How much land-based greenhouse gas mitigation can be achieved without compromising food security and environmental goals?

Feeding 9-10billion people by 2050 and preventing dangerous climate change are two of the greatest challenges facing humanity. Both challenges must be met while reducing the impact of land management on ecosystem services that deliver vital goods and services, and support human health and well-being. Few studies to date have considered the interactions between these challenges. In this study we briefly outline the challenges, review the supply- and demand-side climate mitigation potential available in the Agriculture, Forestry and Other Land Use AFOLU sector and options for delivering food security. We briefly outline some of the synergies and trade-offs afforded by mitigation practices, before presenting an assessment of the mitigation potential possible in the AFOLU sector under possible future scenarios in which demand-side measures codeliver to aid food security. We conclude that while supply-side mitigation measures, such as changes in land management, might either enhance or negatively impact food security, demand-side mitigation measures, such as reduced waste or demand for livestock products, should benefit both food security and greenhouse gas (GHG) mitigation. Demand-side measures offer a greater potential (1.5-15.6Gt CO2-eq. yr(-1)) in meeting both challenges than do supply-side measures (1.5-4.3Gt CO2-eq. yr(-1) at carbon prices between 20 and 100US$ tCO(2)-eq. yr(-1)), but given the enormity of challenges, all options need to be considered. Supply-side measures should be implemented immediately, focussing on those that allow the production of more agricultural product per unit of input. For demand-side measures, given the difficulties in their implementation and lag in their effectiveness, policy should be introduced quickly, and should aim to codeliver to other policy agenda, such as improving environmental quality or improving dietary health. These problems facing humanity in the 21st Century are extremely challenging, and policy that addresses multiple objectives is required now more than ever.

The physicochemical characteristics and anaerobic degradability of desiccated coconut industry waste water

Desiccated coconut industries (DCI) create various intermediates from fresh coconut kernel for cosmetic, pharmaceutical and food industries. The mechanized and non-mechanized DCI process between 10,000 and 100,000 nuts/day to discharge 6-150 m(3) of malodorous waste water leading to a discharge of 2646642 kg chemical oxygen demand (COD) daily. In these units, three main types of waste water streams are coconut kernel water, kernel wash water and virgin oil waste water. The effluent streams contain lipids (1-55 g/l), suspended solids (6-80 g/l) and volatile fatty acids (VFA) at concentrations that are inhibitory to anaerobic bacteria. Coconut water contributes to 20-50 % of the total volume and 50-60 % of the total organic loads and causes higher inhibition of anaerobic bacteria with an initial lag phase of 30 days. The lagooning method of treatment widely adopted failed to appreciably treat the waste water and often led to the accumulation of volatile fatty acids (propionic acid) along with long-chain unsaturated free fatty acids. Biogas generation during biological methane potential (BMP) assay required a 15-day adaptation time, and gas production occurred at low concentrations of coconut water while the other two streams did not appear to be inhibitory. The anaerobic bacteria can mineralize coconut lipids at concentrations of 175 mg/l; however; they are severely inhibited at a lipid level of = 350 mg/g bacterial inoculum. The modified Gompertz model showed a good fit with the BMP data with a simple sigmoid pattern. However, it failed to fit experimental BMP data either possessing a longer lag phase and/or diauxic biogas production suggesting inhibition of anaerobic bacteria.

Time-temperature histories of spherical food products during bulk forced-air precooling

A general mathematical model for forced air precooling of spherical food products in bulk is developed. The food products are arranged inline to form a rectangular parallelepiped. Chilled air is blown along the height of the package. The governing equations for the transient two-dimensional conduction with internal heat generation in the product, simultaneous heat and mass transfer at the product-air interface and one-dimensional transient energy and species conservation equations for the moist air are solved numerically using finite difference methods. Results are presented in the form of time-temperature histories. Experiments are conducted with model foods in a laboratory scale air precooling tunnel. The agreement between the theoretical and experimental results is found to be good. In general, a single product analysis fails to predict the precooling characteristics of bulk loads of food products. In the range of values investigated, the respiration heat is found to have a negligible effect.

Micro-scale anaerobic digestion of point source components of organic fraction of municipal solid waste

The fermentation characteristics of six specific types of the organic fraction of municipal solid waste (OFMSW) were examined, with an emphasis on properties that are needed when designing plug-flow type anaerobic bioreactors. More specifically, the decomposition patterns of a vegetable (cabbage), fruits (banana and citrus peels), fresh leaf litter of bamboo and teak leaves, and paper (newsprint) waste streams as feedstocks were studied. Individual OFMSW components were placed into nylon mesh bags and subjected to various fermentation periods (solids retention time, SRT) within the inlet of a functioning plug-flow biogas fermentor. These were removed at periodic intervals, and their composition was analyzed to monitor decomposition rates and changes in chemical composition. Components like cabbage waste, banana peels, and orange peels fermented rapidly both in a plug-flow biogas reactor (PFBR) as well as under a biological methane potential (BMP) assay, while other OFMSW components (leaf litter from bamboo and teak leaves and newsprint) fermented slowly with poor process stability and moderate biodegradation. For fruit and vegetable wastes (FVW), a rapid and efficient removal of pectins is the main cause of rapid disintegration of these feedstocks, which left behind very little compost forming residues (2–5%). Teak and bamboo leaves and newsprint decomposed only to 25–50% in 30 d. These results confirm the potential for volatile fatty acids accumulation in a PFBR’s inlet and suggest a modification of the inlet zone or operation of a PFBR with the above feedstocks.

Swarm intelligence-based solver for parameter estimation of laboratory through-diffusion transport of contaminants

Theoretical approaches are of fundamental importance to predict the potential impact of waste disposal facilities on ground water contamination. Appropriate design parameters are generally estimated be fitting theoretical models to data gathered from field monitoring or laboratory experiments. Transient through-diffusion tests are generally conducted in the laboratory to estimate the mass transport parameters of the proposed barrier material. Thes parameters are usually estimated either by approximate eye-fitting calibration or by combining the solution of the direct problem with any available gradient-based techniques. In this work, an automated, gradient-free solver is developed to estimate the mass transport parameters of a transient through-diffusion model. The proposed inverse model uses a particle swarm optimization (PSO) algorithm that is based on the social behavior of animals searching for food sources. The finite difference numerical solution of the forward model is integrated with the PSO algorithm to solve the inverse problem of parameter estimation. The working principle of the new solver is demonstrated and mass transport parameters are estimated from laboratory through-diffusion experimental data. An inverse model based on the standard gradient-based technique is formulated to compare with the proposed solver. A detailed comparative study is carried out between conventional methods and the proposed solver. The present automated technique is found to be very efficient and robust. The mass transport parameters are obtained with great precision.

Optimal simultaneous maximum a posterioriestimation of states, noise statistics and parameters I. Algorithm

The simultaneous state and parameter estimation problem for a linear discrete-time system with unknown noise statistics is treated as a large-scale optimization problem. The a posterioriprobability density function is maximized directly with respect to the states and parameters subject to the constraint of the system dynamics. The resulting optimization problem is too large for any of the standard non-linear programming techniques and hence an hierarchical optimization approach is proposed. It turns out that the states can be computed at the first levelfor given noise and system parameters. These, in turn, are to be modified at the second level.The states are to be computed from a large system of linear equations and two solution methods are considered for solving these equations, limiting the horizon to a suitable length. The resulting algorithm is a filter-smoother, suitable for off-line as well as on-line state estimation for given noise and system parameters. The second level problem is split up into two, one for modifying the noise statistics and the other for modifying the system parameters. An adaptive relaxation technique is proposed for modifying the noise statistics and a modified Gauss-Newton technique is used to adjust the system parameters.

Optimal simultaneous maximum a posterioriestimation of states, noise statistics and parameters II. Numerical performance

A very general and numerically quite robust algorithm has been proposed by Sastry and Gauvrit (1980) for system identification. The present paper takes it up and examines its performance on a real test example. The example considered is the lateral dynamics of an aircraft. This is used as a vehicle for demonstrating the performance of various aspects of the algorithm in several possible modes.

Constitutive model for municipal solid waste incorporating mechanical creep and biodegradation-induced compression

A constitutive model is proposed to describe the stress-strain behavior of municipal solid waste (MSW) under loading using the critical state soil mechanics framework. The modified cam clay model is extended to incorporate the effects of mechanical creep and time dependent biodegradation to calculate total compression under loading. Model parameters are evaluated based on one-dimensional compression and triaxial consolidated undrained test series conducted on three types of MSW: (a) fresh MSW obtained from working phase of a landfill, (b) landfilled waste retrieved from a landfill after 1.5 years of degradation, and (c) synthetic MSW with controlled composition. The model captures the stress-strain and pore water pressure response of these three types of MSW adequately. The model is useful for assessing the deformation and stability of landfills and any post-closure development structures located on landfills.

Fuzzy waste load allocation model: a multiobjective approach

Fuzzy Waste Load Allocation Model (FWLAM), developed in an earlier study, derives the optimal fractional levels, for the base flow conditions, considering the goals of the Pollution Control Agency (PCA) and dischargers. The Modified Fuzzy Waste Load Allocation Model (MFWLAM) developed subsequently is a stochastic model and considers the moments (mean, variance and skewness) of water quality indicators, incorporating uncertainty due to randomness of input variables along with uncertainty due to imprecision. The risk of low water quality is reduced significantly by using this modified model, but inclusion of new constraints leads to a low value of acceptability level, A, interpreted as the maximized minimum satisfaction in the system. To improve this value, a new model, which is a combination Of FWLAM and MFWLAM, is presented, allowing for some violations in the constraints of MFWLAM. This combined model is a multiobjective optimization model having the objectives, maximization of acceptability level and minimization of violation of constraints. Fuzzy multiobjective programming, goal programming and fuzzy goal programming are used to find the solutions. For the optimization model, Probabilistic Global Search Lausanne (PGSL) is used as a nonlinear optimization tool. The methodology is applied to a case study of the Tunga-Bhadra river system in south India. The model results in a compromised solution of a higher value of acceptability level as compared to MFWLAM, with a satisfactory value of risk. Thus the goal of risk minimization is achieved with a comparatively better value of acceptability level.

Worst inputs and a bound on the highest peak statistics of a class of non-linear systems

A method is developed by which the input leading to the highest possible response in an interval of time can be determined for a class of non-linear systems. The input, if deterministic, is constrained to have a known finite energy (or norm) in the interval under consideration. In the case of random inputs, the energy is constrained to have a known probability distribution function. The approach has applications when a system has to be put to maximum advantage by getting the largest possible output or when a system has to be designed to the highest maximum response with only the input energy or the energy distribution known. The method is also useful in arriving at a bound on the highest peak distribution of the response, when the excitation is a known random process.As an illustration the Duffing oscillator has been analysed and some numerical results have also been presented.

The Mechanics and Statistics of Active Matter

Active particles contain internal degrees of freedom with the ability to take in and dissipate energy and, in the process, execute systematic movement. Examples include all living organisms and their motile constituents such as molecular motors. This article reviews recent progress in applying the principles of nonequilibrium statistical mechanics and hydrodynamics to form a systematic theory of the behavior of collections of active particles-active matter-with only minimal regard to microscopic details. A unified view of the many kinds of active matter is presented, encompassing not only living systems but inanimate analogs. Theory and experiment are discussed side by side.

Analysis of co-current hydraircooling of food products in bulk

A mathematical model is developed to describe the hydraircooling process when the water and air are flowing in the same direction. The governing equations for the simultaneous heat and mass transfer are solved using finite-difference numerical methods. The half cooling time of the food products is correlated as a function of the dimensionless process parameters. It is observed that a process time of approximately double the half cooling time will result in the food products attaining almost a steady state. The process times of the bulk hydraircooling process and the bulk air precooling process are compared.