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Much attention has been paid to burden shifting of CO2 emissions from developed regions to developing regions through trade. However, less discussed is that trade also acts as a mechanism enabling wealthy consumers to shift water quantity and quality stress to their trading partners. In this study, we investigate how Shanghai, the largest megacity in China, draws water resources from all over China and outsources its pollution through virtual quantity and quality water flows associated with trade. The results show that Shanghai''s consumption of goods and services in 2007 led to 11.6 billion m3 of freshwater consumption, 796 thousand tons of COD, and 16.2 thousand tons of NH3-N in discharged wastewater. Of this, 79% of freshwater consumption, 82.9% of COD and 82.5% of NH3-N occurred in other Chinese Provinces which provide goods and services to Shanghai. Thirteen Provinces with severe and extreme water quantity stress accounted for 60% of net virtual water import to Shanghai, while 19 Provinces experiencing water quality stress endured 79% of net COD outsourcing and 75.5% of net NH3-N outsourcing from Shanghai. In accordance with the three "redlines" recently put forward by the Chinese central government to control water pollution and cap total water use in all provinces, we suggest that Shanghai should share its responsibility for reducing water quantity and quality stress in its trading partners through taking measures at provincial, industrial, and consumer levels. In the meantime, Shanghai needs to enhance demand side management by promoting low water intensity consumption.

It is well-recognised that to achieve long-term sustainable and resilient land management we need to understand the coupled dynamics of social and ecological systems. Land use change scenarios will often aim to understand (i) the behaviours of land management, influenced by direct and indirect drivers, (ii) the resulting changes in land use and (iii) the environmental implications of these changes. While the literature in this field is extensive, approaches to parameterise coupled systems through integration of empirical social science based models and ecology based models still need further development. We propose an approach to land use dynamics modelling based on the integration of behavioural models derived from choice experiments and spatially explicit systems dynamics modelling. This involves the specification of a choice model to parameterise land use behaviour and the integration with a spatial habitat succession model. We test this approach in an upland socio-ecological system in the United Kingdom. We conduct a choice experiment with land managers in the Peak District National Park. The elicited preferences form the basis for a behavioural model, which is integrated with a habitat succession model to predict the landscape level vegetation impacts. The integrated model allows us to create projections of how land use may change in the future under different environmental and policy scenarios, and the impact this may have on landscape vegetation patterns. We illustrate this by showing future projection of landscape changes related to hypothetical changes to EU level agricultural management incentives. The advantages of this approach are (i) the approach takes into account potential environmental and management feedbacks, an aspect often ignored in choice modelling, (ii) the behavioural rules are revealed from actual and hypothetical choice data, which allow the research to test the empirical evidence for various determinants of choice, (iii) the behavioural choice models generate probabilities of alternative behaviours which make them ideally suited for integration with simulation models. The paper concludes that the modelling approach offers a promising route for linking socio-economic and ecological features of socio-ecological systems. Furthermore, our proposed approach allows testing of the underlying socio-economic and environmental drivers and their interaction in real environmental systems.

It is well-recognised that to achieve long-term sustainable and resilient land management we need to understand the coupled dynamics of social and ecological systems. Land use change scenarios will often aim to understand (i) the behaviours of land management, influenced by direct and indirect drivers, (ii) the resulting changes in land use and (iii) the environmental implications of these changes. While the literature in this field is extensive, approaches to parameterise coupled systems through integration of empirical social science based models and ecology based models still need further development. We propose an approach to land use dynamics modelling based on the integration of behavioural models derived from choice experiments and spatially explicit systems dynamics modelling. This involves the specification of a choice model to parameterise land use behaviour and the integration with a spatial habitat succession model. We test this approach in an upland socio-ecological system in the United Kingdom. We conduct a choice experiment with land managers in the Peak District National Park. The elicited preferences form the basis for a behavioural model, which is integrated with a habitat succession model to predict the landscape level vegetation impacts. The integrated model allows us to create projections of how land use may change in the future under different environmental and policy scenarios, and the impact this may have on landscape vegetation patterns. We illustrate this by showing future projection of landscape changes related to hypothetical changes to EU level agricultural management incentives. The advantages of this approach are (i) the approach takes into account potential environmental and management feedbacks, an aspect often ignored in choice modelling, (ii) the behavioural rules are revealed from actual and hypothetical choice data, which allow the research to test the empirical evidence for various determinants of choice, (iii) the behavioural choice models generate probabilities of alternative behaviours which make them ideally suited for integration with simulation models. The paper concludes that the modelling approach offers a promising route for linking socio-economic and ecological features of socio-ecological systems. Furthermore, our proposed approach allows testing of the underlying socio-economic and environmental drivers and their interaction in real environmental systems.

This paper reviews different approaches to modelling the energy transition towards a zero carbon economy. It identifies a number of limitations in current approaches such as a lack of consideration of out-of-equilibrium situations (like an energy transition) and non-linear feedbacks. To tackle those issues, the new open source integrated assessment model pymedeas is introduced, which allows the exploration of the design and planning of appropriate strategies and policies for decarbonizing the energy sector at World and EU level. The main novelty of the new open-source model is that it addresses the energy transition by considering biophysical limits, availability of raw materials, and climate change impacts. This paper showcases the model capabilities through several simulation experiments to explore alternative pathways for the renewable transition. In the selected scenarios of this work, future shortage of fossil fuels is found to be the most influential factor of the simulations system evolution. Changes in efficiency and climate change damages are also important determinants influencing model outcomes.

This paper reviews different approaches to modelling the energy transition towards a zero carbon economy. It identifies a number of limitations in current approaches such as a lack of consideration of out-of-equilibrium situations (like an energy transition) and non-linear feedbacks. To tackle those issues, the new open source integrated assessment model pymedeas is introduced, which allows the exploration of the design and planning of appropriate strategies and policies for decarbonizing the energy sector at World and EU level. The main novelty of the new open-source model is that it addresses the energy transition by considering biophysical limits, availability of raw materials, and climate change impacts. This paper showcases the model capabilities through several simulation experiments to explore alternative pathways for the renewable transition. In the selected scenarios of this work, future shortage of fossil fuels is found to be the most influential factor of the simulations system evolution. Changes in efficiency and climate change damages are also important determinants influencing model outcomes.

This paper reviews different approaches to modelling the energy transition towards a zero carbon economy. It identifies a number of limitations in current approaches such as a lack of consideration of out-of-equilibrium situations (like an energy transition) and non-linear feedbacks. To tackle those issues, the new open source integrated assessment model pymedeas is introduced, which allows the exploration of the design and planning of appropriate strategies and policies for decarbonizing the energy sector at World and EU level. The main novelty of the new open-source model is that it addresses the energy transition by considering biophysical limits, availability of raw materials, and climate change impacts. This paper showcases the model capabilities through several simulation experiments to explore alternative pathways for the renewable transition. In the selected scenarios of this work, future shortage of fossil fuels is found to be the most influential factor of the simulations system evolution. Changes in efficiency and climate change damages are also important determinants influencing model outcomes.

This paper reviews different approaches to modelling the energy transition towards a zero carbon economy. It identifies a number of limitations in current approaches such as a lack of consideration of out-of-equilibrium situations (like an energy transition) and non-linear feedbacks. To tackle those issues, the new open source integrated assessment model pymedeas is introduced, which allows the exploration of the design and planning of appropriate strategies and policies for decarbonizing the energy sector at World and EU level. The main novelty of the new open-source model is that it addresses the energy transition by considering biophysical limits, availability of raw materials, and climate change impacts. This paper showcases the model capabilities through several simulation experiments to explore alternative pathways for the renewable transition. In the selected scenarios of this work, future shortage of fossil fuels is found to be the most influential factor of the simulations system evolution. Changes in efficiency and climate change damages are also important determinants influencing model outcomes.

This paper reviews different approaches to modelling the energy transition towards a zero carbon economy. It identifies a number of limitations in current approaches such as a lack of consideration of out-of-equilibrium situations (like an energy transition) and non-linear feedbacks. To tackle those issues, the new open source integrated assessment model pymedeas is introduced, which allows the exploration of the design and planning of appropriate strategies and policies for decarbonizing the energy sector at World and EU level. The main novelty of the new open-source model is that it addresses the energy transition by considering biophysical limits, availability of raw materials, and climate change impacts. This paper showcases the model capabilities through several simulation experiments to explore alternative pathways for the renewable transition. In the selected scenarios of this work, future shortage of fossil fuels is found to be the most influential factor of the simulations system evolution. Changes in efficiency and climate change damages are also important determinants influencing model outcomes.

This paper reviews different approaches to modelling the energy transition towards a zero carbon economy. It identifies a number of limitations in current approaches such as a lack of consideration of out-of-equilibrium situations (like an energy transition) and non-linear feedbacks. To tackle those issues, the new open source integrated assessment model pymedeas is introduced, which allows the exploration of the design and planning of appropriate strategies and policies for decarbonizing the energy sector at World and EU level. The main novelty of the new open-source model is that it addresses the energy transition by considering biophysical limits, availability of raw materials, and climate change impacts. This paper showcases the model capabilities through several simulation experiments to explore alternative pathways for the renewable transition. In the selected scenarios of this work, future shortage of fossil fuels is found to be the most influential factor of the simulations system evolution. Changes in efficiency and climate change damages are also important determinants influencing model outcomes.

13 pages, 7 figures, 4 tables, 3 appendixes, supplementary data https://doi.org/10.1016/j.rser.2020.110105 ; This paper reviews different approaches to modelling the energy transition towards a zero carbon economy. It identifies a number of limitations in current approaches such as a lack of consideration of out-of-equilibrium situations (like an energy transition) and non-linear feedbacks. To tackle those issues, the new open source integrated assessment model pymedeas is introduced, which allows the exploration of the design and planning of appropriate strategies and policies for decarbonizing the energy sector at World and EU level. The main novelty of the new open-source model is that it addresses the energy transition by considering biophysical limits, availability of raw materials, and climate change impacts. This paper showcases the model capabilities through several simulation experiments to explore alternative pathways for the renewable transition. In the selected scenarios of this work, future shortage of fossil fuels is found to be the most influential factor of the simulations system evolution. Changes in efficiency and climate change damages are also important determinants influencing model outcomes ; This work was supported by the European Union through the funding of the MEDEAS project under the Horizon 2020 research and innovation programme [grant agreement No 69128] ; Peer reviewed