In Europe, emerging organic compounds (EOCs) in groundwater is a growing research area. Prioritisation for monitoring EOCs in Europe was formalised in 2019 through the development of the first voluntary groundwater watch list (GWWL). Despite this, groundwater occurrence data in the peer reviewed literature for Europe has not been reviewed to date. Questions surrounding the effect, toxicity, movement in the subsurface and unsaturated zone make the process of regulating EOC use difficult. The aim in Europe is to develop a unified strategy for the classification, and prioritisation of EOCs to be monitored in groundwater. This paper compiles evidence from the recent published studies from across Europe, since 2012, when the last major literature global review of EOCs in groundwater took place. A total of 39 studies were identified for review based on specific selection criteria (geography, publication date, sample size>10, inclusion of EOCs data). Data on specific compounds, and associated meta-data, are compiled and reviewed. The two most frequently detected EOCs, carbamazepine and caffeine, occurred in groundwater at concentrations of up to 2.3 and 14.8 μg/L, respectively.The most frequently reported category of compounds were ‘Pharmaceuticals’; a highly studied group with 135 compounds identified within 31 of the 39 studies. In Europe, the majority of reviewed studies (23) were at a regional scale, looking specifically at EOCs in a specific city or aquifer. The use of analytical methods is not uniform across Europe, and this inevitably influences the current assessment of EOCs in groundwater. A correlation between the number of compounds analysed for, and the number detected in groundwater highlights the need for further studies, especially larger-scale studies throughout Europe. For the development of EU and national regulation, further work is required to understand the occurrence and impacts of EOCs in groundwater throughout Europe and elsewhere.

PCDD/F and PCB concentrations in remote mountainous spruce stands of the Central European Alps show strong geographic variation. Independent of the matrix (0.5 year old needles, humus or mineral soil), the highest pollutant levels were always found at the lateral zones of the mountain range. High levels coincided with strong precipitation, particularly along the northern margin of the study region. The most volatile PCB congener propagated farther into the colder, drier central Alps than the heavier species. Matrices with different accumulation history (needles and humus) repeatedly reflected different spatial immission patterns. Consistent with its much longer exposure, pollutant levels in humus exceeded those of needles by up to two orders of magnitude. Needle contamination varied with altitude but the vertical trends were highly variable between transsects and changed between years, too. Dioxin-like pollution of forests in the Alps shows strong geographic variation.

Mangrove sediments are prone to anthropogenic activities that could enrich antibiotics resistance genes (ARGs). The emergence and dissemination of ARGs are of serious concern to public health worldwide. Therefore, a comprehensive resistome analysis of global mangrove sediment is of paramount importance. In this study, we have implemented a deep machine learning approach to analyze the resistome of mangrove sediments from Brazil, China, Saudi Arabia, India, and Malaysia. Geography (RANOSIM = 39.26%; p < 0.005) as well as human intervention (RANOSIM = 16.92%; p < 0.005) influenced the ARG diversity. ARG diversity was also inversely correlated to the human development index (HDI) of the host country (R = −0.53; p < 0.05) rather than antibiotics consumption (p > 0.05). Several genes including multidrug efflux pumps were significantly (p < 0.05) enriched in the sites with human intervention. Resistome was consistently dominated by rpoB2 (19.26 ± 0.01%), multidrug ABC transporter (10.40 ± 0.23%), macB (8.84 ± 0.36n%), tetA (4.13 ± 0.35%), mexF (3.26 ± 0.19%), CpxR (2.93 ± 0.2%), bcrA (2.38 ± 0.24%), acrB (2.37 ± 0.18%), mexW (2.19 ± 0.17%), and vanR (1.99 ± 0.11%). Besides, mobile ARGs such as vanA, tet(48), mcr, and tetX were also detected in the mangrove sediments. Comparative analysis against terrestrial and ocean resistomes showed that the ocean ecosystem harbored the lowest ARG diversity (Chao1 = 71.12) followed by mangroves (Chao1 = 258.07) and terrestrial ecosystem (Chao1 = 294.07). ARG subtypes such as abeS and qacG were detected exclusively in ocean datasets. Likewise, rpoB2, multidrug ABC transporter, and macB, detected in mangrove and terrestrial datasets, were not detected in the ocean datasets. This study shows that the socioeconomic factors strongly determine the antibiotic resistome in the mangrove. Direct anthropogenic intervention in the mangrove environment also enriches antibiotic resistome.

Ecological risk assessments (ERAs) of polycyclic aromatic compounds (PACs), as single congeners or in mixtures, present technical challenges that raise concerns about their accuracy and validity for Canadian environments. Of more than 100,000 possible PAC structures, the toxicity of fewer than 1% have been tested as individual compounds, limiting the assessment of complex mixtures. Because of the diversity in modes of PAC action, the additivity of mixtures cannot be assumed, and mixture compositions change rapidly with weathering. In vertebrates, PACs are rapidly oxygenated by cytochrome P450 enzymes, often to metabolites that are more toxic than the parent compound. The ability to predict the ecological fate, distribution and effects of PACs is limited by toxicity data derived from tests of a few responses with a limited array of test species, under optimal laboratory conditions. Although several models are available to predict PAC toxicity and rank species sensitivity, they were developed with data biased by test methods, and the reported toxicities of many PACs exceed their solubility limits. As a result, Canadian Environmental Quality Guidelines for a few individual PACs provide little support for ERAs of complex mixtures in emissions and at contaminated sites. These issues are illustrated by reviews of three case studies of PAC-contaminated sites relevant to Canadian ecosystems. Interactions among ecosystem characteristics, the behaviour, fate and distribution of PACs, and non-chemical stresses on PAC-exposed species prevented clear associations between cause and effect. The uncertainties of ERAs can only be reduced by estimating the toxicity of a wider array of PACs to species typical of Canada’s diverse geography and environmental conditions. Improvements are needed to models that predict toxicity, and more field studies of contaminated sites in Canada are needed to understand the ecological effects of PAC mixtures.

The present study deals with the application of the self-organizing map (SOM) technique in the exploration of spatiotemporal dynamics of spring and stream water samples collected in the Chochołowski Stream Basin located in the Tatra Mountains (Poland). The SOM-based classification helped to uncover relationships between physical and chemical parameters of water samples and factors determining the quality of water in the studied high-mountain area. In the upper part of the Chochołowski Stream Basin, located on the top of the crystalline core of the Tatras, concentrations of the majority of ionic substances were the lowest due to limited leaching. Significantly higher concentration of ionic substances was detected in spring and stream samples draining sedimentary rocks. The influence of karst-type springs on the quality of stream water was also demonstrated.

An agricultural ammonia (NH3) emission inventory in the North China Plain (NCP) on a prefecture level for the year 2004, and a 5 × 5 km2 resolution spatial distribution map, has been calculated for the first time. The census database from China's statistics datasets, and emission factors re-calculated by the RAINS model supported total emissions of 3071 kt NH3–N yr−1 for the NCP, accounting for 27% of the total emissions in China. NH3 emission from mineral fertilizer application contributed 1620 kt NH3–N yr−1, 54% of the total emission, while livestock emissions accounted for the remaining 46% of the total emissions, including 7%, 27%, 7% and 5% from cattle, pigs, sheep and goats, and poultry, respectively. A high-resolution spatial NH3 emissions map was developed based on 1 × 1 km land use database and aggregated to a 5 × 5 km grid resolution. The highest emission density value was 198 kg N ha−1 yr−1. The first high-resolution spatial distribution of ammonia emissions for the North China Plain showed rates up to 200 kg NH3–N ha−1 yr−1.

Heavy metal contamination has been and continues to be a worldwide phenomenon that has attracted a great deal of attention from governments and regulatory bodies. In this context, our study proposes a regression-tree model to predict the concentration level of zinc in the soils of northern Lebanon (as a case study of Mediterranean landscapes) under a GIS environment. The developed tree-model explained 88% of variance in zinc concentration using pH (100% in relative importance), surroundings of waste areas (90%), proximity to roads (80%), nearness to cities (50%), distance to drainage line (25%), lithology (24%), land cover/use (14%), slope gradient (10%), conductivity (7%), soil type (7%), organic matter (5%), and soil depth (5%). The overall accuracy of the quantitative zinc map produced (at 1:50.000 scale) was estimated to be 78%. The proposed tree model is relatively simple and may also be applied to other areas. GIS regression-tree analysis explained 88% of the variability in field/laboratory Zinc concentrations.

Critical loads (CLs) define maximum atmospheric deposition levels apparently preventative of ecosystem harm. We present first nitrogen CLs for northwestern North America’s maritime forests. Using multiple linear regression, we related epiphytic-macrolichen community composition to: 1) wet deposition from the National Atmospheric Deposition Program, 2) wet, dry, and total N deposition from the Communities Multi-Scale Air Quality model, and 3) ambient particulate N from Interagency Monitoring of Protected Visual Environments (IMPROVE). Sensitive species declines of 20-40% were associated with CLs of 1-4 and 3-9 kg N ha-1 y-1 in wet and total deposition. CLs increased with precipitation across the landscape, presumably from dilution or leaching of depositional N. Tight linear correlation between lichen and IMPROVE data suggests a simple screening tool for CL exceedance in US Class I areas. The total N model replicated several US and European lichen CLs and may therefore be helpful in estimating other temperate-forest lichen CLs. Lichen-based critical loads for N deposition in western Oregon and Washington forests ranged from 3 to 9 kg ha-1 y-1, increasing with mean annual precipitation.

A pesticide runoff event was simulated on two 10 m x 50 m constructed wetlands (one non-vegetated, one vegetated) to evaluate the fate of methyl parathion (MeP) (Penncap-M). Water, sediment, and plant samples were collected at five sites downstream of the inflow for 120 d. Semi-permeable membrane devices (SPMDs) were deployed at each wetland outflow to determine exiting pesticide load. MeP was detected in water at all locations of the non-vegetated wetland (50 m), 30 min post-exposure. MeP was detected 20 m from the vegetated wetland inflow 30 min post-exposure, while after 10d it was detected only at 10 m. MeP was measured only in SPMDs deployed in non-vegetated wetland cells, suggesting detectable levels were not present near the vegetated wetland outflow. Furthermore, mass balance calculations indicated vegetated wetlands were more effective in reducing aqueous loadings of MeP introduced into the wetland systems. This demonstrates the importance of vegetation as sorption sites for pesticides in constructed wetlands.