Simulation of Urban Carbon Sequestration Service Flows and the Sustainability of Service Supply and Demand
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data
2.3. Methods
2.3.1. Interpolation of Wind Directions
Calculate the Resistance Coefficient
The Least-Cost Path (LCP) Analysis
Interpolation of Prevailing Wind Directions
2.3.2. Interpolation and Correction of Wind Speed
Interpolation of Wind Speed
Topographic Correction
Surface Correction
2.3.3. Carbon Emission Accounting and Spatialization
Carbon Emission Accounting
Spatialization of Carbon Emissions
- (a)
- Based on the intensity of human activities at different POIs, weights are assigned using the analytic hierarchy process (Table S5). The kernel density estimation results of the POIs are then computed to derive the POI energy consumption factor (ECF) based on these weights.
- (b)
- The road network is categorized into expressways, main roads, secondary roads, and other roads. Weights of 2.39, 1.96, 1.30, and 1.00 are assigned based on the width of each road grade, while railways are weighted at 4.07 [62]. The kernel density estimation of the road traffic ECF is calculated based on assigned weights.
- (c)
- The energy consumption factors are normalized. Given that POIs encompass carbon emissions from both production activities and daily life, the POI ECF is assigned a weight of two-thirds (2/3), whereas the transportation ECF is given a weight of one-third (1/3). The comprehensive ECF is derived from the weighted sum of these two. A masking process is then employed using the extent of the built-up areas, and the carbon emissions within these zones are spatialized using the following equation:
2.3.4. Quantify “Instantaneous” ECSS Flow
3. Results
3.1. Simulation of Wind Directions
3.2. Wind Speed Interpolation and Correction
3.3. Carbon Emission Accounting and Spatialization
3.4. ECSS Flow
4. Discussion
4.1. Impact of Air Inlet Position Changes on ECSS Flows
4.2. Sustainability of ECSS Supply and Demand
4.3. Evaluation of the Method and Limitations of Its Application
4.4. Policy Recommendations
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
AAWS | Annual average wind speed |
CNBH | Chinese building height |
ECSS | Ecosystem carbon sequestration services |
ES | Ecosystem services |
ECF | Energy consumption factor |
DEM | Digital Elevation Model |
JAWS | July average wind speed |
LST | Land surface temperature |
LCP | Least-cost path |
POIs | Points of interest |
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Ma, Y.; Tian, S. Simulation of Urban Carbon Sequestration Service Flows and the Sustainability of Service Supply and Demand. Sustainability 2024, 16, 7738. https://doi.org/10.3390/su16177738
Ma Y, Tian S. Simulation of Urban Carbon Sequestration Service Flows and the Sustainability of Service Supply and Demand. Sustainability. 2024; 16(17):7738. https://doi.org/10.3390/su16177738
Chicago/Turabian StyleMa, Yaoxi, and Shufang Tian. 2024. "Simulation of Urban Carbon Sequestration Service Flows and the Sustainability of Service Supply and Demand" Sustainability 16, no. 17: 7738. https://doi.org/10.3390/su16177738