山西省主要城市的空气质量长期变化特征研究

利用了2007年－2012年山西省11个城市的空气质量日报资料对空气质量的变化特征及其影响因素进行了研究分析。结果表明,太原市API指数累年平均值最大,长治市和忻州市最小;就年际变化而言,6年来,太原市API指数呈逐年下降趋势,其他城市在2011年－2012年均有不同程度的回升。空气质量的季节变化特征为夏季较好,冬季较差;各城市的首要污染物均为可吸入颗粒物。以山西省大气污染防治重点控制区太原市为例,探讨了空气质量的可能影响因素。     

基于土地利用转型视角的“亚喀斯特”区域生态环境效应研究——以黔中部分地区为例

在遥感与GIS的支持下,以1995、2000、2005和2010年的TM影像及2015年的Landsat8 OLI遥感影像为数据源,从土地利用转型的角度,运用区域生态环境质量指数和土地利用转型类型的生态贡献率对亚喀斯特地区的土地利用/覆盖变化过程及生态环境效应进行了定量分析。结果表明,1995~2015年间,亚喀斯特地区土地利用/覆盖变化较为显著,其中生活用地和生态用地面积增加,而生产用地面积减少,主要表现为农业生产用地向城镇、农村生活用地及林地生态用地的转化。计算得到亚喀斯特区域5期的生态环境质量指数分别为0.540 2、0.539 7、0.552 3、0.558 1和0.561 5,生态环境质量总体维持稳定,呈一定的上升趋势。致使亚喀斯特区域生态环境质量改善的主要原因是农业生产用地向林地、草地和水域生态用地的转化;致使生态环境恶化的主要是农业生产用地向城镇、农村生活用地等的转化,但生态环境改善的趋势要大于恶化的趋势。     

节能环保产业公司融资效率研究——基于四阶段DEA-Malmquist模型

在经典的DEA模型的基础上进行了修正,采用四阶段DEA模型,旨在剔除环境控制变量对效率测度结果的影响.同时,在DEA模型的基础上引入Malmquist指数分析法,以弥补DEA模型无法测度面板数据的缺陷.选取了2012年-2014年A股节能环保上市公司的面板数据,测度了样本的融资效率及三年的融资效率变化情况,结果表明:资源循环利用行业的融资效率最高,其次是环保行业,融资效率最低的是节能行业.样本企业总体的融资效率每年都在增长,但增长速度开始放缓.     

铀胁迫对5种牧草种子萌发的影响

为进一步探究放射性重金属铀污染环境对植物种子萌芽及生长所产生的迫害,根据我国铀矿冶废水中铀的质量浓度(5 mg/L)选择不同质量浓度(0、1 mg/L、5 mg/L、10 mg/L、15 mg/L、20 mg/L)的铀溶液进行试验,用以胁迫5种1年生牧草(三叶草、苜蓿草、黑麦草、高丹草和苏丹草)种子,同时观察记录各自的萌发状况(发芽数和第7 d幼苗生长长度),计算其发芽率、发芽势、发芽指数(GI)、活力指数(VI)及耐性指数,并与对照组进行量化指标比较。最后比较各牧草种子所受到的危害并做出评价。结果表明:对于不同程度的铀污染,多数植物表现为低质量浓度促进其种子萌发,高质量浓度则严重抑制甚至致死。对于三叶草、苜蓿草和黑麦草种子,低质量浓度(1 mg/L)铀溶液促进种子的萌发,质量浓度升高则为抑制,其中黑麦草表现稍异常,质量浓度为5 mg/L时对种子萌发有促进作用,使最终发芽率较对照提升14%;对于高丹草,低质量浓度(5 mg/L)时促进种子萌发,而在质量浓度稍低于或超过5 mg/L时表现出明显的抑制现象,各指标低于对照13%左右;苏丹草则仅呈现抑制现象,铀质量浓度为5mg/L时抑制现象稍轻,最终发芽率较对照组仅降4%,小于或大于5mg/L时均受抑制,且质量浓度越高抑制现象越明显,最终发芽率最高仅28%。     

豫西地区植被覆盖的空间变化研究

应用遥感技术,利用长时间序列的SPOT VEGETATION NDVI数据集,结合改进的像元二分模型,对豫西山区1998年、2003年和2008年的植被覆盖度进行计算。结果表明,豫西山区植被覆盖总体上略有上升,局部地区植被覆盖度有所下降。高海拔区域植被覆盖相对稳定,退化概率较低;低海拔区域植被退化和恢复的概率都相对较高;坡度小的区域植被退化和修复的概率都较高;坡度较大的区域植被轻微退化概率增大,坡度越大,植被覆盖修复的概率越低;南坡和北坡植被覆盖度相对较高,东坡和西坡植被覆盖度较低;西南坡向的植被退化相对严重,东南坡向植被退化概率相对较低。     

空气环境质量模糊综合评价方法的改进

针对以往空气环境质量的模糊综合评价方法存在的不足提出了采用综合指数和模糊综合评价方法相结合的方法评价空气环境质量的新方法。     

Analysis of landscape pattern: towards a ‘top down’ indicator for evaluation of landuse

Landscapes as highly complex systems are subject to many different assessment procedures despite the fact that their development is not really predictable. Every synthetic model of landscape functioning will probably fail in demonstrating the landscape behaviour due to the decreasing precision and relevance of its output with increasing complexity. Two approaches are presented here which use deductive methods to describe landscape behaviour as indicated by its spatial structure. The one is a correlative concept which is characterized by all the advantages and disadvantages of statistical regression methods. It is strongly dependent on data quality. In the second study an expert knowledge system is developed. Fuzzy set theory is applied to transfer rules of landscape ecological experience to image parameters derived from satellite data. Both approaches are compared regarding the problems faced in the work during implication. Theoretical restrictions and the applicability in landscape assessment is discussed.     

Determinants of CO2 emissions in Brazil and Russia between 1992 and 2011: A decomposition analysis

This paper deals with the decomposition analysis of energy-related CO₂ emissions in Brazil and Russia from 1992 to 2011. The refined Laspeyres index (RLI) method applied and both aggregated and sectoral changes in CO₂ emissions decomposed. Brazil’s and Russia’s economies divided into three economic sectors including agriculture, industry and services. Impact of four main factors, such as economic activity, employment, energy intensity, and carbon intensity in CO₂ emissions changes were analyzed. The aggregated decomposition analysis revealed that Brazil is still far from a decoupling between economic growth and carbon dioxide emissions where Russia achieved a substantial decline in carbon emissions mainly due to the improved energy intensity. The empirical findings of sectoral decomposition analysis emphasized that the economic activity was the major CO₂ increasing factor in Brazil’s economic sectors. On the other hand the economic activity effect followed a reducing impact in Russia’s sectoral emissions until 2000. The structural changes between sectors and their impacts on CO₂ emissions were captured by employment effect. Energy intensity and carbon intensity effects underlined that environmental sustainability widely neglected in Brazil and Russia during the study period. The results yield important hints for energy planning and sustainable environment.     

关于影响易损性分析结果的区域因素研究——以福建为例

以福建省震害快速评估系统为依托,以分析处理现场实际调查数据为基础,提出了主要影响易损性分析结果的四个区域因素及其影响指数值、区域综合指数值,提供了各分区的划分依据、各分区影响指数值的评定标准以及区域综合指数值的计算方法,为合理应用不同地区之间的易损性矩阵或易损性曲线提供了参考依据。     

Effects of climatic data low-pass filtering on the ICBM temperature- and moisture-based soil biological activity factors in a cool and humid climate

The air temperature (T_air), total precipitation (TP) and potential evapotranspiration (PET) are standard input data for soil carbon dynamic models, i.e., for calculating temperature and moisture effects on soil biological activity. The resolution needed depends on objectives, the complexity of models and inbuilt pedotransfer functions. The Introductory Carbon Balance Model (ICBM) soil climate front end model calculates a multiplicative soil-temperature (r_{e_temp}) and -moisture (r_{e_wat}) factor with a daily time-step to estimate soil biological activity, i.e., r_{e_crop} = r_{e_temp} × r_{e_wat}. Our objective was to determine how much r_{e_temp}, r_{e_wat} and r_{e_crop} are affected by low-pass filtering of the climatic input data for a cool, humid temperate region. To achieve this we conducted spectral analysis on T_air, TP, PET and r_{e_crop} in the frequency domain. Thereafter we applied Fourier low-pass filters of 5, 15, 30, 60 and 180 days on T_air, TP, PET and tracked their effects through the soil climate model's state variables and outputs. This was done using a sandy and a heavy clay soil and an 89-year daily time-series from a meteorological station in Quebec (Canada). The Fourier spectra showed that the variance for T_air, PET and r_{e_crop} was dominated by an annual cycle, as could be expected. There was no yearly cycle for TP. The variation in r_{e_temp} explained most of the variance in r_{e_crop}. The soil climate module outputs were not sensitive to low-pass filtering of PET. A daily time-step was needed to avoid overestimating r_{e_crop} for the sandy soil. Using a weekly time-step for TP and T_air allowed us to explain about 80% of the variance in r_{e_crop} for the heavy clay soil. This study also indicates that the standard leaf (and green) area index functions for calculating transpiration should receive more attention, since they have significant effects on the state and output variables.