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Abstract In this paper, the authors have empirically analyzed the convergence in per capita GDP gap and the convergence in the variation of energy intensity with respect to the change of per capita GDP between China and eight developed countries. Then, the authors run a regression on the impact of decisive factors of economic growth on energy intensity and its change, so as to find out the economic mechanism of energy intensity gap changing with respect to the variation of economic growth. This study concludes that: First, there is a convergence in per capita GDP gap between China and the eight developed countries. With the convergence in per capita GDP gap, the energy intensity gap between China and eight different countries also converge, and the convergence rate of the latter is faster than that of the former, i.e. if the per capita GDP gap between China and the eight developed countries decreases by 1%, the energy intensity gap between them will correspondingly decrease by 1.552%. Second, the energy intensity decreases with the improvement of industrial structure, the rising of energy prices, the advances of technology, and the expansion of investment in fixed assets, and it slightly increases with the increase of FDI. Third, the energy intensity gap between China and eight developed countries narrows with the lessening of the difference in fixed assets investment, energy prices, and technological progress between China and eight developed countries, yet increases with the narrowing of the difference in FDI, and has no significant correlation with the difference in industrial structure. Fourth, the narrowing of difference in per capita GDP between China and the eight developed countries can result in the lessening of energy intensity gap, whose economic mechanism is that the decisive factors, such as difference in investment, technology, and the competition mechanism of prices, which can determine the difference in economic growth, can significantly affect the energy intensity gap. 相似文献
173.
ABSTRACTIn recent years, high-polluting industries have been gradually shifted from the eastern developed regions to the central and western underdeveloped regions in China. Certain environmental regulations have been in place accordingly in various regions, but the pollution in the central and western regions has risen sharply. Based on the data of interprovincial panel in China from 2006 to 2015, this paper calculates high-pollution industry dynamic agglomeration index, environmental pollution agglomeration index and relative environmental regulation intensity index, and uses Generalized Method of Moments to carry out the regression analyses of the whole samples, regional heterogeneity and temporal heterogeneity. The results show that there is an inverted U-shaped relationship between relative environmental regulation and environmental pollution concentration in China. The concentration degrees of industrial wastewater pollution and industrial waste gas pollution are deepened, which are mainly caused by the transfer of highly polluting industries. However, the concentration of industrial solid waste pollution caused by the transfer is not obvious. Furthermore, the deepening of industrialization intensifies the concentration of regional environmental pollution. Environmental Kuznets Curve does exist in China, but it is not significant. The increase of labor cost and quality will reduce the concentration of environmental pollution. 相似文献
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The effects of forest harvest intensity in combination with wind disturbance on carbon dynamics in Lake States Mesic Forests 总被引:2,自引:0,他引:2
Robert M. Scheller Dong HuaPaul V. Bolstad Richard A. BirdseyDavid J. Mladenoff 《Ecological modelling》2011,222(1):144-153
Total forest carbon (C) storage is determined by succession, disturbances, climate, and the edaphic properties of a site or region. Forest harvesting substantially affects C dynamics; these effects may be amplified if forest harvesting is intensified to provide biofuel feedstock. We tested the effects of harvest intensity on landscape C using a simulation modeling approach that included C dynamics, multiple disturbances, and successional changes in composition. We developed a new extension for the LANDIS-II forest landscape disturbance and succession model that incorporates belowground soil C dynamics derived from the CENTURY soil model. The extension was parameterized and calibrated using data from an experimental forest in northeastern Wisconsin, USA. We simulated a 9800 ha forested landscape over 400 years with wind disturbance combined with no harvesting, harvesting with residual slash left on site (‘standard harvest’), and whole-tree harvesting. We also simulated landscapes without wind disturbance and without eastern hemlock (Tsuga canadensis) to examine the effects of detrital quantity and quality on C dynamics. We estimated changes in live C, detrital C, soil organic C, total C, and forest composition. Overall, the simulations without harvesting had substantially greater total C and continued to sequester C. Standard harvest simulations had more C than the whole tree harvest simulations. Under both harvest regimes, C accrual was not evident after 150 years. Without hemlock, SOC was reduced due to a decline in detritus and a shift in detrital chemistry. In conclusion, if the intensity of harvesting increases we can expect a corresponding reduction in potential C storage. Compositional changes due to historic circumstances (loss of hemlock) may also affect forest C although to a lesser degree than harvesting. The modeling approach presented enabled us to consider multiple, interacting drivers of landscape change and the subsequent changes in forest C. 相似文献
176.
为提高煤与瓦斯突出强度的预测精度及预测速度,用最大最小蚂蚁系统和BP神经网络相结合的方法进行预测模型设计。根据煤与瓦斯突出强度及其主要影响因素之间的关系数据,建立其神经网络的预测模型。以网络的权值和阈值为自变量,网络误差为目标函数,通过蚁群算法的迭代运算,搜索出误差的全局最小值,以实现BP神经网络的初始权值、阈值优化,并用优化后的网络进行瓦斯突出强度的预测。实例结果表明,MMAS-BP算法的预测值均方差为0.089,约为BP神经网络的0.1倍,且输出稳定性好,适用于煤与瓦斯突出强度的预测。 相似文献
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178.
2000-2007年省级区域自然灾害灾情分析 总被引:2,自引:0,他引:2
自然灾害是严重影响人民正常生产生活、国家经济持续发展的突发公共事件。区域自然灾害评估对于做好防灾减灾工作有着重要的意义。对区域灾情进行了综合评估,归纳总结了区域灾情分布规律。选择受灾人口、死亡人口、紧急转移安置人口、农作物受灾面积、农作物绝收面积、倒塌房屋、损坏房屋和直接经济损失等8个基本指标参与区域灾情评估,并利用灾情综合指数法构建了灾情指数,其中绝对指数反映了区域灾情的绝对强度,相对指数反映了区域灾情对当地社会经济的影响程度。用灾情指数综合评估了我国东、中、西部三大地带以及省级区域的灾情强度和空间分布规律,认为西部区域受灾程度最大,自然灾害对其的影响程度最深,其次是中部地区和东部地区;文章利用综合灾情的绝对指数和相对指数的对应关系,将我国大陆地区的31个省级单元划分为4类地区,即灾情总量较大且对本地影响较大、灾情总量较大但对本地影响较小、灾情总量较小但对本地影响较大以及灾情总量较小且对本地影响较小等4种类型。文章给出的灾情区域分布规律符合灾害系统理论,特别反映了承灾体的暴露度、脆弱性和抗灾能力是区域灾情强度的决定因素。评估结果与区域实际情况相符,说明所给出的灾情指数评估法是评估区域灾情强弱的合理有效方法。 相似文献
179.
以四尾栅藻(Scenedesmus quadricauda)为研究对象,采用平行平板流动腔装置,基于计算机视觉的藻细胞动态生长观察方法,从单细胞尺度研究不同光照强度对四尾栅藻藻细胞生长的影响.成功建立了四尾栅藻个体生长曲线模型,模型拟合效果良好.结果表明:在8000lux光照强度下,藻细胞的体积最大比生长速率最大,即四尾栅藻生长的最适光照强度为8000lux;适宜的光照条件可以增加藻细胞分裂时的大小,小于8000lux时,藻细胞分裂体积随着光照强度的增加而增加,大于8000lux时,藻细胞分裂时体积反而越来越小;较高的光照强度还有利于藻细胞适应新的环境,减少藻细胞复苏时间. 相似文献
180.
生物可降解地膜覆盖对关中地区小麦-玉米农田温室气体排放的影响 总被引:2,自引:2,他引:0
为探究生物可降解地膜覆盖对冬小麦-夏玉米轮作农田生态系统温室气体排放的影响,布设了普通地膜覆盖(PM)、生物可降解地膜覆盖(BPM)和无覆盖(CK)这3个处理,采用静态暗箱-气相色谱仪法监测了2018~2019年土壤CO2、 CH4和N2O的排放通量,并用水分利用效率(WUE)、温室气体排放强度(GHGI)和净生态系统经济预算(NEEB)指标评估覆膜对作物产量、农田环境和经济效益的影响.结果表明,与CK相比,PM和BPM增加了玉米季土壤CO2的排放,PM处理下CO2排放总量高于BPM处理(P>0.05).PM和BPM处理均能够显著减少土壤对CH4的吸收,CH4的年吸收量较CK处理分别减少了42.0%和24.2%(P<0.05).与CK相比,PM和BPM增加了小麦季N2O排放总量(P>0.05),而显著降低了夏玉米季N2O排放(P<0.05).覆膜能够提高作物产量和水分... 相似文献