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Hebei Province in China is facing a serious water shortage, which is further aggravated by the pressure of industrial transfer and the unreasonable structure of industrial water use. To explore the relationship between industrial water use and carbon emissions, in this study, a refined logarithmic mean divisia index (LMDI) decomposition method was developed to analyze the driving factors of industrial water use in Hebei Province during 2008–2019 from carbon emission and sectoral perspectives. The results show that the carbon emission effect, the water–carbon effect, and the industrial structure effect were the main factors contributing to the decrease in industrial water use during the study period. The carbon emission effect made a great contribution to its decline. The cumulative contributions of these factors were −1425, −533, and −763 million m3 from 2008 to 2019. The contribution of the industrial structure effect was −106.93%, with a large potential for water saving. According to the sectoral analysis, the 32 sectors in Hebei Province exhibited significant sectoral heterogeneity, and the strong promoting industries were identified as the main sectors contributing to the increase in the promotion of industrial water use. This paper provides a reference for the scientific formulation of water-saving and emission-reduction policies and research on the water–carbon relationship in Hebei Province. [ABSTRACT FROM AUTHOR]

China has committed to peak carbon emissions by 2030 and become carbon neutral by 2060. Hebei, as a major energy province in China, has more challenging carbon peaking and carbon neutrality targets. Based on the extended STIRPAT model, this paper evaluates the time to peak carbon and post-peak carbon trend changes in Hebei province under different scenarios from 2020 to 2060. Based on the support vector machine model with particle swarm optimization, this paper evaluates the carbon neutral pathways under different scenarios in Hebei province from 2020 to 2060 in terms of forests, croplands, wetlands, grasslands and Carbon Capture, Utilization and Storage (CCUS). The results show that a monotonically flat trend without inflection point, a single-inflection-point plateau-period trend and a multi-inflection-point inverted U-wave trend occur after carbon peaks. Hebei Province can achieve carbon neutrality by 2060 under the policy scenario and the enhanced scenario, and the enhanced scenario is better. Comparing with existing studies, the innovation of this paper is to design different trends of changes after carbon peak, combining carbon absorption and carbon emission, and providing more diversified development paths for carbon neutral strategies through a more integrated perspective and multi-scenario comprehensive analysis. Therefore, In the future, Hebei Province should establish a platform for carbon emissions monitoring and carbon footprint assessment, and set up an early warning and assessment mechanism for carbon peaking, so as to prevent a rebound trend in carbon emissions after peaking. At the same time, it should introduce and develop carbon capture and conversion technologies and promote the low-carbon transformation of the industrial and energy sectors, thereby forcing the early realization of peak carbon. Pay attention to the role of forestry resources in carbon neutrality, increase carbon sink resources such as forests and wetlands, promote the development of CCUS, and enhance the implementation of the policy. [ABSTRACT FROM AUTHOR]

China is currently recognized as the leading global energy consumer and CO2 emitter. A significant amount of carbon emissions can be attributed to urban public buildings. Establishing an equitable and efficient carbon emission allocation mechanism is a crucial step to meeting the ambitious targets in China's 2030 carbon peak plan. In this study, we estimate the total amount of CO2 emissions from urban public buildings by 2030 and propose a preliminary scheme of carbon quota assignment for each province. By means of applying the zero-sum gains data envelopment analysis (ZSG-DEA) model, the carbon emission quotas allocation of urban public buildings in China's 30 provinces is proposed, and the corresponding pressure to reduce provincial carbon emissions is analyzed. The results indicate that Qinghai has the lowest carbon emission rate (0.01%) for urban public buildings, while Guangdong has the highest (9.06%). Among the provinces, Jiangsu, Jiangxi, and Tianjin face the least pressure in reducing carbon emissions from urban public buildings. On the other hand, Hebei, Beijing, and Anhui are under great pressure to decrease carbon emissions. Notably, Hebei is predicted to have the highest emission reduction requirement of 95.66 million tons. In terms of pressures on carbon emissions reduction for urban public buildings, Jiangsu, Jiangxi, and Tianjin exhibit the least pressure. Hebei, Beijing, and Anhui are facing intense pressure to decrease carbon emissions. These findings offer policymakers valuable insights into developing a fair and efficient carbon allowance allocation strategy, while also contributing to China's efforts to mitigate carbon emissions and combat climate change. [ABSTRACT FROM AUTHOR]

In recent decades, large-scale deployment of photovoltaic (PV) power leads to management challenges for recycling PV module waste in China. With the growth of waste PV volumes, it is necessary to figure out the spatio-temporal distribution of PV waste at the provincial level. Based on China's carbon neutrality goal by 2060, six development pathways of PV installed capacity are proposed to identify in-use stocks of PV capacity. In particular, we develop the retired flow estimation model for PV modules that is constructed by three PV module degradation scenarios. The results show that a relatively large scale of PV waste will be started to emerge in China by 2030 and the cumulative waste is expected to reach 1100 ∼ 1450 GW by 2060. Our findings also indicate an unequal distribution of PV waste across regions and the highest PV waste volumes by 2060 is the East China region at 31.4%, with Shandong (8.99%) and Hebei(8.65%) ranking as the top provinces. This prospective research will help the PV industry plan the location and capacity of recovery facilities at an appropriate time to advance toward a more resource efficient and circular economy. [ABSTRACT FROM AUTHOR]