A double exponential model for biochemical oxygen demand

New Exponential Scoring Functions for Diet Quality Indexes Solve Problems Caused by Truncation

BACKGROUND

Diet quality indexes, including the Healthy Eating Index (HEI), assess diets based on usual dietary intakes and a scoring function. Nearly all diet quality indexes use scoring functions that have floors and ceilings, thereby truncating the scores and losing information about intakes outside the scoring range. This score truncation has two important impacts: 1) the index does not reflect all intakes; and 2) the assumption that measurement error in intake reporting has a neutral impact on the diet quality score cannot be upheld.

OBJECTIVE

The main objective was to devise new diet quality scoring functions that eliminate truncation and its attendant problems.

METHODS

Seven desirable properties of a new scoring function were identified: 1) avoid truncations in component scoring to prevent information loss and to provide scoring sensitivity in the currently truncated regions; 2) reduce dependency on the accuracy of dietary standards; 3) minimize measurement error bias and subsequent misclassification; 4) relate plausibly to biological processes; 5) possess desirable mathematical and statistical properties; 6) have simple representations which are easy to calculate and add minimum artifacts of their own; and 7) otherwise closely mimic existing scoring functions.

RESULTS

The recommended replacement for piecewise-linear scoring is a family of scoring functions based on exponentials. For components where higher intakes are better, the function is a single exponential. For components where lower intakes are better, the function is a concave-convex mirrored pair of exponentials. The proposed exponential scoring functions have all seven desired properties.

CONCLUSIONS

The proposed exponential scoring functions will improve the usefulness of dietary scoring indexes by eliminating truncations. Compared to existing scoring functions, the use of exponentials makes the scores more inclusive of very high and very low intakes, reduces measurement error bias, and is less sensitive to the exact placement of the scoring standards.

A method for the rapid evaluation of leather biodegradability during the production phase

Advances in technological-industrial processes have led to the development of new materials that generate different impacts on the environment when presented as waste. The application of sustainable manufacturing practices in order to improve the environmental behaviour of materials, including in the waste stage, is now an important industry responsibility. This study developed a new method for the rapid evaluation of leather biodegradability that can easily be operated by the tannery industry during the production phase. The method uses the OxiTop® system within which a solid sample is suspended in a liquid medium with no nutritional limitations at a constant temperature and stirring conditions. Ten leather samples were tested based on the existing methodology for determining aerobic biological activity (EN 16087-1: 2011), ultimate aerobic biodegradability of plastic materials in an aqueous medium (ISO 14851: 2004), and OECD 301F guidelines for testing of chemicals. The developed method has been shown to reliably distinguish (over 7 days) between samples produced using different manufacturing processes/treatments. Starch proved to be a better standard reference material for checking inoculum activity and the proper functioning of the measurement system than cellulose. Skin without treatment was shown to be a suitable reference material for defining the maximum biodegradation of leather materials. Double exponential and Gompertz mathematical models closely described the biodegradation of the tested samples. This method offers a way for industry to test and produce leather materials with higher levels of biodegradability, thus reducing the adverse environmental impacts of the final products when presented as solid waste.

SIMSWASTE-AD - A modelling framework for the environmental assessment of agricultural waste management strategies: Anaerobic digestion

On-farm anaerobic digestion (AD) has been promoted due to its improved environmental performance, which is based on a number of life cycle assessments (LCA). However, the influence of site-specific conditions and practices on AD performance is rarely captured in LCA studies and the effects on C and N cycles are often overlooked. In this paper, a new model for AD (SIMS_WASTE-AD) is described in full and tested against a selection of available measured data. Good agreement between modelled and measured values was obtained, reflecting the model capability to predict biogas production (r²=0.84) and N mineralization (r²=0.85) under a range of substrate mixtures and operational conditions. SIMS_WASTE-AD was also used to simulate C and N flows and GHG emissions for a set of scenarios exploring different AD technology levels, feedstock mixtures and climate conditions. The importance of post-digestion emissions and its relationship with the AD performance have been stressed as crucial factors to reduce the net GHG emissions (-75%) but also to enhance digestate fertilizer potential (15%). Gas tight digestate storage with residual biogas collection is highly recommended (especially in temperate to warm climates), as well as those operational conditions that can improve the process efficiency on degrading VS (e.g. thermophilic range, longer hydraulic retention time). Beyond the effects on the manure management stage, SIMS_WASTE-AD also aims to help account for potential effects of AD on other stages by providing the C and nutrient flows. While primarily designed to be applied within the SIMS_DAIRY modelling framework, it can also interact with other models implemented in integrated approaches. Such system scope assessments are essential for stakeholders and policy makers in order to develop effective strategies for reducing GHG emissions and environmental issues in the agriculture sector.

Modelling the simultaneous processes occurring during the BOD(5) test using synthetic waters as a pattern

Synthetic waters imitating BOD(5) test conditions have been studied to model the progress curves of cell growth, organic matter consumption and oxygen demand. Glucose and glutamic acid were used as organic matter and Bacillus subtilis, Escherichia coli and Pseudomonas putida as microorganisms. The concentrations of all the products were measured simultaneously over time and were fitted to the Logistic and Monod models. Following this, the goodness of fit was analysed. Discrimination between models allowed us to conclude that the Logistic model has acceptable accuracy to describe the kinetic behaviour inside a BOD(5) bottle, while the extra parameter in the Monod model would not be statistically justified. Thus, the logistic parameters were determined under different conditions by non-linear regression and their biological meaning was interpreted.

An evaluation of substrate degradation patterns in the composting process. Part 1: profiles at constant temperature

This paper examines the patterns of 32 constant temperature substrate degradation profiles obtained from the composting literature, and evaluates the use of a single exponential model, a double exponential model and a non-logarithmic Gompertz model in describing their behaviour. Profiles were found to be predominantly either sigmoidal in shape, or to exhibit multi-phase behaviour, with a relatively small proportion of convex curves. Of the constant temperature profiles, 26 were either not well modelled by any of the above functions, or of such differing profiles that none of the above functions was applicable. Goodness of fit was measured using a normalised error function, and rated using a five-category descriptive scale, ranging from excellent to poor. No fits rated as excellent were observed. Fits rated as good were obtained for three data sets when using a single exponential function, for two data sets when using a double exponential function, and for one data set when using the non-logarithmic Gompertz function. The remainder of the fits were rated as moderate to poor. It is concluded that the evidence supporting the use of the single exponential model, the double exponential model or the non-logarithmic Gompertz model to describe substrate degradation profiles generated at constant temperature is limited. Further work is suggested in order to establish standard procedures and a standard simulated composting mixture for substrate degradation studies and to build a more comprehensive set of long-term substrate degradation profile data at constant temperature, and under non-limiting moisture and oxygen concentration conditions.