Spatial and diel variations of bacterioplankton and pico-nanoeukaryote communities and potential biotic interactions during macroalgal blooms.

We investigated spatial heterogeneity and diel variations in bacterioplankton and pico-nanoeukaryote communities, and potential biotic interactions at the extinction stage of the Ulva prolifera bloom in the Jiaozhou Bay, Yellow Sea. It was found that the presence of Ulva canopies significantly promoted the cell abundance of heterotrophic bacteria, raised evenness, and altered the community structure of bacterioplankton. A diel pattern was solely significant for pico-nanoeukaryote community structure. >50 % of variation in the heterotrophic bacterial abundance was accounted for by the ratio of Bacteroidota to Firmicutes, and dissolved organic nitrogen effectively explained the variations in cell abundances of phytoplankton populations. The factors representing biotic interactions frequently contributed substantially more than environmental factors in explaining the variations in diversity and community structure of both bacterioplankton and pico-nanoeukaryotes. There were higher proportions of eukaryotic pathogens compared to other marine systems, suggesting a higher ecological risk associated with the Ulva blooms.

The Application of Machine Learning: Controlling the Preparation of Environmental Materials and Carbon Neutrality.

The greenhouse effect is a severe global problem [...].

Response of the Intertidal Microbial Community Structure and Metabolic Profiles to Zinc Oxide Nanoparticle Exposure.

The toxicity of nanomaterials to microorganisms is related to their dose and environmental factors. The aim of this study was to investigate the shifts in the microbial community structure and metabolic profiles and to evaluate the environmental factors in a laboratory scale intertidal wetland system exposed to zinc oxide nanoparticles (ZnO NPs). Microbial assemblages were determined using 16S rRNA high-throughput sequencing. Community-level physiological profiles were determined using Biolog-ECO technology. Results showed Proteobacteria was the predominant (42.6%-55.8%) phylum across all the sediments, followed by Bacteroidetes (18.9%-29.0%). The genera Azoarcus, Maribacter, and Thauera were most frequently detected. At the studied concentrations (40 mg·L-1, 80 mg·L-1, 120 mg·L-1), ZnO NPs had obvious impacts on the activity of Proteobacteria. Adverse effects were particularly evident in sulfur and nitrogen cycling bacteria such as Sulfitobacter, unidentified_Nitrospiraceae, Thauera, and Azoarcus. The alpha diversity index of microbial community did not reflect stronger biological toxicity in the groups with high NP concentrations (80 mg·L-1, 120 mg·L-1) than the group with low NP concentration (40 mg·L-1). The average well color development (AWCD) values of periodically submersed groups were higher than those of long-term submersed groups. The group with NP concentration (40 mg·L-1) had the lowest AWCD value; those of the groups with high NP concentrations (80 mg·L-1, 120 mg·L-1) were slightly lower than that of the control group. The beta diversity showed that tidal activity shaped the similar microbial community among the periodically submerged groups, as well as the long-term submerged groups. The groups with high DO concentrations had higher diversity of the microbial community, better metabolic ability, and stronger resistance to ZnO NPs than the groups with a low DO concentration.

A field study of the relationship between sulfide-bound metals and bioaccumulation by Limnodrilus sp. in a heavily polluted river.

Acid volatile sulfide (AVS) has been regarded as an important factor controlling metal bioavailability in anoxic sediments, but its effect on metal accumulation under natural conditions is poorly understood. Here, a field study of the influence of AVS on metal accumulation by Limnodrilus sp. in a heavily polluted river is provided. Most of the study area was subject to anaerobic and strongly reducing conditions, and the concentration of trace metals in surface sediments was high, as were the concentration of AVS and simultaneously extracted metals (SEM; average AVS = 20.3 µmol g(-1), average ∑SEM5 = 9.42 µmol g(-1); ∑SEM5 refers to the sum of SEMCd, SEMCu, SEMPb, SEMNi, and SEMZn). Only a few species and small quantities of benthic invertebrates were found, and Limnodrilus sp. was dominant. There was no correlation between trace metal accumulation and (SEM-AVS), and in stations where (SEM-AVS) <0, the absolute value of bioaccumulation was high (average ∑BIO5 = 4.07 µmol g(-1); ∑BIO5 refers to the sum of BIOCd, BIOCu, BIOPb, BIONi, and BIOZn), indicating that there was no relationship between (SEM-AVS) and metal accumulation in Limnodrilus sp. This was likely because Limnodrilus sp. ingest sediment particles as their main food source, so pore water metals play a minor role in their bioaccumulation (BIO) of materials. However, ∑BIO5 was significantly correlated with ∑SEM5 (r = 0.795, p < 0.01), revealing that the large number of sulfide-bound metals (SEM) in sediments may play an important role in metal accumulation in Limnodrilus sp., which can assimilate sulfide-associated metals by the help of the digestive fluids in the digestive systems.

Greenhouse gas emissions accounting of urban residential consumption: a household survey based approach.

Devising policies for a low carbon city requires a careful understanding of the characteristics of urban residential lifestyle and consumption. The production-based accounting approach based on top-down statistical data has a limited ability to reflect the total greenhouse gas (GHG) emissions from residential consumption. In this paper, we present a survey-based GHG emissions accounting methodology for urban residential consumption, and apply it in Xiamen City, a rapidly urbanizing coastal city in southeast China. Based on this, the main influencing factors determining residential GHG emissions at the household and community scale are identified, and the typical profiles of low, medium and high GHG emission households and communities are identified. Up to 70% of household GHG emissions are from regional and national activities that support household consumption including the supply of energy and building materials, while 17% are from urban level basic services and supplies such as sewage treatment and solid waste management, and only 13% are direct emissions from household consumption. Housing area and household size are the two main factors determining GHG emissions from residential consumption at the household scale, while average housing area and building height were the main factors at the community scale. Our results show a large disparity in GHG emissions profiles among different households, with high GHG emissions households emitting about five times more than low GHG emissions households. Emissions from high GHG emissions communities are about twice as high as from low GHG emissions communities. Our findings can contribute to better tailored and targeted policies aimed at reducing household GHG emissions, and developing low GHG emissions residential communities in China.