区域规划环境影响跟踪评价的理论研究

随着环境影响评价制度的深入实施,其实施领域已由项目环评向区域环评和规划环评转变,评价内容也由广泛实施的预测评价向后评价和跟踪评价转变。然而,对于区域规划环评的评价层次、评价程序和评价内容,目前还没有明晰的认识;同时,对于促进规划环评有效实施的跟踪评价,其相关的理论和实践研究几乎没有。文中就此问题作了深入探讨。     

Characteristics and driving factors of marsh changes in Zhalong wetland of China

Zhalong National Nature Reserve in the northeast of China is a large wetland and a habitat of hundreds species of fauna and flora. The rare red-crowned crane is one kind of endangered birds in it. Recently, Zhalong wetland is shrinking and it encounters many problems including occasional fires, bad water quality, human activities, etc. In order to find out a proper way to protect and restore the wetland, this study, using a geographic information system, the global positioning system and remote sensing techniques, analyses the spatial characteristics of the changes in marsh landscape pattern and examines the driving factors for these changes. Data sources include 8 Landsat Thematic Mapper satellite images of Zhalong area in the period of 1986–2002 and the investigation information on site. Based on the analysis of changes of marsh area and annual precipitation during the 16 years, it is found that there is a close correlation between annual precipitation and marsh area. It means that climate is one of driving factors of marsh pattern changes. To understand influences of other kinds of land uses on marsh spatial distribution in Zhalong wetland, this paper analyses the relationship between marsh and different kinds of land uses, such as water surface, residential area, farmland, salina land and grass land, respectively. According to the patch analysis theory, a fragmental index and a fractal dimension of the marsh are calculated with perimeter-area method. The results indicate that the marsh pattern is affected by human activities significantly. In addition, the location alteration of marsh centroid point over the 16 years is studied. The movement trace of marsh centroid point is concerned with different hydrological situation in different areas of the wetland. In summary the characteristics of the marsh landscape pattern evolution during the 16 years are affected by multiple driving factors. The main driving factors are climate, human activities, distribution of other kinds of land uses and hydrological situation in different areas.     

Using Spatial Pattern to Quantify Relationship Between Samples, Surroundings, and Populations

The need for accurate carbon budgeting, climate change modelling, and sustainable resource management has lead to an increase in the number of large area forest monitoring programs. Large area forest monitoring programs often utilize field and remotely sensed data sources. Sampling, via field or photo plots, enables the collection of data with the desired level of categorical detail in a timely and efficient manner. When sampling, the aim is to collect representative detailed data enabling the statistical reporting upon the characteristics of larger areas. As a consequence, approaches for investigating how well sample data represent larger areas (i.e., the sample neighbourhood and the population) are desired. Presented in this communication is a quantitative approach for assessing the nature of sampled areas in relation to surrounding areas and the overall population of interest. Classified Landsat data is converted to forest/non-forest categories to provide a consistent and uniform data set over a 130,000 km² study region in central British Columbia, Canada. From this larger study area 322 2 × 2 km photo plots on a 20 × 20 km systematic grid are populated with composition and configuration information for comparison to non-sampled areas. Results indicate that typically, within the study area, the spatial pattern of forest within a photo plot is representative of the forest patterns found within primary and secondary neighbourhoods and over the entire population of the study. These methods have implications for understanding the nature of data used in monitoring programs worldwide. The ability to audit photo and field plot information promotes an increased understanding of the results developed from sampling and provides tools identifying locations of possible bias.     

Suspended Particulate Matter Distribution in Rural-Industrial Satna and in Urban-Industrial South Delhi

An air quality sampling program was designed and implemented to collect the baseline concentrations of respirable suspended particulates (RSP = PM₁₀), non-respirable suspended particulates (NRSP) and fine suspended particulates (FSP = PM_2.5). Over a three-week period, a 24-h average concentrations were calculated from the samples collected at an industrial site in Southern Delhi and compared to datasets collected in Satna by Envirotech Limited, Okhla, Delhi in order to establish the characteristic difference in emission patterns. PM_2.5, PM₁₀, and total suspended particulates (TSP) concentrations at Satna were 20.5 ± 6.0, 102.1 ± 41.1, and 387.6 ± 222.4 μg m⁻³ and at Delhi were 126.7 ± 28.6, 268.6 ± 39.1, and 687.7 ± 117.4 μg m⁻³. Values at Delhi were well above the standard limit for 24-h PM_2.5 United States National Ambient Air Quality Standards (USNAAQS; 65 μg m⁻³), while values at Satna were under the standard limit. Results were compared with various worldwide studies. These comparisons suggest an immediate need for the promulgation of new PM_2.5 standards. The position of PM₁₀ in Delhi is drastic and needs an immediate attention. PM₁₀ levels at Delhi were also well above the standard limit for 24-h PM₁₀ National Ambient Air Quality Standards (NAAQS; 150 μg m⁻³), while levels at Satna remained under the standard limit. PM_2.5/PM₁₀ values were also calculated to determine PM_2.5 contribution. At Satna, PM_2.5 contribution to PM₁₀ was only 20% compared to 47% in Delhi. TSP values at Delhi were well above, while TSP values at Satna were under, the standard limit for 24-h TSP NAAQS (500 μg m⁻³). At Satna, the PM₁₀ contribution to TSP was only 26% compared to 39% in Delhi. The correlation between PM₁₀, PM_2.5, and TSP were also calculated in order to gain an insight to their sources. Both in Satna and in Delhi, none of the sources was dominant a varied pattern of emissions was obtained, showing the presence of heterogeneous emission density and that nonrespirable suspended particulate (NRSP) formed the greatest part of the particulate load.     

Temporal Trends in the Spatial Distribution of Impervious Cover Relative to Stream Location

Use of impervious cover is transitioning from an indicator of surface water condition to one that also guides and informs watershed planning and management, including Clean Water Act (33 U.S.C. §1251 et seq.) reporting. Whether it is for understanding surface water condition or planning and management, impervious cover is most commonly expressed as summary measurement (e.g., percentage watershed in impervious cover). We use the National Land Cover Database to estimate impervious cover in the vicinity of surface waters for three time periods (2001, 2006, 2011). We also compare impervious cover in the vicinity of surface waters to watershed summary estimates of impervious cover for classifying the spatial pattern of impervious cover. Between 2001 and 2011, surface water shorelines (streams and water bodies) in the vicinity of impervious cover increased nearly 10,000 km. Across all time periods, approximately 27% of the watersheds in the continental United States had proximally distributed impervious cover, i.e., the percentage of impervious cover in the vicinity of surface waters was higher than its watershed summary expression. We discuss how impervious cover spatial pattern can be used to inform watershed planning and management, including reporting under the Clean Water Act.     

中国旅游业CO_2排放区域差异的空间分析

在旅游业节能减排形势严峻的背景下,深入研究中国旅游业CO_2排放问题,制定科学的区域节能减排政策已刻不容缓。本文首先运用"自下而上"法,估算了1993-2012年中国整体旅游业、旅游业各分部门、大陆各省区(不含西藏)旅游业CO_2排放量。在此基础上,对全国及三大地带旅游业CO_2排放的总体特征进行分析;利用Theil指数法分析了中国旅游业CO_2排放强度的区域差异、区域内差异和区域间差异;运用AreView软件对中国旅游业CO_2排放强度的省际差异进行直观图示。分析结果显示:1993-2012年,中国旅游业CO_2排放量从1 480.868×10~4t升至6 274.129×10~4t;全国及三大地带旅游业CO_2排放强度整体上呈现出先显著下降、再缓慢梯度下降的趋势;中国旅游业CO_2排放强度空间分布不均匀,东部地区旅游业CO_2排放强度低于中部和西部地区;中国旅游业CO_2排放强度的区域总体差异、区域间差异和区域内差异整体呈逐渐缩小的趋势,区域间差异对总体差异的贡献率为94%-98%,区域间差异占主导地位;中国旅游业CO_2排放强度省际差异明显,属于旅游业CO_2排放强度弱显著区的省区基本位于东部沿海地区,河北、湖南、河南、广西、甘肃和新疆等省区频繁出现在旅游业CO_2排放强度强显著区之列,因此上述省区应是中国旅游业CO_2未来节能减排的区域重点。据此提出差别化的CO_2减排对策:东部地区应通过技术改进和调整产业结构、能源消费结构来降低CO_2排放强度,并以此带动中部和西部地区旅游业节能减排;中部和西部地区应加强与东部地区合作,将提高能源使用率、降低CO_2排放强度作为旅游业减排工作的重点。     

资源产业空间集聚与区域经济增长:“资源诅咒”效应实证

针对"资源诅咒"研究中自然资源度量指标选取存在的科学性问题,利用资源产业空间集聚代替自然资源丰裕度和资源产业依赖度作为自然资源丰裕程度的解释变量。首先,在Krugman空间基尼系数的基础上,构建适用于测度资源产业空间集聚的计算公式,基于我国30个省(区、市)层面的数据,量化1999—2013年间资源产业的空间集聚程度,分析其排名情况和分布格局。研究显示:我国有15个省(区、市)存在资源产业空间集聚现象,这些地区大多位于长江以北,且均为自然资源富集地区。其次,构建经济增长计量模型,选取存在资源产业空间集聚现象的省(区、市)作为样本空间,并采用多种计量分析和检验方法考察资源产业空间集聚度与区域经济增长之间的直接和间接关系,分析"资源诅咒"的传导机制。研究显示:1在模型整体估计中,资源产业空间集聚的系数符号均为负,且在5%的水平上显著,说明资源产业空间集聚与区域经济增长间的关系呈现负相关,符合"资源诅咒"的基本假设。2在模型分步估计中,人力资本投资、技术创新投入和制造业发展与区域经济增长正相关,符合经典经济增长理论的逻辑关系;物质资本投资与区域经济增长负相关,可能是由于当地经济主体的消费跨期替代弹性较小,导致物质资本投资对经济增长的直接增益效应小于其对社会人力资本积累的负向效应,进而阻碍区域经济增长;政府干涉程度越高越不利于经济增长。根据研究结果,建议应明确市场调节为主、政府调控为辅的导向机制,进一步提升资源产业空间集聚程度,强化行业人员素质与技术水平匹配,逐步提高自然资源生产和利用效率,从而实现加快地区经济转型,有效促进经济可持续发展的全面提升。     

近52年来洞庭湖流域气象干旱的时空分布特征

基于洞庭湖流域84个气象站点1962~2013年的逐日气象资料,利用综合干旱指数(CI)对洞庭湖流域气象干旱的时间和空间特征进行分析。结果表明:在过去52 a,区域性干旱强度较强的时段以夏季、秋季、夏秋和秋冬时节为主;区域干旱强度在春季、夏季、夏秋、冬季呈上升趋势;秋冬时节和年干旱强度变化不明显;春夏时节、夏秋时节、秋冬时节和冬春时节的平均干旱强度比春、夏、秋、冬单个季节的平均干旱强度大。小波分析表明,区域干旱强度的周期以10a为主周期,5 a和22 a为次周期。近52 a来,历年干旱站次比主要集中于10%~30%之间,多表现为区域性干旱,以夏季和秋季的干旱范围较大;干旱频率高发时期主要为夏季、夏秋时节和秋季。干旱频率高发地主要以流域的南部山地和北部的洞庭湖平原为主,西北部的山地发生干旱相对较少,衡邵盆地随季节变化干旱频率易发生高低值转换。     

长江中游城市群经济与生态成本空间演化模式分析

综合运用变异系数、泰尔指数及ESDA-GIS多种方法,在充分考虑传统经济影响因子的基础上,尝试引入经济发展生态成本指标,分析长江中游城市群经济综合发展水平与生态成本的空间匹配及演化模式。研究表明:经济综合发展水平高低聚集特征明显,空间极化现象是导致区域经济发展不平衡的主要原因;生态成本空间集聚现象以高高集聚和低低集聚为主,且呈现出高高集聚减少、低低集聚增多的现象,生态成本消耗有所改善;2001~2012年长江中游城市群市域经济综合发展水平与生态成本表现出越来越显著的差异化空间格局,呈现出由低经济综合发展水平-低生态成本过渡到高经济综合发展水平-高生态成本,进而发展到高经济综合发展水平-低生态成本的空间匹配模式的阶段性特征;高经济综合发展水平-高生态成本的经济发展模式仍在大部分城市中存在,经济与生态空间协调发展的潜力仍然很大。     

基于GIS的乌梁素海水体富营养化状况的模糊模式识别

利用基于MATLAB 7.0实现的模糊模式识别交叉迭代模型对2006年5—10月分布于乌梁素海各水体功能区的21个水质监测点的富营养化等级进行了模糊模式识别,并在GIS技术支持下,用Arcview的空间分析功能绘制富营养化等级识别结果、对富营养化状态影响权重最大的评价指标总氮(TN)含量和富营养化状态控制元素总磷(TP)含量对应的富营养化等级水体和地表水质等级水体的空间分布月变化Grid专题图.将富营养化状态变化及其分布区域与乌梁素海同期水质监测指标浓度变化及其分布区域进行对比分析及验证.结果表明,富营养化等级识别结果的时空分布与实际情况相符,能够比较准确地反映富营养化等级定量的时空变化趋势.