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Hybrid energy systems with renewable energy penetration have become popular solutions to improve energy security and realize the carbon neural target in urban areas. In this paper, a holistic framework is proposed for the sustainable development of a neighborhood-scale energy system integrating rooftop PV and waste-to-energy technologies. Under this framework, potential assessment of local renewable energy, optimization approach, and sensitivity analysis are integrated for the optimal design and management of the hybrid energy system with uncertain analysis. Besides, the economic, efficiency, and environmental performance under grid-connected and off-grid operation modes are compared. This proposed framework is applied to a neighborhood area in Beijing. The results show that the grid-connected hybrid energy system will still rely on traditional energy supply with low cost but great carbon emissions. In the off-grid mode, 11 % of the rooftop area will be encouraged to deploy PV panels, which satisfying 39 % of the total electricity demand. Moreover, although decreasing the PV capital cost, raising the electricity price, and increasing carbon emission penalty cost will stimulate the development of local renewable energy, compulsive renewable energy penetration policy is more effective to promote the traditional energy system transformation and reduce carbon emissions. • A holistic framework for optimizing the neighborhood-scale energy system was presented. • A hybrid energy system with the integration of rooftop PV and waste-to-energy was proposed. • The impacts of operation modes, energy policies, and uncertain parameters were investigated. • Technical, economic, and environmental performance of hybrid energy systems was evaluated. [ABSTRACT FROM AUTHOR]

Multi-sensor measurement of complex surfaces requires appropriate sampling to achieve holistic measurement with improved accuracy and efficiency. This paper presents an intelligent sampling strategy for such measurement. A multi-sensor data fusion algorithm is developed based on dependant Gaussian processes regression model and is served as the mathematical foundation to perform adaptive sampling of the surfaces with Bayesian inference by taking the bias and the variance of the fused model as the sampling criteria. The characteristics of the surface features are taken into account by designing domain specific kernel functions. Experimental work on a variety of complex surfaces is also presented. [ABSTRACT FROM AUTHOR]

Objective We aimed to fully describe epidemiologic characteristics, clinical manifestations, and clinical outcomes of Ebola virus disease (EVD), as well as detect independent factors significantly associated with mortality of the disease. Methods One hundred thirty-nine confirmed EVD patients enrolled at the JUI Holding and Treatment Centre in western Sierra Leone between November 15, 2014, and January 18, 2015, and demographic and clinical data were retrospectively collected and analyzed. Results The median age of investigated patients was 29 years and 55.4% were women. Of them, 76 patients (54.7%) died and 63 patients (45.3%) were cured. Case fatality rate among male patients was higher than in female patients (69.4% vs 42.9%). Fatigue (82.0%), anorexia (70.5%), abdominal pain (59.7%), diarrhea (58.3%), vomiting (56.1%), fever (55.4%), and muscle pain (54.0%) were the most common symptoms. In addition, 55.4% of investigated patients reported fever. Bleeding was seen in 10.8% of patients. Conclusions Our data show that mortality of EVD is associated with an older age, fever, and probably hiccups. [ABSTRACT FROM AUTHOR]

• A high spatial resolution land-use suitability assessment for large-scale PV in China. • A PRECIS model-based climate change simulation under RCP 4.5 and 8.5 scenarios. • The impacts of climate change on generation potential for different land classifications. • The contribution of large-scale PV deployment to China's net-zero electricity system by 2050. As China has pledged to become carbon neutral by 2060, electrifying its energy sector is no doubt one of the priority measures to support the transition towards a more sustainable and decarbonized energy system. Solar photovoltaics (PV) has been known as one of the most promising renewable technologies to facilitate the electrification of energy systems. The feasibility of utilizing PV to implement a nationwide decarbonized electricity system now becomes an urgent unanswered question, especially in the context of global climate change and rapid economic growth in China. Here, by using a GIS-based multiple-criteria decision-making approach we address this question by conducting a comprehensive feasibility analysis with consideration of various economic, technological, logistical, and climate change factors. We show that it is feasible for China to fulfill a net-zero electricity system by 2050, through the installation of 7.46 TW solar PV panels on about 1.8% of the national land area (mostly in western China) with a total capital investment of 4.55 trillion USD in the next 30 years. Besides, we show that future climate change may lead to a slight decrease (less than 5%) in solar energy potential, but this would not affect the capability of the nationwide PV system to meet the need for a fully-electrified energy system. [Display omitted] [ABSTRACT FROM AUTHOR]

• Waste biomass and rooftop photovoltaic is integrated into the hybrid power system. • The effects of renewable energy policy and demand response are investigated. • Sensitivity analysis is performed with the consideration of uncertainties. • Demand response program is helpful to reduce both system cost and carbon emission. Modern urban energy system with renewable energy sources has become an effective solution to enhance energy security and promote carbon neutrality. This paper presents a holistic framework for the optimal design and management of such a flexible hybrid power system at the community scale. This framework integrates the potential assessment of rooftop PV and waste biomass, a general optimization approach with multi-perspective performance evaluation, as well as the impacts analysis of energy policy, demand response, and uncertain economic parameters. The proposed framework was applied to a small neighborhood area in Beijing, China. It was found that 100% utilization of available biomass and rooftop PV would satisfy 73% of local electricity demand with the levelized cost of electricity of 0.1030 $/kWh and the embodied carbon emission of 0.5416 kg/kWh. The flexible shiftable load could lead to lower peak load and less electricity supply cost, and help to match the energy demand with the dispatchable rooftop PV output. However, the economic benefits caused by implementing demand response are more obvious than the environmental benefits. Furthermore, a higher electricity tariff and lower capital cost of PV technology would facilitate the investment in rooftop PV and achieve carbon emission reduction targets. [ABSTRACT FROM AUTHOR]

Abstract: This paper analyzes two important problems of online thematic map cartography facing, namely which technique solution is appropriate and how to simplify the cartography process. Firstly, contrasts some popular technique solutions of thematic map, and points out the bottlenecks and inconveniences of thematic map cartography process nowadays, then brings out active online thematic map cartography based on the technique solution of RIA (Rich Internet Applications). In addition, this paper gives out RIA-based implementation framework of active online thematic maps mapping, which is contrasted with RIA-based implementation framework of general online thematic maps mapping, and main methods of building knowledge of active cartography of thematic map. [Copyright &y& Elsevier]

• A GIS-based MCDM method presented for site selection of large-scale solar plants. • Theoretical and technical potentials assessment for both PV and CSP technologies. • Sensitivity analysis performed to investigate the influence of system efficiency variation. • Land suitability map of Ningxia with the spatial distribution of capacity and power output. By combining geographic information systems (GIS) and multi-criteria decision making (MCDM) method, this paper presents a framework to evaluate the suitable location and technical potentials for large-scale solar photovoltaic (PV) and concentrated solar power (CSP) plants. With the assist of spatial tools, the potential locations are identified by extracting restrictive criteria (e.g. protected area, land cover, transport infrastructure, and orography). Using MCDM, the land suitability for PV and CSP plants is evaluated with the comprehensive consideration of different factors, such as climate, orography, water availability, and location, where factor weights are calculated by the analytic hierarchy process (AHP) method. The study framework is illustrated by Ningxia, China, a key energy project area along the Belt and Road with abundant solar radiation. The obtained results suggested that the middle area of Ningxia is recommended for the solar power plant deployment. Besides, due to the limitation of water resource availability, PV technology is more appropriate for the study area than CSP technology. The estimated total technical potentials of PV and CSP systems could be 443 TWh/year and 308 TWh/year, indicating great potential for future solar energy development to enhance the renewable energy supply and participate in energy cooperation with the other regions. Moreover, sensitivity analysis is conducted to investigate the impacts of system efficiency variation on energy output. The results can be used for the identification of the potential areas for solar power plant installation, as well as support for the synergic expansion of generation plants and the power grid. Image, graphical abstract [ABSTRACT FROM AUTHOR]