Table · dataset · 2026
Spatial realization uncertainty; Land-use reallocation; Urban simulation; Transport emissions; Scenario ensemble; Built-out district
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<p dir="ltr">Compact and mixed land use is promoted for transport decarbonization, but the emission effects of land-use reallocation in built-out districts remain unclear.
Description
We examine whether the magnitude and direction of these effects depend on which parcels are converted under the same area targets for each land-use class. In Futian District, Shenzhen, we compare tailpipe CO₂ from interzonal car travel under baseline, service-oriented, and residential-oriented scenarios.
Per scenario-year, repeated stochastic allocation generates 100 parcel maps (spatial realizations) meeting the same targets under a fixed land total. To assess spatial-realization and parameter uncertainty, each realization was evaluated through the same travel-demand and emission chain with the same 500 downstream parameter draws. The findings reveal that (1) with downstream parameters held fixed, service-oriented reallocation lowers mean emissions by 0.33% in 2025 and 1.21% in 2030 and emits less than the baseline in 84% and 93% of realizations, whereas residential-oriented reallocation shows no stable increase; (2) reduced trip generation contributes to lower emissions in every realization, and a smaller share of trips leaving their zone does so in most, while distance and car-share contributions vary in sign; and (3) among the represented uncertainty sources, spatial realization accounts for over nine-tenths of the variation in scenario differences.
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Bounding electrification pathways cut 2030 emissions by 30–53% relative to the 2020 reference fleet. Land-use reallocation is thus a modest, spatially contingent complement to electrification; scenario assessments should report results across maps, not one map.</p>
Links
Where it is published
- DOI doi.org/10.6084/m9.figshare.32162976.v1 ↗
DOI / persistent id · from figshare com
Catalogue records · 1
- OAI-PMH record api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Af… ↗
metadata API · from figshare com
Topics
- From keywords
- Astronomy & Astrophysics · Chemistry · Computational modelling and simulation in earth sciences · Computer Science & AI · Earth & Environmental Science · Economics & Finance · Engineering · Humanities · Life Sciences · Medicine & Health · Ocean & Atmospheric Science · Social Science
- Inferred from text
- Simulation 75%
Provenance · 1 source records, 18 field assertions
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|---|---|---|---|
| figshare | oai:figshare.com:article/32162976 | 4 d ago | JSON v1 |
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