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A good risk warning model is an effective way to guarantee the stable operation of the carbon market and exert its emission reduction function. This paper takes the China's pilot carbon market as the research object and measures the carbon market risk by ARMA-GARCH-VaR. Then, influential factors are selected as non-market characteristics from the perspective of causality and incorporated into the risk warning model, and SMOTE and SMOTEENN are introduced to deal with the unbalanced samples. Results show that (1) The risk fluctuations of Beijing and Shenzhen carbon market are large, and the risk fluctuations of Guangdong carbon market are relatively smooth in the early period and larger in the recent period. (2) Air quality, average daily temperature, CSI 300, power coal, natural gas, European carbon market, exchange rate, and Baidu index are all important factors in the risk volatility of carbon market. (3) The Classification Decision Tree (CDT) has the best performance. CDT has the best performance in Guangdong carbon market, SMOTE-CDT has the best performance in Hubei carbon market, and SMOTEENN-CDT has the best performance in Shanghai carbon market, in which SMOTEENN-CDT has a 76% Recall. The non-equilibrium treatment improves the overall Recall, and the risk warning model after non-equilibrium treatment can avoid missing important risk points. This paper can provide a certain degree of reference for the improvement of carbon trading market and risk management. [Display omitted] • A carbon market warning model is constructed. • The average VaR of the carbon trading markets in Shenzhen and Beijing is larger. • CDT performs better in market risk warning. • The model improves 34.8% in the avoidance of risk compared with other models. [ABSTRACT FROM AUTHOR]

In recent years, promoting regional synergistic development has become the shared objective in city-regions during the new stages of development. This paper aims to uncover the dynamics of synergistic development in urban agglomerations by constructing an index measurement system based on four dimensions: industrial synergy, innovation synergy, infrastructure synergy, and institutional synergy. By comprehensively employing theories and methods such as "space of flow" big data analysis, network analysis, and interlocking network models, this study examines patterns and capacities of synergistic development in the Guangdong-Hong Kong-Macao Greater Bay Area. The main instances of industrial cooperation between cities are observed in Hong Kong-Shenzhen and Guangzhou-Shenzhen; capital flows primarily concentrate in Guangzhou-Shenzhen and Hong Kong-Shenzhen. Research paper and patent collaborations between cities are predominantly concentrated in Hong Kong-Shenzhen; joint laboratories are mainly established in Hong Kong-Macao and Hong Kong-Guangzhou; inter-city co-construction of higher education institutions is mainly focused on Guangzhou-Foshan and Shenzhen-Hong Kong. Infrastructure synergistic development performs best in Guangzhou-Shenzhen, Guangzhou-Foshan, and Shenzhen-Dongguan. Cross-border collaboration benefits from institutional advantages held by Hong Kong and Macao. Urban interactions with outstanding performance include Guangzhou-Shenzhen, Hong Kong-Shenzhen, Guangzhou-Foshan, Shenzhen-Dongguan. Additionally, increasing interaction trends can be observed between Guangzhou-Dongguan as well as Shenzhen-Zhuhai/Shenzen-Foshan partnerships. Understanding the typical characteristics and potential trends of synergetic development within the GBA holds significant practical value for establishing a first-class bay area along with a world-class urban agglomeration. • Concept and connotation of synergistic development in urban agglomeration area was examined. • Indicators and methods for evaluation of synergistic development in the GBA were conducted. • Patterns and capacities of synergistic development at urban scale in the GBA were explained. • Urban interaction with highest synergistic development level is Guangzhou-Shenzhen. [ABSTRACT FROM AUTHOR]

The Yangtze River Major Conservation (YRMC) Action has been strategically crafted to catalyze industrial evolution within the Yangtze River basin, aligning with China's goal of achieving carbon neutrality by 2060, particularly from the corporate perspective. Despite its significance, the potential impact of this initiative on corporate environmental performance (CEP) remains understudied. To address this gap, we utilize panel data from Chinese firms listed on the Shanghai and Shenzhen A-shares (2012–2020) and employ the difference-in-differences (DID) method to investigate the causal relationship between the YRMC Action and the CEP. The main findings are threefold: (i) Firms located within a 100 km radius of the Yangtze River's main stream have exhibited an average increase of 0.1497 units in CEP due to the implementation of the YRMC Action, which are consistently validated across robustness tests; (ii) Mechanisms driving this enhancement include incentivizing firms to undertake green technological R&D programs, securing governmental green R&D subsidies, and credit incentives; and (iii) Heterogeneity analyses show that firms closer to the main stream of the Yangtze River, particularly those upstream and led by senior executives with awareness of green initiatives, have contributed to more pronounced improvements in CEP. This paper highlights policy implications for optimizing the incentive effects of the YRMC Action and strengthening the environmental regulatory governance to ensure enduring enhancements in CEP. [ABSTRACT FROM AUTHOR]

Understanding how municipal solid waste (MSW) classification influences the physiochemical properties and incineration emission characteristics of MSW is imperative for sustainable waste management. To investigate how long-term changes in the composition and physical properties of MSW resulting from MSW classification affect the emissions of polychlorinated dibenzo-p-dioxins/dibenzofurans (PCDD/Fs) and multiple flue gas pollutants, a five-year experiment (2018–2022) was conducted in a full-scale MSW incinerator in Shenzhen City, China. After MSW classification, the food waste in MSW was substantially reduced while the paper, textile, and wood components were notably increased. MSW classification also remarkably decreased the water and chlorine contents of MSW while concomitantly increasing the wet-based calorific value, sulfur content, and nitrogen content. Consequently, the PCDD/Fs emissions declined from 106.7 ng I-TEQ/t MSW in 2018 to 26.0 ng I-TEQ/t MSW in 2022. Moreover, a process-tracing experiment demonstrated noticeable decreases in PCDD/F synthesis in the post-combustion area, with mass-reduction efficiencies of 23.6 %–95.4 %. In a correlation analysis, the PCDD/F emissions were significantly positively correlated with food waste, water content, and chlorine and negatively correlated with the wet-based calorific value and nitrogen content. Furthermore, MSW classification reduced the emissions of conventional flue gas pollutants (SO 2 , CO, and HCl) and multiple heavy metals (total sum of Sb, As, Pb, Cr, Co, Cu, Mn, and Ni). In summary, the long-term study demonstrated that MSW classification can feasibly separate incombustible waste, improve combustion quality, and reduce pollutant emissions from sources. These findings offer practical guidance for promoting MSW classification. [Display omitted] • MSW classification remarkably changes composition and physical properties of MSW. • MSW classification mitigates PCDD/F emission from 106.7 to 26.0 ng I-TEQ/t MSW. • MSW classification effectively reduces the emission of various flue gas pollutants. • The long-term experiment demonstrated the feasibility of MSW classification. [ABSTRACT FROM AUTHOR]

Corporate innovation legitimacy is the key guarantee for listed companies to obtain returns from innovation activities. The purpose of this paper is to investigate the effect of analyst coverage on corporate innovation legitimacy based on effective supervision hypothesis and market pressure hypothesis. Moreover, it examines the moderating effect of analyst coverage characteristics, individual corporate behavior, external governance mechanism on the relationship between analyst coverage and corporate innovation legitimacy. The hypotheses are tested using a data set of Shanghai and Shenzhen A-share listed companies from China Research Data Service Platform (CNRDS) database, Hexun.com and CSMAR database. To overcome sample selection bias and reverse causality, this paper conduct robustness test using propensity score matching, lag variable, substitution variable and sample reduction to ensure the reliability of the research conclusions. Findings show that analyst coverage can effectively improve the innovation legitimacy of listed companies. In addition, based on the heterogeneity of the above relationship in different contexts, further research finds that the depth of analyst tracking, and the assessment of analyst optimism strengthen the positive impact of analyst coverage on innovation legitimacy. The implementation of green social responsibility brings a good reputation for the company, thereby helping analysts to focus on improving the legitimacy of innovation; In the market environment with relatively perfect external governance mechanism, the stronger the effect of analyst coverage on corporate innovation legitimacy. Prior studies mostly considered the R&D investment and other factors to overlook how other dimensions influence companies from the perspective of quantity. The research conclusion confirms the significance of analyst coverage as an external corporate governance mechanism, further enriches the theoretical research framework of innovation legitimacy, and has certain reference value for the improvement of innovation quality of listed companies. [ABSTRACT FROM AUTHOR]

As global warming intensifies, the reduction of carbon emissions is imminent. Carbon price is directly related to whether carbon can be effectively reduced. Therefore, accurately forecasting carbon price has important practical significance. Aiming at the nonstationary and nonlinear characteristics of carbon price, this paper proposes a novel hybrid model for forecasting carbon price, which is based on improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), multiscale fuzzy entropy (MFE), complete ensemble empirical mode decomposition (CEEMD), improved random forest by salp swarm algorithm (SSARF), improved back propagation by cuckoo search (CSBP), improved extreme learning machine by whale optimization algorithm (WOAELM) and error correction (EC), named ICEEMDAN-MFE-CEEMD-SSARF-CSBP-WOAELM-EC. Firstly, carbon price is decomposed by ICEEMDAN, divided into high-, medium-, and low-complexity components by MFE. Secondly, high-complexity components are merged and secondarily decomposed by CEEMD, which are still recorded as high-complexity components. Then, SSARF, CSBP and WOAELM are used to forecast high-, medium-, and low-complexity components, respectively, and forecasting results are reconstructed. Finally, EC is carried out using an extreme learning machine to obtain the final forecasting results, and the Diebold-Mariano test is introduced for a comprehensive evaluation of the model. Taking carbon price in the pilot cities of Shenzhen and Hubei as examples, after 6 aspects and 20 comparative experiments, the results show that the proposed model has higher forecast accuracy, with MAPE, MAE and RMSE up to 0.03131, 0.00089 and 4.02e-06 in Hubei, and its forecasting ability is better than other commonly used international carbon financial price forecasting models, providing a theoretical and data basis for carbon pricing and formulating carbon reduction policies in China. The main contributions of this paper are the improved primary decomposition, the use of secondary decomposition, and the innovative combination of three optimal models to forecast carbon price, but it still needs to be optimized for practice. [Display omitted] • Propose improve CEEMDAN by using Hermite interpolation and calculating residuals first. • High complexity components are secondarily decomposed to reduce its complexity. • Improved RF by SSA, named SSARF, is proposed to solve the dilemmas of RF. • Propose a high-accuracy hybrid model for carbon price forecasting. • Compare multi-faceted experiments to prove the validity of the proposed model. [ABSTRACT FROM AUTHOR]

To achieve its carbon peak and neutrality targets, China is in need of balancing environmental and economic sustainability; In addition, whether environmental regulations can gain economic dividends while protecting the environment is particularly important. Based on the data of A-share listed companies in Shanghai and Shenzhen from 2012 to 2021, this study takes China's environmental fee-to-tax as a quasi-natural experiment, and adopts the difference-in-difference-in-differences model to evaluate the impact of environmental tax on enterprises' total factor productivity (ETFP). The results show that the environmental fee-to-tax significantly hinders the growth of ETFP. Further, this negative impact mainly stems from the fact that the reform prompts enterprises to choose strategic innovation and conduct greenwashing behavior. Furthermore, when considering enterprises' heterogeneity, we find that enterprises with large scale, high investment efficiency, state ownership, high market competitiveness and located in western regions are more resistant to policy shocks. This paper provides reliable empirical evidence and useful policy implications for further formulating environmental tax policies to accomplish the "win-win" goal for both the environment and the economy. [ABSTRACT FROM AUTHOR]

Stimulating enterprises to implement environmental management system certification (EMSC, that is to say ISO14001 certification) to the greatest extent and resolving their obstacles in time are the basis for promoting green development of enterprises. Using the full samples of Shanghai and Shenzhen A-share listed industrial enterprises from 2010 to 2019, and employing the Logit model and Propensity Score Matching method (PSM), this paper empirically analyzes the motivations and obstacles for Chinese enterprises to implement EMSC certification, further explores the transformation between advantages and disadvantages under certain conditions, and the differentiation characteristics among enterprises under different social responsibility, property rights and enterprise size. The results show that: ① There is a "U"-shaped relationship between corporate social responsibility and EMSC, and the social responsibility of non-state-owned enterprises could realize the transformation from obstacle to motivation earlier than that of state-owned enterprises. ② There is an inverted "U"-shaped relationship between environmental regulation and EMSC, precisely speaking, this inverted "U"-shaped relationship only exists in non-state-owned enterprises, large-scale enterprises and enterprises with high social responsibility. ③ The public environmental awareness could promote enterprises to implement EMSC, and would strengthen the impact of environmental regulations on enterprises' implementation of EMSC. ④ Based on Propensity Score Matching method, it is concluded that Chinese enterprises indeed improve their environmental performance rather than their financial performance by EMSC. The conclusions provide helpful practical guidance for comprehensively revealing the motivations and obstacles for China's enterprises to implement EMSC. [ABSTRACT FROM AUTHOR]

The effective assessment of power grid emergency response capability (PERC) is the most fundamental aspect in the emergency continuity plans for urban power grid protection. Existing PERC assessment methods assign PERC indicator values under specific disaster scenarios based on one-round expert scores. However, the emergency continuity plans are often continuous and consider diverse scenarios, which makes the assessment quite time-consuming and unrealistic given too many to consider. In this paper, a case-driven method is proposed to solve the assessment problem of PERC with multiple typhoon disaster scenarios while considering the past experience as a guide for real decision making. Firstly, in terms of hierarchical PERC indicator framework, the framework structure of power grid emergency cases is proposed to make case experience modeled and reusable. Secondly, a case scenario similarity algorithm is applied to select the PERC assessment rules (by mapping relations between response indicators and assessment results) that are most similar to the real scenarios. Then the rules are integrated while considering rule variety and case weights. Next, the hierarchical assessment results are obtained by integrating the confidence coefficient values and corresponding utility values. Finally, the method is verified based on the empirical data from Shenzhen, China. The results show the proposed method not only helps in integrating case experience but also assists in quickly generating reasonable PERC assessment results. • Power grid emergency continuity plan requires considering disaster scenario diversity. • Existing capability assessment methods are limited by unsustainable expert scoring. • We use a case-driven scheme to assess emergency capability through experience reuse. • Capability assessment rules are extracted by measuring case scenario similarity. • A three-level indicator framework is constructed for emergency capability assessment. [ABSTRACT FROM AUTHOR]

A large amount of excavated soil is generated due to rapid urban infrastructure development, resulting in serious safety and environmental threats. From the perspective of resource recycling, this paper conducted a laboratory characterization and environmental impact assessment of the utilization of recycled crushed aggregates (RCAs) arising from excavated soil in cement-treated base materials (CTBM). SEM-EDS was employed to test the chemical elements and surface properties, and it reflected larger pores and cracks compared to diabase and limestone aggregates. A series of experimental tests were carried out to investigate the mechanical behaviors of CTBM with varying cement content incorporating RCAs. The laboratory test results revealed that the UCS, IDT strength, FTS and CRM increased with increasing cement content. Moreover, an environmental impact assessment of the recycling of RCAs to produce CTBM was preliminarily analyzed compared to the traditional CTBM with natural stone aggregates (NSAs). The results showed that the attenuation in different environmental impact categories was more than 26% when recycling RCAs from excavated soil to replace NSAs. It was clear that the utilization of 1 t RCAs could result in a reduction of approximately 75 MJ in energy and 5.17 kg CO 2 -eq in emissions just in terms of reducing transportation and landfill. Thus, a total reduction of 3.15 billion MJ energy and 21.72 million t CO 2 -eq emissions could be realized if all the excavated soil generated in Shenzhen annually was recycled. Furthermore, possible policies and further prospects were suggested based on the research for more sustainable management of construction and demolition waste (CDW) containing excavated soil. [ABSTRACT FROM AUTHOR]

The livability of a city, which includes social, economic, environmental, and other connotations, assumes a central role in determining the quality of life. Only when the city develops in a coordinated manner in these aspects can it truly build a sustainable urbanism. Current literature on urban livability show gaps in terms of its measurement and assessment, especially from a dynamic point of view. To address these gaps, in this paper we design an indicator system for measuring urban livability which is built upon a comprehensive synthesis of existing literature to our knowledge. Based on the indicator system, we build an agent-based simulation model on the NetLogo platform for urban livability which utilizes multi-source geographical data. In applying the model in our study case, Futian District, Shenzhen, the simulated livability scores are tested valid and robust, thus hinting its potentials for generalization. A further global sensitivity analysis on the simulation results reveals the first- and second-order factors' contribution structure to the overall livability score, which proves a useful tool in policy analysis. The simulation tools developed in this paper constitute a practical approach for sustainable development of cities in supporting governance policy evaluation and design, and the methodological framework offers a new scope for understanding the mechanisms of the making of urban livability. [ABSTRACT FROM AUTHOR]

Construction waste recycling is to turn construction waste materials into new resources for use. It is often considered in waste management plans, in which a central dilemma is to ponder the on-site and off-site options. Both recycling options have their respective strengths and weaknesses in dealing with internal and external factors related to site, time, cost, market, and government. However, no previous study has consciously considered the two options by putting them together with the factors in a structured model to support managers in devising their waste management plans. This study aims to develop a decision-support framework to help plan on-site and off-site construction waste recycling. It does so by adopting the qualitative research methods of case study, site visits and semi-structured interviews in Shenzhen, China. Two generic factors, namely (a) project characteristics (e.g., site constraints, time allowed, and project scale), and (b) industrial and governmental supports (e.g., transportation, recycling technology, the material market, regulations, and government subsidies), are found to determine the technical and economic viability of a particular recycling option. The two factors interact with each other and evolve over time and context to effect. This paper further articulated and organized their dynamics in a construction waste recycling decision-support framework. The research can help maximize the practicality of waste management plans. It is also of value to enhance construction waste management in the long run. • To be on-site or off-site is a classic dilemma of construction waste recycling. • Project characteristics and industrial and government supports are the key. • A decision-support framework to structure the factors is developed. • The framework is useful to maximize the practicality of waste management plans. [ABSTRACT FROM AUTHOR]