基于绝对主成分-多元线性回归的滇池污染源解析

定量解析污染源是湖泊流域水环境管理的重要基础.基于滇池草海和外海多年水质监测数据,采用主成分分析（PCA）方法识别了主要水质指标的污染源类型,利用绝对主成分-多元线性回归模型（APCS-MLR）得到不同污染源对水质的贡献程度.结果表明,草海主要的污染源有农业面源、城市面源和内源3类,外海的主要污染源是农业面源、城镇生活污染源、城市面源和内源4类.与河流水污染源解析结果不同,底泥内源与气象因子对滇池主要水质指标的影响较大.     

滆湖水华初期浮游植物群落特征及与水环境因子相关性分析

为探究滆湖水华初期浮游植物群落特征及与水环境因子的相关性,于2018年5—7月在全湖布设22个点,调查研究滆湖水华初期浮游植物群落时空分布特征,并对引起水华主导环境因子进行分析.结果表明：①共获得7门119属,优势属为绿藻门的小球藻与球团藻、蓝藻门的鞘丝藻与微囊藻,其中湖心区域浮游植物丰度与多样性小,均匀性低,属于中偏重污染区域;湖北区以北属于中污染区域,蓝藻堆积严重;西部沿岸及南端区域属于中偏轻污染区域.②冗余分析得出,湖心藻类与水温（T）有强相关性,与叶绿素a（Chl-a）、溶解性总磷（DTP）、pH、溶解氧（DO）呈一定正相关性;湖北区以北藻类与底泥有机质（OM）、水体悬浮物（SS）、Chl-a及DTP呈强相关性,与T呈一定相关性.T与多项环境因子相关,均值从26.1℃上升到32.4℃;OM与有机磷（OP）呈高度相关性（p<0.05,r=0.892）.水华发生的主导环境因子为T、DTP与pH,底泥OM及OP有一定影响.     

中国“四化”建设对水足迹强度的影响分析

采用2000—2016年中国30省市（不包括香港、澳门、台湾、西藏四省区）的数据,构建四化指标体系,计算四化发展指数,进行地区四化水平评价,通过OLS和GMM回归模型考察四化发展对水足迹强度的影响,同时设置四化之间的交互项来识别四化指标之间的相互作用。主要结论如下：首先,从四化水平的地域发展差异上来看,中国四化水平总体上呈现出东部优于中部、中部优于西部的格局,水足迹强度的分布与之类似,说明四化水平发展与水足迹强度之间可能存在相关关系;其次,计量模型显示四化水平的提升对于水足迹强度的改善有积极影响,但每一化对于水足迹强度改善的影响大小不一;第三,以交互项衡量的四化相互作用对于水足迹强度的影响作用为正,表明四化发展对水足迹强度的改善效果逐渐趋于收敛。因此,优先提升落后地区的四化水平,以四化水平的提升推动水足迹强度的降低,能够有效降低我国总体水足迹强度水平。     

铜合金实验室试验与实海挂片结果的比较与分析

目的比较实验室试验结果与实海挂片结果对B10和H62两种铜合金腐蚀性能评价的异同之处。方法采用线性极化、电化学阻抗、显微形貌观察等,比较两种铜合金在实验室模拟海水中的的腐蚀速率、点蚀倾向,结合反应机理、腐蚀形貌、环境等外部因素,分析导致实验室与实海环境下出现差异的原因。结果除榆林海域外,实海挂片与实验室结果都表明,B10试样的平均腐蚀速率小于H62。B10和H62两种铜合金随温度升高腐蚀速率增大,在实验室和实海情况下表现出一致性,且平均腐蚀速率都随浸泡时间的延长而降低。结论在实海环境中,温度不是影响点蚀的主要因素,微生物等其他环境因素会对点蚀产生较大影响。     

海河下游水体中DO与NH_3-N、COD_(Mn)相关关系探讨

本文应用近年来海河下游监测数据对ＤＯ与ＮＨ３Ｎ和ＣＯＤＭｎ进行一元线性回归，得到两回归方程：ＮＨ３Ｎ＝－１２８ＤＯ＋１０５４；ＣＯＤＭｎ＝－１１３ＤＯ＋１６９２。并经相关系数和回归系数显著性检验，表明在９９９％的置信水平下ＤＯ与ＮＨ３Ｎ和ＣＯＤＭｎ线性相关均极其显著     

科技论文的写作

本文介绍了科技论文的写作步骤和基本格式,指出科技论文写作中应注意的事项。     

肿瘤病房医用直线加速器对周围环境电离辐射的调查分析

通过对医院肿瘤病房医用直线加速器机房周围环境的电离辐射监测调查 ,并计算分析各相关人群的年有效剂量当量 ,结果低于《辐射防护规定》(GB870 3- 88)中的标准限值。表明医用直线加速器机房的辐射防护设施设计是安全合理的 ,具有重要的现实意义 ,该辐射防护设施具有推广价值。     

Investigation of the Influence of Seagrass on Fisheries Catch Level Using Isotonic Regression

The relationship between seagrass area and the commercial catch of some economically important South Australian fish species is not known in any quantitative sense. However, there is evidence in the literature to suggest that seagrass decline will detrimentally impact on species abundance and composition, and consequently that the presence or absence of seagrass will compromise the commercial and recreational fishery. In this paper we describe the construction of models based on order restricted (isotonic) regression and discuss the role of seagrass area, in terms of its influence on the level of commercial catch through modifying the effect of fishing 'effort'.     

Modelling of Materials Policies

This paper discusses the REAP1 model and its application for the analysis of CO₂ reduction and waste management policies for Japanese petrochemicals. The pros and cons of this modelling approach in comparison to other tools is elaborated. This is followed by a discussion of the model code and the modelling results. The results show that CO₂ policies can have significant impacts on waste flows and waste policies can have significant CO₂ benefits. As a consequence both effects must be considered in policy assessment. Pricing instruments are recommended instead of regulations because of the complex physical relations in the materials life cycle that extend beyond sector boundaries. A taxation approach is superior to a subsidy approach because rebound effects can be avoided.     

Modeling the spatial pattern of farmland using GIS and multiple logistic regression: a case study of Maotiao River Basin, Guizhou Province, China

Land use change is an important topic in the field of global environmental change and sustainable development. Land use change modeling has attracted substantial attention because it helps researchers understand the mechanisms of land use change and assists regulatory bodies in formulating relevant policies. Maotiao River Basin is located in the province of Guizhou, China, which has a developed agricultural industry in the karst mountain areas. This paper selected biophysical and social–economic factors as independent variables, and constructed a multiple logistic regression of farmland spatial distribution probability by random sampling. Then, by using GIS technology and integrating the 2000 data, this study predicted the farmland spatial pattern. When the predicted map was compared with the actual farmland map for 2000, we noted that 71% of the simulation is in accordance with the 2000 farmland pattern. The result satisfactorily proves the reasonability and applicability of our model.