Insights into leaded gasoline registered in mud depocenters derived from multivariate statistical tool: southeastern Brazilian coast.

Lead has been widely used since antiquity, but its uses drastically increased during the Industrial Revolution. The global emission of Pb into the environment was mainly due to tetraethyl lead added to gasoline as an antiknock additive. Because of its toxicity and neurological effects, the compound was phased out in the 1980s. Isotopic signatures are widely applied to differentiate sources of Pb; however, this is an expensive and sophisticated analysis compared to elemental analysis. Thus, this study aims to gain insight into leaded gasoline registered in mud depocenters from the southeastern Brazilian coast using multivariate statistical tools on elemental analysis data of trace elements. Seven multiple cores were collected on board the Research Vessel Alpha Crucis. Al, As, Ba, Ca, Cd, Cr, Cu, Fe, K, Mg, Mn, Ni, P, Pb, Sc, Sr, V and Zn were analyzed by acid digestion and quantified by ICP-OES. Levels and enrichment factors of Pb resulted in homogeneous columns, indicating that small variations in concentrations can be attributed to grain size differences, not presenting contaminated levels. From statistical results, the highest contribution on the first component was represented by a lithogenic source with the leaching of continental rocks. Lead content was notable in its high loadings in other components, which suggests atmospheric deposition. An increase in these components in subsurface samples from vertical profiles between 1935 and 1996 could represent a fingerprint of the consumption of leaded gasoline in Brazil between 1923 and 1989. Thus, statistical analysis of elemental data enabled to infer possible sources and pathways of Pb to the environment, without isotopic analysis.

Critical evaluation of different methods to calculate the Geoaccumulation Index for environmental studies: A new approach for Baixada Santista - Southeastern Brazil.

Although the Igeo is widely used in heavy metal contamination studies, its application differs in each study in terms of the mathematical equation used, the chosen background, and whether the fine fraction or whole sediment matrix is used. This study aims to assess these different methods, propose a new equation to calculate this index and use the index to evaluate the environmental quality of Baixada Santista. The levels of heavy metals were quantified in fifty sediment samples using both in the whole sediment sample and only in the fine fraction. The index was calculated in both fractions and in the normalized levels. Using the fine fraction of the sample was more suitable to the classification. The ratio of the levels in the whole sediment to the fine content did not present a significant statistical difference compared to the levels obtained from the fine fraction. Based on this study, a new equation is proposed for use in future environmental studies.

Use of a chemometric tool to establish the regional background and assess trace metal enrichment at Baixada Santista - southeastern Brazil.

The trace metals in sediments consist of two components, anthropogenic and lithogenic or natural, which can cause misinterpretations for what actually exists in sediments. Normally, to investigate trace metal background levels, indices are applied in order to normalize the values and reduce natural variability, but it is well known that using the average shale or crust content is not the best choice and vertical sediment profiles are not always available. The purpose of this study is to use a prediction interval to assess metal enrichment without a reference level and to assess a regional background level using the same tool. The levels of eight elements were submitted to a partial digestion technique and analyzed by ICP-OES. The enrichment factor results suggested that using background values from the prediction interval and using values from vertical sediment profiles yield statistically similar results. Furthermore, the background equations present more realistic data than other methods because they consider the mud content of the samples. Thus, a prediction interval can be a useful tool to establish a regional background and assess trace metal enrichment.