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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]

This paper addresses the significant challenges faced by distribution system operators (DSOs) in competitive electricity markets due to uncertainties arising from electricity markets, electric vehicles (EVs), and conventional loads. To tackle these challenges, this paper proposes a pseudo-local reserve market between the DSO and EVs, which enables the DSO to integrate EV flexibility into the overall market framework while compensating for deviations in the conventional load across the wholesale electricity market. Furthermore, a two-stage framework is developed to facilitate the participation of EVs in electricity markets. In the first stage, the reserve capacity of EVs is integrated into the decision-making process for day-ahead bidding, taking into account uncertainties of the load and electricity. In the second stage, the day-ahead results are coordinated to enable the efficient dispatch of EVs for real-time market participation. To assess the efficacy of the proposed framework, a case study is conducted within a 31-node distribution system situated on a university campus located in Guangdong, China. This paper investigates the economic impact of load deviation constraints on EV reserves, revealing a penalty reduction of 3100 CNY for a daily reservation of 1000 EVs and a net profit increase of 1300 CNY for DSOs utilizing reserves. It further introduces a method for quantifying reserve capacity, enhancing DSO decision-making accuracy. • A pseudo-local reserve market is established considering EV's reserve potential. • Optimal bidding strategy for DSO in China's electricity markets is constructed. • A framework for EV coordinated V2G operation is developed. • The proposed method can limit load deviation cost for more profits. [ABSTRACT FROM AUTHOR]

Along with habitat destruction and the intensification of climate change, economic and social development is threatening the living of species. In the context of China's domestic economic circulation, the spatial structure of biodiversity loss is complicated by the decentralization of production, with many regions affecting the survival of species in other regions. Based on the environmentally extended MRIO model, this paper calculated the subnational biodiversity loss footprint through structural path analysis and social network analysis, identified the regional linkages and spatial networks of species loss, and traced the conservation responsibility to specific sectors. Our findings indicate that Yunnan, Tibet, Guangdong, and Sichuan possess the most significant biodiversity footprints, comprising over 40% of the total footprint. In terms of threat patterns, Yunnan and Tibet have the largest intra-regional footprints, indicating their important impact on species within the region; Guangdong and Zhejiang have the largest extra-regional footprints, indicating their role in threatening other species through cross-regional trades. The primary industry, tap water and food and tobacco sectors are major biodiversity footprint producers. Overall, some eastern and coastal areas are the final drivers of biodiversity loss in China, driven by increasingly complex trade links. Notably, the directionality of species loss in biodiversity hotspots is evident, with Shandong and Guangdong significantly influencing the biodiversity of Yunnan and Guangxi, respectively. This study systematically analyzed the complete network of biodiversity loss and divided four biodiversity protection communities to promote the realization of trans-regional protection and compensation. Examining the biodiversity loss through the lens of networks, and connecting economic activities to species, serves as a warning to decision-making bodies that a future of increasingly intricate domestic trade could pose a critical threat to biodiversity, necessitating collaborative conservation efforts. [Display omitted] • 1.Inter-provincial trade contributes to the complex structure of biodiversity loss. • The characteristics of biodiversity footprints vary widely among provinces. • Some eastern and coastal provinces are the final drivers of biodiversity loss. • Four protection communities are established through social network analysis. [ABSTRACT FROM AUTHOR]

Rapid urbanization results in energy shortage and unreasonable energy metabolism structure. The goal of this research is to take Guangdong, China as a special case study to illustrate the influence of energy classification differences on the energy metabolism system. To do so, we introduced the concept of "urban metabolism", and treated sectors and energy flows as nodes and paths in a network model. We used the input output analysis to compile the physical input output table through the embodied energy element intensity. Building on this, we used ecological network analysis to quantify the urban metabolic processes and energy metabolism levels within the urban system. In addition, the alternative indicators are first introduced to explore the best alternative energy in various sectors to avoid a short-term energy crisis. In this paper, different energy groups are considered on the energy metabolism system, including all energy, primary energy, secondary energy and six specific energy, which will fill the research gap about the influence of energy classification on urban energy metabolism. It is found that the energy metabolism of Guangdong is now in the state of sub-health. The energy metabolism hierarchy atlas shows that the pulling force is hardly affected by the energy classification but the driving force is very sensitive, which further illustrate that producers can choose different energy according to their production structure. Facing the shortage of energy supply, the secondary energy with the highest substitutability of all energy value is the better alternative energy for advanced manufacturing sector (containing twelve industries such as Manufacture of transportation equipment and Manufacture of metal products). More specifically, the nonrenewable properties of primary energy make it particularly important to find the corresponding alternative energy. Heat is the best alternative energy for crude oil, while electricity is irreplaceable. It is expected that the results will provide scientific support to guide the reform of urban energy metabolic system in an attempt to coordinate the energy development strategy, improve the energy consumption structure and maintain energy security and stability. • An Energy Metabolism Network (EMN) model from a Guangdong perspective is developed. • Different energy types have a great impact on the level of energy metabolism. • The inherent mechanism of energy ecosystems are revealed by the energy hierarchy atlas. • In-depth analysis is conducted to investigate the energy interactions between different industries. • Scientific basis for supporting the formulation of the effective reform of urban energy metabolism system. [ABSTRACT FROM AUTHOR]

Site selection is a key factor to the success of ocean thermal energy conversion (OTEC) project. It is a multi-criteria decision making (MCDM) problem with a series of conflicting criteria involved. However, limited studies were found concerning this area and problems existing in classical MCDM methods tended to fail OTEC site selection decisions. Therefore, this paper proposes an extended MCDM method and establishes a new decision-making framework to select the optimal location. First, a comprehensive evaluation criteria system for OTEC site selection from the view of sustainability with 16 criteria involved is established. Second, feasible alternative sites for OTEC project are identified by PEST analysis. Third, an extended PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation) under intuitionistic fuzzy environment is proposed to avoid compensation assumptions. During the decision process, seven groups of experts shared the work and cooperated with each other according to their backgrounds. Finally, a real case is studied and sensitive analysis is conducted, demonstrating the robustness and effectiveness of the proposed method. This study can effectively improve OTEC site selection decision making quality and also extends the domains of intuitionistic fuzzy PROMETHEE applications. • A novel multi-criteria decision-making framework for site selection is proposed. • The criteria system for ocean thermal energy conversion site selection is constructed. • A case study is carried out in areas of Guangdong and Guangxi Provinces in China. [ABSTRACT FROM AUTHOR]

Abstract Manufacturing industry is an important part of economic development. Recognizing the sustainable development of regional manufacturing has an important guiding role in the formulation of environmental policies. Based on the meta-frontier Malmquist-Luenberger (MML) productivity index, this paper uses Chinese provincial panel data (2003–2015) to measure the green total factor productivity (TFP) of China's manufacturing. It is decomposed into the following: efficiency change (EC), change of the best practice gap ratio (BPC) and change of technical gap ratio (TGC). We compared the regional differences in green TFP growth in manufacturing in all provinces, analyzed regional and time differences in green TFP and the decomposition of manufacturing between regions and identified innovative regions. The results show that: (1) The average annual growth rate of green TFP in Chinese manufacturing is 0.85% with technological progress playing a key role. (2) There are differences in the causes of the increase in green TFP in all regions. The eastern region and the western region are driven by technological progress while the central region depends on technology catch-up effects. (3) Guangdong and Qinghai are two different types of global innovation regions with Guangdong driven by technological innovation and Qinghai driven by strict environmental protection systems. [ABSTRACT FROM AUTHOR]

Community shared solar (CSS) program has great potentials in contributing to the complete decarbonization of the power sectors worldwide. Few research have focused on its potential diffusion from the user perspective. This paper fills the gap by conducting a survey-based unlabeled choice experiment in the Guangdong Province, China to investigate the determinants of potential users' willingness to participate in CSS programs. We analyzed the survey data using a random parameter logit model. Our results show that users are more likely to participate in CSS programs with lower upfront payment, trialability, shorter payback period, a public utility as provider and larger impact on climate change mitigation. However, they are likely to accept longer payback period in CSS programs with higher participation rate because of the potential benefit from interpersonal communication. Users' previous knowledge of CSS programs and income will also increase their willingness to participate in CSS programs with higher upfront payment. Our results provide important implications for designing policies and business models to promote the distributive renewable energy in China. • Community shared solar is widely accepted among surveyed individuals in our choice experiment. • The business model, and the ownership structure of community shared solar affect its potential adoption. • The interpersonal communication and public promotion of community shared solar program can increase its popularity. [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]

Electrification of public transit bus has been rapidly promoted to reduce carbon dioxide (CO 2) emissions in China. It is essential to evaluate the impacts of battery electric buses (BEBs) adoption on real-world CO 2 emissions. This paper conducted a well-to-well (WTW) analysis to estimate the CO 2 emissions of BEBs in Shenzhen. First, we identified the regional inventory from an extensive review of research papers and data. Based on the mobile BEBs data, we explored the impacts of different driving conditions on WTW CO 2 emissions. Moreover, a sensitivity analysis was performed to assess the reliability of the WTW results. The experiments results show that BEBs can reduce WTW CO 2 emission by 21.8% relative to conventional diesel buses (CDBs) in 2018. And the WTW CO 2 emissions factor of BEBs has a negative correlation with stop headway and average speed. Notably, the impacts of CO 2 emissions reduction are more sensitive when the stop headway is over 2 km or the average speed is under 25 km/h. Besides, for the current power structure and charging technology in Guangdong, if the growths of the thermal power share and the charging loss are over 5%, BEB has more CO 2 emissions reduction benefits by improving the charging efficiency. Moreover, if the thermal power share and the charging loss are decreased, BEB can obtain more CO 2 emissions reduction potential by reducing the thermal share. The improvement of these two technologies can achieve close CO 2 emission reduction effects in other situations. Image 1 • The BEBs can reduce WTW CO 2 emission by 21.8% relative to CDBs in 2018. • The impacts of CO2 emissions reduction are more sensitive when the stop headway is over 2 km and the average speed is under 25 km/h. • If the growths of the thermal power share and the charging loss are over 5%, it's better to improve the charging efficiency to reduce CO 2 emissions. [ABSTRACT FROM AUTHOR]

Green transformation has become the epoch-making needs of Chinese cities to break through the bottleneck of development. Drawing lessons from the urban development experiences of Jiangsu, Zhejiang and Guangdong provinces in China, this paper provides a practical reference for the urban green transformation in Northeast China. According to the theory of urban metabolism, the paper systematically develops a measurable framework of urban green transformation that covers social, economic and environmental dimensions, and uses a super hybrid model with a window analysis to estimate the dynamic efficiency of urban green transformation. The results present opposite trends between Southeast and Northeast cities in China. Afterwards, the generalized method of moments is used to analyze the impacts of spatial agglomeration and science and education supports on the efficiency of urban green transformation. By contrast, a self-weakening trend of urban green transformation occurs in Northeast China, where the urban size is too small to optimize the industry layout by means of urban value chain, and the return on the investment in science and education is not significant enough, which leads to the lack of impetus for a continuous urban transformation. Therefore, the urban development strategy in Northeast China should center on the urban value chain, and then promote urbanization and industrial restructuring and integration, improving the talent adsorption effect, as well as achieving urban complementary advantages and a differential development. • The coexistence of low speed and poor quality is the main situation of current urbanization in Northeast China. • The Matthew effect of sustained self-weakening in the Northeast is significant. • City scale and brain drain become the fetters of the development in Northeast China. • The key to solve the problem in Northeast China lies in reintegrating the city value chain. [ABSTRACT FROM AUTHOR]

As a new clean and sustainable energy that can reduce carbon emissions, offshore wind energy has received much more attention in recent years. In response to the complexity and flexibility issues in the decision-making process of offshore wind power investment, this paper proposes an investment decision framework based on a bidimensional binominal lattice that embeds deferral options, aiming to derive the appropriate development timing and investment potential for corporate investors in uncertain environment of market and technological development. And the investment model embedding revenue from carbon emission reduction highlights the advantages of clean energy. Furthermore, we creatively compare the policy effects of three subsidy schemes using the model as a policy analysis tool and use scenario analysis to simulate the impacts of dynamic adjustments in subsidies on investment decisions. For the case of an offshore wind power plant in Guangdong province, China, we find that the local government has to provide a subsidy of 0.11 CNY/kWh to allow the project to be profitable. In the absence of subsidies, however, it is preferable to defer the decision of investment with a wait-and-see attitude. Given the same total government financial input, we find that it will be more beneficial for the government to provide R&D subsidy than electricity tariff subsidy and operation subsidy in terms of long-term sustainable development. Our findings also demonstrate that considerations in the carbon trading market will also contribute to the development of offshore wind power. The conclusions of this article can provide valuable guidelines for corporate investors to adjust the appropriate development timing and for policymakers to optimize subsidy allocation, so as to promote the healthy development of offshore wind power and low-carbon transition. [ABSTRACT FROM AUTHOR]

With the rapid urbanization and industrialization, the uneven distribution of polluting enterprises among different socioeconomic groups has become a prominent environmental social problem in transitional China but is rarely recognized. This paper introduces environmental justice theories in industrial location studies. A heuristic analytical framework is proposed to analyze the distribution and determinants of polluting enterprises in Guangdong, China, a highly developed region but with high social and economic inequality. Polluting enterprises are mostly agglomerated in the Pearl River Delta (PRD) region with the rest in the mountainous and hilly non-PRD region. Bivariate local spatial autocorrelation analysis shows the colocation of polluting enterprises and migrants. Our regression results reveal that the county where many migrant residents are concentrated historically appears to attract many polluting firms to enter. However, less firms are found in the county with many highly educated groups and ethnic minorities. Land space planning, environmental regulation, labor costs, and agglomeration economy have driven the distribution of new polluting enterprises, whereas the influences of traffic accessibility and border effect do not work actually. To some extent, the distribution of new polluting enterprises must be recognized as a predictable result of the characteristics of prior demographic distribution. • A heuristic analytical framework is provided to study the distribution and determinants of polluting enterprises. • The characteristics of prior demographic distribution have driven the geography of new polluting enterprises. • The special socioeconomic determinants associated with hukou matter a lot in the Chinese context. [ABSTRACT FROM AUTHOR]

This paper proposes a new prediction method incorporating a set of measuring models applicable to the financing efficiency of China's carbon market to quantify such market's maturity, trading risk coefficient, and financing income. Our theoretical analysis indicates that the price of carbon emission quota essentially affects the financing efficiency of carbon market. While a robust safeguard measure to obtain a respectable income from carbon market financing is the long-term average quota price exceeding the initial quota price. Empirical findings derived from China's emissions trading scheme pilots reveal that these pilots can be divided into the growth-oriented market (i.e. Guangdong whose financing capacity is always significant), the balance-oriented market (i.e. Shanghai and Hubei whose quota pricing mechanisms and the financing level of carbon markets both maturely develop), and the risk-oriented market (i.e. Beijing whose quota price runs at a high-level with an intense financing income volatility). It is therefore achieved that carbon market's maturity level and quota price volatility are both robustly explicable for different financing effects among these pilots. Our key findings show that expanding the coverage of quota trading parties, stabilizing carbon price, and promoting carbon asset management help to improve the financing efficiency of carbon market. • The financing mechanism is analyzed with clarifying its main influence factors. • A stochastic process is used to build a price simulation equation that meets the operation law of China's carbon market. • An income model is built and thus evaluate market financing effect based on price expression and financing mechanism. • The financing effect of China's 8 pilot markets is measured, and thus 3 kinds of development modes are proposed. [ABSTRACT FROM AUTHOR]

The switch of coal to gas in power generation enterprises is of great significance for tackling air pollution and mitigating climate change. Under China's emissions trading system, power generation enterprises have incentives to switch to low-carbon clean power, and the cost-benefit of switching is the basis of their decision-making. To this end, this paper studied the impact of changes in carbon and fuel prices on switching prices. The results show that: (1) For per yuan increase in the amount of natural gas, coal, and carbon, the switching price increased 4.768, decreased 5.845 and decreased 0.9994 yuan, respectively. (2) The carbon price is relatively low, and the impact of it on switching price is small. (3) The fluctuation in the carbon price, coal price and the natural gas price has a hysteresis effect on switching price. [Display omitted] • This study assesses the coal-to-gas switch possibility in Guangdong Province. • A new mode of operation of coal-to-gas switch is published. • For per yuan increase of carbon price, the switching price decreased 0.99 yuan. • The impact of carbon price fluctuations on switching price has a lag effect. [ABSTRACT FROM AUTHOR]

The Chinese government is increasingly concerned about the impacts of climate change mitigation policies on social equity. Carbon pricing is an effective measure for reducing carbon emissions, but its distributional effects may exacerbate inequity among different rural and urban households. As a leading carbon pricing pilot area in China, Guangdong Province is the subject area of this paper. By using the environmentally extended input-output model and calculating the Suits index, this study aims to compare the carbon price payments of ten income-level households in Guangdong Province in 2012 and 2017. The results indicate that higher-income households need to pay more for carbon emissions. Total carbon pricing in Guangdong is slightly progressive, and the progressivity increased from 2012 to 2017. Thus, the implementation of carbon pricing may not intensify the inequality between urban and rural areas and between different income groups. Only carbon pricing on residential energy consumption is regressive, which could be compensated by revenue recycling policies. The findings of this study contribute by offering a positive theoretical basis for China's future policies on carbon pricing such as carbon taxes. • Urban households and higher-income households would bear a greater burden of carbon payment in Guangdong. • Carbon pricing will not exacerbate the original income inequality of different households in Guangdong. • Households in urban areas have higher-carbon lifestyles than rural households. • From 2012 to 2017, the progressivity of carbon pricing increased slightly. • Carbon pricing for direct energy consumption is regressive, so revenue recycling schemes are needed. [ABSTRACT FROM AUTHOR]

With continuous growth of economy and population in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), pressure of resources and environment is increasing. Therefore, sustainable green development of the GBA has attracted more and more attention from society. What is relationship among economy, resource and environment in the GBA? How to balance and analyze relationship between Green Economy and carrying capacity of resource and environment in the GBA? It is an important scientific question facing sustainable development of the GBA. This paper constructs a comprehensive ECC index system for economy - resources – environment with data from statistics yearbooks, calculates weights of indicators by entropy weight method and Ecological Carrying Capacity by TOPSIS model later using C++ programming language. It also carries out exponential smoothing for ECC prediction by SPSS software and coupling coordination of economy - resources - environment system in this area. The results show that the comprehensive ECC of the GBA has an upward trend from 2000 to 2017. In the next five years, Comprehensive Ecological Carrying Capacity of GBA will continue to increase linearly. In the process of GE development in the GBA, the environmental carrying capacity has steadily increased. There is a negative correlation between resource carrying capacity and GE but a positive correlation between environmental carrying capacity and GE. The coordination of economy - resource - environment system in the GBA has been continuously strengthened, and development of economy is advancing towards direction of high resource carrying capacity and high environmental carrying capacity. From perspective of comprehensive ecological carrying capacity to explore the world's two kinds of different political and economic system under comparative analysis of the urban Green Economy development. We found that the Macao and nine cities of the GBA are basically stable but Hong Kong is experiencing tortuous growth with dramatic changes. This research would provide theoretical reference for subsequent development direction of GBA and other bay areas. The future research can carry out deep simulation on the economy - resource - environment dynamics system model and formulate specific development plans. Government departments concerned with development of China's GBA should be committed to reducing pressure on resources, developing new energy and clean energy, while continuing to maintain even increase investment in environmental protection • An Eco-Carrying Capacity evaluation index system of the GBA was constructed to economy-resources-environment. • The comprehensive Eco-Carrying Capacity of the GBA were analyzed. • Coupling analysis of green economy and carrying capacity of resource and environment in the GBA was explored. • Provide comparative analysis under two different political and economic systems of the urban green economic development. [ABSTRACT FROM AUTHOR]

Noncooperative policies for transboundary pollution abatement are inefficient and ineffective, but cooperative policies for pollution abatement are seldom successful in regions that have different development goals and conflicting interests. In this paper, by extracting the key components that lead to the success of pollution reduction policies between Hong Kong (HK) and Guangdong, we aim to construct a general framework for cooperative environmental management. The incentive for and the dynamic trajectory, core measures, and outcomes of cooperative pollution abatement policies to address transboundary air pollution were studied using incrementalism analysis. The context that drives the abnormal increment of cooperative policies between HK and Guangdong was analyzed to determine the factors that affect the full cooperation process. The political union between HK and China is the main driving force for fostering cooperative policies in these two regions that have highly asymmetric economic development levels and pollution emission intensities. The factors for successfully designing cooperative pollution reduction policies are revealed from trust building, political support, efficient governance, precise policies, a rational cost-sharing mechanism, and detailed management and implementation plans. Innovative multi-level and cross-department governance, and an unequal but rational cost-sharing scheme sustain long-term cooperation. A general framework is derived from these empirical key components and constructed as a systematic approach to provide a guide for designing cooperation in transboundary pollution reduction for the sustainable management of cross-border natural resources in different regions with conflicts of interest. • An empirical framework of cooperative air pollution abatement model is constructed. • Factors contributing to foster cooperative polices is analyzed via incrementalism model. • Political support produces adequate institutional arrangements and precise policies. • A matching cost-sharing mechanism can catalyze and stabilize the cooperation model. • Multi-level and cross-department policies sustain long-term cooperation. [ABSTRACT FROM AUTHOR]

With the frequent occurrence of global warming, acid rain, and photochemical smog, nitrogen oxide (NOx) pollution has become an increasingly serious global problem. It is essential to establish efficient approaches for seeking reasonable and practical mitigation pathways. In this paper, a NOx mitigation simulation (NMS) model is developed to facilitate the development of mitigation policies. Through constructing the NOx metabolic network, all sectors are classified according to their interactions. With production-side and consumption-side mitigation strategies adopted for different categories respectively, the changes of sectoral and system-wide indirect emissions are accounted for under the framework of urban metabolism. The results of the case study for Guangdong Province, China, illustrate that the mitigation strategies aimed at the specific sectors of the economy might not be as practical as expected. Both the type of mitigation strategies and the sector category it interferes with have a decisive influence on reduction performance. In Guangdong Province, regulating electricity, heat power generation and smelting, pressing of metals can achieve substantial reduction performance through production-based ways, and supervising the sectors with weak control and strong dependence (e.g., Construction and Other social services) is the most effective measure on the consumption side. The comprehensive mitigation strategies made from production and consumption perspectives are capable of acquiring the most efficient reduction performance. Considering cities as an ecosystem, the mitigation simulation framework established in this study has the potential to assess and formulate reduction policies of NOx emissions. • An urban NOx mitigation simulation model (NMS) is developed. • All sectors are classified according to their ecological interactions. • Different mitigation strategies are adopted for each sector category respectively. • The effectiveness of various strategies for emission reductions is evaluated. • The data analysis is conducted by MATLAB. [ABSTRACT FROM AUTHOR]