Evaluating the impact of green roof evapotranspiration on annual building energy performance

The performance of the building envelope predominantly determines the ultimate energy performance throughout the lifecycle of a building. A sustainable alternative to enhance roof performance while limiting heat flux through a roof is integrating passive techniques such as green roof. Particularly, green roof performance is sensitive to local climate. The main objective of this study was to evaluate the evapotranspiration effect of an extensive green roof on annual energy consumption of an office building in relation to the humid continental climate of Republic of Korea. The dynamic behavior of green roof and building energy performance were investigated through a parametric simulation method using green roof module in EnergyPlus coupled with jEPlus. Structural data of the reference building and ASHARE 90.1-2007 operational schedules were used as inputs for baseline building model while inputs for the green roof module were based on experimental data sets. Due to the influence of the humid conditions and local wind current on the evapotranspiration process, it was generally found that high leaf area index (LAI) reduced cooling energy demand and somewhat reduced heating energy demand as well; corresponding to the highest daily evapotranspiration fluxes of 4.79 mm day^?1 in summer and 1.80 mm day^?1 in winter. Increasing LAI from 20% to 100% cover increased evapotranspiration flux by 10.4% in summer and 80.2% in winter. Thus to minimize energy losses in winter, foliage cover must be carefully considered. Within limitations specified, the overall annual building energy consumption deceased by 90.9 GJ (3.7%).     

利用数码相片对冬小麦生物量的试算

数码相片属于地面遥感资料的一种,被广泛应用于实地调查中.然而,目前利用数码相片对植被生物量进行推算的研究很少.利用数码相片提取小麦生长期的小麦覆盖度,结合地面实测叶面积指数(LAI)、归一化植被指数(NDVI)和小麦生物量,分析小麦覆盖度与LAI,NDVI,生物量与小麦覆盖度、LAI,NDVI各自的相关系数,建立各自合适的回归模型推算冬小麦的生物量.结果表明,在小麦生长期,小麦覆盖度与LAI,NDVI的相关系数R2分别达到0.765,0.896,生物量与小麦覆盖度、LAI,NDVI的相关系数R2分别为0.774,0.876,0.712,生物量与其小麦覆盖度、LAI,NDVI之间具有很高的相关性,多元回归分析效果更好,系数R2达0.891.结果说明,在不破坏植被生长状态的情况下,基于数码相片可有效地推算小麦的生物量,这为大面积实地测量和遥感监测作物长势及其生物量估算提供了理论参考依据.     

红壤丘陵区LAI与土壤侵蚀分布特征的关系

叶面积指数(LAI)是常用的一个用于描述植被覆盖的方面指数,土壤侵蚀的分布又与植被的覆盖状况息息相关,这就意味着LAI与土壤侵蚀有一定的相关性,目前有关这二者的相关性研究还鲜有文献报道。基于这此,本研究首先利用2000年的遥感影像(TM)解释出该年度的土壤侵蚀强度图,再利用该遥感影像通过图像的代数运算得出该地区的NDVI栅格图,通过实测该县不同典型植被条件的LAI值,得出实测的LAI与图像NDVI值之间的函数关系式,由图像的代数运算把NDVI图转换成LAI图,即实现了遥感图像的实测LAI纠正。在GIS软件的帮助下,通过将LAI栅格图与土壤侵蚀强度图的空间叠加分析,得到不同LAI条件下的土壤侵蚀分布。结果表明,LAI与土壤侵蚀的分布表现为:大致以LAI=2为分界线,当LAI<2时,土壤侵蚀并未随LAI的增加而迅速减少,LAI>2时,土壤侵蚀的分布随植被指数的增加而减少,当LAI=2左右时,土壤侵蚀的面积最大。这种情况对于轻度、中度及强度土壤侵蚀的影响是类似的,都呈类正态分布的曲线形式,但在曲线的两侧土壤侵蚀类型是有本质区别的,在曲线的左侧土壤侵蚀类型的分布是中度和强度为主,而在曲线右侧则以轻度为主。表明LAI这个指标与土壤侵蚀有很好的相关性,可以用于土壤侵蚀方面的相关研究工作。     

PIXGRO: A model for simulating the ecosystem CO2 exchange and growth of spring barley

A model, PIXGRO, developed by coupling a canopy flux sub-model (PROXEL_NEE; PROcess-based piXEL Net Ecosystem CO₂ Exchange) to a vegetation structure submodel (CGRO), for simulating both net ecosystem CO₂ exchange (NEE) and growth of spring barley is described. PIXGRO is an extension of the stand-level CO₂ and H₂O-flux model PROXEL_NEE, that simulates the NEE on a process basis, but goes further to include the dry matter production, partitioning, and crop development for spring barley. Dry matter partitioned to the leaf was converted to leaf area index (LAI) using relationships for the specific leaf area (SLA). The canopy flux component, PROXEL_NEE was calibrated using information from the literature on C3 plants and was tested using CO₂ flux data from an eddy-covariance (EC) method in Finland with long-term observations. The growth component (CGRO) was calibrated using data from the literature on spring barley as well as data from the Finland site. It was then validated against field data from two sites in Germany and partly via the use of MODIS remotely sensed LAI from the Finland site.Both the diurnal and the seasonal patterns of gross CO₂ uptake were very well simulated (R² = 0.92). A slight seasonal bias may be attributed to leaf ageing. Crop growth was also well simulated; simulated dry matter agreed with field observed data from Germany (R² = 0.90). For LAI, the agreement between the simulated and observed was good (R² = 0.80), giving an indication that functions describing the conversion of fixed CO₂ to dry matter and the subsequent partitioning leaf dry matter and LAI simulation were robust and provided reliable estimates.The MODIS LAI at a resolution of 1000 m agreed poorly (R² = 0.45) with the PIXGRO simulated LAI and the observed LAI at the Finland site in 2001. We attributed this to the coarse resolution of the image and/or the small size of the barley field (about 17 ha or 0.25 km²) at the Finland site. By deriving a regression relation between the observed LAI and NDVI from a higher resolution MODIS (500 m resolution), the MODIS-recalculated LAI agreed better with the PIXGRO-simulated LAI (R² = 0.86).PIXGRO provides a prototype model bridging the disciplines of plant physiology, crop modeling and remote sensing, for use in a spatial context in evaluating carbon balances and plant growth at stand level, landscape, regional, and with some care, continental scales. Since almost 50% of the European land surface is covered by crops, such a model is needed for the dynamic estimation of LAI and NEE of croplands.     

上海市生态用地属性与空气负离子浓度的关联性

空气负离子具有杀菌、降尘、清洁空气的功效,能够表征环境空气的清洁度.为探明上海市生态用地空气负离子浓度的分布特征,便于人们休闲游憩,选择24个上海市生态核查样区,在植被最为茂盛的夏季进行空气离子浓度监测(离子迁移率为0.4 cm2/(V· s)),共获得正、负离子现场监测数据各21 600个,研究生态用地属性与空气负离子浓度的关系.结果表明:外环以内生态用地负离子浓度总体低于外环以外,内陆地区总体低于临海地区,上海植物园最低,海湾森林公园最高;除东平森林公园外,其他生态用地空气负离子浓度均大于正离子浓度;市区的共青森林公园、世纪公园,郊区的余山森林公园、金山岛自然保护区等8个样区CI均大于1,空气清洁度为A,最清洁;负离子浓度与植被覆盖度、LAI总体没有明显相关性,但在同一样区3个样方植被覆盖度相差大于等于0.10或LAI相差大于等于1的地区,负离子与植被覆盖度、LAI呈正相关性;负离子与温度呈负相关,不具备显著性,与相对湿度呈明显的正相关性.     

Net primary productivity of China's terrestrial ecosystems from a process model driven by remote sensing

The terrestrial carbon cycle is one of the foci in global climate change research. Simulating net primary productivity (NPP) of terrestrial ecosystems is important for carbon cycle research. In this study, China's terrestrial NPP was simulated using the Boreal Ecosystem Productivity Simulator (BEPS), a carbon-water coupled process model based on remote sensing inputs. For these purposes, a national-wide database (including leaf area index, land cover, meteorology, vegetation and soil) at a 1 km resolution and a validation database were established. Using these databases and BEPS, daily maps of NPP for the entire China's landmass in 2001 were produced, and gross primary productivity (GPP) and autotrophic respiration (RA) were estimated. Using the simulated results, we explore temporal-spatial patterns of China's terrestrial NPP and the mechanisms of its responses to various environmental factors. The total NPP and mean NPP of China's landmass were 2.235 GtC and 235.2 gCm(-2)yr(-1), respectively; the total GPP and mean GPP were 4.418 GtC and 465 gCm(-2)yr(-1); and the total RA and mean RA were 2.227 GtC and 234 gCm(-2)yr(-1), respectively. On average, NPP was 50.6% of GPP. In addition, statistical analysis of NPP of different land cover types was conducted, and spatiotemporal patterns of NPP were investigated. The response of NPP to changes in some key factors such as LAI, precipitation, temperature, solar radiation, VPD and AWC are evaluated and discussed.