Application of artificial neural network approach and remotely sensed imagery for regional eco-environmental quality evaluation

Eco-environment quality evaluation is an important research theme in environment management. In the present study, Fuzhou city in China was selected as a study area and a limited number of 222 sampling field sites were first investigated in situ with the help of a GPS device. Every sampling site was assessed by ecological experts and given an Eco-environment Background Value (EBV) based on a scoring and ranking system. The higher the EBV, the better the ecological environmental quality. Then, three types of eco-environmental attributes that are physically-based and easily-quantifiable at a grid level were extracted: (1) remote sensing derived attributes (vegetation index, wetness index, soil brightness index, surface land temperature index), (2) meteorological attributes (annual temperature and annual precipitation), and (3) terrain attribute (elevation). A Back Propagation (BP) Artificial Neural Network (ANN) model was proposed for the EBV validation and prediction. A three-layer BP ANN model was designed to automatically learn the internal relationship using a training set of known EBV and eco-environmental attributes, followed by the application of the model for predicting EBV values across the whole study area. It was found that the performance of the BP ANN model was satisfactory and capable of an overall prediction accuracy of 82.4%, with a Kappa coefficient of 0.801 in the validation. The evaluation results showed that the eco-environmental quality of Fuzhou city is considered as satisfactory. Through analyzing the spatial correlation between the eco-environmental quality and land uses, it was found that the best eco-environmental areas were related to forest lands, whereas the urban area had the relatively worst eco-environmental quality. Human activities are still considered as a major impact on the eco-environmental quality in this area.     

Water quality assessment of Ogun river, South West Nigeria

The quality of Ogun river in South-West, Nigeria was studied by a field survey for a period of 1 year (covering dry season and rainy season). Water samples were collected from thirteen sites and analysed for physico-chemical and bacteriological parameters as well as heavy metals using standard methods. Generally, the values obtained for turbidity, phosphate, oil and grease, iron and faecal coliform from all the sites in both seasons were above the maximum acceptable limit set by the World Health Organization (WHO) for drinking water. Also, the manganese content from all the sites in the dry season, lead concentrations from three sites in the dry season and cadmium concentrations from some sites in both seasons were above the WHO limit. The values obtained for total dissolved solids, dissolved oxygen and chloride at site M in the dry season and nitrate at site J in the rainy season were also above the WHO limit. Pollution of Ogun river water along its course is evidenced by the high concentrations of pollution indicators, nutrients and trace metals above the acceptable limit. This poses a health risk to several rural communities who rely on the river primarily as their source of domestic water. The study showed a need for continuous pollution monitoring programme of surface waters in Nigeria.     

Evaluation of Point and Diffuse Sources of Nutrients in a River Basin on Base of Monitoring Data

The methodology of materials accounting is presented and applied to developing nutrient balance (nitrogen and phosphorus) in a river basin. The method is based on the balance principle: inputs and outputs of each nitrogen and phosphorus related sub-systems were balanced. The application of the methodology strategies was illustrated by means of a case study of the Krka river, Slovenia. Different pathways of emission to surface waters were taken into account: WWTP discharges, direct discharges, erosion/runoff and baseflow. Total annual emission into the river Krka was estimated to be 362 tonnes N/year and 73.3 tonnes P/year. The main sources of nitrogen are diffuse sources, emitted via baseflow (52%). Other important sources are effluents from WWTP, which account for 36% of total emissions. Other sources like erosion and direct discharges to surface water (animal manure, industry, households) are of lower magnitude. Erosion is main source of phosphorus emission (55% of total emission), WWTP effluents account for 37% of total emission, while other sources are less important. Besides reduction of point sources by means of wastewater collection and implementation of nutrient removal technology, managing agricultural nitrogen and phosphorus to protect water quality should become a major challenge in the Krka river basin.     

长江沉积物中痕量氯代酚类化合物的测定

本文利用同位素稀释质谱法对长江南京段沉积物中１８种氯代酚进行了分离鉴定,结果表明,沉积物中ＣＰｓ的含量以五氯苯酚为主,     

毛竹林各组分能量估算模型的研究

在建瓯设置40块毛竹林标准地,分别测定了毛竹单株各部分干重与能量,建立了各部分生物量模型,并在此基础上,运用人工神经网络方法对毛竹林各组分能量进行估测.结果表明毛竹林各组分秆、枝叶和地下部分的平均能量依次为4.23225×10     

中国工业CO_2排放的行业间传导网络及协同减排

工业是碳排放的主要部门,科学识别工业CO_2排放的行业间传导并揭示其联动结构对于跨行业协同减排具有重要的理论和现实意义。本文基于1991-2012年中国工业36个两位数行业数据,在VAR模型框架下,利用Granger因果检验方法对CO_2排放的行业间传导关系进行了识别,并从关系视角出发,借助社会网络分析方法(SNA)揭示工业CO_2排放行业间传导的整体和个体网络结构特征,研究发现:工业CO_2排放的行业间传导呈网络结构形态,网络密度在1-6期的滞后阶数下呈先升高后下降的趋势,并且在滞后2期达到最高;燃气生产和供应业、电力热力生产和供应业、服装业、造纸及纸制品业、木材加工业具有较高的度数中心度、中介中心度、接近中心度,在网络中处于核心位置,并发挥中介和桥梁作用;在CO_2排放的行业传导网络中,煤炭采选业、黑色金属矿采选业、有色金属矿采选业等10个行业属于经纪人板块,医药制造业、饮料制造业、化学纤维制造业等9个行业属于净受益板块,金属制品业、塑料制品业、农副食品加工业等11个行业属于双向溢出板块,烟草加工业、石油加工及炼焦业、燃气生产和供应业等6个行业属于净溢出板块。基于上述结论,本文提出了工业CO_2排放的跨行业协同减排思路。     

三峡蓄水前后宜昌–城陵矶水情多尺度变化特征分析

采用Morlet小波分解重构和频谱分析等方法,对宜昌、枝城、沙市、监利和城陵矶1997~2014年水位和流量及三峡水库2003~2014年入库、出库流量和库水位数据进行了统计分析,探究了各水文站在三峡建坝前后水情的变化特征及原因。结果表明:各观测站的水位和流量沿程递减,水位的年内波动处同一水平,研究河段内上游河段流量年内和年际变化比下游河段剧烈;各水文站水位和流量变化的显著周期为6.05、11.78、21.2、30.29和53个月,各水文站水位1 a周期变化幅度均在2 m以上,其他周期上的变化幅度为0.08~0.82 m;三峡水库蓄水活动对下游水文站水位和流量等水情的影响有限,主要反映在对水情趋势项的影响上,三峡大坝蓄水后,各水文站水位和流量受到一定程度影响,呈波动性递减变化。     

小波网络在大气污染物浓度预测中的应用

提出一种“分解-重构-预测”小波网络的大气污染物浓度的预测方法。通过小波分解,把浓度序列分解为不同频段的小波系数序列,再对各层的小波系数子序列重构到原尺度上,然后对小波系数序列采用相匹配的BP神经网络模型进行预测,最后合成浓度序列的最终预测结果。经对二氧化硫浓度预测证明,该方法预测模型推广能力强,预测精度高。     

以浮游生物为指示生物的苏州河生态安全评价

采用斜生栅藻,羊角月牙藻和大水蚤对苏州河主要几种重金属以及不同河段河水及底泥进行了生态影响实验,得到了以大水蚤EC50为指标的苏州河主要几种重金属生态安全阈值。同时结果还表明,与郊区黄渡段相比,苏州河市区河段河水对供试浮游生物呈现了一定的抑制作用,某些点位的生态影响甚至达到统计学显著性水平。黑泥层底泥抑制作用大于浮泥层底泥。因此,尽管苏州河经过二期整治后,水环境质量的景观指标有明显改善,但市区段河水和底泥对生物定居仍有一定的抑制作用,对苏州河生态安全构成一定的影响。     

城市河道水质恢复技术及发展趋势

在分析城市河道水体污染现状和污染源的基础上,介绍了物理、化学、生物生态等城市河道水质恢复技术,分析了不同技术的优缺点及适用性,并预测了城市河道水体恢复技术的发展趋势。