Future Development Scenarios Research Articles

Advancing the potential impact of future scenarios by integrating psychological principles

Engaging with the future to make better decisions in the present is key for sustainable development and climate change responses. In this conceptual paper, we suggest a scenario building approach that connects psychological principles of future thinking with future scenario development in order to advance the impact of scenarios. Future scenario work currently does not sufficiently consider processes of human communication, emotion, cognition and has only begun to focus on people’s local contexts in recent years. We argue that more understanding of psychological processes, such as cognitive biases and heuristics, as well as psychological distance, which typically occur in future thinking, can improve the impact of scenarios. Specifically, we provide a psychological basis for systematically integrating emotion-evoking aspects into future scenario development, using tailored narratives and visuals to make content tangible and meaningful for a broad spectrum of audiences, and adapting content temporally, spatially, and linguistically to audiences, in combination with inclusive and creative co-creation of scenarios and sustainable solutions. We explain why this approach has the potential to overcome some recognised cognitive biases hampering scenario impact and intended sustainable change processes, and can therefore support the co-development of sustainable and inclusive policies and solutions that empower and connect individuals, communities, and decision makers.

Analysing urban growth using machine learning and open data: An artificial neural network modelled case study of five Greek cities

Urban development if not planned and managed adequately can be unsustainable. Urban growth models have been a powerful toolkit to help tackling this challenge. In this paper, we use a machine learning approach, to apply an urban growth model to five of the largest cities in Greece. Specifically, we first develop a methodology to collect, organise, handle and transform historical open spatial data, concerning various impact factors, into machine learning data. Such factors involve social, economic, biophysical, neighbouring-related and political driving forces, which must be transformed into tabular data. We also provide an artificial neural network (ANN) model and the methodology to train and evaluate it using goodness-of-fit metrics, which in turn provide the best weights of impact factors. Finally, we execute a prediction for 2030, presenting the results and output maps for each of the five case study cities. As our study is based on pan-European datasets, our model can be used for any area within Europe, using the open-source utility developed to support it. In this sense, our work provides local policy-makers and urban planners with an instrument that could help them analyse various future development scenarios and take the right decisions going forward.

Risk assessment of urban rainstorm flood disaster based on land use/land cover simulation

AbstractUnder the urbanization context, land use/land cover (LULC) changes rapidly which affects both the probability of urban flood disaster and its consequence. In order to explore the impact of LULC changes on rainstorm flood disaster risk in the future, a framework of rainstorm flood disaster risk assessment is constructed from natural‐social perspective through LULC simulation based on the patch‐generating land use simulation (PLUS) model in this study. Specifically, the spatial LULC under three future development scenarios (inertia development scenario, economic priority scenario and sustainable development scenario) for the year 2030 is simulated, and then assessment model of rainstorm flood disaster risk is constructed through obtaining inundation depth and social vulnerability based on simulated LULC. Jingdezhen City in China is selected as an example. The results show that proposed risk assessment framework based on PLUS model can be used to detect the risk changes in different development scenarios. The risk of urban rainstorm flood disaster under economic priority scenario is most severe and risk under the sustainable development scenario is the lowest under the same return period rainstorm. Under the sustainable development scenario, green land including forest land, grassland and open water increases, which reduces the surface runoff and decrease the risk of rainstorm flood disaster effectively, however the reduction is limited with the greater rainstorm return period. Therefore, adaptive measures should be implemented together with land use planning to prevent and control urban flood risk. This study provides a framework to predict the future risk of urban rainstorm flood under different development scenarios, which can support for flood disaster risk prevention and urban sustainable development.

Simulation analysis of rural land use using rate of change driven by population and economic dynamics - A case study of Huangguashan village in Chongqing, China

The conflicts between various types of land use in rural areas of China are becoming more and more obvious, therefore, how to more accurately simulate and predict the future land cover changes in rural areas has become an important topic of current academic research. In this research, the dynamic multi-year data was used to replace the static one-year data and brought into the future land use simulation (FLUS) model for the simulation of land use in Huangguashan village, Chongqing, China. The accuracy results of the two sets of simulations are compared in terms of accuracy kappa coefficient and Overall Accuracy (OA). Next, using the improved FLUS model, four different future development scenarios of priority ecological conservation, priority economic development, priority farmland conservation and priority integrated development were set up to simulate the land use data of Huangguashan village in 2030. The results of the research found that (1) the kappa coefficient and OA values were higher for the simulation of FLUS model using dynamic multi-year data. The simulation results are closer to the actual situation, especially the simulation enhancement effect is more obvious for the long-term; (2) by comparing the land use types of four different future development scenarios, it is suggested that Huangguashan village should adopt the integrated development priority scenario as the direction of future policy formulation and planning development in the future. This research can provide more effective scientific decision support and significance for governments to formulate multi-scheme rural land use development policies.

Multi-objective energy planning for China's dual carbon goals

Long-term dependence on fossil fuels for economic growth is a primary driver of carbon emissions in emerging economies such as China. To achieve China's dual carbon goals (DCGs) of carbon peaking and carbon neutrality, we developed a dynamic input-output multi-objective optimisation model, combined with scenario setting, to explore the optimization pathways of carbon emissions, economic growth, and energy consumption. With reference to policy reports, we set different economic growth scenarios, and consider ambitious, moderate, and conservative carbon emission scenarios. The results showed that large-scale expansion of the tertiary industry is essential to realize the DCGs. The cumulative carbon emissions for the ambitious scenario were approximately 1.8 times higher than those for the conservative scenario. Further, the carbon intensity in 2030 would decrease by >69.2 % compared to the 2005 level. It means that China can achieve carbon reduction targets for 2030. We projected that future Chinese energy consumption will peak in 2035, reaching 180.64 EJ. We also optimized the installed electricity generation mix to be consistent with future development scenarios for China. This study provides valuable insights into the strategies and policy requirements to meet China's newly announced DCGs to assist in mitigating global climate change.

A well‐being framework for cross‐cultural assessment of development scenarios: A case study from North‐Western Australia

Abstract In Western‐democratic countries, it is widely accepted that affected communities should be involved in natural resource planning and decisions. This is especially so when the well‐being of diverse communities is directly involved, and where alternative future options are being considered. Although there is an agreement that ‘values’ and ‘well‐being’, in some form, guide decisions, there is no consensus on the well‐being framework(s) that might be used in participatory planning. To assist a multicultural group in assessing alternative future development scenarios for the Martuwarra (Fitzroy River) in Western Australia, we developed a well‐being framework that culturally diverse communities could share and use to discuss and assess scenarios. In this paper, we aim to evaluate the effectiveness of the well‐being framework used to assess the potential impacts of scenarios by (i) analysing how effectively participants used the well‐being framework; (ii) verifying whether the well‐being framework was sensitive to the cultural diversity of participants and (iii) direct evaluation by workshop participants. Our analysis shows that participants effectively applied most well‐being categories, and the framework was sensitive to the cross‐cultural context of the application by capturing Aboriginal cultural elements. However, the approach can be improved by including principles of behaviour; producing a more complete system model; and reviewing and amending the well‐being categories in more extensive community consultation. We conclude that the interaction among different worldviews generated valuable knowledge and that, with further adaptation, the framework shows promise for applications involving similar tasks in culturally diverse contexts. Read the free Plain Language Summary for this article on the Journal blog.

Frameworks to envision equitable urban futures in a changing climate: A multi-level, multidisciplinary case study of New York City

Cities are at the forefront of climate change action and planning for futures that are concomitantly more resilient and equitable, making local goals imperative for global sustainability. Under the multiple challenges of changing climatic, ecological and socio-economic conditions, cities need the means to meet these goals. We know cities are and will continue to be points of concentrated and diverse populations, socioeconomic vulnerability, amplified exposure, transformed ecosystems and are responsible for the bulk of the world’s greenhouse gas emissions. Yet, much is also unknown and intrinsically uncertain about urban futures: there is a range of potential plausible futures which have differing implications for both potential mitigation and adaptation actions. To better assess these plausible futures, the “global change” research community developed a framework including scenarios that are applicable for global and regional policy, entitled the Shared Socio-economic Pathways (SSPs) and scenarios exploring future emissions that will drive climate change, entitled Representative Concentration Pathways (RCPs). Importantly, this global scale framework does not include specific city-level perspectives or data at the spatial scales necessary to address questions of local relevance. While the SSPs address many of the key population and socioeconomic drivers of climate change, they do not address important concerns that are particularly relevant to cities, such as racial justice, ecosystem change or migration. Nevertheless, city-level impacts will evolve, in part, as a function of the global scale change characterized by the SSPs, and in part based on demographic and social processes already underway. As such, applying a modification of this framework to cities has the potential to help limit local climate impacts, and create a more resilient, equitable city. To address these needs and respond to city and regional stakeholders, we propose a framework for science-based narratives and quantitative projections for cities and metropolitan areas, such as Greater New York City. In this paper, we review a wide-range of existing approaches to generate estimates of future populations and identify their vulnerabilities to climate-change hazards, ranging from subnational population projections or the spatially-explicit allocation of populations linked to SSPs for the US and selected cities, city-specific population forecasting without climate considerations, and participatory approaches to future scenario development and fine-scale, within-city land use change models. By showcasing the strengths and limitations of various approaches and modeling efforts, their spatial and temporal scales, and thematic breadth, we propose a novel framework that leverages state-of-the art quantitative approaches and couples it with stakeholder engagement that can help cities plan equitably under uncertainty.

Historical Evolution and Scenarios Up to 2050 of Heating Energy Consumption and CO<sub>2</sub> Emissions of Residential Buildings in Vienna

Today, the building sector poses a major problem concerning fossil fuel energy consumption and the corresponding emissions of local pollutants and global greenhouse gases (GHG). In addition, an increasing number of people are living in urban areas, and it is becoming challenging to provide the necessary living space and energy for heating in fast-growing cities. Currently, urban areas host approximately 50 % of the global population and generate 70 % of GHG. The core objective of this study is to analyze the historical development and to derive scenarios for the possible future development of the overall CO<sub>2</sub> emissions in residential buildings in Vienna up to the year 2050, considering all relevant emissions from final energy, as well as the embedded emissions from the construction of new buildings, retrofitting, and rooftop apartment extensions. This study indicates the following key points: (i) The renovation of buildings by improving the thermal quality is the most favorable scenario strategy and produces the least CO<sub>2</sub> emissions. (ii) The transition to the sustainable heating of buildings requires at least a temporary "investment" in embedded CO<sub>2</sub> emission, e.g., in retrofitting and insulation of buildings to harvest reductions in CO<sub>2</sub> emissions in the long run, from a smaller amount of energy used for heating. The major conclusions of this study are as follows: (i) To implement the most favorable renovation scenario, strong policy measures are required, such as standards for new buildings and for building retrofitting, as well as subsidies to ensure an accelerated refurbishment rate of the old low thermal building stock. (ii) It is important to reduce the CO<sub>2</sub> emission of the final energy carriers, especially of district heating, by increasing the usage of renewable energy carriers such as biomass, solar, and geothermal.

Prediction of Urban Thermal Environment Based on Multi-Dimensional Nature and Urban Form Factors

The urban thermal environment is affected by multiple urban form and natural environment factors; research on the accurate prediction of the urban thermal environment, considering the interaction among different urban environmental factors, is still lacking. The development of a machine learning model provides a good means of solving complex problems. This study aims to clarify the relationship between urban environmental variables and the urban thermal environment through high-precision machine learning models as well as provide scenarios of future urban thermal environment developments. We defined an urban thermal environment index (UTEI), considering twelve urban form and natural indicators sourced from the remote sensing data of 150 cities in the Jing-Jin-Ji region from 2000 to 2015. We achieved accurate predictions of UTEI through training a gradient-boosted regression trees model. By unpacking the model, we found that the contribution rate of elevation (ELEV) was the highest. Among all the urban form indicators, the elongation index (ELONG), urban population (POP), nighttime light intensity (NLI), urban area size (AREA), and urban shape index (SHAPE) also had high contributions. We set up five scenarios to simulate the possible impact of different urban form factors on the overall urban thermal environment quality in the region. Under extremely deteriorated patterns that do not control urban expansion and vegetation reduction, the average UTEI could be as high as 0.55–0.76 °C in summer and 0.24–0.29 °C in winter, yet in the extremely optimized situation, UTEI decreased by 0.69 °C in summer and 0.56 °C in winter. Results showed that better urban form improves the quality of urban environments and can provide important insights for urban planners to mitigate urban heat island problems.

Evolution and Prediction of the Coupling Coordination Degree of Production–Living–Ecological Space Based on Land Use Dynamics in the Daqing River Basin, China

Located in China’s Beijing–Tianjin–Hebei region, the Daqing River Basin has a high economic development level. The natural and social conditions within the basin vary greatly, and the spatial configuration of the Production–Living–Ecological Space (PLES) between different sub-regions is unbalanced, with problems and contradictions in the functions of PLES becoming increasingly prominent. This study constructs a PLES classification system for the Daqing River Basin based on multi-period land use data, simulates the future land use evolution of the basin using the Patch-Generating Land Use Simulation (PLUS) model, calculates the coupling degree (CD) coupling coordination degree (CCD) of PLES from 1992 to 2020, and, under the natural trend development scenario (NT), cropland preservation development scenario (CP), and ecological preservation development scenario (EP) of 2030, quantitatively analyses the historical evolution and future direction of the three-life spatial. The results show that: (1) From 1992 to 2020, the area of living space in the Daqing River Basin has increased significantly, while the area of production space and ecological space has decreased significantly. Compared to NT, CP is beneficial to the maintenance of production space, while the EP is beneficial to the maintenance of ecological space. (2) Globally, the CD and the CCD of PLES in the Daqing River Basin show an increasing trend from 1992 to 2010 and a decreasing trend from 2010 to 2020. In 2030, the CD and the CCD of PLES of the three development scenarios decrease significantly compared to 2020; however, the decrease in CP is slight. (3) By region, from 1992 to 2020, the CCD of PLES in the western and eastern parts of the Daqing River Basin increases relatively more, while the central part increases slightly. Compared to 2020, the CCD of PLES in the central part of the Daqing River Basin is predicted to decrease significantly under NT and EP in 2030, while the decrease is slightly less under CP. In all three scenarios, there are some areas where the CCD of PLES increases in the western areas. This study highlights the internal variability of the spatial evolution of PLES in the basin and focuses on the impact of different future development scenarios on the spatial changes of PLES, which can offer an enlightenment for high-quality development and sustainable territorial spatial planning in the Daqing River Basin.

Future changes in habitat availability for two specialist snake species in the imperiled rocklands of South Florida, USA

AbstractRockland habitat in South Florida, USA, is a threatened ecosystem that has been lost, fragmented, or degraded because of urbanization or other anthropogenic disturbance. Furthermore, low‐lying islands and coastal areas are experiencing sea level rise (SLR) and an increased frequency and intensity of tidal flooding, putting rockland habitats there at increasing risk of ecological change. We evaluated changes in the extent of rockland habitat under various scenarios of future SLR, tidal flooding, and human development for two endemic state‐listed threatened species of snakes, the Rim Rock Crowned Snake (Tantilla oolitica) and the Key Ring‐necked Snake (Diadophis punctatus acricus). Both snakes are restricted to South Florida. We used recent and historical species' records to determine each species' habitat range. We then estimated the extent of future habitat loss due to SLR and continued human development, as well as degradation of the remaining habitat. We also asked whether the future potential drivers of habitat loss and degradation differ between the two species and across their habitat ranges. We predicted that saltwater intrusion could negatively affect rocklands by 2050, resulting in degradation of 80% of the existing habitat because of an anticipated 42 cm of SLR. Moreover, our model suggests short‐term stochastic events such as storm surge and high tides may increasingly saturate the root zone of rockland vegetation before complete inundation. Under the extreme scenario, we predict most of the rockland habitat used by these two species of snakes may be inundated by 2080. Under the extreme SLR scenario, current rocklands are likely to convert to more halophytic habitat (mangrove or salt marsh wetland) within 50–60 years. Under the low scenario, 31% of rockland habitat may be lost due to human development by 2030. Therefore, mitigation actions may help to conserve specialist species within rockland habitat threatened by human activities and climate change.

Old forecasts vs actual shoreline evolution: Assessing model's performance and projections accuracy

Nowadays there are numerous computational tools to forecast the evolution of the shoreline position in sandy coast environments. However, few studies have waited for the time horizon of the predictions to actually check the accuracy of the forecasted scenarios. Thus, this work proposed to assess the accuracy of medium-term predictions made with Long-Term Configuration (LTC) and GENEralised model for SImulating Shoreline change (GENESIS) numerical models for the time horizon of 15-year and evaluate the models’ performance in forecasting the actual status of a complex sandy coastal stretch in 2018, the targeting year. The projection premises were already presented in Baptista et al. (2014) on which observational data used to calibrate and blind hindcast future scenarios of shoreline development was discussed. The case study focused on an area located downdrift of Poço da Cruz groin, on the northwest Portuguese coast, and considered two beach sectors in accordance with Baptista et al. (2014): sector AC, about 3.5 km long, and sector AB, about 2.4 km long and included in the first one. The whole coastal stretch is composed of sandy beaches, and past trends highlight erosion downdrift of Poço da Cruz groin due to the interruption of sediment transport. A monitoring program performed by the University of Aveiro between 2003 and 2018 (corresponding to the period of simulation presented in Baptista et al., 2014), including six topographic surveys, was considered for comparison with the projections previously made. An additional topographic survey performed in 2018, within COSMO programme, was also considered. Simulations results have proved divergent performances of LTC and GENESIS models, despite the equity of inputs parameters and modelling processes. It is concluded that GENESIS and LTC, considering the typical (TYP) wave climate (randomly generated to represent the typical frequencies of wave height and direction during five years), create an envelope (GENESIS below and LTC above) to the real average results. For TYP, GENESIS underestimates the mean retreat rates up to 23 m in sector AB and up to 23 m in AC; LTC overestimates the retreat up to 33 m in sector AB and up to 13 m in AC. Conversely, observed (OBS) wave climate (shorter characterisation period but maintaining the registered data sequence) projections overestimate the shoreline retreat in both coastal stretches, suggesting that a larger characterisation period should be more important than maintaining the sequence of recorded waves. For OBS, the models overestimate the mean retreat rates in both sectors: GENESIS overestimates up to 90 m in sector AB and up to 51 m in AC; LTC overestimates up to 60 m in AB and up to 60 m in AC. Also, the consideration of the artificial nourishment operations executed during the simulation period leads to better results in the LTC, which was overestimating the erosion rate. This showed that if all man-made interventions could be anticipated, the average retreat in the main sector, AC, would only be up to 5 % different from the projections made by Baptista et al. (2014) with LTC model and TYP wave climate. • Checked accuracy of 15-year forecasts. • Checked performance of LTC and GENESIS shoreline evolution models. • The wave sampling period used in calibration has relevant impact on forecasts made. • LTC and GENESIS create an envelope to the real average retreat surveyed. • Better projections would be achieved if planed interventions were known in advance.

Multi-Scenario Simulation of Ecosystem Service Values in the Guanzhong Plain Urban Agglomeration, China

Rapid urbanization and human activities enhanced threats to the degradation of various ecosystem services in modern urban agglomerations. This study explored the response of ecosystem service values (ESVs) to land use changes and the trade-offs among various ESVs in urban agglomerations under different future development scenarios. The patch-general land use simulation (PLUS) model and ESV calculation method were used to simulate the ESVs of Guanzhong Plain Urban Agglomeration under the Business As Usual scenario (BAU), Ecological Conservation scenario (EC), and Economic Development scenario (ED) in 2030. Global and local Moran’s I were used to detect the spatial distribution pattern, and correlation analysis was used to measure trade-offs among ecosystem services. The results showed that: (1) The simulated result of land use in Guanzhong Plain Urban Agglomeration showed high accuracy compared to the actual observed result of the same period, with a Kappa coefficient of 0.912. From 2000 to 2030, land use changes were significant, with the rapid decrease in farmland and an increase in construction land. The area of woodland increased significantly under the EC scenario, and the area of construction land increased rapidly under the ED scenario. (2) The decline of total ESV was CNY 218 million from 2000 to 2020, and ESVs remained the downward trend in the BAU and ED scenarios compared to 2020, decreasing by CNY 156 million and CNY 4731 million, respectively. An increasing trend of ESV showed under the EC scenario, with a growth of CNY 849 million. (3) Significant spatial autocorrelation showed in Guanzhong Plain Urban Agglomeration, as the Global Moran’s I were all positive and the p-values were zero. The ESV grids mainly showed “High-High” clusters in the mountainous areas and “Low-Low” clusters in plain areas. Except for food production, a majority of ecosystem services exhibited positive synergistic relationships. In future planning and development, policymakers should focus on the coordinated development of the urbanization process and ecological preservation to build an ecological safety pattern.

Imagining the School of the Future Through Computational Simulations: Scenarios’ Sustainability and Agency as Keywords

Computational simulations are fundamental tools not only for scientific research but also for education. They are frequently used as virtual laboratories to foster students’ understanding of the theoretical concepts that lie at the basis of the simulated systems. Recent research works in STEM education have started to explore the potential of simulations as future-oriented objects, to support students in the development of future scenarios for real-world situations. In this paper, we present a teaching-learning module targeted to upper high-school students on simulations of complex systems. The peculiarity of this course is that, guiding the students through the conceptual and epistemological analysis of some computational agent-based models, we were able to ground on these disciplinary bases the introduction of key concepts of the futures studies, like that of scenario. More specifically, in this paper we address an original future-oriented activity in which the students were required to choose an urgent problem of their interest, imagine possible and desirable scenarios based on a simulation and identify the sequence of actions to be undertaken to reach the preferable future. In presenting the results of the module’s implementation we focus on two groups of students who spontaneously decided to address a problem related to the current educational system. In particular, we discuss how the future-oriented activity based on simulations led the students (i) to imagine sustainable scenarios for the school of the future, in which a dynamical equilibrium between opposite tensions is achieved, without any of them being eliminated and (ii) to recognize themselves as agents of transformation in a public, professional, and personal dimension.

In search of a nomadic pastoralism for the 21st century. A transdisciplinary development of future scenarios to foster a social-ecological transformation in Mongolia

Nomadic pastoralism is of vital importance for grasslands worldwide. As one of the largest, widely intact, temperate grasslands in the world, the eastern Mongolian steppe looks back on a millennia-old tradition of nomadic pastoralism. Thus, this type of use of the ecosystem plays an important role in providing and maintaining ecosystem functions, e.g. seed dispersal, nutrient distribution and composition of plant communities. In addition, the nomadic way of life has important cultural and social functions. Global change processes like urbanisation, globalisation, digitalisation and climate change confront societies worldwide with the need for substantial sustainability transformations. While pastoralists are also strongly affected by these changes, their experiences and way of life, which have been evolving and adapting for millennia, can prove very helpful in addressing the transformation challenges. With this paper, we aim to reflect a new form of nomadic pastoralism for Mongolia in the twenty-first century. Implementing a transdisciplinary research process, we conducted a series of stakeholder workshops, surveys and co-writing periods, involving pastoralists, local and national authorities, economic and conservation actors, as well as scientific project partners from a wide range of disciplines. In doing so, we developed exploratory scenarios of contrasting plausible futures of the Mongolian steppe.

Impact of Future Development Scenario Selection on Landscape Ecological Risk in the Chengdu-Chongqing Economic Zone

The management of regional eco-environmental risks is the key to promoting regional economic sustainability from the macro level, and accurate evaluation of the evolutionary trends of regional ecological risk in the future is of high importance. In order to clearly identify the possible impact of future development scenario selection for the Chengdu-Chongqing Economic Zone (C-C E Zone) on the evolution of landscape ecological risk (LER), we introduced the Patch-generating Land Use Simulation (PLUS) model to simulate land use data for the C-C E Zone from 2030 to 2050 for two scenarios: natural development (ND) and ecological protection (EP). Based on the ecological grid and landscape ecological risk index (LERI) model, the landscape ecological risk (LER) evolutionary trends seen in the C-C E Zone from 2000 to 2050 were analyzed and identified. The results showed that: (1) The PLUS model can obtain high-precision simulation results in the C-C E Zone. In the future, the currently increasing rate of land being used for construction will be reduced, the declining rates of forest and cultivated land area will also be reduced, and the amount of land being used for various purposes will remain stable going into the future. (2) This study found that the optimal size of the ecological grid in the LERI calculation of the mountainous area was 4 × 4 km. Additionally, the mean values of the LERI in 2030, 2040, and 2050 were 0.1612, 0.1628, and 0.1636 for ND and 0.1612, 0.1618, and 0.1620 for EP. (3) The hot spot analysis results showed that an area of about 49,700 km2 in the C-C E Zone from 2000 to 2050 belongs to high agglomeration of LER. (4) Since 2010, the proportions of high and extremely high risk levels have continued to increase, but under the EP scenario, the high and extremely high risk levels in 2040 and 2050 decreased from 14.36% and 6.66% to 14.33% and 6.43%. Regional analysis showed that the high and extremely high risk levels in most regions increased over 2010–2050. (5) Under the ND scenario, the proportions of grids with decreased, unchanged, and increased risk levels were 15.13%, 81.48%, and 3.39% for 2000–2010 and 0.54%, 94.75%, and 4.71% for 2040–2050. These trends indicated that the proportion of grids with changed risk levels gradually decreased going into the future. This study analyzed the evolutionary trends of LER at the C-C E Zone for the ND and EP scenario. On the whole, the LER for the C-C E Zone showed an upward trend, and the EP scenario was conducive to reducing the risk. These research results can serve as a valuable data reference set for regional landscape optimization and risk prevention and control.

Concurrent 15. Presentation for: Trusted environmental and geological information to support Australian energy resource development in a changing world

Presented on Wednesday 18 May: Session 15 The Australian Government’s Trusted Environmental and Geological Information (TEGI) program is a scientific program led by Geoscience Australia. The program is part of the Government’s Strategic Basin Initiative under its Gas-fired Recovery agenda, implemented as a post-COVID19 response to stimulate the economy. This program will deliver regional geological and environmental assessments underpinned by transparent, trusted baseline geological and environmental data, commencing in the north Bowen and Galilee and the Cooper and Adavale Basins. This repository of information is to be used in support of bringing forward energy and mineral developments in basins identified by the Government as strategic. This paper discusses how coupling resource assessments with baseline information such as groundwater, geology, energy and mineral resources, surface water and protected environmental matters, can be used to support exploration and development decisions by industry, regulators and other stakeholders. For example, by establishing a regional baseline resource assessment, through prospectivity play mapping, environmental assessments can be prioritised to match resource prospectivity. In anticipating future development scenarios, potential impacts on environmental assets, including groundwater, can be assessed in advance and with key knowledge gaps identified for redress. This approach aims to optimise the regulatory pathway to resource development and increase regulatory efficiency as future development opportunities arise across the scope of petroleum, minerals, carbon capture and storage, and hydrogen storage and production. An example of Geoscience Australia’s work on the Adavale Basin is presented in this paper describing the first steps in linking energy resources and environmental assessments in a changing world. To access the presentation click the link on the right. To read the full paper click here

Optimal location and operation of waste-to-energy plants when future waste composition is uncertain

In many countries, waste management is increasingly geared towards a circular economy, aiming for a sustainable society with less waste generation, fewer landfills, and a higher rate of recycling. Waste-to-Energy (WtE) plants, which convert waste into heat and energy, can contribute to the circular economy by utilizing types of waste that cannot be recycled. Due to the varying quality of sorting and socio-economic conditions in individual regions, the waste composition differs between regions and has an uncertain future development. Waste composition significantly affects the operation of WtE plants due to differences in energy potential. This paper supports strategic capacity planning for waste energy recovery by introducing a two-stage stochastic mixed-integer linear programming model that captures waste composition uncertainty through scenarios of possible future development. The results of the model provide insights into the economics of operation and identify important factors in the sustainability of the waste handling system. The model is demonstrated on an instance with six scenarios for waste management in the Czech Republic for the year 2030. The solution of the proposed model is to build 14 new WtE plants with a total capacity of 1970 kt in addition to the four existing plants with a capacity of 831 kt. The annual energy recovery capacity is expected to increase almost four times to satisfy EU directives that restrict waste landfilling.

LASAM Model: An Important Tool in the Decision Support System for Policymakers and Farmers

Today’s global food system (including production, transportation, processing, packing, storage, retail sale, consumption, losses and waste) provides income to more than a billion people all over the world and makes up a significant part of many countries’ economies. The 21st century’s food systems that bring food from “farm to fork” face various challenges, including a shortage of agricultural land and water, competition with the energy industry, changes in consumption preferences, a rising global population, negative effects of climate change, etc. Therefore, many countries are working on creating various models to function as an important decision support system tool for policymakers, farmers and other stakeholders. Various agricultural sector models see particularly extensive use in the European Union (EU), determining the impact of the Common Agricultural Policy (CAP) and helping to create future development scenarios. This is why a special model adapted to the national conditions, called LASAM (Latvian Agricultural Sector Analysis Model), was created in Latvia, making it possible to use historical data on the development of agricultural sectors, medium-term price projections for agricultural products in the EU, changes in support policy, as well as the necessity for the resources used to project the long-term (up to 2050) development of agriculture. The LASAM model covers the crop sector, the animal sector and the overall socioeconomic development, as well as the growth of organic farming and greenhouse gas (GHG) emissions. This paper discusses the main objectives achieved in developing a decision support tool and presenting the research results: LASAM was used to prepare projections of the possible development of Latvia’s principal sectors of agriculture until 2050, considering the necessity to reduce GHG emissions, made available through the LASAM web application. Given that the projection data obtained by LASAM are public, they can be used (1) for national policy making in rural business development, which affects the development of the economy as a whole; and (2) internationally, to compare the projections made in Latvia with those obtained through various agricultural sector models and projected development trends.

Trusted environmental and geological information to support Australian energy resource development in a changing world

The Australian Government’s Trusted Environmental and Geological Information (TEGI) program is a scientific program led by Geoscience Australia. The program is part of the Government’s Strategic Basin Initiative under its Gas-fired Recovery agenda, implemented as a post-COVID19 response to stimulate the economy. This program will deliver regional geological and environmental assessments underpinned by transparent, trusted baseline geological and environmental data, commencing in the north Bowen and Galilee and the Cooper and Adavale Basins. This repository of information is to be used in support of bringing forward energy and mineral developments in basins identified by the Government as strategic. This paper discusses how coupling resource assessments with baseline information such as groundwater, geology, energy and mineral resources, surface water and protected environmental matters, can be used to support exploration and development decisions by industry, regulators and other stakeholders. For example, by establishing a regional baseline resource assessment, through prospectivity play mapping, environmental assessments can be prioritised to match resource prospectivity. In anticipating future development scenarios, potential impacts on environmental assets, including groundwater, can be assessed in advance and with key knowledge gaps identified for redress. This approach aims to optimise the regulatory pathway to resource development and increase regulatory efficiency as future development opportunities arise across the scope of petroleum, minerals, carbon capture and storage, and hydrogen storage and production. An example of Geoscience Australia’s work on the Adavale Basin is presented in this paper describing the first steps in linking energy resources and environmental assessments in a changing world.