A Solvent-Free Approach for Production of Films from Pectin and Fungal Biomass

Self-binding ability of the pectin molecules was used to produce pectin films using the compression molding technique, as an alternative method to the high energy-demanding and solvent-using casting technique. Moreover, incorporation of fungal biomass and its effects on the properties of the films was studied. Pectin powder plasticized with 30% glycerol was subjected to heat compression molding (120 °C, 1.33 MPa, 10 min) yielding pectin films with tensile strength and elongation at break of 15.7 MPa and 5.5%, respectively. The filamentous fungus Rhizopus oryzae was cultivated using the water-soluble nutrients obtained from citrus waste and yielded a biomass containing 31% proteins and 20% lipids. Comparatively, the same strain was cultivated in a semi-synthetic medium resulting in a biomass with higher protein (60%) and lower lipid content (10%). SEM images showed addition of biomass yielded films with less debris compared to the pectin films. Incorporation of the low protein content biomass up to 15% did not significantly reduce the mechanical strength of the pectin films. In contrast, addition of protein-rich biomass (up to 20%) enhanced the tensile strength of the films (16.1–19.3 MPa). Lastly, the fungal biomass reduced the water vapor permeability of the pectin films.     

Impacts of COVID-19 on Sustainable Development Goals and effective approaches to maneuver them in the post-pandemic environment

Environmental Science and Pollution Research - In the pursuit of constructing a sustainable world for all through the instrumental seventeen Sustainable Development Goals, the COVID-19 pandemic...     

COVID-19 and beliefs about tobacco use: an online cross-sectional study in Iran

Environmental Science and Pollution Research - There is mixed evidence surrounding the relationship between tobacco use and COVID-19 infection/progression. The current study investigates beliefs...     

Investigation of the association between pesticide exposure and the prevalence of type 2 diabetes in Shahedieh population in Yazd

Environmental Science and Pollution Research - This study aimed to investigate the effect of exposure to pesticides and the prevalence of type 2 diabetes (T2D). In a cross-sectional study with a...     

Designing a mixed performance measurement system for environmental supply chain management using evolutionary game theory and balanced scorecard: A case study of an auto industry supply chain

This paper proposes a mixed performance measurement system using a combination of evolutionary game theory and the balanced scorecard (BSC) in environmental supply chain management (ESCM) that measures and evaluates business operations using the four different perspectives of finance, customer, internal business process, and learning and growth. ESCM plays an important role in the supply chain which leads to the reduction, reuse and recycling of resources involved in both upstream and downstream activities. This paper presents guidance for practical managers in evaluating and measuring ESCM by developing a knowledge-based BSC and evolutionary game theory. The primary purpose of this paper is to apply the proposed method in a case study to one of Iran's biggest auto industry supply chain SAIPA Company. The results of this study indicate that the adoption of ESCM, in the absence of regulatory pressures and cost-saving measures is triggered by public pressures and its implementation is limited by organizational factors and strategic myopia.     

COMPARISON OF STOCHASTIC AND DETERMINISTIC DYNAMIC PROGRAMMING FOR RESERVOIR OPERATING RULE GENERATION1

ABSTRACT: Two dynamic programming models — one deterministic and one stochastic — that may be used to generate reservoir operating rules are compared. The deterministic model (DPR) consists of an algorithm that cycles through three components: a dynamic program, a regression analysis, and a simulation. In this model, the correlation between the general operating rules, defined by the regression analysis and evaluated in the simulation, and the optimal deterministic operation defined by the dynamic program is increased through an iterative process. The stochastic dynamic program (SDP) describes streamflows with a discrete lag-one Markov process. To test the usefulness of both models in generating reservoir operating rules, real-time reservoir operation simulation models are constructed for three hydrologically different sites. The rules generated by DPR and SDP are then applied in the operation simulation model and their performance is evaluated. For the test cases, the DPR generated rules are more effective in the operation of medium to very large reservoirs and the SDP generated rules are more effective for the operation of small reservoirs.     

Empirical likelihood confidence intervals for adaptive cluster sampling

Adaptive cluster sampling (ACS) is an efficient sampling design for estimating parameters of rare and clustered populations. It is widely used in ecological research. The modified Hansen-Hurwitz (HH) and Horvitz-Thompson (HT) estimators based on small samples under ACS have often highly skewed distributions. In such situations, confidence intervals based on traditional normal approximation can lead to unsatisfactory results, with poor coverage properties. Christman and Pontius (Biometrics 56:503–510, 2000) showed that bootstrap percentile methods are appropriate for constructing confidence intervals from the HH estimator. But Perez and Pontius (J Stat Comput Simul 76:755–764, 2006) showed that bootstrap confidence intervals from the HT estimator are even worse than the normal approximation confidence intervals. In this article, we consider two pseudo empirical likelihood functions under the ACS design. One leads to the HH estimator and the other leads to a HT type estimator known as the Hájek estimator. Based on these two empirical likelihood functions, we derive confidence intervals for the population mean. Using a simulation study, we show that the confidence intervals obtained from the first EL function perform as good as the bootstrap confidence intervals from the HH estimator but the confidence intervals obtained from the second EL function perform much better than the bootstrap confidence intervals from the HT estimator, in terms of coverage rate.     

Modeling carbon sequestration under zero tillage at the regional scale. I. The effect of soil erosion

Zero tillage is recognized as a potential measure to sequester carbon dioxide in soils and to reduce CO₂ emissions from arable lands. An up-scaling approach of the output of the Environmental Policy Integrated Climate (EPIC) model with the information system SLISYS-BW has been used to estimate the CO₂-mitigation potential in the state of Baden-Württemberg (SW-Germany). The state territory of 35,742 km² is subdivided into eight agro-ecological zones (AEZ), which have been further subdivided into a total of 3976 spatial response units. Annual CO₂-mitigation rates where estimated from the changes in soil organic carbon content comparing 30 years simulations under conventional and zero tillage. Special attention was given to the influence of tillage practices on the losses of organic carbon through soil erosion, and consequently on the calculation of CO₂-mitigation rates. Under conventional tillage, mean carbon losses through erosion in the AEZ were estimated to be up to 0.45 Mg C ha⁻¹ a⁻¹. The apparent CO₂-mitigation rate for the conversion from conventional to zero tillage ranges from 0.08 to 1.82 Mg C ha⁻¹ a⁻¹ in the eight AEZ, if the carbon losses through soil erosion are included in the calculations. However, the higher carbon losses under conventional tillage compared to zero tillage are composed of both, losses through enhanced CO₂ emissions, and losses through intensified soil erosion. The adjusted net CO₂-mitigation rates of zero tillage, subtracting the reduced carbon losses through soil erosion, are between 0.07 and 1.27 Mg C ha⁻¹ a⁻¹ and the estimated net mitigation rate for the entire state amounts to 285 Gg C a⁻¹. This equals to 1045 Gg CO₂-equivalents per year with the cropping patterns in the reference year 2000. The results call attention to the necessity to revise those estimation methods for CO₂-mitigation which are exclusively or predominantly based on the measurements of differential changes in total soil organic carbon without taking into account the tillage effects on carbon losses through soil erosion.     

Influence of polymethyl acrylate additive on the formation of particulate matter and NOX emission of a biodiesel–diesel-fueled engine

Environmental Science and Pollution Research - The aim of this study is to investigate the effect of the polymethyl acrylate (PMA) additive on the formation of particulate matter (PM) and nitrogen...