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Resource-based cities generally face the dual pressures of ecological damage and high carbon emissions. Taking the National Sustainable Development Plan for Resource-Based Cities (NSDP) issued in China as a quasi-natural experiment, this paper for the first time, uses the difference-in-difference method to test the coordinated effect of green expansion and carbon reduction brought by NSDP at the county level using rich remote sensing data. The results show that NSDP has significantly promoted the ecological quality improvement and CO 2 emission mitigation in resource-based cities, and the above coordinated benefits mainly occur in energy, mature, declining, northeastern, and municipal resource-based cities. Through the mechanism analysis, we find that NSDP mainly works by promoting the transformation of industry sector to agriculture, animal husbandry, accommodation and catering, finance, and environment management sectors, which are reflected in output, employment, product yield, land type and land transaction area. Further discussion on the tertiary industry suggests that developing tourism, easing financing constraint and strengthening environment regulation, are the key channels to borne fruit in green expansion and carbon reduction. • Analysis of placed-based policy on resource at the county-level. • Coordinated effects of green expansion and carbon reduction are tested. • Key areas of policy effects are identified. • Industrial structure transformation and its related mechanisms are discussed. [ABSTRACT FROM AUTHOR]

This paper analyzes the overall and time-varying efficiency of China's carbon market, which is crucial for carbon risk management and policymaking. Due to the severe illiquidity problems other pilots face, we first select Shenzhen, Guangdong, and Hubei pilots out of the eight carbon pilots for our study based on the statistical analysis. We then test the overall efficiency of the markets using the LM, CD, and Wild-Bootstrap variance ratio test. The sliding window method is combined with the above three variance ratio test methods to validate the time-varying efficiency. The results prove that the overall efficiency of the three carbon pilots has not yet reached a weak form. And we observe that the short-term efficiency is time-varying and may be weak-form. The study further found Hubei to be the most efficient carbon pilot, followed by Guangdong and Shenzhen. Finally, this paper conducts a qualitative analysis on the low efficiency from five aspects namely carbon trading rules, market liquidity, price volatility, trading volume, and types of trading products. Several conclusions and recommendations are proposed for policymakers and investors. • Sliding window method is combined with a series of variance ratio test methods. • The overall and time-varying efficiency of China's carbon market is tested. • China's carbon market has not reached weak-form efficiency. • Hubei is the most efficient carbon pilot. • Reasons for low efficiency are analyzed. [ABSTRACT FROM AUTHOR]

Recommended management practices (RMPs, e.g., manuring, no-tillage, crop residue return) can increase soil organic carbon (SOC), reduce greenhouse gas emissions, and maintain soil health in croplands. However, there is no consensus on how RMPs affect the SOC storage potential of cropland soils for climate change mitigation. Here, based on 2301 comparisons from 158 peer-reviewed papers, a meta-analysis was conducted to explore management-induced SOC stock changes and their variations under different conditions. The results show that SOC stocks in the 0–20 cm layer were increased by 31.8% when chemical fertilization combined with manure application was compared with no fertilizer; 9.98% when no-tillage was compared with plow tillage; and 10.84% when straw return was compared with removal. The RMPs favorably increased SOC stock in arid areas, and in alkaline and fine-textured soils. Initial SOC, carbon-nitrogen ratio, and experimental duration could also affect SOC storage. Compared with the initial SOC stock, RMPs increased the SOC sequestration potential by 2.6–4.5% in the 0–20 cm soil depth, indicating that these practices can help China achieve targets to increase SOC by 4.0‰. Hence, it is essential to implement RMPs for climate change mitigation and soil fertility improvement. • RMPs can increase SOC stock and mitigate climate change. • RMPs-induced SOC changes depend on local environmental conditions. • The SOC storage potentials were decreased with the increase of soil depth. • RMPs can achieve targets to increase SOC by 4.0‰ in Chinese croplands. [ABSTRACT FROM AUTHOR]

To abate the severe air pollution, the Chinese government released the Action Plan of Air Pollution Prevention and Control (APAPPC) in 2013. This paper regards the APAPPC as a quasi-experiment and uses the DID method to investigate the impact of environmental regulation on the growth of green total-factor productivity of China's industries. This article employs the non-radial directional distance function (NDDF) and the global Malmquist index to measure the total-factor carbon productivity of China's industries. Further regressions suggest that the implementation of the APAPPC has significantly promoted the growth of the total-factor carbon productivity in the air pollution-intensive industries, and its marginal effect has steadily increased with time. This result is still valid after using a series of counterfactual tests and robustness tests. The further mechanism study shows that the APAPPC has significantly promoted R&D investment, especially in instruments and equipment, which has effectively promoted technical efficiency and technological advancement. It indicates that stringent and well-designed environmental regulations should lead to a "win-win" situation of environmental improvement and economic development by encouraging enterprises to upgrade their technology and equipment. • This paper uses a typical case in China to demonstrate the porter's hypothesis. • This paper uses the DEA method to measure the total-factor carbon productivity of China's industries. • The Action Plan of Air Pollution Prevention and Control in China has significantly promoted the growth of total-factor carbon productivity. • The regulation promotes productivity by propelling enterprises to increase R&D investment and update their technical equipment. [ABSTRACT FROM AUTHOR]

Based on the gross trade accounting method and WIOD data, this paper quantifies the global carbon transfer from 2000 to 2014. The social network analysis and temporal exponential random graph model (TERGM) are employed to investigate the structural change and influencing factors of global carbon transfer network from a global value chains (GVCs) perspective. Results show that the deepening of the GVC division connection has enhanced the relations in global carbon transfer network, and the low reciprocity and high disassortativity lie in the difference in GVC division positions among economies. Block model analysis manifests that Plate Ⅱ acts as the engine plate in the network which consists of China and the other four economies. The GVC division connection and relative GVC division position significantly facilitate the formation of carbon emission transfer relations. Moreover, economies' attribute effects and endogenous network structure effects are non-negligible important determinants of network formation. [Display omitted] • Structural change of global carbon transfer network derives from the GVC division. • Global carbon transfer network has low reciprocity and high disassortativity. • Plate Ⅱ composed of China and the other four economies is the engine plate. • Temporal exponential random graph model is used to analyze the influencing factors. • GVC division connection and relative division position boot the network formation. [ABSTRACT FROM AUTHOR]

This study addresses the question of why industrial restructuring towards light industries or services sometimes fails to achieve carbon emission mitigation goals. By employing a new perspective of dividing industry segments into emission-dominating and non-emission-dominating ones based on Logarithmic Mean Divisia Index (LMDI) decomposition method, this paper analyses city-level carbon dioxide emission reduction performance under three distinctive industrial restructuring directions. Results indicate that carbon dioxide emission dominating segments are relatively fixed across cities, regardless of the various city types in China. The key point to achieve emission reduction through industrial restructuring is to identify and control the emission-dominating segments, instead of economic-leading ones. Besides, emission reduction performance of industrial restructuring from emission-dominating industry segments to services is better than that to non-emission-dominating ones. More importantly, industrial restructuring not involving output scale controlling of emission-dominating segments, or that recklessly rushing towards services are likely to fail the emission mitigation goal. This paper presents a strong international reference that merits cities facing policy hesitation over industrial restructuring directions while in pursuit of emission mitigation. It suggests that cities first focus on identifying the carbon dioxide dominating segments, of which the output scale should be controlled. For cities whose emission-dominating segments are not economic-leading ones, it is necessary to carry out industrial restructuring towards services or non-emission-dominating segments; while for cities heavily dependent on emission-dominating segments, energy efficiency should also be improved. • Identifying CO 2 -dominating segments at city level with LMDI method. • Comparing CO 2 mitigation effects among different industrial restructuring directions. • Providing feasible restructuring paths for distinct cities to reduce CO 2 emissions. [ABSTRACT FROM AUTHOR]

Soil organic carbon (SOC) is of great importance in the global carbon cycle. Distribution patterns of SOC in various regions of China constitute a nation-wide baseline for studies on soil carbon changes. This paper presents an integrated and multi-level study on SOC stock patterns of China, and presents baseline SOC stock estimates by great administrative regions, river watersheds, soil type regions and ecosystem. The assignment is done by means of a recently completed 1: 1,000,000 scale soil database of China, which is the most detailed and reliable one in China at the present time. SOC densities of 7292 soil profiles collected across China in the middle of the 1980s were calculated and then linked to corresponding polygons in a digital soil map, resulting in a SOC Density Map of China on a 1: 1,000,000 scale, and a 1km×1km grid map. Corresponding maps of administrative regions, river watersheds, soil types (ST), and ecosystems in China were also prepared with an identical resolution and coordinate control points, allowing GIS analyses. Results show that soils in China cover an area of 9.281×106 km2 in total, with a total SOC stock of 89.14Pg (1Pg=1015 g) and a mean SOC density of 96.0tC/ha. Confidence limits of the SOC stock and density in China are estimated as [89.23Pg, 89.08Pg] and [96.143tC/ha, 95.981tC/ha] at 95% probability, respectively. The largest total SOC stock (23.60Pg) is found in South-west China while the highest mean SOC density (181.9tC/ha) is found in north-east China. The total SOC stock and the mean SOC density in the Yangtze river watershed are 21.05Pg and 120.0tC/ha, respectively, while the corresponding figures in theYellow river watershed are 8.46Pg and 104.3tC/ha, respectively. The highest total SOC stocks are found in Inceptisols (34.39Pg) with SOC density of 102.8tC/ha. The lowest and highest mean SOC densities are found on Entisols (28.1tC/ha), and on Histosols (994.728.1tC/ha), repectively. Finally, the total SOC stock in shrub and forest ecosystem classes are 25.55 and 21.50Pg, respectively; the highest mean SOC density (209.9tC/ha) was recorded in the wetland ecosystem class and the lowest (29.0tC/ha) in the desert ecosystem class. Among five forest ecosystem types, Evergreen conifer forest stores the highest SOC stock (6.81Pg), and Deciduous conifer forest shows the highest SOC density (225.9tC/ha). Figures of SOC stocks stratified by Administrative regions, river watersheds, soil types and ecosystem types presented in the study may constitute national-wide baseline for studies of SOC stock changes in various regions in the future. [Copyright &y& Elsevier]

This paper reports the annual carbon (C) balance of China''s forests during 1901–2001 estimated using the Integrated Terrestrial Ecosystem C-budget model (InTEC). Annual carbon source and sink distributions are simulated for the same period using various spatial datasets including land cover and leaf area index (LAI) obtained from remote sensing, soil texture, climate, forest age, and nitrogen deposition. During 1901–1949, China''s forests were a source of 21.0±7.8TgCyr−1 due to disturbances (human activities). Its size increased to 122.3±25.3TgCyr−1 during 1950–1987 due to intensified human activities in the late 1950s, early 1960s, 1970s and early 1980s. The forests became large sinks of 176.7±44.8TgCyr−1 during 1988–2001, owing to large-scale plantation and forest regrowth in previously disturbed areas as well as growth stimulation by nondisturbance factors such as climatic warming, atmospheric CO2 fertilization, and N deposition. From 1901 to 2001, China''s forests were a small carbon source of 3.32PgC, about 32.9±22.3TgCyr−1. The overall C balance in biomass from InTEC generally agrees with previous results derived from forest inventories of China''s forests. InTEC results also include C stock variation in soils and are therefore more comprehensive than previous results. The uncertainty in InTEC results is still large, but it can be reduced if a detailed forest age map becomes available. [Copyright &y& Elsevier]

This paper examines the effects of China's foreign direct investment (FDI) on the carbon emissions of its domestic economy and the Belt and Road countries (BRCs). Total inward FDI into China as a host country shows a pollution reducing effect in the western and eastern regions while that in the central region remains unchanged. But China's outward FDI particularly from its eastern region reduces pollution in China. This suggests that China could be exporting carbon emissions via its FDI in the BRCs. The effects on BRCs' pollution from China's FDI is however different depending on the country's level of development. China's FDI was found to have no effect on high and upper middle income BRCs; a decreasing effect on low income BRCs; and an increasing effect on lower middle income BRCs. Evidence shows that China needs to consider a mix of policies to manage its inward and outward FDI to ensure its move to a low carbon economy benefits its own regional development and the BRCs by not contributing to increased carbon emissions. • FDI into China does not reduce pollution in all its regions. • China's FDI to its BRCs has mixed effects on their pollution. • China's low carbon commitments for its FDI strategies needs a rethink. [ABSTRACT FROM AUTHOR]

The difficulty for developing regions to fulfil their industrial carbon emission control target commitments is to take into account the socio-economic and environmental governance. It is necessary not only to accelerate the process of industrialization, but also to rationally allocate carbon emission reduction tasks. This paper takes the northwestern provinces of China as a case study based on the calculation of the industrial carbon emissions of each province from 2006 to 2017. The Gini coefficients such as the industrial economy contribution coefficient, industrial employment contribution coefficient, and carbon carrying coefficient are constructed to evaluate the equity of regional industrial carbon emissions. The results show that the carbon pressure index in the northwestern provinces is increasing, carbon emissions are growing much faster than the carbon carrying capacity, and the differences among the provinces are obvious. The industrial economy contribution, the industrial employment contribution, and the carbon carrying Gini coefficients fluctuate significantly. Carbon emissions inequity has not been suppressed with the socio-economic development, and the " Matthew effect " is even more prominent. Evaluating the equity of carbon emissions allocation will help to rationally allocate carbon emission reduction tasks among provinces and achieve national emission reduction targets. Accordingly, recommendations are provided for formulating a differentiated carbon management policy, strengthening provincial cooperation, determining the provincial ecological function position, and improving the equity of regional carbon emissions allocation. • The inequity of the carbon emissions allocation has intensified and presents " Matthew effect ". • The trend of increasing carbon emission is not consistent with emission reduction targets. • The equity evaluation model was constructed by using the Gini coefficient. • Recommending regional compensation mechanisms and differentiated carbon management. [ABSTRACT FROM AUTHOR]

Considering the enlarging inter-provincial disparities in China as regards carbon emissions and carbon intensity (carbon emissions per unit gross domestic product), this paper is the first study to investigate the inter-provincial carbon imbalance by constructing and employing the Kaya-Zenga index. We use China's panel data of provincial-level carbon emissions over 1995–2016 to quantitatively measure the levels of inter-provincial imbalance and polarization in carbon emissions and carbon intensity. Further, we decompose the Kaya-Zenga index into different contributing factors both regionally and structurally and perform a scenario analysis to identify the corresponding regionally differentiated countermeasures regarding carbon emission reduction. The results show that the imbalance in carbon emissions is mainly caused by imbalances in population scale and income level, while the imbalance in carbon intensity predominantly results from imbalances in energy efficiency and energy mix. In addition, for heavy manufacturing provinces, the respective emission-reduction strategy should aim at lowering energy intensity through local technology improvement and inter-regional technology transfer. For light manufacturing and high technology provinces, carbon emission reduction is harder to be achieved; however, a mix of policies of improving energy efficiency, optimizing energy mix, and industrial upgrading should be implemented. The results of the scenario analysis indicate that reducing imbalance in carbon intensity under different scenarios can lead to a substantial reduction in carbon emissions (up to 10%). • We investigate the inter-provincial carbon imbalance within China. • We construct the Kaya-Zenga index and decompose the index into four contributors. • We use a panel data set of 30 provincial-level regions in China over 1995–2016. • Carbon imbalance is mainly caused by imbalances in population and energy efficiency. • Reducing intra-group imbalance in carbon intensity can abate carbon emissions. [ABSTRACT FROM AUTHOR]

Using the social network analysis method, this paper explores the characteristics of the spatial association network structure of China's provincial transportation carbon emissions from 2005 to 2015 and its driving factors. The results are as follows: (1) The spatial association of China's provincial transportation carbon emissions exhibits an intuitive network structure. The degree of closeness which were 0.2253 and 0.2333 in 2005 and 2015 respectively shows an increasing trend on the whole. However, it hit the bottom in 2011, reaching a minimum of 0.2230, which is the "low closeness degree inflection point". (2) The spatial association network presents a significant "core-edge" distribution pattern. Specifically, in the central and eastern regions of China, Henan and Jiangsu have degrees of up to 58.621 and 44.828, which are at the network center. However, some remote regions, like Jilin and Hainan, have degrees of less than 20.000, which are marginalized. (3) The geographical adjacency, the expansion of the difference in R&D investment, and the narrowing of the difference in economic development promote the formation of the interprovincial spatial association. Therefore, in the process of controlling carbon emissions from transportation, the government should focus on the provinces at the network center and pay attention to the impact of the R&D investment on the spatial association of transportation carbon emissions. • The evolution trend of the spatial association network structure is analyzed. • The "core-edge" distribution of the spatial association network is described. • "Henan is a key governance province" in this study. • "Reducing the R&D investment difference between provinces" is proposed. [ABSTRACT FROM AUTHOR]