Warnerwilkinson5733

The greatest reduction in environmental impacts were achieved with the scenarios using CHO cell metabolism instead of C2C12 cell metabolisim (64-67 % reduction); achieving 128 % cell biomass increase during differentiation instead of no increase (42-56 % reduction); using wind electricity instead of average UK electricity (6-39 % reduction); and adjusting the amino acid use based on experimental data (16-27 % reduction). The use of chemical wastewater treatment instead of heat treatment increased all environmental impacts, except energy demand, by 1-16 %. This study provides valuable insights for the cultured meat field to understand the effects of different process design scenarios on environmental impacts, and therefore provides a framework for deciding where to focus development efforts for improving the environmental performance of the production system.Quantifying flood hazards by employing hydraulic/hydrodynamic models for flood risk mapping is a widely implemented non-structural flood management strategy. However, the unavailability of multi-domain and multi-dimensional input data and expensive computational resources limit its application in resource-constrained regions. The fifth and sixth IPCC assessment reports recommend including vulnerability and exposure components along with hazards for capturing risk on human-environment systems from natural and anthropogenic sources. In this context, the present study showcases a novel flood risk mapping approach that considers a combination of geomorphic flood descriptor (GFD)-based flood susceptibility and often neglected socio-economic vulnerability components. Three popular Machine Learning (ML) models, namely Decision Tree (DT), Random Forest (RF), and Gradient-boosted Decision Trees (GBDT), are evaluated for their abilities to combine digital terrain model-derived GFDs for quantifying flood susceptibility very high flood risk. The proposed novel framework is generic and can be used to derive a wide variety of flood susceptibility, vulnerability, and subsequently risk maps under a data-constrained scenario. Furthermore, since this approach is relatively data and computationally parsimonious, it can be easily implemented over large regions. The exhaustive flood maps will facilitate effective flood control and floodplain planning.Animal farms are known reservoirs for environmental antimicrobial resistance (AMR). However, knowledge of AMR burden in the air around animal farms remains disproportionately limited. In this study, we characterized the airborne AMR based on the quantitative information of 30 antimicrobial resistance genes (ARGs), four mobile genetic elements (MGEs), and four human pathogenic bacteria (HPBs) involving four animal species from 20 farms. By comparing these genes with those in animal feces, the distinguishing features of airborne AMR were revealed, which included high enrichment of ARGs and their potential mobility to host HPBs. We found that depending on the antimicrobial class, the mean concentration of airborne ARGs in the animal farms ranged from 102 to 104 copies/m3 and was accompanied by a considerable intensity of MGEs and HPBs (approximately 103 copies/m3). Although significant correlations were observed between the ARGs and bacterial communities of air and fecal samples, the abundance of target genes was generally high in fine inhalable particles (PM2.5), with an enrichment ratio of up to 102 in swine and cattle farms. The potential transferability of airborne ARGs was universally strengthened, embodied by a pronounced co-occurrence of ARGs-MGEs in air compared with that in feces. Exposure analysis showed that animal farmworkers may inhale approximately 104 copies of human pathogenic bacteria-associated genera per day potentially carrying highly transferable ARGs, including multidrug resistant Staphylococcus aureus. Moreover, PM2.5 inhalation posed higher human daily intake burdens of some ARGs than those associated with drinking water intake. Overall, our findings highlight the severity of animal-related airborne AMR and the subsequent inhalation exposure, thus improving our understanding of the airborne flow of AMR genes from animals to humans. These findings could help develop strategies to mitigate the human exposure and dissemination of ARGs across different media.Vermiremediation, which use earthworms to remove contaminants from soil, has been proven to be an alternative, low-cost technology. However, the effects of earthworm activity, especially the degraders in earthworm intestines, on the fate of sulfamethoxazole (SMX), and the effects of intestinal bacteria on degrading bacteria in soil are unclear. In this study, the effects of earthworms on the fate of SMX and related antibiotic resistance genes (ARGs) were investigated. Special attention was paid to the impact of earthworms on SMX degradation efficiency, degradation products, related ARGs, and degraders in both soil and earthworm intestines; the effect of intestinal bacteria on soil bacteria associated with SMX was also studied. Earthworms significantly accelerated SMX degradation by both intestinal detoxification and the stimulation of indigenous soil bacteria. Compared with the treatment without earthworms, the treatment with earthworms reduced SMX residues by 25.1 %, 49.2 %, 35.7 %, 34.2 %, and 35.7 % on the 10th, 20th, 30th, 60th, and 90th days, respectively. Compared with those in soil (treated with earthworms), the SMX residues in wormcasts were further reduced by 12.2-29.0 % from the 2nd to the 20th day, producing some unique anaerobic degradation products that were distinct from those in the soil. In earthworm intestines, SMX degradation was enhanced by bacteria of the genera Microvirga, Sphingomonas, Methylobacterium, Bacillus, and Tumebacillus. All of these bacteria (except Bacillus spp.) entered and colonised the soil with wormcasts, further promoting SMX degradation. Additionally, earthworms removed a significant number of ARGs by increasing the fraction of potential SMX degraders and inhibiting the potential hosts of ARGs and int1. This study demonstrated that earthworms could remediate SMX-contaminated soil by enhancing the removal of SMX and ARGs.Ongoing climate warming is increasing evapotranspiration, a process that reduces plant-available water and aggravates the impact of extreme droughts during the growing season. Such an exceptional hot drought occurred in Central Europe in 2018 and caused widespread defoliation in mid-summer in European beech (Fagus sylvatica L.) forests. Here, we recorded crown damage in 2021 in nine mature even-aged beech-dominated stands in northwestern Switzerland along a crown damage severity gradient (low, medium, high) and analyzed tree-ring widths of 21 mature trees per stand. We aimed at identifying predisposing factors responsible for differences in crown damage across and within stands such as tree growth characteristics (average growth rates and year-to-year variability) and site-level variables (mean canopy height, soil properties). We found that stand-level crown damage severity was strongly related to soil water availability, inferred from tree canopy height and plant available soil water storage capacity (AWC). Trees were shorter in drier stands, had higher year-to-year variability in radial growth, and showed higher growth sensitivity to moisture conditions of previous late summer than trees growing on soils with sufficient AWC, indicating that radial growth in these forests is principally limited by soil water availability. Within-stand variation of post-drought crown damage corresponded to growth rate and tree size (diameter at breast height, DBH), i.e., smaller and slower-growing trees that face more competition, were associated with increased crown damage after the 2018 drought. These findings point to tree vigor before the extreme 2018 drought (long-term relative growth rate) as an important driver of damage severity within and across stands. Our results suggest that European beech is less likely to be able to cope with future climate change-induced extreme droughts on shallow soils with limited water retention capacity.The objective of this study was to evaluate the impact of turbidity, precipitation, land use, and five-week variation on nutrient levels and atrazine concentrations across Illinois state. To acquire the greatest number of samples in a cost and time-sensitive manner, data were collected by citizen scientists. Volunteers collected data regarding five water quality metrics nitrites, nitrates, phosphates, atrazine, and turbidity once per week from April 19 until May 17, 2017. A subset (24 %) of volunteers also collected turbidity measurements. Data regarding precipitation was obtained from the Community Collaborative Rain, Hail and Snow Network (CoCoRaHS), a long-standing grassroots volunteer network of backyard weather observers. Three ordinal regression analyses were performed one without a blocking effect, a second with week as a blocking effect, and a third with watershed as a blocking effect. In all cases, turbidity was significantly associated with elevated levels of nitrate (Pseudo R2-0.48 to 0.94) and phos.Soon after its emergence, COVID-19 became a global problem. While different types of vaccines and treatments are now available, still non-pharmacological policies play a critical role in managing the pandemic. The literature is enriched enough to provide comprehensive, practical, and scientific insights to better deal with the pandemic. This research aims to find out how the built environment and human factors have affected the transmission of COVID-19 on different scales, including country, state, county, city, and urban district. This is done through a systematic literature review of papers indexed on the Web of Science and Scopus. Initially, these databases returned 4264 papers, and after different stages of screening, we found 166 relevant papers and reviewed them. The empirical papers that had at least one case study and analyzed the effects of at least one built environment factor on the spread of COVID-19 were selected. Results showed that the driving forces can be divided into seven main categories density, land use, transportation and mobility, housing conditions, demographic factors, socio-economic factors, and health-related factors. see more We found that among other things, overcrowding, public transport use, proximity to public spaces, the share of health and services workers, levels of poverty, and the share of minorities and vulnerable populations are major predictors of the spread of the pandemic. As the most studied factor, density was associated with mixed results on different scales, but about 58 % of the papers reported that it is linked with a higher number of cases. This study provides insights for policymakers and academics to better understand the dynamic roles of the non-pharmacological driving forces of COVID-19 at different levels.Subsurface phosphorus (P) loss from deep P stocks in floodplain subsoils can contribute to eutrophication of freshwaters. To date, knowledge on the complex biogeochemical interactions of P in floodplain subsoils is too scarce to enable targeted P management to mitigate subsurface P loss from deep P stocks. We propose using graph theory and the Soilscape Network Approach (SNAp) based on correlations between P-relevant elements to study these complex biogeochemical interactions in the soilscape. Complex interactions of several elements in soils are difficult to investigate from a holistic perspective with conventional data analysis. We translated soil element data from topsoils and subsoils of terrestrial sites, proximal and distal floodplain sites into relational data and analyzed network structure, centrality, and modularity. The results indicate that a higher frequency of groundwater level fluctuations in distal subsoils and proximal topsoils could result in 24-44 % less biogeochemical interaction compared to sites with stable conditions.