Abstract
A key part of reducing CO2 emissions is exploring scientific methods for calculating carbon footprints and allocating their sources. Several limitations in current approaches exist at smaller scales due to shortcomings and uncertainty in data collection. This article implements an improved approach to allocate carbon footprints at the local, neighborhood scale, taking land uses as a criteria, after verifying the correlation between industry sectors and land uses through cointegration test. A case study of the Wuhan Metropolitan Area (WhMA) is provided to examine the method's applicability and effectiveness. Some related spatiotemporal variations in carbon-footprint values at the township scale are depicted as a spatial tendency from zonal agglomeration to radial diffusion in a core-periphery structure, which relates to such human-driven factors as population, transportation, and urban (built-up) area. The findings provide insight for policymakers to generate appropriate allocative strategies for low-carbon development.
| Original language | English |
|---|---|
| Pages (from-to) | 441-464 |
| Number of pages | 24 |
| Journal | Geographical Review |
| Volume | 106 |
| Issue number | 3 |
| DOIs | |
| State | Published - 1 Jul 2016 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
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SDG 15 Life on Land
Keywords
- carbon footprint
- cointegration test
- regional allocation
- spatiotemporal variations
- township scale
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