Spatially explicit carbon emissions by remote sensing and social sensing

Gao, Feng; Wu, Jie; Xiao, Jinghao; Li, Xiaohui; Liao, Shunyi; Chen, Wangyang

doi:10.1016/j.envres.2023.115257

Cited by 23 publications

(6 citation statements)

References 48 publications

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“…For a countyscale simulation, this study has detailed land-use classifications, which can help to finish the first total carbon emissions amount allocation for different land-use types. This can eliminate the bias that comes without the distinction of carbon emissions on different land-use types, such as the use of night light for the whole region's carbon emissions simulation in spatial terms (Gao et al 2023;Lu and Liu 2014;Shi et al 2016). This method has less bias than the dominant carbon emissions from industry, which usually do not have high night-light values.…”

Section: Discussionmentioning

confidence: 99%

Promoting low-carbon land use: from theory to practical application through exploring new methods

Chuai,

Xu,

Liu

et al. 2024

Humanit Soc Sci Commun

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Cities are main carbon emissions generators. Land use changes can not only affect terrestrial ecosystems carbon, but also anthropogenic carbon emissions. However, carbon monitoring at a spatial level is still coarse, and low-carbon land use encounters the challenge of being unable to adjust at the patch scale. This study addresses these limitations by using land-use data and various auxiliary data to explore new methods. The approach involves developing a high-resolution carbon monitoring model and investigating a patch-scale low-carbon land use model by integrating high carbon sink/source images with the Future Land Use Simulation model. Between 2000 and 2020, the results reveal an increasing trend in both carbon emissions and carbon sinks in the Shangyu district. Carbon sinks can only offset approximately 3% of the total carbon emissions. Spatially, the north exhibits net carbon emissions, while the southern region functions more as a carbon sink. A total of 14.5% of the total land area witnessed a change in land-use type, with the transfer-out of cropland constituting the largest area at 96.44 km2, accounting for 50% of the total transferred area. Land-use transfer resulted in an annual increase of 77.72 × 104 t in carbon emissions between 2000 and 2020. Through land-use structure optimisation, carbon emissions are projected to increase by only 7154 t C/year from 2000 to 2030, significantly lower than the amount between 2000 and 2020. Further low-carbon land optimisation at the patch scale can enhance the carbon sink by 129.59 t C/year. The conclusion drawn is that there is considerable potential to reduce carbon emissions through land use control. The new methods developed in our study can effectively contribute to high-resolution carbon monitoring in spatial contexts and support low-carbon land use, promoting the application of low-carbon land use from theory to practice. This will provide technological guidance for land use planning, city planning, and so forth.

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Section: Discussionmentioning

confidence: 99%

Promoting low-carbon land use: from theory to practical application through exploring new methods

Chuai,

Xu,

Liu

et al. 2024

Humanit Soc Sci Commun

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“…The analytics spatial unit is the neighborhood, which is the census unit at the grass-roots level in China. The downtown of Guangzhou comprises the first four districts [39,40]. At present, the total number of AEDs in public has exceeded 1100, among which 16 metro lines and 302 stations have been realizing a complete coverage by AED.…”

Section: Study Areamentioning

confidence: 99%

AED Inequity among Social Groups in Guangzhou

Gao,

Lu,

Liao

et al. 2024

IJGI

Self Cite

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Automated external defibrillators (AEDs) are regarded as the most important public facility after fire extinguishers due to their importance to out-of-hospital cardiac arrest (OHCA) victims. Previous studies focused on the location optimization of the AED, with little attention to inequity among different social groups. To comprehensively investigate the spatial heterogeneity of the AED inequity, we first collected AED data from a WeChat applet. Then, we used the geographically weighted regression (GWR) model to quantify the inequity level and identify the socio-economic status group that faced the worst inequity in each neighborhood. Results showed that immigrants of all ages suffer a more severe AED inequity than residents after controlling population and road density. Immigrants face more severe inequity in downtown, while residents face more severe inequity in the peripheral and outer suburbs. AED inequity among youngsters tends to be concentrated in the center of each district, while inequity among the elderly tends to be distributed at the edge of each district. This study provides a new perspective for investigating the inequity in public facilities, puts forward scientific suggestions for future AED allocation planning, and emphasizes the importance of the equitable access to AED.

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“…At the same time, methods such as the IPCC inventory method and input-output models are also commonly used in carbon emission accounting [6]. In analyzing the influencing factors, scholars have employed various methodologies such as the geographical detector [7,8], geographical weighted regression model [6,9], LMDI model [10], STIRPAT model [11] and spatial econometric model [12,13] to delve into the driving mechanisms behind carbon emissions. Empirical outcomes indicate that economic growth, populace size, urbanization, green technology innovation, energy consumption, foreign investment and other social and economic factors are correlated with carbon emissions [10,14].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Synergistic Benefits between Carbon Emissions and Air Pollution Based on Remote Sensing Observations: A Case Study of the Central Henan Urban Agglomeration

He,

Lv,

et al. 2024

Sustainability

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Reducing carbon emissions while controlling air pollution is a dual challenge for China. However, few studies have analyzed whether there is a synergy between the two. In view of this, this paper takes the urban agglomeration in Central Henan as an example, uses multi-source remote sensing and panel data from 2000 to 2022 and analyzes the spatiotemporal evolution patterns and synergistic benefits of air pollution and carbon emissions based on the spatial distribution direction analysis model, coupling coordination degree model and multi-scale geographic weighting model. The results indicate the following: (1) Carbon emissions show a growing trend, but the difference in the carbon emissions of different cities is relatively large, showing the characteristics of “one center and two zones” in space. Air pollution shows a trend of first increasing and then decreasing. (2) The synergistic benefits have been continuously enhanced, and the overall unbalanced state has gradually become coordinated. There is no obvious aggregation feature. (3) The impact of socioeconomic factors on the synergistic benefit is obviously stronger than that of natural ecological factors, among which the total energy consumption, population density and industrial structure are the leading factors of the synergistic benefit of carbon emissions and air pollution. This study offers valuable insights for green development, high-quality growth and collaborative environmental governance within the Central Henan urban agglomeration.

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Spatially explicit carbon emissions by remote sensing and social sensing

Cited by 23 publications

References 48 publications

Promoting low-carbon land use: from theory to practical application through exploring new methods

Promoting low-carbon land use: from theory to practical application through exploring new methods

AED Inequity among Social Groups in Guangzhou

Analysis of Synergistic Benefits between Carbon Emissions and Air Pollution Based on Remote Sensing Observations: A Case Study of the Central Henan Urban Agglomeration

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