农户专业化对农业低碳化的影响研究————来自北京市蔬菜种植户的证据

农户专业化和农业低碳化是农业现代化和农业可持续发展的必然环节,研究农户专业化对农业低碳化的影响具有重要意义.论文运用专业化分工理论和低碳经济理论分析了农户专业化对农业低碳化的影响.然后,根据2013年北京市蔬菜种植户的实地调查数据,运用联立方程组模型的似不相关回归(SUR)方法对理论分析结果进行了实证检验.结果表明:农户专业化与农业碳排放在5%的显著性水平上负相关,而农户专业化与农业产出和农业碳生产率均在1%的显著性水平上正相关.理论分析结果得到了经验验证,说明农户专业化对农业低碳化具有显著的正向影响.     

Instream and offstream environmental conditions and stream biotic integrity: Importance of scale and site similarities for learning and prediction

Two different methods to predict biotic integrity were tested and compared in the present paper. The first one tries to predict the fish indices of biotic integrity (IBI) at the state or regional scale based on the most similar observations to a specific target site of interest using the simple to implement k-nearest neighbors (or kNN) method. Two different distance functions were considered to find the k-nearest neighbors: the Euclidean and the Mahalanobis. The second method was applied on the same datasets and consisted of a step-wise multiple regression. The two modeling approaches yielded similar results but kNN proved to be more time-efficient and very fast computationally for the given dataset sizes, which allowed applying a leave-one-out cross validation.In an attempt to reveal the importance of scale in the prediction of IBI, regression models were constructed at the state (or regional) scale and at the more refined cluster of sampling sites scale. Clusters of sites were extracted using Kohonen's self-organizing maps (SOM) followed by k-means clustering of the SOM neurons. Cluster-level regression models, constructed after site patterning, performed better in IBI prediction than global regression models constructed without any previous site patterning. The importance of identifying groups of sites with similar environmental characteristics affecting the IBI was revealed. The combined use of site patterning and regression modeling for IBI prediction also helped identifying important variables acting at the local scale which remain latent at the global scale.     

A comparison of two models with Landsat data for estimating above ground grassland biomass in Inner Mongolia,China

Two models, artificial neural network (ANN) and multiple linear regression (MLR), were developed to estimate typical grassland aboveground dry biomass in Xilingol River Basin, Inner Mongolia, China. The normalized difference vegetation index (NDVI) and topographic variables (elevation, aspect, and slope) were combined with atmospherically corrected reflectance from the Landsat ETM+ reflective bands as the candidate input variables for building both models. Seven variables (NDVI, aspect, and bands 1, 3, 4, 5 and 7) were selected by the ANN model (implemented in Statistica 6.0 neural network module), while six (elevation, NDVI, and bands 1, 3, 5 and 7) were picked to fit the MLR function after a stepwise analysis was executed between the candidate input variables and the above ground dry biomass. Both models achieved reasonable results with RMSEs ranging from 39.88% to 50.08%. The ANN model provided a more accurate estimation (RMSE_r = 39.88% for the training set, and RMSE_r = 42.36% for the testing set) than MLR (RMSE_r = 49.51% for the training, and RMSE_r = 53.20% for the testing). The final above ground dry biomass maps of the research area were produced based on the ANN and MLR models, generating the estimated mean values of 121 and 147 g/m², respectively.     

太湖水体Chl-a预测模型ARIMA的构建及应用优化

叶绿素a（Chl-a）是湖泊浮游植物生物量的重要指标,其含量能反映水中浮游植物的丰度和变化规律.以1999年12月~2019年8月太湖水体Chl-a和环境因子的逐月监测数据为基础,运用主成分分析方法探讨了Chl-a与环境因子的关系,据此建立了Chl-a与主要环境因素之间的多元线性逐步回归模型及自回归综合移动平均模型（ARIMA）.结果表明：①太湖Chl-a浓度存在着明显的季节变化,且总体处于上升趋势.总磷（TP）、高锰酸盐指数、月均气温（MAT）和月度降雨量（MR）与Chl-a浓度存在较好的变化同步性,总氮（TN）和氨氮（NH₄⁺-N）则表现出明显的滞后性.②主成分分析结果表明,太湖水体藻类暴发条件不仅仅是基于N和P等限制性因素,而是发展为TN、NH₄⁺-N、TP和高锰酸盐指数、MR和MAT等多元因素的综合影响.③两种模型经验证比较,基于1999~2019年逐月资料建立的Chl-a浓度的ARIMA模型模拟效果和预测精度明显优于所建立的多元线性逐步回归模型,特别是在考虑主要环境因素作为自变量及优化自变量取值情况下其预测效果得到进一步提升.建立的ARIMA（0,1,1）（0,1,1）模型将有助于太湖藻类暴发的预报和预警,并为及时有效地安排水资源调度及调控等水环境管理措施提供依据.     

Investigation of PCDD/Fs and dl-PCBs in fish from the southern Baltic Sea during the 2002–2006 period

Concentrations of polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs), and dioxin-like polychlorinated biphenyls (dl-PCBs) in the southern Baltic herring (Clupea harengus), sprat (Sprattus sprattus), and salmon (Salmo salar) are reported.The significant interspecies and season-specific differences in PCDD/Fs and dl-PCBs concentrations were observed. The contribution of dl-PCBs to the total toxicity equivalents (TEQs) ranged between 50% and 70%, dependently on fish species. In all samples, concentrations of PCDF were higher in comparison with that of PCDD.The permissible limits of the content of PCDD/Fs and dl-PCBs (8 pg g⁻¹ fresh weight for the sum of PCDD/Fs and dl-PCBs, and 4 pg g⁻¹ fresh weight for the PCDD/Fs) were exceeded mainly in salmon samples (in 80% of salmon samples studied). The elevated levels of PCDD/F and dl-PCB were observed only in two of seventy two herring samples, and in ten of 62 sprat samples.The multiple regression analysis revealed that fish lipid content, and concentration of PCB 153, used simultaneously, might be useful in the prediction of TEQ values of fish samples. These two variables explained more than 80% of total variance. For all fish species studied, the correlation coefficients obtained with the multiple regression analysis were higher than that obtained with the regression analysis involving total TEQ values, and only one independent variable: fish lipid content.     

丹江口库区可持续发展能力分析

从区域可持续发展的角度出发,以湖北省丹江口库区为例,首先定性分析库区可持续发展的优势与问题,认为库区移民安置工作困难,库区可持续发展受到限制;经济增长缓慢,基础设施建设滞后;城镇化水平较低,库区社会矛盾突出;自然资源丰富与开发不足并存,库区淹没加剧土地资源稀缺;环境质量较好,生态基础脆弱。然后采用多因素综合评价模型定量分析了1999～2005年库区可持续发展的变化趋势。结果表明：库区可持续发展能力从1999年到2003年呈现明显的上升趋势,却从2004年开始缓慢下降;而人口、经济、社会、资源和环境各子系统也呈现出不同的特征。最后针对定性和定量评价结果提出相应的对策建议：做好库区移民安置,实现移民稳定就业;减少和消除移民贫困,增加基础设施建设;加快小城镇建设步伐,解决库区社会矛盾;发挥水资源优势,改善库区生态环境。     

厦门市大气可吸入颗粒物源解析的研究

采用2004～2005年对厦门大气中PM10开展的3期采样分析数据,利用主因子分析法定性分析厦门大气中可吸入颗粒物的主要来源,并结合多元线性回归法,求出定量的结果。分析结果表明,影响厦门市可吸入颗粒物的主要来源有四种:工业燃煤、汽车尾气、土壤风沙尘和海盐粒子,其中二次粒子为主要污染源,贡献率为30.0%,其次为汽车尾气占29.4%,土壤风沙和建筑尘的贡献约占21.7%,海洋粒子的贡献为6.5%,不可识别源18.1%。     

逐步多元线性回归模型解释近年上海市降水pH降低原因

分析2002年-2007年上海市降水化学组成变化特征可得,近年来,上海市降水的pH下降迅速,硫酸根离子与硝酸根离子的比值以及钙铵离子的比值整体上都呈下降趋势。根据上海市降水中的各离子浓度建立了氢离子的逐步多元线性回归模型,并以建立的模型为基础,分析了降水中各主要离子浓度的变化对氢离子浓度的影响大小情况。由模型可以得出,硫酸根离子与硝酸根离子浓度增加时,氢离子浓度也随之增加,铵离子与钙离子浓度增加时。氢离子浓度则随之减小。氢离子变化对4种主要离子的敏感性顺序为：硝酸根〉硫酸根〉钙离子〉铵离子。结合上海市降水化学组成特征分析结果可得,主要离子浓度的变化是导致降水pH快速下降的原因。     

北京市生活垃圾产生量的预测研究

分析了影响北京市城市生活垃圾产生量的因素,采用多元回归分析方法建立了城市生活垃圾年产生量的预测模型.并采用该模型,对2013-2015年北京市城市生活垃圾年产生量进行了预测.结果表明,未来2年北京市城市生活垃圾产生量呈缓慢上升趋势,预计到2015年北京市城市生活垃圾产生量将达到662.4t.