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Due to the outbreak of COVID-19, a large number of disposable personal protective equipment (PPE) wastes were generated. It has caused great harm to the ecological environment, and even in the future may endanger human health. Therefore, it is of great significance to research biodegradable materials that can be used in the field of medical protective equipment. This article reviews the application of biodegradable materials in personal protective equipment. First of all, the classification, characteristics, and general application of biodegradable materials are described. Then, the application of biodegradable antibacterial materials, which can improve the degradability, antibacterial, and comfort of medical protective articles, is analyzed. Finally, the significance and challenges are discussed, and some prospects in this field are put forward.

This data package includes the two 1-km resolution global maps of tropical mangrove forests between ~31°N and 39°S produced from the study: 1) investible mangrove blue carbon (in tCO2e ha-1y-1) and 2) profitable mangrove blue carbon (in tCO2e ha-1y-1). It also includes a sample R script to reproduce these layers and the relative country-level project development and maintenance cost estimates. Investible mangrove blue carbon: To model and produce a spatially explicit map of investible mangrove blue carbon, we first estimated the total volume of CO2e across three pools in mangrove forest areas—aboveground carbon, belowground carbon and soil organic carbon: Aboveground carbon: We used a recent global mangrove aboveground biomass model by Simard et al. 2019 to estimate the volume of aboveground carbon. We applied a stoichiometric factor of 0.475 to convert biomass estimates to carbon stock values. We also performed an uncertainty analyses to account for variability in this stoichiometric factor. We then used a conversion factor of 3.67 to convert carbon stock values to CO2e volume. Belowground carbon: We then used the aboveground biomass from Simard et al. 2019to estimate the belowground (root) biomass, following the allometric equation from Hutchison et al. 2014: Belowground biomass = 0.073 •Aboveground biomass1.32. Our belowground biomass estimations fall within the range of previously derived ratios of aboveground:belowground (root) biomass ratios. We applied the same stoichiometric factor (0.475) and conversion factor (3.67) to estimate the volume of CO2e associated with belowground biomass. Soil organic carbon: Additionally, to fully consider ecosystem mangrove carbon stock, we also utilized mangrove soil carbon stocks obtained from Sanderman et al. 2018, applying a conversion factor (3.67) to estimate the volume of CO2e. To these biomass carbon estimates, we then applied key criteria that enables certification of carbon credits under the rules of the UNFCCC, Kyoto Protocol, and the various voluntary certification standards such as the Verified Carbon Standard (VCS). Importantly, our analyses were guided by the requirements stipulated by VCS—the most widely used voluntary greenhouse gas program globally: Additionality: A major component of certification is ‘additionality’ or the amount of carbon stocks that would have been lost without the intervention of forest protection of the proposed project. To estimate additionality, we assume future rates of mangrove forest loss to follow existing patterns between the years 2000–2016. This data was obtained from Goldberg et al. 2020. This was calculated as the annualized rate of mangrove loss within each ~1 km cell. We then applied this estimated annual deforestation rate to the volume of CO2e associated with mangrove forest (calculated above), to derive the volume of CO2e that would be certifiable and thus investible under the VCS. Decay rates: We also considered the annual decay rate specific to mangrove forests [29]. This was based on two carbon pools—the belowground (root) biomass, with a decay rate of 0.20, and soil organic carbon, with a decay rate of 0.10. These values are based on median estimates from Lovelock et al. 2017, and we also performed an uncertainty analyses to account for variability in these decay rates. Buffer credits: Lastly, we also applied the VCS requirement to set aside buffer credits of 20% net change carbon stocks in each area to account for risk of non-permanence. Profitable mangrove blue carbon: To estimate the relative profitability of these mangrove blue carbon sites, we utilized the map of investible mangrove blue carbon to calculate the net present values (NPV) based on several simplifying assumptions obtained from previous studies’ published data. We first used the cost of project establishment at US$232 ha-1, based on a wide range of costs that are key to the development of a project such as project design, governance and planning, and enforcement. We also used an annual maintenance cost of US$25 ha-1, which can include aspects such as monitoring, finance and administration. Given the potential for establishment and maintenance cost to vary between countries, then weighted this cost by countries’ per capita gross domestic product (GDP) to estimate the relative cost per country. We then assumed a constant carbon price of US$5 t-1CO2e for the first five years, roughly matching the average carbon price of all avoided deforestation projects recorded by Forest Trends’ Ecosystem Marketplace reports between 2006–2018. After the first five years, we assumed a 5% price appreciation for subsequent years over a 30-years project timeframe. Based on these criteria, we calculated the NPV as well as the accumulated profits over the next 30 years, based on a 10% risk-adjusted discount rate. Using the spatially explicit NPV estimates, we excluded areas that were not financially sustainable (negative NPV), and calculated the extent, climate mitigation potential and return-on-investment within the remaining, profitable, areas.. Further details for these datasets are presented in Zeng et. al. For questions or issues on the spatial data layers, please contact Yiwen Zeng (zengyiwen@nus.edu.sg).&nbsp

Some novel 4,4'-bis(2,4-pyrimidinyl)-diamino stilbene-2,2'-disulfonic acid derivatives 4a-d were designed and synthesized. Their structures were confirmed by proton nuclear magnetic resonance, elemental analysis and ultraviolet absorption spectra. All newly synthesized compounds were interrogated on their whitening effect on cotton fiber as fluorescent whitening agents. Their optical properties were evaluated by the degree of whiteness, color index, light fastness, wet rubbing fastness and dry rubbing fastness. The results indicated that compounds 4a-d showed an obvious whitening effect on cotton fiber and higher fastness than that of C186. The reflectivity of cotton fiber treated with compounds 4a-d at the critical concentration was up to 120.76%. In contrast, the reflectivity of untreated cotton fiber was only 87.23%. The ultraviolet absorption properties of compound 4d were tested under diverse pH values. The results showed that the ultraviolet absorption intensity of compound 4d decreased significantly and the absorption curve had blue shift under acidic conditions. Compound 4d was found to be the most effective molecule as a fluorescent whitening agent with a higher degree of whiteness (CIE Whiteness 135.04) compared to untreated cotton fiber (CIE Whiteness 73.02) at the critical concentration (0.1%).

Four novel stilbene-twelve alkyl quaternary ammonium salts 5a–d were synthesized. All synthesized compounds were characterized by FT-IR, 1H-NMR and elemental analysis. Compounds 5a–d showed efficient whitening effect on cotton fiber and high fastness. Furthermore, compound 5c showed better stability to light than C186 in aqueous solution. The preliminary biological experiment demonstrated compounds 5a–d possessed significant antibacterial activities. Among them, compound 5d turned out to be the most active compound against Candida albicans with MIC50 4 μg/mL as well as E. coli with MIC50 16 μg/mL.

Weyl, Olaf/0000-0002-8935-3296; Perdikaris, Costas/0000-0002-5417-6242; Simonovic, Predrag/0000-0002-4819-4962; Leuven, Rob/0000-0001-5434-6005; Ribeiro, Filipe Manuel Vidas/0000-0003-3531-5072; Verreycken, Hugo/0000-0003-2060-7005; Magalhaes, Maria Filomena/0000-0001-7308-2279; Tarkan, Ali Serhan/0000-0001-8628-0514; Vilizzi, Lorenzo/0000-0001-8103-885X; Koutsikos, Nicholas/0000-0003-0680-4504; Piria, Marina/0000-0001-6324-9282 WOS: 000479264500002 The freshwater Fish Invasiveness Screening Kit (FISK) has been applied in 35 risk assessment areas in 45 countries across the six inhabited continents (11 applications using FISK v1; 25 using FISK v2). The present study aimed: to assess the breadth of FISK applications and the confidence (certainty) levels associated with the decision-support tool's 49 questions and its ability to distinguish between taxa of low-to-medium and high risk of becoming invasive, and thus provide climate-specific, generalised, calibrated thresholds for risk level categorisation; and to identify the most potentially invasive freshwater fish species on a global level. The 1973 risk assessments were carried out by 70 + experts on 372 taxa (47 of the 51 species listed as invasive in the Global Invasive Species Database ), which in decreasing order of importance belonged to the taxonomic Orders Cypriniformes, Perciformes, Siluriformes, Characiformes, Salmoniformes, Cyprinodontiformes, with the remaining approximate to 8% of taxa distributed across an additional 13 orders. The most widely-screened species (in decreasing importance) were: grass carp Ctenopharyngodon idella, common carp Cyprinus carpio, rainbow trout Oncorhynchus mykiss, silver carp Hypophthalmichthys molitrix and topmouth gudgeon Pseudorasbora parva. Nine 'globally' high risk species were identified: common carp, black bullhead Ameiurus melas, round goby Neogobius melanostomus, Chinese (Amur) sleeper Perccottus glenii, brown bullhead Ameiurus nebulosus, eastern mosquitofish Gambusia holbrooki, largemouth (black) bass Micropterus salmoides, pumpkinseed Lepomis gibbosus and pikeperch Sander lucioperca. The relevance of this global review to policy, legislation, and risk assessment and management procedures is discussed. UK Department of Environment, Food Rural AffairsDepartment for Environment, Food & Rural Affairs (DEFRA); Belarus Republican Foundation for Fundamental Research; Bolyai Janos Fellowship of the Hungarian Academy of Sciences; NRF Professional Development Programme [1010140]; Commission for Knowledge and Use of Biodiversity (CONABIO), Mexico; Croatian Science Foundation [IP-06-2016]; University of Zagreb [1-28-121]; FRISK Project (FCT) [PTDC/AAG-MAA/0350/2014]; strategic plan of MARE (Marine and Environmental Sciences Centre) [UID/MAR/04292/2013]; Ministry of Education, Science and Technological Development of Serbia [OI173025]; National Research Foundation-South African Research Chairs Initiative of the Department of Science and Technology [110507]; Cefas Support for participation was provided to: GHC by Cefas and the UK Department of Environment, Food & Rural Affairs; BA by the Belarus Republican Foundation for Fundamental Research; AF by a Bolyai Janos Fellowship of the Hungarian Academy of Sciences; SMMby the NRF Professional Development Programme (Grant No. 1010140); RM by the Commission for Knowledge and Use of Biodiversity (CONABIO), Mexico; MP by grants from the Croatian Science Foundation (IP-06-2016) and the University of Zagreb (1-28-121); FR by FRISK Project (FCT Ref. PTDC/AAG-MAA/0350/2014) and by the strategic plan of MARE (Marine and Environmental Sciences Centre: UID/MAR/04292/2013); PS by grants from the Ministry of Education, Science and Technological Development of Serbia (OI173025) and the Croatian Science Foundation (IP-06-2016); OLFW by the National Research Foundation-South African Research Chairs Initiative of the Department of Science and Technology (Grant No. 110507).