应用微通道热泳脱除可吸入颗粒物的可行性研究

将热泳力和微通道流动两项国际前沿热门研究成果相结合．研究微通道内流动的可吸入颗粒物热泳沉积效率的变化规律．选择能描述有别于一般通道的具有强换热特性的微通道公式,计算分析其中换热特性和流动特性．通过在同样条件下一般通道与微通道内,利用热泳的效应,产生的脱除可吸入颗粒物效率的比较,得到在微通道内有大的热泳沉积效率的结论．这一结果给我们利用微通道内热泳脱除可吸入颗粒物以新的启发．通过多微通道组合可以实现高效率脱除可吸入颗粒物．若这一思路能够赋予实践,将为脱除细微的可吸入颗粒物的污染提供重大新途径．     

中国城市污水处理行业的产业化市场化

在对中国城市污水处理产业现状及产业政策分析的基础上,阐述了中国城市污水处理产业发展的定位以及对其产业化、市场化的具体措施作了论述。     

湘江铜霞段镉环境容量模型研究

镉是一种毒性很强的累积性重金属污染物,在<污水综合排放标准>中是第一类污染物.为了控制湘江铜霞段的镉污染,根据该段水环境功能要求及水力学特征,在分析多年水文参数和相应环境监测资料的基础上,根据质量守恒定律,应用稳态二维模型建立了该江段镉环境容量模型.经用该段2002年的3月、6月、9月和12月份的有关监测数据检验,结果表明,模型预测值与实测值相对误差为1.38%～21.4%,具有较好的相关性.该模型可用于该江段镉环境容量及水体中镉浓度时空分布的预测预报,对强化该江段环境管理、实施区域含镉废水污染源总量控制具有指导意义.     

基于文献计量分析的珊瑚礁生态修复技术研究现状及发展趋势

珊瑚礁是海洋生态系统的重要组成部分,具有食物资源、药用价值、海岸防护等生态功能.近年来受到自然气候及人类活动的影响,珊瑚礁生态系统发生了大规模的退化,因此,珊瑚礁生态修复技术逐渐成为研究热点.本文从Web of Science核心合集、CNKI、德温特数据库等获得相关文献,对全球及国内珊瑚礁生态修复技术研究热点进行全面...     

Coupled electrochemical methods for nitrogen and phosphorus recovery from wastewater: a review

Environmental Chemistry Letters - Declining mineral resources, high fertilizer production cost and widespread eutrophication are calling for the recovery of nitrogen and phosphorus from wastewaters...     

Effects of climate and land-cover change on the conservation status of gibbons

Species shift their distribution in response to climate and land-cover change, which may result in a spatial mismatch between currently protected areas (PAs) and priority conservation areas (PCAs). We examined the effects of climate and land-cover change on potential range of gibbons and sought to identify PCAs that would conserve them effectively. We collected global gibbon occurrence points and modeled (ecological niche model) their current and potential 2050s ranges under climate-change and different land-cover-change scenarios. We examined change in range and PA coverage between the current and future ranges of each gibbon species. We applied spatial conservation prioritization to identify the top 30% PCAs for each species. We then determined how much of the PCAs are conserved in each country within the global range of gibbons. On average, 31% (SD 22) of each species’ current range was covered in PAs. PA coverage of the current range of 9 species was <30%. Nine species lost on average 46% (SD 29) of their potential range due to climate change. Under climate-change with an optimistic land-cover-change scenario (B1), 12 species lost 39% (SD 28) of their range. In a pessimistic land-cover-change scenario (A2), 15 species lost 36% (SD 28) of their range. Five species lost significantly more range under the A2 scenario than the B1 scenario (p = 0.01, SD 0.01), suggesting that gibbons will benefit from effective management of land cover. PA coverage of future range was <30% for 11 species. On average, 32% (SD 25) of PCAs were covered by PAs. Indonesia contained more species and PCAs and thus has the greatest responsibility for gibbon conservation. Indonesia, India, and Myanmar need to expand their PAs to fulfill their responsibility to gibbon conservation. Our results provide a baseline for global gibbon conservation, particularly for countries lacking gibbon research capacity.     

MSWNet: A visual deep machine learning method adopting transfer learning based upon ResNet 50 for municipal solid waste sorting

● MSWNet was proposed to classify municipal solid waste. ● Transfer learning could promote the performance of MSWNet. ● Cyclical learning rate was adopted to quickly tune hyperparameters. An intelligent and efficient methodology is needed owning to the continuous increase of global municipal solid waste (MSW). This is because the common methods of manual and semi-mechanical screenings not only consume large amount of manpower and material resources but also accelerate virus community transmission. As the categories of MSW are diverse considering their compositions, chemical reactions, and processing procedures, etc., resulting in low efficiencies in MSW sorting using the traditional methods. Deep machine learning can help MSW sorting becoming into a smarter and more efficient mode. This study for the first time applied MSWNet in MSW sorting, a ResNet-50 with transfer learning. The method of cyclical learning rate was taken to avoid blind finding, and tests were repeated until accidentally encountering a good value. Measures of visualization were also considered to make the MSWNet model more transparent and accountable. Results showed transfer learning enhanced the efficiency of training time (from 741 s to 598.5 s), and improved the accuracy of recognition performance (from 88.50% to 93.50%); MSWNet showed a better performance in MSW classsification in terms of sensitivity (93.50%), precision (93.40%), F1-score (93.40%), accuracy (93.50%) and AUC (92.00%). The findings of this study can be taken as a reference for building the model MSW classification by deep learning, quantifying a suitable learning rate, and changing the data from high dimensions to two dimensions.     

Low-temperature caproate production,microbial diversity,and metabolic pathway in xylose anaerobic fermentation

● Converting xylose to caproate under a low temperature of 20 °C by MCF was verified. ● Final concentration of caproate from xylose in a batch reactor reached 1.6 g/L. ● Changing the substrate to ethanol did not notably increase the caproate production. ● Four genera, including Bifidobacterium , were revealed as caproate producers. ● The FAB pathway and incomplete RBO pathway were revealed via metagenomic analysis. Mixed culture fermentation (MCF) is challenged by the unqualified activity of enriched bacteria and unwanted methane dissolution under low temperatures. In this work, caproate production from xylose was investigated by MCF at a low temperature (20 °C). The results showed that a 9 d long hydraulic retention time (HRT) in a continuously stirred tank reactor was necessary for caproate production (~0.3 g/L, equal to 0.6 g COD/L) from xylose (10 g/L). The caproate concentration in the batch mode was further increased to 1.6 g/L. However, changing the substrate to ethanol did not promote caproate production, resulting in ~1.0 g/L after 45 d of operation. Four genera, Bifidobacterium, Caproiciproducens, Actinomyces, and Clostridium_sensu_stricto_12, were identified as the enriched caproate-producing bacteria. The enzymes in the fatty acid biosynthesis (FAB) pathway for caproate production were identified via metagenomic analysis. The enzymes for the conversion of (C_n+2)-2,3-Dehydroxyacyl-CoA to (C_n+2)-Acyl-CoA (i.e., EC 1.3.1.8 and EC 1.3.1.38) in the reverse β-oxidation (RBO) pathway were not identified. These results could extend the understanding of low-temperature caproate production.     

化学吸收法采集固定污染源氨气的影响因素探究

固定污染源氨气的手工监测,干扰因素较多,其中采样环节尤为关键。实验通过催化氧化-化学发光法考察不同采样管线材质对氨气的吸附效果,离子色谱法考察化学吸收法采集氨气的吸收瓶类型、采样流量、吸收液种类、吸收液浓度及体积等采样条件对氨气吸收效率的影响。实验表明,316 L不锈钢与聚四氟乙烯对氨气的吸附较小,氨气的采样流量不宜超过1.0 L/min,棕色气泡式吸收瓶更适用于氨气样品的采集,磷酸溶液作吸收液对氨气的吸收效率较好,对于低浓度的氨气样品,应采用低流量长时间采集。     

水生态环境质量评价方法及在黄河流域的应用进展

开展水生态环境质量评价方法研究,建立合适的河流健康评价体系是解决河流健康问题的前提和实现河流健康管理的重要手段。黄河自上而下生态环境现状迥异,水生态环境脆弱,寻求一种或多种适合黄河流域水生态环境质量的评价方法具有重要意义。该文介绍了国内外水生态环境质量评价方法及在黄河流域的应用进展,总结了鱼类生物完整性指数(F-IBI)、底栖无脊椎动物完整指数(B-IBI)、着生藻类生物完整性指数(P-IBI)及水生态环境质量综合评价法的主要指标,以及黄河流域不同区域生物种类的评价指标,分析了各评价方法优缺点及应用范围,并根据目前研究基础评述了黄河流域水生态环境质量评价存在的问题,对黄河流域水生态环境质量评价方法、指示生物的选择及水生态环境质量综合评价法的研究等提出了具体建议。