Research Progress of Land Use Effects on Carbon Emissions and Low Carbon Management

Regional land use is an important source of carbon emissions .To some extent , the optimization land use will change the pattern and structure of human energy consumption .In this paper, we try to put forward a new approach to optimize the land use structure of the low carbon target in Zhangye .Three schemes for land use low-carbon optimization were proposed and analyzed, and the policy suggestions were put forward finally . Compare with the original plan, Optimization program in the year of 2020, the amount of carbon accumulation increase 124.1648 million tons, and carbon emissions reduce 1,152,100 tons. This indicates that the scheme for land use planning to achieve carbon reduction and carbon accumulation has important guiding significance.

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Environmental and resource burdens associated with low carbon, more electric transition pathways to 2050: Footprint components from carbon emissions and land use to waste arisings and water consumption

Global Transitions ◽

10.1016/j.glt.2019.01.001 ◽

2019 ◽

Vol 1 ◽

pp. 28-43 ◽

Cited By ~ 6

Author(s):

Geoffrey P. Hammond ◽

Hayley R. Howard ◽

Hanumant Singh Rana

Keyword(s):

Land Use ◽

Water Consumption ◽

Carbon Emissions ◽

Low Carbon ◽

Transition Pathways ◽

Electric Transition

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Anthropogenic Drivers of Mangrove Loss and Associated Carbon Emissions in South Sumatra, Indonesia

Forests ◽

10.3390/f12020187 ◽

2021 ◽

Vol 12 (2) ◽

pp. 187

Author(s):

Syaiful Eddy ◽

Noril Milantara ◽

Sigit D. Sasmito ◽

Tadashi Kajita ◽

Mohammad Basyuni

Keyword(s):

Land Use ◽

Carbon Emissions ◽

Secondary Forest ◽

Anthropogenic Activities ◽

Total Carbon ◽

Coastal Forest ◽

Low Carbon ◽

Land Clearing ◽

Climate Policies ◽

Nationally Determined Contributions

The Air Telang Protected Forest (ATPF) is one of the most dynamic and essential coastal forest landscapes in South Sumatra, Indonesia, because of its location between multiple river outlets, including the Musi catchment—Sumatra’s largest and most dense lowland catchment area. While most ATPF areas are covered by mangroves, these areas have been experiencing severe anthropogenic-driven degradation and conversion. This study aims to evaluate land cover changes and associated carbon emissions in the ATPF over a 35-year period (1985–2020) by utilizing the available Landsat and Sentinel imagery from 1985, 2000, and 2020. Throughout the analysis period, we observed 63% (from 10,886 to 4059 ha) primary and secondary forest loss due to land use change. We identified three primary anthropogenic activities driving these losses, namely, land clearing for plantations and agriculture (3693 ha), coconut plantations (3315 ha), aquaculture (245 ha). We estimated that the largest carbon emissions were caused by coconut plantation conversion, with total carbon emissions of approximately 14.14 Mt CO2-eq. These amounts were almost 4 and 21 times higher than emissions from land clearing and aquaculture, respectively, as substantial soil carbon loss occurs once mangroves get transformed into coconut plantations. While coconut plantation expansion on mangroves could generate significant carbon stock losses and cleared forests become the primary candidate for restoration, our dataset could be useful for future land-based emission reduction policy intervention at a subnational level. Ultimately, our findings have direct implications for current national climate policies, through low carbon development strategies and emission reductions from the land use sector for 2030, as outlined in the Nationally Determined Contributions (NDCs).

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Research on the Low-Carbon Land Use Pattern

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.598.241 ◽

2012 ◽

Vol 598 ◽

pp. 241-246

Author(s):

Ya Li Luo ◽

Chang Xin Zhang

Keyword(s):

Land Use ◽

Carbon Emissions ◽

High Density ◽

Low Carbon ◽

Land Use Pattern ◽

Mixed Use ◽

Use Pattern ◽

The City

The paper firstly analyzed the carbon emissions effect of the city land use. Then it put forward the high density compact land use pattern is consistent with low-carbon developing goal. Finally, the paper systematically expounded the connotation of the low-carbon high density compact mixed use, and discussed the basic forms of low-carbon land use pattern, such as the giant single building, buildings on the same platform, new units model on the community scale etc..

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Examining the Effects of Land Use on Carbon Emissions: Evidence from Pearl River Delta

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18073623 ◽

2021 ◽

Vol 18 (7) ◽

pp. 3623

Author(s):

Yabo Zhao ◽

Shifa Ma ◽

Jianhong Fan ◽

Yunnan Cai

Keyword(s):

Land Use ◽

Energy Efficiency ◽

Economic Development ◽

Spatial Distribution ◽

Land Use Change ◽

Carbon Emissions ◽

Pearl River Delta ◽

Pearl River ◽

Energy Structure ◽

Low Carbon

Land-use change accounts for a large proportion of the carbon emissions produced each year, especially in highly developed urban agglomerations. In this study, we combined remote sensing data and socioeconomic data to estimate land-use-related carbon emissions, and applied the logarithmic mean Divisia index (LMDI) method to analyze its influencing factors, in the Pearl River Delta (PRD) of China in 1990–2015. The main conclusions are as follows: (1) The total amount of land-use-related carbon emissions increased from 684.84 × 104 t C in 1990 to 11,444.98 × 104 t C in 2015, resulting in a net increase of 10,760.14 × 104 t (16.71 times). (2) Land-use-related carbon emissions presented a “higher in the middle and lower on both sides” spatial distribution. Guangzhou had the highest levels of carbon emissions, and Zhaoqing had the lowest; Shenzhen experienced the greatest net increase, and Jiangmen experienced the least. (3) The land-use-related carbon emissions intensity increased from 4795.76 × 104 Yuan/t C to 12,143.05 × 104 Yuan/t C in 1990–2015, with the greatest increase seen in Huizhou and the lowest in Zhongshan. Differences were also found in the spatial distribution, with higher intensities located in the south, lower intensities in the east and west, and medium intensities in the central region. (4) Land-use change, energy structure, energy efficiency, economic development, and population all contributed to increases in land-use-related carbon emissions. Land-use change, economic development and population made positive contributions, while energy efficiency and energy structure made negative contributions. At last, we put forward several suggestions for promoting low-carbon development, including development of a low-carbon and circular economy, rationally planning land-use structure, promoting reasonable population growth, improving energy efficiency and the energy consumption structure, and advocating low-carbon lifestyles. Our findings are useful in the tasks related to assessing carbon emissions from the perspective of land-use change and analyzing the associated influencing factors, as well as providing a reference for realizing low-carbon and sustainable development in the PRD.

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Land Use Optimization and Simulation of Low-Carbon-Oriented—A Case Study of Jinhua, China

Land ◽

10.3390/land10101020 ◽

2021 ◽

Vol 10 (10) ◽

pp. 1020

Author(s):

Shiqi Huang ◽

Furui Xi ◽

Yiming Chen ◽

Ming Gao ◽

Xu Pan ◽

...

Keyword(s):

Land Use ◽

Carbon Emissions ◽

Eastern China ◽

High Rate ◽

Energy Structure ◽

Cultivated Land ◽

Low Carbon ◽

Land Use Pattern ◽

Construction Land ◽

Use Pattern

Land-use change is an important contributor to atmospheric carbon emissions. Taking Jinhua city in eastern China as an example, this study analyzed the effects on carbon emissions by land-use changes from 2005 to 2018. Then, carbon emissions that will be produced in Jinhua in 2030 were predicted based on the land-use pattern predicted by the CA-Markov model. Finally, a low-carbon optimized land-use pattern more consistent with the law of urban development was proposed based on the prediction and planning model used in this study. The results show that (1) from 2005 to 2018, the area of land used for construction in Jinhua continued to increase, while woodland and cultivated land areas decreased. Carbon emissions from land use rose at a high rate. By 2018, carbon emissions had increased by 1.9 times compared to 2015. (2) During the 2010–2015 period, the total concentration of carbon emissions decreased due to decreases in both the rate of growth in construction land and the rate of decline in a woodland area, as well as an adjustment of the energy structure and the use of polluting fertilizer and pesticide treatments. (3) The carbon emissions produced with an optimal land-use pattern in 2030 are predicted to reduce by 19%. The acreage of woodland in Jinhua’s middle basin occupied by construction land and cultivated land is predicted to reduce. The additional construction land will be concentrated around the main axis of the Jinhua-Yiwu metropolitan area and will exhibit a characteristic ribbon-form with more distinct clusters. The optimized land-use pattern is more conducive to carbon reduction and more in line with the strategy of regional development in the study area. The results of this study can be used as technical support to optimize the land-use spatial pattern and reduce urban land’s contribution to carbon emissions.

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Optimization of Land-Use Structure Based on the Trade-Off Between Carbon Emission Targets and Economic Development in Shenzhen, China

Sustainability ◽

10.3390/su11010011 ◽

2018 ◽

Vol 11 (1) ◽

pp. 11 ◽

Cited By ~ 2

Author(s):

Dang Han ◽

Ruilin Qiao ◽

Xiaoming Ma

Keyword(s):

Land Use ◽

Carbon Emissions ◽

Land Use Planning ◽

Programming Model ◽

Low Carbon ◽

Land Use Pattern ◽

Intergovernmental Panel ◽

Multi Objective ◽

Land Use Structure ◽

Land Types

The approach of choosing an effective low-carbon land-use structure by multi-objective methods is commonly used in land-use planning. A common methodology is to calculate carbon emissions and conduct scenario simulations for the future. However, most Chinese cities have not implemented the methods for monitoring carbon emissions proposed by the Intergovernmental Panel on Climate Change (IPCC), especially Shenzhen, which is one of the fastest-growing cities in China. This study first calculated the carbon emissions for a typical year in Shenzhen under the guidance of the IPCC. Second, nighttime light data were used to spatialize the gross domestic product to obtain the economic benefit coefficients of the various land types. Finally, a multi-objective linear programming model was used to optimize the land-use structure under different scenarios for 2020 and 2025. The results show that (i) energy consumption contributed the most to local carbon emissions in 2016, at 94.75%; (ii) carbon emissions from paddy fields, animals, and humans were the second most dominant source; (iii) the intensity of carbon emissions from different land types in 2016 was variable; and (iv) compared with the natural scenario, an optimized land-use structure could reduce carbon emissions by 5.97% by 2020 and 12.61% by 2025. Under ideal simulation conditions, the simulated land-use pattern could not only meet the requirements of economic and social development, but also could effectively reduce carbon emissions, which is of great value to land managers and decision-makers.

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