活性碳纤维吸附处理对硝基苯酚生产废水

采用活性碳纤维(ACF)吸附处理对硝基苯酚(PNP)生产废水,考察了动态吸附和脱附过程.实验结果表明,在298 K、pH 4时,最佳进水流量为0.25 L/h,ACF的有效吸附量为439.3 mg/g,PNP去除率大于99.95%,TOC去除率大于99.5%,脱附率大于99.5%,ACF的吸附--脱附性能稳定.ACF吸附和电解相结合的工艺能有效去除废水中的有害物质,回收利用PNP和氯化钠,实现了PNP的清洁生产.     

选择性催化还原烟气脱硝技术在玉环电厂4×1000MW机组上的应用

以华能玉环电厂4×1000MW机组增设烟气选择性催化还原法（SCR）脱硝装置的技术改造为例,简要介绍了玉环电厂原机组增加SCR脱硝系统的工艺构成和流程特点、设计参数、总体布置,并对该工程中相关设备的改造进行了描述,为我国大型燃煤机组的脱硝改造工程提供参考。     

应用AHP进行气体灭火系统的优选

在研究了CO2、FM-200(七氟丙烷)、烟烙尽(INERGEN)及气溶胶等气体灭火技术特点的基础上,通过对这4种灭火剂的灭火效率、安全性、环保性和经济性4项性能指标进行AHP综合分析,分析结果表明,气溶胶灭火系统是现阶段最具优势的哈龙替代物.     

Mathematical analysis of the whole core injection method accuracy for measuring phenanthrene biodegradation rates in undisturbed marine sediments

Rates of 14C-phenanthrene mineralization in contaminated, undisturbed marine sediments were measured using the whole core injection method to assess microbial natural attenuation activity as a function of sediment depth. Submerged sediments were sampled from Eagle Harbor, a marine superfund site in Puget Sound. Experiments show significant biodegradation activities (0.0012-0.0036 day(-1)) in the sediment horizons from 0 to 10 cm. The purpose and scope of this paper is to evaluate the range of experimental conditions giving valid results; a mathematical simulation described competing contaminant 14C-phenanthrene diffusion and simultaneous biodegradation (Monod kinetics), both retarded by sorption. The effect of aging was examined with two sorption models in presumed pseudo-homogenous sediments having effective properties. The simulation predictions provide quantitative guidelines for the successful use of the whole core injection method. (1) The effective Monod constant KS' in sediment is increased by a large partition coefficient KP between sediment and water and makes the apparent 14C-phenanthrene biodegradation approach first-order kinetics. (2) When KS'>1 mg(-1) l(-1), the measured 14C-phenanthrene biodegradation extent is biased by inadequately distributed injected tracer only when less than 7% of the sediment horizon is initially probed and mixed with injected tracer. (3) A short incubation time (<20 days) is necessary when a mobile indicator, e.g., gaseous 14CO2, is used. For longer incubation times, predictions show that a 14CO2 indicator diffuses to adjacent horizons, thus smearing the depth profile of biodegradation. (4) This method employing a radiolabeled tracer provides accurate biodegradation rates for freshly contaminated sediments, and represents an upper limit to the natural phenanthrene biodegradation extents if the contaminant is aged over 50 days.     

Challenges in quantifying biosphere-atmosphere exchange of nitrogen species

Recent research in nitrogen exchange with the atmosphere has separated research communities according to N form. The integrated perspective needed to quantify the net effect of N on greenhouse-gas balance is being addressed by the NitroEurope Integrated Project (NEU). Recent advances have depended on improved methodologies, while ongoing challenges include gas-aerosol interactions, organic nitrogen and N(2) fluxes. The NEU strategy applies a 3-tier Flux Network together with a Manipulation Network of global-change experiments, linked by common protocols to facilitate model application. Substantial progress has been made in modelling N fluxes, especially for N(2)O, NO and bi-directional NH(3) exchange. Landscape analysis represents an emerging challenge to address the spatial interactions between farms, fields, ecosystems, catchments and air dispersion/deposition. European up-scaling of N fluxes is highly uncertain and a key priority is for better data on agricultural practices. Finally, attention is needed to develop N flux verification procedures to assess compliance with international protocols.     

Dissipation and residue of triforine in strawberry and soil

Two independent field trials were performed in Guangdong and Hubei, China in 2011 to investigate the dissipation and residue levels of triforine in strawberry and soil. A fast and simple method using gas chromatography with electron capture detector was developed and validated to determine triforine levels in strawberry and soil. The average recovery of triforine in strawberry ranged from 87.46 to 104.32 % with a relative standard deviation (RSD) of 0.72 to 4.54 %; that in soil ranged from 83.82 to 103.01 % with an RSD of 3.89 to 4.36 %. The limit of quantification of the proposed method was 0.01 mg/kg for both strawberry and soil. The results suggest that the triforine dissipation curves followed the first-order kinetic. The half-lives of triforine in strawberry from Guangdong and Hubei were 3.58 and 4.42 days, respectively; those in soil were 3.53 and 4.10 days, respectively. The terminal residues of triforine in strawberry ranged from 0.032 to 0.264 mg/kg at preharvest intervals of 0.5, 1, and 3 days. These values are lower than the maximum residue limit of 1 mg/kg in strawberry set by the Codex Alimentarius Commission.     

Mapping afforestation and deforestation from 1974 to 2012 using Landsat time-series stacks in Yulin District, a key region of the Three-North Shelter region, China

The Three-North Shelter Forest Program is the largest afforestation reconstruction project in the world. Remote sensing is a crucial tool to map land use and land cover change, but it is still challenging to accurately quantify the change in forest extent from time-series satellite images. In this paper, 30 Landsat MSS/TM/ETM+ epochs from 1974 to 2012 were collected, and the high-quality ground surface reflectance (GSR) time-series images were processed by integrating the 6S atmosphere transfer model and a relative reflectance normalization algorithm. Subsequently, we developed a vegetation change tracking method to reconstruct the forest change history (afforestation and deforestation) from the time-series Landsat GSR images based on the integrated forest z-score (IFZ) model by Huang et al. (2009a), which was improved by multi-phenological IFZ models and the smoothing processing of IFZ data for afforestation mapping. The mapping result showed a large increase in the extent of forest, from 380,394 ha (14.8 % of total district area) in 1974 to 1,128,380 ha (43.9 %) in 2010. Finally, the land cover and forest change map was validated with an overall accuracy of 89.1 % and a kappa coefficient of 0.858. The forest change time was also successfully retrieved, with 22.2 % and 86.5 % of the change pixels attributed to the correct epoch and within three epochs, respectively. The results confirmed a great achievement of the ecological revegetation projects in Yulin district over the last 40 years and also illustrated the potential of the time-series of Landsat images for detecting forest changes and estimating tree age for the artificial forest in a semi-arid zone strongly influenced by human activities.     

Development of a multi-criteria index ranking system for urban runoff best management practices (BMPs) selection

Low impact development best management practices (LID-BMPs) are considered to be cost-effective measures for mitigating the water quantity and quality impact of urban runoff. Currently, there are many types of LID-BMPs, and each type has its own intrinsic technical and/or economical characteristics and limitations for implementation. The selection of the most appropriate BMP type(s) for a specific installation site is therefore a very important planning step. In the present study, a multi-criteria selection index system (MCIS) for LID-BMP planning was developed. The selection indexes include 12 first-level indices and 26 second-level indices which reflect the specific installation site characteristics pertaining to site suitability, runoff control performance, and economics of implementation. A mechanism for ranking the BMPs was devised. First, each individual second-level index was assigned a numeric value that was based on site characteristics and information on LID-BMPs. The quantified indices were normalized and then integrated to obtain the score for each of the first-level index. The final evaluation scores of each LID-BMP were then calculated based on the scores for the first-level indices. Finally, the appropriate BMP types for a specific installation site were determined according to the rank of the final evaluation scores. In order to facilitate the application of the MCIS BMP ranking system, the computational process has been coded into a software program, BMPSELEC. A case study demonstrating the MCIS methodology, using an LID-BMP implementation planning at a college campus in Foshan, Guangdong Province, is presented.     

The backend design of an environmental monitoring system upon real-time prediction of groundwater level fluctuation under the hillslope

The groundwater level represents a critical factor to evaluate hillside landslides. A monitoring system upon the real-time prediction platform with online analytical functions is important to forecast the groundwater level due to instantaneously monitored data when the heavy precipitation raises the groundwater level under the hillslope and causes instability. This study is to design the backend of an environmental monitoring system with efficient algorithms for machine learning and knowledge bank for the groundwater level fluctuation prediction. A Web-based platform upon the model-view controller-based architecture is established with technology of Web services and engineering data warehouse to support online analytical process and feedback risk assessment parameters for real-time prediction. The proposed system incorporates models of hydrological computation, machine learning, Web services, and online prediction to satisfy varieties of risk assessment requirements and approaches of hazard prevention. The rainfall data monitored from the potential landslide area at Lu-Shan, Nantou and Li-Shan, Taichung, in Taiwan, are applied to examine the system design.     

Robust Regression with Data-Dependent Regularization Parameters and Autoregressive Temporal Correlations

We introduce robust procedures for analyzing water quality data collected over time. One challenging task in analyzing such data is how to achieve robustness in presence of outliers while maintaining high estimation efficiency so that we can draw valid conclusions and provide useful advices in water management. The robust approach requires specification of a loss function such as the Huber, Tukey’s bisquare and the exponential loss function, and an associated tuning parameter determining the extent of robustness needed. High robustness is at the cost of efficiency loss in parameter loss. To this end, we propose a data-driven method which leads to more efficient parameter estimation. This data-dependent approach allows us to choose a regularization (tuning) parameter that depends on the proportion of “outliers” in the data so that estimation efficiency is maximized. We illustrate the proposed methods using a study on ammonium nitrogen concentrations from two sites in the Huaihe River in China, where the interest is in quantifying the trend in the most recent years while accounting for possible temporal correlations and “irregular” observations in earlier years.