Enhancing treatment efficiency of swine wastewater by effluent recirculation in vertical-flow constructed wetland

Introduction Livestock w astew ater contains highly concen- trated pollutants, including suspended solids (SS), organics, nutrients and bacteria. In C hina, w astew ater generated by concentrated farm s is com m only stored in anaerobic lagoons and partia…     

煤矿水害风险量化评价方法

为提高煤矿防治水管理水平,预防和消除矿井水害,在层次分析法的基础上建立中性值作为参照对象对矿井水害风险进行实时评判的方法。根据《煤矿防治水细则》建立以矿井水文地质类型、矿井涌水量标准分数、突水预兆、采掘面位置、探水结果为准则层的层次结构模型,并对各评价指标赋权。依据制定的水害风险评价指标的评分细则和监测监控数据并结合其权重得到水害评价总得分。通过总得分与中性参照分数比较得出预测结果:水害评价总得分大于中性参照分数,证明水害的威胁小,分数越高越安全;反之则水害的威胁较大,分数越低越危险,这时需要加强防治水的力度,令评价分数管控大于中性参照分数。这种方法依赖于井下监测监控数据进行量化评价,能实时、客观、全面且准确地反映煤矿水害的风险情况。     

基于响应曲面法的遗煤自燃分析与研究*

为研究高瓦斯易自燃煤层不同供风量、高抽巷抽采流量、低抽巷抽采流量3因素对采空区自燃“三带”分布影响规律,选取阳煤五矿8406工作面为研究对象,在数值模拟研究基础上,采用Design Expert软件进行Box Behnken试验设计,构建采空区氧化升温带宽度在3因素、3水平条件下的二次回归响应曲面模型,并对不同条件下采空区氧化升温带宽度进行预测与分析。结果表明:二次回归方程P值为0.001 6,预测模型显著,模型的失拟项为0.606 3,不显著,回归方程具有统计学意义;当供风量为1 500~2 000 m3/min,低抽流量为450~650 m3/min,高抽流量为100~200 m3/min时,对氧化升温带宽度一次项重要度排序为C（高抽巷抽采流量）>A（供风量）>B（低抽巷抽采流量）,二次项重要度排序为AC（供风量和高抽巷抽采流量）>AB（供风量和低抽巷抽采流量）>BC（低抽巷抽采流量和高抽巷抽采流量）,且AB,AC,BC之间均无交互作用。     

屏蔽服冷却系统对人体表面温度影响的研究*

为科学有效地论证多种方式组合的冷却屏蔽服在不同环境条件下对人体表面温度控制的效果,需要对冷却系统及人体敏感部位发热量进行客观评估。通过对5名健康男性的高温测试,探究人体在不同环境温度下体表温度的变化,得出胸部、背部及额头为热量最高部位,并构建以“人体-降温屏蔽服-外界环境”为主体的冷却系统数值模型,对不同环境中的屏蔽服冷却效果展开研究,分析穿戴冷却屏蔽服时人体躯干部分的温度分布及影响。结果表明:在屏蔽服中靠近胸部、背部部位引入相变材料和风扇,均可帮助人体降低体温,提高舒适度。     

基于第二次全国污染源普查质量保证的思考及体系建设初探

通过对清查数据的结果分析,确定第二次全国污染源入户普查的对象,基于企业填报、现场入户、资料收集审核、数据核查等具体工作的实施与开展,思考和归总普查工作中影响数据质量的现实问题和难点,初步构建污染源普查质量保证体系,以期为全国污染源普查数据质量保证提供有益参考。     

煤对CO2，N2和CH4的吸附速率经验公式与异同性研究*

为了解决吸附速率拟合公式缺乏而解吸经验公式众多的问题,通过替换解吸参数、定性和对比分析各经验公式对煤吸附CO₂,N₂,CH₄吸附速率的适用性,选取4种不同煤质的煤样在0.5,1.0和2.0 MPa下进行定温吸附实验,分析压力和煤质对吸附速率的影响规律。研究结果表明:时间函数式对3种气体在不同压力和煤质下的吸附速率拟合效果最佳;压力和煤质对3种气体吸附速率的影响既存在共性又具有差异性,气体吸附速率与压力符合指数函数关系,与挥发分呈现出二次函数关系,并且压力升高会导致最低吸附速率趋向于较高变质程度煤样;CH₄和N₂的吸附速率随压力升高而升高,而CO₂的吸附速率因煤样而不同,且在同压下,不同气体的最高和最低吸附速率煤样的变质程度也不同。     

Adaptation of Climate Model Projections of Streamflow to Account for Upstream Anthropogenic Impairments

A statistical procedure is developed to adjust natural streamflows simulated by dynamical models in downstream reaches, to account for anthropogenic impairments to flow that are not considered in the model. The resulting normalized downstream flows are appropriate for use in assessments of future anthropogenically impaired flows in downstream reaches. The normalization is applied to assess the potential effects of climate change on future water availability on the Rio Grande at a gage just above the major storage reservoir on the river. Model‐simulated streamflow values were normalized using a statistical parameterization based on two constants that relate observed and simulated flows over a 50‐year historical baseline period (1964–2013). The first normalization constant is a ratio of the means, and the second constant is the ratio of interannual standard deviations between annual gaged and simulated flows. This procedure forces the gaged and simulated flows to have the same mean and variance over the baseline period. The normalization constants can be kept fixed for future flows, which effectively assumes that upstream water management does not change in the future, or projected management changes can be parameterized by adjusting the constants. At the gage considered in this study, the effect of the normalization is to reduce simulated historical flow values by an average of 72% over an ensemble of simulations, indicative of the large fraction of natural flow diverted from the river upstream from the gage. A weak tendency for declining flow emerges upon averaging over a large ensemble, with tremendous variability among the simulations. By the end of the 21st Century the higher‐emission scenarios show more pronounced declines in streamflow.     

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.     

Spatial and Seasonal Response of Municipal Water Use to Weather across the Contiguous U.S.

Weather variability has the potential to influence municipal water use, particularly in dry regions such as the western United States (U.S.). Outdoor water use can account for more than half of annual household water use and may be particularly responsive to weather, but little is known about how the expected magnitude of these responses varies across the U.S. This nationwide study identified the response of municipal water use to monthly weather (i.e., temperature, precipitation, evapotranspiration [ET]) using monthly water deliveries for 229 cities in the contiguous U.S. Using city‐specific multiple regression and region‐specific models with city fixed effects, we investigated what portion of the variability in municipal water use was explained by weather across cities, and also estimated responses to weather across seasons and climate regions. Our findings indicated municipal water use was generally well‐explained by weather, with median adjusted R² ranging from 63% to 95% across climate regions. Weather was more predictive of water use in dry climates compared to wet, and temperature had more explanatory power than precipitation or ET. In response to a 1°C increase in monthly maximum temperature, municipal water use was shown to increase by 3.2% and 3.9% in dry cities in winter and summer, respectively, with smaller changes in wet cities. Quantifying these responses allows urban water managers to plan for weather‐driven variability in water use.     

Estimating Potential Climate Change Effects on the Upper Neuse Watershed Water Balance Using the SWAT Model

Climate change poses water resource challenges for many already water stressed watersheds throughout the world. One such watershed is the Upper Neuse Watershed in North Carolina, which serves as a water source for the large and growing Research Triangle Park region. The aim of this study was to quantify possible changes in the watershed’s water balance due to climate change. To do this, we used the Soil and Water Assessment Tool (SWAT) model forced with different climate scenarios for baseline, mid‐century, and end‐century time periods using five different downscaled General Circulation Models. Before running these scenarios, the SWAT model was calibrated and validated using daily streamflow records within the watershed. The study results suggest that, even under a mitigation scenario, precipitation will increase by 7.7% from the baseline to mid‐century time period and by 9.8% between the baseline and end‐century time period. Over the same periods, evapotranspiration (ET) would decrease by 5.5 and 7.6%, water yield would increase by 25.1% and 33.2%, and soil water would increase by 1.4% and 1.9%. Perhaps most importantly, the model results show, under a high emission scenario, large seasonal differences with ET estimated to decrease by up to 42% and water yield to increase by up to 157% in late summer and fall. Planning for the wetter predicted future and corresponding seasonal changes will be critical for mitigating the impacts of climate change on water resources.