Carbon Emission Efficiency And Low Carbon Optimization Study Of Land Use Taking Tongling County As An Example

Due to the increase of human activities that contribute to greenhouse gases,causing the global warming has become an indisputable fact.Global warming will bring extreme weather, causing a great threat to the survival of mankind.The world that is facing climate change issues must be jointly from the source to reduce greenhouse gas emissions, China is the largest developing country in the world, has gone beyond the America became the world’s largest emitter of greenhouse gases,must choose the development of low carbon economy, and makes the contribution for the world energy saving and emission reduction.Studies have shown that, the changes of land use have an important effect on carbon emissions, controlling the carbon emissions through the adjustment of land use types.Therefore, estimation of carbon emissions in different land use, and to study the spatio-temporal changes of land use law of carbon emissions, has the vital significance to realize the sustainable development of economy.This paper takes Tongling County as an example, on the basis of land utilization of carbon sources and sinks of theory,and it uses the emission coefficient method to estimate the carbon emission of land use during2000-2013 of the study area,analyzing the carbon emissions temporal characteristics of land; in the spatial scale of1 km * 1km and through the method of general Craig difference, it explores spatial distribution pattern of the carbon emission risk of Tong ling County; according to minimization of carbon emissions and maximization of carbon savings, it uses the linear programming model to optimize quantity structure of land use of Tong ling County; integrated with the CA model, it simulates low carbon spatial distribution of land use of Tongling County of 2020, and puts forward some suggestions and measures of low carbon land use. The main results are as follows:(1)Land use change of Tongling County between 2000-2013 showed :in 13 years,cultivated land area had been declining,but the area of construction had been increasing;we can see from the analysis of structure change of land use :the dynamic degree of arable land,grassland, water and other land was negative, showing an decreasing trend;the dynamic degree of garden, woodland and construction land was positive, showing an increasing trend.(2)Land use carbon emissions of Tongling County in the mass presented the trend of growing during 2000-2013, from the temporal changes of view, and it could be classified into three stages: a period of slower growth during 2000-2007, a period of rapid growth during 2007-2011, a period of decreasing year by year during2011-2013. The cultivated land and construction land were both influenced by carbon source, construction land carbon emissions played a decisive role in land use carbon emissions of Tongling County.(3)Net carbon emission intensity, per capita carbon emission intensity and land use change trend of carbon emission intensity of Tongling County were basically consistent in the change tendency during 2000-2013, and they have experienced an increased first and then decreased process. So it showed the development of the economy of Tongling County was relatively reasonable after 2010, economic development model was relatively lower-carbon.(4)We can see from the spatial distribution characteristics of carbon emission risks of land use: the index of carbon emission risk of land use of Tongling County during 2000-2010 became larger and larger, and at the same time, the index of carbon emission risk of land use showed a trend from high to low, with carrying out the process of urbanization.(5)It constructed two objective functions based on minimization of carbon emissions and maximization of carbon savings, using linear programming model,finding two kinds of optimization scheme of land use, and it showed: the results of optimization based on minimization of carbon emissions and maximization of carbon savings were basically consistent, which suggests the results of optimization of two schemes of had a good effect on carbon reduction and carbon sink.