Development of phenanthrene catabolism in natural and artificial soils

The characteristics of natural soils often vary from those of artificial soil (e.g. OECD), which may lead to substantial differences in the bioavailability of test substances. The aim of this investigation was to characterise the development of phenanthrene catabolism in both natural and artificial soils with varying total organic carbon (TOC) content after 1, 14, 42 and 84 d soil-phenanthrene contact time. Indigenous catabolic activity was measured via the addition of 14C-phenanthrene using the respirometric soil slurry assay. Notably, the lag phases, fastest rates and total extents of 14C-phenanthrene degradation were relatively comparable in soils with similar TOC content after 1 d contact time. However, natural soils generally exhibited significantly shorter lag phases, faster rates and higher extents of mineralisation, than their artificial counterparts after 42 and 84 d contact time. Such findings suggest that the extrapolation of results from artificial soils to real/natural soils may not be straightforward.     

When Has an Abandoned Field Become a Semi-Natural Grassland or Heathland?

This study presents a meta-analysis of a collective dataset describing the succession from abandoned fields to semi-natural grassland and heathland vegetation over the past century. The study objectives were to develop a method for statistical discrimination between abandoned fields and semi-natural habitats and to analyze the probability that an abandoned field had developed into a semi-natural habitat. A statistical classification model was developed, based on lists of vascular plants from 2059 plots from Danish semi-natural grasslands and heathlands, and abandoned fields of varying age. This model was shown to discriminate effectively between abandoned fields and semi-natural habitats, and it was found to be potentially useful for the detection of abandoned fields approaching semi-natural vegetation. We suggest that the model may help clarify restoration targets and assess biological condition in formerly cultivated areas. Statistical modeling revealed that succession age, period of abandonment and succession trajectory had significant effects on the probability that abandoned fields reached the semi-natural phase. Our study indicates that restoration projects targeting grassland and heathland should take local species pools and soil fertility into account. Nomenclature: Species names follow Flora Europaea (Tutin and others 1964–1993).     

涤沦仿真丝污水治理的研究

经实验比较了涤沦仿真丝污水治理中常见的两种工艺即“厌氧酸化＋好氧酸化”和“加酸沉淀＋好氧生化”的处理效果,提出了后一种工艺才能真正治理污染的观点。加酸沉淀可去除CODcr77％左右,同时大大提高了污水的可生化性。     

人工替代栖息地对长江口湿地的补充作用研究

利用恢复生态学和景观生态学原理构建人工替代栖息地是恢复和重建生物栖息地环境的重要手段之一,是用于滨海河口区修复或重建滩涂湿地等栖息地的一种替代方法。人工替代栖息地构建出了接近自然原貌的人工系统,创造一种湿地植被和湿地动物可以协调共存的生境,不仅可以为鸟类资源和渔业资源提供良好的栖息环境,其中多样化组合的植被群落在滨水景观、水质净化等方面也起到了重要的作用,对长江口自然湿地的恢复和自然保护区的动态管理具有不可忽视的补充作用。在迁徙鸟类重要中转驿站,珍稀或者经济鱼类的洄游通道,特殊价值的重要湿地景观格局以及水资源战略储备区域中布局人工替代栖息地,可以发挥其对长江口湿地的补充作用,使高度开放而又极为敏感的长江河口地区循着生态健康道路发展。     

A novel method for mapping reefs and subtidal rocky habitats using artificial neural networks

Reefs and subtidal rocky habitats are sites of high biodiversity and productivity which harbour commercially important species of fish and invertebrates. Although the conservation management of reef associated species has been informed using species distribution models (SDM) and community based approaches, to date their use has been constrained to specific regions where the locality and spatial extent of reefs is well known. Much of the world's subtidal habitats remain either undiscovered or unmapped, including coasts of intense human use. Consequently, to facilitate a stronger understanding of species-environmental relationships there is an urgent need for a cost and time effective standard method to map reefs at fine spatial resolutions across broad geographical extents. We used bathymetric data (∼250 m resolution) to calculate the local slope and curvature of the seabed. We then constructed artificial neural networks (ANNs) to forecast the probability of reef occurrence within grid cells as a function of bathymetric and slope variables. Testing over an independent data set not used in training showed that ANNs were able to accurately predict the location of reefs for 86% of all grid cells (Kappa = 0.63) without over fitting. The ANN with greatest support, combining bathymetric values of the target grid cell with the slope of adjacent grid cells, was used to map inshore reef locations around the Southern Australian coastline (∼250 m resolution). Broadly, our results show that reefs are identifiable from coarse-scale bathymetry data of the seabed. We anticipate that our research technique will strengthen systematic conservation planning tools in many regions of the world, by enabling the identification of rocky substratum and mapping in localities that remain poorly surveyed due to logistics or monetary constraints.     

Artificially roughened solar air heater: A comparative study

Artificially roughened solar air heater has been topic in research for the last 30 years. Prediction of heat transfer and fluid flow processes of an artificially roughened solar air heater can be obtained by three approaches: theoretical, experimental, and computational fluid dynamics (CFD). This article provides a comprehensive review of the published literature on the investigations of artificially roughened solar air heater. In the present article, an attempt has been made to present holistic view of various roughness geometries used for creating artificial roughness in solar air heater for heat transfer enhancement. This extensive review reveals that quite a lot of work has been reported on design of artificially roughened solar air heater by experimental approach but only a few studies have been done by theoretical and CFD approaches. Finally this article presents a comparative study of thermo-hydraulic performance of 21 different types of artificial roughness geometries attached on the absorber plate of solar air heater in terms of thermo-hydraulic performance parameter. Heat transfer and friction factor correlations developed by various investigators for different types of artificially roughened solar air heaters have also been reported in this article.     

Artificial neural network based maximum power point tracking controller for photovoltaic standalone system

This article presents a two-stage maximum power point tracking (MPPT) controller using artificial neural network (ANN) for photovoltaic (PV) standalone system, under varying weather conditions of solar irradiation and module temperature. At the first-stage, the ANN algorithm locates the maximum power point (MPP) associated to solar irradiation and module temperature. Then, a simple controller at the second-step, by changing the duty cycle of a DC–DC boost converter, tracks the MPP. In this method, in addition to experimental data collection for training the ANN, a circuit is designed in MATLAB-Simulink to acquire data for whole ranges of weather condition. The whole system is simulated in Simulink. Simulation results show small transient response time, and low power oscillation in steady-state. Furthermore, dynamic response verifies that this method is very fast and precise at tracking the MPP under rapidly changing irradiation, and has very low power oscillation under slowly changing irradiation. Experimental results are provided to verify the simulation results as well.     

Non-linear autoregressive neural network approach for inside air temperature prediction of a pillar cooler

The volcanic plate made pillar cooler system is designed for outdoor spaces as a heat exchanging medium and reduces the outcoming air temperature which flows through the exhaust port. This paper proposes the use of artificial neural networks (ANNs) to predict inside air temperature of a pillar cooler. For this purpose, at first, three statistically significant factors (outside temperature, airing and watering) influencing the inside air temperature of the pillar cooler are identified as input parameters for predicting the output (inside air temperature) and then an ANN was employed to predict the output. In addition, 70%, 15% and 15% data was chosen from a previously obtained data set during the field trial of the pillar cooler for training, testing and validation, respectively, and then an ANN was employed to predict inside air temperature. The training (0.99918), testing (0.99799) and validation errors (0.99432) obtained from the model indicate that the artificial neural network model (NARX) may be used to predict inside air temperature of pillar cooler. This study reveals that, an ANN approach can be used successfully for predicting the performance of pillar cooler.     

Evaluating efforts to build sustainable WEEE reverse logistics network design: comparison of regulatory and non-regulatory approaches

Many developing countries such as Turkey are still making an effort on building an infrastructure for waste of electrical and electronic equipment (WEEE) reverse logistic network design (RLND) processes. It is obvious that policies/laws/regulations related to WEEE management provide a sustainable framework for implementation in the RLND. The question is here: Does the implementation of WEEE directives make sense in terms of reducing the total cost of the network in the long term? This study aims to compare regulatory and non-regulatory situations of WEEE RLND in developing countries by formulating two models named as ‘regulatory’ and ‘non-regulatory’. Model 1 is considered as sustainable with economic, environmental and social goals, and the quotas imposed by the environmental directive are taken into consideration as the data of product return amount. In Model 2, only economic goal is considered, and product return amount is forecasted using Artificial Neural Network (ANN). A case study is conducted in a recycling company in order to evaluate performance of the proposed models. This study contributes to the relevant literature by (1) comparing the regulatory and non-regulatory situations RL models explicitly and (2) proposing ANN model to forecast EEE product return or WEEE quantity for non-regulatory situation.