Mitigating Impact of Devils Lake Flooding on the Sheyenne River Sulfate Concentration

Devils Lake is a terminal lake located in northeast North Dakota. Because of its glacial origin and accumulated salts from evaporation, the lake has a high concentration of sulfate compared to the surrounding water bodies. From 1993 to 2011, Devils Lake water levels rose by ~10 m, which flooded surrounding communities and increased the chance of an overspill to the Sheyenne River. To control the flooding, the State of North Dakota constructed two outlets to pump the lake water to the river. However, the pumped water has raised concerns about of water quality degradation and potential flooding risk of the Sheyenne River. To investigate these perceived impacts, a Soil and Water Assessment Tool (SWAT) model was developed for the Sheyenne River and it was linked to a coupled SWAT and CE‐QUAL‐W2 model that was developed for Devils Lake in a previous study. While the current outlet schedule has attempted to maintain the total river discharge within the confines of a two‐year flood (36 m³/s), our simulation from 2012 to 2018 revealed that the diversion increased the Sheyenne River sulfate concentration from an average of 125 to >750 mg/L. Furthermore, a conceptual optimization model was developed with a goal of better preserving the water quality of the Sheyenne River while effectively mitigating the flooding of Devils Lake. The optimal solution provides a “win–win” outlet management that maintains the efficiency of the outlets while reducing the Sheyenne River sulfate concentration to ≤600 mg/L.     

Experimental research of LNG accidental underwater release and combustion behavior

Evaluating potential hazards caused by accidental LNG release from underwater pipelines or vessels is a significant consideration in marine transportation safety. The aim of this study was to capture the dynamic behavior of LNG jet released under water and to analyze its vapor dispersion characteristics and combustion characteristics on the water surface during different release scenarios. Controlled experiments were conducted where LNG was jet released from a cryogenic storage tank. The dynamic process of LNG being jet released from orifices of different sizes and shapes, as well as the rising plume structure, were captured by a high-speed camera. The leakage flow rate and pipeline pressure were recorded by a flow meter and pressure gauge, respectively. The concentration distribution that emanated from the water surface was measured utilizing methane sensors in different positions with various wind speeds. The flame combustion characteristics of LNG vapor clouds, which immediately ignited upon the enclosed water tank, were also recorded. Additionally, the mass burning rate of the flame on the water surface was evaluated, and a new correlation between the ratio of flame length and width was established. The results indicated a large dimensionless heat release rate (Q*) and a continuous release flow rate in a limited burning area. This study could provide greater understanding of the mechanisms of LNG release and combustion behavior under water.     

大型碳化硅生产园区面源源强及减排指标核算

以某年产25万吨大型碳化硅园区无组织排放面源为例,提出基于多个地面站气象数据的CALPUFF模型地面浓度反推方法,优化流场模拟,使得无组织面源源强核算结果更加准确,并以环境保护目标空气质量达标为原则,核算其大气污染物减排指标,得出具体结论:园区大气污染物SO2、NOX、CO、PM10年排放量分别为449.06t、86.98t、5158.58t、115.06t;无组织排放SO2、CO及PM10的减排比例分别为63.5%、19.2%、42.44%,对应减排量分别为285.16 t/a、990.45 t/a、48.83 t/a。     

基于3S技术对太湖底质及水质总磷的研究

应用3S技术研究了太湖底质与水质总磷(TP)的分布情况,并结合水华频次分析了其相关性。结果表明:2016—2018年,太湖底质TP年均值在433~537 mg/kg波动,水质TP年均值从0.064 mg/L上升至0.087 mg/L。从空间分布来看,底质TP、水质TP和水华频次均呈现“西高东低”的规律,太湖西部区尤其是竺山湖区是需要开展治理的重点区域。3年间,太湖西部区水质TP上升,而底质TP与入湖河流TP下降,说明内源磷污染是太湖西部区水质TP升高的主要原因,须加强科学清淤。     

篦齿眼子菜对废水中氮和磷的去除行为研究

一些常见的沉水草本植物对水质具有较强的净化作用,能够有效控制氮和磷的浓度.本试验通过模拟氮、磷污染的水质条件,采用篦齿眼子菜对氮、磷营养盐的吸附和去除效果进行研究.结果 表明:设定模拟废水中的初始总氮(TN)浓度在1～50 mg/L范围内,培养30天后的植株对总氮的去除率最高可达85.4％,随着初始培养环境中总氮浓度的...     

Cancer and Non-Cancer Health Risk from Eating Cassava Grown in Some Mining Communities in Ghana

Food crops such as cassava, cocoyam and other tuber crops grown in mining communities uptake toxic or hazardous chemicals such as arsenic, and cadmium, from the soil. Cassava is a stable food for Ghanaians. This study evaluated human health risk from eating cassava grown in some mining communities in Ghana such as Bogoso, Prestea, Tarkwa and Tamso, which are important mining towns in the Western Region of Ghana. The study evaluated cancer and non-cancer health effects from eating cassava grown in the study areas in accordance with US Environmental Protection Agency’s Risk Assessment guidelines. The results of the study revealed the following: cancer health risk for Tamso, 0.098 (RME – Reasonable Maximum Exposure) and 0.082 (CTE – Central Tendency Exposure). This means that approximately 10 and 8 out of 100 resident adults are likely to suffer from cancer related cases by RME and CTE parameters respectively. For Prestea, we have 0.010 and 0.12, which also means that approximately 1 out of 100 and 10 resident adults out of 100 are also likely to suffer from cancer related diseases by RME and CTE parameters. The results of the study obtained were found to be above the acceptable cancer risk range of 1× 10⁻⁶ to 1× 10⁻⁴, i.e., 1 case of cancer out of 1 million or 100,000 people respectively.     

乌鲁木齐市大气中二氧化硫的灰色预测

根据灰色系统理论,联系乌鲁木齐市大气环境的实际状况,建立了精度检验为一级的灰色预测模型,经模型检验其精度完全满足要求。对乌鲁木齐大气中的SO2值进行预测分析的结果表明,乌鲁木齐市大气中SO2值呈上升的趋势,在未来几年中,乌鲁木齐市大气中SO2的预测值超过国家三级标准值(即大气中SO2的质量浓度年均值≤0.10mg/m3),这种发展趋势应引起有关部门的关注。     

三峡水库典型支流磷素赋存形态特征及其成因

采用2018年三峡水库低水位期(6月)、蓄水期(9月)和高水位期(12月)对库区内的典型一级支流——香溪河与神农溪回水区水质、水动力及环境因子的监测数据,对比分析了三峡水库内的典型支流在水库不同调度期时水体中磷素的存在形态及成因.结果表明,香溪河与神农溪库湾水体总磷(TP)质量浓度变化范围分别为0.049～0.168m...     

The Influence of Chironomus plumosus Larvae on Nutrient Fluxes and Phosphorus Fractions in Aluminum Treated Lake Sediment

One of the methods to diminish the internal phosphorus (P) loading is inactivation of P by aluminum (Al). After addition of Al to lake water an Al(OH)₃ floc is formed, which settles to the bottom and initially form a lid on the sediment surface. The effects of Chironomus plumosus larvae on sediment nutrient fluxes and P binding-sites in the sediment after addition of Al were tested. C. plumosus larvae were added to sediment cores in which sediment–water fluxes of nutrients were measured four times. After one month, the sediment was sectioned with depth and P fractions were measured by sequential chemical extraction. The chironomids created burrows through the Al layer which caused a significantly increased efflux of P from the Al treated sediment, because the P had only limited contact to the added Al. The chironomids also affected the P fractions in the sediment by their bioturbating activity. Thus, they caused increased Al concentrations in the upper part of the Al treated sediment. This created an enhanced contact between Al and P in the upper 7 cm of the sediment and, as a result, an increased binding of P to Al and a lowered porewater P. The DIP efflux is therefore expected to be lowered after the initial phase. Al had no effects on the nitrogen fluxes, but the chironomids enhanced the release, and decreased the release or increased the uptake by the sediments.     

Modelling Phosphorus Retention in Lakes and Reservoirs

Steady-state models for the prediction of P retention coefficient (R) in lakes were evaluated using data from 93 natural lakes and 119 reservoirs situated in the temperate zone. Most of the already existing models predicted R relatively successfully in lakes while it was seriously under-estimated in reservoirs. A statistical analysis indicated the main causes of differences in R between lakes and reservoirs: (a) distinct relationships between P sedimentation coefficient, depth, and water residence time; (b) existence of significant inflow–outflow P concentration gradients in reservoirs. Two new models of different complexity were developed for estimating R in reservoirs: , where τ is water residence time (year), was derived from the Vollenweider/Larsen and Mercier model by adding a calibrated parameter accounting for spatial P non-homogeneity in the water body, and is applicable for reservoirs but not lakes, and , where [P_in] is volume-weighted P concentration in all inputs to the water body (μg l⁻¹), was obtained by re-calibrating the OECD general equation, and is generally applicable for both lakes and reservoirs. These optimised models yield unbiased estimates over a large range of reservoir types.