Synthesis and potential applications of cyclodextrin-based metal–organic frameworks: a review

Metal–organic frameworks are porous polymeric materials formed by linking metal ions with organic bridging ligands. Metal–organic frameworks are used as sensors, catalysts for organic transformations, biomass conversion, photovoltaics, electrochemical applications, gas storage and separation, and photocatalysis. Nonetheless, many actual metal–organic frameworks present limitations such as toxicity of preparation reagents and components, which make frameworks unusable for food and pharmaceutical applications. Here, we review the structure, synthesis and properties of cyclodextrin-based metal–organic frameworks that could be used in bioapplications. Synthetic methods include vapor diffusion, microwave-assisted, hydro/solvothermal, and ultrasound techniques. The vapor diffusion method can produce cyclodextrin-based metal–organic framework crystals with particle sizes ranging from 200 nm to 400 μm. Applications comprise food packaging, drug delivery, sensors, adsorbents, gas separation, and membranes. Cyclodextrin-based metal–organic frameworks showed loading efficacy of the bioactive compounds ranging from 3.29 to 97.80%.

     

Risk assessment of PBDEs and PAHs in house dust in Kocaeli,Turkey: levels and sources

Indoor dust samples were collected from 40 homes in Kocaeli, Turkey and were analyzed simultaneously for 14 polybrominated diphenyl ethers (PBDEs) and 16 poly aromatic hydrocarbons (PAHs) isomers. The total concentrations of PBDEs (Σ₁₄PBDEs) ranged from 29.32 to 4790 ng g^?1, with a median of 316.1 ng g^?1, while the total indoor dust concentrations of 16 PAHs (Σ₁₆PAHs) extending over three to four orders of magnitude ranged from 85.91 to 40,359 ng g^?1 with a median value of 2489 ng g^?1. Although deca-PBDE products (BDE-209) were the principal source of PBDEs contamination in the homes (median, 138.3 ng g^?1), the correlation in the homes was indicative of similar sources for both the commercial penta and deca-PBDE formulas. The PAHs diagnostic ratios indicated that the main sources of PAHs measured in the indoor samples could be coal/biomass combustion, smoking, and cooking emissions. For children and adults, the contributions to ∑₁₄PBDEs exposure were approximately 93 and 25 % for the ingestion of indoor dust, and 7 and 75 % for dermal contact. Exposure to ∑₁₆PAHs through dermal contact was the dominant route for both children (90.6 %) and adults (99.7 %). For both groups, exposure by way of inhalation of indoor dust contaminated with PBDEs and PAHs was negligible. The hazard index (HI) values for BDE-47, BDE-99, BDE-153, and BDE-209 were lower than the safe limit of 1, and this result suggested that none of the population groups would be likely to experience potential health risk due to exposure to PBDEs from indoor dust in the study area. Considering only ingestion + dermal contact, the carcinogenic risk levels of both B2 PAHs and BDE-209 for adults were 6.2 × 10^?5 in the US EPA safe limit range while those for children were 5.6 × 10^?4 and slightly higher than the US EPA safe limit range (1 × 10^?6 and 1 × 10^?4). Certain precautions should be considered for children.     

The global solar radiation estimation and analysis of solar energy: Case study for Osmaniye,Turkey

This paper investigates the prediction of solar radiation model and actual solar energy in Osmaniye, Turkey. Four models were used to estimate using the parameters of sunshine duration and average temperature. In order to obtain the statistical performance analysis of models, the coefficient of determination (R²), mean absolute percentage error (MAPE), mean absolute bias error (MABE), and root mean square error (RMSE) were used. Results obtained from the linear regression using the parameters of sunshine duration and average temperature showed a good prediction of the monthly average daily global solar radiation on a horizontal surface. In order to obtain solar energy, daily and monthly average solar radiation values were calculated from the five minute average recorded values by using meteorological measuring device. As a result of this measurement, the highest monthly and yearly mean solar radiation values were 698 (April in 2013) and 549 (2014 year) W/m² respectively. On an annual scale the maximum global solar radiation changes from 26.38 MJ/m²/day by June to 19.19 MJ/m²/day by September in 2013. Minimum global solar radiation changes from 14.05 MJ/m²/day by October to 7.20 MJ/m²/day by January in 2013. Yearly average energy potential during the measurement period was 16.53 MJ/m²/day (in 2013). The results show that Osmaniye has a considerable solar energy potential to produce electricity.     

Modelling cadmium bioaccumulation in Gammarus pulex by using experimental design approach

Recently, although dynamic approaches have been used increasingly to describe metal bioaccumulation in aquatic organisms, the validation of such laboratory-derived modelling is rarely assessed under environmental conditions. The present study aims to evaluate and verify statistical and mathematical models for the bioaccumulation of cadmium (Cd) and to evaluate the suitability of Gammarus pulex as a biomonitor for Cd. To optimise Cd²⁺ ion bioaccumulation conditions a Box–Behnken design was used and whether G. pulex can be used as an estimated tool to assess aquatic quality was investigated. A Box–Behnken experimental design combined with response surface modelling (RSM) was employed for Cd²⁺ bioaccumulation in G. pulex. Independent variables including temperature, contact time and Cd²⁺ ion concentration significance and their interactions were tested using analysis of variance. The selected variables’ optimum values were obtained by solving the quadratic regression model along with by analysing the response surface contour plots. Based on Box–Behnken design, the applied model is significant because model F-value and R² were obtained as 5121.49, 0.9998, respectively. Bioaccumulation of Cd amount was analysed using electrothermal atomic absorption spectrophotometer. The obtained data suggest that G. pulex can be evaluated as Cd biomonitor.     

Recycling bottom ash in production of eco-friendly interlocking concrete paving blocks

Journal of Material Cycles and Waste Management - Coal combustion waste reaches huge amount that causes environmental problem. In modern world, wastes generated from an industry can be used by...     

The effects of drainage basin geomorphometry on minimum low flow discharge: the study of small watershed in Kelang River Valley in Peninsular Malaysia

This study investigate the relationships between genomorphometric properties and the minimum low flow dischare of undisturbed drainage basins in the Taman BukitCahaya Seri Alam Forest Reserve,Peninsular Malaysia.The drainage basins selected were third-order basins so as to facilitate a common base for sampling and performing an unbiased statistical analyses.Three levels of relationships were observed in the study.Significant relationships exised between the genomorphometric properties as shown by the correlation network analysis;secondly,individual geomorphometric properties were observed to influence minimum flow discharge;and finally,the multiple regression model set up showed that minimum flow discharge(Qnub)was dependent of basin area(AU),stream length(LS),maximum relief(Hmax),average relief (HAV) and stream frequency(SF).These findings further enforced other studies of this nature that drainage basins were dynamic and functional entities whose operations were governed by complex interrelationships occurring within the basins.Changes to any of the geomorphometric properties would influence their role as basin regulators thus influencing a change in basin response.In the case of the basin‘s minimum low flow,a change in any of the properties considered in the regression model influenced the “time to peak”of flow.A shorter time period would mean higher discharge,which is generally considered the prerquisite to flooding.This research also conclude that the role of geomorphometric properties to control the water supply within the stream through out the year even though during the drought and less precipitations months .Drainage basins are sensitive entities and any deterioratons involve will generate reciprocals and response to water supply as well as the habitat within the areas.     

Modeling of SO<Subscript>2</Subscript> distribution in Istanbul using artificial neural networks

Urban air pollution is a growing problem in developing countries. Some compounds especially sulphur dioxide (SO₂) is considered as typical indicators of the urban air quality. Air pollution modeling and prediction have great importance in preventing the occurrence of air pollution episodes and provide sufficient time to take the necessary precautions. Recently, various stochastic image-processing algorithms such as Artificial Neural Network (ANN) are applied to environmental engineering. ANN structure employs input, hidden and output layers. Due to the complexity of the problem, as the number of input–output parameters differs, ANN model settings such as the number of neurons of these layers changes. The ability of ANN models to learn, particularly capability of handling large amounts (or sets) of data simultaneously as well as their fast response time, are invariably the characteristics desired for predictive and forecasting purposes. In this paper, ANN models have been used to predict air pollutant parameter in meteorological considerations. We have especially focused on modeling of SO₂ distribution and predicting its future concentration in Istanbul, Turkey. We have obtained data sets including meteorological variables and SO₂ concentrations from Istanbul-Florya meteorological station and Istanbul-Yenibosna air pollution station. We have preferred three-layer perceptron type of ANN which consists of 10, 22 and 1 neurons for input, hidden and output layers, respectively. All considered parameters are measured as daily mean. The input parameters are: SO₂ concentration, pressure, temperature, humidity, wind direction, wind speed, strength of sunshine, sunshine, cloudy, rainfall and output parameter is the future prediction of SO₂. To evaluate the performance of ANN model, our results are compared to classical nonlinear regression methods. The over all system finds an optimum correlation between input–output variables. Here, the correlation parameter, r is 0.999 and 0.528 for training and test data. Thus in our model, the trend of SO₂ is well estimated and seasonal effects are well represented. As a result, we conclude that ANN is one of the compromising methods in estimation of environmental complex air pollution problems.     

Estimation of stream temperature in firtina creek (Rize-Turkiye) using artificial neural network model

Water temperature is one of the most important environmental variables in aquatic ecosystem. Temperature changes may have positive or negative effects on organisms. High water temperatures have caused mortalities in salmonid fishes. Therefore, monitoring and prediction of potential adverse changes in water temperature is very important. Here, we have developed and tested an artificial neural network (ANN) model to predict stream temperature of Firtina Creekin Black Sea region; using local water temperature, dissolved oxygen, pH and other available meteorological data (air temperature, rainfall). Thus, enabling define suitable habitat for native Sea Trout (Salmo trutta labrax, Pallas 1811) under past drought or other adverse envIronmental conditions.     

Ecosystem service lens reveals diverse community values of small-scale fisheries

The ocean provides benefits to coastal communities around the world, however, the depth and complexity of people’s interactions with marine ecosystems are not well represented in many marine management initiatives. Many fisheries are managed to maximize provisioning value, which is readily quantified, while ignoring cultural values. An ecosystem services approach that includes both provisioning and cultural services will enable managers to better account for the diverse values marine fisheries provide to coastal communities. In this study, we assess community values related to a top fished species, the Mexican chocolate clam, Megapitaria squalida, in Loreto, Baja California Sur, Mexico. We conducted an exploratory analysis based on 42 household surveys, and found that community members perceive multiple provisioning and cultural benefits from the clam, including community economic, historical, and identity values. Despite reporting infrequent harvest and consumption of clams, participants perceive the species as an important part of community identity, highlighting the role of Mexican chocolate clams as a cultural keystone species in the Loreto region. Fisheries management that recognizes the full range of ecosystem services a species contributes to coastal communities will be better equipped to sustain these diverse values into the future.Electronic supplementary materialThe online version of this article (10.1007/s13280-020-01405-w) contains supplementary material, which is available to authorized users.     

Recycling municipal,agricultural and industrial waste into energy,fertilizers, food and construction materials,and economic feasibility: a review

The global amount of solid waste has dramatically increased as a result of rapid population growth, accelerated urbanization, agricultural demand, and industrial development. The world's population is expected to reach 8.5 billion by 2030, while solid waste production will reach 2.59 billion tons. This will deteriorate the already strained environment and climate situation. Consequently, there is an urgent need for methods to recycle solid waste. Here, we review recent technologies to treat solid waste, and we assess the economic feasibility of transforming waste into energy. We focus on municipal, agricultural, and industrial waste. We found that methane captured from landfilled-municipal solid waste in Delhi could supply 8–18 million houses with electricity and generate 7140 gigawatt-hour, with a prospected potential of 31,346 and 77,748 gigawatt-hour by 2030 and 2060, respectively. Valorization of agricultural solid waste and food waste by anaerobic digestion systems could replace 61.46% of natural gas and 38.54% of coal use in the United Kingdom, and could reduce land use of 1.8 million hectares if provided as animal feeds. We also estimated a levelized cost of landfill solid and anaerobic digestion waste-to-energy technologies of $0.04/kilowatt-hour and $0.07/kilowatt-hour, with a payback time of 0.73–1.86 years and 1.17–2.37 years, respectively. Nonetheless, current landfill waste treatment methods are still inefficient, in particular for treating food waste containing over 60% water.