Prediction of non-methane hydrocarbons in Kuwait using regression and Bayesian kriged Kalman model

This article describes the hierarchical Bayesian approach for predicting average hourly concentrations of ambient non-methane hydrocarbons (NMHC) in Kuwait where records of six monitor stations located in different sites are observed at successive time points. Our objective is to predict the concentration level of NMHC in unmonitored areas. Here an attempt is made for the prediction of unmeasured concentration of NMHC at two additional locations in Kuwait. We will implement a kriged Kalman filter (KKF) hierarchical Bayesian approach assuming a Gaussian random field, a technique that allows the pooling of data from different sites in order to predict the exposure of the NMHC in different regions of Kuwait. In order to increase the accuracy of the KKF we will use other statistical models such as imputation, regression, principal components, and time series analysis in our approach. We considered four different types of imputation techniques to address the missing data. At the primary level, the logarithmic field is modeled as a trend plus Gaussian stochastic residual model. The trend model depends on hourly meteorological predictors which are common to all sites. The residuals are then modeled using KKF, and the prediction equation is derived conditioned on adjoining hours. On this basis we developed a spatial predictive distribution for these residuals at unmonitored sites. By transforming the predicted residuals back to the original data scales, we can impute Kuwait’s hourly non-methane hydrocarbons field.     

Bioinspired cellulose-based membranes in oily wastewater treatment

• Cellulose-based membrane separates oily wastewater mimicking the living things. • The three central surface mechanisms were reviewed. • Preparation, performance, and mechanism are critically evaluated. • First review of wettability based cellulose membrane as major material. • The current and future importance of the research are discussed. It is challenging to purify oily wastewater, which affects water-energy-food production. One promising method is membrane-based separation. This paper reviews the current research trend of applying cellulose as a membrane material that mimics one of three typical biostructures: superhydrophobic, underwater superoleophobic, and Janus surfaces. Nature has provided efficient and effective structures through the evolutionary process. This has inspired many researchers to create technologies that mimic nature’s structures or the fabrication process. Lotus leaves, fish scales, and Namib beetles are three representative structures with distinct functional and surface properties: superhydrophobic, underwater superoleophobic, and Janus surfaces. The characteristics of these structures have been widely studied and applied to membrane materials to improve their performance. One attractive membrane material is cellulose, which has been studied from the perspective of its biodegradability and sustainability. In this review, the principles, mechanisms, fabrication processes, and membrane performances are summarized and compared. The theory of wettability is also described to build a comprehensive understanding of the concept. Finally, future outlook is discussed to challenge the gap between laboratory and industrial applications.