A composite analysis is used to evaluate the teleconnections between the long term (June-August) rainfall anomalies with east and west phases of quasi-biennial oscillation (QBO) in the stratospheric zonal winds from 1979–2017. Applying the lower equatorial stratospheric zonal wind index in JJA rainfall prediction is based on its tendency to persist for several months after the phase change from easterly to westerly and vice versa. Below normal condition rainfall used to coin drought. This study is important because, the Upper Blue Nile region is one of the most inviting areas for different activities like agriculture and hydroelectric power; therefore, timely prediction of June-August rainfall serves farmers and other concerned sectors. The aim of this analysis is to establish the global signal quasi-biennial oscillation contribution alone at different time lags and its association among Southern Oscillation Index (SOI) for estimation June-August rainfall of the Upper Blue Nile. The rainfall used as predictand while quasi-biennial oscillation & SOI datasets are used as predictors in regression model after testing collinearity of these two independent variables. Performance of regression model and actual value is tested by using statistical techniques: Root Mean Square Error, Mean Absolute Error and bias. The performance is seen reasonably high between actual and estimated values show strong agreement.

Microplastics (5 mm to1 nm) and plasticizers are ubiquitous worldwide in waterways, beaches, sediments, and biota. Ingestion of microplastics by various marine species and bioaccumulation of plasticizers continues to be of concern. Additionally, microplastics act as a carrier for the transport of persistent organic pollutants and some harmful microorganisms, increasing the hazard to aquatic species. Microplastics vary in composition based on their monomeric component and the specific plasticizer(s). There is a large data gap in our understanding of the biological toxicity of the different plastic polymers. The results presented here examine gross morphological alterations in sac fry zebrafish as a result of exposure to weathered microplastics and virgin/pure plastic polymers. Embryos were exposed from 3 hours post fertilization (hpf) to 96 hpf with samples of weathered microplastics from estuaries in Newark Bay, NJ, as well as commercially available virgin/pure plastics at concentrations of 1 µg/mL or 10 µg/mL. The Newark Bay microplastics were chemically identified using pyrolysis GC-MS. The three field samples were composed primarily of polyethylene (FPE), polypropylene (FPP) and polyvinyl chloride vinyl acetate mixture (FVA). Significant morphometric changes (P< 0.05) were noted between the control zebrafish and the treated groups in the embryonic zebrafish samples for the Newark Bay, weathered samples following statistical analysis of morphometric data. The commercial microplastics tested included: low density polyethylene (LDPE), medium density polyethylene (MDPE), high density polyethylene (HDPE), polypropylene (PP), polystyrene (PS), polyvinyl chloride (PVC), sodium polyacrylate (SPA), polyethylene terephthalate (PET), polyurethane (PUR), poly methyl-methacrylate (PMMA), polyethylene (co-vinyl-acetate) (PEVA), and polystyrene (co-acrylonitrile) (PSAN). Significant changes were seen in total body length in all three Newark Bay field sample microplastics, as well as virgin/pure microplastic treatment groups PET, PUR, PMMA. The pericardial sac size was found significantly altered in FPP 10 µg/mL sample plastic as well as pure microplastic treatment groups HDPE, SPA, PET, PUR, PMMA, PP, and PEVA. The interocular distance was found to be significantly changed in the pure microplastic treatment groups HDPE and PET. The pericardial sac size was the most sensitive endpoint measured followed by total body length. The least sensitive endpoint was interocular distance. These results highlight the associated toxicity with both weathered and lab standard grade microplastics exposure to treated zebrafish developing embryos. The laboratory induced cardiac and growth alterations following laboratory microplastic exposure could be examined in field populations exposed to high microplastic concentrations.

The studies on polycyclic aromatic hydrocarbons (PAHs) occurrence, distribution, health risk, and effect of them on aquatic environments are limited in worldwide. To cope with this critical challenge, the process of eliminating oil compounds and growing algae were investigated by conducting various experiments in an artificial environment of petroleum that were called M1, M2 and M3 (0.05 mg/L, 1.5 mg/L, 2.5 mg/L concentration of oil per 100 mg/L distilled water) using mix cultivating Scenedesmus. obliquus and Chlamydomonas reinhardtii algae. In this matter, the highest rate of the growth of algae was significantly reported in M2 treatment (P<0.01). Moreover, the percentage of removal of all light petroleum hydrocarbons in M1 treatment was 100% on day 14 of cultivation (P<0.05). Compared to light hydrocarbon compounds, 8 heavy combinations with 97.33% in the concentration of 0.5 g/100 mL and 85.66% in the initial concentration of 1.5 g/100 mL and 73.66% at the initial concentration of 2.5 g/100 mL of crude oil were eliminated by S. obliquus and C. reinhartiialgae (P <0.01). Finally, the experimental results revealed that in terms of the potential for nutrient removal, the cultivation of mixing two algae S. obliquus and Chlamydomonas reinhardtii in wastewater, hydrocarbon compounds, and water quality and biomass production, can be distinguished as some acceptable options to exploit in the biological treatment of contaminated aquatic environments.

Despite the various initiatives being employed for fostering sustainability to globally achieve Agenda 2030, the understanding of the Higher Education Institutions (HEI) practices, discourse, and management remains limited. The present study identifies and quantifies the development of sustainable practices for HEI. It is an exploratory cross-sectional study conducted in 2014 at King Abdul Aziz University (KAU) to identify knowledge, attitudes, and behaviour concerning waste management and what could be done to develop sustainable practices at the campus. The study population comprised of academic and non-academic staff of KAU recruited through random sampling technique. The data was collected through two closed-ended questionnaires and analyzed using IBM Statistical Package of Social Sciences software (SPSS) version 20. The study's findings showed that waste management (WM) would improve KAU’s reputation at local, national and international levels resulting in improved regulatory compliance. The results also reflected that environmental pollution caused by the emissions from the energy used and the materials consumed could considerably be reduced by the effective technical measures taken by the organization. The study concluded that sustainability in universities could be achieved when HEI works to inform citizens; there still is a long way to be at par with the European counterparts.

Solid waste management is seen as a response to the increase in waste generation due to the rising number of industrial facilities. This includes digital manufacturing facilities such as Fabrication Laboratories (FAB LAB) which acts as innovation centers that generates prototypes using a common set of digital fabrication equipment. Previous studies have tackled with the environmental impacts of FAB LABs in a macro-level scale; however, there has been a lack of research specifically assessing the solid waste of laboratories, more so on Philippine FAB LABs. A baseline assessment study on FAB LABs of the Philippines could be applicable in future implementations of solid waste management systems through the crafting of institutional policies and guidelines for environmental sustainability. Using data gathered from 11 respondent FAB LABs, this study quantified percentage compositions of the waste according to waste type as well as the relative waste generated by each respondent FAB LAB. Machine availability was seen as a factor in waste generation resulting in the high generation of wood and plastic waste. Moreover, it was observed that earlier established laboratories generally had more active makers than recently established ones, hence the older FAB LABs statistically produced more waste. Approximately 53% of the overall waste produced was considered recyclable by Philippine standards but the actual recyclability of the waste was still undetermined due to the ambiguous criteria for recyclables and the lack of feedback data from recycling facilities. The initial findings suggest that an implementation of continuous waste monitoring, sufficient in-laboratory protocols, and coordination between FAB LABs and recycling facilities could improve actual waste recyclability and-by extension-the environmental sustainability of Philippine FAB LABs.

The water quality index (WQI) is an aggregated indicator used to represent the overall quality of water for any intended use. It is typically calculated from several biological, chemical, and physical parameters. Assessment of factors that affect the WQI is then essential. Climate change is expected to impact a wide range of water quality issues; hence, climate variables are likely to be significant factors to evaluate the WQI. We propose three statistical models; multiple linear regression (MLR), artificial neuron network (ANN), and Gaussian process regression (GPR) to assess the WQI using the climate variables. The data is the WQI of Ping River, which flows through the provinces in the north of Thailand. The climate variables are temperature, humidity, total rainfall, and evaporation. A comparison between these models is determined by model prediction accuracy scores. The results show that the total rainfall is the most significant variable to predict the WQI for the Ping River. Although these three methods can predict the WQI relatively good, overall, the GPR model performs better than the MLR and the ANN. Besides, the GPR is more flexible as it can relax some restrictions and assumptions. Therefore, the GPR is appropriate to assess the WQI under the climate variables for the Ping River.