Insight into key interactions between diverse factors and membrane fouling mitigation in anaerobic membrane bioreactor.

Anaerobic membrane bioreactors (AnMBRs) have garnered considerable attention as a low-energy and low-carbon footprint treatment technology. With an increasing number of scholars focusing on AnMBR research, its outstanding performance in the field of water treatment has gradually become evident. However, the primary obstacle to the widespread application of AnMBR technology lies in membrane fouling, which leads to reduced membrane flux and increased energy demand. To ensure the efficient and long-term operation of AnMBRs, effective control of membrane fouling is imperative. Nevertheless, the interactions between various fouling factors are complex, making it challenging to predict the changes in membrane fouling. Therefore, a comprehensive analysis of the fouling factors in AnMBRs is necessary to establish a theoretical basis for subsequent membrane fouling control in AnMBR applications. This review aims to provide a thorough analysis of membrane fouling issues in AnMBR applications, particularly focusing on fouling factors and fouling control. By delving into the mechanisms behind membrane fouling in AnMBRs, this review offers valuable insights into mitigating membrane fouling, thus enhancing the lifespan of membrane components in AnMBRs and identifying potential directions for future AnMBR research.

Highly Efficient Transformation of Tar Model Compounds into Hydrogen by a Ni-Co Alloy Nanocatalyst During Tar Steam Reforming.

Hydrogen (H2) production from coal and biomass gasification was considered a long-term and viable way to solve energy crises and global warming. Tar, generated as a hazardous byproduct, limited its large-scale applications by clogging and corroding gasification equipment. Although catalytic steam reforming technology was used to convert tar into H2, catalyst deactivation restricted its applicability. A novel nanocatalyst was first synthesized by the modified sol-gel method using activated biochar as the support, nickel (Ni) as the active component, and cobalt (Co) as the promoter for converting tar into H2. The results indicated that a high H2 yield of 263.84 g H2/kg TMCs (Tar Model Compounds) and TMC conversion of almost 100% were obtained over 6% Ni-4% Co/char, with more than 30% increase in hydrogen yield compared to traditional catalysts. Moreover, 6% Ni-4% Co/char exhibited excellent resistance to carbon deposition by removing the nucleation sites for graphite formation, forming stable Ni-Co alloy, and promoting the char gasification reaction; resistance to oxidation deactivation due to the high oxygen affinity of Co and reduction of the oxidized nickel by H2 and CO; resistance to sintering deactivation by strengthened interaction between Ni and Co, high specific surface area (920.61 m2/g), and high dispersion (7.3%) of Ni nanoparticles. This work provided a novel nanocatalyst with significant potential for long-term practical applications in the in situ conversion of tar into H2 during steam reforming.

Isolation and characterization of ovine monocyte-derived macrophages from peripheral blood.

As key elements and targets for various intracellular pathogens, macrophages play an essential role in host defense. Although ovine peripheral blood monocyte-derived cell lines have been established, their phenotypic characteristics and functional properties remain unknown. We have established several ovine macrophage cell lines from peripheral blood adherent cells that can proliferate spontaneously in long-term culture in vitro. Characteristics of macrophages were shaped by cell morphology, cell adhesion, expression of cell surface markers, phagocytic activity and inflammatory response. Furthermore, the differences of genes expression (such as membrane proteins, pro-inflammatory cytokines and chemokine) were compared between blood macrophages (BMs) and alveolar macrophages (AMs), and between BMs and splenic macrophages (SMs), respectively. The expression of membrane genes (CD11b and CD80), pro-inflammatory cytokines (IL-1ß and TNFα) and chemokines (IL-8/CXCL8 and CCL-21) was lower than that in AMs or SMs, but not CD200. Moreover, BMs maintained lower expression level of M1 macrophage related genes (iNOS and IDO), but high expression levels of M2 macrophage related genes (ARG2 and TGFß1). BMs showed lower phagocytic ability than AMs and SMs. Compared with AMs, BMs showed higher salmonella proliferation rate within cells. Collectively, BMs could suppress inflammatory responses and possessed partly phenotypic characteristics of M2 macrophages.

Change in rainfall drives malaria re-emergence in Anhui Province, China.

Malaria is re-emerging in Anhui Province, China after a decade long' low level of endemicity. The number of human cases has increased rapidly since 2000 and reached its peak in 2006. That year, the malaria cases accounted for 54.5% of total cases in mainland China. However, the spatial and temporal patterns of human cases and factors underlying the re-emergence remain unclear. We established a database containing 20 years' (1990-2009) records of monthly reported malaria cases and meteorological parameters. Spearman correlations were used to assess the crude association between malaria incidence and meteorological variables, and a polynomial distributed lag (PDL) time-series regression was performed to examine contribution of meteorological factors to malaria transmission in three geographic regions (northern, mid and southern Anhui Province), respectively. Then, a two-year (2008-2009) prediction was performed to validate the PDL model that was created by using the data collected from 1990 to 2007. We found that malaria incidence decreased in Anhui Province in 1990s. However, the incidence has dramatically increased in the north since 2000, while the transmission has remained at a relatively low level in the mid and south. Spearman correlation analyses showed that the monthly incidences of malaria were significantly associated with temperature, rainfall, relative humidity, and the multivariate El Niño/Southern Oscillation index with lags of 0-2 months in all three regions. The PDL model revealed that only rainfall with a 1-2 month lag was significantly associated with malaria incidence in all three regions. The model validation showed a high accuracy for the prediction of monthly incidence over a 2-year predictive period. Malaria epidemics showed a high spatial heterogeneity in Anhui Province during the 1990-2009 study periods. The change in rainfall drives the reemergence of malaria in the northern Anhui Province.