Integrated Land Use Change Related Carbon Source/Sink Examination in Jiangsu Province

Multiangle land use-linked carbon balance examination in Nanjing City, China

Evaluating and simulating the impacts of land use patterns on carbon emissions in coal resource-based regions: A case study of shanxi province, China

The dramatic changes in land use caused by human economic activities have a profound impact on carbon emissions and ecosystem service value （ESV）. In order to explore the evolution characteristics of carbon emissions and ESV on the spatial and temporal scales， based on the land use data of the Yellow River Basin from 2000 to 2020， this study used spatial autocorrelation and multivariate Logit regression models to study the spatial and temporal characteristics and spatial correlation of total carbon emissions and ESV in counties of the Yellow River Basin， then to explore the influencing factors of spatial correlation. The research findings were as follows： ① In the past 20 years， the total amount of land use carbon emissions in the basin has shown an overall growth trend， and the increasing counties were concentrated in energy-rich areas such as Inner Mongolia， Ningxia， and northern Shaanxi. The total amount of ESV increased first and then decreased， and the high value counties were mainly distributed on the edge of the Yellow River Basin， among which Qumalai County in Qinghai Province had the most ESV. The low value counties of ESV were mainly located in the economically active urban agglomerations such as the Shandong Peninsula Region， Central Plains Region， Guanzhong Plains Region， and cities along the yellow river in Ningxia. The lowest value of ESV has always been located in Xi'an. ② There was a spatial negative correlation between total carbon emissions and total ESV. The number of counties with high carbon emissions and high ESV has been increasing， mainly distributed in southern Inner Mongolia， eastern Ningxia， and northern Shaanxi， which was related to the location near the Yellow River and energy development. The double low type was mainly located in the gully area of the Loess Plateau， which is connected to the strip from the east and west. The low-high class was contiguously distributed in Qinghai， Sichuan， and western Gansu， and some were island-like distributed around the double-low class. The number of high-low classes was increasing year by year， mainly located in the core city area. ③ In low ESV counties， regions with better economic development and higher population were more likely to increase their carbon emissions. Taking the low carbon emissions from land use as a reference， the per capita GDP， energy use efficiency， and rainfall were significantly negatively correlated with the high-high and high-low categories. This indicates that most counties with high carbon emissions had relatively dense populations and less rainfall， resulting in higher energy dependence. Additionally， there was a positive correlation between low-high class areas and total population. When located in areas with low land use carbon emissions， areas with higher ESV values tended to have more a concentrated population distribution. The increase in land reclamation rate may encroach on forests and grasslands that can provide higher ecosystem services， reducing the value of regional ecosystem services. The research findings have certain reference significance for ecological protection and high-quality development decision-making in the Yellow River Basin.

Spatial-temporal characteristics of carbon emissions corrected by socio-economic driving factors under land use changes in Sichuan Province, southwestern China

PDF HTML阅读 XML下载 导出引用 引用提醒 基于土地利用变化的四川省碳排放与碳足迹效应及时空格局 DOI: 10.5846/stxb201506111188 作者: 作者单位: 地理与资源科学学院,地理与资源科学学院,中国科学院资源环境科学数据中心,地理与资源科学学院,地理与资源科学学院,地理与资源科学学院 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金资助项目（41371125） Effect of land use changes on the temporal and spatial patterns of carbon emissions and carbon footprints in the Sichuan Province of Western China, from 1990 to 2010 Author: Affiliation: Key Lab of Land Resources Evaluation and Monitoring in Southwest,Ministry of Education,Sichuan Normal University,Key Lab of Land Resources Evaluation and Monitoring in Southwest,Ministry of Education,Sichuan Normal University,Data Center for Resources and Environmental Sciences,Chinese Academy of Sciences RESDC,Key Lab of Land Resources Evaluation and Monitoring in Southwest,Ministry of Education,Sichuan Normal University,Key Lab of Land Resources Evaluation and Monitoring in Southwest,Ministry of Education,Sichuan Normal University,Key Lab of Land Resources Evaluation and Monitoring in Southwest,Ministry of Education,Sichuan Normal University Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:土地利用变化的碳排放与碳足迹研究对了解人类活动对生态环境的扰动程度及其机理、制定有效的碳排放政策具有重要意义。采用1990-2010年四川省能源消费数据和土地利用数据，通过构建碳排放模型、碳足迹及其压力指数模型，对研究区20年来土地利用的碳排放及碳足迹进行了定量分析。结果表明：（1）土地利用变化的碳排放和能源消费碳的足迹呈显著增加趋势。碳排放增加5407.839×104 t，增长率达143%；能源消费的碳足迹增加1566.622×104 hm2，四川全省的生态赤字达1563.598×104 hm2。（2）建设用地和林地分别为四川省最大的碳源与碳汇。20年间建设用地的碳排放增加5407.072×104 t，增长率达126.27%，占碳排放总量的88%以上；林地的碳汇减少10.351×104 t，但仍占四川省碳汇的96%以上。（3）土地利用碳排放、碳足迹和生态赤字存在明显区域差异。成都平原区碳排放、碳足迹压力最大，生态赤字严重，西部高山高原区和盆周山区碳排放、碳足迹最小，未出现生态赤字；成都、德阳、资阳和内江等地的碳排放、碳足迹压力最大，生态赤字最严重，甘孜、阿坝等地的碳排放、碳足迹最小，未出现生态赤字。（4）土地利用结构与碳排放、碳足迹存在一定的相互关系，趋高的碳源、碳汇比导致土地利用的碳源效应远大于碳汇效应。因此，四川省减排的重点应该在保持或增加现有的林地的同时，主要以降低建设用地的碳排放、碳足迹为主。 Abstract:Land use changes significantly affect the carbon dynamics of terrestrial ecosystems, and are one of the main factors influencing climate change on a global scale. Analyzing the effects of land use on carbon emissions is important for understanding the mechanisms of carbon emissions and the success of carbon reduction and climate change mitigation efforts. In this study, we developed carbon emission, pressure index, and carbon footprint models to evaluate a carbon budget, and carried out research in the Sichuan Province of western China to estimate carbon sinks and carbon sources, based on energy consumption and land use change data from 1990 to 2010 (obtained from remote sensing technologies). The results showed that:(1) Changes in land use and energy consumption from 1990 to 2010 significantly increased carbon emissions (5407.839×104 t, or 143%), with an average annual rate of increase of 7.151% (1566.622×104 hm2). During the same period, the carbon footprint for energy consumption increased, and the area of ecological deficit reached 1563.598×104 hm2. Overall, the increase in carbon emissions was associated with a rapid increase in fossil fuel consumption as well as land use changes; (2) Land under construction (carbon source) and forests (carbon sink) were the largest carbon pools in the carbon budget. Higher carbon emissions were noted for built-up land than for other land use types. Between 1990 and 2010, there was a continuous increase in carbon sources, and a slight decrease in carbon sinks. Carbon emissions from built-up land increased by 126.27%, which was the largest percentage increase in carbon emissions; (3) There were considerable regional differences in carbon emissions and carbon footprints. The Chengdu plain, and its surroundings regions (e.g., Chengdu, Deyang, Ziyang, and Neijiang), had higher carbon emissions, carbon footprints, and ecological deficits in 2010 than in 1990. In contrast, the west, northwest, and southwest mountainous regions and plateau areas (e.g., the Ganzhi, Aba, and Liangshan autonomous prefectures) had lower carbon emissions in 2010 than in 1990. In general, these regions had low carbon footprints and ecological deficits because of their widespread coverage by forests and grasslands. Compared to the Chengdu plain (and its surroundings regions), these regions had relatively low fossil fuel consumption, slow urbanization rates, and limited industrial development and transportation corridors. Overall, in Sichuan, there was an increase from 1990 to 2010 in the spatial distribution and severity of carbon emissions, carbon footprints, and ecological deficits; and (4) Land use had a greater effect on carbon sources than on carbon sinks. Forests, grasslands, water areas, and unused land were the main carbon sinks, while land under construction and cultivated land were the main carbon sources. The rapid increase in carbon sources and slow decrease in carbon sinks resulted in a substantial increase in carbon emissions in Sichuan from 1990 to 2010, with the ratio of sources to sinks increasing from 4.002 in 1990 to 9.739 in 2010. In conclusion, one key focus of future carbon emission reduction efforts in Sichuan should be to maintain or increase forest areas. It would also be worthwhile to reduce carbon emissions from land under construction. Through targeted land use and land management activities, ecosystems can be managed to enhance carbon sequestration and mitigate fluxes of greenhouse gases. 参考文献 相似文献 引证文献

Land use directly affects the carbon emissions and carbon stock of the ecosystem, and indirectly affects the carbon emissions from anthropogenic activities, which occur more frequently in coastal regions. Taking Nantong City as an example, detailed carbon emission projects were classified and calculated for different land use types by combining land use images of five typical years. Based on the complex relationship between land use carbon emissions and socio-economic factors, the system dynamics model (SD) was used to simulate the land use carbon emissions from 2005 to 2060, and to construct carbon-neutral policy scenarios. Compared with inlands, carbon emissions from land use in Nantong are more pronounced than inland areas, and unique land use types, such as shallows, play an important role as carbon sinks. Total land use carbon emissions show an upward trend from 2005 to 2020 and carbon emissions from construction land dominate. Under the natural development condition, the total net carbon emissions of Nantong are about 4,298,250 tons in 2060, failing to achieve carbon neutrality. The scenario with all four policies adjusted (LO, IO, TP, and PC) has the best emission reductions, peaking at 10,949,010 tons of net carbon emissions in 2029 and reducing them to 1,370,202 tons in 2060, which is the scenario closest to the carbon-neutral target. Overall, this study provides a meaningful conclusion for the study of land use carbon emission characteristics and low-carbon pathways in coastal cities, which can guide the formation of government policies.

The farming-pastoral ecotone has an important strategic place in the energy supply and ecological layout of China. Thus, exploring the spatial and temporal variation characteristics of carbon emissions in this region will help to deeply understand the information on the historical carbon emissions in China's energy production bases and provide data references for the formulation of differentiated emission reduction policies and the promotion of regional energy-saving and carbon-reducing measures, which is of great significance for the realization of low-carbon economic development. This study constructed a spatialization model of carbon emissions based on land use, night lighting, and provincial energy consumption data； explored the spatiotemporal changes and aggregation characteristics of carbon emissions in the farming-pastoral ecotone from 1995 to 2020 using the global Moran's index and hotspot analysis； and then combined it with the slack-based measure model to calculate the carbon emission efficiency and emission reduction potential of each city from 2010 to 2020 and classify cities to propose a differentiated emission reduction path. The results showed that, firstly, the estimated results at the prefectural city level of the carbon emission spatialization model constructed in this study with multi-source data could reach an R2 of 0.92 for a linear fit. Secondly, the total carbon emissions in the farming-pastoral ecotone increased from 176.29 million tons in 1995 to 1 014.51 million tons in 2020. However, the carbon emission intensity and growth rate both decreased, which was related to adjusting the energy structure and improving energy efficiency. Regarding spatial distribution, the cities with high carbon emissions over time were Datong, Baotou, and Yulin in order. Thirdly, the carbon emissions in the study area showed a significant global spatial positive correlation at the county level, with the hot spots mainly located at the junction of Shanxi, Shaanxi, and Inner Mongolia, while the cold spots were extended from Yanan City to Qingyang and Guyuan City after 2010. Finally, based on the differences in carbon emission efficiency and reduction potential, cities could be classified into four types： "high-efficiency and high potential," "low-efficiency and high potential," "high-efficiency and low potential," and "low-efficiency and low potential" to implement targeted emission reduction strategies.

Examining the relationships between carbon emissions and land supply in China

The transformation of ecosystem types caused by land use change plays an extremely important role in the regional carbon cycle. Studying the response of vegetation carbon source/sink systems to land use change is helpful to improve the understanding of the vegetation carbon sink effect in the process of land use change. However, few studies have focused on the response of vegetation carbon sources/sinks to land use change. The CASA model and soil microbial respiration model were combined to estimate the net ecosystem productivity （NEP） of vegetation in the Yanhe River Basin in the Chinese Loess Plateau from 2000 to 2020 based on remote sensing, meteorological, and land use data. The spatiotemporal pattern evolution characteristics of the carbon source/sink and land use were identified using a significance test, univariate linear regression analysis, and land use status transition matrix methods, and the response of the carbon source/sink to land use change was further analyzed. The results showed that from 2000 to 2020, the multi-year average NEP in the Yanhe River Basin showed a spatial distribution pattern of lower in the upstream and higher in the midstream and downstream. The Yanhe River Basin belonged to a weak carbon sink area as a whole, with this type of area accounting for 88.81% of the basin area. The annual NEP of the basin showed a significant increase trend in fluctuations, and the carbon sequestration capacity was gradually improving. The areas with significant and extremely significant increases in annual NEP accounted for 65.78% of the basin area, and the types of annual NEP restoration, basic stability, and degradation accounted for 79.70%, 10.15%, and 10.15% of the basin area, respectively. Over the past 20 years, the land use transformation of Yanhe River Basin mainly included five types, that is, cropland was converted into grassland, woodland, and construction land, and grassland was converted into cropland and woodland. The land use in the Yanhe River Basin was mainly shifting towards promoting the improvement of the carbon sink capacity, and the transformation of land type to woodland had a more significant effect on improving carbon sink capacity. During the five main land use transformation processes in the Yanhe River Basin, the area ratio of NEP recovery-recovery type for cropland shifting to woodland was the highest at 80.78%. The area ratios of NEP recovery-recovery type for grassland shifting to cropland and cropland shifting to grassland were relatively low, at 48.05% and 51.97%, respectively. The stability of NEP restoration when shifting cropland to woodland was the strongest, and the fluctuation of NEP restoration when shifting between cropland and grassland mutually was strong. When adjusting cropland and grassland mutually, attention should be paid to select suitable vegetation types and increase vegetation coverage reasonably to improve carbon sequestration and sink enhancement capabilities, so as to avoid carbon losses during land transformations. The research methods and results in this study can provide reference for land management departments to formulate scientific and reasonable land use decisions to promote vegetation carbon sequestration and sink enhancement.

The spatial and temporal characteristics of land use carbon emissions are relevant to the sustainable use of land resources. Although spatial and temporal studies have been conducted on land use carbon emissions, the spatial correlation of land use carbon emissions at the city level still requires further research. Here, we estimated the distribution of carbon emissions at the city level in Shandong Peninsula urban agglomeration in spatial and temporal terms based on land use remote sensing data and fossil energy consumption data during 2000–2019. The results showed that the land use change in the 16 cities in the study area was the conversion of cropland to construction land. Carbon emissions from land use had an upward trend for all 16 cities overall during the period of 2000–2019, but the incremental carbon emissions trended downward after 2010. Among them, Jinan and Qingdao had higher carbon emissions than other cities. In addition, we also found that land use carbon emissions at the city level were characterized by stochasticity, while per capita carbon emissions displayed geospatial aggregation. Among them, Yantai displayed a spatial pattern of high–high clustering of carbon emissions, while Jining presented a spatial pattern of low–low clustering in terms of land-average carbon emissions and carbon emissions per capita during 2000–2019. The results of the study are important for guiding the achievement of urban carbon emission reduction and carbon neutrality targets at the city level.

Land use changes play a major role in determining sources and sinks of carbon at regional and global scales. This study employs a modified Global biome model‐biogeochemical cycle model to examine the changes in the spatiotemporal pattern of net ecosystem production (NEP) in the Taihu Lake Basin of China during 1985–2010 and the extent to which land use change impacted NEP. The model is calibrated with observed NEP at three flux sites for three dominant land use types in the basin including cropland, evergreen needleleaf forest, and mixed forest. Two simulations are conducted to distinguish the net effects of land use change and increasing atmospheric concentrations of CO2 and nitrogen deposition on NEP. The study estimates that NEP in the basin decreased by 9.8% (1.57 Tg C) from 1985 to 2010, showing an overall downward trend. The NEP distribution exhibits an apparent spatial heterogeneity at the municipal level. Land use changes during 1985–2010 reduced the regional NEP (3.21 Tg C in year 2010) by 19.9% compared to its 1985 level, while the increasing atmospheric CO2 concentrations and nitrogen deposition compensated for a half of the total carbon loss. Critical measures for regulating rapid urban expansion and population growth and reinforcing environment protection programs are recommended to increase the regional carbon sink.

In a rapid urbanization context, socio-economic development has caused large increases in carbon emissions. In this study, various techniques such as cointegration analysis, vector autoregression, and decoupling elastic function methods are applied to analyze the sequential collaborative relationship between economic development and carbon emissions in the process of urbanization in terms of the time-series lag relationship and the decoupling relationship. The main findings are as follows: (1) urbanization and carbon emissions displayed a temporal correlation relation with a lag of order 4, according to stability tests, and (2) the development of urbanization, economic growth, and changes in land use may be responsible for the time lag in carbon emissions. Furthermore, the mechanisms behind the effect of urbanization on carbon emissions are investigated to assist future carbon emissions reduction efforts. (3) From 1990 to 2014, carbon emissions and economic development showed a temporal evolution trend of "weak decoupling-expansionary coupling-weak decoupling" in the Pearl River Delta region, and there was an overall weak decoupling state: carbon emissions increased with growth in economic development, but the emissions growth rate was lower than the speed of economic development. (4) From 1990 to 2014, economic development showed a trend of sustained growth in the Pearl River Delta region, and differences were detected in the decoupling status between carbon emissions and economic development at different times. The overall decoupling status of the nine cities in the region was one of weak decoupling; however, the decoupling index, carbon emissions, and economic development levels displayed differences, whereby cities with high carbon emissions and high economic development levels were not necessarily the cities in which environmental pressures from economic development were the most severe. Our results have important theoretical and practical significance as they clarify the impact of economic development on carbon emissions in the process of urbanization, as well as the carbon emissions reduction work that must be undertaken in urban systems.

Land use, as one of the major sources of carbon emissions, has profound implications for global climate change. County-level land-use systems play a critical role in national carbon emission management and control. Consequently, it is essential to explore the spatiotemporal effects and optimization strategies of land-use carbon emissions at the county scale to promote the achievement of regional dual carbon targets. This study, focusing on Shaanxi Province, analyzed the spatiotemporal characteristics of land use from 2000 to 2020. By establishing a carbon emission evaluation model, the spatiotemporal effects of county-level carbon emissions were clarified. Utilizing Geodetector and K-means clustering methods, the driving mechanisms and clustering characteristics of county-level carbon emissions were elucidated, and optimization strategies for land use carbon emission were explored. The results showed that during 2000–2020, land use in Shaanxi Province underwent significant spatiotemporal changes, with constructed land increasing by 97.62%, while cultivated land and grassland were substantially reduced. The overall county-level carbon emissions exhibited a pattern of North > Central > South. The total carbon emissions within the province increased nearly fourfold over 20 years, reaching 1.00 × 108 tons. Constructed land was the primary source of emissions, while forest land contributed significantly to the carbon sink of the study area. Interactions among factors had significant impacts on the spatial differentiation of total county-level carbon emissions. For counties with different types of carbon emissions, differentiated optimization strategies were recommended. Low-carbon emission counties should intensify ecological protection and rational utilization, medium-carbon emission counties need to strike a balance between economic development and environmental protection, while high-carbon emission counties should prioritize profound emission reduction and structural transformation.

Land use changes lead to changes in the functions of different types of carbon sources and sinks, which are key sources of carbon emissions. The study of carbon emissions and its influencing factors in the Aksu River Basin from the perspective of land use change is of great importance for the promotion of integrated protection and restoration of mountains, water, forests, fields, lakes, grasslands, sand, and ice in the basin and to help achieve the goal of carbon peaking and carbon neutrality. Based on four periods of land use data and socio-economic data from 1990 to 2020, the total carbon emissions from land use were measured, and the spatial and temporal trajectories of carbon emissions and their influencing factors were explored. The results showed that:① from 1990 to 2020, arable land, forest land, construction land, and unused land showed a general increasing trend, whereas grasslands and water areas showed a decreasing trend. The spatial change in land use types was mainly characterized by the conversion of grasslands and unused land into arable land, and 83.58 % of the arable land conversion areas were concentrated in the southwest of Wensu, Aksu, and the northern part of Awat. ② The total net carbon emissions in the basin showed a continuous growth trend from 1990 to 2020, with a cumulative increase of 14.78×104 t. The increase in arable land was a key factor causing an increase in net carbon emissions in the basin. ③ The spatial distribution pattern of land use carbon emissions in the basin was high in the middle and low in the fourth, with significant changes in net carbon emissions mainly in the southern part of Wensu, Aksu, Awat, and Alaer. ④ Human activities had the strongest driving effect on land use carbon emissions, with their effects gradually increasing from east to west. The contribution of average annual temperature to land use carbon emissions was mainly concentrated in the eastern part of Aksu and the northern part of Awat, whereas average annual rainfall had a strong inhibitory effect on the northern part of Wensu and the western part of Aheqi.

This study takes Kunming City, Yunnan Province, China as the research area, to provide reference basis for revealing the change law of land use structure and energy consumption and carbon emissions in Kunming, optimizing land use structure and realizing the development of low-carbon city. Based on the data of land use structure and energy consumption in Kunming from 1997 to 2017, based on the estimation of total energy consumption carbon emissions, carbon intensity and per capita carbon emissions, the correlation between land use structure and energy consumption carbon emissions in Kunming has been calculated and analyzed in the past 20 years. Results: 1) The total amount of carbon emissions in Kunming has increased significantly in the past 20 years. It increased from 34.46 × 105 t to 95.09 × 105 t, an increase of about 2.8 times. 2) The types of land use with the highest correlation between land use structure and total carbon emissions of energy consumption, carbon emission intensity and per capita carbon emissions are urban and village and industrial and mining land (0.8258), cultivated land (0.8733) and garden land (0.7971) respectively. 3) The correlation between construction land and total carbon emissions is greater than that of agricultural land. Conclusion: There is a close correlation between land use structure and carbon emissions from energy consumption in Kunming.