Chlorinated paraffins: A review of sample preparation, instrumental analysis, and occurrence and distribution in food samples.

Chlorinated paraffins (CPs) are released into natural environment during processes of production and utilization with diet being the most important exposure route of CPs for human beings. Short-chain chlorinated paraffins (SCCPs) have lower molecular weights, higher vapor pressures, and higher water solubilities than medium-chain chlorinated paraffins (MCCPs) and long-chain chlorinated paraffins (LCCPs), making SCCPs more likely to be readily released into the environment. Thus, SCCPs were enlisted as persistent organic pollutants being included in the Stockholm Convention in 2017. This review article summarized sample preparation and instrumental analysis methods of CPs for food types such as oil, meat, and aquatic foods. In addition, reported concentrations and profiles, dietary intake and risk assessment of CPs in food samples from various regions, such as China, Japan, and Germany are discussed for studies published between 2005 and 2022. This review is timely given the lack of a recent literature summary of the concentration and distribution of CPs in food. All these studies warranted the necessity to maintain continuous monitoring of CPs concentrations and their potential health risks given the concentrations of CPs in food are increasing worldwide.

Greenhouse gas emission estimation from municipal wastewater using a hybrid approach of generative adversarial network and data-driven modelling.

Greenhouse gas (GHG) emissions including carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) created via wastewater treatment processes are not easily modeled given the non-linearity and complexity of biological processes. These factors are also impacted by limited data availability making the development of artificial data generation algorithms, such as a generative adversarial network (GAN), useful for determination of GHG emission rate estimates (EREs). The main objective of this study was to develop a hybrid approach of using GAN and regression modelling to determine GHG EREs from a cold-region biological nutrient removal (BNR) municipal wastewater treatment plant (MWTP) in which the aerobic reactor has previously been established as the main GHG emission source. To our knowledge, this is the first application of GAN used for MWTP modelling purposes. The EREs were generated from laboratory-scale reactors used in conjunction with facility-monitored operating parameters to develop the GAN and regression models. Results showed that regression models provided reasonable EREs using parameters including hydraulic retention time (HRT), temperature, total organic carbon, and dissolved oxygen (DO) concentrations for CO2 EREs; HRT, temperature, DO and phosphate (PO43-) concentrations for CH4 EREs; and temperature, DO, and nitrogen (nitrite, nitrate, and ammonium) concentrations for N2O EREs. Additionally, the addition of 100 GAN-created virtual data points improved regression model metrics including increased correlation coefficient and index agreement values, and decreased root mean square error values. Clearly, virtual data augmentation using GAN is a valuable resource in supplementation of limited data for improved modelling outcomes. Genetic algorithm optimization was also used to determine operating parameter modifications resulting in potential for minimization (or maximization) of GHG emissions.

Treatment of aqueous arsenic - A review of biochar modification methods.

Arsenic (As) is an ever-present worldwide environmental contamination issue. The process of As sorption for treatment of contaminated waters is regarded as a promising treatment technology approach due to its simplicity and potential for high efficiency. Biochars are carbon-rich porous solids produced by heating of biomasses under low oxygen conditions. Biochars are considered to be environmentally friendly sorbents that can be used to treat various As-containing waters. However, unmodified biochar is generally a poor sorbent for As species due to static repulsion between the As oxyanions and the negatively charged biochar surface. The As sorption capacity of biochars can be substantially improved by treatments using various physical and chemical activation and modification methods. Thus, this review includes 63 research studies using physical and chemical approaches to enhance biochar physicochemical structures and As sorption efficiencies. The effectiveness of each method for altering the characteristics and sorption capacity of biochars is described. This review can help to focus the scope of future As biochar sorption studies and aid researchers in optimization of biochar-based sorbents for As treatment.