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This paper studies the carbon price fluctuation in China through the adaptive Fourier decomposition (AFD). Apart from the transient time-frequency distribution of the original AFD model, we also reconstruct the mono-components of this model to obtain the components in different time-frequency scales. Our empirical results based on the carbon price in Hubei Province demonstrate that there are three periods when the price fluctuates dramatically, mainly affected by the governmental policies about carbon emission and the development of clean energies, as well as the outbreak of COVID-19. Furthermore, the fluctuations of the price in the three identified periods are reflected in different scales. The comparison of the decomposition results and those of EMD and VMD shows that the AFD performs best in absorbing the price's useful information extracted through all these methods. [ABSTRACT FROM AUTHOR]

Swine manure has become rural China's primary source of agricultural non-point pollution. Various sustainable manure management practices (SMMPs) have been promoted in rural areas. Although SMMPs are becoming more popular, little evidence exists regarding their ex-post impacts. Using survey data from 710 swine breeding households in rural Hubei, China, this paper estimates the adoption and impacts of SMMPs on household income and happiness. This paper discusses the use of an endogenous switching regression model to solve the endogeneity problem that arises from both observable and unobservable factors. The results showed that 48.5% of farmers sampled adopted SMMPs. Furthermore, on average, the adoption of SMMPs was associated with a 28.7% increase in household income per capita and a 22% improvement in happiness. Then robustness tests were conducted to verify these results. Several factors influence the adoption of SMMPs, including health, swine breeding scale, swine breeding experience, technical training, internet, waste management facility and previous adoption experience. These findings highlight the importance of promoting SMMPs in rural areas to increase farmer income and enhancing their perceived happiness, and measures should be taken to scale up their adoption of SMMPs. • Adoption of SMMPs positively influences swine breeding farmers' household income. • Adoption of SMMPs significantly enhances swine breeding farmers' happiness. • Less than half of the sampled swine breeding farmers adopted SMMPs. • Endogenous switching regression model is employed. [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]

In recent years, sustainable digital economy development goals have received increasing attention because of the serious influence environment with the development of the rapid economy. Meanwhile, Multiple Criteria Decision-Making (MCDM) methods are efficient ways to measure sustainable developments, which can controls environmental pollution and protects sustainability improvement. However, assessment results are unconvincing by using the common MCDM methods because various areas that caused pollution conditions are inconsistent. Therefore, the purpose of this paper is to design an interpretable MCDM method with uncertain weights for various areas evaluation. In particular, MCDM can be used to evaluate environmental sustainability development efficiently, and deep neural networks can supply credible weights to MCDM. Interpretability is used to understand key factors in the decision-making process. Referring to the national policy and urgent areas from central areas in China, six areas are conducted to assess the sustainable digital economy problem, which could be interpreted as demonstrating the effectiveness and feasibility of the proposed approach. Besides, the experimental results demonstrate that the sustainable developmental level of Hubei is the best in the latest year. [ABSTRACT FROM AUTHOR]

Although China boasts the largest online consumption market, there has been no prior case study addressing the carbon footprint of online consumption. The rapid expansion of online consumption has posed a challenge to China's carbon neutrality pledge. This paper aims to fill this crucial gap by conducting a pioneering study based on survey data collected from 6000 households. To achieve this goal, this study has combined provincial Multi-Regional Input-Output (MRIO) tables with residents' online consumption calculated by the Non-Linear Optimization model, and applied the Environmental Input-Output Life Cycle Assessment (EIO-LCA) model to calculate the carbon footprint of residents' online consumption. Result indicated that the average carbon footprint of residents' online consumption was 0.46 tCO 2 e in 2016, accounting for 12.30% of the total consumption carbon footprint. Notably, high-emission regions include Beijing-Tianjin, Jiangsu-Zhejiang-Shanghai, and Hubei. Moreover, the dominant sources of the online consumption carbon footprint were electricity, food, clothing, and beauty products. Furthermore, we found that the carbon footprint of online consumption tends to increase with income, with differential income elasticities observed for various products and income groups. We also quantified the average expenditure-based life-cycle carbon coefficient for parcel delivery (0.22 kgCO 2 e/yuan) and conducted two scenario analyses to assess its impact. From a policy perspective, our research on measuring the carbon footprint of residents' online consumption can provide valuable insights for designing future policies and decisions related to e-commerce and key sectors along the supply chains. Additionally, it will further encourage Chinese residents to adopt low-carbon lifestyles. • Identifies the expenditure structure of residents' online consumption. • The carbon footprint of Chinese residents' online consumption in 25 regions. • The income elasticity of online consumption carbon footprint. • The last mile emission intensity of e-commerce is quantified. [ABSTRACT FROM AUTHOR]

Flood Detection and Service (FD&S) is of great significance to flood management and decision-making. But most of the state-of-art FD&S methods are weak in timeliness and extensibility, and could not reflect flood processes. To resolve the abovementioned problems, this paper proposed the process-based FD&S (PFD&S) method based on Sensor Web. PFD&S is a four-layer architecture the core components of which are the access adapter and process-based detection rules and it is capable of heterogeneous sensor access, flood detection, and flood phase adaptive services. A prototype was developed based on the PFD&S method. Two floods occurring in the Huanghan basin (Hubei, China, with the area of 5.04 × 104 km2) during July 2016, was selected as the case studies to validate the PFD&S method and prototype. The results demonstrated that the proposed PFD&S method and prototype could achieve the instant flood process detection and services in 2.7 min. • The PFD&S method was proposed to achieve the rapid flood process detection and flood phase adaptive services. • The PFD&S prototype was designed and implemented based on the PFD&S method. • The method and prototype were sensor web - based, with universality and extensibility. [ABSTRACT FROM AUTHOR]

Abstract: In the process of building a two-oriented society, it is of reference significance to analyze the current situation of rural ecology and environment so as to build a two-oriented society and of realistic and practical significance to achieve coordinated development of three systems of rural society, economy and resource environment. With the case study of Xiantao City in Hubei Province, one of cities of comprehensive support reform pilot area of “two-oriented society”, this paper conducts investigation and research on local countryside. Through field investigation, typical survey and literature review, this paper learns about pollution and control situation of natural environment, social environment and ecological environment in the countryside of Xiantao, and analyzes the situation of rural ecological environment control in building a two-oriented society. [Copyright &y& Elsevier]

Abstract: Tourism Environmental Carrying Capacity (TECC) is an important index to judge sustainability of scenic zone, which is calculated by Tourism Ecological Footprint (TEF) and Tourism Ecological Capacity (TEC). Based on theories and models of TEF, this paper calculated TEF, TEC, and TECC in Yellow Crane Tower scenic spot. In 2008, TEF per capita was 0.0570hm2, footprint of transportation and waste were large, occupied 55.89% and 33.20% respectively. TEC of Yellow Crane Tower was 108.45hm2 in 2008 and it will be 176.80hm2 in 2012. Therefore, TECC was 3 804 tourists per day and it will be 6 204 tourists per day in 2012. Actually, TECC reached 3 354 tourists per day in 2008, which showed that tourists were under Carrying Capacity, but it is in vigilant situation of sustainable development. Finally, this paper put forward some suggestions on tourism sustainable development in Yellow Crane Tower. [Copyright &y& Elsevier]

The utilization of renewable energy sources to produce electricity is capable of relieving the pressure of limited natural resources and achieving the sustainability of future energy. This paper addresses a multi-period multi-feedstock multi-technology biomass-based power generation supply chain planning problem with parameter uncertainty, balancing economic, environmental, and social objectives simultaneously. However, the main challenges in optimizing this problem are correlated with multiple conflicting objectives and uncertain parameters. This study proposes a novel globalized robust goal programming model with goal constraints to balance three conflicting objectives using priority levels and characterize the uncertainty of unit emissions and social scores by inner–outer uncertainty sets. After transforming globalized robust environmental and social goal constraints into their equivalent forms, the tractable counterpart of the proposed model is obtained, which is mixed-integer linear programming (MILP). Finally, the effectiveness of the proposed model is demonstrated through a case study about the design of a sustainable biomass-based power generation supply chain (SBPSC) network in Hubei Province, China. Computational results reveal that by adjusting several parameters, environmental and social aspired goals consistently can achieve, whereas the economic objective is vulnerable to being influenced. Comparative studies with nominal goal programming model and robust goal programming model indicate that the proposed model is uncertainty-immunized and less conservative. Under investigated circumstances, the realized economic profit by the proposed model is approximately 42.5% higher than that of the robust goal programming model on average. • A pair of uncertainty sets is presented to characterize the parameter uncertainty. • Globalized robust environmental and social goal constraints are established. • Established goal constraints are transformed into their computationally tractable forms. • A novel globalized robust goal optimization method is proposed to balance three conflicting objectives using priority structure. • A case study shows the feasibility and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper examines the risk spillover effect between the carbon market and the stock market in China and the role of corporate social responsibility (CSR) on this effect. Employing Beijing, Hubei, and Guangdong carbon markets, we apply time-domain and frequency-domain spillover approaches and find that during the Chinese stock market crisis in 2015, risk spillovers from the stock market to the carbon market were more pronounced. Additionally, CSR firms are more dominant as information transmitters than those non-CSR (NCSR) firms in the carbon market. However, plausibly, due to the infancy of carbon trading, our results show that the level of connectedness between the carbon market and the stock market in China is relatively low. [ABSTRACT FROM AUTHOR]

• Thermal performance reduction was observed by monitoring the system operation. • Pipe corrosion and groundwater fouling were detected in heat pump maintenance. • The effects of pipe corrosion on heat transfer were investigated. • Thermal efficiency decreases significantly once a pipe was rusted. This paper investigates the thermal performance reduction of a groundwater heat pump (GWHP) system installed in Hubei province, China by the monitoring of the system operation over a two-year period. Pipe corrosion and deposits were detected in the maintenance of heat pumps, which might contribute to the thermal performance reduction. In order to understand the physic-chemical dynamics inside heat pumps during the system operation, the groundwater pumped out from the aquifers and the deposits collected in a condenser of a heat pump were analyzed. The groundwater has electrical conductivity of 973 μS/cm, indicating low salinity. The X-ray fluorescence (XRF) analysis shows the deposits were composed mainly of 66.4% Fe 2 O 3 and 17.8% CaCO 3 , indicating both effects of iron oxidation and groundwater fouling. The corrosion effects on the heat transfer efficiency of metal pipes were examined. The heat transfer coefficient (HTC) comparison of a raw pipe and three rusted pipes show that the HTC of the rusted pipes was reduced by 8.3–41.5%, meaning a significant decrease in heat transfer efficiency. It is verified that the thermal reduction of the GWHP system could be attributed to the pipe corrosion which desires to be carefully considered in system design and operation in future. [ABSTRACT FROM AUTHOR]

Abstract: It is well known that maintaining stable coordination of social security and economic development is absolutely necessary for Hubei province, so how to analyze the coordination becomes an important content in Hubei economic development. In this paper, using factor analysis and hierarchical cluster analysis, the author try to evaluate the regional level of social security and economic develop in Hubei province. The results indicate that Hubei need to take measures to promote social security level and balanced development. At the end of this article, some economic suggestions are given to deal with uncoordinated problem. [Copyright &y& Elsevier]

Abstract: The key to build the rural well-off society is to actively develop rural human resources and transform the abundant rural human resources into solid human capital. This paper, based on the view angle of departmental benefits, carries out the demonstration analysis of the problems in rural work force training in minority nationality regions in China at present. It is held by the task team that the decentralization of fiscal investment is the immediate cause of these problems while the effects of the departmental benefits are the in-depth cause and the realistic approach to settle the problem is to establish the multi-cooperative training system in the minority nationality regions. [Copyright &y& Elsevier]

Abstract: Many water quality models have been extensively used to evaluate non-point source pollution, such as SWMM (Storm Water Management Model), AnnAGNPS (Annualized Agricultural Non-point Source), HSPF (Hydrological Simulation Program– Fortran), SWAT (Soil and Water Assessment Tool) and so on. However, these models’ construction tended to be complex, only used well in the condition of many parameters and normative data can be obtained. There were much problem to use these models in tidal plain, where topography were flat, stream network were complex and controlled by many water conservancy systems. The L-THIA (Long-Term Hydrologic Impact Assessment) model can be used in the areas with uncompleted data, evaluate the effects of land use on non-point source pollution, because it only needs land use, soil types and some rainfall data. But the output results of L-THIA model are the annual average runoff volume and pollution load, which cannot be obtained easily in in-site observation. In this paper, one of typical tidal plain, Sihu basin in Hubei province of China, was studied. The annual average runoff volume and the non-point source nitrogen and phosphorus load of each grid (16m*16m) and the spatial distribution were estimated by L-THIA model. The average load of non-point source nitrogen and phosphorus at each exit of the units were calculated based on the suppose that the pollution load is inverse to the distance of water flow. Model validation was executed by comparing calculated results and observed water quality data for study area. The results demonstrated that there were highly significant linear correlation between the calculated average load of non-point source nitrogen and phosphorus and the measured concentrations of TP and TN (TN: R=0.828; TP: R=0.957). These suggested that the average load of non-point source nitrogen and phosphorus were reliable to evaluate non-point source pollution. Moreover, the simulation results illustrated that the non-point source nitrogen and phosphorus loads under different land uses were quite different. The impact of dry lands on the non-point source nitrogen and phosphorus was the highest; that of paddy fields and residential areas were secondary; and the impact of woodlands to non-point source nitrogen and phosphorus was the minimum. [Copyright &y& Elsevier]

Abstract: Designing scientifically drought vulnerability evaluation index system has great meaning to the quantitative analysis of drought vulnerability, vulnerability zoning of drought and drought risk management. This article takes seven counties of Xiaogan city in Hubei Province as the case study area, screens out 17 factors which closely related to drought vulnerability as evaluation index mainly from a socio-economic perspective, applies AHP to determine the weights of various relevant factors in the evaluation index, and then uses the fuzzy comprehensive evaluation method to achieve a drought vulnerability assessment. The results show that the overall level of drought vulnerability degree in Xiaogan City is high, in which Dawu County and Xiaochang County have the highest level of vulnerability. Accordingly, the paper brings forward the policy recommendations, including: diversifying peasants’ income channels, increasing non-agricultural income and reducing the dependence on agriculture; improving government''s risk management capacity and establishing drought emergency management programs; developing rural micro-credit capital markets and a variety of intermediary organizations. This article aims to make references to the study and practice of drought vulnerability evaluation. [Copyright &y& Elsevier]

• It evaluates the effect of China's ETS on non-fossil energy development. • It analyzes ETS's effects from energy type, pilot, and pilot-energy type aspects. • The ETS has the most significant promoting effect on hydropower and photovoltaics. • Carbon price plays a positive role in moderating the effect of China's ETS. Emissions Trading Scheme (ETS) can internalize the environmental costs of fossil energy consumption and encourage enterprises to consume non-fossil energy, which is crucial for People's Republic of China (PRC) to achieve the contribution target of the Paris Agreement cost-effectively. However, whether the ETS in PRC can promote non-fossil energy development remains to be answered. This paper uses a difference-in-differences model to evaluate the effect of the ETS on non-fossil energy development in PRC. Using provincial monthly panel data from January 2004 to December 2019, we find that (1) the ETS has significantly promoted non-fossil energy development in PRC, increasing the monthly average share of non-fossil energy power generation in total power generation by 2.326 percentage points, which has been verified by a series of robustness tests. (2) The effect of the ETS on non-fossil energy development is heterogeneous by energy type, pilot region, and pilot-energy type. The ETS has significantly increased the share of hydropower and photovoltaic power generation, and has significantly promoted non-fossil energy development in Guangdong; meanwhile, the ETS has significantly increased the share of hydropower and nuclear power in Guangdong, and the share of wind power and photovoltaic power in Hubei. (3) The higher the carbon price, the greater the role of the ETS in promoting non fossil energy development. [ABSTRACT FROM AUTHOR]

Upon the occurrence of a disaster, emergency supplies should arrive at disaster areas with different severities in the shortest time. Therefore, it is of pivotal importance to plan and schedule appropriate processes. This paper first elaborates on the principle of ordered arrival of emergency supplies. Then, it establishes a multi-objective multi-constraint emergency material scheduling (EMS) model based on the principle of ordered arrival. Subsequently, a hybrid ant colony optimization (HACO) is proposed to solve EMS. The computational results for 15 multi-depot benchmark instances are reported and the average error between HACO and the best known solution (BKS) is only 0.16% Then, real geological disasters from Hubei province in China are examined as a case study. Experimental results show that HACO performs better than non-dominated sorting genetic algorithm II (NSGA-II) and multi-objective ant colony algorithm (MOACO) in the case study and benchmark instances. • Study a large-scale real landslide disaster. • Establish a multi-objective multi-constraint EMS model. • Propose a HACO to solve the EMS model. • The HACO is tested on benchmarks and disaster network. [ABSTRACT FROM AUTHOR]

China launched seven emissions trading scheme (ETS) pilots in 2011, and a national ETS, at the end of 2017 in an attempt to reduce its greenhouse gas emissions (GHGs) and drive its extensive energy transition in a cost-effective way. The Hubei province pilot ETS has operated since 2014, and an analysis of its effectiveness can provide lessons for the nascent national system. This paper disaggregates Hubei's industrial carbon dioxide (CO 2) emissions from 2005 to 2018 into economic scale, economic structure, energy efficiency, and energy structure effects using the logarithmic mean Divisia index (LMDI). Difference-in-difference (DID) models then assess the implementation effectiveness of this ETS, and its impact on the main influencing factors of the LMDI. Ten cities each in the Hubei and Hunan provinces are selected as treatment and control groups, respectively, in the DID models. Results show that the change in industrial CO 2 emissions is mainly due to the economic scale and energy efficiency effects. After the ETS implementation, the energy structure effect has a limited impact on emissions, while the economic structure effect makes a negligible contribution. Moreover, the implementation of the ETS has had little demonstrable impact on industrial CO 2 emissions, gross domestic product (GDP), energy consumption intensity, and CO 2 emission intensity. This lacking of impact is caused by the GHG monitoring capacity deficits of the local Development and Reform Commission, and irrational quota allocations. Effective supervision and quota allocation should be developed to increase the impacts of the ETS. [ABSTRACT FROM AUTHOR]

To investigate the impacts of regulatory announcements on China's pilot carbon markets, as well as test the semi-strong form of market efficiency, a multivariate regression model with GARCH effects combined with multiple bilaterally modified dummy variables is established which allows us to investigate the potential overlapping influence from two timely adjacent events. The Shanghai, Guangdong and Hubei pilot carbon markets are taken as case studies. Based on the ADF test and the runs test, the results show that the China's pilot carbon markets have achieved the weak form of efficiency but not the semi-strong form of efficiency. With the regression model the results show that the release of the allowance allocation plan will affect the carbon price trend, and the allowance auction can only play an auxiliary role as its impact on the carbon price is not decisive. In addition, ubiquitous ex-ante impact proves that the information leakage exists in each pilot carbon market. The model established in this paper is suitable for analyzing the impacts of overlapping events in different markets, which can effectively assist decision makers to distinguish the effects caused by overlapping events. [ABSTRACT FROM AUTHOR]

• The replacing of a coal-fired boiler by a GWHP system is investigated. • The operation of each system has been monitored over one-year period. • The boiler has lower investments and covers lower thermal load than the GWHP. • GWHP shows higher economic performance considering Average Energy Price. • GWHP system may be cost effective over traditional boilers for applications. Currently in China, the replacement of coal-fired boilers by clean and renewable energy sources is considered as an essential measure to alleviate air pollution. This paper investigates the thermo-economic performance of replacing a coal-fired boiler by a Groundwater Heat Pump (GWHP) system for a greenhouse, where the GWHP system was constructed to reduce emission and also to provide cooling. The operation of this system has been monitored over a one–year period. The results show that the thermal efficiency factor of the boiler varies in the range of 0.53–0.68 and the Coefficient of Performance (COP) of the GWHP system averages at 4.1 for cooling and at 3.3 for heating. Although the boiler has both lower capital costs and lower operating costs, the analysis of Average Energy Price (AEP) shows that the GWHP system has a higher economic performance, since it has a lower AEP of 0.040 USD /kWh in heating and 0.023 USD/kWh in cooling over an expecting lifetime of 20 years, in comparison to the boiler at 0.052 USD/kWh over a lifetime of 10 years. This indicates that GWHP system may be considered as an alternative over traditional boilers in terms of thermo-economic performance for applications in other places of the world with similar climate condition. [ABSTRACT FROM AUTHOR]

• A Maximum-Entropy Ecological Niche Model is used to estimate a global-scale probability distribution of COVID-19 high infection rate. • Environmental parameters (surface air temperature, precipitation, and elevation) and humanrelated parameters (CO 2 emission and population density) are used in the model. • The model is trained only with data of Italian provinces with high infection rate, but predicts known actual infection focuses, e.g. the Hubei province in China. • A risk index is proposed, which correctly classifies most World countries, which have reported high COVID-19 spread rate, as zones with high-risk of infection rate increase. • The methodology follows an Open-science approach where the model is published as a standardized Web service that maximises re-usability on new data and new diseases, and guarantees the transparency of the approach and the results. COVID-19 pandemic is a global threat to human health and economy that requires urgent prevention and monitoring strategies. Several models are under study to control the disease spread and infection rate and to detect possible factors that might favour them, with a focus on understanding the correlation between the disease and specific geophysical parameters. However, the pandemic does not present evident environmental hindrances in the infected countries. Nevertheless, a lower rate of infections has been observed in some countries, which might be related to particular population and climatic conditions. In this paper, infection rate of COVID-19 is modelled globally at a 0.5∘ resolution, using a Maximum Entropy-based Ecological Niche Model that identifies geographical areas potentially subject to a high infection rate. The model identifies locations that could favour infection rate due to their particular geophysical (surface air temperature, precipitation, and elevation) and human-related characteristics (CO 2 and population density). It was trained by facilitating data from Italian provinces that have reported a high infection rate and subsequently tested using datasets from World countries' reports. Based on this model, a risk index was calculated to identify the potential World countries and regions that have a high risk of disease increment. The distribution outputs foresee a high infection rate in many locations where real-world disease outbreaks have occurred, e.g. the Hubei province in China, and reports a high risk of disease increment in most World countries which have reported significant outbreaks (e.g. Western U.S.A.). Overall, the results suggest that a complex combination of the selected parameters might be of integral importance to understand the propagation of COVID-19 among human populations, particularly in Europe. The model and the data were distributed through Open-science Web services to maximise opportunities for re-usability regarding new data and new diseases, and also to enhance the transparency of the approach and results. [ABSTRACT FROM AUTHOR]

China is the world's largest developing country and a carbon dioxide emitter. A functional carbon market can effectively reduce carbon emissions. This paper uses the Markov chain Monte Carlo-stochastic volatility model and the wavelet multi-resolution model to analyze the volatility of price returns and the dynamic characteristics of price fluctuations in the carbon pilot markets in Hubei, Shanghai, and Shenzhen. The price movements in these markets are compared to the emissions trading system of the European Union (EU-ETS). The results show that there is a volatility clustering in the price of carbon trading in Hubei, Shanghai, Shenzhen and the EU-ETS. China's carbon pilot markets have a deficiency in terms of volatility stability, as does the EU-ETS. From a long-term perspective, China's carbon market lacks a detailed development plan, which is vital because the construction of the market system is not yet optimal. From a short-term view, China's carbon market is not active and the participants' attitude toward risk is extremely sensitive. • MCMC-SV and wavelet multi-resolution model applied to carbon price volatility. • Three major Chinese markets are compared to the EU-ETS. • All markets evidence volatility clustering. • China's carbon market lacks a detailed development plan for the long term. • Short-term, China's carbon market must become more active and offer more products. [ABSTRACT FROM AUTHOR]

As an economic means to cope with climate change, carbon trading has become an important measure to reduce carbon emissions in China. It has been over seven years since the initiation of seven pilot carbon markets, but has the implementation achieved the goal of controlling carbon emissions in the region? Are the effects really resulted from the carbon market other than other energy-saving and emission reduction policies? Based on the provincial panel data of China from 2005 to 2016 this paper conducts an empirical study on the emission reduction effects of pilot projects using the Difference-in-differences model (DID). The results show that: (1) The implementation of carbon markets in Beijing, Shanghai and Hubei exhibited a significant inhibitory effect on local carbon emissions, but a promoting effect in Guangdong, and no significant effect was found in Tianjin; (2) In terms of time lag effect, no significant inhibiting effect on the local carbon emissions is found during the first year of opening of Shanghai carbon market but the effect grew significantly from 2015 to 2016; while for Hubei and Beijing, significant effect was shown from the first year of running. Being an experimental program to see whether the carbon trading policy would work in China or not and if it does, under what conditions and settings the policy becomes effective, the 7 pilot markets provide important experiences and lessons to the upcoming nationwide market in China. Based on the empirical result that the carbon trading system in Beijing, Shanghai and Hubei effectively reduced carbon emissions, it is suggested that the national carbon market should actively learn from the experiences of these three pilot markets particularly. [ABSTRACT FROM AUTHOR]