Only ammonia reduction is insufficient: Meeting vegetation critical levels but not PM2.5 air quality targets.

This study investigates the impact of new quality productive forces (NQPF) on carbon emission reduction in China, with a particular focus on the mediating roles of industrial agglomeration effect (IAE) and energy intensity (EI). Using panel data covering 30 provincial-level regions in China over the period 2003-2023, we control for key confounding factors including urbanization, industrialization, industrial structure upgrading, human capital, and foreign direct investment to empirically examine the relationship between NQPF and carbon emission reduction as well as its underlying transmission mechanisms. The results indicate that NQPF exerts a significantly negative effect on carbon emissions, with this carbon reduction impact being particularly prominent in economically developed regions and eastern coastal areas of China. Further mediation analysis reveals that IAE and EI function as two critical pathways through which NQPF influences carbon emission reduction. Specifically, the enhancement of IAE reinforces the carbon reduction effect of NQPF, whereas an increase in EI weakens this effect. Overall, our findings highlight that the development of NQPF can serve as a long-term driving mechanism for effectively achieving carbon emission reduction targets, thereby providing valuable policy implications for advancing low-carbon transition and green sustainable development in China's economy and society.

Industry is the core sector with the most challenging task of carbon emission reduction in China. This paper explores how industrial transformation in China's industrial sector affects carbon emissions. We shed light on the effect of industrial sector transformation on carbon emissions, and divide industrial sector transformation into two aspects: industrial structure optimization and industrial spatial layout.We construct socioeconomic panel data for 30 cities in the urban agglomeration in the middle reaches of the Yangtze River from 2000 to 2020, and explore the influence of industrial transformation on carbon emissions in 33 industrial sectors in China from three dimensions: spatial spillover effect, spatiotemporal heterogeneity, and threshold effect. The results show that: (1) In the industrial structure optimization dimension, industrial rationalization has effect on decreasing carbon emissions, while industrial upgrading increases carbon emissions. In the industrial spatial layout dimension, industrial specialization agglomeration can decline carbon emissions, while industrial diversification agglomeration does not reduce carbon emissions but instead increase carbon emissions.(2)Both industrial structure optimization and industrial spatial layout have spatiotemporal heterogeneous impacts on carbon emissions during the study period.(3) Under different levels of economic development, industrial transformation will have different impacts on carbon emissions. In the future, the Chinese government should increase efforts to promote technological progress and innovation, taking technological progress and independent innovation capabilities as the central link in promoting industrial transformation. Those findings not only provide certain environmental research reference for China's industrial economic development and transformation, but also provide a practical reference for carbon reduction in other developing countries that are undergoing economic transformation.

The power sector is one of the largest carbon emitters in China and faces nonlinear cost impacts from different emission reduction measures across regions with varying electricity demand characteristics. In this study, we analyze the effects and cost efficiency of supply-side and demand-side emission reduction pathways by classifying Chinese provinces into four categories. This is accomplished through integration of the Next Energy Modeling System for Optimization (NEMO) and the Low Emissions Analysis Platform (LEAP), i.e., LEAP-NEMO. Applying this method, our results show that urbanization will likely drive stable growth in residential electricity demand, while industrial development will vary regionally. Resource-rich regions require wind and solar energy as foundational methods to decarbonize their mix of electricity sources, whereas areas with limited natural resources need nuclear energy and alternative energy generation technologies to mitigate supply gaps. Furthermore, we find that delaying the emission peak year raises marginal carbon reduction costs and the cumulative cost per unit of carbon abatement. A 1.5% reduction in energy intensity is the most cost-effective for the majority of regions.

The tourism sector, being a major contributor to worldwide carbon emissions, is pivotal in the shift towards a low-carbon economy. This research utilizes systematic GMM models alongside mediation analysis to investigate the mechanisms by which digital trade (DT) influences tourism carbon emissions efficiency (TCEE). The results showed that an increase in digital trade activities leads to a significant reduction in tourism carbon emission inefficiency (ITCE), which indicates an improvement in tourism carbon emission efficiency. This negative relationship between DT and ITCE (indicating a positive effect on TCEE) is especially evident in the eastern regions. The DT affects tourism services on both the production and consumption sides, with diverse implications for TCEE. Additionally, the effects of DT on TCEE are notably moderated by factors such as industrial agglomeration and specific low-carbon pilot policies. The concentration of high-tech industries and the agglomeration of producer services amplify the adverse effects of DT and TCEE. Conversely, implementing low-carbon pilot policies enhances the potential benefits of DT and contributes to further reductions in carbon emissions. The enhancement of digital infrastructure and technological innovations in DT is all conducive to reducing TCEE. These findings offer several policy recommendations for managers seeking to promote green tourism development and the sustainable development of low-carbon industrial economies.

Spatial difference, dynamic evolution and influencing factors of carbon emission efficiency in China at the provincial level

Abstract The complexity of ozone chemistry makes it difficult to quantify the extent to which different national ozone reduction scenarios affect the country that implemented the strategy, neighboring countries, and the world. To better understand ozone sensitivity to national/regional emission scenarios, the zero-out method was applied for the anthropogenic emission of ozone precursors, i.e., nitrogen oxides (NO x ), in nine regions and three countries worldwide. In this study, ozone simulations were performed at a high global resolution of 56 km via the use of a nonhydrostatic icosahedral atmosphere model coupled with chemistry (NICAM-Chem). The model performance in predicting surface ozone was evaluated with ground-based measurements worldwide. The correlation was moderate to high, but both bias and uncertainty were high but remained within the ranges of values obtained from other global chemistry models. Experiments based on zero-out methods for assessing anthropogenic NO x emissions revealed that the domestic impacts of anthropogenic NO x emission reduction on ozone reduction were the largest in India (14 ppbv, regional and annual average) and China (11 ppbv, regional and annual average). The influence of anthropogenic NO x emission reduction in China on transboundary ozone concentrations was notable, with a reduction in ozone of 7 ppbv (regional and annual average) in Japan and even yielding ozone reductions in North America (1 ppbv, regional and annual average) and western Europe (1 ppbv, regional and annual average). Sensitivity experiments with a 20% reduction in anthropogenic NO x emissions were also conducted, and the results were generally consistent with those of previous studies. However, the results for a 20% reduction in anthropogenic NO x emissions partially differed from the results for a 100% reduction in anthropogenic NO x emissions because of the high nonlinearity of ozone chemistry. For example, in Japan, a 20% reduction in domestic NO x emissions resulted in a larger reduction in ozone levels than that obtained with a 20% reduction in Chinese NO x emissions. This indicates the inherent uncertainty resulting from experimental settings that assume a substantial reduction, such as a 100% decrease in the NO x flux. Understanding the impact of emission reduction in a given country on other countries is important for accelerating future international collaboration on ozone reduction for ensuring climate and human health.

Is digital finance green Considering digital blind spot and the human capital threshold in carbon emission reduction in China

China has made considerable effort to address methane emissions in the agricultural sector. This paper analyzes the trends in China’s agricultural methane emissions using national greenhouse gas inventory data from 1994 to 2021, identifies key emission sources and reviews relevant policies, while summarizing the practical challenges currently faced in mitigation efforts. The findings reveal that China’s agricultural methane emissions remain high. Although a turning point emerged in 2017, emissions rebounded slightly in 2021 with the recovery of pork production. Rice production, enteric fermentation and manure management are the key agricultural methane emission sources. China has made progress in reducing agricultural methane emissions by integrating climate change policies with green agricultural development initiatives. However, the implementation of these policies must overcome several challenges. The growing food demand will further intensify the pressure on methane reduction. Low adoption rates of existing technologies and limited development of innovative solutions hinder progress toward emission reduction targets. The measurement, reporting and verification (MRV) system remains inadequately developed. Inadequate policy support and financial incentives compromise the sustainability of current efforts. This paper proposes several pathways to promote agricultural methane reduction and support the transition to low-carbon agricultural development. These include strengthening the MRV system, enhancing policy and financial support for emission reduction, advancing research and development, establishing compensation mechanisms for emission reduction, encouraging low-carbon and healthy dietary habits among consumers and strengthening international cooperation.

The study investigates the effects of smart city pilot policy (SCPP) on energy-saving and emissions-reduction (ESER) in urban areas of China. Using smart pilot cities in three batches in China since 2012 as quasi-natural experimental subjects and the time-varying Difference-in-Differences (DID) method, the study reveals that the ESER ramifications stemming from the implementation of SCPP manifest themselves as follows: energy saving increased by 1.7%, emission decreased by 5.3%, and the effects continue to enhance over time. This conclusion is still robust in multi-dimensional situations such as the placebo test and propensity score matching with Difference-in-Differences (PSM-DID). In addition, the ESER effect of SCPP has a significant dynamic effect and spatial spillover effect. The mechanism analysis reveals that smart cities can achieve ESER through industrial restructuring (front-prevention), energy efficiency improvement (process control), and green technology innovation (end treatment). Further heterogeneity analysis indicates that ESER effects of SCPP are more significant in central cities, non-old industrial-based cities, and non-resource-based cities. The study demonstrates the significance of smart city construction in achieving ESER goals from the perspective of a low-carbon economy and provides valuable insights for the coordinated development of intelligent, energy-saving, low-carbon, and green cities in developing countries.

While the “Comprehensive Demonstration Policy for E-commerce in Rural Areas” has been widely acknowledged for stimulating rural economic vitality, its implications for carbon emissions remain underexplored and lack sufficient empirical evidence. Leveraging this policy as a quasi-natural experiment, this article employs a multi-period Difference-in-Differences strategy on a panel dataset of 2,132 Chinese counties to assess the carbon emission impacts of rural e-commerce expansion. Notably, the results show that: (1) The advancement of rural e-commerce has a significant carbon emission reduction effect. (2) Rural e-commerce has significantly narrowed the income gap between urban and rural areas, effectively promoted industrial structure optimization, and enhanced the level of digital infrastructure to facilitate carbon emission reduction. (3) The carbon reduction effect of rural e-commerce is particularly significant in areas with high industrial development level and high disposable income of rural residents. This article has broader implications for the digital-green transition paradigm, while offering actionable insights and evidence-based strategies to help developing economies to foster integrated rural development and environmental stewardship.

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Agriculture has become a major source of greenhouse gases in China. Agricultural carbon emission efficiency (AECC), as a key indicator of agricultural greening and sustainability, holds significant importance for advancing synergistic pollution reduction and carbon emission reduction in China and implementing the “dual carbon” strategy in China, also providing ideas for agricultural emission reduction in developing countries around the world. Taking 24 counties (cities/districts) in the Dabie Mountains, a typical traditional agricultural mountainous region in central China that is currently facing agricultural green transformation, as the research objects, this study constructed an AECC measurement index system, collected 2010–2022 data, used a super-efficiency SBM model with undesirable outputs under the CRS mode to measure AECC, analyzed its spatiotemporal evolution, and applied a BP neural network for dynamic prediction. Our results show the following: (1) during the study period, Dabie Mountains’ overall AECC was low with fluctuations, showing significant but low-dispersion spatial differences; (2) temporally, the overall AECC showed an upward trend over the years, though the distribution pattern remained relatively dispersed; (3) spatially, a prominent “core-periphery” structure exists, with high-value areas showing a trend of spreading from block-like to patch-like, while overall spatial disparities converged; (4) in the coming years, the AECC in the Dabie Mountains will rise significantly with steady growth and shrinking spatial differences, and the spatial pattern will evolve into a “bipolar → tripolar → multipolar” structure.

As key supervised entities for carbon emissions, the effective carbon reduction of industrial enterprises is crucial to the achievement of the “Dual Carbon” goal. With the arrival of the digital era, digital transformation has become an inevitable path for the high-quality development of all industries, providing new ideas for carbon emission reduction in industrial enterprises. This paper aims to explore the necessity of carbon emission reduction in China’s industrial sector and the importance of digital transformation for achieving carbon emission reduction, analyze the impact of digital transformation of industrial enterprises on carbon emission reduction, and explore effective paths for digital transformation to reduce carbon emissions. It is of great significance for the coordinated development of low-carbon transformation and digital transformation of industrial enterprises.

Application of the distributed photovoltaic systems towards oil-gas field and its implications for carbon emission reduction in China: A review on current and novel perspective on engineering approaches

Logistics hub policies and carbon emission efficiency: insights into emission reduction in China

Synergistic air pollution and CO2 emission reduction in China's iron and steel industry based on real-time monitoring data.

Voluntary or mandatory? Convergence and coexistence of “dual carbon” markets: A system dynamics analysis based on multi-agent evolutionary games

Under the "dual carbon" goal and the strategic layout of "digital China，" digital technology， as a new green production factor， has great significance for the smooth promotion of the "double carbon" goal. Based on the data of 281 prefecture-level cities in China from 2011 to 2021， this paper systematically analyzes the current status of carbon emission reduction in China and the form and characteristics of the spatial correlation network of digital technology by using UCINNET software and an econometric model. Moreover， it explores the influence and mechanism of the spatial correlation network of digital technology on carbon emission reduction. The results follow： ① China's carbon emissions show an increasing trend through time， and the spatial distribution changes from a point-zone distribution to core urban agglomeration. The spatial correlation network of digital technology presents an obvious network development pattern as a whole， and the trend is good. ② During the sample period， the spatial correlation network of digital technology has a significant positive promotion effect on carbon emission reduction， and this conclusion remains valid after robustness testing and endogenous treatment. ③ The differences in geographical location and urban agglomeration types lead to heterogeneity in the emission reduction effect of the spatial correlation network of digital technology. ④ The spatial correlation network of digital technology can achieve emission reduction pathways by promoting the transformation and upgrading of industrial structure and improving energy efficiency. ⑤ Public environmental supervision plays a strong role in strengthening the emission reduction effect of the digital technology spatial correlation network.

The development of digital rural areas has important theoretical and practical implications for promoting agricultural carbon emission reduction in China. Based on the panel data of 29 provinces， cities， and autonomous regions in China （with data for Hong Kong， Macau， Taiwan， Tibet， and Hainan temporarily unavailable） from 2011 to 2021， the spatial spillover effect of digital rural development on agricultural carbon emission reduction was tested using the Spatial Durbin Model. The study produced several interesting results： ① The process of digital rural development and the changes in agricultural carbon emissions are highly correlated in space. ② Digital rural development has significant spatial spillover characteristics in suppressing agricultural carbon emissions. The development of digital rural areas not only effectively suppresses carbon emissions in the region but also has a positive inhibitory effect on the carbon emissions of nearby regions. ③ Digital rural development can lower the level of agricultural carbon emissions through the pathway of promoting green technology innovation. ④ The heterogeneity test results show that the inhibitory effect of digital rural development on agricultural carbon emissions in the central region is more significant than the effect in the eastern and western regions. ⑤ The spatial spillover effect of digital rural development first increases and then decreases as the geographic distance increases and reaches its maximum value at a distance of 500 km.