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Recent studies suggest that hypolimnetic respiration may be responsible for greenhouse gas (GHG) emissions from deep reservoirs. Currently, quantitative evaluation of aerobic vs. anaerobic processes and priming (enhanced processing of organic matter due to the addition of labile carbon) in regulating GHG production and emissions across the reservoir-downstream continuum remains largely unknown. High-resolution, annual time-series observations in a large, subtropical reservoir (Shuikou) experiencing seasonal hypoxia in southeast China indicate that aerobic hypolimnetic CO2 production dominated in most periods of the stratified spring/summer with higher rates at higher temperatures. In addition, anaerobic production of hypolimnetic CO2 occurred in the late stratified spring/summer period, which stimulated hypolimnetic production of CH4 and N2O. Incubation experiments showed that priming in spring enhanced both aerobic and anaerobic production of excess GHGs. A late spring flood event generated the highest daily efflux of CO2 through the flushing of GHG-enriched hypolimnion waters. Turbine degassing contributed 59%, 93%, and 63% of annual CO2, CH4, and N2O effluxes, respectively. Moreover, annual downstream GHG emissions were similar to those in the transition/lacustrine zone of the Shuikou reservoir. Diurnal variation observations revealed net CO2 emissions even during algal bloom seasons. The reservoir-downstream river continuum was a year-round source of GHGs (218.5 ± 18.9 Gg CO2-equivalent yr−1; CO2 contributed 91%). However, the loss of oxygen also leads to increased production and storage of recalcitrant dissolved organic carbon (RDOC). Thus, identifying mechanisms controlling both GHG emissions and RDOC production is crucial to constrain the carbon neutrality issue of hydroelectric reservoirs in the context of climate change mitigation strategies.

Microplastics are an emerging and persistent pollutant due to their threat to global ecological systems and human health. Recent studies showed that microplastics have infiltrated the remote Third Pole - the Tibetan Plateau. Here, we summarize the current evidence for microplastic pollution in the different environments (rivers/lakes, sediment, soil, ice/snow and atmosphere) of the Tibetan Plateau. We assess the spatial distribution, source, fate, and potential ecological effects of microplastics in this broad plateau. The integrated results show that microplastics were pervasive in biotic and abiotic components of the Tibetan Plateau, even at the global highest-altitude, Mt. Everest. Although the concentration of microplastics in the Tibetan Plateau was far below that found in the densely populated lowlands, it showed a higher concentration than that in the ocean system. Tourist populations are identified as a substantial source of anthropogenic plastic input rather than local residents due to the rapid development of the tourism industry. In the sparsely inhabited remote area of the Tibetan Plateau, long-range atmospheric transport facilitates allochthonous microplastic diffusion. Robust solar radiation in the Tibetan Plateau might enhanced production of secondary microplastics by weathering (UV-photooxidation) of abandoned plastic waste. A rough estimation showed that the microplastic export flux from melting glaciers was higher than that measured in most of the world's largest rivers, which affects local and downstream areas. Since the Tibetan Plateau is vital for Asian water supply and numerous endangered wildlife, the potential human and ecological risk of microplastics to these fragile ecosystems needs to be fully evaluated within the context of climate-change impacts.

Global impoundment of river systems represents a major anthropogenic forcing to carbon cycling in reservoirs with seasonal thermal stratification. Currently, a quantitative and mechanistic understanding of how hypolimnetic deoxygenation in stratified reservoirs alters dissolved organic matter (DOM) cycling and lateral transport along the river continuum remains unresolved. Herein, we used optical and high-resolution mass spectrometric analyses to track seasonal and spatial compositional changes of DOM from a large, subtropical impounded river in southeast China. Aliphatic compounds were contributed by algal blooms to epilimnetic DOM during the spring/summer and by baseflow to the overall DOM pool during low-discharge periods. Deoxygenation-driven hypolimnetic mineralization enhanced in situ production of bio-refractory molecules and humic-like fluorescent DOM (FDOMH) by utilizing bio-labile DOM and settling biogenic particles during periods of stratification. Production efficiency of hypolimnetic FDOMH was 159-444% higher than that of the global dark ocean, and was strongly regulated by temperature and possibly substrate supply. The in situ production rate of hypolimnetic FDOMH was four to five orders-of-magnitude higher than the dark ocean, with much faster turnover rates in dark inland waters versus the dark ocean. Collectively, these findings indicate that the hypolimnion is a hotspot for microbial carbon transformations, and hence an important source and pool of refractory DOM in aquatic systems. The lateral FDOMH flux increased 10.8-32.1% due to hypolimnetic reservoir release during periods of stratification, highlighting the importance of incorporating hypolimnetic carbon transformations into models for carbon cycling of inland waters and the land-sea interface.

Oceanic absorption of heat generated by greenhouse gas emissions has resulted in warming of the dark ocean (>200 m) that contains a large refractory DOM (RDOM) pool. However, changes in microbially mediated production and degradation dynamics for RDOM components in response to warming of dark marginal basins remain unclear. Herein, we integrated data from the dark South China, Mediterranean and Japan Seas (temperature range: 0.09–15.1°C) to demonstrate that in situ production efficiency of two ubiquitous humic-like fluorophores increased at higher dark ocean temperature, whereas chromophores at a wavelength of 325 nm (aCDOM(325)) changed from production to degradation at higher temperature. Increased oxygen consumption and a reduction of labile substrates in future warmer dark ocean environments may initiate the final degradation of some semi-refractory components, thereby increasing the recalcitrance of RDOM, but decreasing the DOM inventory in dark basins and creating a positive feedback to rising atmospheric CO2.

Base-extracted particulate organic matter (BEPOM) collected in low (spring) and high (summer) runoff seasons in the Changjiang Estuary and adjacent nearshore/offshore shelf areas was examined using absorption and fluorescence spectroscopy. Parallel factor analysis (PARAFAC) identified two humic-like (C1p and C2p) biologically-refractory components and two protein-like (C3p and C4p) bioreactive components. Absorption coefficient a350p, C1p and C2p of BEPOM showed strong positive correlations with particulate organic carbon (POC), and were generally higher in spring than in summer. C4p correlated positively with Chl a, and was higher in summer than in spring. In the inner estuary, an anthropogenic POM signal from the highly polluted Huangpu River was effectively identified by the fluorescent component ratio (IT:IC)P. In the nearshore area during spring, resuspension within the well-developed turbidity maximum zone (TMZ) supplied large amounts of refractory POM into the water column. POM fractions from an autochthonous source (i.e., algal bloom) were dominant in the offshore area during the summer. A multivariate regression model inferred that POM export fluxes from the Changjiang River during spring had a higher percentage of labile POM fractions, which were subsequently retained by the TMZ. However, these labile fractions were discharged into the offshore shelf area contributing to hypoxia in the summer. The summer high runoff season also transported large amounts of refractory POM that was subsequently buried in the sediment. This study highlights the utilization of optical analyses to trace pollution sources and reveal POM fate and transport dynamics allowing better assessment of its ecological consequences in estuaries.

Integrated source apportionment and risk assessment of metals is of great importance for contamination source control and remediation at the regional watershed scale. To identify metal sources and source-specific ecological risks, sediments were collected in the Wen-Rui Tang urban watershed for metal analysis. Risk assessment showed considerable and extremely high risk for Cu and Cd with large spatial variation. Positive matrix factorization model extracted three main sources with reasonable prediction efficacy for metal concentrations. Due to different toxicity coefficients for various metals, the low concentration contribution of source factor 2 (27.2%) contributed 83.7% of total risk, while a high concentration loading for factor 3 (40.8%) only contributed 4.6% to total risk. Predicted source-specific risk was similar to determined risk level for Cr, Ni and Pb; however, Cu and Cd were predicted with decreased risk, while Zn had increased risk. Triangular fuzzy number (TFN) coupled with stochastic simulation showed elevated trend in risk simulation for Cd and Cu when compared with determined risk. The uncertainties for risk evaluation appear to result from spatial variations in metal concentrations. Source apportionment and specific-risk assessment results suggest that different strategies may be required to address mitigation of elevated metal concentrations versus ecological risk.

The 2015/2016 super El Niño event resulted in a positive precipitation anomaly during dry seasons in the Jiulong River watershed, southeast China. Four years (2014–2017) of high frequency, in situ humic-like fluorescent DOM (FDOMH) data in the Jiulong Estuary were coupled with extrapolation to a freshwater end-member FDOMH concentration and river discharge data to estimate riverine FDOMH export. The wetter El Niño dry season was followed by lower FDOMH export during the subsequent wet season. Furthermore, in the dry season after El Niño reached its strongest phase, a 90–187% increase in FDOMH export occurred. If widespread, this pattern suggests El Niño events may enhance export of FDOMH from south China rivers in dry seasons resulting in seasonal and annual shunting of the terrestrial DOM export, modulating coastal carbon cycling. This study highlights the need to incorporate climate-driven regulation patterns on DOM transport across the land-ocean interface.

Quantitative assessment of metal sources in sediments is essential for implementation of source control and remediation strategies. This study investigated metal contamination in sediments to assess potential ecological risks and quantify pollutant sources of metals (Cu, Zn, Pb, Cd, Cr, Co and Ni) in the Wen-Rui Tang River watershed. Total and fraction analysis indicated high pollution levels of metals. Zinc and Cd posed high ecological risk based on the risk assessment code, with the highest ecological risk found in the southwestern of the watershed. The positive matrix factorization (PMF) model was highly effective in predicting total metal concentrations and identified three contributing metal sources. An agricultural source (factor 1) contributed highly to Cu (74.1%) and Zn (42.5%), and was most prominent in the west and south-central portions of the watershed. Cd (93.5%) showed a high weighting with industrial sources (factor 2) with a hot spot in the southwest. Factor 3 was identified as a mixed natural and vehicle traffic source that showed large contribution to Cr (65.2%), Ni (63.9%) and Pb (50.7%). Spatial analysis indicated a consistent pattern between PMF-identified factors and suspected metal sources at the watershed scale demonstrating the efficacy of the PMF modeling approach for watershed analysis.

Metal contamination in aquatic environments is a severe global concern to human health and aquatic ecosystems. This study used several risk assessment indices, to evaluate metal (Cu, Zn, Pb, Cd and Cr) environmental risk of riverine surface sediments across the rural-urban interface of the rapidly developing Wen-Rui Tang River watershed in eastern China. Risk assessments were determined for 38 sites based on the potential ecological risk index (RI), consensus-based sediment quality guidelines (SQGs) and risk assessment code (RAC). Land-use cluster analysis showed that sediments were severely contaminated, especially for Cd, whose concentrations were ∼100 times higher than background levels and had a high proportion in the bioaccessible fraction. According to RI, ErCd was identified with extremely high risk potential, resulting in the highest ecological risk of Cluster 4 (industrial). Similarly, risk within Cluster 4 (industrial) was also ranked highest by SQGs assessment due to the high proportion of industrial land use. Zinc was determined with high risk due to its high concentration compared to its effect range medium (ERM) value. Discrepancies in predicting environmental risks from metals among the three indices were mainly attributed to the contrasting definitions of these metrics. Environmental risk uncertainty derived from spatial variation was further estimated by Monte Carlo simulation and ranked as: Zn > Cd > Cr > Pb > Cu. This comprehensive environmental risk assessment provides important information to guide remediation strategies for management of metal contamination at the watershed scale.

Assessing heavy metal pollution in river sediments and identifying the key factors contributing to metal pollution are critical components for devising river environmental protection and remediation strategies to protect human and ecological health. This is especially important in urban areas where metals from a wide range of sources contribute to sediment pollution. In this study, the metal enrichment factor (EF) was used to measure the watershed distribution of Cu, Zn, Pb and Cd in sediments in the Wen-Rui Tang urban river system in Wenzhou, Eastern China. The Geographical Detector Method (GDM) was specifically evaluated for its ability to analyze spatial relationships between metal EFs and their anthropogenic and natural control factors, including densities of industry (DI), livestock (DL), service industries (DS), population (DP), and roads (DR), along with agricultural area (AG), sediment total organic carbon (TOC), and soil types (ST). Results showed that the watershed was highly contaminated by all metals with an EF trend of Cd ≫ Zn > Cu > Pb. The spatial distribution of EFs demonstrated high contamination of all metals in the southwestern region of the watershed where industrial activities were concentrated, and higher Cu and Zn concentrations in the northeastern region having a high density of livestock production. GDM results identified DI as the dominant determinant for all metals, while TOC and ST were determined to have a moderate secondary influence for Zn, Pb and Cd. Additionally, GDM revealed several additive and nonlinear interactions between anthropogenic and natural factors influencing metal concentrations. Compared to other correlation, multiple linear regression and geographically weighted regression, GDM demonstrated distinct advantages of being able to assess both categorical and continuous variables and determine both single and multiple factor interactions. These attributes provide a more comprehensive understanding of metal spatial distributions while avoiding multicollinearity issues when identifying significant contributing factors at the watershed scale.

Heavy metal pollution of aquatic environments in rapidly developing industrial regions is of considerable global concern due to its potential to cause serious harm to aquatic ecosystems and human health. This study assessed heavy metal contamination of sediments in a highly industrialized urban watershed of eastern China containing several historically unregulated manufacturing enterprises. Total concentrations and solid-phase fractionation of Cu, Zn, Pb, Cr and Cd were investigated for 39 river sediments using multivariate statistical analysis and geographically weighted regression (GWR) methods to quantitatively examine the relationship between land use and heavy metal pollution at the watershed scale. Results showed distinct spatial patterns of heavy metal contamination within the watershed, such as higher concentrations of Zn, Pb and Cd in the southwest and higher Cu concentration in the east, indicating links to specific pollution sources within the watershed. Correlation and PCA analyses revealed that Zn, Pb and Cd were dominantly contributed by anthropogenic activities; Cu originated from both industrial and agricultural sources; and Cr has been altered by recent pollution control strategies. The GWR model indicated that several heavy metal fractions were strongly correlated with industrial land proportion and this correlation varied with the level of industrialization as demonstrated by variations in local GWR R2 values. This study provides important information for assessing heavy metal contaminated areas, identifying heavy metal pollutant sources, and developing regional-scale remediation strategies.

Heavy metal pollution is a major concern in China because of its serious effects on human health. To assess potential human health and ecological risks of heavy metal pollution, concentration data for seven heavy metals (As, Pb, Cd, Cr, Hg, Cu, Zn) from 14 sites spanning the rural-urban interface of the Wen-Rui Tang River watershed in southeast China were collected from 2000 to 2010. The heavy metal pollution index (HPI), hazard index (HI) and carcinogenic risk (CR) metrics were used to assess potential heavy metal risks. Further, we evaluated the uncertainty associated with the risk assessment indices using Monte Carlo analysis. Results indicated that all HPI values were lower than the critical level of 100 suggesting that heavy metal levels posed acceptable ecological risks; however, one site having an industrial point-source input reached levels of 80-97 on several occasions. Heavy metal concentrations fluctuated over time, and the decrease after 2007 is due to increased wastewater collection. The HI suggested low non-carcinogenic risk throughout the study period (HI  10-4). While most metrics for human health risk did not exceed critical values for heavy metals, there is still a potential human health risk from chronic exposure to low heavy metal concentrations due to long-term exposure and potential metal interactions. Results of this study inform water pollution remediation and management efforts designed to protect public health in polluted urban area waterways common in rapidly developing regions.

Recent studies suggest that hypolimnetic respiration may be responsible for greenhouse gas (GHG) emissions from deep reservoirs. Currently, quantitative evaluation of aerobic vs. anaerobic processes and priming (enhanced processing of organic matter due to the addition of labile carbon) in regulating GHG production and emissions across the reservoir‐downstream continuum remains largely unknown. High‐resolution, annual time‐series observations in a large, subtropical reservoir (Shuikou) experiencing seasonal hypoxia in southeast China indicate that aerobic hypolimnetic CO2 production dominated in most periods of the stratified spring/summer with higher rates at higher temperatures. In addition, anaerobic production of hypolimnetic CO2 occurred in the late stratified spring/summer period, which stimulated hypolimnetic production of CH4 and N2O. Incubation experiments showed that priming in spring enhanced both aerobic and anaerobic production of excess GHGs. A late spring flood event generated the highest daily efflux of CO2 through the flushing of GHG‐enriched hypolimnion waters. Turbine degassing contributed 59%, 93%, and 63% of annual CO2, CH4, and N2O effluxes, respectively. Moreover, annual downstream GHG emissions were similar to those in the transition/lacustrine zone of the Shuikou reservoir. Diurnal variation observations revealed net CO2 emissions even during algal bloom seasons. The reservoir‐downstream river continuum was a year‐round source of GHGs (218.5 ± 18.9 Gg CO2‐equivalent yr−1; CO2 contributed 91%). However, the loss of oxygen also leads to increased production and storage of recalcitrant dissolved organic carbon (RDOC). Thus, identifying mechanisms controlling both GHG emissions and RDOC production is crucial to constrain the carbon neutrality issue of hydroelectric reservoirs in the context of climate change mitigation strategies. [ABSTRACT FROM AUTHOR]