Determination of optimum polymeric coagulant in palm oil mill effluent coagulation using multiple-objective optimisation on the basis of ratio analysis (MOORA)

The main limitation of a conventional palm oil mill effluent (POME) ponding system lies in its inability to completely decolourise effluent. Decolourisation of effluent is aesthetically and environmentally crucial. However, determination of the optimum process parameters is becoming more complex with the increase of the number of coagulants and responses. The primary objective of this study is to determine the optimum polymeric coagulant in the coagulation–flocculation process of palm oil mill effluent by considering all output responses, namely lignin–tannin, low molecular mass coloured compounds (LMMCC), chemical oxygen demand (COD), ammonia nitrogen (NH₃-N), pH and conductivity. Here, multiple-objective optimisation on the basis of ratio analysis (MOORA) is employed to discretely measure multiple response characteristics of five different types of coagulants as a function of assessment value. The optimum coagulant is determined based on the highest assessment value and was identified as QF25610 (cationic polyacrylamide). On the other hand, the lowest assessment value was represented by AN1800 (anionic polyacrylamide). This study highlights the simplicity of MOORA approach in handling various input and output parameters, and it may be useful in other wastewater treatment processes as well.     

Prediction of membrane fouling using artificial neural networks for wastewater treated by membrane bioreactor technologies: bottlenecks and possibilities

Membrane fouling is a major concern for the optimization of membrane bioreactor (MBR) technologies. Numerous studies have been led in the field of membrane fouling control in order to assess with precision the fouling mechanisms which affect membrane resistance to filtration, such as the wastewater characteristics, the mixed liquor constituents, or the operational conditions, for example. Worldwide applications of MBRs in wastewater treatment plants treating all kinds of influents require new methods to predict membrane fouling and thus optimize operating MBRs. That is why new models capable of simulating membrane fouling phenomenon were progressively developed, using mainly a mathematical or numerical approach. Faced with the limits of such models, artificial neural networks (ANNs) were progressively considered to predict membrane fouling in MBRs and showed great potential. This review summarizes fouling control methods used in MBRs and models built in order to predict membrane fouling. A critical study of the application of ANNs in the prediction of membrane fouling in MBRs was carried out with the aim of presenting the bottlenecks associated with this method and the possibilities for further investigation on the subject.     

Triclocarban: UV photolysis,wastewater disinfection,and ecotoxicity assessment using molecular biomarkers

Triclocarban (TCC) is an antibacterial agent found in pharmaceuticals and personal care products (PPCP). It is potentially bioaccumulative and an endocrine disruptor, being classified as a contaminant of emerging concern (CEC). In normal uses, approximately 96% of the used TCC can be washed down the drain going into the sewer system and eventually enter in the aquatic environment. UV photolysis can be used to photodegrade TCC and ecotoxicity assays could indicate the photodegradation efficiency, since the enormous structural diversity of photoproducts and their low concentrations do not always allow to identify and quantify them. In this work, the TCC was efficiently degraded by UVC direct photolysis and the ecotoxicity of the UV-treated mixtures was investigated. Bioassays indicates that Daphnia similis (48 h EC₅₀ = 0.044 μM) was more sensitive to TCC than Pseudokirchneriella subcapitata (72 h IC₅₀ = 1.01 μM). TCC and its photoproducts caused significant effects on Eisenia andrei biochemical responses (catalase and glutathione-S-transferase); 48 h was a critical exposure time, since GST reached the highest activity values. UVC reduced the TCC toxic effect after 120 min. Furthermore, TCC was photodegraded in domestic wastewater which was simultaneously disinfected for total coliform bacterial (TCB) (360 min) and Escherichia coli (60 min).

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Graphical abstract TCC degradation and ecotoxicological assessment

     

Assessment of indoor climate of Mogiła Abbey in Kraków (Poland) and the application of the analogues method to predict microclimate indoor conditions

The microclimatic monitoring of the historic church of Mogi?a Abbey (Kraków, Poland) was carried out to study the impact of the environmental parameters on the organic and hygroscopic artworks. Specific indexes were proposed to objectively assess the quality of time series of temperature (T), relative humidity (RH), and carbon dioxide (CO₂) before applying the exploratory data analysis. The series were used to define the historic environmental conditions as stated in the European Standard EN 15757:2010 and with the use of the climate evaluation chart (CEC). It was found that the percentage of time in which T and RH values are within the allowable limits of the ASHRAE (2011) Class B is more than 85 %. This means that, for about 15 % of the time, there is a high risk of mechanical damage to highly vulnerable objects mainly due to the RH variability. The environment at the chancel resulted moister than that at the cornice, and the fungal growth is possible. In addition, the time-weighted preservation index (TWPI) is computed to evaluate the life expectancy of the objects, taking into account the environmental conditions of the site under study. The method of analogues, developed to predict the evolution of a system given observations of the past and without the knowledge of any equation among variables, was proposed and applied to the time series of temperature, relative humidity, and carbon dioxide with a 1-h sampling time to avoid the influence of the autocorrelation.     

When experts disagree: the need to rethink indicator selection for assessing sustainability of agriculture

Sustainability indicators are well recognized for their potential to assess and monitor sustainable development of agricultural systems. A large number of indicators are proposed in various sustainability assessment frameworks, which raises concerns regarding the validity of approaches, usefulness and trust in such frameworks. Selecting indicators requires transparent and well-defined procedures to ensure the relevance and validity of sustainability assessments. The objective of this study, therefore, was to determine whether experts agree on which criteria are most important in the selection of indicators and indicator sets for robust sustainability assessments. Two groups of experts (Temperate Agriculture Research Network and New Zealand Sustainability Dashboard) were asked to rank the relative importance of eleven criteria for selecting individual indicators and of nine criteria for balancing a collective set of indicators. Both ranking surveys reveal a startling lack of consensus amongst experts about how best to measure agricultural sustainability and call for a radical rethink about how complementary approaches to sustainability assessments are used alongside each other to ensure a plurality of views and maximum collaboration and trust amongst stakeholders. To improve the transparency, relevance and robustness of sustainable assessments, the context of the sustainability assessment, including prioritizations of selection criteria for indicator selection, must be accounted for. A collaborative design process will enhance the acceptance of diverse values and prioritizations embedded in sustainability assessments. The process by which indicators and sustainability frameworks are established may be a much more important determinant of their success than the final shape of the assessment tools. Such an emphasis on process would make assessments more transparent, transformative and enduring.     

Perceptions matter: household adaptive capacity and capability in two Australian coastal communities

Regional Environmental Change - This paper presents empirical data on household perceptions of capability to adapt to climate hazards and associated capacity needs. Households play an important...     

Perceived stressors of climate vulnerability across scales in the Savannah zone of Ghana: a participatory approach

Smallholder farmers in sub-Saharan Africa are confronted with climatic and non-climatic stressors. Research attention has focused on climatic stressors, such as rainfall variability, with few empirical studies exploring non-climatic stressors and how these interact with climatic stressors at multiple scales to affect food security and livelihoods. This focus on climatic factors restricts understanding of the combinations of stressors that exacerbate the vulnerability of farming households and hampers the development of holistic climate change adaptation policies. This study addresses this particular research gap by adopting a multi-scale approach to understand how climatic and non-climatic stressors vary, and interact, across three spatial scales (household, community and district levels) to influence livelihood vulnerability of smallholder farming households in the Savannah zone of northern Ghana. This study across three case study villages utilises a series of participatory tools including semi-structured interviews, key informant interviews and focus group discussions. The incidence, importance, severity and overall risk indices for stressors are calculated at the household, community, and district levels. Results show that climatic and non-climatic stressors were perceived differently; yet, there were a number of common stressors including lack of money, high cost of farm inputs, erratic rainfall, cattle destruction of crops, limited access to markets and lack of agricultural equipment that crossed all scales. Results indicate that the gender of respondents influenced the perception and severity assessment of stressors on rural livelihoods at the community level. Findings suggest a mismatch between local and district level priorities that have implications for policy and development of agricultural and related livelihoods in rural communities. Ghana’s climate change adaptation policies need to take a more holistic approach that integrates both climatic and non-climatic factors to ensure policy coherence between national climate adaptation plans and District development plans.     

Free market ideology and deregulation in Colorado’s oil fields: Evidence for triple movement activism?

Unconventional oil and gas extraction (UOGE) has spurred an unprecedented boom in onshore production in the US. Despite a surge in related research, a void exists regarding inquiries into policy outcomes and perceptions. To address this, support for federal regulatory exemptions for UOGE is examined using survey data collected in 2015 from two Northern Colorado communities. Current regulatory exemptions for UOGE can be understood as components of broader societal processes of neoliberalization. Free market ideology increases public support for federal regulatory exemptions for UOGE. Perceived negative impacts do not necessarily drive people to support increased federal regulation. Utilizing neo-Polanyian theory, interaction between free market ideology and perceived negative impacts is explored. Free market ideology appears to moderate people’s views of regulation: increasing the effect of perceived negative impacts while simultaneously increasing support for deregulation. To conclude, the ways in which free market ideology might normalize the impacts of UOGE activity are discussed.