Recent advances on palm oil mill effluent (POME) pretreatment and anaerobic reactor for sustainable biogas production

Palm oil is one of the leading agricultural crops in the world, as it dominates 34% of the global vegetable oil market, with approximately 64.6*103 million kgs of production in 2017. However, along with its breakthrough, the generation of palm oil mill effluent (POME) as uncontrolled waste has become a serious matter and requires proper management to reduce its negative effects on the environment. Subsequently, the high organic content of POME makes it possible to convert waste into value-added products, such as biogas. A ratio of 0.5 for biological oxygen demand to chemical oxygen demand (BOD/COD) indicates a high possibility for biological treatment. Recently, the utilisation of POME as a cheap source for biogas production has gained an extraordinary amount of attention, and intensive research has been conducted on the upstream to downstream process. Finding the most suitable and efficient pretreatment technique and reactor configuration are vital parameters for the treatment and conversion of POME to biogas. This review describes existing pretreatment processes for POME and recommends recently manufactured high-rate anaerobic reactors as the most suitable and efficient pretreatment technique for maximising the extraction of biogas from POME

GIS-based FRASTIC model for pollution vulnerability assessment of fractured-rock aquifer systems

All groundwater is vulnerable to pollution, but the level of susceptibility depends on the spatial peculiarities of a region. Among the numerous vulnerability assessment methodologies, the geographical information system-based DRASTIC model is the most sophisticated and achieves reliable results even in complex areas. Fractured-rock aquifers are not only complex, but they are also potential sources of radioactive and other types of waste and are liable to high recharge rates. Hence, they can serve as a conduit for fluid (and potentially) contaminants. Therefore, in this study, a new parameter, ‘fracture media’ (F), is fashioned to replace the weakest parameter (i.e. depth to water, D) in the standardized DRASTIC model to create a new model (FRASTIC) for the complex fractured aquifer system. The proposed model was tested on a case study area (Kano, Nigeria), and the FRASTIC minimum and maximum indices obtained were in the range of 63–170. The region was characterized as having very low (covering 0.16% of the total study area), low (55.52%), medium (42.53%), and high (1.79%) vulnerability based on the standardized classification system. In addition, the modified FRASTIC model was further developed using the sensitivity analysis (SA) and recorded the highest vulnerable area coverage (32.86%) within Kano. Thus, the modified FRASTIC model is appropriate for the complex nature of the study area because it contributes appreciably to defining the vulnerable zones. The single-parameter SA was employed to obtain effective weights for two modified models, which were then implemented to improve efficacy. Conventional nitrate validation indicated that there is a strong correlation between nitrate and vulnerability for the modified models. In addition, a new approach for identifying the relationship between the water quality and vulnerability indices was developed by this study and was proven to be an effective validation tool

Rainwater harvesting systems reduce detergent use

Unidad de excelencia María de Maeztu MdM-2015-0552Purpose: Due to population growth, urban water demand is expected to increase significantly, as well as the environmental and economic costs required to supply it. Rainwater harvesting (RWH) systems can play a key role in helping cities meet part of their water demand as an alternative to conventional water abstraction and treatment. This paper presents an environmental and economic analysis of RWH systems providing households with water for laundry purposes in a life cycle thinking perspective. Conclusions: LCA and LCC present better results for high-density scenarios. Overall, avoided environmental and economic impacts from detergent reduction clearly surpass environmental impacts (in all categories except terrestrial acidification) and economic cost of the RWHsystem in most cases (except two scenarios). Another important finding is that 80%of the savings are achieved by minimizing detergent and fabric softener by using soft rainwater; and the remaining 20% comes from replacing the use of tap water

Decision support system for the estimation of rainfall intensity based on Intensity-Frequency-Duration (IFD) Diagram

Abstract not available

First-order hydrothermal oxidation kinetics of digested sludge compared with raw sludge

This article presents an assessment of the first-order hydrothermal oxidation kinetics of a selected digested sludge at subcritical (< 374°C) and supercritical (> 374°C) temperatures in the range of 250-460°C. Furthermore, the results were compared with reported oxidation kinetics of raw sludge treated under identical experimental conditions. In the assessment, oxidation was considered to proceed in two steps: (1) decomposition of the particulate, or non-filterable, chemical oxygen demand (PCOD); followed by (2) ultimate oxidation and removal of the total, particulate and soluble, COD. The accumulation and removal of soluble COD (SCOD) was determined from the difference between the rates of sludge decomposition and ultimate oxidation. Using results from batch and continuous-flow hydrothermal treatment experiments, the reacting organic ingredients were separated into groups according to the ease or difficulty at which they were decomposed or removed, with Arrhenius-type activation energy levels assigned to the different groups. The analysis confirmed that within the treatment range of 75% to more than 97% COD removal, the oxidation kinetics of the digested and raw sludges were nearly identical despite differences in the proportions of their original organic ingredients. The original organic ingredients were mostly removed above 75% COD removal, and the oxidation kinetics appeared to be dominated by the removal of acetic acid, an intermediate by-product which constituted 50% to more than 80% of the remaining COD. Furthermore, the oxidation kinetics of both sludge types were consistent with reported first-order oxidation kinetics of pure acetic acid solutions. The resulting kinetic models adequately represented hydrothermal oxidation of digested sludge, in terms of COD and PCOD removals, as well as accumulation and removal of the soluble SCOD

Impact of climate change on runoff in the upper part of the Euphrates basin

Among the processes most affected by global warming are the hydrological cycle and water resources. Regions where the majority of runoff consists of snowmelt are very sensitive to climate change. It is significant to express the relationship between climate change and snow hydrology and it is imperative to perform climate change impact studies on snow hydrology at global and regional scales. Climate change impacts on the mountainous Upper Euphrates Basin were investigated in this paper. First, historical data trend analysis of significant hydro-meteorological data is presented. Available future climate data are then explained, and, finally, future climate data are used in hydrological models, which are calibrated and validated using historical hydro-meteorological data, and future streamflow is projected for the period 2070–2100. The hydrological model outcomes indicate substantial runoff decreases in summer and spring season runoff, which will have significant consequences on water sectors in the Euphrates Basin

Forecasting Victorian spring rainfall using ENSO and IOD: a comparison of linear multiple regression and nonlinear ANN

El Nino southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) have enormous effects on the precipitations around the world. Australian rainfall is also affected by these key modes of complex climate variables. Many studies have tried to establish the relationships of these large-scale climate indices among the rainfalls of different parts of Australia, particularly Western Australia, New South Wales, Queensland and Victoria. Unlike the other regions, no clear relationship can be found between each individual largescale climate mode and Victorian rainfall. Past studies considering southeast Australian rainfall predictability could achieve a maximum of 30% correlation. This study looks into the lagged-time relationships of these modes on Victorian spring rainfall. On the other hand, few attempts have been made to establish the combined effect of these indices on rainfall in order to develop a better understanding and forecasting system. Thus, the aim of this research was to investigate the combined lagged relationship of ENSO and IOD with Victorian spring rainfall using multiple regression as a linear method compared to Artificial Neural Networks (ANN) as a nonlinear method. This study found that predicting spring rainfall using combined lagged ENSO-DMI indices with ANN can achieve 96.96% correlation as compared to multiple regression with only 66.15% correlation. This method can be used for other parts of the world where a relationship exists between rainfall and large scale climate modes which could not be established by linear methods

Modifications of TOPMODEL for the rainforest catchments of North Queensland

Abstract not available

Highest flood level modelling: a combined statistical and mathematical modelling approach

Abstract not available