Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 2610.26696

Commercial building decarbonization across countries: Future emission trajectories and mitigation priorities

Qinwen Tang·Tianyi Wang·Nan Zhou·Minda Ma
View original source ↗Read source document ↗Export metadata ↓

Abstract

With energy-related carbon dioxide emissions remaining at high levels, decarbonizing commercial building operations across key economies is critical for achieving global climate targets. This study assesses future operational carbon trajectories, mitigation potential, and the driving factors of this potential in commercial building operations across 16 countries from 2024 to 2060 by combining a Kaya-based emission model and Monte Carlo uncertainty analysis. The key findings indicate that (1) under the business-as-usual scenario, China's commercial building operational carbon emissions are projected to peak at 1150 (+-120) million tonnes of carbon dioxide (MtCO2) in 2033 (+-5 years), while the remaining countries exhibit differentiated carbon lock-in levels, with the highest level in the United States at 470 (+-89) MtCO2. (2) The total emission reduction potential increases from 352 MtCO2 in 2030 to 1119 MtCO2 in 2050 and stabilizes at 1123 MtCO2 in 2060, with China, the United States, and Japan contributing 84.7%-88.9% of the total potential. (3) By 2060, the mitigation potential from energy intensity reduction is concentrated mainly in China and the United States, reaching 52 and 32 MtCO2, respectively; end-use decomposition further identifies space heating and appliances as key targets for decarbonizing commercial building operations. In summary, this study characterizes future operational carbon trajectories and clarifies the drivers and end-use priorities of mitigation potential in commercial building operations, providing cross-country evidence for differentiated strategies for long-term commercial building decarbonization.

Explore related subjects

physics.soc-ph

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Qinwen Tang, Tianyi Wang, Nan Zhou, Minda Ma. 2026-10-19. Commercial building decarbonization across countries: Future emission trajectories and mitigation priorities. https://arxiv.org/abs/2610.26696

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Percolation Transition of K-Destinations Reveals Universal Backbone of Urban Mobility Networks

Cities are held together by a small subset of recurrent origin--destination ties, but extracting this backbone from noisy mobility data remains difficult, and most models still prioritize distance over connectivity. We build directed mobility networks from 48 months of mobile-phone data across eight U.S. cities (2018--2021) and apply a rank-based percolation filter that retains, for each origin, its top-K destinations. Defining K* as the smallest cutoff that yields a strongly connected network, we find that city-specific thresholds cluster tightly across space and time, with a representative value near $K\approx130$. Degree-preserving and gravity-style baselines do not recover this scale, underscoring the importance of selectively preserved long-range functional ties. We then define PPD(K), an origin-level mobility concentration measure, and show that socioeconomic associations peak around the percolation-derived integration regime. Together, these findings offer a principled method to extract a minimal mobility backbone and connect its structure to persistent socioeconomic variation.

physics.soc-ph↗
arXiv2026

Mobility and Contact Networks Shape Epidemic Outcomes: A Large-Scale Agent-Based Modeling Study

Human mobility plays a central role in shaping contact patterns that drive infectious disease transmission, yet mobility is often simplified in agent-based models (ABMs) due to data and computational constraints. The effects of these simplifications on model outputs are poorly understood. In this study, we systematically examined how alternative mobility assumptions influence emergent contact networks and epidemic dynamics within a large-scale ABM. Using a synthetic population of one million agents representing an urban environment, we implemented five mobility models varying along two dimensions: activity patterns (empirically derived vs. randomized) and destination choice mechanisms (empirical popularity, distance-based, or random). Holding disease parameters constant, we found that mobility assumptions alone produced substantially different contact network structures and epidemic trajectories, including differences in peak incidence and shifts in outbreak timing. Importantly, these differences could not be attributed to agents simply moving more or less overall since aggregate movement volumes were broadly comparable across models. Instead, the contrasting dynamics arose from how mobility generates contact opportunities: specifically, who meets whom, where, and how often. These results suggest that in models where mobility has not been carefully calibrated, simulated epidemic outcomes and evaluations of interventions may reflect mobility assumptions as much as underlying disease parameters. Our findings underscore the importance of mobility model calibration and validation, particularly in policy-facing applications.

physics.soc-ph↗
arXiv2026

A mechanism for collective foraging: percolating recruitment cascades coupled to a maximum-entropy

Foraging recruitment is a contagion: an agent that finds a resource triggers a linear-threshold cascade, the model built for rumour and adoption spread on social networks, now embedded in space. Because activation is degree-normalized, the same rule that spreads the cascade also stifles it as neighbourhoods crowd, so the swarm aggregates on a resource and then releases to explore again. The cascade runs on the communication network, but acting on it moves agents in physical space, and that motion rewires the network: network and space are one coupled system, and this feedback, not any tuning, makes the coordination self-limiting. Because recruitment chains along the graph rather than reaching near neighbours alone, whether a discovery stays local or spans the swarm is a question of percolation. The swarm holds itself in a cascade window that is locally near-critical though globally subcritical, a self-organized, self-limiting drive-release cycle, sandpile-like but non-conservative. Nothing is tuned, yet behaviours that foraging biology documents separately emerge together: recruitment to discoveries, marginal-value patch-leaving, and Levy search with a switch to local exploitation. These follow from one least-committal principle, the resource field and the search both as maximum entropy, with Levy search matched to the field's sparsity and recruitment to its clustering, so active-matter order and optimal foraging appear as one system seen in two domains. The gains are real but conditional: up to 7.6x the harvest of solitary search when resources are sparse and clustered, shrinking to nothing when search is already easy. That sparse, clustered field is also the generic one, because resources almost inevitably aggregate, so one untuned rule should recur widely.

physics.soc-ph↗