自来水中痕量挥发性有机物的测定

近十年来,水中污染物的鉴定及分析逐渐引起了人们的重视,BOD、COD及TOC指标的测定只能说明有机污染物的存在,并不能提供关于污染物分子结构特性及其毒性的重要信息.水中原来就不同程度地含有一些有机和无机化合物,经过自来水厂氯化处理后会形成一系列挥发性有机卤化物,其中有些是已知的致癌物.因此,饮用水氯化处理与人体健康的关系受到人们的密切关注,水中痕量有机挥发物的分析已成为环境化学研究中的重大课题之一.填充柱GC/ECD测定法由于柱容量大,而且有较高的分析灵敏度,所以适合水中挥发性卤化物的常规测定,但是对复杂组分的分离不甚理想,     

SBR中生物除磷颗粒污泥的反硝化聚磷研究

反硝化聚磷菌(DNPAOs)可利用厌氧储存的聚.3.羟基丁酸(PHB)以硝酸盐和亚硝酸盐为电子受体进行过量吸磷和反硝化,从而达到在低碳源下脱氮除磷的双重目的.本试验在SBR反应器中,采用厌氧,缺氧/好氧(A/A/O)交替运行的方式.将富集聚磷菌(PAOs)的颗粒污泥成功地诱导为具有反硝化聚磷能力的颗粒污泥.诱导结束后P的去除率在90%以上,NOx-N的去除率在93%以上,厌氧段释磷量在25-33 mg/L,缺氧段每去除lg NOx-N吸收P约1.3 g;典型周期运行结果显示,厌氧段最大比释磷速率(SRPR)为18.39 mg/(g.h),缺氧段最大比吸磷速率(SUPR)为23.72 mg/(g·h),最大比反硝化速率(SDNR)为18.19mg/(g·h),好氧段最大SUPR为17.15 me,/(g·h):颗粒污泥中DNPAOs的数量由诱导前的14.9%增加到80.7%.与除磷颗粒污泥相比.反硝化聚磷颗粒污泥沉速提高0.16-0.7倍,比重提高0.003 1.     

油气管道风险评价研究

管道风险评价作为管道风险管理的基础,其目的是通过计算某段管道或整条管道系统的风险值对各个管段(或各条管道)进行风险排序,以识别高风险的部位,确定那些最大可能导致管道事故和有利于潜在事故预防的至关重要的因素,确定管段维护的优先次序,为维护活动经济性的决策提供依据,最终使管道的运行管理更加科学化。本文对油气管道风险评价现状及评价方法进行描述,并提出我国油气管道风险评价技术的对策。     

水源热泵空调系统的水质处理技术

针对影响水源热泵系统运行效能的地下水水质和回灌过程中井堵塞的问题,提出相应的水质处理方法和水源热泵用地下水水质参考标准.     

Modification of ferrite–manganese oxide sorbent by doping with cerium oxide

Fe–Mn oxide and Ce-doped Fe–Mn oxide sorbents were studied on the structural and desulfurization behavior in COS removal from syngas. The effects of cerium oxide on the Fe–Mn oxides have been investigated by XRD, BET, TPR, XPS and TEM methods. Analysis data show that the Ce-doped sorbent has larger specific surface area and better particles’ dispersion compared with non-modified Fe–Mn sorbent. The addition of Ce improves the reduction performance of Fe–Mn species. The desulfurization experiments show that the desulfurization activity of sorbent can be increased because of the promotion of the structural and redox properties by ceria doped. The Ce-doped sorbent can reduce COS from 15,000 ppmv to less than 0.1 ppmv at 325 °C and a space velocity of 1000 h⁻¹.     

Ozone concentrations, flux and potential effect on yield during wheat growth in the Northwest-Shandong Plain of China

Ozone (O₃) concentration and flux (F_o) were measured using the eddy covariance technique over a wheat field in the Northwest-Shandong Plain of China. The O₃-induced wheat yield loss was estimated by utilizing O₃ exposure-response models. The results showed that: (1) During the growing season (7 March to 7 June, 2012), the minimum (16.1 ppbV) and maximum (53.3 ppbV) mean O₃ concentrations occurred at approximately 6:30 and 16:00, respectively. The mean and maximum of all measured O₃ concentrations were 31.3 and 128.4 ppbV, respectively. The variation of O₃ concentration was mainly affected by solar radiation and temperature. (2) The mean diurnal variation of deposition velocity (V_d) can be divided into four phases, and the maximum occurred at noon (12:00). Averaged V_d during daytime (6:00–18:00) and nighttime (18:00–6:00) were 0.42 and 0.14 cm/sec, respectively. The maximum of measured V_d was about 1.5 cm/sec. The magnitude of V_d was influenced by the wheat growing stage, and its variation was significantly correlated with both global radiation and friction velocity. (3) The maximum mean F_o appeared at 14:00, and the maximum measured F_o was − 33.5 nmol/(m²·sec). Averaged F_o during daytime and nighttime were − 6.9 and − 1.5 nmol/(m²·sec), respectively. (4) Using O₃ exposure-response functions obtained from the USA, Europe, and China, the O₃-induced wheat yield reduction in the district was estimated as 12.9% on average (5.5%–23.3%). Large uncertainties were related to the statistical methods and environmental conditions involved in deriving the exposure-response functions.     

厌氧膨胀床处理低浓度污水的污泥颗粒和生物活性变化

污泥的聚集形态和活性,是影响厌氧反应器处理效率的关键因素。通过对厌氧膨胀床反应器（anaerobicex—pandedblanketreactor,AEBR）处理低浓度城镇污水在启动和稳定运行期的污泥活性研究,AEBR在启动运行期内,接种颗粒污泥为适应低浓度基质条件,污泥粒径经历从大变小,再重新颗粒化粒径变大的过程。在运行期第103天,粒径小于1000μm污泥的体积比达到44．7％,平均粒径为952μm,到运行期第173天,粒径小于1000μm污泥的体积比降为28％,平均粒径达1179μm,污泥重新颗粒化完成。颗粒污泥适应新的环境后,单位重量污泥的最大比产甲烷活性（specificmetha．nogensisactivity,SMA）值和胞外聚合物含量增加,分别达到112mLCH4／（gVSS·d）和215mg／gVSS。在处理实际城镇污水的AEBR反应器内,辅酶F420含量可以有效指示污泥样品的产甲烷活性,AEBR反应器不同高度位置的污泥活性不一样,反应器底部污泥活性低于中上部区域污泥的活性。     

Comparison of the daily global solar radiation from different data sources in Northwest China climate

The solar radiation data are of high importance to the solar energy systems. Conventional methods to obtain the solar radiation data are from weather stations, solar radiation models, commercial software databases, and field measurements. In the present study, a new daily global solar radiation model is proposed, by combining the quadratic function of sunshine fraction and sine function of the day of the year. The solar radiation model calculated data are then compared with China Meteorological Data Sharing System (CMDSS) data, TRNSYS data, and field-measured data in Northwest China climate. It is found that the newly proposed solar radiation model has better performance than the other nine solar radiation models in the literature. The solar radiation model calculated data fit well with the CMDSS annually average data. The TRNSYS data are a bit larger than the CMDSS annually average data in summer half year and a little smaller than those in winter half year. The solar radiation model and the CMDSS annually average data have the best correlation, whereas the TRNSYS data and the field-measured data have the worst correlation. The solar radiation model calculated data have the best correlation with the other three data sources.     

Approaching the upper boundary of driver-response relationships: identifying factors using a novel framework integrating quantile regression with interpretable machine learning

● A novel framework integrating quantile regression with machine learning is proposed. ● It aims to identify factors driving observations to upper boundary of relationship. ● Increasing N:P and TN concentration help fulfill the effect of TP on CHL. ● Wetter and warmer decrease potential and increase eutrophication control difficulty. ● The framework advances applications of quantile regression and machine learning. The identification of factors that may be forcing ecological observations to approach the upper boundary provides insight into potential mechanisms affecting driver-response relationships, and can help inform ecosystem management, but has rarely been explored. In this study, we propose a novel framework integrating quantile regression with interpretable machine learning. In the first stage of the framework, we estimate the upper boundary of a driver-response relationship using quantile regression. Next, we calculate “potentials” of the response variable depending on the driver, which are defined as vertical distances from the estimated upper boundary of the relationship to observations in the driver-response variable scatter plot. Finally, we identify key factors impacting the potential using a machine learning model. We illustrate the necessary steps to implement the framework using the total phosphorus (TP)-Chlorophyll a (CHL) relationship in lakes across the continental US. We found that the nitrogen to phosphorus ratio (N׃P), annual average precipitation, total nitrogen (TN), and summer average air temperature were key factors impacting the potential of CHL depending on TP. We further revealed important implications of our findings for lake eutrophication management. The important role of N׃P and TN on the potential highlights the co-limitation of phosphorus and nitrogen and indicates the need for dual nutrient criteria. Future wetter and/or warmer climate scenarios can decrease the potential which may reduce the efficacy of lake eutrophication management. The novel framework advances the application of quantile regression to identify factors driving observations to approach the upper boundary of driver-response relationships.     

超声-臭氧氧化处理硝基苯废水实验研究

在实验装置上对超声-臭氧氧化处理硝基苯废水进行了实验研究，主要考察了废水初始pH值、反应时间，臭氧通入量、超声功率等因素对硝基苯去除率的影响，实验结果表明，超声辐射可以在臭氧氧化过程中起加速反应的作用，而且随着超声功率的增大，加速反应的能力增强；废水初始pH值为11时硝基苯去除效果最佳；随着臭氧通入量的增大，反应时间的延长，硝基苯去除率不断增大；超声-臭氧处理硝基苯废水过程中硝基苯的降解规律为表现一级反应。