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Exploring urban scenarios of individual residential waste sorting using a spatially explicit agent-based model

WASTE MANAGEMENT 2025年 193卷 350-362页

作者： Cohen, Jonathan Gil, Jorge Rosado, Leonardo Chalmers Univ Technol Dept Architecture & Civil Engn S-41296 Gothenburg Sweden

Managing the diverse waste fractions generated by households presents a significant environmental and logistical challenge. One widely adopted solution is waste sorting at the source, where residents are required to separate their waste into designated containers. The success of this strategy depends on the extent of adoption and the behaviour of residents. Waste separation is a complex activity influenced by various interrelated factors. While the Theory of Planned Behaviour (TPB) has been effectively applied to characterise waste-sorting behaviour, it primarily focuses on internal psychological mechanisms, often overlooking environmental factors such as the placement of waste bins or the condition of sorting stations-critical elements for spatial planning. To bridge this gap, this study presents an agent-based model (ABM) that simulates residential waste sorting in urban scenarios, incorporating TPB for the agents' behavioural architecture (residents). Three features distinguish this ABM from previous efforts: (i) agents in the model are residents and not aggregated households, allowing for a one-to-one integration with TPB;(ii) the ABM bridges the gap between individual waste sorting behaviour extracted by TPB and outcomes quantifiable through waste sorting metrics;and (iii) the ABM is spatially explicit, enabling the exploration of various urban scenarios. The ABM was applied to two urban areas with differing population densities, demonstrating that changes in bin placement impacts sorting behaviour, and proximity to recyclable waste bins influences the correct sorting of residual waste. This study illustrates how modelling the interaction between the urban environment and waste sorting behaviour can reveal the impact of individual residents' actions on overall waste sorting performance.

关键词： agent-based model Theory of Planned Behaviour Waste sorting Waste management Urban planning

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An agent-based model to simulate field-specific nitrogen fertilizer applications in grasslands

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EUROPEAN JOURNAL OF AGRONOMY 2025年 165卷

作者： Kaim, A. Schmitt, T. M. Annuth, S. H. Haensel, M. Koellner, T. UFZ Helmholtz Ctr Environm Res Dept Computat Landscape Ecol Permoserstr 15 D-04318 Leipzig Germany Karlsruhe Inst Technol Inst Meteorol & Climate Res Atmospher Environm Res Kreuzeckbahnstr 19 D-82467 Garmisch Partenkirchen Germany Univ Bayreuth Bayreuth Ctr Ecol & Environm Res BayCEER Professorship Ecol Serv Univ Str 30 D-95447 Bayreuth Germany

Grasslands have a large share of the world's land cover and their sustainable management is important for the protection and provisioning of grassland ecosystem services. The question of how to manage grassland sustainably is becoming increasingly important, especially in view of climate change, which on the one hand extends the vegetation period (and thus potentially allows use intensification) and on the other hand causes yield losses due to droughts. Fertilization plays an important role in grassland management and decisions are usually made at farm level. Data on fertilizer application rates are crucial for an accurate assessment of the effects of grassland management on ecosystem services. However, these are generally not available on farm/field scale. To close this gap, we present an agent-based model for Fertilization In Grasslands (FertIG). based on animal, landuse, and cutting data, the model estimates grassland yields and calculates field-specific amounts of applied organic and mineral nitrogen on grassland (and partly cropland). Furthermore, the model considers different legal requirements (including fertilization ordinances) and nutrient trade among farms. FertIG was applied to a grassland-dominated region in Bavaria, Germany comparing the effects of changes in the fertilization ordinance as well as nutrient trade. The results show that the consideration of nutrient trade improves organic fertilizer distribution and leads to slightly lower Nmin applications. On a regional scale, recent legal changes (fertilization ordinance) had limited impacts. Limiting the maximum applicable amount of Norg to 170 kg N/ha fertilized area instead of farm area as of 2020 hardly changed fertilizer application rates. No longer considering application losses in the calculation of fertilizer requirements had the strongest effects, leading to lower supplementary Nmin applications. The model can be applied to other regions in Germany and, with respective adjustments, in Europe.

关键词： agent-based model Grassland management Nitrogen fertilizer Nutrient trade Field-scale

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Impact of farm size on the function of landscape-level payments for ecosystem services: an agent-based model study

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ENVIRONMENTAL RESEARCH COMMUNICATIONS 2025年第3期7卷 031010-031010页

作者： Wu, Vince Bell, Andrew Reid Zhang, Wei Palo Alto High Sch Palo Alto CA 94301 USA Cornell Univ Dept Global Dev Ithaca NY USA Int Food Policy Res Inst Nat Resources & Resilience Unit Washington DC USA

Reducing pesticide use and restoring biodiversity are among the most pressing environmental challenges. Enhancing natural pest control ecosystem services through the integration of non-crop habitats (NCH) offers promising potential, creating a positive feedback loop by harnessing insect biodiversity to reduce pesticide reliance. Policy support is needed at the landscape level to encourage adoption of this currently underutilized approach, which depends on spatial coordination and collective behavioral change. Farm size, which critically influences farmers' agrochemical inputs, agroecological practices, and interactions with neighboring farms, varies across agricultural landscapes. It is unclear what role farm size plays in landscape-scale agri-environmental incentive programs, which have recently seen growing attention in scientific research and policy implementation. We employ framed field games and agent-based modeling as complementary research tools, exploring how farm size impacts the function of landscape-scale NCH subsidies aimed at encouraging coordinated provision and sharing of natural pest control services to reduce pesticide use. Our model simulation shows that, in landscapes of larger average farm size or lower farm size heterogeneity, NCH subsidies are significantly more effective at reducing pesticide use and increasing NCH efficiency in providing joint production benefits. Our results imply that landscape-scale payments for natural pest control ecosystem services face fewer obstacles as incentive-based mechanisms in landscapes of larger, more homogeneous farms, supporting the implementation of landscape-scale initiatives in such areas to effectively enhance ecosystem services. Our findings contribute to the growing discussion around landscape-level financial incentive programs that depend on spatial coordination, highlighting the importance of farmers' land holding size.

关键词： payments for ecosystem services landscape-scale pest control non-crop habitat farm size coordination game agent-based model

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Investor Structure and Corn Futures Price Volatility in China: Evidence based on the agent-based model

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COMPUTATIONAL ECONOMICS 2025年第2期65卷 937-961页

作者： Zhao, Yuhe Ju, Ronghua China Agr Univ Coll Econ & Management Tsinghua East Rd Beijing 100083 Peoples R China China Agr Univ Ctr Futures & Financial Derivat Res Tsinghua East Rd Beijing 100083 Peoples R China

This study investigates how the investor structures affect the corn futures price volatility using corn futures and spot price daily data ranging from 5 January 2009 to 31 December 2022. Our contribution to the expanding literature lies in the introduction of an artificial Chinese corn futures market model based on the agent-based model (ABM), which offers an innovative solution to the issue of the unavailability of commercial positions data. Moreover, we improve the prediction accuracy of corn futures prices by the autoregressive neural network (AR-Net) model. The scenario simulation results demonstrate that hedgers can stabilize corn futures prices, and price volatility tends to be more dramatic in structures with a low hedger ratio. In addition, robustness tests by the empirical mode decomposition (EMD) model support the conclusion.

关键词： Price volatility Heterogeneous investor Investor behavior AR-Net model agent-based model Scenario simulation

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An agent-based model of residents' group decision making in neighborhood regeneration: Assessing the impacts of consensus-reaching approaches

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CITIES 2025年 161卷

作者： Huang, Ruopeng Fu, Xinyue Wang, Wenshun You, Kairui Zheng, Saina Xu, Na China Univ Min & Technol Sch Mech & Civil Engn 1 Daxue Rd Xuzhou 221116 Jiangsu Peoples R China Chongqing Univ Sch Management Sci & Real Estate 174 Shazheng St Chongqing 400044 Peoples R China Beijing Inst Technol Ctr Energy & Environm Policy Res Beijing 100081 Peoples R China Southeast Univ Sch Civil Engn Dept Construct & Real Estate Nanjing Peoples R China

In the context of neighborhood regeneration, the group decision-making process among residents is inherently complex and significantly influenced by their intricate social relationships. This complexity necessitates effective strategies to achieve consensus among residents. To address this, this study developed an agent-based model for resident group decision-making, incorporating a dynamic social network model, preference evolution rules, and resident agent decision-making rules. based on prior research, the study designed five consensus-reaching approaches: Changing network structure, Adjusting opinions, Directed informed decision makers, Non-directed informed decision makers, and Media. These strategies were implemented within the agent-based model and subjected to simulation and comparative analysis. The simulation results indicated that Adjusting opinions and Non-directed informed decision makers were more effective in fostering consensus. Additionally, the study identified and analyzed the dynamic characteristics of consensus-reaching approaches and the impact of social network structures on consensus levels. The agent-based model developed in this study enables dynamic analysis of group decision-making in neighborhood regeneration, contributing to the theoretical framework of group decision-making and neighborhood regeneration. Moreover, the findings offer valuable insights for conflict resolution and consensus-reaching in practical neighborhood regeneration projects, providing essential knowledge to support effective implementation and sustainability.

关键词： Neighborhood regeneration Group decision making agent-based model

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Roof or real estate? An agent-based model of housing affordability in The Netherlands

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STRUCTURAL CHANGE AND ECONOMIC DYNAMICS 2025年 72卷 163-178页

作者： Tarne, Ruben Bezemer, Dirk Univ Groningen Groningen Netherlands

Housing shortages in monetary economies are defined by affordability, which is the balance between income, savings and borrowing to access housing on one hand and purchase prices and rents, providing access, on the other. Yet analysis often confuses (monetary) affordability with (real) supply shortages. In a heterogeneous-agent housing market model calibrated on survey data, we analyse the housing affordability crisis in the Netherlands since around 2015. We find trade-offs between shocks to the housing supply, to interest rates and to banks' loan- to-value norms by estimating their effects on house prices. Financial and monetary policies are alternatives to supply responses in reducing cyclical house price peaks and average house prices and increasing affordability.

关键词： Housing affordability Monetary economy agent-based model The Netherlands

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Bio-Inspired agent-based model for Collective Shepherding 17th

Bio-Inspired Agent-Based Model for Collective Shepherding

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17th International Conference on Simulation of Adaptive Behavior (SAB)

作者： Zheng, Yating Romanczuk, Pawel Humboldt Univ Inst Theoret Biol Dept Biol Berlin Germany Tech Univ Berlin Sci Intelligence Berlin Germany

ISBN: (纸本)9783031715327;9783031715334

Collective shepherding is a complex problem with potentially a broad range of applications. Its complexity arises from the interaction of two collectives: 'sheep' and 'shepherds', with the latter attempting to control and guide the 'sheep'. Here, we combine an agent-based model for the 'sheep'-flock with a heuristic algorithm for the adaptive behavior of shepherds with two different behavioral modes: collecting, i.e. keeping the sheep flock together, and driving the sheep towards the target. We show that this algorithm can achieve selforganized coordination among multiple shepherds without direct communication, and investigate how the shepherding performance depends on selected parameters of the system such as sheep flock size, number of shepherds, or parameters governing the switching between the shepherd behavioral modes. We demonstrate that the algorithm can also be applied to more challenging scenarios like controlling non-cohesive or passive agents without self-propulsion. Besides extending our understanding of collective shepherding, our model provides a starting point for future research into unexplored aspects of this complex dynamical behavior.

关键词： Collective shepherding agent-based model coordination

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An agent-based model to assess the impact of shared staff and occupancy rate on infectious disease burden in nursing homes

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BMC INFECTIOUS DISEASES 2025年第1期25卷 1-15页

作者： Corkran, Kiel Gomez-Vazquez, Jose Pablo Arjmand, Arash Nuno, Miriam Bani-Yaghoub, Majid Univ Missouri Kansas City Sch Sci & Engn Div Comp Analyt & Math Kansas City MO 64110 USA Univ Calif Davis Dept Vet Med & Epidemiol Davis CA 95616 USA Univ Calif Davis Dept Publ Hlth Sci Davis CA 95616 USA

Infectious diseases can propagate between nursing homes through asymptomatic staff members who are employed at multiple facilities. However, the transmission dynamics of infections, both within individual nursing homes and across facilities, has been less investigated. To fill this gap, we developed an agent-based model of two nursing homes extendible to a network of n nursing homes connected with different percentages of shared staff. Focusing on the outbreaks of COVID-19 in U.S. nursing homes, we calibrated the model according to the COVID-19 prevalence data and estimated levels of shared staff for each State. The model simulations indicate that reducing the percentage of shared staff below 5% plays a significant role in controlling the spread of infection from one nursing home to another through personal protective equipment usage, rapid testing, and vaccination. As the percentage of shared staff increases to more than 30%, these measures become less effective, and the mean prevalence of infection reaches a steady state in both nursing homes. The hazard ratios for infection and mortality indicate that nursing homes with higher occupancy rates are more significantly affected by increased staff-sharing percentages. In conclusion, the burden of infection significantly increases with greater staff sharing between nursing homes, particularly in high-occupancy facilities, where transmission dynamics are amplified due to greater resident density and staff interactions.

关键词： agent-based model Nursing home Shared staff COVID-19 Infection GAMA

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Residential land growth simulation of agent-based model by coupling big data and reinforcement learning

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Frontiers of Earth Science 2025年 1-17页

作者： Gao, Jinding Liang, Chao Guo, Jiaojiao Liu, Xiaoping Zhang, Honghui Liu, Geng School of Geography and Planning Sun Yat-sen University Guangzhou 510000 China Guangdong Guodi Institute of Resources and Environment Guangzhou 510000 China

Urban expansion has far-reaching implications for economy, environment, and socio-cultural aspects of a city. Therefore, it is essential to have a thorough understanding of the complex dynamics and driving factors behind urban expansion in order to make informed decisions that promote the long-term sustainability of a city. Currently, cellular automata (CA) and agent-based modeling (ABM) have been widely employed to simulate urban land growth. However, existing research lacks a comprehensive consideration of the influence of individual agent attributes and land population capacity on site selection decisions. Consequently, we propose a novel approach that incorporates fine-scale population data into the site-selection decision simulation process, allowing for a granular depiction of individual decision attributes. Moreover, the site selection process integrates assessment criteria, including population capacity and neighborhood development status. Furthermore, to address the issue of fragmented simulated residential land use outcomes, population redistribution is iteratively conducted. Additionally, by integrating extended reinforcement learning mechanisms, the site selection process of residential multi-agent systems experiences a significant improvement in overall simulation accuracy. The proposed model was applied to simulate urban expansion in Shenzhen, Guangdong province, China. The results demonstrated that this model effectively enhances the behavioral decision-making capabilities of intelligent agents, thereby providing insights into the mechanisms underlying urban expansion. These findings hold considerable significance for making informed urban planning decisions and advancing the goal of sustainable urban development. © Higher Education Press 2025.

关键词： agent-based model population portrait reinforcement learning residential land

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Simulating the uptake of electric motorized two-wheelers in Italy. An agent-based model parametrized with a discrete choice experiment

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CASE STUDIES ON TRANSPORT POLICY 2025年 19卷

作者： Scorrano, Mariangela Danielis, Romeo Univ Trieste Dipartimento Sci Econ Aziendali Matemat & Stat Bru Via A Valerio 4-1 I-34127 Trieste Italy

Electric motorized two-wheelers (e-M2Ws) have the potential to reduce noise and air quality in urban environments. The paper develops an agent-based model, parametrized with a discrete choice experiment, to forecast e-M2Ws' uptake in Italy. The application considers two market segments: mopeds and (seated) scooters. A scenario analysis is performed assessing the e-M2Ws prospects in different technological and policy scenarios. We find that electric mopeds enjoy a higher consumers' acceptance than electric scooters. Our model predicts that they might play a relevant role in most scenarios, achieving in 2030 a market share ranging between 21.1 % and 44.2 %. On the contrary, electric scooters have much poorer prospects, achieving in 2030 a maximum of 5.5 % market share.

关键词： Mopeds/scooters agent-based model Discrete choice experiment

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