An Intelligent Early Warning System for Harmful Algal Blooms: Harnessing the Power of Big Data and Deep Learning.

Harmful algal blooms (HABs) pose a significant ecological threat and economic detriment to freshwater environments. In order to develop an intelligent early warning system for HABs, big data and deep learning models were harnessed in this study. Data collection was achieved utilizing the vertical aquatic monitoring system (VAMS). Subsequently, the analysis and stratification of the vertical aquatic layer were conducted employing the "DeepDPM-Spectral Clustering" method. This approach drastically reduced the number of predictive models and enhanced the adaptability of the system. The Bloomformer-2 model was developed to conduct both single-step and multistep predictions of Chl-a, integrating the " Alert Level Framework" issued by the World Health Organization to accomplish early warning for HABs. The case study conducted in Taihu Lake revealed that during the winter of 2018, the water column could be partitioned into four clusters (Groups W1-W4), while in the summer of 2019, the water column could be partitioned into five clusters (Groups S1-S5). Moreover, in a subsequent predictive task, Bloomformer-2 exhibited superiority in performance across all clusters for both the winter of 2018 and the summer of 2019 (MAE: 0.175-0.394, MSE: 0.042-0.305, and MAPE: 0.228-2.279 for single-step prediction; MAE: 0.184-0.505, MSE: 0.101-0.378, and MAPE: 0.243-4.011 for multistep prediction). The prediction for the 3 days indicated that Group W1 was in a Level I alert state at all times. Conversely, Group S1 was mainly under an Level I alert, with seven specific time points escalating to a Level II alert. Furthermore, the end-to-end architecture of this system, coupled with the automation of its various processes, minimized human intervention, endowing it with intelligent characteristics. This research highlights the transformative potential of integrating big data and artificial intelligence in environmental management and emphasizes the importance of model interpretability in machine learning applications.

Simulating chlorophyll-a fluorescence changing rate and phycocyanin fluorescence by using a multi-sensor system in Lake Taihu, China.

Algal pollution in water sources has posed a serious problem. Estimating algal concentration in advance saves time for drinking water plants to take measures and helps us to understand causal chains of algal dynamics. This paper explores the possibility of building a short-term algal early warning model with online monitoring systems. In this study, we collected high-frequency data for water quality and weather conditions in shallow and eutrophic Lake Taihu by an in situ multi-sensor system (BIOLIFT) combined with a weather station. Extracted chlorophyll-a from water samples and chlorophyll-a fluorescence differentiated according to different algal classeses verified that chlorophyll-a fluorescence continuously measured by BIOLIFT only represent chlorophyll-a of green algae and diatoms. Stepwise linear regression was used to simulate the chlorophyll-a fluorescence changing rate of green algae and diatoms together (ΔChla-f%) and phycocyanin fluorescence concentration (blue-green algae) on the water surface layer (CyanoS). The results show that nutrients (total N, NO3-N, NH4-N, total P) were not necessary parameters for short-term algal models. ΔChla-f % is greatly influenced by the seasons, so seasonal partition of data before modeling is highly recommended. CyanoSmax and ΔChla-f% were simulated by only using multi-sensor and meteorological data (R2 = 0.73; 0.75). All the independent variables (wave, water temperature, relative humidity, depth, cloud cover) used in the model were measured online and predictable. Wave height is the most important independent variable in the shallow lake. This paper offers a new approach to simulate and predict the algal dynamics, which also can be applied in other surface water.

Identifying spatio-temporal dynamics of trace metals in shallow eutrophic lakes on the basis of a case study in Lake Taihu, China.

In shallow eutrophic lakes, metal remobilization is closely related to the resuspension and eutrophication. An improved understanding of metal dynamics by biogeochemical processes is essential for effective management strategies. We measured concentrations of nine metals (Cr, Cu, Zn, Ni, Pb, Fe, Al, Mg, and Mn) in water and sediments during seven periods from 2014 to 2018 in northern Lake Taihu, to investigate the metal pollution status, spatial distributions, mineral constituents, and their interactions with P. Moreover, an automatic weather station and online multi-sensor systems were used to measure meteorological and physicochemical parameters. Combining these measurements, we analyzed the controlling factors of metal dynamics. Shallow and eutrophic northern Lake Taihu presents more serious metal pollution in sediments than the average of lakes in Jiangsu Province. We found chronic and acute toxicity levels of dissolved Pb and Zn (respectively), compared with US-EPA "National Recommended Water Quality Criteria". Suspended particles and sediment have been polluted in different degrees from uncontaminated to extremely contaminated according to German pollution grade by LAWA (Bund/Länder-Arbeitsgemeinschaft Wasser). Polluted particles might pose a risk due to high resuspension rate and intense algal activity in shallow eutrophic lakes. Suspended particles have similar mineral constituents to sediments and increased with increasing wind velocity. Al, Fe, Mg, and Mn in the sediment were rarely affected by anthropogenic pollution according to the geoaccumulation index. Among them, Mn dynamics is very likely associated with algae. Micronutrient uptake by algal will affect the migration of metals and intensifies their remobilization. Intensive pollution of most particulate metals were in the industrialized and down-wind area, where algae form mats and decompose. Moreover, algal decomposition induced low-oxygen might stimulate the release of metals from sediment. Improving the eutrophication status, dredging sediment, and salvaging cyanobacteria biomass are possible ways to remove or reduce metal contaminations.

Enhanced removal of antimony in dyeing wastewater by mixing Fe3 O4 with manganese sand filter material.

Wastewaters from the printing and dyeing industries contain many contaminants in particular antimony (Sb) that end up in the environment. Both manganese sand filter and Fe3 O4 have good removal effect on Sb, and are cheap and easy to obtain. We made a filter material by mechanically mixing the manganese sand filter material and ferro-ferric oxide (Fe3 O4 ). The Fe-Mn oxide filter material was analyzed by X-ray diffraction. We studied the filtration of real wastewater from a dyeing wastewater resource recovery facility in Suzhou, China, containing Sb at high concentration of 410 µg/L, using dynamic tests in adsorption columns during 7 days. We tested the effects of filter material volume filling ratio, the empty bed contact time (EBCT), pH, and back washing on the removal of Sb. Results show that the addition of Fe3 O4 enhanced the removal of Sb, reaching 85% of initial Sb. When the initial influent pH of the raw water is 3.0, the volume filling ratio of filter material is 60%, the EBCT is 20 min, and the developed dynamic Fe-Mn oxide filter has the best removal effect on Sb. Daily back washing of the filter keeps a Sb removal rate of about 80%. PRACTITIONER POINTS: A novel and cheap Fe-Mn oxide was developed for Sb removal from dyeing wastewater. A self-designed filter device was designed to verify performance of the low-cost material. Optimal design and operational parameters of the filtration process were determined.

Effects of hairy crab breeding on drinking water quality in a shallow lake.

The Yangcheng Lake, connected to Taihu, is partly served as drinking water source for Suzhou, China; the temporal and spatial changes of water quality parameters of it are investigated in this study. The Yangcheng Middle Lake with aquaculture area and the Yangcheng East Lake with important water intake are chosen to make a comparative investigation of the relationship between crab breeding and water quality. Phytoplankton community and the composition of dissolved organic matters (DOM) at different areas of the Yangcheng Lake are characterized with spectral fluorescence signatures. Results reveal that biopolymers and humic substances (HS) are the two major DOM compositions in the Yangcheng Lake. In the Yangcheng Middle Lake, the CODMn concentration at the large breeding area was lower than that in most other areas; while the concentration of algae and HS fluorescence intensity are positively correlated with each other in the Yangcheng Middle Lake. Crab breeding could accelerate nitrogen transformation and utilization. In summer and winter, the cumulative risk of building up potential harmful by-products such as DPBs caused by the biopolymers and HS is greater; the breeding of hairy crabs could reduce biopolymers and improve drinking water safety.

Highly time-resolved analysis of seasonal water dynamics and algal kinetics based on in-situ multi-sensor-system monitoring data in Lake Taihu, China.

Predicting algal blooms is challenging due to rapid growth rates under suitable conditions and the complex physical, chemical, and biological processes involved. Physico-chemical parameters, monitored in this study by a high-resolution in-situ multi-sensor system and derived from lab-based water sample analyses, show the seasonal variation and have different degrees of vertical gradients across the water column. Through analyzing the changes and relations between multi-factors, we reveal pictures of water quality dynamics and algal kinetics. Nitrate has regular seasonal changes different to the seasonal patterns of total dissolved Phosphorus. Positive correlations are found between Chlorophyll a fluorescence and temperature, wind-induced resuspension and mixing promote the augment of Cyanobacteria fluorescence (Phycocyanin) signal. While the resuspension can also result in the increase of turbidity and affect the light environment for hydrophytes, the algal scums are the main reason for the high turbidity on the surface, which lower the illumination radiation in the water body. Those parameters are the primary dominants responsible for the change of algae from our monitoring data, which could be used as indicators for the dynamic changes of algae in the future.

Hyperspectral Data and Machine Learning for Estimating CDOM, Chlorophyll a, Diatoms, Green Algae and Turbidity.

Inland waters are of great importance for scientists as well as authorities since they are essential ecosystems and well known for their biodiversity. When monitoring their respective water quality, in situ measurements of water quality parameters are spatially limited, costly and time-consuming. In this paper, we propose a combination of hyperspectral data and machine learning methods to estimate and therefore to monitor different parameters for water quality. In contrast to commonly-applied techniques such as band ratios, this approach is data-driven and does not rely on any domain knowledge. We focus on CDOM, chlorophyll a and turbidity as well as the concentrations of the two algae types, diatoms and green algae. In order to investigate the potential of our proposal, we rely on measured data, which we sampled with three different sensors on the river Elbe in Germany from 24 June⁻12 July 2017. The measurement setup with two probe sensors and a hyperspectral sensor is described in detail. To estimate the five mentioned variables, we present an appropriate regression framework involving ten machine learning models and two preprocessing methods. This allows the regression performance of each model and variable to be evaluated. The best performing model for each variable results in a coefficient of determination R 2 in the range of 89.9% to 94.6%. That clearly reveals the potential of the machine learning approaches with hyperspectral data. In further investigations, we focus on the generalization of the regression framework to prepare its application to different types of inland waters.

Simulation-based assessment of the impact of fertiliser and herbicide application on freshwater ecosystems at the Three Gorges Reservoir in China.

Dams have profound impacts on river ecosystems, amongst them inundation of land, altered dynamics of the water body or uprising reservoir backwaters influencing tributary or upstream river sections. Along the outstandingly ecologically important Yangtze River in China, the Three Gorges Reservoir (TGR) is the largest project, covering an area of 1080 km2. From the beginning, the dam-project came in for criticism on increasing environmental risks due to sub-merging former industrial and urban areas. We simulated dynamics of biotic and abiotic components of the TGR ecosystem (trophic guilds of aquatic organisms, hydrodynamics, nutrients), as well as the behaviour of the herbicidal substance propanil and its metabolites 3,4-Dichloroaniline (DCA) and 3,3',4,4'-tetrachloroazoxybenzene (TCAB). A modelling environment, provided by the AQUATOX software, was adapted to the specific situation at a tributary reach to the Yangtze river 'Daning River'. As the simulated food web contained several interconnected trophic levels, a significant biomagnification of metabolites was demonstrated by our simulation studies. In particular, newly emerging stagnant downstream sections of tributaries exhibited high probabilities due to accumulating pesticides from upstream sources. The common problem of algal blooms in the TGR-region was addressed by dose-response simulation experiments with essential nutrients. Impacts on structure and abundance of populations of aquatic organisms were shown. However, even high nutrient loads resulted in only slight changes of densities of organisms of all trophic levels. Nevertheless, the probabilities for large-scale algal blooms affecting drinking water quality were considered low because of high flow velocities and discharge rates towards the Yangtze River. We see high potential of simulation-based assessments that provide information for risk managers dealing with whole catchment areas. They are put in the position to differentiate the magnitude of impacts of various factors and decide about the most effective remediation measures.

On the complexity of measuring forests microclimate and interpreting its relevance in habitat ecology: the example of Ixodes ricinus ticks.

BACKGROUND: Ecological field research on the influence of meteorological parameters on a forest inhabiting species is confronted with the complex relations between measured data and the real conditions the species is exposed to. This study highlights this complexity for the example of Ixodes ricinus. This species lives mainly in forest habitats near the ground, but field research on impacts of meteorological conditions on population dynamics is often based on data from nearby official weather stations or occasional in situ measurements. In addition, studies use very different data approaches to analyze comparable research questions. This study is an extensive examination of the methodology used to analyze the impact of meteorological parameters on Ixodes ricinus and proposes a methodological approach that tackles the underlying complexity. METHODS: Our specifically developed measurement concept was implemented at 25 forest study sites across Baden-Württemberg, Germany. Meteorological weather stations recorded data in situ and continuously between summer 2012 and autumn 2015, including relative humidity measures in the litter layer and different heights above it (50 cm, 2 m). Hourly averages of relative humidity were calculated and compared with data from the nearest official weather station. RESULTS: Data measured directly in the forest can differ dramatically from conditions recorded at official weather stations. In general, data indicate a remarkable relative humidity decrease from inside to outside the forest and from ground to atmosphere. Relative humidity measured in the litter layer were, on average, 24% higher than the official data and were much more balanced, especially in summer. CONCLUSIONS: The results illustrate the need for, and benefit of, continuous in situ measurements to grasp the complex relative humidity conditions in forests. Data from official weather stations do not accurately represent actual humidity conditions in forest stands and the explanatory power of short period and fragmentary in situ measurements is extremely limited. However, it is still an open question to what kind of meteorological data are necessary to answer specific questions in tick research. The comparison of research findings was hindered by the variety of information provided, which is why we propose details for future reporting.

Long term (1997-2014) spatial and temporal variations in nitrogen in Dongting Lake, China.

In order to protect the water quality of Dongting Lake, it is significant to find out its nitrogen pollution characteristics. Using long-term monthly to seasonally data (1997-2014), we investigated the spatial and temporal variations in nitrogen in Dongting Lake, the second largest freshwater lake in China. The average concentrations of total nitrogen (TN) in the eastern, southern, and western parts of the lake were 1.77, 1.56, and 1.35 mg/L, respectively, in 2014. TN pollution was generally worse in the southern area than in the western area. Concentrations showed temporal variation, and were significantly higher during the dry season than during the wet season. Based on the concentration and growth rate of TN, three different stages were identified in the long term lake data, from 1997 to 2002, from 2003 to 2008, and from 2009 to 2014, during which the concentrations and the growth rate ranged from 1.09-1.51 mg/L and 22.09%-40.03%, 1.05-1.57 mg/L and -9.05%-7.74%, and 1.68-2.02 mg/L and 57.99%-60.41%, respectively. The main controls on the lake water TN concentrations were the quality and quantity of the lake inflows, spatial and temporal variations in hydrodynamic conditions within the lake (flow velocity, flow direction), and point and nonpoint inputs from human activities. Diffuse nutrient losses from agricultural land are a significant contributor. As a priority, the local government should aim to control the pollutant inputs from upstream and non-point nutrient losses from land.

Since 2015 the SinoGerman research project SIGN supports water quality improvement in the Taihu region, China.

The Taihu (Tai lake) region is one of the most economically prospering areas of China. Due to its location within this district of high anthropogenic activities, Taihu represents a drastic example of water pollution with nutrients (nitrogen, phosphate), organic contaminants and heavy metals. High nutrient levels combined with very shallow water create large eutrophication problems, threatening the drinking water supply of the surrounding cities. Within the international research project SIGN (SinoGerman Water Supply Network, www.water-sign.de), funded by the German Federal Ministry of Education and Research (BMBF), a powerful consortium of fifteen German partners is working on the overall aim of assuring good water quality from the source to the tap by taking the whole water cycle into account: The diverse research topics range from future proof strategies for urban catchment, innovative monitoring and early warning approaches for lake and drinking water, control and use of biological degradation processes, efficient water treatment technologies, adapted water distribution up to promoting sector policy by good governance. The implementation in China is warranted, since the leading Chinese research institutes as well as the most important local stakeholders, e.g. water suppliers, are involved.

Sulfur Cycling-Related Biogeochemical Processes of Arsenic Mobilization in the Western Hetao Basin, China: Evidence from Multiple Isotope Approaches.

The role of sulfur cycling in arsenic behavior under reducing conditions is not well-understood in previous investigations. This study provides observations of sulfur and oxygen isotope fractionation in sulfate and evaluation of sulfur cycling-related biogeochemical processes controlling dissolved arsenic groundwater concentrations using multiple isotope approaches. As a typical basin hosting high arsenic groundwater, the western Hetao basin was selected as the study area. Results showed that, along the groundwater flow paths, groundwater δ34SSO4, δ18OSO4, and δ13CDOC increased with increases in arsenic, dissolved iron, hydrogen sulfide and ammonium concentrations, while δ13CDIC decreased with decreasing Eh and sulfate/chloride. Bacterial sulfate reduction (BSR) was responsible for many of these observed changes. The δ34SSO4 indicated that dissolved sulfate was mainly sourced from oxidative weathering of sulfides in upgradient alluvial fans. The high oxygen-sulfur isotope fractionation ratio (0.60) may result from both slow sulfate reduction rates and bacterial disproportionation of sulfur intermediates (BDSI). Data indicate that both the sulfide produced by BSR and the overall BDSI reduce arsenic-bearing iron(III) oxyhydroxides, leading to the release of arsenic into groundwater. These results suggest that sulfur-related biogeochemical processes are important in mobilizing arsenic in aquifer systems.

Evaluation of impact factors on PM2.5 based on long-term chemical components analyses in the megacity Beijing, China.

Nine years of sampling and analyses of fine particles (PM2.5) were performed in Beijing from 2005 to 2013. Twenty-seven chemical elements and black carbon (BC) in PM2.5 were analyzed in order to study chemical characteristics and temporal distribution of Beijing aerosols. Principle component analysis defined different types of elemental sources, based on which, the influences of a variety of anthropogenic activities including governmental intervention measures and natural sources on air quality were evaluated. For the first time, Ga is used as a tracer element for heating activities mainly using coal in Beijing, due to its correlation with BC and coal combustion, as well as its concentration variation between the heating- and non-heating periods. The traffic restrictions effectively reduced emissions of relevant heavy metals such as As, Cd, Sn and Sb. The expected long-term effectiveness of the steel smelters relocation was not observed due to the nearby relocation with increased capacity. Firework display during every Chinese spring festival season and special events such as the Olympic Games resulted in several times higher concentrations of K, Sr and Ba than other days and thus they were proposed as tracers for firework display. The impacts of all these factors were quantified and evaluated. Sand dust or dust storms induced higher concentrations of geogenic elements in PM2.5 compared to non-dust days. Sustainable mitigation measures, such as traffic restrictions, are necessary to be continued and improved to obtain more "blue sky" days in the future.

Long-term variation of black carbon and PM2.5 in Beijing, China with respect to meteorological conditions and governmental measures.

Black carbon (BC) and PM2.5 were studied for nine years from 2005 to 2013 in the Beijing urban area. The overall weekly average mass concentrations of BC and PM2.5 were 4.3 and 66.8 µg/m³. PM2.5 annual means of the nine years are around 2 times of the standard (GB3095-2012) in China, and are 5-7 times higher than the WHO standard. The Beijing Olympic Games in 2008 was a milestone to mitigate aerosol pollution. Temporal distribution of BC shows a distinct declining trend, and annual mean mass concentrations of PM2.5 after 2008 were lower than those before 2008 but increased from 2011 to 2013. Wind rose plots show that high BC concentrations are usually associated with low wind speed of northeastern or southwestern winds, generally causing poor visibility. Governmental mitigation measures such as traffic restriction despite increased motor vehicle numbers and gasoline consumption and industry relocation with declining consumption of coal and coke were successful in reducing BC emissions. Annual mean of BC was reduced by 38% in 2013 compared to 2005. However, BC contamination in Beijing is still severe when compared to other urban areas around the world.

Estimating Ixodes ricinus densities on the landscape scale.

BACKGROUND: The study describes the estimation of the spatial distribution of questing nymphal tick densities by investigating Ixodes ricinus in Southwest Germany as an example. The production of high-resolution maps of questing tick densities is an important key to quantify the risk of tick-borne diseases. Previous I. ricinus maps were based on quantitative as well as semi-quantitative categorisations of the tick density observed at study sites with different vegetation types or indices, all compiled on local scales. Here, a quantitative approach on the landscape scale is introduced. METHODS: During 2 years, 2013 and 2014, host-seeking ticks were collected each month at 25 sampling sites by flagging an area of 100 square meters. All tick stages were identified to species level to select nymphal ticks of I. ricinus, which were used to develop and calibrate Poisson regression models. The environmental variables height above sea level, temperature, relative humidity, saturation deficit and land cover classification were used as explanatory variables. RESULTS: The number of flagged nymphal tick densities range from zero (mountain site) to more than 1,000 nymphs/100 m(2). Calibrating the Poisson regression models with these nymphal densities results in an explained variance of 72 % and a prediction error of 110 nymphs/100 m(2) in 2013. Generally, nymphal densities (maximum 374 nymphs/100 m(2)), explained variance (46 %) and prediction error (61 nymphs/100 m(2)) were lower in 2014. The models were used to compile high-resolution maps with 0.5 km(2) grid size for the study region of the German federal state Baden-Württemberg. The accuracy of the mapped tick densities was investigated by leave-one-out cross-validation resulting in root-mean-square-errors of 227 nymphs/100 m(2) for 2013 and 104 nymphs/100 m(2) for 2014. CONCLUSIONS: The methodology introduced here may be applied to further tick species or extended to other study regions. Finally, the study is a first step towards the spatial estimation of tick-borne diseases in Central Europe.

The influence of governmental mitigation measures on contamination characteristics of PM(2.5) in Beijing.

Beijing, the capital of China, has become one of the most air-polluted cities due to its rapid economic growth. Weekly PM2.5 samples-collected continuously from 2007 to 2010-were used to study the contamination characteristics of atmospheric particles and effects of governmental mitigation measures especially since the 2008 Summer Olympic Games. PM2.5 mass concentrations during the sampling period were reduced compared to the previous studies before 2005, although they were still too high in comparison with environmental standards of China and many other countries as well as WHO standards. Results of principle component analysis show that elements of primary anthropogenic origin had an obvious decline while elements mainly from the natural environment kept a relatively stable course. The governmental macro-control measures influenced both anthropogenic and geogenic sources, but they also led to some pollution peaks prior to implementation of the respective measures. Some element concentrations correlated to the restrictiveness of relative measures, especially during different traffic restrictions. The comparison with other countries and international standards shows that there is a long way to go in order to improve air quality in Beijing, and that governmental mitigation measures need to be continued and reinforced.

Three Gorges Reservoir: density pump amplification of pollutant transport into tributaries.

The impoundment of the Three Gorges Reservoir (TGR) on the Yangtze River in China burdened its tributary backwaters with severe environmental problems.1 Confluence zones of reservoir tributaries with the Yangtze River main channel are main drivers of pollutant dynamics in the TGR2 and are thus keys to develop mitigation measures. Here, we show a novel experimental approach of spatiotemporal water quality analysis to trace water mass movements and identify pollutant transport pathways in reservoir water bodies. Our results show the movements of density currents in a major tributary backwater of the TGR. A huge interflow density current from the Yangtze River main channel transported its heavy metal carriage to the upstream reaches of the tributary backwater. Water from the upstream backwater moved counterwise and carried less but pollutant-enriched suspended sediments. This scenario illustrates the importance of confluence zone hydrodynamics for fates and pathways of pollutants through the widely unknown hydrodynamics of new reservoirs.

Spatio-temporal variations of black carbon concentrations in the Megacity Beijing.

The spatial and temporal distribution and the flux of black carbon (BC) concentration in Beijing were continuously investigated over a two-year period at five sites to highlight the relative influence of contributing sources. The results demonstrate firstly that there is significant spatio-temporal variability of BC in Beijing. Highest concentrations occurred during winter primarily due to stagnant meteorological conditions, and seasonal BC sources, such as coal combustion for heating purposes. Biomass burning was identified as a minor seasonal source during the summer months. BC also varied spatially with higher concentrations in the SE of Beijing and lower concentrations in the NW, due to the differing emission intensity of various local BC sources such as traffic and industry. Frequently, overnight BC concentrations were higher due to specific meteorological conditions, such as the lower urban mixing layer height and various anthropogenic activities, such as exclusive night-time heavy duty vehicle traffic in the inner-city.

Preparative separation of arsenate from phosphate by IRA-400 (OH) for oxygen isotopic work.

The paper reports about a series of tests carried out to find out the optimal conditions for the preparative separation of arsenate and phosphate from natural waters, using the anion exchange resin Amberlite IRA-400 (OH). Freundlich isotherms have been constructed on basis of data obtained by stirring different amounts of resin (0.05-1.00 g) with solutions containing 1mg/L As and 10mg/L P in form of arsenate and phosphate and the effect of pH and P/As ratio on adsorption was investigated. It was found that at these concentrations 0.5 g of IRA-400 (OH) can adsorb quantitatively arsenate and phosphate within 1h. In a range of 3.6-11.1, pH seems to have no influence on the adsorption behavior of the resin, but at pH 1.5 the adsorption of both arsenate and phosphate drops to values close to zero. Experiments with solutions with P/As ratios in a range between 1 and 30 have shown that the concentration ratios have also little effect on adsorption. An efficient selective desorption of the anions could be achieved with 2 mol/L HNO3 or HCl, but the use of HCl is impracticable if the separation aims at precipitating arsenate for oxygen isotopic work. The reported adsorption/ desorption properties of the resin are supported also by data obtained by investigating the resin particles with a scanning electron microscope equipped with a fluorescence detection device.

An integrated approach to model the biomagnification of organic pollutants in aquatic food webs of the Yangtze Three Gorges Reservoir ecosystem using adapted pollution scenarios.

The impounding of the Three Gorges Reservoir (TGR) at the Yangtze River caused large flooding of urban, industrial, and agricultural areas, and profound land use changes took place. Consequently, substantial amounts of organic and inorganic pollutants were released into the reservoir. Additionally, contaminants and nutrients are entering the reservoir by drift, drainage, and runoff from adjacent agricultural areas as well as from sewage of industry, aquacultures, and households. The main aim of the presented research project is a deeper understanding of the processes that determines the bioaccumulation and biomagnification of organic pollutants, i.e., mainly pesticides, in aquatic food webs under the newly developing conditions of the TGR. The project is part of the Yangtze-Hydro environmental program, financed by the German Ministry of Education and Science. In order to test combinations of environmental factors like nutrients and pollution, we use an integrated modeling approach to study the potential accumulation and biomagnification. We describe the integrative modeling approach and the consecutive adaption of the AQUATOX model, used as modeling framework for ecological risk assessment. As a starting point, pre-calibrated simulations were adapted to Yangtze-specific conditions (regionalization). Two exemplary food webs were developed by a thorough review of the pertinent literature. The first typical for the flowing conditions of the original Yangtze River and the Daning River near the city of Wushan, and the second for the stagnant reservoir characteristics of the aforementioned region that is marked by an intermediate between lake and large river communities of aquatic organisms. In close cooperation with German and Chinese partners of the Yangtze-Hydro Research Association, other site-specific parameters were estimated. The MINIBAT project contributed to the calibration of physicochemical and bathymetric parameters, and the TRANSMIC project delivered hydrodynamic models for water volume and flow velocity conditions. The research questions were firstly focused on the definition of scenarios that could depict representative situations regarding food webs, pollution, and flow conditions in the TGR. The food webs and the abiotic site conditions in the main study area near the city of Wushan that determine the environmental preconditions for the organisms were defined. In our conceptual approach, we used the pesticide propanil as a model substance.