Universal high-frequency monitoring methods of river water quality in China based on machine learning.

The in-situ high-frequency monitoring of total nitrogen (TN) and total phosphorus (TP) in rivers is a challenge and key to instant water quality judgment and early warning. Based on the physical and chemical association between TN/TP and sensor-measurable predictors, we proposed a novel "indirect" measurement method for TN and TP in rivers. This method combines the timeliness of multi-sensor and the accuracy of intelligent algorithms, utilizing 188,629 data sets from 131 water monitoring stations across China. Under 5 algorithms and 4 predictor group scenarios, the results showed that: (1) extra tree regression (ETR) with 6 predictors exhibited the best precision, and mean determination coefficient (R2) of TN and TP inversion across 131 stations reached 0.78 ±â€¯0.25 and 0.79 ±â€¯0.22 respectively; (2) among 6 potential predictors, the importance degrees of temperature, electrical conductivity, NH4-N, and turbidity were large than pH and dissolved oxygen (DO), and >80 % of stations exhibited acceptable prediction accuracy (R2 > 0.6) when the number of predictors (P) ranged from 4 to 6, which showed good tolerability to predictor variations; (3) the accurate classification rate of water quality standard (ACRws) of all stations based on TN and TP reached 90.41 ±â€¯6.96 % and 92.33 ±â€¯6.41 %; (4) in 9 regions/basins of China, this method showed universal application potential with no significant prediction difference. Compared with laboratory test, water quality automatic monitoring station, and remote sensing inversion, the proposed method has high-frequency, high-precision, regional adaptability, low cost, and stable operation under rainy, cloudy, and nighttime conditions. The new method may provide important technological support for timely pollutant tracing, pre-warning, and emergency control for river pollution.

Perspectives on total phosphorus response in rivers: Examining the influence of rainfall extremes and post-dry rainfall.

Eutrophication is a significant environmental problem caused by nutrient loads from both point and non-point sources. Weather variables, particularly precipitation, affect the concentration of nutrients in water bodies, particularly those from non-point sources, in two contrasting ways. Heavy precipitation causes surface runoff which transports pollutants to rivers and increases nutrient concentration. Conversely, increased river flow can dilute the concentration, lowering it. This study investigates the impact of extreme precipitation, prolonged precipitation, and precipitation after a dry period on the total phosphorus concentration in the Moehne and Erft rivers in Germany, given the projected increase in frequency of extreme precipitation events and long drought periods due to climate change. The study comprises two parts: selecting extreme weather days from 2001 to 2021 and comparing observed Total Phosphorus concentrations with estimated concentrations derived from Generalized Additive Models and linear regression based on the discharge-concentration relationship. Changes in river TP concentration in response to continuous precipitation and precipitation after a dry period were also studied. Our results showed that during wet extreme and post-dry period rainfall events, TP concentration consistently surpassed expected values, underscoring the profound influence of intense rainfall on nutrient mobilization. However, we observed the impact of continuous rainfall to be non-unidirectional. Our work is distinguished by three key innovations: 1) addressing limitations in studying the effects of extreme weather on water quality due to limited temporal resolution, 2) incorporating both linear and non-linear modeling approaches for discharge-concentration relationships, and 3) performing a comprehensive analysis of temporal and spatial patterns of Total Phosphorus concentrations in response to varying rainfall patterns.

Implications of the operation of continuous granular activated carbon filters on the effluent quality.

Granular activated carbon (GAC) filtration is a commonly used method for advanced wastewater treatment. Filters can be operated continuously or discontinuously, with continuous operation not requiring feed flow interruption for backwashing and circulation (B/C). This study investigated the influence of B/C on the effluent quality of continuous filters. Two continuous GAC filters were operated for 1.5 years, with analysis of dissolved substances and particulate matter in the influent and effluent. The results indicated that various B/C modes had no impact on the removal of dissolved organic carbon and organic micropollutants (OMP), achieving an OMP removal of over 70% after 5,600 treated bed volumes (m3 treated wastewater per m3 GAC). However, it was evident that continuous B/C over 2-4 h resulted in increased turbidity, total suspended solids over 30 mg/L and total phosphorus concentrations of 1.3 mg/L in the filter effluent. Additionally, the study demonstrated that longer and more intensive B/C processes resulted in GAC size degradation with AC concentrations of up to 6.9 mg/L in the filter effluent, along with a change in GAC particle size. Furthermore, the importance of pre-filtration in reducing particulate matter in the filter influent and decreasing hydraulic head loss could be demonstrated.

Assessing spatiotemporal risks of nonpoint source pollution via soil erosion: a coastal case in the Yellow River Delta, China.

Nonpoint source pollution (NPSP) has always been the dominant threat to regional waters. Based on empirical models of the revised universal soil loss equation and the phosphorus index, an NPSP risk assessment model denoted as SL-NPSRI was developed. The surface soil pollutant loss was estimated by simulating the rain-runoff topographic process, and the influence of path attenuation was quantified. A case study in the Yellow River Delta and corresponding field surveys of soil pollutants and water quality showed that the established model can be applied to evaluate the spatial heterogeneity of NPSP. NPSP usually occurs during high-intensity rainfall periods and in larger estuaries. Summer rainfall increased pollutant transport into the sea from late July to mid-August and caused estuarine dilution. Higher NPSP risks often correspond to coastal areas with lower vegetation coverage, higher soil erodibility, and higher soil pollutant concentrations. Agricultural NPSP originating from cropland significantly increase the pollutant fluxes. Therefore, area-specific land use management and vegetation coverage improvement, and temporal-specific strategies can be explored for NPSP control during source-transport hydrological processes. This research provides a novel insight for coastal NPSP simulations by comprehensively analyzing the soil erosion process and its associated pollutant loss effects, which can be useful for targeted spatiotemporal solutions.

TP or Not TP? Successful Comparison of Two Independent Methods Validates Total Phosphorus Inference for Long-Term Eutrophication Studies.

Validating paleo total phosphorus (TP) inference methods over long time scales is essential for understanding historic changes in lake P supply and the processes leading up to the present-day global lake eutrophication crisis. Monitored lake water TP time series have enabled us to identify the drivers of eutrophication over recent decades. However, over longer time scales, the lack of reliable TP inference means our understanding of drivers is speculative. Validation of lake water TP reconstruction, therefore, remains the "ultimate aim" of eutrophication studies. Here, we present the first critical comparison of two fully independent paleo TP inference approaches: the well-established diatom method (DI-TP) and a recently developed sediment geochemical method (SI-TP). Using lake sediment records from a small eutrophic U.K. lake (Crose Mere), we find a statistically significant agreement between the two inferred TP records with greater than 60% shared variance. Both records show identical timings, with a 19th century acceleration in TP concentration and subsequent declines following a peak in 1930. This significant agreement establishes the validity of long-term paleo TP inference for the first time. With this, we can now test assumptions and paradigms that underpin understanding of catchment P sources and pathways over longer time scales.

Spatiotemporal variation reconstruction of total phosphorus in the Great Lakes since 2002 using remote sensing and deep neural network.

Total phosphorus (TP) is non-optically active, thus TP concentration (CTP) estimation using remote sensing still exists grand challenge. This study developed a deep neural network model (DNN) for CTP estimation with synchronous in-situ measurements and MODIS-derived remote sensing reflectance (Rrs) (N = 3916). Using DNN, the annual and intra-annual CTP spatial distributions of the Great Lakes since 2002 were reconstructed. Then, the reconstructions were correlated to nine potential factors, e.g., Chlorophyll-a, snowmelt, and cropland, to explain seasonal and long-term CTP variations. The results showed that DNN reliably estimated CTP from MODIS Rrs, with R2, mean absolute error (MAE), root mean squared error (RMSE), mean absolute percentage error (MAPE), and root mean squared logarithmic error (RMSLE) of 0.83, 1.05 µg/L, 2.95 µg/L, 9.92%, and 0.13 on the test set. The near-surface CTP in the Great Lakes decreased significantly (p < 0.05) during 2002 - 2022, primarily attributed to cropland reduction, coupled with improvements in basin natural ecosystems. The sensitivity analysis verified the model robustness when confronted with input feature changes < 35%. This result along with the marginal difference between CTP derived from two sensors (R2 = 0.76, MAE = 2.12 µg/L, RMSE = 2.51 µg/L, MAPE = 11.52%, RMSLE = 0.24) suggested the model transferability from MODIS to VIIRS. This transformation facilitated optimal usage of MODIS-related archive and enhanced the continuity of CTP estimation at moderate resolution. This study presents a practical method for spatiotemporal reconstruction of CTP using remote sensing, and contributes to better understandings of driving factors behind CTP variations in the Great Lakes.

Transport dynamics of watershed discharged diffuse phosphorus pollution load to the lake in middle of Yangtze River Basin.

Diffuse pollution, including that in the lower and middle reaches of the Yangtze River, is the primary source of pollution in several agricultural watersheds globally. As the largest river basin in China, the Yangtze River Basin has suffered from total phosphorus (TP) pollution in the past decade owing to diffuse pollution and aquatic ecology destruction, especially in the midstream tributaries and mid-lower reaches of the lakes. However, the transport dynamics of diffuse pollutants, such as phosphorus (P) from land to water bodies have not been well evaluated, which is of great significance for quantifying nutrient loss and its impact on water bodies. In this study, diffuse pollution estimation with remote sensing (DPeRS) model coupled with Soil and Water Assessment Tools (SWAT) was utilized to simulate the transport dynamics of P, investigate the spatial heterogeneity and P sources in the Poyang Lake Basin. Additionally, the P transport mechanism from land to water and the migration process in water bodies were considered to investigate the impact of each loss unit on the water body and evaluate the load generated by diverse pollution types. The estimated diffuse TP loss was 6016 t P·yr-1, and the load to inflow rivers and to Poyang Lake were 11,619 and 9812 t P·yr-1, respectively. Gan River Basin (51.09%) contributed most TP to Poyang Lake among five inflow rivers, while waterfront area demonstrated the highest TP load per unit area with 0.057 t km-2·yr-1. Our study also identified P sources in the sub-basins and emphasized agricultural diffuse sources, especially planting, as the most significant factor contributing to TP pollution. Additionally, to improve the aquatic environment and water ecological conditions, further nutrient management should be applied using a comprehensive approach that encompasses the entire process, from source transportation to the water body.

Pervasive soil phosphorus losses in terrestrial ecosystems in China.

Future phosphorus (P) shortages could seriously affect terrestrial productivity and food security. We investigated the changes in topsoil available P (AP) and total P (TP) in China's forests, grasslands, paddy fields, and upland croplands during the 1980s-2010s based on substantial repeated soil P measurements (63,220 samples in the 1980s, 2000s, and 2010s) and machine learning techniques. Between the 1980s and 2010s, total soil AP stock increased with a small but significant rate of 0.13 kg P ha-1 year-1 , but total soil TP stock declined substantially (4.5 kg P ha-1 year-1 ) in the four ecosystems. We quantified the P budgets of soil-plant systems by harmonizing P fluxes from various sources for this period. Matching trends of soil contents over the decades with P budgets and fluxes, we found that the P-surplus in cultivated soils (especially in upland croplands) might be overestimated due to the great soil TP pool compared to fertilization and the substantial soil P losses through plant uptake and water erosion that offset the P additions. Our findings of P-deficit in China raise the alarm on the sustainability of future biomass production (especially in forests), highlight the urgency of P recycling in croplands, and emphasize the critical role of country-level basic data in guiding sound policies to tackle the global P crises.

How a reservoir modulates downstream water quality under declining upstream loading and progressing climate change.

Reservoirs regulate water flow and pollutant transport in catchments. However, climate change can significantly impact their ability to perform this function. This study analysed a multi-decadal time series of data to examine the complex relationship between climate and nutrient pollution trends in the Möhne reservoir catchment. The study aimed at understanding the effect of the reservoir on downstream nutrient pollution in the face of a changing climate. The analysis revealed that upstream nutrient concentrations were higher than downstream, indicating a general nutrient-trapping effect of the reservoir. Upstream stations exhibited a declining trend in total nitrogen (TN) and total phosphorus (TP) concentrations. This was due to improved wastewater management and reduced nutrient mobilisation resulting from decreasing surface runoff and streamflow. At the downstream station, whereas TN concentrations decreased, TP concentrations mildly increased. These opposite downstream trends were likely due to rising temperatures and declining dissolved oxygen concentration within the reservoir, which might have favoured nitrogen denitrification and internal phosphorus loading, causing the decline and increase in downstream TN and TP concentrations, respectively. The contrasting downstream TN and TP trends alter the nutrient stoichiometry, which can profoundly affect the ecosystem's biogeochemical functioning. Therefore, in a warming climate, reservoirs may modulate nitrogen and phosphorus nutrients differently, leading to ecological discontinuities along river networks due to changes in TN-to-TP ratios. The study highlights the need to develop adaptable and precise nutrient pollution management strategies in reservoir catchments to address the challenges of climate change effectively.

Airport Deicers: An Unrecognized Source of Phosphorus Loading in Receiving Waters.

Airport ice control products contributed to total phosphorus (TP) loadings in a study of surface water runoff at a medium-sized airport from 2015 to 2021. Eleven airport ice control products had TP concentrations from 1-807 mg L-1 in liquid formulas, while solid pavement deicer had a TP concentration of 805 mg kg-1. Product application data, formula TP concentrations, and surface water sampling results were used to estimate TP concentration and loading contributions from these ice control products to receiving streams. Airport ice control products were found to contribute to TP in 84% of the water samples collected at downstream sites during deicing events, and TP concentrations at those sites exceeded aquatic life benchmarks in 70% of samples collected during deicing. A receiving stream 6 km downstream had TP attributed to airport ice control sources in 78% of the samples. TP loadings at an upstream site and the receiving stream site were greatest during the largest runoff events as is typical in urban runoff, but this pattern was not always followed at airport outfall sites due to the influence of TP in deicer products. Products analyzed in this study are used at airports across the United States and abroad, and findings suggest that airport deicers could represent a previously unrecognized source of phosphorus to adjacent waterways.

Study on H2SO4-modified corn straw biochar as substrate material of constructed wetland.

The high value resource utilization of corn straw is a long-term problem at present and in the future. Biochar preparation is an important utilization way of corn straw. The research on city tail water treated by constructed wetland (CW) with biochar was carried out to further increase the wastewater treatment capacity of the CW. Surface characterization, structural characteristics, and adsorption of straw biochar modified by different acids were measured. The study found that the ability of H2SO4 to remove ash from biochar was stronger than other acids and H2SO4-biochar was easy to be cleaned without H2SO4 residue. The performance of biochar modified by H2SO4 was obviously better than other acids, and the biochar adsorption was enhanced. The modification of biochar substrate modified by H2SO4 in CW reduced the change of electrical conductivity (EC) and promoted denitrification. H2SO4-modified biochar promoted the absorption of N and P by Iris pseudacorus L. The compound modification effect of straw biochar was obvious. The results revealed the acid modification characteristics of straw biochar, which were beneficial for increasing the wastewater treatment rate by CW. This study will promote the sustainable development of CW.

Evaluation of pollutant removal efficiency of urban stormwater wet ponds and the application of machine learning algorithms.

Wet ponds have been extensively used for controlling stormwater pollutants, such as sediment and nutrients, in urban watersheds. The removal of pollutants relies on a combination of physical, chemical, and biological processes. It is crucial to assess the performance of wet ponds in terms of removal efficiency and develop an effective modeling scheme for removal efficiency prediction to optimize water quality management. To achieve this, a two-year field program was conducted at two wet ponds in Calgary, Alberta, Canada to evaluate the wet ponds' performance. Additionally, machine learning (ML) algorithms have been shown to provide promising predictions in datasets with intricate interactions between variables. In this study, the generalized linear model (GLM), partial least squares (PLS) regression, support vector machine (SVM), random forest (RF), and K-nearest neighbors (KNN) were applied to predict the outflow concentrations of three key pollutants: total suspended solids (TSS), total nitrogen (TN), and total phosphorus (TP). Generally, the concentrations of inflow pollutants in the two study ponds are highly variable, and a wide range of removal efficiencies are observed. The results indicate that the concentrations of TSS, TN, and TP decrease significantly from the inlet to outlet of the ponds. Meanwhile, inflow concentration, rainfall characteristics, and wind are important indicators of pond removal efficiency. In addition, ML algorithms can be an effective approach for predicting outflow water quality: PLS, GLM, and SVM have shown strong potential to capture the dynamic interactions in wet ponds and predict the outflow concentration. This study highlights the complexity of pollutant removal dynamics in wet ponds and demonstrates the potential of data-driven outflow water quality prediction.

Analysis of the characteristics of major pollutants discharged from wastewater in China's provinces.

In recent years, the discharge of major pollutants in China's wastewater has been decreasing but remains at a high level. Controlling the discharge of pollutants in sewage is of great importance for protecting water quality and maintaining ecological balance. Based on data collected from 31 provinces in China from 2011 to 2020 (except 2018), this study analyzes the spatiotemporal variation emissions of the wastewater pollutants: chemical oxygen demand (COD), ammonia nitrogen (NH3-N), total nitrogen (TN), and total phosphorus (TP). The entropy method was used to evaluate the effectiveness of water pollution control in different provinces. Our results revealed that the total emission per gross domestic product (GDP) for COD, NH3-N, TN and TP in China decreased by 50.7%, 81.9%, 65.4% and 70.8%, respectively. In terms of regional annual emission differences, the Northwest region was the lowest compared with other regions, accounting for 4.87%-6.59% of the national pollutant emissions, and the Central China region was the highest, accounting for 22.4%-26.05% of the national pollutant emissions. The average value of pollutant emissions per unit of GDP decreased year-to-year overall, but Guangxi and Tibet showed a trend of first decreasing and then increasing. The correlation results indicated a significant correlation (0.977) between TN and TP emissions in wastewater in China during 2011-2020. Through clustering and Multidimensional Scaling model (MDS) analysis, Beijing and Shanghai have been performing well in controlling water pollution discharge, while the provinces of Tibet and Guangxi must still increase their efforts in water pollution control. Furthermore, these results demonstrate the experience and achievements of the Chinese government in the treatment of wastewater pollution and provide a useful reference for treatment of wastewater pollution in the world.

Measurement of Total Phosphorus and Polyphosphate in Chlamydomonas reinhardtii.

Phosphorus is an essential nutrient for plants. Green algae usually store excess P as polyphosphate (polyP) in the vacuoles. PolyP, a linear chain of three to hundreds of phosphate residues linked by phosphoanhydride bonds, is important for cell growth. Based on the previous method of polyP purification with silica gel columns (Werner et al., 2005; Canadell et al., 2016) in yeast cells, we developed a protocol to purify and determine the total P and polyP in Chlamydomonas reinhardtii by a quick, simplified, and quantitative method. We use hydrochloric acid or nitric acid to digest polyP or total P in dried cells and analyze P content using the malachite green colorimetric method. This method may be applied to other microalgae.

Biological processes in seagrass beds of coastal lagoons to maintain estuary-dependent marine fisheries.

Following the planned FAO Ecosystem Restoration Programme for estuarine habitats to support estuarine fisheries and early life stages of estuary-dependent marine fish, direct relationships of total seagrass and eelgrass Zostera m. capricorni areas and biomass with fish harvest were derived for a range of slightly to highly urbanized coastal lagoons that are expected to support the larvae and juveniles of estuary-dependent marine fisheries. Fish harvest and seagrass area and biomass in the lagoons increased with moderate catchment total suspended sediment and total phosphorus loads due to lagoon flushing rates directing excess silt and nutrients out to sea via the lagoon entrances. Well managed, sewered catchment management works are shown that could assist estuary managers maintain seagrass for estuarine and offshore estuary-dependent fisheries by maintenance of seagrass and fishery ecological processes. Further research is suggested to investigate estuary-dependent post-juveniles leaving estuaries and lagoons migrating to nearshore, offshore and shelf marine fisheries.

Exploration of the factors that influence total phosphorus in surface water and an evaluation of surface water vulnerability based on an advanced algorithm and traditional index method.

Due to the continuous influence of human activities, phosphorus pollution in surface water has become a persistent problem that needs to be addressed since phosphorous entails certain risks and degrees of damage to ecosystems and humans. The presence and accumulation of total phosphorus (TP) concentrations in surface waters is the result of a combined effect of many natural and anthropogenic factors, and it is often difficult to intuitively identify the individual importance of each factor in regard to the pollution of the aquatic environment. Considering these issues, this study provides a new methodology to better understand the vulnerability of surface water to TP pollution and the factors that influence TP pollution through the application of two modeling approaches. This includes the boosted regression tree (BRT), an advanced machine learning method, and the traditional comprehensive index method (CIM). Different factors, such as natural variables (including slope, soil texture, normalized difference vegetation index (NDVI), precipitation, and drainage density) and point and nonpoint source anthropogenic factors were included to model the vulnerability of surface water to TP pollution. Two methods were used to produce a vulnerability map of surface water to TP pollution. Pearson correlation analysis was used to validate the two vulnerability assessment methods. The results showed that BRT was more strongly correlated than CIM. In addition, the importance ranking results showed that slope, precipitation, NDVI, decentralized livestock farming and soil texture had a greater influence on TP pollution. Industrial activities, scale livestock farming and population density, which are all contributing sources of pollution, were all relatively less important. The introduced methodology can be used to quickly identify the area most vulnerable to TP pollution and to develop problem specific adaptive policies and measures to reduce the damage from TP pollution.

[Analysis of Influencing Factors of Chlorophyll-a in Lake Taihu Based on Bayesian Network].

Global warming has aggravated the problem of lake eutrophication. As a typical large, eutrophic, shallow lake in China, the issue of cyanobacterial harmful algal blooms (cyanoHABs) was particularly prominent in Lake Taihu. We took Lake Taihu as the study area, using the meteorological (temperature, wind speed, rainfall, and sunshine hours), water quality (total nitrogen, total phosphorus, conductivity, pH, and chemical oxygen demand), and biological (chlorophyll-a in phytoplankton) monitoring data from 1992 to 2020. We built a simulation model of chlorophyll-a based on the Bayesian network model with continuous variables to study the chlorophyll-a level of Lake Taihu under different meteorological and water quality conditions. The 75th percentile of chlorophyll-a concentration was used as the threshold to judge the risk of cyanobacterial bloom. When the probability of chlorophyll-a concentration below this threshold was greater than 75%, it was regarded as "low risk" of cyanobacterial bloom outbreak. The results showed that the average level of "temperature wind ratio" (ratio of air temperature to wind speed) in spring was 6.67℃·s·m-1, and the probability of high chlorophyll-a was less than 75% when the total phosphorus concentration was less than 0.130 mg·L-1. The average "temperature wind ratio" level in summer was 10.52℃·s·m-1, and the probability of high chlorophyll-a was less than 75% when the total phosphorus concentration was less than 0.257 mg·L-1. The average level of total phosphorus concentration in autumn was 0.154 mg·L-1, and the probability of high chlorophyll-a was less than 75% when the "temperature wind ratio" was less than 6.30℃·s·m-1. Based on the above research, the chlorophyll-a model constructed by the Bayesian network model with continuous variables was further used to simulate the nutrient control objectives under different climate change backgrounds. In order to control chlorophyll-a in Lake Taihu at the:"low risk" level of cyanoHABs, the target concentration thresholds of total phosphorus needed to be controlled under the climate level background from 1992 to 2000, 2001 to 2010, and 2011 to 2020 were given. From 1992 to 2000, the threshold value of total phosphorus concentration was 0.135 mg·L-1 in spring, 0.174 mg·L-1 in summer, and 0.171 mg·L-1 in autumn. From 2001 to 2010, the threshold value of total phosphorus concentration was 0.115 mg·L-1 in spring, 0.164 mg·L-1 in summer, and 0.162 mg·L-1 in autumn. From 2011 to 2020, the threshold value of total phosphorus concentration was 0.059 mg·L-1 in spring, 0.145 mg·L-1 in summer, and 0.145 mg·L-1 in autumn. The results showed that the control of cyanoHABs in eutrophic lakes required more stringent nutrient control strategies with global warming. It provided a reference for preventing and controlling cyanoHABs and eutrophication in Lake Taihu. Previous studies have used multiple regression models, hydrodynamic numerical models, and other methods to predict chlorophyll-a concentrations or cyanobacterial blooms in lakes. However, there has been no study on the prediction of cyanoHABs in lakes based on the Bayesian network model with continuous variables and the "dynamic" evaluation of nutrient thresholds. Therefore, based on the seasonal meteorological, water quality, and biological monitoring data of Lake Taihu from 1992 to 2020, the chlorophyll-a model of Lake Taihu was constructed for the first time based on the Bayesian network model with continuous variables to simulate the chlorophyll-a concentration of Lake Taihu under different climate indicators and total phosphorus concentrations. The weight of its influencing factors was also analyzed, and the nutrient control objectives under different climate scenarios were "dynamically" evaluated.

Efficient protection of the Baltic Sea needs a revision of phosphorus metric.

Eutrophication of the Baltic Sea is driven by phosphorus and nitrogen. While the anthropogenic point source loads of both nutrients have decreased markedly, further reductions are needed. This is true particularly for phosphorus, as highlighted by its stringent abatement targets in HELCOM's Baltic Sea Action Plan. To meet the targets, more results need to be achieved in non-point source abatement, specifically from agricultural sources. The growing pressure for phosphorus abatement from agriculture may lead to environmentally and economically inefficient outcomes unless we account for the variability in how different forms of phosphorus respond to abatement measures, and how these forms contribute to eutrophication. The precautionary and efficiency improving way to advance policies is to either replace or supplement the Total Phosphorus metric with a metric more accurate in reflecting the biologically available phosphorus. This policy fix becomes more important as the relative share of agricultural emissions of total pollution increases.

Sediments are important in regulating the algae-derived off-flavor (ß-cyclocitral) in eutrophic lakes.

In recent years, due to global warming and water eutrophication, cyanobacterial blooms have occurred frequently worldwide, resulting in a series of water quality problems, among which the odor problem in lakes is one of the focuses of attention. In the late stage of the bloom, a large amount of algae accumulated on the surface sediment, which will be a great hidden danger to cause odor pollution in lakes. ß-Cyclocitral is one of the typical algae-derived odor compounds that cause odor in lakes. In this study, an annual survey of 13 eutrophic lakes in the Taihu Lake basin was investigated to assess the effects of abiotic and biotic factors on ß-cyclocitral in water. Our results showed that high concentrations of ß-cyclocitral in the pore water (pore-ß-cyclocitral) were detected in the sediment and far exceeded that in the water column, with an average of about 100.37 times. Structural equation modeling indicated that algal biomass and pore-ß-cyclocitral can directly regulate the concentrations of ß-cyclocitral in the water column, and total phosphorus (TP) and temperature (Temp) promoted the algal biomass which further enhanced the production of ß-cyclocitral both in the water column and pore water. It was worth noting that when Chla ≥30 µg/L, the effects of algae on pore-ß-cyclocitral were significantly enhanced, and pore-ß-cyclocitral played a major role in the regulation of ß-cyclocitral concentrations in water column. Overall, our study facilitated a comprehensive and systematic understanding of the effects of algae on odorants and the dynamic regulatory processes in complex aquatic ecosystems, and revealed a long-neglected process, that was, the important contribution of sediments to ß-cyclocitral in the water column in eutrophic lakes, which would conduce to a more accurate understanding of the evolution of off flavors in lakes and also useful for the management of odors in lakes in the future.

Use of Microbial Fuel Cells for the Treatment of Residue Effluents Discharged from an Anaerobic Digester Treating Food Wastes.

One of practical challenges in anaerobic-digestion (AD) technology is the cost-effective treatment of residue effluents containing high concentrations of organics, nitrogen and phosphorus (CNP). In order to evaluate the utility of microbial fuel cells (MFCs) for treating anaerobic-digester effluents (ADEs) and generating power from them, laboratory-scale single-chamber MFCs were filled with ADE obtained from a commercial AD plant treating food wastes and thereafter operated by routinely supplying ADE at different hydraulic residence times (HRTs, 5 to 20 days). It is shown that MFCs were able to reduce not only organics in ADE but also nitrogen and phosphorus. For instance, data demonstrated that over 50% of CNP was removed in MFCs operated at an HRT of 10 days, at which the maximum power density reached over 200 mW m-2 (based on the projected area of anode). Metabarcoding of 16S rRNA genes showed that some bacteria were specifically enriched in anode biofilms, suggesting their involvement in power generation. Our study suggests that MFCs are applicable to reducing CNP in ADEs at reasonable rates, and provides subsequent work with fundamental data useful for setting targets for further developments.