城镇化对工业能源消费的门槛效应研究——以长江经济带省份为例

高效能源利用是推动工业发展,进而促使城镇格局演化的重要催化剂,同时城镇化的高速发展对工业能源的消费结构和利用效率提出了进一步的要求,这必将影响到低碳城市建设和环境保护等生态责任目标的实现。选取2003—2012年长江经济带11个省份(直辖市)的相关数据,运用门槛模型对城镇化率、城镇居民人均总收入、能源工业投资、工业总产值、城市人口密度、产业结构等影响工业能源消费的因素进行分析,重点研究城镇化率和工业能源消费的非线性关系和相应的地区差异。结果表明:(1)长江经济带城镇化发展存在着明显的地区差异,上海、浙江等东部地区城镇化发展速度和水平明显优于云南、贵州等中西部地区。云南和贵州2012年的城镇化率远远低于2003年上海、浙江的城镇化率,显示出长江上游和下游之间存在着巨大的发展水平差距。(2)城镇化对工业能源消费存在显著的门槛效应,以城镇化率为门槛变量,存在两个结构变化点,分别为36.9%和48.3%。(3)在第一个门槛点前,城镇化对工业能源消费起抑制作用,前期城镇化的发展导致资源和人口的集聚效应明显,资源的利用效率和配置效率得到提升,从而抑制工业能源消费。在越过第二个门槛点后,城镇化对工业能源消费起正向作用,此时工业的发展和生活消费水准的提升对能源消费提出了更多的要求。最后为促进长江经济带城镇化和工业低碳化的协调发展,提出以下建议:加快长江经济带沿线各省份联动发展,缩小城镇化发展差异;针对城镇化率和工业能源消费的非线性关系,采取相应的措施引导和控制工业能源消费的变化趋势;协调城镇化进程和地区工业能源消耗,促进城镇化的健康发展。     

中部地区资源型城市城市化与生态环境动态耦合关系

通过构建城市化与生态环境耦合模型,利用中部地区37个资源型城市2005—2014年城市化系统和生态环境系统的30个指标数据,对城市化与生态环境耦合关系动态变化进行测度,并比较分析不同类型资源型城市城市化水平、生态环境水平及其二者耦合协调度的变化。结果表明:(1)2005以来人口城市化对资源型地区城市化综合水平的影响力减弱,社会城市化的影响力逐渐加大并趋于比较重要的地位。尽管资源条件对资源型城市的生态环境综合水平影响最大,但生态环境治理水平对资源型地区生态环境综合水平的影响力正变得日益重要。(2)各城市间城市化综合水平差异较大,而生态环境综合水平差异较小。自2005年以来城市化发展综合水平的城际差异无较大改变,但生态环境发展水平的城际差异正变得日趋缩小。位于山西省的资源型城市城市化综合水平和生态环境综合水平的变动较之其他省份更为显著。(3)中部地区资源型城市的协调类型处于勉强协调、初级协调和中级协调,并以初级协调型为主。2005以来中部地区多数资源型城市城市化与生态环境关系保持不变,关系恶化的资源型城市主要分布在安徽、江西和湖南,关系更为协调的资源型城市主要位于山西。(4)不同类型资源型城市的城市化综合水平差异显著,而生态环境综合水平差异并不明显。再生型和衰退型城市的耦合协调度水平较高,成熟型城市的耦合协调度较低。(5)城市化滞后仍是资源型城市城市化与生态环境关系不协调发展的主要原因。     

Conservation implications of anthropogenic impacts on visual communication and camouflage

Anthropogenic environmental impacts can disrupt the sensory environment of animals and affect important processes from mate choice to predator avoidance. Currently, these effects are best understood for auditory and chemosensory modalities, and recent reviews highlight their importance for conservation. We examined how anthropogenic changes to the visual environment (ambient light, transmission, and backgrounds) affect visual communication and camouflage and considered the implications of these effects for conservation. Human changes to the visual environment can increase predation risk by affecting camouflage effectiveness, lead to maladaptive patterns of mate choice, and disrupt mutualistic interactions between pollinators and plants. Implications for conservation are particularly evident for disrupted camouflage due to its tight links with survival. The conservation importance of impaired visual communication is less documented. The effects of anthropogenic changes on visual communication and camouflage may be severe when they affect critical processes such as pollination or species recognition. However, when impaired mate choice does not lead to hybridization, the conservation consequences are less clear. We suggest that the demographic effects of human impacts on visual communication and camouflage will be particularly strong when human‐induced modifications to the visual environment are evolutionarily novel (i.e., very different from natural variation); affected species and populations have low levels of intraspecific (genotypic and phenotypic) variation and behavioral, sensory, or physiological plasticity; and the processes affected are directly related to survival (camouflage), species recognition, or number of offspring produced, rather than offspring quality or attractiveness. Our findings suggest that anthropogenic effects on the visual environment may be of similar importance relative to conservation as anthropogenic effects on other sensory modalities.     

长江经济带人口城镇化与土地城镇化协调发展时空差异研究

长江经济带是我国经济发展的战略区域,人口城镇化和土地城镇化的协调发展是推进新型城镇化发展的战略重点之一。本文以2006-2013年长江经济带126个地级市的人口、土地数据为基础,从长江经济带、区域和市域视角,采用熵值法、发展水平评价模型和均衡发展模型测度人口城镇化和土地城镇化协调发展度,结合空间分析方法对协调发展度进行分析,并使用ArcGIS10.2得出二者协调发展度的空间分布图。研究发现,从整体来看长江经济带2006-2013年人口城镇化与土地城镇化协调发展水平不断提高,并呈现相对平稳增长,2013年总体上达到较高协调发展水平。从区域视角来看,协调发展度呈现阶梯特征即下游地区中游地区上游地区的状态,且自2009年起3大区域协调发展度差距呈扩大趋势。从市域视角分析,长江经济带126个地级市2006-2008年协调发展度的发展速度慢,2009年后发展速度显著提升;在空间上呈现"东北-西南"的空间非均衡性和空间异质性,东北高、西南低,并表现明显的"城市群集聚"发展特征。长江经济带在人口城镇化和土地城镇化进程中应不断推进区域经济发展,加快中上游城市的城镇化进程,充分发挥"城市群"的经济辐射带动作用,同时转变土地财政思想,真正实现地区发展水平的提高,最终实现人口城镇化和土地城镇化协调发展。     

近60a长三角地区极端高温事件变化特征及其对城市化的响应

基于长三角地区1951~2014年56个国家级气象站点逐日气温记录资料,通过计算极端高温事件相关指标(极端最高温TXx,极端最低温TNn,高温日数Htd和低温日数Ltd),利用GIS空间分析技术和Mann-Kendall时间趋势分析方法分析了长三角地区近60 a极端高温事件的空间分异特征和时间变化趋势,并探讨了城市化发展对区域极端高温事件时空变异的影响。结果表明:(1)长三角地区极端高温事件指标均表现为一定的上升趋势,极端低温指标(TNn和Ltd)线性变化趋势比极端高温指标(TXx和Htd)更为显著,变化趋势最显著的地区集中在经济和城市化水平较高的城市及周边地区(如上海、杭州等)。(2)极端高温指标(TXx和Htd)多年平均总体表现为南高北低,西高东低的趋势,而极端低温指标中TNn多年平均为由中部向南北两侧降低,Ltd多年平均呈现自中部向南北南侧增多的趋势。(3)从1990~2000到2000~2010年,城市化对极端高温事件的影响增强,快速城市化对北部城市极端高温事件的影响高于南部城市。     

低气压试验标准及试验技术分析

详细阐述了低气压环境对装备的各种影响,介绍了我国主要军用、民用环境试验标准中规定的试验程序及其应用对象,分析了有关低气压试验条件,包括低气压贮存、工作和快速/爆炸减压的试验条件和变化速率,最后简单介绍了低气压试验设备的一般要求、特别是快速减压和爆炸减压设备的使用和低气压试验技术。     

快速城市化背景下的思雅河流域水环境分析

通过对思雅河流域连续3年的水环境质量监测,结合遥感影像获得其土地利用类型变化,据此研究城市化对水环境的影响。结果表明:2012—2014年间思雅河流域自然、农业景观面积占比减少,而建设用地面积持续增加;研究期间除TDS年均值略微下降外,其余水质指标的年均值几乎均呈递增趋势,尤以TSS和COD增加最显著;TSS、COD、NH 3-N和TP的相对标准偏差均>0.1,显著高于其余参数,说明其波动程度较大。主成分分析表明水环境变化最主要的影响因子为第一主成分(TSS、COD、NH 3-N和TP)。贵安新区大学城建设活动加重了思雅河流域水体污染趋势。     

饮用水源微生物快速检测技术的发展及应用

微生物是威胁饮用水安全的首要问题，水环境微生物快速检测技术的开发和应用是推动饮用水源微生物快速检测和水质安全预警技术发展的保障。随着对水质微生物污染快速检测和准确预警新要求的提出，水环境中微生物在线检测和预警技术得到了越来越多的开发和应用。笔者总结了水环境常见微生物检测方法和技术的发展，重点讨论了饮用水源微生物快速检测技术的发展和应用，根据各项技术的应用和推广使用程度，将其归纳为常用快速检测技术、潜在适用快速检测技术和新型快速检测技术等类别，并详细阐述了一些应用较广的技术，以期为构建水质微生物污染早期预警系统提供参考。     

Coupling of the Water Cycle with Patterns of Urban Growth in the Baltimore Metropolitan Region,United States

Regional municipal water plans typically do not recognize complex coupling patterns or that increased withdrawals in one location can result in changes in water availability in others. We investigated the interaction between urban growth and water availability in the Baltimore metropolitan region where urban growth has occurred beyond the reaches of municipal water systems into areas that rely on wells in low‐productivity Piedmont aquifers. We used the urban growth model SLEUTH and the hydrologic model ParFlow.CLM to evaluate this interaction with urban growth scenarios in 2007 and 2030. We found decreasing groundwater availability outside of the municipal water service area. Within the municipal service area we found zones of increasing storage resulting from increased urban growth, where reduced vegetation cover dominated the effect of urbanization on the hydrologic cycle. We also found areas of decreasing storage, where expanding impervious surfaces played a larger role. Although the magnitude of urban growth and change in water availability for the simulation period were generally small, there was considerable spatial heterogeneity of changes in subsurface storage. This suggests that there are locally concentrated areas of groundwater sensitivity to urban growth where water shortages could occur or where drying up of headwater streams would be more likely. The simulation approach presented here could be used to identify early warning indicators of future risk.     

Designing and Implementing a Network for Sensing Water Quality and Hydrology across Mountain to Urban Transitions

Water resources are increasingly impacted by growing human populations, land use, and climate changes, and complex interactions among biophysical processes. In an effort to better understand these factors in semiarid northern Utah, United States, we created a real‐time observatory consisting of sensors deployed at aquatic and terrestrial stations to monitor water quality, water inputs, and outputs along mountain to urban gradients. The Gradients Along Mountain to Urban Transitions (GAMUT) monitoring network spans three watersheds with similar climates and streams fed by mountain winter‐derived precipitation, but that differ in urbanization level, land use, and biophysical characteristics. The aquatic monitoring stations in the GAMUT network include sensors to measure chemical (dissolved oxygen, specific conductance, pH, nitrate, and dissolved organic matter), physical (stage, temperature, and turbidity), and biological components (chlorophyll‐a and phycocyanin). We present the logistics of designing, implementing, and maintaining the network; quality assurance and control of numerous, large datasets; and data acquisition, dissemination, and visualization. Data from GAMUT reveal spatial differences in water quality due to urbanization and built infrastructure; capture rapid temporal changes in water quality due to anthropogenic activity; and identify changes in biological structure, each of which are demonstrated via case study datasets.