农村垃圾厌氧-准好氧时空联合生物反应器中微生物群落分析

生物反应器是处理农村中小型固体废物的有效技术，该研究以时空联合型厌氧-准好氧生物反应器（STASAB）为研究对象，利用16S rRNA高通量测序分析了STASAB中的微生物群落，以期为该反应器的高效运行提供理论依据。结果表明，各生物反应器处理单元中的优势菌门为Proteobacteria(18.5%~26.6%)、Firmicutes(14.9%~26.6%)、Chloroflexi(6.6%~25.2%)、Bacteroidetes(8.2%~24.0%)、Actinobacteria(6.9%~13.8%)。C3处理单元在厌氧阶段中的优势菌属为Lentimicrobiume、vadinBC27_wastewater-sludge_group、Treponema_2、norank_f_Synergistaceae（产甲烷菌）等。在STASAB各处理单元（C1、C2、C3）中发现了硝化细菌Deinococcus-Thermus以及大量的反硝化细菌norank_f_Anaerolineaceae、unclassified_o_Rhizobiales、Hyphomicrobiu、AKYG587、Bacillus、norank_f_Caldilineaceae等。Venn图与PCA分析显示C1、C2具有相似的微生物群落结构，C3中的特有菌属显著高于其它反应器；RDA分析表明C1、C2（STASAB）中的微生物群落具有更高的稳定性，不易受到外界环境因素的影响。因此，STASAB的空间布局和运行方式能够有效发挥厌氧和准好氧生物反应器的优势，高效促进产甲烷菌、硝化菌和反硝化菌的共存和生长代谢，实现农村生活垃圾的快速降解。

Analysis of microbial community in the anaerobic/semi-aerobic spatiotemporal bioreactor for rural wastes

Life cycle assessment (LCA) is an important method that can fully evaluate the natural resources consumed in the production process and activities, as well as its impacts on the environment. In recent years, LCA has been widely used in the biodiesel production process. China is enriched in various biodiesel feedstocks, such as soybean oil, colza oil, jatropha, microalgae and waste cooking oil. In the current study, a life cycle assessment methodology was applied to evaluate the energy consumption and emissions of biodiesel products derived from soybean oil and waste cooking oil in the process of a whole life cycle. The results showed that in the whole life cycle, the total energy consumption of soybean-derived biodiesel was about 2.65 times higher than that of biodiesel derived from waste cooking oil. In the life cycle of soybean oil production for biodiesel, the majority energy consumption was contributed by the soybean planting stage, accounting for 62.55% of the total energy consumption. Particularly, the energy consumption of methanol production was rather high, accounting for 25.88% of the total energy consumption. In the life cycle of biodiesel made from cooking waste oil, the main energy consumption was in the production stage of methanol and catalyst, accounting for 81.12% of the total energy consumption. It was followed by the pretreatment stage of gutter oil, consuming 11.25% of the total energy input. In combustion, the CO2, SO2 and CO emissions from biodiesels either from soybean oil or waste cooking oil were both lower than those from the conventional diesel. Moreover, compared with the emissions of biodiesel derived from soybean oil, the CO2, SO2, NOx, CO, and dust emissions of biodiesel from the waste cooking oil were reduced by 82.92%, 45.68%, 94.91%, 53.40% and 90.61%, respectively. It infers that the application of biodiesel can significantly reduce the emissions of greenhouse and acid gas. It also confirms that the greenhouse effect can be inevitably slowed down when using the biodiesel on a large scale. According to the environmental impact analysis of biodiesel production and utilization processes in the concept of LCA, the potential value of life cycle for the environmental impact of soybean oil as raw material was 11.70 times that of waste cooking oil, which was 8.42 and 0.72, respectively. Global warming was the predominant environmental impact of the biodiesel from soybean oil. In the case of biodiesel derived from waste cooking oil, the regional acidification was the most significant factor. Compared with soybean oil, the biodiesel made from waste cooking oil can effectively reduce the consumption of energy and the emission of pollutants. In addition, it can realize the efficient reuse of waste resources. The life cycle assessment method was of practical significance to evaluate the biodiesel industry. Nevertheless, it is still challenging to form a unified standard among different processes, because of the complex calculation involved in the LCA process. In the future, it is highly necessary to construct a standard database of Chinese biodiesel industry, further to optimize different processes in the production stage. The findings can provide a sound reference for industrial upgrading and department decision-making, and a specific data support for the sustainable development of agricultural industry.