Contribution Of Multiple Sources Research Articles

Microplastics in the Surface Sediment of the main Red River Estuary

Microplastics (< 5mm) are one emerging pollutant in the environment. These are the threats and challenges facing the global environment, economy, and society, especially in hotspot regions such as Asia. This paper presents the microplastic characteristics found in the surface sediment of the main Red River estuary (the Ba Lat) during four separate monitoring runs in 2020. The microplastic amount in the sediment samples varied from 800 items per kg of dried weight (dw) to 3,817 items.kg-1 dw, averaging 2,188 ± 1,499 items.kg-1 dw. Fiber and fragment microplastics were discovered to be primary shapes, of which fibers dominated (94%). Microplastic fiber sizes were found mainly in the < 500 µm (69%) range. The most primarily observed colors of microplastics were blue (36%), white (21%), and red (11%). There were five recognized polymer types (polypropylene (PP), polyethylene (PE), polyurethane (PU), polyamide (PA), and polystyrene (PS)) in the sediment samples, with PE and PP predominating. Seasonal fluctuations in microplastic concentrations at the Ba Lat site, a significant aquaculture zone, may indicate the contribution of multiple sources. Our research demonstrated the necessity of microplastic observation in organisms, particularly in the aquaculture zones in Vietnam. Our findings further underline the importance of managing and minimizing the amount of plastic garbage that enters the ecosystem.

Source appointment of nitrogen in PM2.5 based on bulk δ15N signatures and a Bayesian isotope mixing model

Nitrogen isotope (δ15N) has been employed to differentiate major sources of atmospheric N. However, it remains a challenge to quantify contributions of multiple sources based on δ15N values of the N mixture in atmospheric samples. This study measured δ15N of bulk N in PM2.5 at an urban site of Beijing during a severe haze episode of 22–30 January 2013 and a background site of Qinghai, north-western China from 6 September to 15 October 2013, then applied a Bayesian isotope mixing model (SIAR, Stable Isotope Analysis in R) to analyse the N sources. At Beijing site, δ15N values of PM2.5 (−4.1‰ to +13.5‰, +2.8 ± 6.4‰) were distributed within the range of major anthropogenic sources (including NH3 and NO2 from coal combustion, vehicle exhausts and domestic wastes/sewage). At Menyuan site, δ15N values of PM2.5 (+8.0‰ to +27.9‰, +18.5 ± 5.8‰) were significantly higher than that of potential sources (including NH3 and NO2 from biomass burning, animal wastes, soil N cycle, fertilizer application and dust N). High molar ratios of to and/or in PM2.5 at the background site suggested that the equilibrium of NH3 ↔ caused apparent 15N enrichments in ammonium. Results of the SIAR model showed that 39 and 32% of bulk N in PM2.5 of Beijing site were contributed from N emissions of coal combustion and vehicle exhausts, respectively, whereas N in PM2.5 at Menyuan site was derived mainly from N emissions of biomass burning (46%) and NH3 volatilization (34%). These results revealed that the stoichiometry between NH3 and acidic gases plays an important role in controlling the bulk δ15N signatures of PM2.5 and emissions of reactive N from coal combustion and urban transportation should be strictly controlled to advert the risk of haze episodes in Beijing.

Knowledge behaviour and social adoption of innovation

A key element in the adoption of innovation is addressing the knowledge gap caused by its introduction in practice. This study examines the context in which information is searched, found and retrieved, reviewing previous related research work, especially in the area of cognitive information retrieval. As result of an extensive review of research literature on the adoption of online learning design systems in education and on information behaviour, the study proposes a social adoption of innovation model, which includes information systems and social networks, and features innovators and adopters of innovation that influence each other and participate simultaneously in the process of knowledge generation. The study also proposes two symbolic equations for general knowledge behaviour and general information seeking skills that reflect the contribution of multiple sources of information and the type of skills that are needed as part of the overall knowledge behaviour.

Grading Between the Lines: What Really Impacts Professors’ Holistic Evaluation of ESL Graduate Student Writing?

This study examines score variations and differences in the reliability of ratings between English-as-a-second-language (ESL) and native English (NE) authored papers in a graduate course. Generalizability (G-) theory was used as a framework for analysis because it is powerful in detecting rater variability and the relative contributions of multiple sources of error. The results indicate that ESL papers received consistently lower scores than NE papers. The G-coefficients for ESL and NE papers were considerably different revealing concern about the reliability of ratings of ESL papers. The significant increase in the number of ESL students pursuing graduate degrees in North American institutions warrants further research to determine the extent to which consistency differences affect the validity of the assessment of ESL students' writing and to identify ways to alleviate these differences.

Stable isotopes as ecological tracers: an efficient method for assessing the contribution of multiple sources to mixtures

Abstract. Stable isotopes are increasingly being used as tracers of ecological processes potentially providing relevant information to environmental management issues. An application of the methodology consists in relating the stable isotopic composition of a sample mixture to that of sources. The number of stable isotopes, however, is usually lower than that of potential sources existing in an ecosystem, which creates mathematical difficulties in correctly tracing sources. We discuss a linear programming model which efficiently derives information on the contribution of sources to mixtures for any number of stable isotopes and any number of sources by addressing multiple sources simultaneously. The model identifies which sources are present in all, present in a subset of the samples or absent from all samples simultaneously and calculates minimum and maximum values of each source in the mixtures. We illustrate the model using a data set consisting of the isotopic signatures of different plant sources ingested by primary consumers in tropical riverine habitat in Asia. The model discussed may contribute to extend the scope of stable isotopes methodology to a range of new problems dealing with multiple sources and multiple tracers. For instance, in food web studies, if particular organic matter sources disappear or decrease in availability (e.g. climate change scenarios) the model allows simulation of alternative diets of the consumers providing potentially relevant information for managers and decision makers.