Anaerobic digestion and recycling of kitchen waste: a review

About 1.6 billion tons of food are wasted worldwide annually, calling for advanced methods to recycle food waste into energy and materials. Anaerobic digestion of kitchen waste allows the efficient recovery of energy, and induces low-carbon emissions. Nonetheless, digestion stability and biogas production are variables, due to dietary habits and seasonal diet variations that modify the components of kitchen waste. Another challenge is the recycling of the digestate, which could be partly solved by more efficient reactors of anaerobic digestion. Here, we review the bottlenecks of anaerobic digestion treatment of kitchen waste, with focus on components inhibition, and energy recovery from biogas slurry and residue. We provide rules for the optimal treatment of the organic fraction of kitchen waste, and guidelines to upgrade the anaerobic digestion processes. We propose a strategy using an anaerobic dynamic membrane bioreactor to improve anaerobic digestion of kitchen waste, and a model for the complete transformation and recycling of kitchen waste, based on component properties.

     

Effects of nuclear chimney on climate

In this paper, according to the data from several single nuclear explosion experiments of an equivalent to magnitude of million tons, and combined with meteorological data, their effects on the regional climate nave been analysed.     

“碳达峰和碳中和”的科学内涵及我国的政策措施

中国提出的"碳达峰和碳中和"目标是基于统筹国际国内两个大局的战略考量,基于科学论证的国家战略需求提出的,实现这一目标挑战和机遇并存。我国的承诺为全球高质量绿色复苏注入了强心剂和新活力,但实现该目标比发达国家面临更大挑战。它将倒逼我国社会经济结构进行重大调整,对科技创新提出了新要求,会给经济高质量发展、建设美丽中国带来机遇。建议切实贯彻我国"十四五"规划纲要提出的"碳强度控制为主,碳排放总量控制为辅的双控目标",充分考虑将碳排放总量控制目标考核和现有污染减排考核体系相结合,增强"十四五"的行动力。尽快制定碳中和目标下的科技创新规划和实施方案。统筹考虑短期经济复苏、中期结构调整、长期低碳转型,布局低碳/脱碳技术,提升未来绿色产业竞争力。     

微塑料污染现状及其毒性效应和机制研究进展

微塑料(microplastics,MPs)作为一种新型的环境污染物近年来逐渐引起全世界的关注,除了对生态环境的影响,微塑料对生物体的毒性效应及其潜在的健康风险也日益成为环境领域的研究热点.本文基于已有研究,阐述微塑料的污染现况,总结微塑料进入机体的分布,归纳微塑料的生物毒性作用和机制,分析微塑料毒性效应的影响因素,并展望了未来的研究方向,为进一步开展微塑料的生物毒性效应、机制研究和健康风险评估提供科学线索和参考.     

气候变化情景下能源效率及其平等准则的研究

为适应气候变化领域国际斗争的需要,本文分析了中国能源生产消费特点、温室气体排放情景、能耗强度和温室气体排放强度及其发展趋势;在温气体限控上提出能源效率与人均温室气体累积和、与人均GDP发展水平、与技术转让相联系的准则。     

Evaluation of PM10 forecasting based on the artificial neural network model and intake fraction in an urban area: A case study in Taiyuan City,China

Primary fine particulate matters with a diameter of less than 10 µm (PM₁₀) are important air emissions causing human health damage. PM₁₀ concentration forecast is important and necessary to perform in order to assess the impact of air on the health of living beings. To better understand the PM₁₀ pollution health risk in Taiyuan City, China, this paper forecasted the temporal and spatial distribution of PM₁₀ yearly average concentration, using Back Propagation Artificial Neural Network (BPANN) model with various air quality parameters. The predicted results of the models were consistent with the observations with a correlation coefficient of 0.72. The PM₁₀ yearly average concentrations combined with the population data from 2002 to 2008 were given into the Intake Fraction (IF) model to calculate the IFs, which are defined as the integrated incremental intake of a pollutant released from a source category or a region over all exposed individuals. The results in this study are only for main stationary sources of the research area, and the traffic sources have not been included. The computed IFs results are therefore under-estimations. The IFs of PM₁₀ from Taiyuan with a mean of 8.5 per million were relatively high compared with other IFs of the United States, Northern Europe and other cities in China. The results of this study indicate that the artificial neural network is an effective method for PM₁₀ pollution modeling, and the Intake Fraction model provides a rapid population risk estimate for pollutant emission reduction strategies and policies.

Implications The PM₁₀ (particulate matter with an aerodynamic diameter ≤10 μm) yearly average concentration of Taiyuan, with a mean of 0.176 mg/m³, was higher than the 65 μg/m³ recommended by the U.S. Environmental Protection Agency (EPA). The spatial distribution of PM₁₀ yearly average concentrations showed that wind direction and wind speed played an important role, whereas temperature and humidity had a lower effect than expected. Intake fraction estimates of Taiyuan were relatively high compared with those observed in other cities. Population density was the major factor influencing PM₁₀ spatial distribution. The results indicated that the artificial neural network was an effective method for PM₁₀ pollution modeling.