Nitric oxide removal by wastewater bacteria in a biotrickling filter

Nitric oxide(NO) is one of the most important air pollutants in atmosphere mainly emitted from combustion source. A biotrickling filter was designed and operated to remove NO from an air stream using bacteria extracted from the sewage sludge of a municipal sewage treatment plant. To obtain the best operation conditions for the biotrickling filter, orthogonal experiments(L9(34)) were designed. Inlet oxygen concentration was found to be the most significant factor of the biotrickling filter and has a significant negative effect on the system. The optimal conditions of the biotrickling filter occurred at a temperature of 40℃, a pH of 8.0 and a chemical oxygen demand of 165 mg/L in the recycled water with no oxygen in the system. The bacteria sample was detected by DNA sequencing technology and showed 93%–98% similarity to Pseudomonas mendocina. Moreover, a full gene sequencing results indicated the bacterium was a brand new strain and named as P. mendocina DLHK. This strain can transfer nitrate to organic nitrogen. The result suggested the assimilation nitrogen process in this system. Through the isotope experimental analysis, two intermediate products(15NO and 15N2O) were found. The results indicated the denitrification function and capability of the biotrickling filter in removing NO.     

Total cobalt determination in human blood and synovial fluid using inductively coupled plasma-mass spectrometry: method validation and evaluation of performance variables affecting metal hip implant patient samples

Inductively coupled plasma with mass spectrometric detection (ICP-MS) has been used for clinical analysis of cobalt (Co) due to its sensitivity and specificity; however, media-specific validation studies are lacking. This study provides data on performance variables affecting differences between selected analytical platforms (Perkin Elmer and Agilent), tissue sample preparation, storage, and interferences affecting measurements in whole blood, serum, and synovial fluid. The limits of detection (LOD) range from 0.2–0.5 µg/L in serum and synovial fluid, and 0.6–1.7 µg Co/L in whole blood. The Agilent platform with collision reaction cell is more sensitive, while the Perkin Elmer platform with dynamic reaction cell demonstrates more polyatomic interferences near the LOD for serum and whole blood. Split sample analysis showed good accuracy, precision, and reproducibility between serum Co measurements using acid digestion or detergent dilution preparations for persons with metal hip implants or following supplement intake. The results demonstrated reliability of the ICP-MS methodology across the two analytical platforms and between two commercial laboratories for Co concentrations above 5 µg Co/L, but digestion procedures and polyatomic interferences may affect measurements in some media at lower concentrations. These studies validate the described ICP-MS methodology for clinical purposes with precautions at low cobalt concentrations (<5 µg Co/L).     

A conceptual model of the social–ecological system of nature-based solutions in urban environments

This article provides a perspective on nature-based solutions. First, the argument is developed that nature-based solutions integrate social and ecological systems. Then, theoretical considerations relating to relational values, multifunctionality, transdisciplinarity, and polycentric governance are briefly outlined. Finally, a conceptual model of the social–ecological system of nature-based solutions is synthesised and presented. This conceptual model comprehensively defines the social and ecological external and internal systems that make up nature-based solutions, and identifies theoretical considerations that need to be addressed at different stages of their planning and implementation The model bridges the normative gaps of existing nature-based solution frameworks and could be used for consistent, comprehensive, and transferable comparisons internationally. The theoretical considerations addressed in this article inform practitioners, policymakers, and researchers about the essential components of nature-based solutions. The conceptual model can facilitate the identification of social and ecological interconnections within nature-based solutions and the range of stakeholders and disciplines involved.     

Genetic diversity affects colony survivorship in commercial honey bee colonies

Honey bee (Apis mellifera) queens mate with unusually high numbers of males (average of approximately 12 drones), although there is much variation among queens. One main consequence of such extreme polyandry is an increased diversity of worker genotypes within a colony, which has been shown empirically to confer significant adaptive advantages that result in higher colony productivity and survival. Moreover, honey bees are the primary insect pollinators used in modern commercial production agriculture, and their populations have been in decline worldwide. Here, we compare the mating frequencies of queens, and therefore, intracolony genetic diversity, in three commercial beekeeping operations to determine how they correlate with various measures of colony health and productivity, particularly the likelihood of queen supersedure and colony survival in functional, intensively managed beehives. We found the average effective paternity frequency (m _e ) of this population of honey bee queens to be 13.6?±?6.76, which was not significantly different between colonies that superseded their queen and those that did not. However, colonies that were less genetically diverse (headed by queens with m _e ?≤?7.0) were 2.86 times more likely to die by the end of the study when compared to colonies that were more genetically diverse (headed by queens with m _e ?>?7.0). The stark contrast in colony survival based on increased genetic diversity suggests that there are important tangible benefits of increased queen mating number in managed honey bees, although the exact mechanism(s) that govern these benefits have not been fully elucidated.     

Estimating home energy decision parameters for a hybrid energy—economy policy model

Hybrid energy–economy models combine the advantages of a technologically explicit bottom–up model with the behavioral realism sought after by top–down models in order to help policymakers assess the likely technology-specific response and economy-wide impact of policies to induce technological change. We use a discrete choice survey to estimate key technology choice parameters for a hybrid model. Two choice experiments are conducted for household energy-related decisions about retrofitting home building structures and choosing a space heating and conditioning system. Based on a discrete choice survey of 625 householders, we estimate a discrete choice model and then demonstrate how its parameters translate into the behavioral parameters of a hybrid model. We then simulate household energy policies, including, individual subsidies and increased regulations.