东平湖DOM荧光特征及与氢氧同位素指标的相关性

本研究在运用三维荧光光谱示踪平水期东平湖DOM荧光特征的基础上,进一步分析其与氢氧同位素指标的相关性,并在此基础上尝试对大气降水的DOC贡献进行估算,以期为东平湖的污染控制及治理提供依据.结果表明,东平湖平水期DOM主要由类蛋白组分（C1和C4）和类腐殖质组分（C2和C3）构成,以类酪氨酸组分C1为主,C1所占比重将近50%.平水期东平湖DOM同时受陆源、内源及大气降水的影响,但以内源输入为主;外源输入中大气降水补给与大汶河输入所占比例相当;大气降水中的溶解性有机碳输入可能会对东平湖DOM产生不可忽视的影响,需进一步系统研究.氢氧稳定同位素与溶解态有机碳以及类腐殖质荧光之间呈显著相关关系,可以在一定程度上指示DOM的变化趋势.     

Simulation of a 100-MW solar-powered thermo-chemical air separation system combined with an oxy-fuel power plant for bio-energy with carbon capture and storage (BECCS)

The combination of concentrated solar power–chemical looping air separation (CSP-CLAS) with an oxy-fuel combustion process for carbon dioxide (CO₂) capture is a novel system to generate electricity from solar power and biomass while being able to store solar power efficiently. In this study, the computer program Advanced System for Process Engineering Plus (ASPEN Plus) was used to develop models to assess the process performance of such a process with manganese (Mn)-based oxygen carriers on alumina (Al₂O₃) support for a location in the region of Seville in Spain, using real solar beam irradiance and electricity demand data. It was shown that the utilisation of olive tree prunings (Olea europaea) as the fuel—an agricultural residue produced locally—results in negative CO₂ emissions (a net removal of CO₂ from the atmosphere). Furthermore, it was found that the process with an annual average electricity output of 18 MW would utilise 2.43% of Andalusia’s olive tree prunings, thereby capturing 260.5 k-tonnes of CO₂, annually. Drawbacks of the system are its relatively high complexity, a significant energy penalty in the CLAS process associated with the steam requirements for the loop-seal fluidisation, and the gas storage requirements. Nevertheless, the utilisation of agricultural residues is highly promising, and given the large quantities produced globally (~?4 billion tonnes/year), it is suggested that other novel processes tailored to these fuels should be investigated, under consideration of a future price on CO₂ emissions, integration potential with a likely electricity grid system, and based on the local conditions and real data.