Integrated compensatory responses of physiological systems towards homeostasis are generally overlooked when it comes to analysing alterations in biochemical parameters indicative of such processes. Here an hypothesis-driven multivariate analysis accounting for interactive multibiomarker responses was used to investigate effects of long-term exposure of Carcinus maenas to Hazardous and Noxious Substances (HNS). Adult male crabs were exposed to low and high post-spill levels of acrylonitrile (ACN) or aniline (ANL) for 21d. Bioaccumulation, feeding behaviour, and biomarkers related to mode-of-action (MoA) (detoxification, neurotransmission and energy production) were evaluated over time. Distinct temporal patterns of response to low and high exposure concentrations were depicted, with a main set of interactive multibiomarker predictors identified for each HNS (five for ACN and three for ANL), useful to follow coupled evolvement of biomarker responses. ACN caused peripheral neurotoxic effects coupled with enhanced biotransformation and significant oxidative damage particularly relevant in gills. ANL elicited alterations in central neurotransmission affecting ventilation coupled with very low levels of oxidative damage in gills. Results indicate chronic toxicity data are determinant to improve HNS hazard assessment if the aim is to obtain reliable risk calculations, and develop effective predictive models avoiding overestimation but sufficiently protective. Accounting for multibiomarker interactions brought otherwise overlooked information about C. maenas responses and MoA of ACN and ANL.

Benzene series (BTEX) pollutants which are generated by traffic can deposit (build-up) on urban road surfaces. When they are washed-off by stormwater runoff, BTEX are toxic to ecological and human health if the stormwater is reused. To understand the risk posed by BTEX, it is essential to have an in-depth investigation on BTEX build-up, one of the most important stormwater pollutant processes. This study analysed the relationship between BTEX build-up and BTEX build-up's influential factors. The outcomes confirmed an important role of climatic factors (particularly temperature) on influencing BTEX build-up. This has not been considered in previous stormwater studies although this has been widely focused in atmospheric pollution. BTEX build-up loads were generally higher and the variability was low in dry seasons with low temperature such as winter and spring. Additionally, the influence of temperature on BTEX build-up on urban road surfaces is more important in the case of larger particles (such as >75 μm) than smaller particles. The study also showed that petrol station areas have a potential to export stormwater runoff with high BTEX concentrations, compared to typical urban roads. This is particularly applicable in winter and spring. These outcomes can provide useful guidance to improving stormwater quality modelling approaches, especially relevant to estimation of BTEX concentrations in the stormwater.

Multi-elemental isotopic approach associated with a land-use characteristic sampling strategy may be relevant for conducting biomonitoring studies to determine the spatial extent of atmospheric contamination sources. In this work, we investigated how the combined isotopic signatures in epiphytic lichens of two major metallic pollutants, lead (²⁰⁶Pb/²⁰⁷Pb) and mercury (δ²⁰²Hg, Δ¹⁹⁹Hg), together with the isotopic composition of nitrogen and carbon (δ¹⁵N, δ¹³C), can be used to better constrain atmospheric contamination inputs. To this end, an intensive and integrated sampling strategy based on land-use characteristics (Geographic information system, GIS) over a meso-scale area (Pyrénées-Atlantiques, SW France) was applied to more than 90 sampling stations. To depict potential relationships between such multi-elemental isotopic fingerprint and land-use characteristics, multivariate analysis was carried out. Combined Pb and Hg isotopic signatures resolved spatially the contribution of background atmospheric inputs from long range transport, from local legacy contamination (i.e. Pb) or actual industrial inputs (i.e. Pb and Hg from steel industry). Application of clustering multivariate analysis to all studied isotopes provided a new assessment of the region in accordance with the land-use characteristics and anthropogenic pressures.

The United States Environmental Protection Agency (USEPA) completed nationwide screening of six perfluoroalkyl substances in U.S. drinking water from 2013 to 2015 under the Third Unregulated Contaminant Monitoring Rule (UCMR3). UCMR3 efforts yielded a dataset of 36,139 samples containing analytical results from >5000 public water systems (PWSs). This study used UCMR3 data to investigate three aspects of per- and polyfluoroalkyl substances (PFASs) in drinking water: the occurrence of PFAS and co-contaminant mixtures, trends in PFAS detections relative to PWS characteristics and potential release types, and temporal trends in PFAS occurrence. This was achieved through bivariate and multivariate analyses including categorical analysis, concentration ratios, and hierarchical cluster analysis. Approximately 50% of samples with PFAS detections contained ≥2 PFASs, and 72% of detections occurred in groundwater. Large PWSs (>10,000 customers) were 5.6 times more likely than small PWSs (≤10,000 customers) to exhibit PFAS detections; however, when detected, median total PFAS concentrations were higher in small PWSs (0.12 μg/L) than in large (0.053 μg/L). Bivariate and multivariate analyses of PFAS composition suggested PWSs reflect impacts due to firefighting foam use and WWTP effluent as compared to other source types for which data were available. Mann-Kendall analysis of quarterly total PFAS detection rates indicated an increasing trend over time (p = 0.03). UCMR3 data provide a foundation for tiered design of targeted sampling and analysis plans to address remaining knowledge gaps in the sources, composition, and concentrations of PFASs in U.S. drinking water.

The present study aimed to investigate the metabolic response of edible amaranth cultivars to salt stress and the induced rhizosphere effects on Cd mobilization in soil. Two edible amaranth cultivars (Amaranthus mangostanus L.), Quanhong (low-Cd accumulator; LC) and Liuye (high-Cd accumulator; HC), were subject to salinity treatment in both soil and hydroponic cultures. The total amount of mobilized Cd in rhizosphere soil under salinity treatment increased by 2.78-fold in LC cultivar and 4.36-fold in HC cultivar compared with controls, with 51.2% in LC cultivar and 80.5% in HC cultivar being attributed to biological mobilization of salinity. Multivariate statistical analysis generated from metabolite profiles in both rhizosphere soil and root revealed clear discrimination between control and salt treated samples. Tricarboxylic acid cycle in root was up-regulated to cope with salinity treatment, which promoted release of organic acids from root. The increased accumulation of organic acids in rhizosphere under salt stress obviously promoted soil Cd mobility. These results suggested that salinity promoted release of organic acids from root and enhanced soil Cd mobilization and accumulation in edible amaranth cultivar in soil culture.

Despite the abundant literature on the adverse effects of Bisphenol A (BPA) as endocrine disruptor, its toxicity mechanisms are still poorly understood. We present here a study of its effects on the zebrafish eleutheroembryo transcriptome at concentrations ranging from 0.1 to 4 mg L⁻¹, this latter representing the lowest observed effect concentration (LOEC) found in our study at three different macroscopical endpoints (survival, hatching and swim bladder inflation). Multivariate data analysis methods identified both monotonic and bi-phasic patterns of dose-dependent responses. Functional analyses of genes affected by BPA exposure suggest an interaction of BPA with different signaling pathways, being the estrogenic and retinoid receptors two likely targets. In addition, we identified an apparently unrelated inhibitory effect on, among others, visual function genes. We interpret our data as the result of a sum of underlying, independent molecular mechanisms occurring simultaneously at the exposed animals, well below the macroscopic LOEC, but related to at least some of the observed morphological alterations, particularly in eye size and yolk sac resorption. Our data supports the idea that the physiological effects of BPA cannot be only explained by its rather weak interaction with the estrogen receptor, and that multivariate analyses are required to analyze the effects of toxicants like BPA, which interact with different cellular targets producing complex phenotypes.

The Laurentian Great Lakes are a valuable natural resource that is affected by contaminants of emerging concern (CECs), including sex steroid hormones, personal care products, pharmaceuticals, industrial chemicals, and new generation pesticides. However, little is known about the fate and biological effects of CECs in tributaries to the Great Lakes. In the current study, 16 sites on three rivers in the Great Lakes basin (Fox, Cuyahoga, and Raquette Rivers) were assessed for CEC presence using polar organic chemical integrative samplers (POCIS) and grab water samplers. Biological activity was assessed through a combination of in vitro bioassays (focused on estrogenic activity) and in vivo assays with larval fathead minnows. In addition, resident sunfish, largemouth bass, and white suckers were assessed for changes in biological endpoints associated with CEC exposure. CECs were present in all water samples and POCIS extracts. A total of 111 and 97 chemicals were detected in at least one water sample and POCIS extract, respectively. Known estrogenic chemicals were detected in water samples at all 16 sites and in POCIS extracts at 13 sites. Most sites elicited estrogenic activity in bioassays. Ranking sites and rivers based on water chemistry, POCIS chemistry, or total in vitro estrogenicity produced comparable patterns with the Cuyahoga River ranking as most and the Raquette River as least affected by CECs. Changes in biological responses grouped according to physiological processes, and differed between species but not sex. The Fox and Cuyahoga Rivers often had significantly different patterns in biological response Our study supports the need for multiple lines of evidence and provides a framework to assess CEC presence and effects in fish in the Laurentian Great Lakes basin.

This research is designed to determine the level and types of pollution in the highly contaminated sediments of the international Begej canal in Timiş district, Romania and north-eastern Serbia. The cross-border canal stretch investigated is currently not navigable, but represents an important waterway between the Danube River in Serbia and the city of Timisoara. Surface sediments were monitored annually from 2008 to 2016 at 36 representative sampling locations, with a wide range of analyses, including eight heavy metals of long-term monitoring concern (Ni, Zn, Cd, Cr, Cu, Pb, As and Hg) and the 16 USEPA PAHs. The purpose of this study was to determine the diversity and impact of anthropogenic and natural sources of pollution at the pollution hot spots on the canal: at the Itebej lock (near the border with Romania) and downstream at the Klek lock.Sediment quality and ecological risk were assessed in order to determine pollutants of concern. Several multi-proxies were applied (e.g. geo-accumulation index (Igₑₒ), ecological risk index (RI) and total benzo[a]pyrene equivalent (B[a]Pₑq)). To determine and predict trends, multivariate statistical methods (factor analysis of principal component analysis (PCA/FA)) were carried out on the organic and inorganic parameters analysed.In the near-border region, acute and significant ecological impacts were observed. The heavy metals Hg, Cr, Pb, Cu and Zn, and the carcinogenic PAH dibenzo[a,h]anthracene, were historically the most frequently detected harmful substances to biota in this and the wider Pannonia region. This is the first long-term study to quantify and derivate the most frequently detected harmful substances of concern for this and similar sites in the wider region, and is additionally supported by significant national and similar environmental data from previous studies in the region.

During the last years, declines in honey bee colonies are being registered worldwide. Cholinergic pesticides and their extensive use have been correlated to the decline of pollinators and there is evidence that pesticides act as neuroendocrine disruptors affecting the metabolism of neuropeptides. However, there is a big absence of studies with quantitative results correlating the effect of pesticide exposure with changes on neuropeptides insects, and most of them are conducted under laboratory conditions, typically with individual active ingredients. In this study, we present an analytical workflow to evaluate pesticide effects on honey bees through the analysis of (neuro)peptides. The workflow consists of a rapid extraction method and liquid chromatography with triple quadrupole for preselected neuropeptides. For non-target analysis, high resolution mass spectrometry, multivariate analysis and automatic identification of discriminated peptides using a specific software and protein sequence databases. The analytical method was applied to the analysis of target and non-target (neuro)peptides in honey bees with low and high content of a wide range of pesticides to which have been exposed in field conditions. Our findings show that the identification frequency of target neuropeptides decreases significantly in honey bees with high concentration of pesticides (pesticide concentrations ≥ 500 μg kg⁻¹) in comparison with the honey bees with low content of pesticides (pesticide concentrations ≤ 20 μg kg⁻¹). Moreover, the principal component analysis in non-target search shows a clear distinction between peptide concentration in honey bees with high level of pesticides and honey bees with low level. The use of high resolution mass spectrometry has allowed the identification of 25 non-redundant peptides responsible for discrimination between the two groups, derived from 18 precursor proteins.

Shallow aquifers are the most accessible reservoirs of potable groundwater; nevertheless, they are also prone to various sources of pollution and it is usually difficult to distinguish between human and natural sources at the watershed scale. The area chosen for this study (the Campania Plain) is characterized by high spatial heterogeneities both in geochemical features and in hydraulic properties. Groundwater mineralization is driven by many processes such as, geothermal activity, weathering of volcanic products and intense human activities. In such a landscape, multivariate statistical analysis has been used to differentiate among the main hydrochemical processes occurring in the area, using three different approaches of factor analysis: (i) major elements, (ii) trace elements, (iii) both major and trace elements. The elaboration of the factor analysis approaches has revealed seven distinct hydrogeochemical processes: i) Salinization (Cl⁻, Na⁺); ii) Carbonate rocks dissolution; iii) Anthropogenic inputs (NO₃⁻, SO₄²⁻, U, V); iv) Reducing conditions (Fe²⁺, Mn²⁺); v) Heavy metals contamination (Cr and Ni); vi) Geothermal fluids influence (Li⁺); and vii) Volcanic products contribution (As, Rb). Results from this study highlight the need to separately apply factor analysis when a large data set of trace elements is available. In fact, the impact of geothermal fluids in the shallow aquifer was identified from the application of the factor analysis using only trace elements. This study also reveals that the factor analysis of major and trace elements can differentiate between anthropogenic and geogenic sources of pollution in intensively exploited aquifers.