饮用水源微生物快速检测技术的发展及应用

微生物是威胁饮用水安全的首要问题,水环境微生物快速检测技术的开发和应用是推动饮用水源微生物快速检测和水质安全预警技术发展的保障。随着对水质微生物污染快速检测和准确预警新要求的提出,水环境中微生物在线检测和预警技术得到了越来越多的开发和应用。笔者总结了水环境常见微生物检测方法和技术的发展,重点讨论了饮用水源微生物快速检测技术的发展和应用,根据各项技术的应用和推广使用程度,将其归纳为常用快速检测技术、潜在适用快速检测技术和新型快速检测技术等类别,并详细阐述了一些应用较广的技术,以期为构建水质微生物污染早期预警系统提供参考。     

区域主体功能实现与自然资源利用的定量关系研究

主体功能区划通过主体功能划分的方式将开发和保护结合,自然资源开发利用复杂化过程中资源利用与目标实现之间亟需实现基本的定量核算关系。本文从自然资源可持续利用角度,试图探讨建立初步的主体功能核算关系,通过核算框架进行生产、生活、生态主体功能概算与比较。以京津冀主体功能区与水资源为例,对所设立的核算关系进行了验证与应用,并构造绝对与相对量指标量化京津冀主体功能量、功能水资源投入量与效率,进行了异空间尺度与异质性功能的比较,为以主体功能实现最大化为目标的资源优化配置提供量化工具。结果显示:①利用生态服务价值测算的当量因子法与水足迹测算的投入产出法,刻画了水资源对于地区主体功能的支撑作用。②利用功能总量与单位功能水资源投入量指标完成了异质性功能在异质性空间上规模、结构、相应水资源效率的比较。基于算例结果得到以下结论:①本文构建的自然资源-主体功能核算关系框架能够有效衔接主体功能规划,定量核算能有效反映与评价资源对区域功能目标、经济开发活动的支撑作用。②区域资源配置存在相对功能实现的效率差异,可根据资源投入与功能产出之间的关系引导实现功能最大化目标的资源配置。合理、有效的量化手段能够推进主体功能制度的落实,也有助于当前中国空间规划体系编制与落实的实际指导效果。     

固相萃取-超高效液相色谱/三重四极杆质谱法同时测定地表水中8种亚硝胺类化合物

建立了固相萃取（SPE）-超高效液相色谱/三重四极杆串联质谱（UPLC-MS/MS）同时测定地表水中8种亚硝胺类化合物的方法。水样中目标物经椰壳活性炭固相萃取小柱吸附富集,小柱经氮气吹干后采用二氯甲烷洗脱。待测样品采用Atlantis T₃柱,以水-甲醇作为流动相进行梯度洗脱,大气压力化学电离源（APCI）正离子模式多反应监测方式（MRM）进行检测,内标法定量分析。8种目标物在相关线性范围内线性良好(r≥0.9950),地表水加标回收率为55.4%~90.4%,相对标准偏差为3.1%~14.3%,方法检出限为1.1 ~1.8 ng/L。本方法准确度和灵敏度高,适用于快速测定地表水中8种亚硝胺类化合物含量。     

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。     

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.     

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.     

天津市地表水体与沉积物中7种高关注酚类化合物的污染特征与生态风险分析

为探究地表水体与沉积物中酚类化合物的污染分布特征和生态风险,选择天津市3个水源地与6条主要河流,采集了26个地表水样与6个沉积物样品,利用固相萃取与超声萃取、高效液相色谱-串联质谱法(HPLC-MS/MS)测定了水样及沉积物中1-萘酚(1-naphthol)、壬基酚(nonylphenol, NP)、双酚A(bisphenol A, BPA)、2-苯基苯酚(biphenyl-2-ol)、3,4-二氯酚(3,4-dichlorophenol)、四溴双酚A(tetrabromobisphenol A, TBBPA)和对叔丁基苯酚(p-tert-butylphenol, PTBP)等7种高关注酚类化合物的浓度水平,并应用物种敏感性分布(species sensitivity distribution, SSD)法和熵值法(ecological risk quotient, RQ)评估7种酚类化合物水环境和沉积物的生态风险。结果表明,地表水样中7种酚类化合物均全部检出;其中壬基酚的检出浓度最高,其次为四溴双酚A、对叔丁基苯酚、1-萘酚、2-苯基苯酚、3,4-二氯酚和双酚A。沉积物中酚类化合物的污染分布规律与水样相似,除双酚A外的目标物全部检出。其中,壬基酚浓度比其他物质浓度高2个数量级。风险评估结果显示,壬基酚对水环境与沉积物存在不可接受的风险;而四溴双酚A、对叔丁基苯酚、1-萘酚、2-苯基苯酚、3,4-二氯酚和双酚A则对环境具有较低风险或者存在一定的风险。     

Biofiltration and disinfection codetermine the bacterial antibiotic resistome in drinking water: A review and meta-analysis

• Published data was used to analyze the fate of ARGs in water treatment. • Biomass removal leads to the reduction in absolute abundance of ARGs. • Mechanism that filter biofilm maintain ARB/ARGs was summarized. • Potential BAR risks caused by biofiltration and chlorination were proposed. The bacterial antibiotic resistome (BAR) is one of the most serious contemporary medical challenges. The BAR problem in drinking water is receiving growing attention. In this study, we focused on the distribution, changes, and health risks of the BAR throughout the drinking water treatment system. We extracted the antibiotic resistance gene (ARG) data from recent publications and analyzed ARG profiles based on diversity, absolute abundance, and relative abundance. The absolute abundance of ARG was found to decrease with water treatment processes and was positively correlated with the abundance of 16S rRNA (r² = 0.963, p<0.001), indicating that the reduction of ARG concentration was accompanied by decreasing biomass. Among treatment processes, biofiltration and chlorination were discovered to play important roles in shaping the bacterial antibiotic resistome. Chlorination exhibited positive effects in controlling the diversity of ARG, while biofiltration, especially granular activated carbon filtration, increased the diversity of ARG. Both biofiltration and chlorination altered the structure of the resistome by affecting relative ARG abundance. In addition, we analyzed the mechanism behind the impact of biofiltration and chlorination on the bacterial antibiotic resistome. By intercepting influent ARG-carrying bacteria, biofilters can enrich various ARGs and maintain ARGs in biofilm. Chlorination further selects bacteria co-resistant to chlorine and antibiotics. Finally, we proposed the BAR health risks caused by biofiltration and chlorination in water treatment. To reduce potential BAR risk in drinking water, membrane filtration technology and water boiling are recommended at the point of use.