Exploration Of Scenarios Research Articles

Analytical solutions of ray-tracing equations in generalized elliptical anisotropy

Ray-tracing in anisotropic media is pivotal for interpreting observed seismic data and creating high-resolution images of subsurface structures, which are crucial in exploration geophysics. Elliptical anisotropy, a simplified model that approximates a transversely isotropic medium, is particularly relevant for geologic settings such as shale formations or stressed sedimentary layers where directional dependencies of seismic velocities are pronounced. We develop an analytical solution of the ray-tracing equations for a 2D inhomogeneous and anisotropic medium, where velocities depend elliptically on direction and increase linearly with depth — a scenario frequently encountered in stratified geologic formations. Unlike previous studies that assume constant ellipticity throughout the medium, our approach allows for variations in ellipticity, providing a more flexible and realistic representation of subsurface anisotropy. The phase velocities along the x- and z-axes are not necessarily multiples of each other at every point, offering a generalized version of the elliptical anisotropy. This enhancement may enable more accurate predictions and interpretations of observed seismic data, particularly in complex exploration scenarios. The analytical solution yields expressions for the ray paths and the wavefront normals. By setting the normals of the wavefront at the seismic source point and the location of the seismic source as the initial conditions in phase space, we explore the evolution of these wavefront normal curves across different types of the elliptical anisotropy. Our innovative approach includes plotting the evolution of wavefront normal curves on the generalized momentum coordinate plane of the phase space — that commonly overlooked in traditional models focused only on position coordinates.

Décroissance et capital : Assembler une théorie du changement centrée sur le pouvoir

Making degrowth emerge from the confines of capitalism remains a major challenge. In this context, this thesis develops a power-centred theory of change, noting that the literature on degrowth has done little to investigate the obstacles to transformations or their potential for systemic scale in the face of capital accumulation. Examining and rethinking the relationship between capital accumulation and degrowth, conceptualising the key dynamics of transformation and resistance, and developing exploratory scenarios, this research draws on an interdisciplinary, processual and systemic approach. Inspired principally by the theory of Capital as Power, the thesis conceptualises transition as a confrontation between transformation and sabotage. The thesis offers an original perspective on the challenges and possibilities of transition to degrowth in a capitalist context, inviting a renewal of thinking about socio-ecological change and a direct confrontation with capitalist power dynamics.

Under what conditions? A scenario‐based approach for exploring the prerequisites of future events

AbstractIn an increasingly complex world, futures thinking can be used to understand the conditions that define future events' realization. This paper presents a novel approach to explore under what conditions some chosen future event would occur. The approach can be seen as a fusion of exploratory scenarios with the backward‐looking perspective of backcasting while resembling cross‐impact methods in how future events' realization arises from the interaction of several uncertain assumptions. The approach maps the causal mechanisms and assumptions that lead to the investigated event's realization, and results in a subset of assumption combinations that lead to the event being realized or not, and scenario sets where the event is either realized or not. This analysis provides insights beyond “Is the event likely to occur?”, revealing the various circumstances under which it can occur. We also provide ways for considering probabilities and deliberate decisions within the approach. We illustrate the approach with three example cases from different problem domains, such as reaching long‐term climate targets, and employing various methods, such as causal mapping, influence diagrams, and optimization. We conclude with a discussion on the approach's potential to enhance foresight practice, emphasizing its synergistic relation to existing methods and its contribution to a richer, more nuanced anticipation of the future.

Infliximab in Inflammatory Bowel Disease: Leveraging Physiologically Based Pharmacokinetic Modeling in the Clinical Context.

In this study, a physiologically based pharmacokinetic (PBPK) modeling framework was employed to explore infliximab exposure following intravenous (5 mg/kg) and subcutaneous administration (encompassing the approved 120 mg flat-fixed dose as a switching option) in virtual adult and pediatric patients with inflammatory bowel disease (IBD). The PBPK model and corresponding simulations were conducted using the PK-Sim® software platform. The PBPK simulation indicated that a 120 mg subcutaneous flat-fixed dose might not be optimal for heavier adults with IBD, suggesting the need for infliximab dose escalation. For an older virtual pediatric patient (14 years old), subcutaneous administration of a 120 mg flat-fixed dose appears to be a feasible IBD treatment option. In the final exploration scenario, the model was extended to predict hypothetical subcutaneous infliximab doses in a virtual pediatric population (6-18 years old), stratified into three weight bands (20-30 kg, 30-45 kg, and 45-70 kg), that would yield post-switch trough concentrations of infliximab comparable to those seen in adults with the 120 mg flat-fixed subcutaneous dose. The PBPK-model-informed dose suggestions were 40 mg for the 20-30 kg band, 80 mg for the 30-45 kg band, and 120 mg for the 45-70 kg band. As demonstrated in this paper, the PBPK modeling framework can serve as a versatile tool in clinical pharmacology to investigate various clinical scenarios, such as exploring alternative dosing regimens and routes of administration, ultimately advancing IBD treatment across diverse (sub)populations of clinical interest.

A Framework for Using Regional Scenarios in Racial Equity Planning

Problem, research strategy, and findings Planning under uncertainty and planning for racial equity both require imagination. In confronting the uncertain future, regional planners often opt for exploratory scenario planning: telling multiple future stories to prepare for any outcome. For equity planning, imagination supports vision beyond the deeply unequal present condition, wherein policy tinkering is insufficient for necessary change. And yet, scenario planning and equity planning are estranged. Although regional planners wish to engage both, they lack guidance on how. I look to close this gap by providing a framework (the Framework) for using scenarios in equity planning. The Framework builds on the five types of racial equity, a six-stage hybrid scenario process, and the three outcomes of public-sector scenarios. Using the Framework, I assessed the inclusion of equity in the Delaware Valley Regional Planning Commission’s Dispatches From Alternative Futures scenario plan. This plan successfully raises racial equity as a concern for the future of the Philadelphia (PA) region. However, the stakeholder group was not sufficiently diverse for deliberative equity and the scenario planners did not use tools that could assess the distributional outcomes. Neither epistemic nor restorative equity were a significant part of the scenario plan, leaving open the possibility for co-designed scenarios for a racial equity future. Takeaway for practice Metropolitan planning organizations (MPOs) can use the Framework to ensure that exploratory scenarios advance equity goals. Although the Framework can supply a starting point for MPOs, the most important voices are those from Black, Indigenous, and people of color (BIPOC) and other marginalized communities. Scenario planners should consider how they can reach out to community members not just as stakeholders but as co-creators of a more epistemically equitable scenario planning process, one that addresses the uncertainties and aspirations that already percolate within these communities.

Large-scale 3D inversion of semi-airborne electromagnetic data — Topography and induced polarization effects in a graphite exploration scenario

The transition toward renewable energies demands a secure supply of critical raw materials and requires efficient noninvasive methods for deep earth resource exploration. The novel, deep electromagnetic (EM) sounding for the mineral exploration semi-airborne EM (semi-AEM) exploration concept aims at the efficient exploration of resources down to a depth of 1 km. Here, we evaluate a large-scale semi-AEM exploration study in a graphite mining district in eastern Bavaria, Germany. The derived 3D semi-AEM model is based on approximately 70,000 complex-valued data points recorded using seven transmitters. Strong conductivity contrasts with dominant east–west-trending anomalies are visible. Shallow high-conductivity structures correlate well with the known occurrence of graphite and match existing helicopter-borne EM results. The main anomaly reaches down to several hundred meters depth. To investigate different interpretation scenarios for large-scale semi-AEM data, we determine the effect of topography and analyze the feasibility of fast 2D inversion applications. To validate the robustness of the 3D semi-AEM model, the data set is inverted with two different 3D inversion algorithms and the results are compared. The presence of graphite leads to significant induced polarization (IP) effects with considerably high chargeabilities superposing EM induction. We include these effects in a realistic 3D inversion using a synthetic data study to analyze if the IP effect alters the overall conductivity structure and demonstrate that the obtained 3D model is reliable.

Effect of wildfire on the prevalence of opioid misuse through anxiety among young adults in the United States: a modeling study

BackgroundExposure to climate change events like wildfires can lead to health and mental health problems. While conceptual frameworks have been hypothesized describing the potential relationship between disaster exposure and substance use, the association remains under-researched and unquantified.MethodsWe constructed a quantitative portrayal of one proposed conceptual framework that focuses on the intermediary role of anxiety. We used the Monte Carlo simulation to estimate the impact of wildfire exposure on opioid misuse outcomes through increased anxiety. We searched for and extracted prior empirical evidence on the associations between wildfire anxiety and anxiety-opioid misuse. Three scenarios were devised: in S1 the impact of wildfire on opioid misuse was limited to increasing anxiety incidence; in S2 we also considered the additive role of altered anxiety phenotype; and in S3 we further considered the role of increased opioid-related consequences of pre-existing anxiety due to wildfire exposure.ResultsModels show that the prevalence of opioid misuse post-wildfire may rise to 6.0%-7.2% from a baseline of 5.3%. In S1, the opioid misuse prevalence ratio was 1.12 (95% uncertainty interval [UI]: 1.00 – 1.27). The two exploratory scenarios, with less stringent assumptions, yielded prevalence ratios of 1.23 (95% UI: 1.00 – 1.51) and 1.34 (95% UI: 1.11 – 1.63).ConclusionsOur modeling study suggests that exposure to wildfires may elevate opioid misuse through increasing anxiety incidence and severity. This can lead to substantial health burdens, possibly beyond the duration of the wildfire event, which may offset recent gains in opioid misuse prevention.

Are pensions “growth-dependent”?

Limits to growth raise concerns about “growth dependencies” or adverse social effects that follow if the economy does not grow. The first point of this article is that identifying pensions as growth-dependent is more conditional than has so far been recognized. It requires operationalizing growth dependence, making complete economic assumptions, and scoping the issue to specific pension functions. The second point is to take those steps and, with exploratory scenarios, show how growth dependence is and is not evident under all ideal-type pension-financing principles. All plans would be growth-dependent if we interpret the end of growth as lower interest rates and earnings development but higher inflation than under growth assumptions. However, no plan shows growth dependence under all assumptions. I also discuss post-growth pensions, arguing that funded pensions entail vulnerability and distributional issues that make them problematic in a non-growing system. Unfunded financing combined with comprehensive social and economic policies could work as a long-term approach. Growth dependence is an important research area. However, without specification, the concept may blur the conditionalities that generate and alleviate pension vulnerabilities.

A reliable cluster-based opportunistic routing protocol for underwater wireless sensor networks

Underwater Acoustic Sensor Networks (UASNs) have gained significant popularity and application in various marine engineering exploration scenarios, driven by the global evolution of the ocean ecosystem. However, UASNs face numerous challenges arising from the unique characteristics of the underwater environment and acoustic channels, such as limited energy resources, unreliable communication, and dynamic network topology in uncertain environments, all of which impact the network lifetime and transmission reliability. To address these challenges and enable efficient underwater data packet transmissions, this paper proposes a reliable cluster-based routing method called RCRP. The RCRP organizes sensor nodes into clusters, where cluster heads transmit the fused data to the sink node through multi-hop forwarding. To overcome routing voids caused by node failures during packet transmission, a prediction model based on the Markov chain is introduced to identify void nodes and inform neighboring nodes about the routing holes. Furthermore, a connection prediction mechanism is developed to tackle changes in the uncertain network topology, taking into account node mobility and the received SNR. For packet transmissions, a waiting mechanism inspired by the opportunistic routing (OR) paradigm is proposed, which determines the optimal forwarding route based on the calculated probability of successful connection between nodes. Simulation results demonstrate that RCRP outperforms existing routing protocols in terms of packet delivery ratio, surviving time, and energy consumption, highlighting its effectiveness in enhancing the performance of UASNs.

Ending groundwater overdraft without affecting food security

Groundwater development is key to accelerating agricultural growth and to achieving food security in a climate crisis. However, the rapid increase in groundwater exploitation over the past four decades has resulted in depletion and degradation, particularly in regions already facing acute water scarcity, with potential irreversible impacts for food security and economic prosperity. Using a climate–water–food systems modelling framework, we develop exploratory scenarios and find that halting groundwater depletion without complementary policy actions would adversely affect food production and trade, increase food prices and grow the number of people at risk of hunger by 26 million by 2050. Supportive policy interventions in food and water systems such as increasing the effective use of precipitation and investments in agricultural research and development could mitigate most negative effects of sustainable groundwater use on food security. In addition, changing preferences of high-income countries towards less-meat-based diets would marginally alleviate pressures on food price. To safeguard the ability of groundwater systems to realize water and food security objectives amidst climate challenges, comprehensive measures encompassing improved water management practices, advancements in seed technologies and appropriate institutions will be needed.

The impact on climate and emissions of clean household cooking energy policies in Tanzania

The transition to cleaner cooking fuels currently ongoing in many low- and middle-income countries may have benefits for health, but also climate. We have studied the climate implications of the SE4ALL policy goal in Tanzania of “75 percent access to modern cooking solutions by 2030” in which mainly firewood and charcoal are replaced by LPG and electricity. To see the long-term climate benefit, we have estimated the reduction in CO2-equivalent emissions (GWP100) and effect on global temperature until 2100 relative to the baseline for three explorative scenarios with different levels of ambition: baseline growth to nearly complete transition to modern cooking. Due to population growth the energy demand and CO2-eq. emissions increase even in the most ambitious energy transition scenario. We model reduction in global temperature in 2100 relative to the baseline to be between −0.63 and −2.9 milli °C. While we confirm the climate benefit of a transition to cleaner cooking fuels in households, the benefit is smaller than previously thought. This is mainly due to a much weaker radiative forcing of black carbon and somewhat stronger radiative forcing for organic carbon, in the climate parameters from IPCC Sixth Assessment Report.

Participatory mapping in exploratory scenario planning: Necessity or luxury?

Exploratory scenarios based on participatory approaches proved helpful in dealing with uncertainty and complexity in urban and transport systems. Such scenarios usually create coherent and manageable narratives that capture broad patterns and trends at global scales. However, significant difficulties exist in bridging exploratory scenario narratives with spatial and local realities, which is crucial for guiding policymaking in urban, regional, and mobility planning. This paper explores whether and how exploratory scenario narratives and participatory mapping processes can establish a reciprocal relationship, wherein narrative-based maps contribute to spatially shaping scenario narratives. It uses an experimental approach involving three participatory workshops with experts and local stakeholders specifically tailored to the mapping of land use and transportation-related scenario narratives for the year 2050 in the Henares Corridor (Madrid, Spain). The spatial transformations mapped during workshops have indicated that participatory mapping processes have an impact on scenario narratives in different ways, enabling the identification of three categories of mapping episodes with different meanings: (i) complementing narratives, (ii) expanding narratives, and (iii) modifying narratives. The paper closes by examining the implications of the obtained findings for policymaking, including a reflection on the research’s limitations and potential for application in real-world planning processes.

The value of scenario discovery in land-use modeling: An automated vehicle test case

Long-range planning is an uncertain endeavor. This is especially true for urban regions, small ships in a global urban storm that are too small to influence macro policies and without the land-use powers of local governments. Exploratory scenarios, the established practice for planning under deep uncertainty, have inspired stakeholders to consider multiple futures but have fallen short of identifying robust and contingent policies. We need new tools to plan under conditions of deep uncertainty. Scenario discovery is a technique for using simulation models to explore the performance of policy options across uncertain scenarios. This paper presents an application of scenario discovery in land-use modeling and asks what this computationally intensive approach offers relative to a more circumscribed exploration of uncertainty space. The introduction of autonomous vehicles (AVs) and their associated impacts on land use provide a test case demonstrating this method, as well as a topic of substantive concern. This research concludes that scenario discovery is particularly valuable for identifying the conditions under which contingent policies are likely to succeed. In terms of AV policy, this research establishes that forward-thinking, transit-oriented-development strategies can mitigate spatial dispersion while also reducing overall housing costs. In addition, I find that AVs may blunt the impacts of some current policy tools if they extend the distance individuals are willing to travel to work.

Breaking out of conventions: How scenario planners can increase their reflexivity regarding societal imaginaries

Futures imagined in scenario processes reflect both stakeholder perspectives and broader societal imaginaries: collectively-held, institutionally-stabilized visions of the future. The presence of imaginaries has mostly remained implicit in studies of scenario planning, especially in development contexts. We argue that scenario planning will benefit from reflexivity regarding imaginaries. Here, reflexivity refers to an awareness regarding different perspectives, assumptions, values, and—oft-hidden—politics at play. We developed a framework of relevant imaginaries and assessed how and to what extent these are expressed in scenario narratives, through analyzing seven scenario sets focused on agriculture, food security and climate change in the Global South. Our results show that neoliberal and sustainable development imaginaries are dominant in these scenarios. Imaginaries from the Global South are scarcely represented—arguably because of that, we observe few regional perspectives on potential challenges in these scenario sets. We conclude that the scenario sets offer effective critique on neoliberal mechanisms and global development dynamics, but do not provide significant room for transformational alternatives from the Global South. We argue that opening up explorative scenario planning to more pluralistic conceptions of the future can greatly enhance its reflexivity, and a representative mix of imaginaries allows for scenario planning that leads to more transformational policies.

Performance investigations of auxiliary‐space Maxwell solver preconditioned iterative algorithm for controlled‐source electromagnetic induction problems with electrical anisotropy

AbstractMany studies have highlighted the superior performance of iterative solvers employing the auxiliary‐space Maxwell solver preconditioner in controlled‐source electromagnetic induction problems featuring isotropic conductivity. The importance of considering the presence of electrical anisotropy in controlled‐source electromagnetic data has been well recognized. However, considering anisotropic conductivity will impose difficulty in robustly solving the final system of linear equations as the electrical anisotropy may significantly increase its condition number and degrade the performances of iterative solvers. Whether or not iterative solvers using the auxiliary‐space Maxwell solver preconditioner have similar superior performances in the case of arbitrary electrical anisotropy is still an issue to be discussed. In this study, within the framework of finite element simulation employing unstructured tetrahedral meshes, we conduct a comprehensive examination to evaluate the performance of the flexible generalized minimum residual solver with the auxiliary‐space Maxwell solver preconditioner for three‐dimensional controlled‐source electromagnetic forward modelling problems involving arbitrary anisotropic media. Tests on synthetic one‐ and three‐dimensional models show that our iterative scheme performs better than widely used iterative or direct solvers for controlled‐source electromagnetic anisotropy forward problems. Its convergence rate is nearly independent of working frequencies, anisotropy ratio and problem size. Finally, we applied the newly developed parallel iterative scheme to the Bay du Nord reservoir in a complicated real‐life offshore hydrocarbon exploration scenario characterized by anisotropic conductivity, in which our iterative scheme with an auxiliary‐space Maxwell solver preconditioner has good robustness. Furthermore, we investigated how data responses at different frequencies are sensitive to the actual hydrocarbon reservoir. Our sensitivity analysis revealed that data at large measuring offsets are considerably more sensitive to the reservoir than data at shorter measuring offsets. We also assessed the impact of neglecting anisotropy in data analysis for the realistic example and found that ignoring anisotropy can lead to noticeable changes in the data. This suggests that considering anisotropy in the interpretation of the observed data is essential to guarantee the precision of controlled‐source electromagnetic field surveys.

Tomofast-x 2.0: an open-source parallel code for inversion of potential field data with topography using wavelet compression

Abstract. We present a major release of the Tomofast-x open-source gravity and magnetic inversion code that incorporates several functionalities enhancing its performance and applicability for both industrial and academic studies. The code has been re-designed with a focus on real-world mineral exploration scenarios, while offering flexibility for applications at regional scale or for crustal studies. This new version includes several major improvements: magnetisation vector inversion, inversion of multi-component magnetic data, wavelet compression, improved handling of topography with support for non-uniform grids, a new and efficient parallelisation scheme, a flexible parameter file, and optimised input–output operations. Extensive testing has been conducted on a large synthetic dataset and field data from a prospective area of the Eastern Goldfields (Western Australia) to explore new functionalities with a focus on inversion for magnetisation vectors and magnetic susceptibility, respectively. Results demonstrate the effectiveness of Tomofast-x 2.0 in real-world studies in terms of both the recovery of subsurface features and performances on shared and distributed memory machines. Overall, with its updated features, improved capabilities, and performances, the new version of Tomofast-x provides a free open-source, validated advanced and versatile tool for constrained gravity and magnetic inversion.

Dare to imagine. Explorative scenarios for re-shaping human-nature relationships in an inner periphery in the Italian Apennines

The article investigates the relationship between planning and future by presenting and discussing the application of the scenario-making approach to an inner periphery in the Italian Northern Appennine, the semi-abandoned village of Ebbio, in the province of Piacenza. Inner peripheries are commonly described as the territories that have “no future”, namely those where the idea of the future is most problematic due to socio-economic decline, marginalization, and demographic shrinkage. In particular, we present two explorative scenarios and discuss them comparatively, looking at their space and time declinations, and their capacity to shape different patterns of human-nature relationships. The two scenarios imagine the case study transformed, respectively, into an “agroecological village” in which food is interpreted as a key component in the creation of a new local economy based on agroecological practices, and into a “wild village” with the invasion of nature in the village according to a “more-than-human” perspective. Results highlight the relevance that the scenarios’ reflexive and dialogic construction can have for exploring possibilities about the future that were not previously considered by local institutions and civil society. Moreover, the scenario-making approach proved a relevant means to guide local communities to change their relationship with and perception toward nature, passing from a traditional view of “dominance” over natural resources and habitats, toward more balanced patterns of coexistence shaped by reciprocal socio-ecological relations.

3D seismic mask auto encoder: Seismic inversion using transformer-based reconstruction representation learning

Estimating acoustic impedance from seismic data is a crucial step in reservoir characterization. While data-driven impedance inversion based on deep learning has shown promising results, it relies heavily on extensive well logs for labeling, which is often impractical in many exploration scenarios. Recently, the zero-shot or few-shot learning performance of Pretrained Foundation Models like Generative Pre-trained Transformer (GPT) and Mask Auto Encoder (MAE) has highlighted that knowledge learned from vast amounts of unlabeled data can be transferred to downstream tasks with minimal labeled data. However, applying Transformer-based representation learning models to 3D seismic data inversion poses three challenges: (1) Computational and memory constraints due to the high-dimensional nature of the data; (2) Difficulty in extracting fine-grained image features using Transformers, hampering high-frequency impedance inversion; (3) Fixed input size in Transformers, leading to inversion artifacts. In this work, we introduce the Seismic Mask Auto Encoder (SeisMAE), a Transformer-based representation model tailored for the inversion of 3D seismic data. It incorporates three key components: (1) Aggregated dimensionality reduction encoding to handle redundancy in seismic data, significantly improving computational efficiency; (2) Multi-scale self-attention feature fusion to enhance the model’s capacity for low-level feature representation; and (3) A stitching decoding strategy to eliminate inversion stitching artifacts. Experimental validations highlight the efficacy of our approach. On the synthetic SEAM I dataset, we demonstrate the effectiveness of each component and SeisMAE’s superior performance. For real-world data on The Netherlands F3, SeisMAE delivers reliable inversion outcomes with only four labeled examples. We compared SeisMAE against various inversion techniques, including 1D Convolutional Neural Network (1D-CNN), UNet-based, HRNet-based, and TransInver, where SeisMAE exhibited significant advantages.

Socio-Environmental Overview of The Main Sugarcane Producing Municipalities in Sergipe Between the Years of 2001 and 2022

Objective: Analysis of the socio-environmental situation of the main sugarcane producing municipalities in the state of Sergipe, in the period between 2001 and 2022. Theoretical Framework: Sugarcane cultivation represents an important economic role for communities and countries that produce this commodity. In this scenario, Brazil emerges as the main sugarcane producer on the planet and, along with the benefits arising from the agro-industrial sugarcane production chain, there are socio-environmental problems arising from the anthropization of the landscape and natural resources allocated in the production of co-products of this culture that need to be reviewed in light of climate emergencies and the demands of different social actors. Method: The research has an exploratory nature, using scientific articles available from Science Direct and Capes Periodical Platform and secondary data collected on the Mapbiomas and Terrabrasilis platforms. Results and conclusions: The results showed the dissonance between the global analysis of environmental degradation indicators, such as fires and deforestation, and the data relating to each municipality analyzed. And it was concluded that there is an urgent need to re-analyze public policies for monitoring and controlling socio-environmental indicators in order to contain the anthropization processes caused by sugarcane cultivation. Implications of the research: This research allows us to clearly understand the socio-environmental dynamics caused by sugarcane cultivation in the main sugarcane producing municipalities of Sergipe, in order to contribute to a realistic debate on the current stage of environmental degradation and on the construction of the near future due to social and environmental demands arising from changes in the climate. Originality/value: No analysis was found on the set of municipalities studied based on the main agricultural crop produced, which implies a scenario of exploration that is not only reflective and political but also open to new work that can be developed in each of these municipalities separately, or together, with the purpose of bringing quality of life and conscious and environmentally appropriate development to the communities in this group of municipalities and to the state of Sergipe.

Scenario Planning Approach of Coal Market Sales on PT ABCoal Towards Energy Transitions Era

Nowadays, energy transition is one of the major events faced by coal producers, particularly Indonesian coal producers. PT ABCoal is one of the largest coal producers in Indonesia. Based on the company’s 5-year plan, PT ABCoal is expected to increase its production volume from 25 to 30 million metric tons to around 35 to 45 million metric tons. Within the export market, most of the sales (around 50%) were sold to the Chinese market through off-takers. Meanwhile, the 25% for the domestic market is obliged by the Indonesian government regulation and is not negotiable. This research aimed to understand the future condition of the coal market within the next five years and what scenario would likely happen in the next five years. Afterward, it would try to provide the coal sales strategy that will fit into those scenarios using explorative scenario planning with expert interviews to obtain the perspective and knowledge from an interviewee who has expertise in this field. The obtained answers are then mapped into the PESTLE analysis framework to obtain more understanding and collect thorough driving forces data. The critical impact and high uncertainty were determined through qualitative-quantitative analysis from interview results using content analysis. Based on the analysis in this research, it is concluded that the top driving forces that are being used for scenario elements are coal price and government regulation. This research creates four scenarios that are called business as usual, finding a new home, home sweet home, and more is better. Each scenario needs a different approach to coal sales strategy to optimize its revenue and ensure the sustainability of its selling operation. The coal sales strategy optimization for each scenario is based on domestic and export composition, preferable domestic industry target composition, and developing-country export composition.