Programa de Pós-Graduação em Qualidade Ambiental, Universidade FEEVALE, RS 239, 2755, CEP 93352-000, Novo Hamburgo, RS, Brazil.
Instituto de Botânica, Caixa Postal 68041, 04045-972, São Paulo, Brazil.
Environ Pollut. 2019 May;248:471-477. doi: 10.1016/j.envpol.2019.01.130. Epub 2019 Feb 1.
Air pollution has been identified as a major cause of environmental and human health damage. O is an oxidative pollutant that causes leaf symptoms in sensitive plants. This study aims to adjust a multilinear model for the monitoring of O in subtropical climatic conditions by associating O concentrations with measurements of morphological leaf traits in tobacco plants and different environmental variables. The plants were distributed into five areas (residential, urban or industrial) in the southern region of Brazil and exposed during 14 periods, of 14 days each, during the years of 2014 and 2015. The environmental variables and leaf traits during the exposure periods were described by mean, median, standard deviation and minimum and maximum values. Spearman correlation and multiple linear regression analyses were applied on data from exposure periods. Leaf injury index, leaf area, leaf dry mass, temperature, relative humidity, global solar radiation and accumulated rainfall were used in the regression analyses to select the best models for predicting O concentrations. Leaf injury characteristically caused by O was verified in all areas and periods of plant exposure. Higher values of leaf injury (24.5% and 27.7%) were registered in the 13th and 12th exposure periods during spring and in areas influenced by urban and industrial clutches. The VPD, temperature, global solar radiation and O were correlated to leaf injury. Environmental variables [leaf area, leaf dry mass, global solar radiation and accumulated rainfall] and primarily the VPD were fundamental to improve the adjustments done in the bioindicator model (R ≥ 0.73). Our research shows that biomonitoring employing the tobacco "Bel-W3" can be improved by measuring morphological leaf traits and meteorological parameters. Additionally, O fumigation experiment should be performed with biomonitoring as conducted in this study, which are useful in understanding the role of other environmental factors.
空气污染已被确定为环境和人类健康损害的主要原因。O 是一种氧化污染物,会导致敏感植物出现叶片症状。本研究旨在通过将 O 浓度与烟草植物的形态叶片特征测量值和不同环境变量相关联,调整用于亚热带气候条件下 O 监测的多线性模型。这些植物分布在巴西南部的五个地区(居民区、城市或工业区),在 2014 年和 2015 年期间,每个地区暴露于 14 天的 14 个时期。在暴露期间,环境变量和叶片特征用平均值、中位数、标准差和最小值和最大值来描述。对暴露期间的数据进行 Spearman 相关性和多元线性回归分析。在回归分析中,使用叶片伤害指数、叶面积、叶片干质量、温度、相对湿度、总太阳辐射和累积降雨量来选择预测 O 浓度的最佳模型。所有地区和植物暴露时期都出现了典型的 O 引起的叶片伤害。叶片伤害在春季的第 13 次和第 12 次暴露期以及受城市和工业团簇影响的地区记录值较高(24.5%和 27.7%)。VPD、温度、总太阳辐射和 O 与叶片伤害相关。环境变量[叶面积、叶片干质量、总太阳辐射和累积降雨量]和主要是 VPD 对于改进生物指示剂模型的调整至关重要(R≥0.73)。我们的研究表明,通过测量形态叶片特征和气象参数,可以改进使用烟草“Bel-W3”进行的生物监测。此外,如本研究中进行的生物监测那样,应进行 O 熏气实验,这对于理解其他环境因素的作用很有用。