三峡典型区农村居民点格局及人居环境适宜性评价研究

与我国平原区农村居民点呈团簇状分布不同,三峡库区农村居民点规模小、密度大、分布散乱,呈现出"满天星"状的分布格局。以渝北、万州和秭归移民区作为三峡典型区,利用面向对象分类和监督分类相结合的方法从高分辨率遥感影像提取了农村居民点。在此基础上利用GIS技术对农村居民点空间分布规律特征和制约农村居民点分布的要素如海拔、坡度、坡向、道路、水源等进行了分析;借鉴农用地评价方法,利用评价中的多指标综合评价法,结合层次分析法（AHP）生成人居环境适宜性评价图。研究结果表明,三峡农村居民点受到海拔、坡度、坡向等因子的影响呈现出较明显的空间分布规律。三峡典型区农村居民点格局及人居环境适宜性评价结果为农村居民点布局的合理规划提供了参考和依据。     

京津冀地区散煤燃烧大气污染物排放清单

为研究京津冀地区民用散煤燃烧大气污染物的排放情况，结合散煤燃烧活动水平与燃用特征，根据排放因子法自下而上建立了2018年京津冀地区民用散煤燃烧污染物排放清单，研究了污染物排放的时空分布特征并使用蒙特卡罗方法对排放清单进行了不确定性分析.结果表明：2018年京津冀地区民用散煤燃烧量共计3799.22万t，PM_2.5、CO、SO₂、NO_x的排放量分别为9.27，341.31，5.17，5.44万t.污染物排放集中在11月份~次年3月份，大多数地区呈现出相同的日排放趋势.8：00、11：00、18：00、21：00左右出现污染物排放峰值，小时排放系数平均值分别为11%，6%，7%，13%.PM_2.5排放高值区主要集中在北部、东部及部分南部地区，CO主要集中在北京和天津地区，SO₂和NO_x主要集中在天津和承德地区.     

Factors affecting the variability of household water use in Melbourne,Australia

This study investigates the variability of household water use in Melbourne with the aim of improving the current understanding of factors affecting residential water use. This understanding is critical to predicting household water demand, particularly at an appropriate spatial and temporal resolution to support Integrated Urban Water Management based planning and to improve the understanding on how different household water demands respond to demand management strategies. The study used two sets of data each collected from 837 households under significantly different water use conditions in the years 2003 and 2011. Data from each household consist of the household characteristics and quarterly metre readings. Ordinary Least Square regression analysis followed by detailed analysis of each factor was used to identify key factors affecting household water use. The variables studied are household size, typology of dwelling, appliance efficiency, presence of children under 12 years, presence of children aged between 12 and 18 years, tenancy, dwelling age, presence of swimming pool, evaporative cooler, and dishwasher. All of them except presence of children aged between 12 and 18 years, tenancy and dwelling age were identified as variables that contribute to the variability of household water use in Melbourne. The study also found that the explanatory capacity of these variables increases with decreasing water use. This paper also discusses the significance of the explanatory variables, their impact and how they vary over the seasons and years. The variables found in this study can be used to inform improved prediction and modelling of residential water demand. The paper also explores other possible drivers to explain residential water use in light of the moderate explanatory capacity of the variables selected for this study thus, provides useful insights into future research into water demand modelling.