Factors Affecting Domestic Water Consumption on the Spanish Mediterranean Coastline

During the last decades on the Spanish Mediterranean coastline there has been a great development of low-density urban areas, as well as a change in the sociodemographic structures, especially in the municipalities that have developed a residential tourism model. Likewise, urban and tourist development have stressed the balance between the availability of water resources and urban water demands, generating situations of scarcity that might be aggravated by climate change. This study identifies the determinants of water consumption on the Spanish Mediterranean coastline, focusing on the variables related to urban land uses and socioeconomic and sociodemographic variables at the municipal level using an ordinary least square (OLS) and a geographically weighted regression (GWR) model. The GWR model results substantially improved the results of the OLS model, explaining 88.27 percent of the variance in domestic water consumption and solving the spatial autocorrelation problem of some independent variables. The most influential variables include the percentage of second homes or the percentage of residential properties with swimming pools at the municipal level. These characteristics must be considered to develop demand management policies and an updated hydrological planning to ensure urban supply in a future with less available water resources.     

Electricity Consumption and Economic Growth in the Beijing-Tianjin-Hebei Agglomeration of China

Nowadays, increased attention is being paid to the causal relationship between electricity consumption and economic growth. This paper attempts to examine the causal relationship between electricity consumption and economic growth for China’s Beijing-Tianjin-Hebei agglomeration, using annual data covering the period 1982- 2008. In this study, unit root tests, the Johansen co-integration test, and the Granger causality test are applied. The empirical results indicate that the two series (electricity consumption and economic growth) of the three locales (Beijing, Tianjin, and Hebei) are non-stationary. But first differences of the two series are stationary. The results of the Johansen co-integration test indicate that electricity consumption and economic growth are co-integrated in Hebei and Tianjin while this is not the case in Beijing. The Granger causality test implies that there is causality running from electricity consumption to economic growth in all of the three locales. Causality running from economic growth to electricity consumption is found in Hebei and Beijing while this is not the case in Tianjin. This means that an increase in electricity consumption directly affects economic growth and that economic growth also stimulates further electricity consumption in Hebei and Beijing. But in Tianjin, an increase in electricity consumption directly affects economic growth while economic growth cannot affect electricity consumption. These findings can provide useful information for local governments of the three locales to formulate sustainable energy and economic policies. The study is of great significance for circular economy and building a resource-conserving society.     

Spatial Variations of Single-Family Residential Water Consumption in Portland,Oregon

Although water demand theories identify price structures, technology, and individual behavior as determinants of water demand, limited theoretical or empirical evidence suggests a link between urban development patterns and water use. To assess the role of urban development patterns on water demand, we used GIS and statistical models to analyze single-family residential water consumption in the Portland, Oregon, metropolitan area. Our results show that residential water consumption per household at the census block group scale is best explained by average building size, followed by building density and building age, with low water consumption areas clustering together and typically located in high-density and older neighborhoods. Accounting for spatial dependence among residuals, explanatory variables explain up to 87% of variations in water consumption. Our results help to develop a water demand framework that incorporates existing factors with urban development policies to more effectively manage limited water and land resources.     

Urban heat and residential electricity consumption: A preliminary study

The Urban Heat Island (UHI) is a well-documented phenomenon occurring in cities across the world resulting in city centres often being several degrees warmer than their surroundings. This local elevation in temperatures could potentially impact upon local energy consumption, with residents in the warmer central section of the city using more energy to cool their homes in summer and less energy to warm them in winter. This study uses a combination of Geographical Information System techniques and Remote Sensing data (MODIS LST and NDVI), as a preliminary investigation, to assess the spatial relationship between UHI, urban greenspace, household income and electricity consumption in Birmingham, UK. It provides simple and repeatable steps, based on freely available datasets, for urban planners, industry, human and physical geographers, and non-specialists to reproduce the analyses. The results show that, the present impact of the UHI is limited and instead highlights the dominance of household income over local climate in explaining consumption patterns across Birmingham.     

我国城市居民直接能耗的碳排放类型及影响因素

针对我国287个地级以上城市,在测算了近9年居民直接能耗导致的CO₂排放量的基础上,进行聚类、对比,并分析城市居民直接能耗的碳排放影响因素,得到以下结论:全国分为6类城市居民直接能耗碳排放类型;高碳排放型城市的地均碳排放强度、人均工资碳排放强度及居民直接能耗CO₂排放总量等方面均比低碳排放型城市高,人均地方生产总值碳排放强度低于低碳排放型城市,并多为经济发达城市和资源丰富城市,其碳排放构成上分别以电、交通能耗碳排放和气碳排放为主导,高碳排放型城市居民直接能耗CO₂排放量占全国地级以上城市的86.20%。我国大部分地级城市居民直接能耗的碳排放属于相对低碳排放型,其人均CO₂排放量低于全国平均水平。城市所在地的降温度日数(CDD)、采暖期、采暖强度、人均能源供给量、居民的人均工资、城市人均地方生产总值是影响城市居民直接能耗CO₂排放量的主要因素。     

中小城市家庭生活用能碳排放空间分异——以开封市为例

利用2015年开封市居民家庭生活用能的大样本问卷调查数据,采用探索性空间数据分析（ESDA）和标准差椭圆（SDE）方法,探索城市居住区家庭生活用能碳排放空间分布特征。结果表明：① 家庭生活用能碳排放存在以热点区为主的空间正相关特性,碳排放高值集聚发生在城市新建开发区和建成区向外扩张较快区域,以2000年以后新建高档商品房小区和机关事业单位家属院为主,低值集聚区则发生在建成时间长、后续开发力度小的区域,以老商品房小区和胡同社区为主;② 开封市家庭电力消耗碳排放占生活用能总碳排放的67%,但人均生活用能碳排放空间格局由供暖碳排放决定,且人均供暖碳排放空间格局又由集中供暖碳排放空间格局决定,故降低集中供暖能耗、缩小居民供暖用能差异成为居民生活用能碳减排工作的重中之重;③ 家庭经济状况、集中供暖设施分布和城市发展的空间格局是家庭生活用能碳排放空间依赖性和空间异质性形成的主要驱动因素。     

收缩城市住房空置时空分异及影响机制——基于居民用电量视角

以中国典型的资源型收缩城市——伊春市的伊春区为研究对象,从居民用电量视角对住房空置情况进行判定,同时综合运用核密度估计、网络分析以及问卷访谈等方法,基于区域、居住区、格网3种尺度,对2013—2018年住房空置时空分异格局及影响机制进行深入探究。结果表明：① 伊春区空置住房总量和空置率总体表现为波动上升态势,在国际通行标准下处于“供需基本平衡”状态;② 伊春区住房空置格局在区域尺度、居住区尺度、格网尺度等不同尺度下表现出一定差异性,但各尺度均总体呈现“核心?边缘”的空间分布特点;③ 人口流失、经济支撑、城市功能地位以及居民感知等因素影响伊春区住房空置时序演变,而城市空间开发扩展、住区建设演变、教育医疗设施布局、公共交通可达性等因素共同作用于住房空置的空间分异。     

城市能源消费碳排放特征及其机理分析 ——以广州市为例

采用表观能源消费数据进行分能源品种和分行业类型的碳排放总量核算,利用基于IDA理论和Kaya恒等式的LMDI模型对碳排放总量变化进行多要素的分解分析,在解析人口规模效应、经济产出效应、能源强度效应对碳排放影响机理的同时,进一步纳入人口结构性因素、产业结构性因素和能源结构性因素对碳排放的影响。以广州市为例,对其2003—2013年产业活动和居民消费2个部门碳排放的主要驱动因素进行时间序列分析,并定量研究各个影响因子在2003—2005、2005—2010和2010—2013年3个不同发展阶段的作用机理,主要研究结论如下：1）广州市能源消费及其碳排放前期以煤炭为主,近年来以石油为主,同时外购电力对广州市的能源消费结构优化影响显著。2）各影响因子对广州市碳排放总量变化的作用机理与影响机制在3个发展阶段各不相同,不同发展阶段的发展措施和政策背景对于各个影响因子的碳排放效应影响显著。3）总体分析,经济产出效应和人口规模效应是产业部门碳排放增长的最主要贡献因子;工业能源消费强度效应、工业能源消费结构效应和经济结构效应是遏制产业部门碳排放增长的最主要贡献因子。城镇居民收入效应是居民消费碳排放增长的最主要贡献因子,城镇居民能源消费强度效应是遏制居民消费碳排放增长的最主要贡献因子。     

Relationships between energy consumption and climate change in China

Energy consumption has an inevitable connection with economic level and climate. Based on selected data covering annual total energy consumption and its composition and that of all kinds of energy in 1953-1999, the annual residential energy consumption and the coal and electricity consumption in 1980-1999 in China, the acreage of crops under cultivation suffered from drought and flood annually and gross domestic product (GDP) in 1953-1999 in the whole country, and mean daily temperature data from 29 provincial meteorological stations in the whole country from 1970 to 1999, this paper divides energy consumption into socio-economic energy consumption and climatic energy consumption in the way of multinomial. It also goes further into the relations and their changes between the climate energy consumption and climate factor and between the socio-economic energy consumption and the economic level in China with the method of statistical analysis. At present, there are obvious transitions in the changing relationships of the energy consumption to economy and climate, which comprises the transition of economic system from resource-intensive industry to technology-intensive industry and the transition of climatic driving factors of the energy consumption from driven by the disasters of drought and flood to driven by temperature.     

中国能源消费与气候变化的关系

Energy consumption has an inevitable connection with economic level and climate. Based on selected data covering annual total energy consumption and its composition and that of all kinds of energy in 1953-1999, the annual residential energy consumption and the coal and electricity consumption in 1980-1999 in China, the acreage of crops under cultivation suffered from drought and flood annually and gross domestic product (GDP) in 1953-1999 in the whole country, and mean daily temperature data from 29 provincial meteorological stations in the whole country from 1970 to 1999, this paper divides energy consumption into socio-economic energy consumption and climatic energy consumption in the way of multinomial. Itchanges between the climate energy consumption andalso goes further into the relations and their changes between the climate energy consumptionenergy consumption and the economic level inand climate factor and between the socio-economic energy between the climate energy level in China with the method of statistical analysis. At present, there are obvious transitions in the changing relationships of the energy consumption to economy and climate, which comprises the transition of economic system from resource-intensive industry to technology-intensive industry and the transition of climatic driving factors of the energy consumption from driven by the disasters of drought and flood to driven by temperature.     

Pricing Weather Derivatives Index based on Temperature: The Case of Bahir Dar,Ethiopia

In this paper we present a stochastic model for daily average temperature to calculate the temperature indices upon which temperature-based derivatives are written. We propose a seasonal mean and volatility model that describes the daily average temperature behavior using the mean-reverting Ornstein-Uhlenbeck process. We also use higher order continuous-time autoregressive process with lag 3 for modeling the time evolution of the temperatures after removing trend and seasonality. Our model is fitted to 11 years of data recorded, in the period 1 January 2005 to 31 December 2015, Bahir Dar, Ethiopia, obtained from Ethiopia National Meteorological Services Agency. The analytical approximation formulas are used to price heating degree days (HDD) and cooling degree days (CDD) futures. The suggested model is analytically tractable for derivation of explicit prices for CDD and HDD futures and option. The price of the CDD future is calculated, using analytical approximation formulas. Numerical examples are presented to indicate the accuracy of the method. The results show that our model performs better to predict CDD indices.     

山岳型酒店能源强度与碳排放特征研究

以黄山西海饭店为山岳型景区案例酒店,采用能源消费账户法与碳足迹法对样本数据进行深入分析,系统地研究了案例酒店近5 a来的能耗与碳排放情况。结果表明,水电是案例酒店的主要能耗,其中,用电能耗在酒店总能耗中占比最高,平均为98%左右;用水占比最小,只有总能耗的1%左右。案例酒店能源消耗总量每年约500 t标准煤,年均碳排放量约为3 695.5 tCO₂,呈现逐年增加趋势。2014?2018年,水电能源消耗最大的部门不是客房部和餐饮部等酒店主营部门,而是园林绿化、公用等酒店辅助部门,用水量达到用水总量的39%~58%,用电量达到用电总量的59.41%~66.68%。酒店年平均能源强度约为0.06 t标准煤/万元,每晚游客人均能耗约0.001 t标准煤。案例酒店碳排放量为217.17~257.84 kgCO₂/m²,年均碳排放量为236.79 kgCO₂/m²。案例酒店年碳排放量与能耗强度呈正相关,且随着酒店能耗强度的上升,碳排放总量也随之增加。     

基于夜间灯光影像的中国电力消耗量估算及时空动态

提出夜间灯光降饱和指数模型,以中国大陆为研究对象,基于DMSP/OLS夜间灯光数据、MODIS NDVI产品、基础地理信息数据及社会经济统计数据,构建电力消耗估算模型,定量估算了2000-2012年电力消耗量,并采用空间统计分析方法,从不同时间、空间角度对省级、地级和县级单元的电力消耗量变化趋势和空间集聚程度进行分析。结果表明：夜间灯光降饱和指数模型能较好地降低夜间灯光的数据饱和和溢出,其中MDNVI模型的效果最好。从县级尺度电力消耗变化趋势的显著性来看,无明显变化区域主要出现在青藏高原,迅猛增长型多数分布在京津冀、长三角、珠三角和中东部省会城市。     

Residential Burglaries and Neighborhood Socioeconomic Context in London,Ontario: Global and Local Regression Analysis*

The main aim of this article is to analyze the relationships between the spatial patterns of residential burglaries and the socioeconomic characteristics of neighborhoods in London, Ontario. Relative risk ratios are applied as a measure of the intensity of residential burglary. The variation in the risks of burglary is modeled as a function of contextual neighborhood variables. Following a conventional (global) regression analysis, spatial variations in the relationships are examined using geographically weighted regression (GWR). The GWR results show that there are significant local variations in the relationships between the risk of residential burglary victimization and the average value of dwellings and percentage of the population in multifamily housing. The results are discussed in the context of four hypotheses, which may explain geographical variations in residential burglary. The practical implication of the GWR analysis is that different crime prevention policies should be implemented in different neighborhoods of the city.     

The Suburbanization of Water Scarcity in the Barcelona Metropolitan Region: Sociodemographic and Urban Changes Influencing Domestic Water Consumption

The metropolitan region of Barcelona is facing change in urban development patterns, sociodemographic structures, and domestic water use and management. In recent years, several drought alerts have been enacted and water restrictions applied, uncovering the fragile equilibrium between the demand and the supply of this resource. We find the literature on determinants of domestic water consumption to be strongly biased toward the effects of economic instruments in the suburban Anglo-American world. Therefore, we widen the scope of determinants by including sociodemographic and territorial variables for the mixed urban model of the metropolitan region of Barcelona. Our results show the relevance of residential land uses for water consumption and can be taken as a guide for developing different urban water policies for different urban forms.     

省域经济增长与电力消费的局域空间计量经济分析

中国各个地区经济发展对电力消费需求量大且存在地域差异,不同区域间的电力需求与经济增长之间的关系十分复杂,并非能由常系数的普通最小二乘回归分析所解释.采用电力消费模型,利用局域空间计量经济学模型方法--空间变系数的地理加权回归模型,对中国省域电力消费与经济增长之间的关系进行了局域空间计量经济分析.结果发现,中国大陆30个省域的电力消费和经济增长之间表现为一种非均衡的联动关系和局域性特征,制定差异化的区域电力消费调控政策是非常必要的.     

城市流动人口居住自选择中的空间权衡分析——以成都市为例

基于成都市主城区各街道的流动人口数据,分析2010-2015年流动人口规模的空间分布格局及居住空间分异程度,并从流动人口行为决策的视角选取影响变量,分析其对居住自选择的影响程度及其空间差异,据此揭示居住自选择中的空间权衡过程,探讨流动人口的空间权衡对其居住自选择和居住空间格局形成的作用。结果表明：2010-2015年,成都流动人口在主城区南部和城市中心快速增加,其集聚态势为西高东低;流动人口相较于本地户籍人口表现出一定程度的居住空间分异性;流动人口占常住人口比、居住区面积、房租、公交、企业及生活服务设施对流动人口居住自选择有明显影响,且流动人口占常住人口比、居住区面积和房租影响显著,但影响关系受流动人口空间自相关影响显著;地理加权回归结果显示不同变量对居住自选择的解释能力存在空间差异性,流动人口通过不同变量空间分布的差异性权衡不同区域,以此完成居住自选择并最终形成居住空间格局。     

Statistics of cloud heights over the Tibetan Plateau and its surrounding region derived from CloudSat data

Cloud-radiation interaction has a large impact on the Earth's weather and climate change, and clouds with different heights cause different radiative forcing. Thus, the information on the statistics of cloud height and its variation in space and time is very important to global climate change studies. In this paper, cloud top height (CTH), cloud base height (CBH) and cloud thickness over regions of the Tibetan Plateau, south slope of the plateau and South Asian Monsoon are analyzed based on CloudSat data during the period from June 2006 to December 2007. The results show that frequency of CTH and CBH in unit area over the studied regions have certain temporal-spatial continuity. The CTH and CBH of different cloud types have different variation scopes, and their seasonal variations are distinct. Cloud thickness is large (small) in summer (winter), and the percentages of different cloud types also have certain regularity.     

都市新区住宅地价空间异质性驱动因素研究 ——基于空间扩展模型和GWR模型的对比

以南京市江宁区为例,基于2004~2011年住宅用地出让数据,利用空间扩展模型和GWR模型对都市新区住宅地价空间异质性及其驱动因素进行研究。结果表明：① 空间扩展模型与GWR模型分别可解释采样区63%、61%的住宅地价变化,较全局回归模型(47%)有显著提升,更有利于研究土地市场的空间异质性。② 空间扩展模型可有效表征各解释变量及其交互项对住宅地价作用的空间结构总体趋势,其拟合效果相对较优。GWR模型则在局部参数估计方面存在优势,借助GIS可将各变量的地价作用模式可视化,从而比空间扩展模型更能有效刻画住宅地价影响因素的空间非平稳性特征,各因素对地价的平均边际贡献排序为水域> 地铁> 大学园区> CBD> 商业网点> 医院,且商业网点、 医院系数值具有方向差异性。③ 距地铁站点、水域、大学园区以及CBD的距离是研究区住宅地价的关键驱动因素,各自存在特有的地价空间作用模式,可为研究区住宅土地市场细分提供科学依据。