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Within scenario-based research of social-ecological systems, there has been a growing recognition of the importance of normative scenarios that define positive outcomes for both nature and society. While several frameworks exist to guide the co-creation of normative scenario narratives, examples of operationalizing these narratives in quantitative simulation modelling are still limited. To address this gap, this paper presents an example of how aspects of normative scenarios can be realized within a spatial model of land use and land cover change. This is achieved through a combination of data-driven approaches to encapsulate scenario-specific differences in local and global scale phenomena, as well as iterative expert elicitation to quantify descriptive trends from narratives. This approach is demonstrated with a case study simulating five scenarios of landscape change (three normative and two exploratory) in Switzerland between 2020 and 2060. The resulting maps of future land use and land cover exhibited distinct variations between the scenarios, notably with regard to the prevalence of areas of heterogeneous semi-natural land, such as alpine pastures and grassland, often considered culturally emblematic of Switzerland. While the simulation results were generally consistent with the outcomes expressed in the scenario narratives, following a process of expert feedback, we reflect that there are clear challenges in leveraging such results to elicit further discussions as to the desirability and plausibility of future scenarios. Specifically, the need to summarize spatial simulations in a manner that is easily interpretable and encourages consideration of the broader patterns of change rather than focusing on fine-scale details. [ABSTRACT FROM AUTHOR]

Abstract Road-based transport is a significant contributor to global transport emissions of greenhouse gases and local pollutants, thus contributing to the environmental impact of the mobility of people and goods. In order to develop strategies to mitigate this impact, it is necessary to build reliable emission inventories that include sector-specific emissions. Furthermore, the methods for creating these inventories should be applicable for forecasts and scenario calculations to facilitate the evaluation of pathways towards a more sustainable transport system. The study at hand proposes a model-based framework to predict travel demand and its spatial distribution for a bottom-up calculation of road transport emissions in Europe. With this framework, it is possible to calculate emissions based on the road network structure, traffic flows and vehicle types. In order to demonstrate the applicability of the framework for scenario calculations, it is applied to three exemplary scenarios where population data is modified. With the developed methodology, a tool for the large-scale assessment of emissions from road transport is provided, which is able to simulate the impact of socio-economic and economic changes on these emissions.

Nature‐inclusive scenarios of the future can help address numerous societal challenges related to soil health. As nature‐inclusive scenarios imply sustainable management of natural systems and resources, land use and soil health are assumed to be mutually beneficial in such scenarios. However, the interplay between nature‐inclusive land use scenarios and soil health has never been modelled using digital soil mapping. We predicted soil organic matter (SOM), an important indicator of soil health, in 2050, based on a recently developed nature‐inclusive scenario and machine learning in 3D space and time in the Netherlands. By deriving dynamic covariates related to land use and the occurrence of peat for 2050, we predicted SOM and its uncertainty in 2050 and assessed SOM changes between 2022 and 2050 from 0 to 2 m depth at 25 m resolution. We found little changes in the majority of mineral soils. However, SOM decreases of up to 5% were predicted in grasslands used for animal‐based production systems in 2022, which transitioned into croplands for plant‐based production systems by 2050. Although increases up to 25% SOM were predicted between 0 and 40 cm depth in rewetted peatlands, even larger decreases, on reclaimed land even surpassing 25% SOM, were predicted on non‐rewetted land in peat layers below 40 cm depth. There were several limitations to our approach, mostly due to predicting future trends based on historic data. Furthermore, nuanced nature‐inclusive practices, such as the adoption of agroecological farming methods, were too complex to incorporate in the model and would likely affect SOM spatial variability. Nonetheless, 3D‐mapping of SOM in 2050 created new insights and raised important questions related to soil health behind nature‐inclusive scenarios. Using machine learning explicit in 3D space and time to predict the impact of future scenarios on soil health is a useful tool for facilitating societal discussion, aiding policy making and promoting transformative change. [ABSTRACT FROM AUTHOR]

Road-based transport is a significant contributor to global transport emissions of greenhouse gases and local pollutants, thus contributing to the environmental impact of the mobility of people and goods. In order to develop strategies to mitigate this impact, it is necessary to build reliable emission inventories that include sector-specific emissions. Furthermore, the methods for creating these inventories should be applicable for forecasts and scenario calculations to facilitate the evaluation of pathways towards a more sustainable transport system. The study at hand proposes a model-based framework to predict travel demand and its spatial distribution for a bottom-up calculation of road transport emissions in Europe. With this framework, it is possible to calculate emissions based on the road network structure, traffic flows and vehicle types. In order to demonstrate the applicability of the framework for scenario calculations, it is applied to three exemplary scenarios where population data is modified. With the developed methodology, a tool for the large-scale assessment of emissions from road transport is provided, which is able to simulate the impact of socio-economic and economic changes on these emissions. [ABSTRACT FROM AUTHOR]

The investigation of the impact of energy consumption patterns on peak emissions in China is pertinent and crucial for achieving global climate goals. The study aims to form a forecast of carbon emissions in China and diagnose the achievement of established decarbonization goals based on structural changes in primary energy consumption until 2030. To achieve the goal, the study formed a Dynamic stochastic general equilibrium (DSGE) model with the implementation of Markov chains. The obtained research results yield important insights into the influence of various scenarios on carbon emissions in China by the year 2030. Specifically, considering structural transformations, an increase in emissions by 15 % can be anticipated, which is 7 % less than predicted by the classical scenario. Among the proposed scenarios, the Net Zero scenario is deemed the most efficient, where emissions could reach a level of 8509.5 million tons of CO₂. Conversely, the New Momentum scenario proves to be the most precarious, as it entails an escalation in coal usage, leading to a 4 % increase in emissions, amounting to 13264.84 million tons of CO₂. The contribution of this study is the approach to conducting carbon emission projections, which is based on the DSGE model with the implementation of Markov chains. This makes it possible to assess the adequacy of the set targets for carbon reduction based on alternative scenarios, which in crisis conditions can overlap and thus complement each other.

Mpox is a viral disease caused by the monkey pox virus (MPXV) of the Poxviridae family. It is similar to smallpox and cowpox. Mpox is not categorized as a sexually transmitted infection, however, most transmission in the recent global outbreak has been attributed to be through men who have sex with men (MSM). Agent-based modelling (ABM) is an effective approach to simulate the spread of Mpox because it enables the detailed representation of heterogeneity among individuals or sub-populations, including variations in behaviour, susceptibility to disease, and contact patterns. This is crucial for accurately modelling diseases in populations with long tailed distributions of characteristics such as sexual activity, that has been seen in the recent Mpox outbreak. Two ABMs are presented in this paper which simulate the spread of Mpox in an artificial population. The parameters for contact formation and dissolution are drawn from the NATSAL-3 dataset (National Survey of Sexual Attitudes and Lifestyles) (Mercer et al. 2013). The presented ABMs are based on the principles of the classic compartmental Susceptible-Exposed-Infected-Recovered (SEIR) model and complexity is further added to break the assumptions of homogeneous mixing and populations. The first ABM is based on an heterogeneous population, consisting of people from two self-identified genders (male and female) and three sexual preferences: homosexual, bi-sexual and heterosexual. The second ABM is a subset of the first ABM, that focuses on the MSM population, which is considered to be at high-risk of Mpox. We report a set of experiments modelling relevant scenarios by number of imported cases, number of super-spreader events, and different vaccination strategies. Our analysis concludes that Mpox infection reaches locally stable disease-free equilibrium in the absence of concurrent partnerships. Our simulations demonstrate that prioritizing vaccines for the MSM population can significantly reduce the effective R value from 1.62 to 0.19, highlighting the potential impact of targeted vaccination strategies in mitigating Mpox transmission. [ABSTRACT FROM AUTHOR]

This paper presents and demonstrates a novel scenario-building methodology that integrates contextual and future time uncertainty into the performance assessment of water distribution networks (WDNs). A three-step approach is proposed: (i) System context analysis, identifying the main key factors that impact the WDN performance; (ii) Scenario definition, identifying the implicated WDN variables, describing its possible evolution, and conjugating them to further establish the reference scenario and the two most relevant and opposite ones; and (iii) Scenario modelling, simulating the WDN behaviour for those scenarios. The obtained spatial and temporal hydraulic results are further used to calculate performance metrics. The methodology is applied to a real WDN to assess resilience performance considering infrastructure asset robustness (real water loss performance indicator), service reliability (minimum pressure index), and service flexibility (network resilience index). A new formulation to assess the metric evolution over time is proposed, deducting the further-away performance results by using an uncertainty weight. The results demonstrate that the increase in metric amplitude for the opposite scenarios over time highlights future uncertainty, reflecting context uncertainty, and the comparison of metric spatial distribution (i.e., at the pipe/node levels) highlights critical areas with higher associated uncertainty. [ABSTRACT FROM AUTHOR]

Water electrolysis for hydrogen production with renewable electricity is regularly studied as an option for decarbonised future energy scenarios. The inclusion of byproduct electrolytic oxygen capture and sale is of interest for parallel decarbonisation efforts elsewhere in the industry and could contribute to reducing green hydrogen costs. A deterministic hydrogen electrolysis system model is constructed to compare oxygen inclusion/exclusion scenarios. This uses wind and solar-PV electricity generation timeseries, a power-dependent electrolysis model to determine the energy efficiency of gas yield, and power allocation for gas post-processing energy within each hourly timestep. This maintains a fully renewable (and therefore low/zero carbon) electricity source for electrolysis and gas post-processing. The model is validated (excluding oxygen) against an existing low-cost GW-scale solar-hydrogen production scenario and an existing hydrogen production costs study with offshore wind generation at the multi-MW scale. For both comparisons, oxygen inclusion is then evaluated to demonstrate both the benefits and drawbacks of capture and utilisation, for different scenario conditions, and high parameter sensitivity can be seen regarding the price of renewable electricity. This work subsequently proposes that the option for the potential utilisation of byproduct oxygen should be included in future research to exemplify otherwise missed benefits. [ABSTRACT FROM AUTHOR]

Sustainable diets must consider health, economic, environmental, and social outcomes. The development and production of alternative protein foods should also make these considerations. We examined the nutritional role of these foods, with New Zealand (NZ) as a case study.We used the DELTA Model® to assess 2020 NZ nutrient supply. We then simulated the substitution of 50% of meat supply (by mass) with various plant protein sources (soy, peas, beans, and mushroom), and observed the impact on nutrient supply.NZ had an undersupply of calcium (38%), vitamin E (34% deficit), dietary fibre (20%), potassium (13%), and vitamin C (10%) compared to population requirements. Contrastingly, there was sufficient protein and amino acid supply for an additional 2.4 million people. Halving of meat supply resulted in decreased availability for potassium (21% deficit), zinc (17%), folate (10%), and iron (9%).Soy proved the best nutritional replacement for meat, with reduced deficits for all undersupplied nutrients compared to 2020. Replacement with other modelled protein sources resulted in greater nutrient deficits.The nutritional implications beyond protein must be considered when making dietary substitutions. There are clear public health reasons to fortify alternative proteins with both the nutrients lost in substitution and those already in deficit. [ABSTRACT FROM AUTHOR]

The goals set forth by the European Green Deal require extensive preparation and coordination of all stakeholders. As a valuable tool, energy scenarios can generate the necessary information for stakeholders to envision the right steps in preparing this transition. The manufacturing industries represent an especially important sector to investigate. They are responsible for both high energy consumption and GHG emission figures on the one hand side and provide great economic value for member countries on the other. We aim to provide a close investigation of all thirteen industrial subsectors that can be used as a solid information basis both for stakeholders within the manufacturing industries and policymakers. Our approach includes all industrial production processes. We achieve this by considering both transformation processes, such as blast furnaces or industrial power plants, and final energy-application. In addition, both scope 1 and 2 emissions of manufacturing industry are assessed in an effort to transparently indicate the interdependencies of industrial decarbonisation efforts with the overall energy system. We propose the integration of a novel stakeholder-based scenario, that puts special emphasis on first-hand information on mid to long-term planning of key industrial representatives, thereby going beyond existing scenario narratives (e.g., scenarios according to the European Monitoring Mechanism). Thus, a balanced deep decarbonisation scenario using best-available technologies can be compared with existing industry plans. To address these points, we have chosen Austria as a case study. Results indicate that industry stakeholders are in general agreement on their subsector-specific technology deployment and already envision investments towards a low-carbon pathway for their respective subsectors. While today's manufacturing industries rely at large on a great diversity of (mostly fossil) energy carrier supply, deeply decarbonised manufacturing industries of the future may be based on the following main energy carriers; electricity, CO2-neutral gases, and biomass. To mitigate emissions from geogenic sources, carbon capture technologies are needed. On the other hand, the synthesis of olefins in the chemical industry may provide a sink for CO2 assuming long-term use after production. In addition to the option of using it across subsectors, captured CO2 will have to be stored or sold to other economies. Comparison of the developed scenarios allows the identification of no-regret measures to enable climate neutrality by 2050 that should be deployed as soon as possible by push and pull incentives. The model results of the two transition scenarios show the need for technology promotion as well as infrastructure development needs and allow the identification of possible corridors, focal points, and fuel shifts – on the subsector level as well as in energy policy. Among others, the modelled magnitude of renewable energy consumption shows the need for swift expansion of existing national renewable energy potentials and energy infrastructure, especially for energy intensive industry regions. In light of the current energy consumption in other economic sectors (most notably in buildings or transport) and limited renewable potentials, large import shares of national gross domestic energy consumption are likely for Austria in the future.

Today's fast-changing environment for construction companies requires rapid responses and adaptation of their projects. Despite the multitude of tools applied for project cost management in engineering and construction companies, there is a need to form comprehensive solutions. The purpose of the study is to form a methodological approach to project cost management in the field of engineering construction based on alternative models to diagnose the development, assessment and selection of functional areas and content of cost management in the construction project, which allows one to increase adaptability and flexibility in the process of its implementation. The basis of research methodology is modeling, which allows one to adjust the economic and financial flows based on three S-curves, one for each component of the total cost of the work: direct costs, indirect costs and reserves. These curves include the direct cost curve for the main purchasing packages as well. This brings financial flows closer to reality because it is possible to adjust the S-curves according to the behavior of each subsystem. The contribution of the study is the proposed approach of integrating concepts related to the coordination and development of project design and production management (lean construction), forming a "3D model of management", in a broad and comprehensive management system. It assumes a comprehensive and complete way to manage civil engineering projects. The proposed methodological approach can make a significant contribution to the preparation of forecasts and estimates by planners and controllers in the context of construction projects. [ABSTRACT FROM AUTHOR]

In spite of, the importance of sustainability, and its concept and protection begun in the 1970s. Yet, with framework for action 2005-2025, it integrated risk prevention strategies into sustainable development activities. Whilst, Al-Hillah is the city center of important location near the holy governorate is surrounded by archaeological sites back to more than 4 000 years ago. These features make it perfect city as the case study. Parctically, this article compares multiple planning to obtain an effective scenario that manages events of operations before, during, and after the disaster. By creating a proactive scenario can based on indicators inspired from population density, easy access of traffic movement, and the shortest time at road intersections, barriers, and land uses. The article process represented by spatial analysis a12 planned based on the parameters, to choose the preferred evocation scenarios. Firstly, combined between rout and service network analysis to evaluate roads of the city by the shortest time, number of barriers, intersection, construction of shrouding zone and density of population. That result scenario (B) is selected, which protection for (19.08%) of the city's population within a radius of two zones (0-4000), (4000-7000) m, followed by scenario (D) within a radius (0-4000) m zone, which serves 12.9% of the city's population, then scenario (C) within a radius (4000-7000) m zone, can protect the city center of the city. Finally, scenario (A) within a radius (0-4000) m zone, can protect 4.9% city's population towards the university. In conclusion, an integrated scenario that includes the entire city to obtain goal of the article can be achieved by protecting the civilian people to protect and directed chaos directed away from holy sites and farther from the heritage sites to achieve urban sustainability. [ABSTRACT FROM AUTHOR]

This paper presents and demonstrates a novel scenario-building methodology that integrates contextual and future time uncertainty into the performance assessment of water distribution networks (WDNs). A three-step approach is proposed: (i) System context analysis, identifying the main key factors that impact the WDN performance; (ii) Scenario definition, identifying the implicated WDN variables, describing its possible evolution, and conjugating them to further establish the reference scenario and the two most relevant and opposite ones; and (iii) Scenario modelling, simulating the WDN behaviour for those scenarios. The obtained spatial and temporal hydraulic results are further used to calculate performance metrics. The methodology is applied to a real WDN to assess resilience performance considering infrastructure asset robustness (real water loss performance indicator), service reliability (minimum pressure index), and service flexibility (network resilience index). A new formulation to assess the metric evolution over time is proposed, deducting the further-away performance results by using an uncertainty weight. The results demonstrate that the increase in metric amplitude for the opposite scenarios over time highlights future uncertainty, reflecting context uncertainty, and the comparison of metric spatial distribution (i.e., at the pipe/node levels) highlights critical areas with higher associated uncertainty.

Abstract Background Predicting the likely size of future SARS-CoV-2 waves is necessary for public health planning. In England, voluntary “plan B” mitigation measures were introduced in December 2021 including increased home working and face coverings in shops but stopped short of restrictions on social contacts. The impact of voluntary risk mitigation behaviours on future SARS-CoV-2 burden is unknown. Methods We developed a rapid online survey of risk mitigation behaviours ahead of the winter 2021 festive period and deployed in two longitudinal cohort studies in the UK (Avon Longitudinal Study of Parents and Children (ALSPAC) and TwinsUK/COVID Symptom Study (CSS) Biobank) in December 2021. Using an individual-based, probabilistic model of COVID-19 transmission between social contacts with SARS-CoV-2 Omicron variant parameters and realistic vaccine coverage in England, we predicted the potential impact of the SARS-CoV-2 Omicron wave in England in terms of the effective reproduction number and cumulative infections, hospital admissions and deaths. Using survey results, we estimated in real-time the impact of voluntary risk mitigation behaviours on the Omicron wave in England, if implemented for the entire epidemic wave. Results Over 95% of survey respondents (NALSPAC = 2686 and NTwins = 6155) reported some risk mitigation behaviours, with vaccination and using home testing kits reported most frequently. Less than half of those respondents reported that their behaviour was due to “plan B”. We estimate that without risk mitigation behaviours, the Omicron variant is consistent with an effective reproduction number between 2.5 and 3.5. Due to the reduced vaccine effectiveness against infection with the Omicron variant, our modelled estimates suggest that between 55% and 60% of the English population could be infected during the current wave, translating into between 12,000 and 46,000 cumulative deaths, depending on assumptions about severity and vaccine effectiveness. The actual number of deaths was 15,208 (26 November 2021–1 March 2022). We estimate that voluntary risk reduction measures could reduce the effective reproduction number to between 1.8 and 2.2 and reduce the cumulative number of deaths by up to 24%. Conclusions Predicting future infection burden is affected by uncertainty in disease severity and vaccine effectiveness estimates. In addition to biological uncertainty, we show that voluntary measures substantially reduce the projected impact of the SARS-CoV-2 Omicron variant but that voluntary measures alone would be unlikely to completely control transmission.

Research background: The European Green deal set by the European Commission has launched new business models in sustainable development. Major contributions are expected in the road transport sector; as far as conventional internal combustion creates significant input in Green House Gas emission inventories. Each EU member state has an obligation to reduce GhG emission by accelerating Electric Vehicle development. In order to foster growth of EVs, there is the need of significant investment into charging infrastructures. The article propose the model of forecasting of investment based on the forecast of the growth of the amount of electric vehicles and their demand on energy. The model includes the behaviouristic approach based on the total cost of ownership model as well as calculations of efficient usage of EV charging points. The model takes into account all types of vehicles including personal and commercial, freight and passenger.

Abstract Global change is affecting soil biodiversity and functioning across all terrestrial ecosystems. Still, much is unknown about how soil biodiversity and function will change in the future in response to simultaneous alterations in climate and land use, as well as other environmental drivers. It is crucial to understand the direct, indirect and interactive effects of global change drivers on soil communities and ecosystems across environmental contexts, not only today but also in the near future. This is particularly relevant for international efforts to tackle climate change like the Paris Agreement, and considering the failure to achieve the 2020 biodiversity targets, especially the target of halting soil degradation. Here, we outline the main frontiers related to soil ecology that were presented and discussed at the thematic sessions of the World Biodiversity Forum 2022 in Davos, Switzerland. We highlight multiple frontiers of knowledge associated with data integration, causal inference, soil biodiversity and function scenarios, critical soil biodiversity facets, underrepresented drivers, global collaboration, knowledge application and transdisciplinarity, as well as policy and public communication. These identified research priorities are not only of immediate interest to the scientific community but may also be considered in research priority programmes and calls for funding.

A project for monitoring, analysis, and modelling trim blasting at an open pit copper/molybdenum mine in Canada in 2021 was conducted using Orica's in-house developed proprietary tools, which includes the accelerometer near-field vibration monitoring system, the Multiple Seed Waveform near-field and far-field blast vibration model, and the multiple blasthole fragmentation model. Both models are built on the fundamentals and empirical aspects of blasting mechanics. They input full blast design parameters and site-specific information from the near-field signature hole blast vibration. The blast vibration at the highwall from trim blasts was predicted with multiple seed waveform blast vibration model. The effects of parameters from the trim blast design scenarios on fragmentation and vibration at the highwall were simulated at the mine site. Improved blast designs for finer fragmentation and controlled vibration were proposed based on the modelling. The multiple blasthole fragmentation model can simulate real blast designs in three dimensions with the actual geometry of the blasted overburden and free faces. The multiple blasthole fragmentation model can explicitly model all blast design parameters, including explosive properties, loading configuration, and delay timing of each explosive charge. The multiple seed waveform blast vibration model uses multiple seed waveforms at different distances from a blasthole and is suitable for near-field blast vibration at the highwalls. Through the application of the two models, various design scenarios can be explored, and rock fragmentation can be optimized while controlling blast vibration levels. These models have been successfully applied to several open pit mines and quarries around the world, including Canada, the United States, and Africa. Highlights: A case application of innovative technologies to optimizing field trim blast designs. New field technique to collect site input data and evaluate effectiveness of presplit blasting. Near-field blast vibration monitoring and modelling in parallel with fragmentation modelling. [ABSTRACT FROM AUTHOR]

The tectono-sedimentary history of Gippsland Basin from the Early Cretaceous to present was modelled using Badlands landscape software constrained by a 3D structural and stratigraphic Petrel model. The aim is to assess the theoretical sedimentary models using empirical data to better understand the sedimentary history for this rift basin. The models measure the relative effects and most significant variables for basin evolution, including climate, deposition and erosion with extension, subsidence, uplift and eustacy. They show how the detailed basin landscapes evolved and provide new insights to understand facies development in the basin. Early Cretaceous paleotopography ca 137 Ma had extensive highland areas to north, east and south of a rapidly subsiding intracratonic rift with sediment transport east to west. The simulated paleoenvironments are alluvial and fluvial with floodplain lakes developing into extensive lake systems further west. The mid-Cretaceous uplift changed basin architecture, initiating the Strzelecki Ranges and regional erosion. Tasman Sea rifting in early Late Cretaceous formed the Central Deep further east and flipped the paleodrainage eastwards. Latrobe Group sediments filled this smaller depocentre to the east starting with rapidly deposited very thick intracratonic fluvial and lacustrine sediments becoming more coastal plain and shallow marine up section, with Emperor, Golden Beach and Halibut subgroups containing reservoirs and potential source rocks for petroleum. Rising sea-levels in the Late Cretaceous transgressed most of the Latrobe Group by the Oligocene. Simulations from Oligocene to Holocene show less extensive non-marine deposition onshore with incised valleys and very thick coals, while a widespread carbonate shelf built and prograded offshore, periodically cut by submarine canyons. Scenario analysis for 13 variables shows that no single factor is the main control on rift basin evolution; rather basin history is shaped by interactions between climate, uplift, erosion, subsidence and deposition. These controls usually balance sea-level except where it changes rapidly. Numerical tectono-sedimentary basin history reconstruction constrained by empirical data requires a balance of uplift, sediment supply and subsidence. Paleolandscape simulation in the Gippsland Basin from Early Cretaceous to present-day shows how the detailed facies distribution changed with time. New potential reservoirs and source rocks are recognised within the Cretaceous Strzelecki Group, Emperor and Golden Beach subgroups. Organic-rich Turonian source rocks were deposited in restricted lacustrine intra-rift settings. [ABSTRACT FROM AUTHOR]

This paper aims to demonstrate the use of qualitative research methods, specifically in-depth interviews, to explore the intangible and often difficult-to-quantify needs for forestry scenario modelling in Lithuania, which are frequently not adequately perceived. The study involved informants representing key actors in forest policy, forest management, research, and education. A total of 21 informants from 11 different institutions, which hold significant power and expertise in forest decision making, were interviewed. The purpose of these interviews was to gather their perspectives on the potential forest decision support system in the country, aiming to address most of their needs. The interview questions explored various aspects, including the requirements for forestry scenario modelling, the desired level of detail and information content for decision making, and both functional and nonfunctional requirements for the scenario modelling system. It is worth noting that the expected functionality of the planned forest DSSs aligns with modern international standards. Nevertheless, the diversity of perspectives, wishes, visions, and intentions of key Lithuanian forestry actors regarding the aims, objectives, and essential functionality of forestry scenario modelling tools were identified. The understanding of the requirements for modern forest DSSs was greatly influenced by the current forestry paradigms in the country and the professional experiences of individual informants. In conclusion, our findings demonstrate that the utilization of qualitative research, particularly through in-depth interviews, has proven to be a highly effective tool for accurately specifying the requirements of a modern forest DSS. It helped mitigate preconceived notions and address gaps in the envisioned product, specifically by developing a framework of core solutions for the national forestry and land-use scenario modelling system.

Water electrolysis for hydrogen production with renewable electricity is regularly studied as an option for decarbonised future energy scenarios. The inclusion of byproduct electrolytic oxygen capture and sale is of interest for parallel decarbonisation efforts elsewhere in the industry and could contribute to reducing green hydrogen costs. A deterministic hydrogen electrolysis system model is constructed to compare oxygen inclusion/exclusion scenarios. This uses wind and solar-PV electricity generation timeseries, a power-dependent electrolysis model to determine the energy efficiency of gas yield, and power allocation for gas post-processing energy within each hourly timestep. This maintains a fully renewable (and therefore low/zero carbon) electricity source for electrolysis and gas post-processing. The model is validated (excluding oxygen) against an existing low-cost GW-scale solar-hydrogen production scenario and an existing hydrogen production costs study with offshore wind generation at the multi-MW scale. For both comparisons, oxygen inclusion is then evaluated to demonstrate both the benefits and drawbacks of capture and utilisation, for different scenario conditions, and high parameter sensitivity can be seen regarding the price of renewable electricity. This work subsequently proposes that the option for the potential utilisation of byproduct oxygen should be included in future research to exemplify otherwise missed benefits.

Background: Predicting the likely size of future SARS-CoV-2 waves is necessary for public health planning. In England, voluntary "plan B" mitigation measures were introduced in December 2021 including increased home working and face coverings in shops but stopped short of restrictions on social contacts. The impact of voluntary risk mitigation behaviours on future SARS-CoV-2 burden is unknown. Methods: We developed a rapid online survey of risk mitigation behaviours ahead of the winter 2021 festive period and deployed in two longitudinal cohort studies in the UK (Avon Longitudinal Study of Parents and Children (ALSPAC) and TwinsUK/COVID Symptom Study (CSS) Biobank) in December 2021. Using an individual-based, probabilistic model of COVID-19 transmission between social contacts with SARS-CoV-2 Omicron variant parameters and realistic vaccine coverage in England, we predicted the potential impact of the SARS-CoV-2 Omicron wave in England in terms of the effective reproduction number and cumulative infections, hospital admissions and deaths. Using survey results, we estimated in real-time the impact of voluntary risk mitigation behaviours on the Omicron wave in England, if implemented for the entire epidemic wave. Results: Over 95% of survey respondents (NALSPAC = 2686 and NTwins = 6155) reported some risk mitigation behaviours, with vaccination and using home testing kits reported most frequently. Less than half of those respondents reported that their behaviour was due to "plan B". We estimate that without risk mitigation behaviours, the Omicron variant is consistent with an effective reproduction number between 2.5 and 3.5. Due to the reduced vaccine effectiveness against infection with the Omicron variant, our modelled estimates suggest that between 55% and 60% of the English population could be infected during the current wave, translating into between 12,000 and 46,000 cumulative deaths, depending on assumptions about severity and vaccine effectiveness. The actual number of deaths was 15,208 (26 November 2021–1 March 2022). We estimate that voluntary risk reduction measures could reduce the effective reproduction number to between 1.8 and 2.2 and reduce the cumulative number of deaths by up to 24%. Conclusions: Predicting future infection burden is affected by uncertainty in disease severity and vaccine effectiveness estimates. In addition to biological uncertainty, we show that voluntary measures substantially reduce the projected impact of the SARS-CoV-2 Omicron variant but that voluntary measures alone would be unlikely to completely control transmission. [ABSTRACT FROM AUTHOR]

To analyse the future transition towards fossil-free fuels in the Swedish maritime transport sector, this study develops a scenario modelling tool to assess implications of policy instruments, such as the European Union Emissions Trading System and the FuelEU Maritime regulation. Using data for individual ships and their operational patterns, the model estimates the lowest-cost fuel option for shipowners in different scenarios and calculates the resulting annual fuel consumption and greenhouse gas emissions. Scenario analyses indicate that policy instruments have the potential to affect shipowners' investment choices, but that relatively strong price signals are required for significant effects to arise. Battery-electric propulsion is most common for passenger ferries, ropax ships, and small passenger cruises, while fishing vessels and service ships typically choose conventional fuels across all scenarios. Choices are found to vary between ship segments and scenarios, emphasising the need to consider ship-specific data when analysing effects of policy instruments. [ABSTRACT FROM AUTHOR]

The investigation of the impact of energy consumption patterns on peak emissions in China is pertinent and crucial for achieving global climate goals. The study aims to form a forecast of carbon emissions in China and diagnose the achievement of established decarbonization goals based on structural changes in primary energy consumption until 2030. To achieve the goal, the study formed a Dynamic stochastic general equilibrium (DSGE) model with the implementation of Markov chains. The obtained research results yield important insights into the influence of various scenarios on carbon emissions in China by the year 2030. Specifically, considering structural transformations, an increase in emissions by 15 % can be anticipated, which is 7 % less than predicted by the classical scenario. Among the proposed scenarios, the Net Zero scenario is deemed the most efficient, where emissions could reach a level of 8509.5 million tons of CO₂. Conversely, the New Momentum scenario proves to be the most precarious, as it entails an escalation in coal usage, leading to a 4 % increase in emissions, amounting to 13264.84 million tons of CO₂. The contribution of this study is the approach to conducting carbon emission projections, which is based on the DSGE model with the implementation of Markov chains. This makes it possible to assess the adequacy of the set targets for carbon reduction based on alternative scenarios, which in crisis conditions can overlap and thus complement each other. • A forecast of carbon emissions in China. • The Net Zero scenario is assumed to be the most effective. • The approach to conducting carbon emission projections. • The potential threats to slow the rate of reduction of carbon emissions in China. [ABSTRACT FROM AUTHOR]

The article discusses the specific features of the risk management of internationalisation of Russian small and medium-sized companies operating in the high-tech sector of the economy. International expansion has been considered on the example of the countries of the Visegrad Group – Poland, Czech Republic, Slovakia and Hungary. A review of the methodological base of foreign economic risk management, formed by the efforts of Russian and foreign scientists, is carried out. Possible export risks have been described and assessed on the basis of scenario modelling and factor analysis. The essence of the identified risks and the key reasons for their formation are disclosed. Methods, measures and possible actors within the risk strategy's passport to affect the identified risks, are proposed. Conclusions about the effectiveness and performance of the proposed toolkit for export risk management, are made.

Hundreds of megatons of the second most important greenhouse gas (GHG), methane, are released annually to the atmosphere, often from emission sources which are difficult to abate. Research on post-emission mitigation technology is scarce and still in its infancy. This paper proposes a self-sufficient photocatalytic system to mitigate atmospheric methane via total oxidation to CO2 and analyzes its future viability and feasibility using environmental as well as physicochemical metrics. A four-step, explorative, scaled-up, prospective life cycle assessment (LCA) for the year 2050 shows that, in the best-case scenario, the market-ready photocatalytic module will amortize the produced GHG emissions in 1.5 years, while under more conservative assumptions, the physicochemical properties hinder a climate reasonable implementation. Targets like photocatalytic turnover numbers as well as reaction rates are calculated and compared to values reported in the literature to enable goal-oriented research and development. It is shown that more R&D is needed to have the proposed photocatalyst ready by 2050. The importance of methane mitigation development is highlighted and avenues for doing so are presented.

Maintaining landscape integrity in terms of ecological functions is a key principle of sustainable forest management. Bird assemblages use all parts of forest landscapes and provide an opportunity to analyze their broad-scale integrity in those regions where bird census data are of sufficient quality and detail. In this study, I modelled likely landscape-composition consequences of different scenarios of even-aged (clear-cutting-based) silviculture on breeding-bird assemblages. The models were parameterized using high-quality territory-mapping data from Estonia. I considered three approaches for obtaining the model parameters. Of these, (i) a formal analysis of rank-abundance curves was rejected due to the inconsistency of the curve shapes among habitat types. Two other approaches were used and complemented each other: (ii) smoothed forest-type specific functions of total assemblage densities along post-clear-cut succession, and (iii) empirical average densities of each species by forest type and age class (for species composition analyses). The modelling revealed a parallel loss of bird densities and, to a lesser extent, of species at shorter rotations; currently, this effect is disproportionately large on productive soils. For conserving the productive hotspots, the 30% protection target of the EU Biodiversity Strategy overperformed other scenarios. In all landscape settings, typologically representative old-forest reserves (even artificially drained stands) helped to mitigate rotational forestry. The potential of even-aged production forestry to host early-successional species was already realized at much longer rotations than currently (given uniform stand-age structure). Comparing potential and realized bird assemblages provides a tool for assessing ecological integrity at the landscape scale, and the results can be used for elaborating regional management goals of ecologically sustainable forestry. [ABSTRACT FROM AUTHOR]

Aluminum is an energy‐intensive material that is typically used as an alloy. The environmental impacts caused by its production can potentially be spread out over multiple uses through repeated recycling loops. However, inter‐alloy contamination can limit the circularity of aluminum, which highlights the importance of analyzing prospective stock dynamics of aluminum at an alloy and alloying element level to inform a more sustainable management of this resource. A dynamic material flow analysis (MFA) of aluminum alloys was developed in line with the shared socioeconomic pathways (SSP) framework to generate consistent scenarios of the evolution of aluminum stocks and flows from 2015 to 2100 covering 11 economic sectors in 5 world regions. A sector‐specific and bottom‐up modeling approach was developed. Results show no saturation of global stock per capita before 2100, reaching a range between 200 and 400 kg per capita according to different socioeconomic scenarios. For the business‐as‐usual scenario, the global annual inflow rises to 100 Mt in 2050 and peaks at 130 Mt in 2090, showing a saturation in total stock. Electricity‐sector demand has the highest relative growth over the century, while building and construction demand saturates and decreases from 2090. No major mismatch between inflows and outflows of aluminum alloy is observed. This means that with appropriate dismantling and sorting, changes in alloy demand would not limit the implementation of a closed‐loop aluminum industry. This study demonstrates the advantages of combining detailed MFAs and SSPs, both for greater consistency in circular economy modeling and for furthering scenario development efforts. This article met the requirements for a gold‐gold JIE data openness badge described at http://jie.click/badges [ABSTRACT FROM AUTHOR]

Sustainable production and consumption allows every individual to meet their basic needs and societies to flourish, all with limited overall throughput constrained by ecological ceilings. The question is how exactly basic needs satisfaction, flourishing societies, and limited throughput can come together. Based on the insight that decent living standards constrain the slope of the Lorenz curve for the lowest decile, a simple model can be derived that determines total consumption from only three factors: per capita decent living standards, the Gini coefficient of inequality , and population. With a constraint on maximum living standards, overall consumption splits into three components: basic needs satisfaction, prosperous consumption, and excessive consumption. The model calculates sustainable consumption corridors based on decent living standards and the acceptable maximum under ecological ceilings, while still allowing for reasonable levels of inequality and ample prosperous consumption. The model can be applied to economic and physical stock and flow indicators, and examples for all four combinations are provided. The work concludes with calling upon the research community to assess the inequality of physical stock and flow indicators related to human wellbeing, identify suitable physical wellbeing measures, and extend the debate on desirable levels of inequality to physical socio-metabolic indicators. [Display omitted] • Decent living standards are introduced as constraints to the Lorenz curve. • Consumption is split into basic needs satisfaction, prosperous, and excessive. • Simple model for total demand as function of decent living standard and Gini coefficient. • Need a debate on suitable physical stock and flow indicators and their inequality. [ABSTRACT FROM AUTHOR]

Urban trees are important nature‐based solutions for future well‐being and liveability but are at high risk of mortality from insect pests. In the United States (US), 82% of the population live in urban settings and this number is growing, making urban tree mortality a matter of concern for most of its population. Until now, the magnitudes and spatial distributions of risks were unknown.Here, we combine new models of street tree populations in ~30,000 US communities, species‐specific spread predictions for 57 invasive insect species and estimates of tree death due to insect exposure for 48 host tree genera.We estimate that 1.4 million street trees will be killed by invasive insects from 2020 through 2050, costing an annualized average of US$ 30 M. However, these estimates hide substantial variation: 23% of urban centres will experience 95% of all insect‐induced mortality. Furthermore, 90% of all mortality will be due to emerald ash borer (Agrilus planipennis, EAB), which is expected to kill virtually all ash trees (Fraxinus spp.) in >6,000 communities.We define an EAB high‐impact zone spanning 902,500 km2, largely within the southern and central US, within which we predict the death of 98.8% of all ash trees. 'Mortality hotspot cities' include Milwaukee, WI; Chicago, IL; and New York, NY.We identify Asian wood borers of maple and oak trees as the highest risk future invaders, where a new establishment could cost US$ 4.9B over 30 years.Policy implications. To plan effective mitigation, forest pest managers must know which tree species in which communities will be at the greatest risk, as well as the highest risk species. We provide the first country‐wide, spatial forecast of urban tree mortality due to invasive insect pests. This framework identifies dominant pest insects and spatial impact hotspots, which can provide the basis for spatial prioritization of spread control efforts such as quarantines and biological control release sites. Our results highlight the need for emerald ash borer (EAB) early‐detection efforts as far from current infestations as Seattle, WA. Furthermore, these findings produce a list of biotic and spatiotemporal risk factors for future high‐impact US urban forest insect pests. [ABSTRACT FROM AUTHOR]

Addressing modern water management challenges requires the integration of physical, environmental and socio-economic aspects, including diverse stakeholders' values, interests and goals. Early stakeholder involvement increases the likelihood of acceptance and legitimacy of potential solutions to these challenges. Participatory modelling allows stakeholders to co-design solutions, thus facilitating knowledge co-construction/social learning. In this work, we combine integrated modelling and participatory modelling to develop and deploy a digital platform supporting decision-making for water management in a semiarid basin under contentious water use. The purpose of this tool is exploring "on-the-fly" alternative water management strategies and potential policy pathways with stakeholders. We first co-designed specific water management strategies/impact indicators and collected local knowledge about farmers' behaviour regarding groundwater regulation. Second, we coupled a node–link water balance model, a groundwater model and an agent-based model in a digital platform (SimCopiapo) for scenario exploration. This was done with constant input from key stakeholders through a participatory process. Our results suggest that reductions of groundwater demand (40%) alone are not sufficient to capture stakeholders' interests and steer the system towards sustainable water use, and thus a portfolio of management strategies including exchanges of water rights, improvements to hydraulic infrastructure and robust enforcement policies is required. The establishment of an efficient enforcement policy to monitor compliance on caps imposed on groundwater use and sanction those breaching this regulation is required to trigger the minimum momentum for policy acceptance. Finally, the participatory modelling process led to the definition of a diverse collection of strategies/impact indicators, which are reflections of the stakeholders' interests. This indicates that not only the final product—i.e., SimCopiapo—is of value but also the process leading to its creation. [ABSTRACT FROM AUTHOR]

The authors analyze the trends and patterns for reproducing investment potential of institutional sectors. This is relevant for the economic and financial security of territorial systems. The aim of the study is to design a scenario model for reproducing investment potential of institutional sectors at the regional level. This model suggests systems of predictive scenarios for the reproduction and choosing the optimal one to achieve positive dynamics of the socio-economic development of the regions. When designing the scenario model, the authors used statistical methods for data collecting and processing, regression analysis with the least squares method and ARIMA forecasting. The authors developed an algorithm of scenario modelling for reproducing investment potential of institutional sectors in regional systems. The authors designed a balance model for financial flows between them for various investment instruments. They analysed the regularities of reproducing their investment potential. The paper presents an econometric analysis of financial flows among the sectors considering the impact factors, and the basic scenarios of reproducing their investment potential. The work reveals a stable trend of the outflow of investment resources in institutional sectors accumulated by the banking sector abroad during periods of economic downturns and the development of financial and economic crises. The study suggests a model allowing to determine the most likely forecast scenarios for reproducing investment potential of institutional sectors: inertial, extremely negative (pessimistic) and the most favorable (optimistic). The authors conclude that an increase in volatility in financial markets, a weakening of the domestic currency, and an increase in negative trends in economic development significantly increase the likelihood of a pessimistic scenario. To prevent this, the Central Bank of the Russian Federation, must change its policy of regulating the financial and economic activities of the banking sector: to limit the speculative activities of credit institutions that facilitate the withdrawal of financial resources from the domestic economy, to support investment programs for developing of enterprises of the real sector. The prospect for further research is building a system of mechanisms for transiting to the implementation of the optimal scenario of reproducing investment potential of institutional sectors, ensuring the restoration and progressive socio-economic development of territorial systems.

Delineating urban growth boundaries (UGBs) has been proved as an effective approach to constrain urban encroachment and achieve sustainable urban development. However, so far, many studies have not fully taken account of the ecosystem integrity in simulating the urban growth as well as the corresponding UGBs delineation. To bridge this research gap, this paper proposes an ESP-FLUS model to predict the future land use pattern with a comprehensive consideration of ecological protection. In this paper, on the one hand, the ecological security pattern (ESP) is integrated from four ecological aspects (i.e., hydrology, geology, biodiversity, and recreation) and classified into three levels (i.e., basic ESP, intermediate ESP, and optimal ESP). On the other hand, drawing on historical records, random forest coupled with Gini importance are applied to identify the driving factors in shaping the land use variation. Taking the classified ESP as the spatial constraint allied with the identified driving factors into a FLUS model, this paper predicts the urban growth in 2035 in a multi-scenario manner. By analysing the multi-scenario simulation results at both region and district levels, the possible urban planning option under the requirements of local master plans is suggested for sustainable urban development. Against a backdrop of an increasingly severe environmental crisis, this paper develops a new research paradigm to incorporate ESP into UGBs delineation as a way to shed light for urban planners on reaching the balance between eco-environment protection and socio-economic development.

An ex-ante impact assessment of land use plans is required in the preparation or revision phase to inform planners and other stakeholders about the possible or likely impacts of the plans. This study presents a method for estimating the quantitative effects of legislative decisions, the forest owner decisions, and a regional land use plan for forest resources and potential wood supply. The uncertainty associated with the interpretation of design codes used in regional land use plans was taken into account in the estimation. The analyses used MELA software, designed to operate on big data sets involving the characteristics of a large forest area. Estimates were produced for the Kainuu and Varsinais-Suomi case study areas in Finland. We observed large differences in the effects of legislative decisions, the forest owner decisions and a regional land use plan on forest resources available for wood supply and potential wood supply between these two provinces. In Varsinais-Suomi private forest owners and companies were affected considerably more than in Kainuu. There was little uncertainty associated with the interpretation of design codes in Kainuu, but the selection of the interpretation set may have a large effect on the estimates in Varsinais-Suomi. [ABSTRACT FROM AUTHOR]

Addressing modern water management challenges requires the integration of physical, environmental and socio-economic aspects, including diverse stakeholders’ values, interests and goals. Early stakeholder involvement increases the likelihood of acceptance and legitimacy of potential solutions to these challenges. Participatory modelling allows stakeholders to co-design solutions, thus facilitating knowledge co-construction/social learning. In this work, we combine integrated modelling and participatory modelling to develop and deploy a digital platform supporting decision-making for water management in a semiarid basin under contentious water use. The purpose of this tool is exploring “on-the-fly” alternative water management strategies and potential policy pathways with stakeholders. We first co-designed specific water management strategies/impact indicators and collected local knowledge about farmers’ behaviour regarding groundwater regulation. Second, we coupled a node–link water balance model, a groundwater model and an agent-based model in a digital platform (SimCopiapo) for scenario exploration. This was done with constant input from key stakeholders through a participatory process. Our results suggest that reductions of groundwater demand (40%) alone are not sufficient to capture stakeholders’ interests and steer the system towards sustainable water use, and thus a portfolio of management strategies including exchanges of water rights, improvements to hydraulic infrastructure and robust enforcement policies is required. The establishment of an efficient enforcement policy to monitor compliance on caps imposed on groundwater use and sanction those breaching this regulation is required to trigger the minimum momentum for policy acceptance. Finally, the participatory modelling process led to the definition of a diverse collection of strategies/impact indicators, which are reflections of the stakeholders’ interests. This indicates that not only the final product—i.e., SimCopiapo—is of value but also the process leading to its creation.

This paper and accompanying maps focus on a land suitability assessment of the Olomouc region in the Czech Republic. All results were calculated in Urban Planner, a model designed by the authors of this paper. The method of calculation is based on a multi-criteria analysis (weighted overlay method), respects the principles of sustainable development, and allows for execution of several scenarios. The main result of this work is a set of maps. The first map sheet shows the land suitability for housing, recreation, public services, heavy industry, light industry, and transportation. The second map sheet consists of four maps showing different scenarios of land suitability for housing: one map showing the evaluation of existing proposals for housing from urban plans, and one map showing optimal areas for housing calculated by the Urban Planner model. The maps can be used as a significant source of information about the suitability of development in the Olomouc region in geographic or urban studies, both for experts and the general public. All thematic maps are on the scale of 1:125,000; supplementary maps are smaller.

Economic growth, urbanization and changes in lifestyles are leading to a transition from traditional fuels to liquefied petroleum gas (LPG) and electricity in Indian households. We use National Sample Survey data – 43rd (1987–88) and 68th (2011−12) rounds – to show that contrary to concerns about rising greenhouse gas (GHG) emissions from fossil-fuel use, switching to LPG and electricity provides health and climate benefits, if non-Kyoto emissions are considered. Our modelled household energy transition scenarios (2011–2030) show that: one, adoption of LPG by 2030 in Business-As-Usual (BAU) projections results in 80% of urban India meeting the World Health Organization's (WHO) indoor PM 2.5 guidelines. In rural households, persistent use of firewood does not significantly improve indoor air quality across the income spectrum. Two, BAU scenario projects only a 3% rise in rural GHG emissions by 2030, driven by a transition away from kerosene lighting in spite of rising electricity consumption. Three, a complete transition to LPG and electricity by 2030 reduces PM 2.5 exposure to below WHO guidelines across all urban and rural households. This is not achieved in the other partial transition scenarios. Four, across scenarios improving coal-based power plant efficiency to 40% and increasing renewables' share to 40% lead to a decrease of 14–18% in GHG emissions by 2030 relative to 2011. Finally, improved biomass cookstoves can reduce indoor exposure by 75–86% but not below the WHO guideline, and result in higher GHG emissions compared to LPG replacement due to non-Kyoto emissions from burning firewood. • Complete switch to LPG maximizes health and climate benefits (incl. non-Kyoto emissions). • Current initiatives in India will not fully benefit low-income rural households by 2030. • Improved biomass cookstoves have higher climate and PM 2.5 exposure impact than LPG. [ABSTRACT FROM AUTHOR]

A Futures Literacy application to a major healthcare project is described. Funded under the EU FP7 framework, the 'Managed Outcomes' project modelled resource usage across four different medical conditions and linked this with patient health outcomes. A Futures Literacy approach was undertaken to explore scenarios for future care provision in 18 workshops, and five languages. Facilitator training, workshop preparation, delivery and outcomes are described. The process provided a consistent framework for generating relevant outputs from local care professionals and indicated potential operational process developments to improve patient outcomes. [ABSTRACT FROM AUTHOR]

Antibiotics have been heavily used over the past decades, resulting in their frequent detections in rivers and increasing ecological risks. Recognizing characteristics of antibiotic ecological risks (AERs) and making effective strategies to mitigate the AERs are essential to ensure the safety of aquatic ecosystem and public health. In this study, an integrated technological framework has been proposed toward identifying management options for reducing AERs by jointly utilizing multimedia fugacity modelling and ecotoxicological risk assessment, and applied to characterize the AERs in a peri-urban river in Beijing. Specifically, a level III fugacity model has been successfully established to simulate the fate of antibiotics in the environment, and the manageable parameters have been screened out via sensitivity analysis of the model. Then the validated fugacity model has been used for scenario modellings to optimize mitigation strategies of AERs. Results show most of the antibiotics considered are frequently detected in the river, and pose medium or high risks to aquatic organisms. Relatively, the macrolides and fluoroquinolones present higher ecotoxicological risks than sulfonamides and tetracyclines. Furthermore, the mixture risk quotient and predictive equation of concentration addition suggest joint and synergistic/antagonistic effects of AERs for multiple or binary antibiotics in the environment. Largely, the concentrations of antibiotics in the river are determined by the source emissions into water and soil. Scenario modellings show the improvement of antibiotic removal rates would be considered preferentially to mitigate the AERs. Also, controlling human consumption is conducive to reducing the risks posed by tetracyclines, macrolides and trimethoprim, while controlling animal consumption would benefit the reduction for sulfonamides. Overall, the joint strategy presents the greatest reduction of AERs by reducing antibiotic consumption and together improving sewage treatment rate and antibiotic removal rate. The study provides us a useful guideline to make ecological risk-based mitigation strategy for reducing AERs in environment. • A framework was proposed toward identifying ecological risk-based mitigation strategy. • The sixteen antibiotics were widely detected in the river and posed medium or high risks. • The constructed fugacity model could be successfully used for predicting antibiotics. • Improvement of antibiotic removal rate would be considered preferentially to mitigate the AERs. • Controlling consumption was conducive to reducing the AERs. [ABSTRACT FROM AUTHOR]