Economics analysis of food waste treatment in China and its influencing factors

• Economics of food waste treatment projects at 29 pilot cities in China was examined. • Roles of location, population size, processing technique, and income were studied. • Economic benefits were limited with a profit to cost ratio of 0.08±0.37. • Service population size affects construction economics significantly (P = 0.016). • Choice of food waste processing technique affects operating economics notably. This study examines the economic benefits of food waste treatment projects in China and factors affecting them. National-level pilot projects for food waste treatment located in 29 cities were selected as samples. The economics of food waste recycling from the investors’ perspective, in terms of investment during the construction phase and cost and benefit during the operation phase, was assessed. Results indicate that the average tonnage investment of food waste treatment projects was RMB 700.0±188.9 thousand yuan, with a profit to cost ratio of 0.08±0.37. This ratio increased to 0.95±0.57 following the application of government subsidies. It highlights the limited economic benefits of food waste treatment facilities, which rely on government subsidies to maintain their operations in China. Further analysis using a multi-factor analysis model revealed that regional location, service population size, processing techniques, and urban income exerted varying impacts on the economy of food waste treatment. Population size exerted the highest impact (P = 0.016) during the construction stage, and processing techniques notably influenced the project economy during the operation stage. The study highlights the need to prioritize service population size and processing techniques during economic decision-making and management of food waste recycling projects. The results of this study can serve as a valuable practical reference for guiding future policies regarding food waste treatment and related planning.     

微塑料污染的水生生态毒性与载体作用

近年来,微塑料的水生生态环境污染与生态毒害问题引起了科学界的广泛关注。在总结国内外相关研究的基础上,本文对水生态环境中微塑料的来源、形成与分布展开分析;对微塑料污染的生态毒性研究进展给予评述;并深入探讨了微塑料在生态系统中扮演的多重载体角色。鉴于微塑料污染的严峻现实,我国应尽快开展有关微塑料环境污染和生态毒理方面的系统研究,并辅以政策引导和经济支持。     

基于生物光谱技术的污染物毒性效应研究进展

生物光谱技术能够有效反映生物、组织以及细胞等样本中生物化学的综合信息,能够精确检测和评价生物分子成分或构象的微观变化,具有快速、客观、无损、重现性好等优点。本文系统综述了生物光谱技术在环境污染物毒性效应研究方面的进展,其中常用的2种技术是红外光谱和拉曼光谱技术。红外光谱技术目前已被广泛用于单一污染物(重金属、有机污染物、纳米材料等)以及复合污染对细胞、植物、动物以及微生物的蛋白质、氨基酸、脂质、DNA/RNA、多糖以及碳水化合物等方面的影响研究之中;拉曼光谱技术包括常规拉曼技术和表面增强拉曼光谱技术,二者均可以用于污染物的毒性效应研究之中,表面增强拉曼光谱技术具有信噪比高、检测限低、灵敏度高等特点,并提供丰富的细胞生物化学指纹图谱信息。数据处理是生物光谱技术应用的重要一环,光谱数据分析大致分为光谱数据预处理、提取光谱信息特征、以及信息分类和光谱特征峰解析3个部分。本研究结果将为进一步系统地开展生物光谱技术在污染物毒性效应方面的研究提供支持。     

Release of elements from municipal solid waste incineration fly ash

The element-release behavior of municipal solid waste incineration fly ash was explored through leaching test with continuous set-point pH (pH_stat test) and serial single reaction cell (SSRC) tests. First, the relationship between element release and acid neutralizing capacity (ANC) consumption was examined with a pH_stat test. Four types of release behaviors were identified which are characteristic for different elements: (1) release curves that were almost linear with ANC consumption (Ca, Zn, and Cd); (2) release that was significantly faster than ANC (Na, K, and Cl); (3) curves that featured a strong increase with ANC consumption, after a transient release, followed by an almost equal decrease (Si and S); and (4) release that is strongly retarded compared with ANC consumption (Cr, Cu, and Pb). In the SSRC system, it the existence of a pH front and a wash-out phenomenon is demonstrated. Combining the results from the SSRC test with the kinetic analysis of the ANC system in the pH_stat test, it was inferred that less than one-third of the ANC measured from a batch pH titration plays a neutralization role in a field situation. The methodologies described may provide a powerful set of tools for systematic evaluation of element release from solid wastes.     

用苎麻生物脱胶废水生产热带假丝酵母单细胞蛋白

采用热带假丝酵母处理苎麻生物脱胶废水。将COD为23 060 mg/L的苎麻生物脱胶废水稀释1倍后进行发酵处理,COD去除率最高,为60.85%。发酵条件的正交实验结果表明:在发酵温度为35℃、初始发酵pH为7.0、接种量为10%、发酵时间为48 h的条件下,苎麻生物脱胶废水COD去除率最高;发酵温度为30℃、初始发酵pH为7.0、接种量为10%、发酵时间为48 h的条件下,单细胞蛋白生成量最高。发酵时间为48 h时,灭菌的发酵培养基的COD去除率为75.75%,单细胞蛋白生成量为5.375 g/L;未灭菌的发酵培养基的COD去除率为72.25%,单细胞蛋白生成量为2.875 g/L。     

Vocal competition in male Xenopus laevis frogs

Male Xenopus laevis frogs produce underwater advertisement calls that attract gravid females and suppress calling by male competitors. Here we explore whether groups of males establish vocal ranks and whether auditory cues alone suffice for vocal suppression. Tests of male–male pairs within assigned groups reveal linear vocal dominance relations, in which each male has a defined rank. Both the duration over which males interact, as well as the number of competitive opportunities, affect linearity. Linear dominance across the group is stable for about 2 weeks; rank is dynamic. Males engage in physical interactions (clasping) while paired but clasping and vocal rank are not correlated. Playbacks of advertisement calls suppress calling and calls from high- and low-ranking males are equally effective. Thus, auditory cues alone suffice to suppress vocal behavior. Playback intensities equivalent to a nearby male advertising effectively suppress calling while low-intensity playbacks are either ineffective or stimulate vocal behavior. X. laevis advertisement calls are biphasic, composed of alternating fast and slow click trills. Approximately half the males tested are more vocally suppressed by all slow than by all fast trills; thus, these males can distinguish between the two phases. The fully aquatic family Pipidae diverged from terrestrial ancestors approximately 170 mya. Vocal suppression in the X. laevis mating system may represent the translation of an ancient anuran social strategy to underwater life.     

基于LEAP模型的工业园区碳达峰路径：以南京某国家级开发区为例

工业园区是能源消费和碳排放的密集区域,推动工业园区碳达峰对国家早日实现碳达峰目标具有重要意义.以南京某国家级开发区为例,基于LEAP模型,设置基准情景（BAU）、非工业减排（S1）、全行业一般减排（S2）、全行业强化减排（S3）和深度减排（S4）共5类情景,分析各情景下的能源消费需求和CO2排放变化情况,评估各项措施的碳减排贡献,提出园区实现碳达峰目标的政策建议.结果表明,S2、S3和S4情景下能源消费需求和CO2排放量将分别于2035、2030和2028年达到峰值,能源消费需求峰值（以标煤计）分别为26.28、21.66和19.10万t,CO2排放峰值分别为75.35、59.34和53.24万t.工业是研究区域能源消费和碳排放的主要贡献行业,S2、S3和S4情景下工业能源消费和碳排放占比分别于2035年、2030年和2028年达到峰值57.1%、56.0%、53.6%和64.2%、66.2%和62.9%.工业能效提升的碳减排贡献最大,其次为经济增速放缓,交通新能源汽车推广和公共建筑节能的碳减排贡献不显著.综合考虑碳达峰时间和园区碳排放强度考核目标,建议将S3情景作为该园区碳达峰的实施...     

环境自动监测站固定式辐射监测仪性能测试与评价

参考计量技术规范《固定式环境γ辐射空气比释动能(率)仪现场校准规范》(JJF 1733—2018),对辐射环境空气自动监测站78台高气压电离室开展辐射特性测试。现场校准方面,仅88%的电离室满足1±0.2的响应范围要求;78台电离室的重复性均不超过1%,响应的非线性均不超过6.5%,符合规范要求。针对电离室开展辐射性能测试,发现电离室在9.0×10^-2~1.0×10⁹ μGy/h范围内的响应均不超过1±0.2;电离室对164 keV以上的光子的能量响应趋于1.0,对60 keV以下的光子无响应能力,而当光子能量在60~164 keV范围内时,响应曲线会因γ光子与电离室内部惰性气体的光电效应出现"鼓包";电离室不具备对核临界事故脉冲辐射的监测与警示能力;电离室能够在2 s内给出测量范围内的准确示值,但在分段电压的交界处,响应时间会延长至180~360 s;电离室的响应受环境温度、湿度变化的影响大小不足±0.01,表明电离室的环境适应性优良。     

Prediction of high-density polyethylene pyrolysis using kinetic parameters based on thermogravimetric and artificial neural networks

● Reducting the sampling frequency can enhance the modelling process. ● The pyrolysis of HDPE was investigated at three different heating rates. ● The average E_a and k₀ were calculated by Friedman, KAS, FWO, and CR methods. ● ANN was employed to predict the HDPE weight loss with the optimal MSE and R². Pyrolysis is considered an attractive option and a promising way to dispose waste plastics. The thermogravimetric experiments of high-density polyethylene (HDPE) were conducted from 105 °C to 900 °C at different heating rates (10 °C/min, 20 °C/min, and 30 °C/min) to investigate their thermal pyrolysis behavior. We investigated four methods including three model-free methods and one model-fitting method to estimate dynamic parameters. Additionally, an artificial neural network model was developed by providing the heating rates and temperatures to predict the weight loss (wt.%) of HDPE, and optimized via assessing mean squared error and determination coefficient on the test set. The optimal MSE (2.6297 × 10⁻²) and R² value (R² > 0.999) were obtained. Activation energy and pre-exponential factor obtained from four different models achieves the acceptable value between experimental and predicted results. The relative error of the model increased from 2.4 % to 6.8 % when the sampling frequency changed from 50 s to 60 s, but showed no significant difference when the sampling frequency was below 50 s. This result provides a promising approach to simplify the further modelling work and to reduce the required data storage space. This study revealed the possibility of simulating the HDPE pyrolysis process via machine learning with no significant accuracy loss of the kinetic parameters. It is hoped that this work could potentially benefit to the development of pyrolysis process modelling of HDPE and the other plastics.