额济纳绿洲生态环境演变的研究

根据实地考察和资料分析,对内蒙古额济纳绿洲生态环境的演变进行了研究,并提出防止绿洲生态环境退化的措施     

天津地区土壤中萘的生态风险分析

以天津地区表土188个样点的实测萘浓度以及萘对10种代表性土壤生物的半致死浓度为基础资料,尝试用3种方式评价了该地区土壤中萘的生态风险.并进行了方法学比较.研究结果发现,暴露浓度和毒性效应概率密度函数的重叠面积与联合概率曲线一致地反映出很低的生态风险,准确计算的暴露浓度超过LC50的概率仅为1.67%.结果说明该地区土壤萘的生态风险极低,仅严重污染的局部地区可能发生最敏感生物种受害.用于进行风险评价的3种方法各有利弊.     

提高环评报告书质量加快浙江省环境影响评价有效性建设

影响环境影响评价(EIA)有效性的因素较多．如相应的政策法规、管理机制和技术的正确性等。文章从环评技术角度出发,以抽样选取的浙江省1997～2001年间完成的100本环评报告书(EIS)为统计对象．按建设项目环保审批6项原则为依据,从产业政策符合性、选址与总图布局合理性、清洁生产、达标排放、总量控制、区域环境质量可达性等方面进行分析．评估了浙江省EIA有效性,探讨了目前EIA中存在的问题及原冈,提出了一些提高EIS质量、加快浙江省EIA有效性建设的建议     

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．     

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...     

智能型防碰天车装置的安全可靠性分析

针对目前油田钻井现场使用的智能型防碰天车装置存在一些安全问题，分析了问题的实质是设计测量精度和安全可靠性不高。提出了具体改进设计的方案与意见。     

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.     

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。