Dynamic Scenario Analysis Research Articles

Projected waste and recycling potential of China’s photovoltaic industry

The massive expansion of the photovoltaic (PV) industry, driven by the decarbonization of the energy mix, has led to an exponential increase in PV waste. In order to ensure the stable development of the PV industry, it is crucial to make accurate macro forecasts of future PV waste in China. In this study, a multifactor installed capacity forecasting model based on long- and short-term bi-directional memory GRA is proposed to predict the cumulative installed PV capacity in China from 2024 to 2050. The Weibull distribution and dynamic scenario analysis are utilized to quantify the recycling of panel materials for different technologies and to assess the potential economic value of recycling. The results show that China’s cumulative installed PV capacity will reach 2,901 GW by 2050. 99.75 million tons, 40.96 million tons, and 5.29 million tons of C-si, CdTe, and CIGS panels could be cumulatively recycled in the baseline scenario of Regular loss. Distributed PV will generate more end-of-life equipment than centralized PV, up to an estimated 11.8–0.5 % more. In all scenarios, the capacity of recycled equipment averages up to 64.7 % of new capacity, with a significant complementary effect of recycling. Recycling is projected to generate $13.99 billion, with significant economic benefits. Helps decision makers to take measures based on recycled materials from different technologies.

Toward the full implementation of the water-energy-food nexus in computable general equilibrium modelling: methods and macroeconomic implications

ABSTRACT This paper contributes to the advancement of Computable General Equilibrium (CGE) modelling in addressing the Water-Energy-Food (WEF) Nexus. As such, it introduces water resources as a production factor for both the energy sector and irrigated agriculture, as well as their competition for the endowment, aiming to explicitly represent additional components of the WEF with respect to a standard CGE in the literature. Thus, it develops different modelling structures by computing impacts on regional GDP, sectorial prices, and production outputs in response to hypothetical water scarcity scenarios. This analysis allows for the determination of the role of data and modelling assumptions, such as production function, water substitutability with other endowments, water mobility across sectors, and sectorial water intensity, in influencing the results. Finally, the paper develops a dynamic scenario analysis, showing that an enhanced representation of the Nexus can significantly affect the macroeconomic dynamics of the simulations and their regional implications.

Scenario analysis on carbon peaking pathways for China's aluminum casting industry

To support high-quality carbon peaking, a scenario analysis of carbon peaking pathways according to an industrial chain perspective considering both material and part production needs exploring. As a critical segment in the aluminum industrial chain, aluminum casting industry was focused on in this paper. A bottom-up scenario analysis approach was proposed for the carbon emission simulation of China's aluminum casting industry, including: (1) a carbon emission assessment model based on material flow analysis and life-cycle assessment, (2) key influence factor selection and variation scenario prediction, (3) static and dynamic scenario analysis, and (4) driving factor decomposition analysis. Key findings are as follows: (1) China's aluminum casting industry accounted for about 1.1% of the national carbon emissions in 2020; (2) the production stage accounted for around 15% of the total carbon emissions of China's aluminum casting industry in 2020; (3) carbon peaking probabilities before 2030 for the static and dynamic scenario analysis are around 60% and 35%, respectively; and (4) the carbon peaking result differences in whether considering the production stage are about 20% for the static simulation and average 40% for the dynamic simulation. These findings effectively support the formulation of a high-quality carbon peaking pathway.

Quantitative and dynamic scenario analysis of SDGs outcomes upon global sustainability 1990–2050

The UN Sustainable Development Goals (SDGs) are the keystone policy framework for countries to achieve sustainable development. However, in fulfilling the SDGs, there is no definitive evaluation of the potential long-term outcomes upon the level, nature, and dynamics of global sustainability. This is crucial to understand, as otherwise, governments and societies may implement policies which achieve the SDGs, but are detrimental to the long-term global co-evolutionary environment-human relationship and system. Therefore, this paper determines and evaluates the potential global sustainability outcomes of the implementation of the SDGs for the specified period of 1990–2050. This is achieved by the application of the Sustainability Dynamics Framework to the results of the Earth3 model. The Earth3 model evaluated the degree of success of implementing the SDGs in respect to four development scenarios: (1) Same (business-as-usual); (2) Faster; (3) Harder and (4) Smarter. The results from the SDF application indicate that Scenario 4 (Smarter) had the best potential outcomes of the scenarios evaluated, approaching a borderline weak-strong sustainability state by the end of the specified period. The other scenarios had relatively stagnant levels of very weak sustainability. Based upon the results obtained, the broader context and implications are discussed, primarily in respect to the role and impact of the SDGs. The paper concludes by stating that humanity as a species needs to fundamentally transform its relationship with the environment, or risk being lost not only as a species, but also to the planet as well.

Dynamic material flow analysis of Chinese ethylene production processes and optimal pathway exploration with potential environmental-economic impacts

China is expected to become the largest ethylene producer globally; environmental problems related with traditional ethylene production process of Chinese petrochemical industry will be further stern. This study aims to propose a feasible and optimal ethylene production expansion pathway to improve the trade-off between the environment and economy. A novel approach was adopted with material-energy-value flow analysis integration by combining dynamic scenario analysis. According to the results of scenario analysis, cleaner and lightweight production processes optimization achieved by adopting the alternative ethylene production process mix alleviated environmental pressure and achieved a weak decoupling of the low-carbon economy. A 26.1% increase in carbon productivity was achieved compared with the baseline scenario, whereas the coal to ethylene route should be phased-out, as more than 90% of the pollutants are generated by 10%–17% of the coal to ethylene facilities. However, CO2 emissions from ethylene will inevitably increase along with doubling ethylene production. An imbalance in pollutant generation also emerges if large-scale naphtha is exclusively promoted for ethylene plant implementation. The study provides methodological support for investigating feasible roadmaps for key product capacity expansion, and has practical meaning for high-quality industrial development domestically and globally.

Dynamic Scenario Analysis of Science and Technology Innovation to Support Chinese Cities in Achieving the "Double Carbon" Goal: A Case Study of Xi'an City.

Since the Chinese government proclaimed the "double carbon" goal in 2020, carbon emissions reduction has become an important task for the Chinese government. Cities generate more than 60% of carbon emissions. There are many challenges in achieving the "double carbon" goal for the cities of China. Science and technology innovation (STI) provides a feasible path, and the mechanism of STI influencing carbon emissions is analyzed. The STI factors, economic factors, energy factors, and population factors are studied based on the generalized Divisia index method. According to the decomposing results, science and technology innovation investment is the most important increasing factor in carbon emissions, and technology innovation investment efficiency is the most important decreasing factor, respectively. Three scenarios are set up and simulated with Monte Carlo technology evaluating the city of Xi'an in China. Under the baseline development scenario, it cannot achieve the carbon peak goal, and the uncertainty of carbon emissions increases. Under the green development scenario, it will peak in 2051, with a 95% confidence interval of 6668.47-7756.90 × 104 tons. Under the technology breakthrough scenario, the lower and median boundaries of carbon emissions peak at 4703.94 × 104 tons and 4852.39 × 104 tons in 2026, and the upper boundary peaks at 5042.15 × 104 tons in 2030. According to the Environmental Kuznets Curve theory, it will peak between 2028 and 2029 with a GDP per capita of CNY 153,223.85. However, it will fail to achieve the carbon neutrality goal by 2060, and should rely on the national carbon trading market of China to achieve the goal with a trading volume of 2524.61-3007.01 × 104 tons.

Dynamic scenario analysis of CO2 emission in China’s cement industry by 2100 under the context of cutting overcapacity

Dynamic scenario analysis of CO2 emission in China’s cement industry by 2100 under the context of cutting overcapacity

Energy consumption inequality in China: What can an agent-based model tell us?

China is a major energy consumer, however, related empirical research on China's unequal energy consumption is very limited. Therefore, according to the data from 30 provinces and cities, this study aims to establish a simulation model to analyse the Gini coefficient (the Lorenz curve) of China's energy consumption, and identify the main factors affecting the Gini coefficient through dynamic scenario analysis. During the simulation cycle (from 2022 to 2081), the average Gini coefficient of energy consumption fluctuates between 0.30 and 0.41, which indicates the inequality is slightly high. But the maximum value fluctuation ranges from 0.40 to 0.50, which indicates the inequality is high. The author also found that three factors—technological level, government subsidies, and growth rate of energy supply—can significantly affect the Gini coefficient of energy consumption. It is necessary to promote the technological level, increase subsidies for energy production, and promote the growth of total energy supply to significantly reduce inequity in energy consumption.

Will China's Carbon Intensity Achieve its Policy Goals by 2030? Dynamic Scenario Analysis Based on Stirpat-Pls Framework

Will China's Carbon Intensity Achieve its Policy Goals by 2030? Dynamic Scenario Analysis Based on Stirpat-Pls Framework

Modeling of Characteristics on Artificial Intelligence IQ Test: a Fuzzy Cognitive Map-Based Dynamic Scenario Analysis

This research article uses a Fuzzy Cognitive Map (FCM) approach to improve an earlier proposed IQ test characteristics of Artificial Intelligence (AI) systems. The defuzzification process makes use of fuzzy logic and the triangular membership function along with linguistic term analyses. Each edge of the proposed FCM is assigned to a positive or negative influence type associated with a quantitative weight. All the weights are based on the defuzzified value in the defuzzification results. This research also leverages a dynamic scenario analysis to investigate the interrelationships between driver concepts and other concepts. Worst and best-case scenarios have been conducted on the correlation among concepts. We also use an inference simulation to examine the concepts importance order and the FCM convergence status. The analysis results not only examine the FCM complexity, but also draws insightful conclusions.

Dynamic Macro Scenario Analysis via Bridge Sampling

Dynamicmacroeconomicmodels shouldby designbe amenabletomacro scenario analyses under some stated policy objective or presumed stress environment, for example, anticipating how an economy would look like with an inflation target or under severe economic downturn. However, such analyses are difficult to conduct mainly due to the technical complexity associated with partially conditioning on a future scenario. In this paper, we devise a generic bridging sampling method for dynamic scenario analyses that is flexible with scenario setting while accommodating parameter uncertainty. In contrast to the literature, our method is efficient and can be straightforwardly applied beyond linear-Gaussian models. We demonstrate that macroeconomic models with comparable forecasting performance can have very different implications while being considered under a policy scenario. Dynamic scenario analysis thus goes beyond helping policy formation, and now provides a new angle for discriminating competing models with a specific reference to real-world usage.

Synergetics and development processes in socio-economic systems: Search for effective modeling constructs

Natalya N.Lychkina - Associate Professor, Department of Information Systems and Technologies in Logistics, National Research University Higher School of EconomicsAddress: 20, Myasnitskaya Street, Moscow, 101000, Russian FederationE-mail: nlychkina@hse.ru This paper explores the genesis of socio-economic processes of strategic development of social transformations in a transition economy. The author studies the system patterns and structural and dynamic aspects of developing socio-economic systems, defining the need for appropriate modeling methods. Restrictive features of traditional mathematical modeling are analyzed. Synergetics is applied as a theoretical and methodological fundamental of research and modeling of developing socio-economic systems. Modeling social behavior, individual choice, various forms of social interaction and self-organization processes are recognized to be significant aspects. Searching for methods of model description is based on carrying out interdisciplinary research in the field of economic and social sciences, using modern paradigms (system dynamics, agent-based computer simulation) and simulation technologies and analysis of their possibilities in the study of the dynamic aspects of the development processes in socio-economic systems. A general concept of simulation of developing socio-economic systems based on the principles of stratification is proposed: the micro-level reproduces individual decisions of social and economic agents, as well as the collective organizational forms; and the macro-level describes processes of evolution. The interpretation of the interactions between socio-economic configurations is based on analysis of causal dependencies and dynamic manifestations of the interpenetration of phenomena occurring in different strata of the social system. It offers methods of combining composite system-dynamic and agent-based models, allowing us to investigate the dynamics of socio-economic processes by a cyclical interaction of processes of individual and group behavior of economic and social agents at the micro level with the basic processes of socio-economic system at the macro level. The basic directions of development of technologies of simulation in procedures and strategic decision support systems are defined as follows: a computer dynamic scenario analysis based on a generalized simulation model of the control object; a model of balance of interests in the procedures of coordination of scenarios and interests of the participants of the process of social design; a stratified description of the model set with the use of ontologies; methods of parameterization of models of socio-economic systems and the specifications of agents.

Methodical Approaches to Risk Management in a Regional Commercial Bank

The article presents the results of the research of the methodological and information infrastructure of the integrated risk management in a regional commercial bank. Within the study of the general development tendencies of the regional banking services market, the most significant risks for a regional bank are revealed. The analysis is carried out on the basis of the stress testing technique developed at the Plekhanov Russian University of Economics. It is based on a technique of dynamic economic and mathematical modeling with the application of information technologies. The created combination of the methodological and instrumental tools allows to carry out the dynamic scenario analysis of the activity of a commercial bank for the identification of potential risks and for the development of the strategy of financial management reducing the potential risks and leveling the consequences of their realization. The received tool allows during the computer test to watch the predicted dynamics of the condition of the key indicators of the activity of a regional commercial bank changing under the influence of the exogenous regulatory measures and instruments of bank management applied to decrease risk and at the same time to introduce adjustments in the perspective strategy of management. As the result of the analysis, the universal management model of the main bank risks in a regional commercial bank within three alternative scenarios is created. The software product allowing to develop and acquire the practical skills of the students in banking is developed. It also may help to develop the methodological support for the regulation of the organizational procedures of risk management in a regional commercial bank. The received software product may be used in a system of the improving the professional skills, and also for obtaining the expected data in a risk management system in a regional commercial bank.

Using neural networks and cognitive mapping in scenario analysis: The case of Turkey's inflation dynamics

This paper has two objectives. First of all, it proposes a dynamic scenario analysis approach, which is a revised version of extended anomaly relaxation (EFAR) model [J. Operat. Res. Soc. 48 (1997) 793]; hereafter referred to as REFAR. REFAR aims to eliminate the basic drawbacks of EFAR and improve its efficiency. The basic steps of REFAR are presented and the improvement with respect to the original version realized in each step is emphasized. The second objective of the study is to estimate the future of inflation in Turkey through REFAR using data corresponding to the period January 1994–December 1998. The main reasons for selecting REFAR-based inflation estimation instead of adopting traditional forecasting techniques are explained. The basic scenarios finally reached through REFAR, the transition among each key scenario as well as among the scenarios grouped under each key scenario are explained in detail and the validity of the REFAR-based inflation estimation model is tested through several case studies.