Development,larvicide activity,and toxicity in nontarget species of the Croton linearis Jacq essential oil nanoemulsion

Environmental Science and Pollution Research - In this study, the essential oil (EO) from leaves of Croton linearis Jacq was extracted and characterized by GC/MS. The EO hydrophilic-lipophilic...     

Life-cycle greenhouse gas emissions and economic analysis of alternative treatments of solid waste from city markets in Vietnam

We utilize life cycle assessment to trace conversion of degradable organic carbon (DOC) contained in organic waste from city markets in Da Nang, Vietnam. Our methodology makes explicit the process of conversion of DOC under aerobic and anaerobic conditions, as well as the balance of nutrients. Greenhouse gas emissions were calculated for six alternative scenarios: (i) anaerobic landfilling (current situation); (ii) semi-aerobic landfilling; (iii) landfill gas capture; (iv) composting; (v) pre-composting before landfill; and (vi) biogas production. We calculate that 1 t of waste in anaerobic landfilling emits 1.70 t CO₂-eq. with life-cycle perspective. Lowest emission occurs in biogas scenario with 0.26 t CO₂-eq./t. Composting occupies an intermediate position with 0.39 t CO₂-eq./t. Likewise, we estimate that cost of emission reduction in solid waste sector of Vietnam is 15.13 US$/t CO₂-eq., given by alternative of composting and taking anaerobic landfilling as reference. On the other hand, if social cost of carbon (SCC) is incorporated lowest cost to treat 1 t of waste is given by composting and semi-aerobic landfilling at discount rate of 5 %. However, using lower discount rates, and consequently higher values of SCC, composting and biogas production become the alternatives with lowest treatment costs.     

Modelling plant species richness using functional groups

Conservation biologists increasingly rely on spatial predictive models of biodiversity to support decision-making. Therefore, highly accurate and ecologically meaningful models are required at relatively broad spatial scales. While statistical techniques have been optimized to improve model accuracy, less focus has been given to the question: How does the autecology of a single species affect model quality? We compare a direct modelling approach versus a cumulative modelling approach for predicting plant species richness, where the latter gives more weight to the ecology of functional species groups. In the direct modelling approach, species richness is predicted by a single model calibrated for all species. In the cumulative modelling approach, the species were partitioned into functional groups, with each group calibrated separately and species richness of each group was cumulated to predict total species richness. We hypothesized that model accuracy depends on the ecology of individual species and that the cumulative modelling approach would predict species richness more accurately. The predictors explained plant species richness by ca. 25%. However, depending on the functional group the deviance explained varied from 3 to 67%. While both modelling approaches performed equally well, the models of the different functional groups highly varied in their quality and their spatial richness pattern. This variability helps to improve our understanding on how plant functional groups respond to ecological gradients.