Effects of land-use change on carbon emission and its driving factors in Shaanxi Province from 2000 to 2020

Identifying resource-conscious and low-carbon agricultural development pathways through land use modelling

Increasing agricultural production with current resources and technology may lead to increased GHG emissions. Additionally, large population countries like India face substantial challenges in terms of food demand, agro-ecological heterogeneity, carbon footprint and depleting natural resources, thus increasing the decision complexities for policymakers and planners. We aim to examine the potential of producing more food from available agricultural land with low-carbon (reduced GHG emissions) and resource-conscious (optimal resource use) options. The current study develops multiple calorie production and emission-centric land use using a land use optimization model wherein the calorie production and emission objective, resource and emissions constraints, and food production targets interact across multiple spatial levels. The capabilities of the developed model are demonstrated with a case study in India targeting ten crops (grown over two seasons) covering three food groups (cereals, legumes, and oilseeds). Three hypothetical scenarios for each objective of maximizing calories production (Calories-nation, Calories-group, Calories-crop) and minimizing GHG emissions (Emissions-nation, Emissions-group, Emissions-crop) are developed concerning targets of national crop production (Calories-nation, Emissions-nation), state food groups production (Calories-group, Emissions-group), and state crop production(Calories-crop, Emissions-crop), with different spatial levels of constraints. A maximum growth of 11% in calorie production is observed in Calories-nation while mitigating 2.5% emissions. Besides, the highest emission reduction of around 30% is observed in Emissions-group but with no change in calorie production. Emission scenarios can spare up to 14.8% land and 18.2% water, while calorie production-maximization scenarios can spare a maximum of 4.7% land and 6.5% water. The optimization-based methodology identifies the regions of altered land use by proposing appropriate crop substitution strategies, such as increasing oilseeds in Rajasthan and soybean in east Maharashtra. Many states show conservative production growth and emission reduction with state-level crop production targets (Calories-crop), suggesting crop redistribution within the state alone will not be sufficient unless improved technologies are introduced. The maximum growth and mitigation potential estimated in this study may be affected by climate shocks; therefore, introducing the improved technologies needs to be coupled with a crop redistribution mechanism to design climate-resilient and futuristic land use systems. The proposed land use model can be modified to incorporate climate change effects through consideration of scenarios of changed crop yields or through direct/indirect coupling with dynamic crop simulation models.

Balancing low-carbon and eco-friendly development: coordinated development strategy for land use carbon emission efficiency and land ecological security

Correctly identifying and handling the relationship between land use carbon emission efficiency (LUCEE) and land ecological security (LES) are important to promote carbon neutrality in the overall layout of ecological civilization construction. This study takes 30 provinces in China as the research unit and measures the level of LUCEE and LES in each province in the period from 2011 to 2020 via a super-efficient slack-based measure model considering undesirable output. The coupling coordination degree (CCD) of LUCEE and LES is calculated, and its spatiotemporal evolution pattern is explored by kernel density estimation and standard deviational ellipse (SDE). The Dagum Gini coefficient is used to study spatial regional differences and the sources of differences. Results show that (1) China's LUCEE exhibited a downward and then an upward trend, as well as a spatial pattern of "high in the west and low in the east" with obvious regional differences. The LES experienced a positive transformation of "less secure → basically secure → more secure" nationwide, with no apparent regional differences. (2) The kernel density curves showed a continuous increase in CCD in general, while interprovincial differences increased, then decreased, and shifted from multipolar to bipolar differentiation. (3) The migration of SDE centers in CCD demonstrated a path of "southeast → southwest → northeast," and the ellipticity increased from 0.167 to 0.173, showing a trend of concentrated distribution. (4) The overall Gini coefficient of the national CCD indicated a decreasing trend, but imbalances remained, with the largest annual average value in the western region (0.120) and the smallest in the northeast (0.044). The main source of regional disparity was the intensity of transvariation. Accordingly, this study proposes targeted regional development strategies to promote low-carbon sustainable land use and improve the ability of land ecosystems to prevent security risks.

Spatiotemporal analysis of national carbon emission and regional carbon simulation in China

Land use and land cover (LULC) will cause large flows of carbon sources and sinks. As the world's largest carbon emitter with a complicated LULC, China's carbon emissions have profound implications for its ecological environment and future development. In this paper, we account for the land-use changes and carbon emissions of 30 Chinese provinces and cities in China from 2000 to 2020. Furthermore, the spatial correlation of carbon emissions among the study areas is explored. Four typical regions with spatial association (Beijing, Hebei, Sichuan, and Anhui) are selected, and their land-use change trends in 2025 and 2030 are simulated to predict the total carbon emissions in the future. The results show that the distribution of land-use in China is mainly cultivated and woodland, but the growth of urban built-up (UBL) land area indirectly leads to the continuous increase of carbon emissions. Total carbon emissions have increased over the past two decades, albeit at a slower growth rate, with some provinces experiencing no further growth. In the typical regional carbon emission simulation, it is found that the carbon emissions of the four provinces would show a downward trend in the future. The main reason is the reduction in indirect carbon emissions from fossil energy in UBL, while the other part is the influx of carbon sinks due to grassland, woodland, etc. We recommended that future carbon reduction measures should focus and prioritize controlling fossil energy and mitigating carbon emissions from UBL. Simultaneously, the significant contribution of forests and other land types as carbon sinks should be acknowledged to better implement China's carbon neutral commitment.

Spatiotemporal characteristics and influencing factors of carbon emissions from land-use change in Shaanxi Province, China

Due to global warming, there evolves a global consensus and urgent need on carbon emission mitigations, especially in developing countries. We investigated the spatiotemporal characteristics of carbon emissions induced by land use change in Shaanxi at the city level, from 2000 to 2020, by combining direct and indirect emission calculation methods with correction coefficients. In addition, we evaluated the impact of 10 different factors through the geodetector model and their spatial heterogeneity with the geographic weighted regression (GWR) model. Our results showed that the carbon emissions and carbon intensity of Shaanxi had increased overall in the study period but with a decreased growth rate during each 5-year period: 2000-2005, 2005-2010, 2010-2015, and 2015-2020. In terms of carbon emissions, the conversion of croplands into built-up land contributed the most. The spatial distribution of carbon emissions in Shaanxi was ranked as follows: Central Shaanxi > Northern Shaanxi > Southern Shaanxi. Local spatial agglomeration was reflected in the cold spots around Xi'an, and hot spots around Yulin. With respect to the principal driving factors, the gross domestic product (GDP) was the dominant factor affecting most of the carbon emissions induced by land cover and land use change in Shaanxi, and socioeconomic factors generally had a greater influence than natural factors. Socioeconomic variables also showed evident spatial heterogeneity in carbon emissions. The results of this study may aid in the formulation of land use policy that is based on reducing carbon emissions in developing areas of China, as well as contribute to transitioning into a "low-carbon" economy.

Macroalgae culture-induced carbon sink in a large cultivation area of China

Macroalgae culture-induced carbon sink in sediments has been little investigated. Here, total organic carbon (TOC), total nitrogen (TN), and δ13C were examined in sediments in a cultivation field of macroalgae (kelp and Gracilariopsis lemaneiformis) in Sansha Bay, Southeast China. Both proxies of C/N (TOC to TN ratio) and δ13C indicated a multisource of TOC. Based on a three-endmember model, macroalgae-derived TOC (TOCma) accounted for < 35% of the total TOC, averaging 16 ± 9% (mean ± SD). On average, terrestrial and phytoplankton-derived TOC showed much higher percentages of 24 ± 17% and 60 ± 20%, respectively (t-test, p < 0.02). A preliminary estimate suggested that TOCma represents a carbon sink of 8.2 × 103 tons per year, corresponding to about 22% of the sink associated with phytoplankton and macroalgae and 8 ± 6% of the macroalgae carbon production in Sansha Bay. Considering its production magnitude, the macroalgae-induced carbon sink seems to be insignificant, on a national or global scale, to phytoplankton, though it should be taken into account given the small cultivation area.

Land resource management patterns and urban air quality-evidence from the "land for development" model with Chinese characteristics

Based on panel data of 282 prefecture-level and above cities in China from 2013 to 2020, this paper investigates the impact and transmission paths of the "LFD" land disposal model on urban air quality at the theoretical and empirical levels using dynamic fixed-effects and dynamic spatial Durbin models. The results show that the way land is allocated in a city has a lagging and long-term impact on air quality not only locally but also in neighboring cities. The type of land supply by local governments to different sectors is an important pathway to influence urban air quality. Extended analysis shows that land market reforms in China can significantly reduce urban air quality index (AQI) and effectively mitigate urban air quality, with long-term effects. This paper provides a theoretical and scientific basis for correcting the mismatch of land resources and promoting urban ecological environment in China.