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This study investigates the carbon compensation mechanism as a tool to promote coordinated economic and environmental development in China's Jing-Jin-Ji region (Beijing, Tianjin, and Hebei). A novel approach for calculating carbon compensation cost that integrate emission responsibility as well as carbon abatement cost through a bi-level programming model is proposed. Shared producer and consumer responsibility is established for carbon emissions under the multi-regional input-output model. Marginal abatement costs of Beijing, Tianjin, and Hebei are further calculated through the input-output and linear programming method. Results highlight that the emission responsibility allocation method significantly affects the inter-regional carbon compensation amount. The production-based approach leads to a 77% reduction of carbon compensation amount from Beijing to Hebei, and a 170% overestimation from Tianjin to Hebei compared with the shared responsibility approach in 2060. The optimal carbon compensation unit cost ranges from 1539 to 6438 yuan/ton when the carbon reduction ratio ranges from 10% to 20%. Beijing would compensate Hebei 3.56 and 29.74 billion yuan for achieving 10% and 20% emission reduction, respectively. Similarly, Tianjin's compensation for Hebei would be 0.23 and 1.87 billion yuan in the two scenarios. Results further show that implementing the proposed carbon compensation mechanism can reduce total abatement cost by 43% and 84% in Jing-Jin-Ji under the two scenarios. The methods and results of this paper could help inform future carbon compensation implementation in China and other countries. • Develop a bi-level programming model to determine optimal carbon compensation cost. • Consider emission responsibility and carbon abatement cost in Jing-Jin-Ji. • Resulting mechanism reduces abatement cost by 43% for 10% emission reduction. • Production-based allocation underestimates carbon compensation amount by 62%. • Optimal carbon compensation unit cost changes with marginal abatement cost. [ABSTRACT FROM AUTHOR]

Beijing-Tianjin-Hebei metropolitan area is a significant carbon emission center. The region's early achievement of peak carbon targets is critical to the nation's achievement of peak carbon targets. In this paper, it is proposed to use different orders of grey models to classify into three scenarios. Based on three scenarios, the grey multivariate convolutional model with new information priority accumulation is adopted to predict carbon emissions in the Beijing-Tianjin-Hebei region and select the scenario suitable for local development. The results show that: (1) The Beijing region has already achieved peak carbon, the Tianjin region may not reach its peak carbon target by 2030, and the Hebei region is expected to reach its peak carbon target by 2030. (2) The high rate of carbon emission reduction scenario will greatly improve the air quality of Beijing. The low-speed growth carbon emission scenario is more in line with the future development of Tianjin city. The low-rate carbon reduction scenario is more in line with the synergistic governance of pollution reduction and carbon reduction in Hebei Province. (3) Beijing's population policy in the most recent years has been conducive to improving the local environment. Tianjin's medium-term population policy is more in line with the local area. Hebei's medium-term industrial structure reform is favorable to local development. • Grey correlation analysis is used to analyze the factors affected carbon emissions in a region. • The factors with high correlation are predicted by using grey prediction models of different orders. • The high rate of carbon emission reduction scenario will greatly improve the air quality of Beijing. [ABSTRACT FROM AUTHOR]

Even though renewable energy development has gained momentum in China, thermal power generation still accounts for approximately 70% of the county's total power generation serving as the major source of carbon dioxide (CO 2) emissions in China. Facing the challenges of meeting 2030 peak target of CO 2 emission and realizing the coordinated development of thermal power generation in Beijing-Tianjin-Hebei region, this paper applies generalized Divisia Index Method (GDIM) to decompose the dynamics in the relevant CO 2 emission. The effects of five factors including electricity demand, energy consumption, technology, energy efficiency and energy-mix are considered. The decomposition suggests that electricity demand is the primary factor driving the CO 2 emission up, whereas technology effect decreases CO 2 emission the most. Given the significant roles of technology, energy-mix and energy efficiency in CO 2 emissions reduction, seven scenarios are designed to identify the optimal coordinated development pathway for thermal power generation in Beijing-Tianjin-Hebei region. Through upgrading energy structure and/or enhancing energy efficiency, the thermal power generation in Beijing-Tianjin-Hebei region can achieve coordinated development and realize the 2030 peak target under four scenarios. The detailed development pathways for CO 2 emissions and specific policy implications for Beijing, Tianjin and Hebei are provided to further govern CO 2 emissions and maintain sustainable development. • Proposed a five-factor Generalized Divisia Index Model (GDIM) for CO 2 emission analysis. • Analyzed the CO 2 from thermal power generation in China's Beijing-Tianjin-Hebei region. • Electricity demand and technology contributed the most to the positive and negative changes of CO 2 , respectively. • Designed seven thermal generation development scenarios to study the CO 2 change until 2030. • The 2030 CO 2 peak target can be achieved under four scenarios. [ABSTRACT FROM AUTHOR]

Promoting the coupled development of water, energy, and food (WEF) subsystems is a critical step to enhance synergies and increase efficiencies in the WEF nexus. However, the evolution and obstacles of coupled development are largely ignored. This study developed a framework dividing links in the nexus to select indicators and integrated models for the degree of coordination and obstacle diagnosis to explore the coupled development of the WEF nexus from 2000 to 2020 in the water-scarce megacities of Beijing and Tianjin. The results show that the average coordination degree of the WEF nexus in Beijing (0.315) and Tianjin (0.317) is at a low level, indicating a limited interaction between the WEF subsystems, while the coordinated development degree of the WEF nexus is increasing. The order degree of the WEF subsystems shows a two-level hierarchical structure, indicating that both similarities and differences are included in place-specific characteristics. Furthermore, obstacle factors are identified from water and energy subsystems, in which environmental water use (W3) and the energy consumption per gross domestic production unit (E4) played the most significant roles and require a higher priority in policy response. The results in this paper complement obstacle factor analysis in WEF nexus practice, and provide operational indicators for nexus governance. [Display omitted] • Linkages are divided into one-, two-, and three-resource scales. • The number of related official documents is used to define the weight of subsystems. • The water subsystem dominated the coupled development of the water-energy-food nexus. • The order degree of subsystems show a two-level hierarchical structure. • Key obstacle factors are identified from water and energy subsystems. [ABSTRACT FROM AUTHOR]

High-speed rail (HSR) is considered a safe, fast, comfortable and ecological mode of transportation, which has profoundly changed the way passengers travel. However, how green it is and how it affects county air quality remains to be investigated. Based on panel data of 51 counties in southern Beijing-Tianjin-Hebei (Jing-Jin-Ji) from 2014 to 2018, Fixed Effect Model (FEM) and Propensity-Score-Matching and Difference-in-Difference (PSM-DID) methods are used to study the impact of HSR on air quality in counties. FEM is used as the preliminary regression and PSM-DID model is used to avoid the endogenous problem and selection bias. Research shows that HSR has direct and indirect effects on air quality in counties. HSR directly affects it by changing the way of long-distance travel. Furthermore, HSR indirectly affects it by promoting the regional economy, which affects air quality through scale effects, innovation effects and structural effects caused by regional economy development. The results show that the operation of the HSR reduces the air quality index (AQI) by 11.2% and the concentrations of the three major pollutants index, including PM2.5 by 10.1%, PM10 by 14.8% and O 3 by 11%. We also find that HSR brings at least 4% more environmental benefits on the side closer to Beijing and Tianjin in southern Jing-Jin-Ji than the farther side. Among the two sides, the closer side has more government concern and economic activities. In addition, we conducted further robustness tests and concluded that HSR improves air quality in counties. This paper provides some policy implications for improving county environmental quality and planning of HSR stations. • The direct and indirect impacts of HSR on air quality are considered. • Two models are used to improve the robustness of empirical analysis results. • The results indicate that HSR has positive impacts on air quality of counties. • The impact of HSR on air quality in counties shows regional heterogeneity. [ABSTRACT FROM AUTHOR]

The main purpose of this paper is to build an objective and effective environmental performance evaluation model of air pollution control. Based on the severe air polluted region in China, that is Beijing-Tianjin-Hebei region, this evaluation model consists of four parts, including economic benefits, public service, government management and development potential, and uses the balanced scorecard theory. The weights of the indexes are measured by comprehensive evaluation method, which combined entropy weight method and analytic hierarchy process (AHP). To test the applicability of the evaluation method to different stages, back propagation (BP) neural network is introduced to simulate air pollution control in the future. The results reveal that the environmental performance of air pollution control in Beijing had an upward trend during 2010–2016, and the trend would continue in the next five years. The environmental performance of Tianjin continuously increased, especially from 2014 to 2016. Tianjin has great potential of air pollution control in the future. The environmental performance of air pollution control in Hebei fluctuated from 2010 to 2016 and it dropped to the lowest level in 2015, which mainly due to the large increase in number of days with air quality levelⅡor above compared with 2014 and the nonsignificant growth in the amount of expenditure on atmospheric prevention and control, the amount of investment in the control of industrial pollution sources and the number of law enforcement personnel. Moreover, the environmental performance of air pollution control closely related with industrial structure, especially with the proportion of the tertiary industry. The upgrading of urban industrial structure and the coordinated development of green industry should be implemented to restructure the environmental transformation in air-polluted region. Image 1000 • The traditional Balanced Scorecard is revised and applied into the environmental performance evaluation. • The effective control of vehicle emission directly determines the air quality of Beijing. • A fundamental improvement in air quality in Hebei requires a large amount of environmental investment. • The environmental law enforcement is an important guarantee for air quality improvement of Tianjin. [ABSTRACT FROM AUTHOR]

Beijing-Tianjin-Hebei (BTH) in China is a key metropolitan area with high development imbalance and serious environment pollution spillovers. While foreign direct investment (FDI) only accounts for 5% of local GDP in this region, Beijing direct investment (BDI) to its two neighbors starts to play an important role in promoting integrated development and tackling regional environmental problems ever since 2014. In this paper, we construct a unique dataset on 157 county-level administrative units in the BTH area as a host of BDI, and test if BDI has resulted in a pollution haven effect or a pollution halo effect in the industrial sector. Results show that BDI has been conducive to reducing industrial pollution emissions in the host administrative units, a pollution halo effect and win-win situation for both Beijing and its neighbors. However, FDI is estimated to have a pollution haven effect for certain industrial pollutants or insignificant. Our results stand with several robustness checks, heterogeneity analysis and a further test on reverse causality, and point to a new avenue for regional environment improvement via environmental friendly and sustainable industrial relocation. [ABSTRACT FROM AUTHOR]