Search

Carbon neutrality strategies have a significant role in climate mitigation efforts. As global concerns regarding climate change continue to increase, achieving carbon neutrality has emerged as a paramount objective for reducing greenhouse gas emissions and limiting the adverse impacts of anthropogenic activities on the environment. This research investigates a wide range of scholarly works to conduct an in-depth analysis and synthesis of the relevant information about carbon neutrality strategies. The review introduces carbon neutrality principles and terminologies, highlighting their importance in climate mitigation. It then proceeds to explore the wide range of strategies employed across different sectors and industries, investigating their effectiveness, scalability, and potential challenges. A multidimensional analysis contrasts the United States Nationally Determined Contributions pathway 2023, China's Nationally Determined contributions 2023, and the EU Directive 2023/2413, assessing their economic, environmental, political, and social impacts. The study evaluates strategies' effectiveness, scalability, and innovation for transitioning to a sustainable, low-carbon future. It fills a gap by analyzing global approaches across the US, China, and the EU, which account for about 50% of the world's total GHG emissions. It evaluates the novel application of diverse strategies, from renewable energy transitions to innovative policy measures, highlighting their potential to mitigate climate change effectively. By providing a multidimensional analysis of these strategies' impacts, the research not only enhances understanding of effective carbon neutrality tactics but also underscores the importance of international cooperation in realizing a sustainable, low-carbon future. • Identifies and analyzes carbon neutrality strategies, emphasizing the need for diverse US, Chinese, and EU approaches. • Evaluate renewable energy, carbon capture, and policy tools for carbon reduction effectiveness, scalability, and innovation. • Highlights the study's novelty in synthesizing current knowledge on carbon neutrality, addressing a significant research gap. • Concludes with strategic ideas for international collaboration and policy development for low-carbon futures. [ABSTRACT FROM AUTHOR]

• A CGE model elaborately depicting six CCS technologies was developed. • Impacts of four CCS incentive scenarios on decarbonization pathways were simulated. • CCS can sequester 960 ∼ 1,604 MtCO 2 annually in China by 2060 with policy incentives. • CCS incentives can reduce China's future primary energy demand by 7.7 ∼ 17.4 %. • CCS incentives can increase GDP by 5.64 ∼ 6.59 % compared to no policy scenario. Carbon capture and storage (CCS) technology, considered as a pivotal tool in mitigating climate change within the fossil energy system, particularly in China, has experienced slower development than expected. The exploration of direct incentive policies to facilitate its growth remains relatively underdeveloped. This study developed a hybrid dynamic computable general equilibrium (CGE) model to simulate the substantial impacts of CCS incentive policies on China within the context of carbon neutrality target. Two potential incentive policies, carbon emission trading system (ETS) and 45Q tax credit, were simulated, with different sectoral coverage. The results indicate that CCS technologies can reduce carbon emissions by 960 ∼ 1,604 MtCO 2 annually by 2060 through the strategic implementation of these incentive policies. The 45Q tax credit demonstrates its effectiveness in promoting early-stage research and development (R&D) and demonstration of CCS, while the ETS policy facilitates the commercial development of CCS in the later stage of development. By 2060, the implementation of CCS incentive policies could potentially result in 7.7 ∼ 17.4 % reduction in China's primary energy consumption, 71.2 ∼ 82.7 % decrease in the carbon price of ETS and 5.64 ∼ 6.59 % increase in the GDP compared with the no-policy scenario. In addition, the sectoral output in various sectors and the welfare of urban and rural households also increase. This paper provides an important reference for the realization of China's carbon neutrality goal and the model framework can be applied to other countries. [ABSTRACT FROM AUTHOR]

Coastal salt marshes suffering from anthropogenic coastal development and sea level rise have attracted much attention because of their capacity for carbon sequestration and global climate change mitigation. Accurate mapping of coastal salt marshes is always the first step for their protection, management, and restoration. The inherent complexities of vegetation, dynamics of tides, and anthropogenic disturbances pose challenges for remote sensing-based approaches. Existing studies have utilized phenology information and various black-box algorithms to reduce misclassifications. However, the approaches with dual-temporal images containing phenology information have suffered from inefficiency; the misclassifications have been objectively post-processed rather than considered in the method design, and the tacit knowledge of the trained black-box models has not been revealed. To address the above issues, we proposed a new approach with solid improvements in dual-temporal image construction, misclassification processing, and tacit knowledge analysis, including an efficient method to synthesize dual-temporal images based on the common divisor of the green-up season or senescence season resulting from latitudinal gradients in narrow coastal areas of China, a detailed classification scheme by interpretation of iteratively collected samples, and a key decision rule approximating the trained model. We applied the approach to Sentinel-1/2 images and DEM data, thus deriving a 10-m resolution coastal salt marsh map of China with an overall accuracy of 92.5%. A qualitative comparison showed that the map produced in this study was fitted well with actual salt marsh distributions, resulting in improved accuracy when compared to recently generated maps. The most important contribution is that the overall nature of the trained model observed from the training samples was approximated by a four-feature decision rule following the principle of explainable artificial intelligence, i.e., B8 senescence /B4 senescence < 2.06 & B4 green /B8 green < 0.78 & B12 green /B11 green < 0.72 & elevation < 2.13 , and thus established a new potential classification mechanism for dual-temporal black-box algorithms, i.e., the water signal was covered up by flourishing vegetation, but the situation changed when vegetation withered. This study not only generates an accurate coastal salt marsh map at a national scale but also provides a classification mechanism for dual-temporal image-based coastal salt marsh identification and mapping. • Developed an efficient method for constructing senescence and green images. • Established a mechanism for dual-temporal image-based coastal salt marsh mapping. • Provided a coastal salt marsh map with solid improvements on the most recent one. • Explored a case of explainable artificial intelligence (XAI) in the coastal. [ABSTRACT FROM AUTHOR]

The carbon balance in urban areas has become a major research challenge and a principal policy concern in efforts to address anthropogenic climate change. Rapid urbanization and industrialization in China urge the search for integrated strategies to mitigate and adapt to climate change, which not only limit to traditional infrastructure sectors, but also cover urban green infrastructure, because plants and soils function as carbon sinks through biotic sequestration. This study presents a nationwide study about how urban green infrastructure could contribute to the carbon balance in 35 major Chinese cities. By the end of 2010, the total area of urban green spaces (the dominant components of urban green infrastructure) accounts for 6.38% of the total land area of these cities and represented 51.7% of the total urban green spaces of all 657 cities in China. Based on empirical data from the literature, the total amount of carbon stored in the vegetation of the urban green infrastructure of 35 cities was estimated at 18.7 million tons, with an average carbon density of 21.34 t/ha. In 2010, the amount of carbon sequestration totaled 1.90 million tons with an average carbon sequestration rate of 2.16 t/ha/year. Collectively, only 0.33% of the carbon emissions from fossil fuel combustion can be offset, ranging from 0.01% in Hohhot to 22.45% in Haikou. Nevertheless, the dominance of young vegetation stands in Chinese urban green infrastructure suggests this small carbon sequestration efficiency could become substantial in the near future, given that appropriate policies and management practices are adopted to promote urban green infrastructure for climate change mitigation and adaptation. [ABSTRACT FROM AUTHOR]

Abstract: Soil C sequestration in cropland could play an important role in mitigating the rapidly increasing CO2 emissions in China. Many efforts had been dedicated to estimating the potential for C sequestration in croplands. Potential increases in SOC in China''s croplands had been recently evaluated using inventory-up-scaling simulation and crop-soil C process-based modeling. In this study, data of SOC change at monitoring sites from croplands across mainland China were collected from publications available from 1985 to 2006 to perform a statistical analysis. The data set comprises 1081 observations (404 from rice paddies, RPs and 677 from dry croplands, DCs). Frequency analysis indicates that over 70% of observations show an increase in SOC, which is higher among RPs than DCs. To quantify SOC dynamics, a Relative Annual Change Index in gkg−1 year−1 (RAC, gkg−1 year−1) is defined and calculated using the initial and final SOC values for the duration of monitored observations. RAC values ranged from −0.806 to 0.963gkg−1 year−1 for DCs and from −0.597 to 0.959gkg−1 year−1 for RPs, respectively. From this data, the average is estimated to be 0.056±0.200gkg−1 year−1 for DCs, and 0.110±0.244gkg−1 year−1 for RPs, with an overall estimate for China''s croplands, with RPs and DCs combined, of 0.076±0.219gkg−1 year−1. A mean increase in topsoil C (0–20cm) stock of China''s croplands was estimated to be 25.5TgCyear−1 (8TgCyear−1 in RPs and 17.5TgCyear−1 in DCs) between 1985 and 2006, with a total topsoil C stock increase of 0.64 Pg C over the whole period. The annual stock increase may offset ∼20%, on average, of the total CO2 emissions of China for 1994. This study suggests an important role of China''s croplands, especially rice paddies, for C sequestration to mitigate climate change. [Copyright &y& Elsevier]

As bioenergy produces neutral or even negative carbon emissions, the assessment of biomass resources and associated emissions mitigation is a key step toward a low carbon future. However, relevant comprehensive estimates lack in China. Here, we measure the energy potential of China's domestic biomass resources (including crop residues, forest residues, animal manure, municipal solid waste and sewage sludge) from 2000 to 2016 and draw the spatial-temporal variation trajectories at provincial resolution. Scenario analysis and life cycle assessment are also applied to discuss the greenhouse gas mitigation potentials. Results show that the collectable potential of domestic biomass resources increased from 18.31 EJ in 2000 to 22.67 EJ in 2016 with overall uncertainties fluctuating between (−26.6%, 39.7%) and (−27.6%, 39.5%). Taking energy crops into account, the total potential in 2016 (32.69 EJ) was equivalent to 27.6% of China's energy consumption. If this potential can be realized in a planned way to displace fossil fuels during the period 2020–2050, cumulative greenhouse gas emissions mitigation would be in the range of 1652.73–5859.56 Mt CO 2 -equivalent, in which the negative greenhouse gas emissions due to the introduction of bioenergy with carbon capture and storage would account for 923.78–1344.13 Mt CO 2 -equivalent. Contrary to increasing bioenergy potentials in most provinces, there are declining trends in Tibet, Beijing, Shanghai and Zhejiang. In addition, Yunnan, Sichuan and Inner Mongolia would have the highest associated greenhouse gas mitigation potentials. This study can provide valuable guidance on the exploitation of China's untapped biomass resources for the mitigation of global climate change. • China's bioenergy potential in 2016 accounted for 27.6% of its energy consumption. • The bioenergy potential in Tibet, Beijing, Shanghai and Zhejiang was declining. • GHG mitigation potentials of China's bioenergy would be 1653–5860 Mt CO 2 e by 2050. • China's bioenergy can contribute 6–21% to a global carbon mitigation goal in 2050. [ABSTRACT FROM AUTHOR]