Abstract: Reactive nitrogen (Nr) is an indispensable nutrient for agricultural production and human alimentation. Simultaneously, agriculture is the largest contributor to Nr pollution, causing severe damages to human health and ecosystem services. The trade-off between food availability and Nr pollution can be attenuated by several key mitigation options, including Nr efficiency improvements in crop and animal production systems, food waste reduction in households and lower consumption of Nr-intensive animal products. However, their quantitative mitigation potential remains unclear, especially under the added pressure of population growth and changes in food consumption. Here we show by model simulations, that under baseline conditions, Nr pollution in 2050 can be expected to rise to 102-156% of the 2010 value. Only under ambitious mitigation, does pollution possibly decrease to 36-76% of the 2010 value. Air, water and atmospheric Nr pollution go far beyond critical environmental thresholds without mitigation actions. Even under ambitious mitigation, the risk remains that thresholds are exceeded.

Abstract: An environmental dynamic system is usually modeled as a nonlinear system described by a set of nonlinear ODEs. A central challenge in computational modeling of environmental systems is the determination of the model parameters. In these cases, estimating these variables or parameters from other easily obtained measurements can be extremely useful. This work addresses the problem of monitoring and modeling a leaf area index and soil moisture model (LSM) using state estimation. The performances of various conventional and state-of-the-art state estimation techniques are compared when they are utilized to achieve this objective. These techniques include the extended Kalman filter (EKF), particle filter (PF), and the more recently developed technique variational filter (VF). Specifically, two comparative studies are performed. In the first comparative study, the state variables (the leaf-area index LAI, the volumetric water content of the soil layer 1, HUR1 and the volumetric water content of the soil layer 2, HUR2) are estimated from noisy measurements of these variables, and the various estimation techniques are compared by computing the estimation root mean square error (RMSE) with respect to the noise-free data. In the second comparative study, the state variables as well as the model parameters are simultaneously estimated. In this case, in addition to comparing the performances of the various state estimation techniques, the effect of number of estimated model parameters on the accuracy and convergence of these techniques are also assessed. The results of both comparative studies show that the PF provides a higher accuracy than the EKF, which is due to the limited ability of the EKF to handle highly nonlinear processes. The results also show that the VF provides a significant improvement over the PF because, unlike the PF which depends on the choice of sampling distribution used to estimate the posterior distribution, the VF yields an optimum choice of the sampling distribution, which also accounts for the observed data. The results of the second comparative study show that, for all techniques, estimating more model parameters affects the estimation accuracy as well as the convergence of the estimated states and parameters. However, the VF can still provide both convergence as well as accuracy related advantages over other estimation methods. (C) 2013 Elsevier B.V. All rights reserved.

Abstract: The impact of land use changes on sustainable development is of increasing interest in many regions of the world. This study aimed to test the transferability of the Framework for Participatory Impact Assessment (FoPIA), which was originally developed in the European context, to developing countries, in which lack of data often prevents the use of data-driven impact assessment methods. The core aspect of FoPIA is the stakeholder-based assessment of alternative land use scenarios. Scenario impacts on regional sustainability are assessed by using a set of nine regional land use functions (LUFs), which equally cover the economic, social and environmental dimensions of sustainability. The cases analysed in this study include (1) the alternative spatial planning policies around the Merapi volcano and surrounding areas of Yogyakarta City, Indonesia; (2) the large-scale afforestation of agricultural areas to reduce soil erosion in Guyuan, China; (3) the expansion of soil and water conservation measures in the Oum Zessar watershed, Tunisia; (4) the agricultural intensification and the potential for organic agriculture in Bijapur, India; and (5) the land degradation and land conflicts resulting from land division and privatisation in Narok, Kenya. All five regions are characterised by population growth, partially combined with considerable economic development, environmental degradation problems and social conflicts. Implications of the regional scenario impacts as well as methodological aspects are discussed. Overall, FoPIA proved to be a useful tool for diagnosing regional human-environment interactions and for supporting the communication and social learning process among different stakeholder groups.