Spatially explicit estimates of critical loads of nitrogen (N) deposition (CLNdₑₚ) for nutrient enrichment in aquatic ecosystems were developed for the Rocky Mountains, USA, using a geostatistical approach. The lowest CLNdₑₚ estimates (<1.5 ± 1 kg N ha⁻¹ yr⁻¹) occurred in high-elevation basins with steep slopes, sparse vegetation, and abundance of exposed bedrock and talus. These areas often correspond with areas of high N deposition (>3 kg N ha⁻¹ yr⁻¹), resulting in CLNdₑₚ exceedances ≥1.5 ± 1 kg N ha⁻¹ yr⁻¹. CLNdₑₚ and CLNdₑₚ exceedances exhibit substantial spatial variability related to basin characteristics and are highly sensitive to the NO₃ ⁻ threshold at which ecological effects are thought to occur. Based on an NO₃ ⁻ threshold of 0.5 μmol L⁻¹, N deposition exceeds CLNdₑₚ in 21 ± 8% of the study area; thus, broad areas of the Rocky Mountains may be impacted by excess N deposition, with greatest impacts at high elevations.

Mercury concentration ([Hg]), δ¹⁵N, and δ¹³C values were measured in eggs from common murres (Uria aalge), thick-billed murres (U. lomvia), glaucous gulls (Larus hyperboreus), and glaucous-winged gulls (L. glaucescens) collected in Alaska from 1999 to 2005. [Hg] was normalized to a common trophic level using egg δ¹⁵N values and published Hg trophic magnification factors. Egg [Hg] was higher in murres from Gulf of Alaska, Cook Inlet, and Norton Sound regions compared to Bering Sea and Bering Strait regions, independent of trophic level. We believe the Yukon River outflow and terrestrial Hg sources on the southern Seward Peninsula are responsible for the elevated [Hg] in Norton Sound eggs. Normalizing for trophic level generally diminished or eliminated differences in [Hg] among taxa, but temporal variability was unrelated to trophic level. Normalizing murre egg [Hg] by trophic level improves the confidence in regional comparisons of Hg sources and biogeochemical cycling in Alaska.

A comprehensive, weight-of-evidence based ecological risk assessment approach integrating laboratory and in situ bioaccumulation and toxicity testing, passive sampler devices, hydrological characterization tools, continuous water quality sensing, and multi-phase chemical analyses was evaluated. The test site used to demonstrate the approach was a shallow estuarine wetland where groundwater seepage and elevated organic and inorganic contaminants were of potential concern. Although groundwater was discharging into the surficial sediments, little to no chemical contamination was associated with the infiltrating groundwater. Results from bulk chemistry analysis, toxicity testing, and bioaccumulation, however, suggested possible PAH toxicity at one station, which might have been enhanced by UV photoactivation, explaining the differences between in situ and laboratory amphipod survival. Concurrently deployed PAH bioaccumulation on solid-phase micro-extraction fibers positively correlated (r² ≥ 0.977) with in situ PAH bioaccumulation in amphipods, attesting to their utility as biomimetics, and contributing to the overall improved linkage between exposure and effects demonstrated by this approach.

The spatial distribution of per- and polyfluoroalkyl compounds (PFCs) were investigated in coastal waters collected onboard research vessel Snow Dragon from the East to South China Sea in 2010. All samples were prepared by solid-phase extraction and analyzed using high performance liquid chromatography/negative electrospray ionization-tandem mass spectrometry (HPLC/(−)ESI-MS/MS). Concentrations of 9 PFCs, including C₄ and C₈ (PFBS, PFOS) perfluoroalkyl sulfonate (PFSAs), C₅–C₉ and C₁₃ (PFPA, PFHxA, PFHpA, PFOA, PFNA, PFTriDA) perfluoroalkyl carboxylates (PFCAs), and N-ethyl perfluorooctane sulfonamide (EtFOSA) were quantified. The ΣPFC concentrations ranged from 133 pg/L to 3320 pg/L, with PFOA (37.5–1541 pg/L), PFBS (23.0–941 pg/L) and PFHpA (0–422 pg/L) as dominant compounds. Concentrations of PFCs were greater in coastal waters along Shanghai, Ningbo, Taizhou, Xiamen and along coastal cities of the Guangdong province compared to less populated areas along the east Chinese coast. Additionally, the comparison with other seawater PFC measurements showed lower levels in this study.

Lichens are an excellent model to study the bioaccumulation of heavy metals but limited information is available on the molecular mechanisms occurring during bioaccumulation. We investigated the changes of the lichen proteome during exposure to constant concentrations of mercury. We found that most of changes involves proteins of the photosynthetic pathway, such as the chloroplastic photosystem I reaction center subunit II, the oxygen-evolving protein and the chloroplastic ATP synthase β-subunit. This suggests that photosynthesis is a target of the toxic effects of mercury. These findings are also supported by changes in the content of photosynthetic pigments (chlorophyll a and b, and β-carotene). Alterations to the photosynthetic machinery also reflect on the structure of thylakoid membranes of algal cells. Response of lichens to mercury also involves stress-related proteins (such as Hsp70) but not cytoskeletal proteins. Results suggest that lichens adapt to mercury exposure by changing the metabolic production of energy.

Non-PR | IFPRI4; 2020 | DGO

Book chapter | IFPRI4; 2020 | Non-PR | DGO

China has implemented a soil testing and fertilizer recommendation (STFR) program to reduce the over-usage of synthetic nitrogen (N) fertilizer on cereal crops since the late 1990s. Using province scale datasets, we estimated an annual reduction rate of 2.5–5.1 kg N ha⁻¹ from 1998 to 2008 and improving grain yields, which were attributed to the balanced application of phosphate and potassium fertilization. Relative to the means for 1998–2000, the synthetic N fertilizer input and the corresponding N-induced N₂O production in cereal crops were reduced by 22 ± 0.7 Tg N and 241 ± 4 Gg N₂O–N in 2001–2008. Further investigation suggested that the N₂O emission related to wheat and maize cultivation could be reduced by 32–43 Gg N₂O–N per year in China (26%–41% of the emissions in 2008) if the STFR practice is implemented universally in the future.

As the eutrophication of lakes becomes an increasingly widespread phenomenon, cyanobacterial blooms are occurring in many countries. Although some research has been reported, there is currently no good method for bloom removal. We propose here a new two-step integrated approach to resolve this problem. The first step is the inactivation of the cyanobacteria via the addition of H₂O₂. We found 60 mg/L was the lowest effective dose for a cyanobacterial concentration corresponding to 100 μg/L chlorophyll-a. The second step is the flocculation and sedimentation of the inactivated cyanobacteria. We found the addition of lake sediment clay (2 g/L) plus polymeric ferric sulfate (20 mg/L) effectively deposited them on the lake bottom. Since algaecides and flocculants had been used separately in previous reports, we innovatively combined these two types of reagents to remove blooms from the lake surface and to improve the dissolved oxygen content of lake sediments.

Here we evaluate the performance and limitations of two frequently used model-types to predict trace element solubility in soils: regression based “partition-relations” and thermodynamically based “multisurface models”, for a large set of elements. For this purpose partition-relations were derived for As, Ba, Cd, Co, Cr, Cu, Mo, Ni, Pb, Sb, Se, V, Zn. The multi-surface model included aqueous speciation, mineral equilibria, sorption to organic matter, Fe/Al-(hydr)oxides and clay. Both approaches were evaluated by their application to independent data for a wide variety of conditions. We conclude that Freundlich-based partition-relations are robust predictors for most cations and can be used for independent soils, but within the environmental conditions of the data used for their derivation. The multisurface model is shown to be able to successfully predict solution concentrations over a wide range of conditions. Predicted trends for oxy-anions agree well for both approaches but with larger (random) deviations than for cations.