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Air pollution poses a grave threat to human health and everyday life. Accurate air-quality prediction plays a crucial role in effectively preventing and controlling air pollution. A multi-graph spatial-temporal attention network is proposed to predict the air quality in a given area by analyzing the interconnections between stations and the individual characteristics of each station. Firstly, this paper constructs multi-scale spatial-temporal graphs from spatial and temporal perspectives to effectively capture the interconnections between stations, thereby comprehensively understanding the spatial-temporal relationships among them. Secondly, incorporating the nonlinear temporal correlation of station data, this paper proposes a temporal multi-graph attention-fusion module to integrate information from both neighboring stations and the station itself. Finally, predictions are made using a spatial-temporal graph network. The experiments in this paper were based on air-quality data from Beijing and Tianjin, and the following experimental results were obtained. (1) The proposed model outperforms the baselines significantly in both single-step and multi-step prediction tasks. (2) The ablation study confirms that the graph constructed in this paper contributes to improving the performance of the model. (3) Comparing the performance of attention components, the proposed attention mechanism exhibits better performance than other attention mechanisms. [ABSTRACT FROM AUTHOR]

The Chinese government aims to balance employment stabilization and emissions reduction when it initiates an emissions trading scheme (ETS) to control carbon emissions. However, the policymakers should not neglect the role of imperfectly competitive market structure and market power from incumbent firms. In view of this, classical framework of Berman and Bui's (2001) is extended in this paper to clarify the theoretical mechanism of employment effect of the ETS considering firm-level market power. In addition, based on the firm-level panel data from 2008 to 2019 of China, the employment effect of each pilot ETS is measured with the method of difference-in-difference-in-differences. Then a moderating effect model is established to verify the role of firm-level market power on the heterogeneous employment effect among the pilot ETSs. Moreover, the employment effect is further decomposed to evaluate the influential mechanism from the perspective of firms' strategic behavior. It is found that there is negative employment effect of China's ETS policy, due to the significant moderating role of firm-level market power. This decrease in labor demand is mainly dominated by a negative output effect rather than a positive substitution effect because strategic allowance sellers with stronger market power tend to hire fewer employees to reduce carbon emissions by controlling production scale. However, the heterogeneity of policy effects resulted by market structure is also identified in different pilot regions. Employment dividend has been found in Beijing and Tianjin where strategic allowance buyers manipulate the carbon market and hire more employees to consolidate their market power. Therefore, policymakers should improve the design of the ETS to overcome the adverse employment effect duo to the region-specific market structure. [ABSTRACT FROM AUTHOR]

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]

Currently, ozone pollution is one of the key environmental concerns, and to provide more effective strategies for ozone control, this paper proposes the use of the Geostationary Environmental Monitoring Spectrometer (GEMS) in conjunction with MAX-DOAS for observations and ozone sensitivity analysis. Compared to traditional polar-orbiting satellites, GEMS, launched by South Korea in 2019, offers superior spatiotemporal resolution. However, there is a lack of ground validation for GEMS data related to ozone and its precursors. In this study, we conducted validation in the Jing-Jin-Ji (Beijing-Tianjin-Hebei) region using two typical MAX-DOAS sites and the China National Environmental Monitoring Center (CNEMC) sites, confirming the accuracy of GEMS data. Analysis of the seasonal horizontal distribution results from GEMS and vertical distribution results from MAX-DOAS in 2022 reveals that the concentrations of NO 2 , HCHO, O 3 , and ozone sensitivity not only display seasonality and regional variations but also exhibit distinct characteristics at different altitudes and times, influenced by local climatic conditions, human activities, and topography. When formulating ozone control policies, it becomes imperative to consider factors such as time, regional characteristics, and seasonality. Comparisons between daily results from TROPOMI and GEMS indicate that polar-orbiting satellites may overlook high-pollution periods within a single day, and their measurements may not provide a comprehensive representation of an entire day's data. Consequently, relying solely on polar-orbiting satellite data for shaping ozone prevention and control policies may inadvertently encourage ozone formation during specific time periods, rendering these policies ineffective. Therefore, leveraging GEMS is essential for the development of comprehensive, around-the-clock ozone control policies. Finally, we used monitoring data from Beijing on October 6, 2022, to illustrate how the combination of GEMS and MAX-DOAS enables three-dimensional monitoring of pollutant transport processes on an hourly scale. [Display omitted] • Validation of the accuracy of ozone and its precursor data from GEMS. • Analysis of hourly ozone sensitivity level distribution using GEMS. • Limitations of polar orbit satellites in O 3 sensitivity analysis compared to GEMS. • Observation of the transport of pollutants combining GEMS and MAX-DOAS. [ABSTRACT FROM AUTHOR]

• Coordination among subsystems is key to improving urban resilience. • There is a large gap between the UR of Hebei Province and of Beijing-Tianjin. • The CCD of the urban resilience subsystem is trending upward but growing slowly. • The degree of spatial correlation of subsystems CCD in BTHUA is weak. Building resilient cities is a novel concept for dealing with risk crises and achieving sustainable urban development in modern times. This paper utilized data from the Beijing-Tianjin-Hebei urban agglomeration (BTHUA) spanning from 2009 to 2019, along with the CRITIC-Entropy weight method, coupling coordination degree (CCD) model and spatial correlation analysis to measure urban resilience and investigate subsystem coupling coordination relationships while considering spatial clustering characteristics. The results indicate that: (1) Spatially, there is a significant gap between the UR index of cities in Hebei Province and that of Beijing-Tianjin, with a "Beijing-Tianjin dual-core driven" trend. Regarding temporal evolution, the growth trend of the UR index is consistent with that of the subsystem resilience index. (2) In general, the CCD of the urban resilience subsystem is slowly trending upwards, with the overall CCD level of BTHUA ranging from primary coordination to moderate coordination. (3) The degree of spatial correlation of subsystem CCD in BTHUA is weak, and more cities exhibit heterogeneous agglomeration. These findings provide valuable inspiration and reference for resilient city construction and coordinated regional development to a certain extent. [ABSTRACT FROM AUTHOR]