中国碳排放强度与煤炭消耗的冲击效应分析

受能源消费结构的影响,煤炭作为我国经济发展的资源支柱,一方面推动着经济快速增长,另一方面也对中国节能减排、降低碳排放强度提出了挑战,因而准确认识碳排放强度与煤炭消耗之间的交互冲击作用机理,为挖掘碳减排路径提供了科学依据.本文选取1990 - 2008年间中国碳排放强度与煤炭消耗指标,采用EG协整检验证明碳排放强度与煤炭消耗之间存在长期稳定关系,并以此建立VAR模型和脉冲响应函数,考察碳排放强度与煤炭消耗之间的长期动态影响特征.冲击响应分析结果表明:(1)煤炭消耗比重的变化对碳排放强度的冲击影晌具有一定滞后性和波动性,但冲击作用长期持久;(2)碳排放强度对煤炭消耗比重的冲击影响在短期内较剧烈,但长期冲击影响不明显;(3)煤炭消耗比重的降低在长期内会促使碳排放强度的降低,因而可以通过降低煤炭消耗比重来达到降低碳排放强度的目的.最后,从结构性降低、产业传导性降低以及技术性降低等角度,提出减少煤炭消耗、降低碳排放强度的相关对策措施.     

COMPARISON OF REGRESSION AND TIME-SERIES METHODS FOR SYNTHESIZING MISSING STREAMFLOW RECORDS1

ABSTRACT: Regression and time-series techniques have been used to synthesize and predict the stream flow at the Foresta Bridge gage from information at the upstream Pohono Bridge gage on the Merced River near Yosemite National Park. Using the available data from two time periods (calendar year 1979 and water year 1986), we evaluated the two techniques in their ability to model the variation in the observed flows and in their ability to predict stream flow at the Foresta Bridge gage for the 1979 time period with data from the 1986 time period. Both techniques produced reasonably good estimates and forecasts of the flow at the downstream gage. However, the regression model was found to have a significant amount of autocorrelation in the residuals, which the time-series model was able to eliminate. The time-series technique presented can be of great assistance in arriving at reasonable estimates of flow in data sets that have large missing portions of data.     

MFAM模型在河流水质污染模拟及预测中的应用

文中以时间序列分析为基础，介绍了均值生成函数这一崭新概念，并且经成份因子提取分析推导建立了模拟序列的数字模型（简记为MFAM），经对黄河下游花园口断面的1988-1989年实测水质污染指标溶解氧（DO），氨氧，化学耗氧量（COD），五日生化需氧量（BOD5）等序列模拟，结果表明MFAM模型能较好地模拟河流水质污染指标的变化趋势，拟合平均误差只有5.2-6.4%，MFAM模型应用于预测1990-1991年水质污染指标变化，结果表明预测精度达85%以上，文中最后得出结论：MFAM模型应用于河流污染模拟和预测，是完全可行且十分方便。     

估计近场地震动的统计—经验格林函数法

本文提出统计-经验格林函数法,用以估计缺乏小震记录场点在大震时的地震动时程。统计-经验格林函数的富里哀幅值谱从其它类似场地获得的小震记录的富里哀谱的衰减关系中得到,其相位谱则直接取自小震记录的相位谱。本文分别用经验格林函数法和统计-经验格林函数法,用迁安台记录到的1976年唐山地震的三次余震(M_L 5.8、M_L 5.7和M_L 5.4)的加速度记录,合成唐山地震的最大余震滦县地震(M_s 7.1)时迁安台的加速度时程曲线,合成结果说明了所提方法的可行性。     

FLOOD FREQUENCY ANALYSIS FOR SMALL WATERSHEDS IN SOUTHERN ILLINOIS1

ABSTRACT: Twenty-two gaging stations were selected for developing a regional flood frequency curve for small (area less than 2 square miles) watersheds in southern Illinois. Five probability functions were compared, and the extreme value type I function was selected to develop the regional flood curve. The curve was generated with the index flood method and also another empirical method that related the function parameters to the watershed area. Estimated peak discharges with various return periods were compared with the results obtained from multiple regression analysis.     

Estimation of the shadow prices of pollutants with production/environment inefficiency taken into account: a nonparametric directional distance function approach

This paper deals with the estimation of the shadow prices of pollutants with a nonparametric directional distance function approach, where the inefficiency involved in the production process is taken into account unlike the previous studies. The directional vector, which is critical to the estimation and subject to the criterion for an appropriate efficiency rule proposed here, is calculated by using the annual plans of power plants in terms of production and environment. In the empirical study for Korea's electric power industry during the period of 1990-1995, we find that the average shadow prices of sulfur oxides (SOx), nitrogen oxides (NOx), and total suspended particulates (TSP) are approximately 10% lower than those calculated under the assumption of full efficiency. The methodology we propose and the findings obtained in the empirical study allow us to undertake better decision-making over a broad range of environmental policy issues.     

谈森林防火中的计划火烧

计划火烧是预防森林火灾的一种有效手段,成本低,效果显著。本文详细阐述了计划火烧的意义和作用、计划火烧前的准备工作,并提出了计划火烧的注意事项及实际操作要领。     

经济体制转轨下的环境管理模式初探

党的十五大提出发展多种形式的公有制经济,在这种新形势下,环境管理如何转轨,本文进行了探讨和研究。     

Short-term wind speed forecasting based on random forest model combining ensemble empirical mode decomposition and improved harmony search algorithm

ABSTRACT

Wind speed forecasting plays an important role in power grid dispatching management. This article proposes a short-term wind speed forecasting method based on random forest model combining ensemble empirical modal decomposition and improved harmony search algorithm. First, the initial wind speed data set is decomposed into several ensemble empirical mode functions by EEMD, then feature extraction of each sub-modal IMF is performed using fast Fourier transform to solve the cycle of each sub-modal IMF. Next, combining the high-performance parameter optimization ability of the improved harmony search algorithm, two optimal parameters of random forest model, number of decision trees, and number of split features are determined. Finally, the random forest model is used to forecast the processing results of each submodal IMF. The proposed model is applied to the simulation analysis of historical wind data of Chaoyang District, Liaoning Province from April 27, 2015 to May 22, 2015. To illustrate the suitability and superiority of the EEMD-RF-IHS model, three types of models are used for comparison: single models including ANN, SVM, RF; EMD combination models including EMD-ANN, EMD-SVM, EMD-RF; EEMD combination models including EEMD-ANN, EEMD-SVM, EEMD-RF. The analysis results of evaluation indicators show that the proposed model can effectively forecast short-term wind data with high stability and precision, providing a reference for forecasting application in other industry fields.