Average Concentrations Of Total Nitrogen Research Articles

A pilot-scale anoxic-anaerobic-anoxic-oxic combined with moving bed biofilm reactor system for advanced treatment of rural wastewater

Rural domestic poses a significant challenge to treatment technologies due to significant fluctuations in both water quality, particularly in terms of carbon concentration, and quantity. Conventional biological technology, such as anaerobic-anoxic-oxic (A2O) systems, is inefficient. In this work, a continuous pilot-scale anoxic-anaerobic-anoxic-oxic (A3O) reactor with a moving bed biofilm reactor (MBBR) system was constructed and optimized to improve the treatment efficiency of rural domestic wastewater. The sludge return ratio, volume ratio of the oxic-to-anoxic zone (Voxi/Vano), step-feeding and hydraulic retention time (HRT) at low temperature were considered the main parameters for optimization. Microbial analysis was performed on both the mixed liquor and carrier of the A3O-MBBR system under initial and post-optimized conditions. The results indicated that the A3O-MBBR improved the treatment efficiency of rural domestic wastewater, especially for total phosphorus (TP), which increased by 20 % compared with that of the A2O-MBR. In addition, the removal efficiencies of nitrogen and phosphorus were further optimized, and the average concentrations of total nitrogen (TN) and TP in the effluent reached 2.46 and 0.364 mg/L, respectively, at a sludge reflux ratio of 100 or 150 %, Voxi/Vano =200 %, step-feeding of 0.5Q/0.5Q (anaerobic/anoxic) and HRT of 15 h at low temperature in the A3O-MBBR, which met standard A of GB18918–2002, China (TN < 15 mg/L, TP < 0.5 mg/L). The average rate of attaining the standard increased by 58.63 % (post optimization). The microbial analysis showed an increase in species diversity and richness after the parameters were optimized. Moreover, compared to the microbial community structure before optimization, the post-optimization exhibited a more stable microbial structure with a significant enrichment of functional bacteria. Defluviimonas, Novosphingobium and Bifidobacterium, considered as the dominant nitrification or denitrifying bacteria, were enriched in the suspended sludge of the MBBR reactor, which the relative abundance increased by 3.11 %, 3.84 %, and 3.24 %, respectively. Further analysis of the microbial community in the carrier revealed that the abundance of Nitrospira and the denitrifying bacteria carried by the carrier were much greater than those in the suspended sludge. Consequently, the microorganism cooperation between suspended sludge and biofilm might be responsible for the improved performance of the optimized A3O-MBBR.

Effects of storm runoff on the spatial-temporal variation and stratified water quality in Biliuhe Reservoir, a drinking water reservoir.

Stormflow runoff is an important non-point source of pollution in drinking water reservoirs. Storm runoff is usually very turbid and contains a high concentration of organic matter, therefore affecting water quality when it enters reservoirs. In order to investigate the impact of storm runoff on spatial-temporal variation and stratification of water quality during this rainstorm event, the inflow process of the storm runoff was studied through a combination of field investigation and simulation using the Delft3D-Flow model. Water samples were collected from Biliuhe Reservoir at four different periods: before storm runoff, storm runoff flood peak period, 1week after storm runoff, and 5weeks after storm runoff. The results showed that the input of storm runoff resulted in a significant increase in the nitrogen (N) and phosphorus (P) in the reservoir water, especially in the reservoir entrance. The concentrations of total nitrogen (TN) and total phosphorus (TP) gradually decreased after the flood peak period; however, the average concentrations of TN and TP in the entire reservoir remained higher than those before the storm runoff levels for an extended duration. The storm runoff will greatly contribute to the contamination of water quality in a reservoir, and the water quality cannot be quickly restored by self-purification in the short term. During the flood peak period, under the influence of density current, the electrical conductivity (EC) and turbidity increased significantly in the water depth of 10-15m, so that the reservoir water had obvious stratification between 10 and 15m. The form of pollutants in storm runoff was mostly in particle phosphorus. Total particulate phosphorus (TPP) concentration was 0.015 ± 0.011mg/L, accounting for 44.12% of total phosphorus (TP) concentration in storm runoff flood peak period. The process of a rainstorm caused runoff, which carried high levels of turbidity, particulate phosphorus, and organic matter. The storm runoff disrupts the stratification of the reservoir water. In terms of vertical distribution, the turbidity in the reservoir area increased to 73.75 NTU. Therefore, the occurrence of significant turbidity density flow in the reservoir is frequently accompanied by intense rainfall events. Gaining insights into the impact of storm runoff on the vertical distribution of reservoir turbidity can help managers in selecting an appropriate inlet height to mitigate high turbidity outflow.

Prediction of algal bloom using a combination of sparse modeling and a machine learning algorithm: Automatic relevance determination and support vector machine

Algae can produce odor substances and toxins that make the smell and taste of water unpleasant and impair the quality of human and aquatic life. Appropriate countermeasures can be implemented in advance in water purification processes to prevent algal disorders if the occurrence of algal blooms is accurately predicted. Several models have been developed to predict algal blooms. However, a comprehensive model that can be universally applied under various conditions is lacking. In this study, automatic relevance determination, a sparse modeling algorithm, and support vector machine were combined to construct prediction models for algal blooms in four Japanese dam reservoirs to predict their occurrence over 7 days. Automatic relevance determination was applied to a dataset consisting of monthly water quality data and daily hydraulic and meteorological data to identify variables relevant to the concentrations of Microcystis spp. and Dolichospermum spp., which are bloom-forming cyanobacteria and are dominant in freshwater ecosystems. A dataset of selected variables was used to train and validate the support vector machine models. The results of variable selection by automatic relevance determination revealed that the average concentration of total nitrogen in the past year and the average maximum temperature in the past 7 days may have an association with the algal concentration. Support vector machine models resulted in 92.3% accuracy and 86.4% precision for Microcystis spp. and 71.4% accuracy and 77.5% precision for Dolichospermum spp. on average in binary classification. The competitive relationship between Microcystis spp. and Dolichospermum spp., which differs according to the nutrient level and temperature, probably affects the prediction performance of the models. Our study suggests that the combination of sparse modeling and machine learning is applicable to the construction of a prediction model for site-specific algal bloom events in dam reservoirs.

Distribution Characteristics of Carbon, Nitrogen, and Phosphorus and Pollution Load Estimation of Sediments in Danjiangkou Reservoir, China

Danjiangkou Reservoir is a world-famous large artificial freshwater lake that offers water resources for the middle route of the South-to-North Water Diversion Project in China. In this study, the distribution of carbon, nitrogen, and phosphorus in reservoir sediments and their pollution assessments were elucidated at different water periods. The average TN (total nitrogen), TP (total phosphorus), and TOM (total organic matter) contents were 794.8 mg/kg, 807.2 mg/kg, and 8.7% in the nonflood season, respectively. When the time comes to flood season, with the large amount of nitrogen pollution inputted from peripheral nonpoint sources and phosphorus released by the accelerated exchange of water bodies, the average TN concentration increased to 1061.2 mg/kg. In addition, the average TP and TOM contents were reduced to 559.5 mg/kg and 6.3%. Nutrient pollution fluctuated between the safe and lowest level. Reservoir eutrophication risk was low. There was a certain nitrogen enrichment in the Danjiangkou Reservoir, and the flood season was the main period of nitrogen pollution input. Water exchange during flood season might accelerate organic matter degradation. Near the dam, sediment organic matter content increased significantly, reaching severe pollution levels. The results of the simulated sediment nutrient release test showed that the nitrogen and phosphorus in the reservoir would release slowly. Moreover, their annual release flux was calculated as 470.4 t and 87.9 t, respectively. It illustrated that the internal pollution of Danjiangkou Reservoir was light, and the release amount was small, so it was not the main pollution source of the reservoir at present.

Activation of indigenous denitrifying bacteria and enhanced nitrogen removal via artificial mixing in a drinking water reservoir: Insights into gene abundance, community structure, and co-existence model

Nitrogen pollution poses a severe threat to aquatic ecosystems and human health. This study investigated the use of water lifting aerators for in situ nitrogen reduction in a drinking water reservoir. The reservoir was thoroughly mixed and oxygenated after using water-lifting aerators for 42 days. The average total nitrogen concentration, nitrate nitrogen, and ammonium nitrogen—in all water layers—decreased significantly (P < 0.01), with a reduction efficiency of 35 ± 3%, 34 ± 2%, and 70 ± 6%, respectively. Other pollutants, including organic matter, phosphorus, iron, and manganese, were also effectively removed. Quantitative polymerase chain reactions indicated that bacterial nirS gene abundance was enhanced 26.34-fold. High-throughput sequencing, phylogenetic tree, and network analysis suggested that core indigenous nirS-type denitrifying bacteria, such as Dechloromonas, Simplicispira, Thauera, and Azospira, played vital roles in nitrogen and other pollutant removal processes. Furthermore, structural equation modeling revealed that nitrogen removal responded positively to WT, DO, and nirS gene abundance. Our findings provide a promising strategy for nitrogen removal in oligotrophic drinking water reservoirs with carbon deficiencies.

Advanced treatment of low-pollution and poor biodegradability sewage by combined process

A system was developed for the treatment of low-pollution sewage with poor biodegradability and a low ratio of chemical oxygen demand (CODCr) to nitrate-nitrogen (COD/NO3−-N (C/N)) ratio to achieve high efficiency. This system combines the anaerobic-oxic (AO) process with the biological aerated filter (BAF) and introduces the Fenton advanced oxidation process. A pilot test system was established, and feasibility investigations were conducted using a continuous flow of 500 L/h. The results showed that the optimal conditions for removing nitrate from sewage were achieved with a C/N ratio of 5.5–6 and a hydraulic retention time (HRT) of 4 h. Under these conditions, the average nitrate removal efficiency was 83.36%, and the average concentration of total nitrogen (TN) in the effluent was reduced to 6.68 mg/L. Additionally, the Fenton oxidation treatment was effective in reducing the COD content of sewage, with an average removal efficiency of 82.47% and a decrease in CODCr from 55.24 mg/L to 9.68 mg/L. The combined process successfully met the stringent discharge standards after advanced treatment. Microbial community analysis revealed that the dominant genera in anoxic BAFs were Trichococcus, Comamonadaceae, Lentimicrobium, and Thauera, while the dominant genera in aerobic BAFs were mainly Acinetobacter, Thiothrix, Gemmobacter, and Caldilineaceae. The synergistic effect of various nitrifying and denitrifying bacteria in BAFs effectively removed nitrate from the sewage. Furthermore, GC-MS analysis indicated that the Fenton oxidation significantly reduced the concentration of refractory organic compounds in the sewage, including long-chain organic compounds and acrylic acid maleic acid copolymer (MA/AA). After upgrading and renovating the factory's sewage treatment facilities, the impact of the discharged effluent on the receiving drainage basin will be minimized.

Filtration columns containing waste iron shavings, loofah, and plastic shavings for further removal of nitrate and phosphate from wastewater effluent

A novel pilot-scale advanced treatment system combining waste products as fillers is proposed and established to enhance the removal of nitrate (NO3−-N) and phosphate (PO43−-P) from secondary treated effluent. The system consists of four modular filter columns, one containing iron shavings (R1), two containing loofahs (R2 and R3), and one containing plastic shavings (R4). The monthly average concentration of total nitrogen (TN) and total phosphorus (TP) decreased from 8.87 to 2.52 mg/L and 0.607 to 0.299 mg/L, respectively. Micro-electrolysis of iron shavings produces Fe2+ and Fe3+ to remove PO43−-P, while oxygen (O2) consumption creates anoxic conditions for subsequent denitrification. Gallionellaceae, iron-autotrophic Microorganisms, enriched the surface of iron shavings. The loofah served as a carbon source to remove NO3−-N, and its porous mesh structure facilitated the attachment of biofilm. The plastic shavings intercepted suspended solids and degraded excess carbon sources. This system can be scaled up and installed at wastewater plants to improve the water quality of effluent cost-effectively.

Effects of river input flux on spatiotemporal patterns of total nitrogen and phosphorus in the Pearl River Estuary, China

The increasing riverine nutrient sources have significantly affected the ecological environment of estuaries and coastal waters, resulting in deteriorating land-sea water quality and intensified eutrophication. However, the effects of river input flux on spatiotemporal patterns of total nitrogen (TN) and total phosphorus (TP) were poorly understood in the Pearl River Estuary (PRE). In this study, the spatiotemporal patterns of TN and TP concentrations and river input flux of PRE were studied based on the seasonal nutrients monitoring data obtained for the rivers and estuary in 2019. The results showed the spatiotemporal patterns of the TN and TP concentrations in the eight rivers of the PRE were different, and the annual average concentrations of TN and TP in the rivers entering the PRE were 207.18 ± 105.13 and 3.51 ± 1.70 μmol/L, respectively. The annual river TN and TP fluxes discharged into the PRE were 8.61 × 1010 and 1.55 × 109 mol/year, respectively. In addition, the significantly decreasing trends in of TN and TP concentrations from upper estuary to offshore seawater were observed in the PRE, which implied TN and TP showed conservative behaviour in all season and only the dry season, respectively. Moreover, the annual average concentrations of TN and TP in the estuary were 70.64 ± 10.10 and 1.67 ± 0.78 μmol/L, respectively. The annual average ratios of TN/TP for rivers, freshwater, mixed and seawater were 59.31 ± 5.98, 59.45 ± 3.75, 45.73 ± 21.27 and 330.94 ± 434.71 respectively, which were higher than the Redfield ratios. These results indicated that the water quality in most areas of the PRE is significantly polluted and that the TN and TP in seawater were significantly influenced by river inputs. Therefore, monitoring and management of unified TN and TP nutrient indicators discharge from rivers entering the sea can be strengthened in the PRE, and eutrophication mitigation strategy should be established and implemented across river-estuary-coast continuum systems in the Great Bay Area.

Unravelling Nutrients and Carbon Interactions in an Urban Coastal Water during Algal Bloom Period in Zhanjiang Bay, China

Nutrients and carbon play important roles in algal bloom and development. However, nutrients and carbon interactions in the period of the spring algal bloom are not well understood. The aim of this study is to explore the nutrients and carbon interactions in the period of the spring algal bloom covering an urban Jinsha Bay (JSB) coastal water in Zhanjiang Bay (South China Sea) using in situ multidiscipline observation. The results showed that the average concentration of total nitrogen (TN), total phosphorus (TP), and dissolved silicon (DSi) was 97.79 ± 26.31 μmol/L, 12.84 ± 4.48 μmol/L, and 16.29 ± 4.00 μmol/L in coastal water, respectively. Moreover, the average concentration of total dissolved carbon (TDC), dissolved inorganic carbon (DIC) and organic carbon (DOC) in JSB was 2187.43 ± 195.92 μmol/L, 1516.25 ± 133.24 μmol/L, and 671.13 ± 150.81 μmol/L, respectively. Furthermore, the main dominant species were Phaeocystis globosa and Nitzschia closterium during the spring algal bloom. Additionally, the correlation analysis showed salinity (S) was significantly negatively correlated with nutrients, indicating that nutrients derived from land-based sources sustained spring algal bloom development. However, as the major fraction of TDC, DIC was significantly positively correlated with S, which was mainly derived from marine sources. Besides, the algal density showed a significant positive correlation with temperature (T) (p &lt; 0.001) and dissolved oxygen (DO) (p &lt; 0.001), but a significant negative correlation with DIC (p &lt; 0.05), suggesting that spring algal blooms may be simulated by water T increase, and then large amounts of DIC and nutrients were adsorbed, accompanying DO release through photosynthesis in coastal water. This study revealed nutrients and carbon interactions in the spring algal bloom of urban eutrophic coastal water, which has implications for understanding the nutrients and carbon biogeochemical cycle and algal bloom mitigation under climate change and anthropogenic pressures in the future.

Characteristics analysis of water pollutants in Cihu Lake, China, based on a multivariate statistical analysis method

In order to understand the sources of pollutants and the temporal and spatial distribution characteristics of the water quality in Cihu Lake, China, the monitoring data of seven water quality indicators from 12 sampling sites from 2015 to 2019 were selected, and the temporal and spatial variation laws of the water quality and pollution sources were analyzed by the use of the multivariate statistical analysis method. The results show that nitrogen and phosphorus pollution in the lake is dominant. The average concentrations of total nitrogen (TN) and total phosphorus (TP) exceed the surface water quality Class III standards by 1.6 and 2.2 times, respectively. Spatially, the results of the cluster analysis showed that the water quality in Cihu Lake can be categorized into three regions: the northern half of the lake, the southern half of the lake, and the canal entering the lake. Temporally, the water quality in these three regions can be classified into three categories: March to May (the northern half of Cihu Lake), September to November (the southern half of Cihu Lake), and September (the canal entering Cihu Lake). The discriminant analysis results showed that NH3-N, TN, CODCr, and BOD5 are the main factors that affect the uneven spatial distribution of the water quality of Cihu Lake, while TN, DO, and CODMn are the main factors that affect the temporal difference in the northern half of Cihu Lake, and NH3-N, TP, CODCr, DO, CODMn, TN, and TP are the main factors affecting the temporal difference in the southern half of Cihu Lake and the canal entering Cihu Lake. It was found that the water pollution in the study area can be mainly attributed to the incoming water and urban domestic pollution. The main pollution sources for the canal entering Cihu Lake and the southern half of Cihu Lake are the water from the sewage treatment plant and the domestic sewage that has not been intercepted, while the northern half of Cihu Lake is mainly affected by surface runoff, mixed rainwater and sewage, and internal pollution.

Scale Effects of Landscape Pattern on Water Quality in Dongjiang River Source Watershed

Based on water quality monitoring data and land use data, Dongjiang River source watershed water quality variation characteristics from 2017 to 2019 and the relationships between the landscape pattern of the Dongjiang River source watershed and water quality were analyzed using spatial analysis, correlation analysis, and redundancy analysis. The results showed that:① the water quality of the Dongjiang River source watershed improved overall, but the total nitrogen pollution was still severe. As of 2019, the annual average concentration of total nitrogen in all sampling points exceeded the type Ⅲ water quality standard. ② At the landscape level, water quality was positively correlated with landscape shape index, number of patches, and Shannon's diversity index but negatively correlated with largest patch index and aggregation index. Considering the land use type, construction land was the primary source of total nitrogen and total phosphorus. Landscape shape index and number of forest patches were positively correlated with NH4+-N. The number of forest patches was positively correlated with total phosphorus. However, the largest patch index and aggregation index of the forest were negatively correlated with total phosphorus. The number of patches of grassland was positively correlated with total phosphorus. The aggregation index of grassland was negatively correlated with total phosphorus. ③ It is suggested that management departments should focus on the optimization of the landscape pattern within the 2000 m buffer zone of monitoring points. The reasonable allocation of urban sewage-centralized treatment facilities, strengthening management of abandoned mining areas, improvement of intensive treatment of cultivated land, and construction of shelterbelt in areas where cultivated land is concentrated are beneficial for the water quality of Dongjiang River source watershed.

Source apportionment of surface water pollution in North Anhui Plain, Eastern China, using APCS-MLR model combined with GIS approach and socioeconomic parameters

• APCS-MLR model combined with GIS approach and socioeconomic parameters were used in this study. • Northern and western parts of the North Anhui Plain were the most polluted. • The contributions of river pollution sources in the North Anhui Plain were quantified for the first time. • Consideration of socioeconomic data with hydrochemical data improved the identification of pollution source. Various human activities have led to the deterioration of river water quality in many plain areas, which threatens human health and restricts social development. Identifying the spatio-temporal distribution of river pollutants and the objective apportionment of pollution sources is important for effectively protecting water resources. In this study, a geographic information system (GIS approach), principal component analysis/factor analysis (PCA/FA), and the absolute principal component score-multiple liner regression (APCS-MLR) receptor model were applied to evaluate the water quality and identify pollution sources in rivers in the North Anhui Plain, Eastern China. River water quality data for 43 months (January 2017 to July 2020), comprising 10 physico-chemical parameters from 43 monitoring sites across the study area, were used. The average concentrations of total nitrogen (TN), chemical oxygen demand (COD Cr ), permanganate index (COD Mn ), fluoride (F − ), biochemical oxygen demand (BOD), total phosphorous (TP), and NH 4 + –N in 66.9 %, 59.7 %, 41.9 %, 41.25, 30 %, 27.1 %, and 14.7 % of the samples, respectively, exceeded the Chinese surface water standards. BOD, NH 4 + –N, TN, and TP showed a decreasing annual trend, and the northern and western parts of the study area were the most polluted. According to the PCA/FA and the spatial distribution characteristics of pollutants and socio-economic parameters, industrial wastewater and municipal effluents, agricultural cultivation and domestic sewage, geogenic processes and meteorological factors were identified as being responsible for the degradation of the river water quality. The mean contributions of these source were 28.6 %, 5.5 %, 16.1 % and 25.1 %, respectively. This study shows the objectivity and reliability of using a combined approach of GIS with multivariate statistics to evaluate the river water quality status, which can help decision makers to develop more effective strategies for water resource protection.

Nitrate loss by runoff in response to rainfall amount category and different combinations of fertilization and cultivation in sloping croplands

Nitrate (NO3-N) loss by runoff from agricultural lands causes substantial soil fertility loss and water quality degradation in downstream aquatic systems. Rainfall, fertilization and cultivation direction are key factors influencing NO3-N loss in runoff from sloping croplands; however, these effects are still elusive. The responses of runoff NO3-N and total nitrogen (TN) losses to rainfall amount, fertilization and cultivation direction were studied under more than 100 natural rainfall events occurring between 2008 and 2020 in sloping croplands. Five treatments (three replications for each) including CK (no fertilizer + downslope cultivation), T1 (combined manure and chemical fertilizers + downslope cultivation), T2 (chemical fertilizer + downslope cultivation), T3 (1.5-fold chemical fertilizer + downslope cultivation) and T4 (chemical fertilizer + contour cultivation) were deployed on fifteen plots (8 m long × 4 m wide for each). The results showed that runoff depth was 83.9–318 % higher in the large rainstorms than in the other rainfall events, and 29.3–77.8 % higher in the unfertilized plots (i.e., CK) than in the fertilized plots (i.e., T1, T2, T3 and T4). The runoff NO3-N concentration, on average, was significantly higher in the moderate and heavy rains than in the light rain and large rainstorms but did not differ in these five treatments. Conversely, the average TN concentration was not affected by the rainfall amount category but was significantly higher in the unfertilized plots than in the fertilized plots. Significantly higher losses of NO3-N and TN were found in the large rainstorms, implying the dominant role of runoff rather than nutrient concentrations. The unfertilized plots presented 50–100 % and 66.7–150 % higher NO3-N and TN losses, respectively, than the fertilized plots. The NO3-N: TN ratio differed markedly by rainfall amount category, and was higher in the contour cultivation (i.e., T4) than in the downslope cultivation (i.e., T2). Our results have great significance for understanding the dynamics of NO3-N loss by runoff driven by changeable rainfall features and intense agricultural management practices in sloping croplands.

Trends in total nitrogen concentrations in the Three Rivers Headwater Region

It is important to protect the quality of the water in the Three Rivers Headwater Region (TRHR), known as the water tower of China, to guarantee the water security in downstream areas. However, because of a lack of long-term studies that span wide geographical areas, it is difficult to understand how the water resource in the TRHR should be protected. In this paper, we report the findings from our analysis of total nitrogen (TN) concentration data from 39 river monitoring stations for the period from 2012 to 2018. The water quality status was evaluated by comparing the concentrations with the national standards and calculating exceedance ratios for surface water. Trends were calculated with ordinary linear least-squares regression and a weighted least-squares (WLS) meta-analysis method. The results showed that the annual average TN concentrations in the TRHR rivers from 2012 to 2018 ranged from 0.68 to 1.06 mg/L, and were lower than those in the downstream reaches but higher than the global average in natural river waters. For the period from 2012 to 2018, the TN concentrations showed a highly significant increase (0.03 mg/L/year) across the entire TRHR and were increasing and decreasing at 71.8 % and 28.2 % of the stations, respectively. From the trend results, we divided the study area into two zones, one with increasing TN concentrations and one with decreasing TN concentrations. It is found that environmental factors had little influence on TN concentrations in the increasing and decreasing areas, but artificial factors such as population and restoration project areas contributed to the increases in TN concentrations in the increasing area. The TRHR remains a source of clean water in China; however, the water quality should be monitored closely, and measures should be implemented to protect the resource and mitigate the disturbances caused by human activities.

Seasonal Total Nitrogen and Phosphorus Variation, Speciation, and Composition in the Maowei Sea Affected by Riverine Flux Input, South China Sea

Human activities have altered global nutrient cycling and have significantly changed marine systems. This is evidenced by the significant changes in nitrogen and phosphorus availability. The Maowei Sea (MWS) is the largest oyster culture bay in southwest China. From August 2018 to May 2019, the spatial and temporal nutrient concentrations and fluxes in MWS using system-wide scale seasonal data were assessed from river estuaries and adjacent coastal waters. The annual average concentrations of total nitrogen (TN) and total phosphorus (TP) in the three estuaries of Maolingjiang River (MLJR), Dalanjiang River (DLJR) and Qinjiang River (QJR) were 3.00 mg/L and 0.183 mg/L, respectively. Therein, the highest TN and TP concentrations were in DLJR, the lowest TN concentration was in MLJR, and the lowest TP concentration was in QJR. DIN and DIP were the main forms of TN and TP, accounting for 80.9% and 59.4%, respectively. The main form of DIN in MLJR and QJR was NO3−, accounting for 86.8% and 84.4%, respectively, while the main form of DIN in DLJR was NH4+, accounting for 55.9%. The annual flux of pollutants discharged into MWS from the three estuaries is 10,409.52 t for TN and 556.21 t for TP. The month with the largest contribution to the annual load was July, accounting for 29.2% and 24.2% of TN and TP, respectively, and the fluxes of TN and TP were significantly different among the three seasons (p &lt; 0.05). The annual average concentrations in the surface waters of the MWS were 1.07 mg/L for TN and 0.129 mg/L for TP, and there were significant differences (p &lt; 0.05) in the concentrations of TN and TP among the three seasons. The annual average N/P ratios of the river water and seawater were 43 and 18, respectively, which were higher than the Redfield ratio (N/P = 16), indicating that the growth of phytoplankton in MWS may be limited by phosphorus. Eutrophication owing to nutrient pollution in the three estuaries may be persistent in adjacent coastal waters, and land–ocean integrated mitigation measures should be taken to effectively improve the water quality in the river estuary and coastal water.

Temporal heterogeneity of bacterial communities and their responses to Raphidiopsis raciborskii blooms

To elucidate the interspecies connectivity between cyanobacteria and other bacteria (noncyanobacteria), microbial diversity and composition were investigated through high-throughput sequencing (HTS) in a drinking water reservoir in Chongqing city, Southwest China, during Raphidiopsis raciborskii blooms. Significant temporal changes were observed in microbial community composition during the sampling period, primarily reflected by variations in relative bacterial abundance. The modularity analysis of the network demonstrated that the bacterial community forms co-occurrence/exclusion patterns in response to variations in environmental factors. Moreover, five modules involved in the dynamic phases of the R. raciborskii bloom were categorized into the Pre-Bloom, Bloom, Post-Bloom, and Non-Bloom Groups. The reservoir was eutrophic (i.e., the average concentrations of total nitrogen (TN) and total phosphorus (TP) were 2.32 and 0.07 mg L−1, respectively) during the investigation; however, Pearson’s correlation coefficient showed that R. raciborskii was not significantly correlated with nitrogen and phosphorus. However, other environmental factors, such as water temperature, pH, and the permanganate index, were positively correlated with R. raciborskii. Importantly, Proteobacteria (α-, γ-Proteobacteria), Acidobacteria, Chloroflexi, and Firmicutes were preferentially associated with increased R. raciborskii blooms. These results suggested that the transition of R. raciborskii bloom-related microbial modules and their keystone species could be crucial in the development and collapse of R. raciborskii blooms and could provide a fundamental basis for understanding the linkage between the structure and function of the microbial community during bloom dynamics.

Effect of Aquatic Vegetation Restoration after Removal of Culture Purse Seine on Phytoplankton Community Structure in Caizi Lakes

Many reports have demonstrated that the removal of aquaculture purse seine is conducive to the restoration of aquatic vegetation and the improvement in water quality, but less attention has been paid to the effects on phytoplankton. This paper addressed the response of phytoplankton community structure to aquatic vegetation restoration after purse seine removal in Caizi Lakes. The results showed that the average dissolved oxygen (from 7.43 ± 0.25 mg/L to 9.12 ± 0.49 mg/L) and Secchi depth (from 28.40 ± 6.20 cm to 47.61 ± 14.62 cm) in the water column of the Caizi Lakes increased after the restoration of aquatic vegetation, while the average concentrations of total nitrogen (from 2.00 ± 0.16 mg/L to 1.34 ± 0.18 mg/L) and total phosphorus (from 0.15 ± 0.02 mg/L to 0.06 ± 0.01 mg/L) decreased. After the restoration of the aquatic vegetation, the cell density of phytoplankton declined from 21.04 ± 4.57 × 106 cells/L to 12.74 ± 3.63 × 106 cells/L, and the biomass fell from 18.13 ± 3.57 mg/L to 9.72 ± 2.55 mg/L. We also observed that Shannon–Wiener diversity, Margalef and Pielou indices of phytoplankton surged by 66.50%, 46.20% and 84.68%, respectively. Because this study demonstrated that aquatic vegetation could alleviate the eutrophication, it can provide guidance for the restoration and protection of the aquatic ecosystem.

Leaf litter species affects decomposition rate and nutrient release in a cocoa plantation

Mineral nutrient fluxes derived from litterfall are key components of nutrient biogeochemical cycles in both natural and agroforesty systems. Cocoa production systems are generally nutrient depleted and may benefit from on external nutrient application to maintain primary productivity. However, in developing countries the main source of nutrients is often nutrient recycling through decomposing leaf litter, and in this regard shade-tree species play an important role in cocoa agroforestry. This study aimed to investigate the nutrient inputs of litter from two shade-tree species (Canarium indium and Gliricidia sepium) and cocoa trees (Theobroma cacao) after 15 months of decomposition in a cocoa plantation. Litter from G. sepium lost more mass (59%) than T. cacao (37%) and C. indium (10%), and showed a higher average concentration of total nitrogen (TN), boron (B), iron (Fe) and phosphorus (P) after 15 months of field incubation than that of C. indium. It also showed a low C:N ratio and N release, which suggest N mineralisation. All litter species showed high C:P ratio and negative P release, which suggests P immobilisation. Litter from G. sepium and T. cacao showed a rapid K release after 1 month of decomposition. The differing mass loss rates and litter nutrient concentrations of the three species could benefit T. cacao by providing asynchronous nutrient inputs and improve long-term sustainability of mixed-species plantations.

Spatial–Temporal Variations of Total Nitrogen and Phosphorus in Poyang, Dongting and Taihu Lakes from Landsat-8 Data

Poyang Lake, Dongting Lake, and Taihu Lake are the largest freshwater lakes in the middle and lower reaches of the Yangtze River, China. In recent years, the eutrophication level of lakes has increased with the development of the social economy and caused many environmental and social problems. The concentrations of total nitrogen (TN) and total phosphorus (TP) are the key indicators of the degree of eutrophication, but the traditional ground monitoring methods are not capable of capturing such parameters in whole lakes with high spatial-temporal resolution. In this paper, empirical models are established and evaluated between the TN and TP and remote sensing spectral factors in the three lakes using Landsat 8 Operational Land Imager (OLI) satellite data and in-situ data. The results show that the inversion accuracy is higher than 75%. The TN and TP concentrations in the three lakes are inversed based on the Google Earth Engine (GEE) platform from 2014 to 2020 and their spatial-temporal variations are analyzed. The results show that the concentrations of TN and TP in Poyang Lake were decreased by 5.99% and 7.13% over 7 years, respectively, and the TN in Dongting Lake was decreased by 5.25% while the TP remained stable. The temporal changes in TN and TP concentrations displayed seasonal variations. A low concentration was observed in summer and high concentrations were in spring and winter. The average concentrations of TN and TP in Taihu Lake were higher than that of the other two lakes. The TP concentration was increased by 17.3% over 7 years, while the TN concentration remained almost stable. The variation in TN in Taihu Lake was the same as the growth cycle of algae, with higher value in spring and winter and lower value in summer, while the concentration of TP was lower in spring and winter and higher in summer. The spatial distribution of TN and TP concentrations in the three major lakes was significantly affected by human activities, and the concentrations of TN and TP were higher in areas near cities and agricultural activities.

Loss of nitrogen and phosphorus from farmland runoff and the interception effect of an ecological drainage ditch in the North China Plain—A field study in a modern agricultural park

Agricultural non-point source pollution caused by excessive fertilization is a problem in the North China Plain. The experimental site was at a modern high-tech agricultural park in Dezhou City of Shandong Province that is located within the lower Yellow River impact plain. The fertilization, irrigation, and crop management in the modern agricultural park were investigated to determine the proportion of nitrogen and phosphorus loss of the total input. An ecological drainage ditch was constructed in the modern agricultural park in 2016. At the same time, a Doppler flowmeter and a runoff automatic acquisition instrument were installed in the inlet and outlet of the ecological drainage ditch for monitoring the flow of runoff and collecting runoff samples under natural rainfall in 2018 and 2019. The nitrogen, phosphorus, and sediment runoff contents were determined in the laboratory in order to calculate the loss of nitrogen and phosphorus from farmland runoff and the nitrogen and phosphorus interception rate of the ecological drainage ditch. The results showed that there were a total of 13 runoff events in 2018 and 2019 and that the average concentration of total nitrogen and phosphorus in farmland runoff was 2.63–18.84 mg·L−1and 0.81–13.14 mg·L−1 in both years combined, respectively. The main forms of nitrogen found in runoff were NO3−-N, and the main form of phosphorus found in runoff was particulate phosphorus. The amount of nitrogen and phosphorus lost through runoff was 2.90% and 5.07%, respectively, of the average nitrogen and phosphorus input from both years combined. Runoff was generated when daily precipitation was above 17.4 mm and daily maximum precipitation intensity was above 5.1 mm·h−1. There was a linear relationship between daily precipitation, daily maximum precipitation intensity, and the amount of runoff after natural rainfall. A linear regression equation was established to predict the amount of runoff in the study area. The results indicated that ecological ditches in the watersheds of modern agricultural parks could be used to intercept nitrogen and phosphorus from farmland runoff effectively.