Online platforms provide a public sphere for discussion, debate, and deliberation among citizens. The engagement of online deliberation enables participants to exchange viewpoints and form communities. This paper aims to explore the influencing factors on engagement level of online deliberation by examining the relationship between an initial post’s content features and length and the engagement of the discussion thread it initiates. We sampled 254 discussion threads with 254 initial posts and 2934 following posts and conducted quantitative and qualitative analysis of the posts. Findings show that initial posts which are longer and allocentric (as opposed to egocentric) would evoke longer following posts in a discussion. Different content type (social interaction, claim, argument) of initial posts would lead to significant different engagement, arguments would trigger higher level engagement (average posts per participant and average length of posts in discussions). Whether an initial post holds a clear position has no significant impact on discussion engagement. These findings contribute to a deeper understanding of online deliberation and its engagement and can be useful in promoting engagements in online deliberation.
Hexavalent chromium Cr(VI) is a highly toxic groundwater contaminant. In this study, we demonstrate a selective electrochemical process tailored for removal of Cr(VI) using a hybrid MOF@rGO nanomaterial synthesized by in situ growth of a nanocrystalline, mixed ligand octahedral metal–organic framework with cobalt metal centers, [Co2(btec)(bipy)(DMF)2]n (Co-MOF), on the surface of reduced graphene oxide (rGO). The rGO provides the electric conductivity necessary for an electrode, while the Co-MOF endows highly selective adsorption sites for CrO42–. When used as an anode in the treatment cycles, the MOF@rGO electrode exhibits strong selectivity for adsorption of CrO42– over competing anions including Cl–, SO42–, and As(III) and achieves charge efficiency (CE) >100% due to the strong physisorption of CrO42– by Co-MOF; both electro- and physisorption capacities are regenerated with the reversal of the applied voltage, when highly toxic Cr(VI) is reduced to less toxic reduced Cr species and subsequently released into brine. This approach allows easy regeneration of the nonconducting Co-MOF without any chemical addition while simultaneously transforming Cr(VI), inspiring a novel electrochemical method for highly selective degradation of toxic contaminants using tailor-designed electrodes with high affinity adsorbents.
Interactions between graphene oxide (GO) and cell membranes play a crucial role in the nanotoxicity of GO toward organisms. However, little is known about interactions of GO with lipid membranes in the presence of heavy metals. This study investigated the attachment of GO and adsorption of heavy metals onto simulated cell membranes (spherical supported lipid bilayers, SSLBs) formed by cationic, neutral and anionic lipids, i.e., SSLB(+), SSLB(0) and SSLB(−), using batch experiments, density functional theory (DFT) calculations, and spectroscopic analyses. In the binary systems, the SSLBs bind with GO through hydrogen binding and with heavy metals via complexation. The attachment of GO or adsorption of heavy metals onto SSLBs decreased in the order SSLB(−) > SSLB(0) > SSLB(+), largely controlled by the type and number of functional groups in the SSLBs. Evidence from batch experiments, DFT calculations and spectroscopic analyses confirmed that in the ternary system GO first binds with metals, and then the GO–metal complexes attach to SSLBs via hydrogen bonding through GO rather than cation bridging through metals. Moreover, metal adsorption onto GO strengthens hydrogen bonding by withdrawing electrons from the GO surface. Therefore, in the ternary system, heavy metals promoted the GO attachment to SSLBs. However, GO suppressed the adsorption of heavy metals onto SSLBs by blocking the adsorption sites via steric hindrance. This study highlighted the importance of molecular interactions on assessing the nanotoxicity of GO to cells in the coexistence of heavy metals.
The management of river-lake systems is hindered by limitations in the applicability of existing models that describe the relationship between environmental factors and phytoplankton community characteristics but rarely include common and indirect effects on algae dynamics. In this study, we assumed that the interaction of light, water, temperature, pH, and nutrients, including direct and indirect effects, are the potential factors affecting phytoplankton dynamics. We determined which of these are the main drivers of phytoplankton community structure and production in a river-lake system by using three different models based on the partial least squares structural equation modeling method. Our results indicated that the models achieved more than 60% of the overall explanatory power of various environmental factors on phytoplankton characteristics, including indirect and direct effects. In particular, light, pH, and nutrient content and ratios commonly control phytoplankton dynamic characteristics rather than a single nutrient, but light is the main driving force of phytoplankton community characteristics. Controlling the underwater light conditions, and nitrogen and phosphorus pollution load could effectively regulate algal blooms, increase productivity, promote ecological balance, and reduce water pollution. Our findings provide a scientific and theoretical basis for water resource management and pollution control.
Carboxymethyl cellulose stabilized iron sulfide (CMC-FeS) nanoparticles have been shown promising for reductive immobilization of U(VI) in water and soil. This work aimed to fill some critical knowledge gaps on the effects of the stabilizer and water chemistry, reaction mechanisms, and long-term stability of stabilized uranium. The optimal CMC-to-FeS molar ratio was determined to be 0.0010. CMC-FeS performed effectively over pH 6.0–9.0, with the best removal being at pH 7.0 and 8.0. The retarded first-order model adequately interpreted the kinetic data, representing a mechanistically sounder model for heterogeneous reactants of decaying reactivity. The presence of Ca2+ (1 mM) or bicarbonate (1 mM) lowered the initial rate constant by a factor of 1.6 and 9.5, respectively, while 1 mM of Na+ showed negligible effect. Humic acid at 1.0 mg/L (as total organic carbon) doubled the removal rate, but inhibited the removal at elevated concentrations (≥5.0 mg/L). Fourier transform infrared spectroscopy, X-ray diffractometer, X-ray photoelectron spectroscopy, and extraction studies indicated that reductive conversion of UO22+ to UO2(s) was the primary reaction mechanism, accounting for 90% of U removal at pH 7.0. S2− and S22− were the primary electron sources, whereas sorbed and structural Fe(II) acted as supplementary electron donors. The immobilized U remained stable under anoxic conditions after 180 days of aging, while 26% immobilized U was remobilized when exposed to air for 180 days. The long-term stability is attributed to the protective reduction potential of CMC-FeS, the formation of uraninite and associated structural resistance to oxidation, and the high affinity of FeS oxidation products toward U(VI).
Electrokinetic remediation is an effective technology for soil contaminated with heavy metals. However, little is known about the fate of antibiotic resistance in the process under heavy metal stress, since antibiotic resistance genes (ARGs) are widely distributed and can be co-selected with heavy metals. This study focused on antibiotic resistant bacteria and ARGs over different remediation periods (1, 2, and 5 days), voltages (0.4 and 0.8 V cm−1), and initial concentrations (250–1,000 mg kg−1 for Cu, and 1,000–3,000 mg kg−1 for Zn). The application of polarity-reversal maintained a suitable pH, eliminating possible negative effects on soil quality. In addition to a decrease in total metals, the speciation was modified as residual forms decreased while reactive forms increased. Compared with anti-oxytetracycline bacteria, anti-sulfamethoxazole bacteria were more resistant to the electric field, which might be ascribed to greater constraints on their resistance enzymes. The presence of heavy metals accelerated the spread of ARGs, with a 2.67-fold increase for tetG, and a 3.86-fold increase for sul1. Among the ARGs studied, tetM and tetW, as well as sul genes were more easily removed than tetC and tetG genes. Finally, a significant correlation was found between ARGs and Cu, consistent with the relatively stronger toxicity of Cu and its high potential to induce the SOS response. This study advances the understanding of how electrokinetics influences antibiotic resistance in soil with heavy metals, which has important implications for the simultaneous control of these pollutants in soil.
The decarbonisation of energy provision is key to managing global greenhouse gas emissions and hence mitigating climate change. Digital technologies such as big data, machine learning, and the Internet of Things are receiving more and more attention as they can aid the decarbonisation process while requiring limited investments. The orchestration of these novel technologies, so-called cyber-physical systems (CPS), provides further, synergetic effects that increase efficiency of energy provision and industrial production, thereby optimising economic feasibility and environmental impact. This comprehensive review article assesses the current as well as the potential impact of digital technologies within CPS on the decarbonisation of energy systems. Ad hoc calculation for selected applications of CPS and its subsystems estimates not only the economic impact but also the emission reduction potential. This assessment clearly shows that digitalisation of energy systems using CPS completely alters the marginal abatement cost curve (MACC) and creates novel pathways for the transition to a low-carbon energy system. Moreover, the assessment concludes that when CPS are combined with artificial intelligence (AI), decarbonisation could potentially progress at an unforeseeable pace while introducing unpredictable and potentially existential risks. Therefore, the impact of intelligent CPS on systemic resilience and energy security is discussed and policy recommendations are deducted. The assessment shows that the potential benefits clearly outweigh the latent risks as long as these are managed by policy makers.
Abstract In China, irrigation is widespread in 40.7% cropland to sustain crop yields. By its action on water cycle, irrigation affects water resources, and local climate. In this study, a new irrigation module, including flood and paddy irrigation technologies, was developed in the ORCHIDEE-CROP land surface model which describes crop phenology and growth in order to estimate irrigation demands over China from 1982 to 2014. Three simulations were performed including NI: no irrigation; IR: with irrigation limited by local water resources; and FI: with irrigation demand fulfilled. Observations and census data were used to validate the simulations. Results showed that the estimated irrigation water withdrawal (W) based on IR and FI scenarios bracket statistical W with fair spatial agreements (r = 0.68 ± 0.07; p < 0.01). Improving irrigation efficiency was found to be the dominant factor leading to the observed W decrease. By comparing simulated total water storage (TWS) with GRACE observations, we found that simulated TWS with irrigation well explained the TWS variation over China. However, our simulation overestimated the seasonality of TWS in the Yangtze River Basin due to ignoring regulation of artificial reservoirs. The observed TWS decrease in the Yellow River Basin caused by groundwater depletion was not totally captured in our simulation, but it can be inferred by combining simulated TWS with census data. Moreover, we demonstrated that land use change tended to drive W locally, but had little effect on total W over China due to water resources limitation.