Recycling food and agriculture by-products to mitigate climate change: a review

Food loss and waste is a major issue affecting food security, environmental pollution, producer profitability, consumer prices, and climate change. About 1.3 billion tons of food products are yearly lost globally, with China producing approximately 20 million tons of soybean dregs annually. Here, we review food and agricultural byproducts with emphasis on the strategies to convert this waste into valuable materials. Byproducts can be used for animal and plant nutrition, biogas production, food, extraction of oils and bioactive substances, and production of vinegar, wine, edible coatings and organic fertilizers. For instance, bioactive compounds represent approximately 8–20% of apple pomace, 5–17% of orange peel, 10–25% of grape seeds, 3–15% of pomegranate peel, and 2–13% of date palm seeds. Similarly, the pharmaceutical industry uses approximately 6.5% of the total output of gelatin derived from fish bones and animal skin. Animals fed with pomegranate peel and olive pomace improved the concentration of deoxyribonucleic acid and protein, the litter size, the milk yield, and nest characteristics. Biogas production amounts to 57.1% using soybean residue, 53.7% using papaya peel, and 49.1% using sugarcane bagasse.

     

Personal exposure to PM2.5-bound heavy metals associated with cardiopulmonary function in general population

Environmental Science and Pollution Research - To better understand the cardiopulmonary alterations associated with personal exposed PM2.5-bound heavy meals, we conducted a cross-sectional study in...     

Research progress and hot spots of hydrothermal liquefaction for bio-oil production based on bibliometric analysis

Environmental Science and Pollution Research - Hydrothermal liquefaction (HTL) of biomass used HTL reaction under high temperature and pressure to produce bio-oil. This technology is considered as...     

AI-based runoff simulation based on remote sensing observations: A case study of two river basins in the United States and Canada

Data-driven techniques are used extensively for hydrologic time-series prediction. We created various data-driven models (DDMs) based on machine learning: long short-term memory (LSTM), support vector regression (SVR), extreme learning machines, and an artificial neural network with backpropagation, to define the optimal approach to predicting streamflow time series in the Carson River (California, USA) and Montmorency (Canada) catchments. The moderate resolution imaging spectroradiometer (MODIS) snow-coverage dataset was applied to improve the streamflow estimate. In addition to the DDMs, the conceptual snowmelt runoff model was applied to simulate and forecast daily streamflow. The four main predictor variables, namely snow-coverage (S-C), precipitation (P), maximum temperature (T_max), and minimum temperature (T_min), and their corresponding values for each river basin, were obtained from National Climatic Data Center and National Snow and Ice Data Center to develop the model. The most relevant predictor variable was chosen using the support vector machine-recursive feature elimination feature selection approach. The results show that incorporating the MODIS snow-coverage dataset improves the models' prediction accuracies in the snowmelt-dominated basin. SVR and LSTM exhibited the best performances (root mean square error = 8.63 and 9.80) using monthly and daily snowmelt time series, respectively. In summary, machine learning is a reliable method to forecast runoff as it can be employed in global climate forecasts that require high-volume data processing.     

Mechanism of complexation of toxic arsenate,selenate, and molybdate with hydrotalcites

Environmental Chemistry Letters - Wastewater from the uranium mining industry contains toxic arsenate (AsO43–), selenate (SeO42–), and molybdate (MoO42–) that can be removed by...     

全氟辛烷磺酸盐(PFOS)对半滑舌鳎(Cynoglossus semilaevis)免疫相关基因表达的影响

为了解全氟辛烷磺酸盐(perfluorooctane sulfonate, PFOS)暴露对半滑舌鳎(Cynoglossus semilaevis)免疫功能的影响,在实验室条件下,运用RT-PCR方法分析了PFOS暴露对半滑舌鳎热休克蛋白hsp70、hsp90、C型凝集素(c-type lectin)和细胞色素c氧化酶(cytochrome c oxidase, cox)等4种免疫相关基因表达水平的影响。实验测定了上述4种基因在半滑舌鳎肝、鳃、肠及肌肉4种不同组织中随时间(0、24 h、48 h、96 h和7 d)的表达变化情况。结果表明,在4种组织中,hsp70基因的表达与对照相比为上调,其中,肝组织hsp70基因的表达量显著高于其他各组织,且表达高峰值的出现也早于其他各组织;hsp90基因在肝和鳃组织中表达量随时间不同而波动,在肠组织中表达上调,在肌肉中表达显著下调;c-type lectin基因表达量与对照组相比表达显著下调或无明显差异;cox基因在肝组织和肠组织中表达下调,在鳃和肌肉中表达上调。上述研究结果表明,PFOS能引起免疫相关基因的表达变化,对半滑舌鳎具有潜在的免疫毒性。肝组织中各免疫基因对PFOS胁迫的响应高于其他组织。本研究可为阐明全氟辛烷磺酸盐对半滑舌鳎的免疫毒性提供基础数据。     

Determination of 27 pharmaceuticals and personal care products (PPCPs) in water: The benefit of isotope dilution

• Isotope dilution method was developed for the determination of 27 PPCPs in water. • The established method was successfully applied to different types of water samples. • The correction effect of corresponding 27 ILSs over 70 d was investigated. • Benefit of isotopic dilution method was illustrated for three examples. Pharmaceuticals and personal care products (PPCPs) are a unique group of emerging and non-persistent contaminants. In this study, 27 PPCPs in various water samples were extracted by solid phase extraction (SPE), and determined by isotope dilution method using liquid chromatography coupled to tandem triple quadruple mass spectrometer (LC-MS/MS). A total of 27 isotopically labeled standards (ILSs) were applied to correct the concentration of PPCPs in spiked ultrapure water, drinking water, river, effluent and influent sewage. The corrected recoveries were 73%–122% with the relative standard deviation (RSD)<16%, except for acetaminophen. The matrix effect for all kinds of water samples was<22% and the method quantitation limits (MQLs) were 0.45–8.6 ng/L. The developed method was successfully applied on environmental water samples. The SPE extracts of spiked ultrapure water, drinking water, river and wastewater effluent were stored for 70 days, and the ILSs-corrected recoveries of 27 PPCPs were obtained to evaluate the correction ability of ILSs in the presence of variety interferences. The recoveries of 27 PPCPs over 70 days were within the scope of 72%–140% with the recovery variation<37% in all cases. The isotope dilution method seems to be of benefit when the extract has to be stored for long time before the instrument analysis.     

A review of measurement methods for peracetic acid (PAA)

• Physical and chemical properties and application of peracetic acid solution. • Determination method of high concentration peracetic acid. • Determination method of residual peracetic acid (low concentration). Peroxyacetic acid has been widely used in food, medical, and synthetic chemical fields for the past several decades. Recently, peroxyacetic acid has gradually become an effective alternative disinfectant in wastewater disinfection and has strong redox capacity for removing micro-pollutants from drinking water. However, commercial peroxyacetic acid solutions are primarily multi-component mixtures of peroxyacetic acid, acetic acid, hydrogen peroxide, and water. During the process of water treatment, peroxyacetic acid and hydrogen peroxide (H₂O₂) often coexist, which limits further investigation on the properties of peroxyacetic acid. Therefore, analytical methods need to achieve a certain level of selectivity, particularly when peroxyacetic acid and hydrogen peroxide coexist. This review summarizes the measurement and detection methods of peroxyacetic acid, comparing the principle, adaptability, and relative merits of these methods.     

饱和粉末活性炭电化学再生研究

采用电化学再生法对吸附处理染料废水产生的饱和粉末活性炭(PAC)进行再生,以NaCl为电解质,考察了电源类型、pH、再生时间、电压和NaCl浓度对活性炭再生率的影响,并对活性炭表面酸性含氧官能团进行测定。结果表明:(1)在pH=1、直流电压为6V、NaCl为6g/L、再生90min的最佳条件下,采用单室反应器,饱和PAC再生率达到59.09%。(2)电极循环伏安曲线结果表明,饱和PAC电极表面发生氧化反应,与主电极直接和间接氧化共同作用,使活性炭表面吸附的污染物降解。活性炭表面酸性含氧官能团滴定和红外光谱测试结果进一步表明,电化学再生法使活性炭表面基团得到恢复。