Eating fish provides numerous health benefits, but it is also a dominant pathway for human exposure to contaminants. Many studies have examined mercury (Hg) accumulation in fish, but fewer have considered other elements, such as arsenic (As) and chromium (Cr). Recently, freshwater fish from several pristine boreal systems across northern Ontario, Canada, have been reported with elevated concentrations of As and Cr for reasons that are not well understood. Our goal was to investigate the ecological and environmental influences over concentrations of As, Cr, and other elements in these fish to better understand what affects metal uptake and the risk to consumers. We measured 10 elements (including As, Cr, Hg) as well as carbon (δ¹³C), nitrogen (δ¹⁵N), and sulfur (δ³⁴S) stable isotopes in 388 fish from 25 lake and river sites across this remote region. These data were used to determine the effect of: 1) trophic ecology; and 2) watershed geology on piscine elemental content. Overall, most element concentrations were low, often below provincial advisory benchmarks (ABs). However, traces of Hg, As, Cr, and selenium (Se) were detected in most fish. Based on their exceedance of their respective ABs, the most restrictive elements on fish consumption in these boreal systems were Hg > As > Cr. Arsenic and Se, but not Cr concentrations were related to fish size and trophic ecology (inferred from δ¹³C and δ¹⁵N), suggesting bioaccumulation of the former elements. Fish with enriched δ³⁴S values, suggestive of anadromous behaviour, had marginally lower Hg but higher Se concentrations. Modeling results suggested a strong effect of site-specific factors, though we found weak trends between piscine elemental content and geological features (e.g., mafic intrusions), potentially due to the broad spatial scale of this study. Results from this study address gaps in our understanding of As and Cr bioaccumulation and will help to inform fish consumption guidelines.

In aquatic environments, organisms such as freshwater mussels are likely exposed to complex contaminant mixtures related to industrial, agricultural, and urban activities. With growing interest in understanding the risk that chemical mixtures pose to mussels, this investigation focused on the effects of various waterborne contaminants (ammonia, chloride, copper, and potassium) and selected binary mixtures of these chemicals following a fixed-ratio design to Villosa iris glochidia and juvenile Lampsilis fasciola. In individual exposures, 48-h EC50 values were determined for V. iris glochidia exposed to ammonia chloride (7.4 [95% confidence interval (CI) 6.6–8.2] mg N/L), ammonia sulfate (8.4 [7.6–9.1] mg N/L), copper sulfate (14.2 [12.9–15.4] μg Cu2+/L), potassium chloride (12.8 [11.9–13.7] mg K+/L), potassium sulfate (10.1 [8.9–11.2] mg K+/L), and sodium chloride (480.5 [435.5–525.5] mg Cl−/L). The 7-d LC50 values for juvenile L. fasciola were determined for potassium sulfate (45.0 [18.8–71.2] mg K+/L), and sodium chloride (1738.2 [1418.6–2057.8] mg Cl−/L). In Ontario these waterborne contaminants have been reported to co-occur, with concentrations exceeding the EC10 for both life stages at some locations. Data from binary mixture exposures for V. iris glochidia (chloride-ammonia, chloride-copper, and copper-ammonia) and juvenile L. fasciola (chloride-potassium) were analyzed using a regression-based, dose-response mixture analysis modeling framework. Results from the mixture analysis were used to determine if an additive model for mixture toxicity [concentration addition (CA) or independent action (IA)] best described the toxicity of each mixture and if deviation towards dose-ratio (DR) or dose-level (DL) synergism/antagonism (S/A) occurred. For all glochidia binary mixture exposures, CA was the best fit model with DL deviation reported for the chloride-copper mixture and DR deviation reported for the copper-ammonia mixture. Using the model deviation ratio (MDR), the observed toxicity in all three glochidia mixture exposures were adequately described by both CA (mean = 0.71) and IA (mean = 0.97) whereas the juvenile mixture exposure was only adequately described by CA (mean = 0.64; IA mean = 0.05).

Naphthalene sulfonic acids (NSAs) are used extensively in industrial applications as dispersants in dyes, rubbers, and pesticides, and as anti-corrosive agents in coatings, gels, and sealants. This study examined the toxicity of three NSA congeners, barium dinonylnaphthalene sulfonate (BaDNS), calcium dinonylnaphthalene sulfonate (CaDNS), and dinonylnaphthalene disulfonic acid (DNDS), to two benthic species, Tubifex tubifex and Hyalella azteca. Two substrates with different levels of organic carbon (sediment [2%] and sand [0%]) were used in toxicity tests. Juvenile production was the most sensitive endpoint for T. tubifex: the 28-d EC50s were <18.2, 22.2, and 64.0 μg/g dw in sand and 281.3, 361.6, and 218.9 μg/g dw in sediment for BaDNS, CaDNS, and DNDS, respectively. The 28-d LC50s for H. azteca were similar among compounds: 115.3, 82.1, and 49.0 μg/g dry weight (dw) in sand, and 627.3, 757.9, and >188.5 μg/g dw in sediment, for BaDNS, CaDNS, and DNDS, respectively. However, when LC50s were estimated based on concentrations of NSAs measured in overlying water (which can be an important route of exposure for H. azteca), BaDNS and CaDNS were 3–4 orders of magnitude more toxic than DNDS. The NSAs examined were >3-fold more toxic when present in substrates with no organic carbon (e.g., sand) for all H. azteca endpoints where LC/EC50s could be calculated and for sublethal endpoints for T. tubifex. The organic carbon content of the sediment appears to have acted as a sink and reduced NSA toxicity by decreasing bioavailability. Environmental sediment samples were collected from 12 river sites across southern Ontario. The maximum concentration of CaDNS observed in sediment collected from this region was 2.8 μg/g dw in sediment with 2% organic carbon; 100-fold lower than the lowest EC10 in the current study.

The state of practice for noise assessment utilizes established standards for emission and propagation modelling of linear and point sources. Recently, land use regression (LUR) modelling has emerged as an alternative method due to relatively low data and computing resource demands. However, a limitation of LUR modelling is that is does not account for noise attenuation and reflections by features of the built environment. This study demonstrates and validates a method that combines the two modelling frameworks to exploit their respective strengths: Emission and propagation based prediction of traffic noise, the predominant source of noise at the level of streetscapes, and a LUR-based correction for noise sources that vary on spatial scales beyond the streetscape.Multi-criteria analysis, location-allocation modelling and stakeholder consultation identified 220 monitoring sites with optimal coverage for a 1-week sampling period. A subset of sites was used to validate a road traffic noise emission and propagation model and to specify a LUR model that predicted the contribution of other sources. The equivalent 24-h sound pressure level (LAeq) for all sites was 62.9 dBA (SD 6.4). This varied by time of day, weekday, types of roads and land uses. The traffic noise emission model demonstrated a high level of covariance with observed noise levels, with R² values of 0.58, 0.60 and 0.59 for daytime, nighttime and 24-h periods, respectively. Combined with LUR models to correct for other noise sources, the hybrid models R² values were 0.64, 0.71 and 0.67 for the respective time periods.The study showed that road traffic noise emissions account for most of the variability of total environmental noise in Toronto. The combined approach to predict fine resolution noise exposures with emission and receptor-based models presents an effective alternative to noise modelling approaches based on emission and propagation or LUR modelling.

While considerable attention has been given to the measurement of mercury (Hg) and lead (Pb) concentrations and accumulation in detailed peat cores in central Canada, the geographic distribution and density of sampling are generally limited. Here, we use the Ontario Peatland Inventory to examine broad patterns of Hg and Pb concentration with depth, based on 338 peat cores (containing >1500 analyzed samples) from 127 bogs, fens and swamps located in southeastern, northeastern and northwestern sections of Ontario. Overall, Hg concentrations averaged 0.05 μg g⁻¹ and that of Pb averaged 10.8 μg g⁻¹. Maximum values in the top 50 cm of the profiles are 0.08 μg g⁻¹ and 26.2 μg g⁻¹ for Hg and Pb, respectively. The ratio between these values (surface) and the values from below 100 cm (background), where peat likely accumulated before 1850 and industrial activities were limited, are 2.3 and 6.6 for Hg and Pb, respectively. The highest surface:background concentration ratios are generally found in the westernmost part of the province and in the southeast for Hg and around areas that are more heavily populated for Pb. Our results show that a vast amount of Hg and Pb are stored in Ontarian peatlands, although the spatial distribution of these stores varies. The rapid decomposition of peat in a changing climate could release these pollutants to the atmosphere.

Wetlands are prevalent in the Sudbury, Ontario region and often operate at the interface between terrestrial and aquatic ecosystems, modifying water chemistry and potentially affecting the recovery of impacted lakes. The deposition of metals and sulphur in Sudbury in 2010–2012 was far below that reported in the 1970's, but still higher than background values. Wetlands in the area have accumulated large quantities of metals, and high concentrations of these metals in streams occurred primarily in response to SO4-related acidification events or associated with high dissolved organic carbon production in early summer. Concentrations of most metals in streams exceeded provincial guidelines and fluxes of some metals from catchments exceeded deposition inputs to lakes by as much as 12 times. The release of metals long after emissions reductions have been achieved must be considered in ecosystem recovery studies, particularly as dry conditions may become more prevalent in boreal regions affected by mining.

Highways are major sources of nitrogen dioxide (NO2) and ammonia (NH3). In this study, springtime NO2 and NH3 concentrations were measured at 17 Ontario Forest Biomonitoring Network (OFBN) plots using passive samplers. Average springtime NO2 concentrations were between 1.3 μg m−3 and 27 μg m−3, and NH3 concentrations were between 0.2 μg m−3 and 1.7 μg m−3, although concentrations measured in May (before leaf out) were typically twice as high as values recorded in June. Average NO2 concentrations, and to a lesser extent NH3, could be predicted by road density at all radii (around the plot) tested (500 m, 1000 m, 1500 m). Springtime NO2 concentrations were predicted for a further 50 OFBN sites. Normalized plant/lichen N concentrations were positively correlated with estimated springtime NO2 and NH3 concentrations. Epiphytic foliose lichen richness decreased with increasing NO2 and NH3, but vascular plant richness was positively related to estimated springtime NO2 and NH3.

Natural abundance 14C analysis was applied to PLFAs collected from an industrial site in southern Ontario in order to assess microbial carbon sources and potential PAH biodegradation in soils. Δ14C of microbial phospholipid fatty acids (PLFA) at the site ranged from +54‰ to −697‰. Comparison of these values to surrounding carbon sources found that microbial carbon sources were derived primarily from vegetation and/or natural organic matter present in the soils rather than PAHs. This study highlights that microbes are able to utilize almost all available pools of organic matter including older pools which are thought to contain recalcitrant compounds. Furthermore, it shows that even with the presence of an active microbial community, there may be little biodegradation of PAHs. This study illustrates challenges in assessing microbial activity in the environment and the advantage of using natural abundance 14C analysis as a tool to elucidate microbial carbon sources.