是臭氧暴露变量每周平均值的显著预测指标,估计标准误差在13.6至24.3微克 立方米⁻³(绝对值)之间。利用一个专门的空间模型在研究区域以22公里的网格分辨率绘制了LII图,并通过一阶线性模型使用绘制值来预测臭氧浓度。结果表明,臭氧的高估计值(每周最大值的平均值,M1,高达188微克 立方米⁻³)在丘陵和山区更频繁出现,且空间格局每年都在变化。预测的臭氧浓度与测量浓度没有显著差异(P值为0.34),尽管个别站点和年份存在明显差异。该研究提供了证据,表明使用不同方法整合监测网络可以是获取大面积臭氧浓度估计值的可行选择。