Table of Content

20 February 2024, Volume 26 Issue 1

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MEASUREMENT AND TEMPORAL-SPATIAL DIFFERENTIATION OF BEIJING-TIANJIN-HEBEI (JJJ) CITY CLUSTER’S QUALITY DEVELOPMENT

KE Wenlan, LI Wenhui, YAN Jingjing

2024, 26(1):  1-14.  DOI: 10.13776/j.cnki.resourcesindustries.20240016.003

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China is entering a new era with its economy turning to quality development from rapid growth. JJJ, as a new capital economic zone, plays a key role in demonstrating city cluster’s quality development. This paper, aiming at JJJ’s coalition in developing strategy for a quality city cluster’s quality development, this paper, based on JJJ"s 13 perfectures’ 2011 to 2020 data, uses the contents of quality development to establish a comprehensive evaluation index system for JJJ city cluster’s quality development, and employs entropy-TOPSIS model to estimate JJJ city cluster’s 2011 to 2020 quality developing index, and applies coupling coordination model & spatial autocorrelation model to study its coupling coordinating level, temporal-spatial evolutionary trend and spatial concentrating effect.The coupling coordination of JJJ city cluster’s quality development shows a weak-then-strong trend, with major cities in coordination in 2011 to 2015 changing to developing cities, at a decreasing coupling coordination, but rising after 2015. The coupling has been steadily rising, 84% of JJJ’s cities are rising in their coupling, most with strong correlation among economy, eco-environment, innovation, and civilian welfare. Temporal-spatial pattern of coordination has not changed, Cangzhou, Tianjin, Tangshan and Qinhuangdao have always been at the tier 2 except Beijing seats atop. Spatial evolutionary pattern of quality development suggests Beijing, Tianjin and Langfang are in the core area of city cluster’s quality development, radiating outward to southeast, falling toward northeast. Economy, eco-environment innovation and civilian welfare are the same. JJJ’s city cluster’s quality development has a positive overall auto-correlation, cities of high quality development are geographically closer, with outstanding spatial heterogeneity, their capitals are mainly located in the promoting area, Cangzhou, Hengshui and Qinhuangdao in the transition zone, and Langfang in the radiation zone, negatively correlated. A key mission for JJJ’s city cluster’s quality development is to make up the regional developing gap. This paper presents suggestions on accelerating industrial transformation to diminish regional gap, intensifying environmental cooperation to promote green development, activating regional resources to drive innovation, and jointly constructing public services to share the dividends.

CHINA’S 2012 TO 2021 INDUSTRIAL DEVIATION BASED ON IMPROVED THEIL INDEX AND SHIFT-SHARE MODEL

GAO Xiaowei, ZHANG Yingkun, LI Hua, et al.

2024, 26(1):  15-24.  DOI: 10.13776/j.cnki.resourcesindustries.20231212.002

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Overviews over references reveal that defects are existing in traditional industrial deviation E coefficient, Theil Index and Shift-Share model. Defects in E coefficient and Theil Index are in calculating principles, and those in Shift-Share model are in rationality of selecting reference system and feasibility of data collection. This paper presents an improved model that is used to study China’s 2012 to 2021 industrial deviation via cases. It concludes that China’s industrial deviation is diminishing. According to the corrected model and combined with the current global environment, this paper suggests that the first industry rely on scientific innovation to promote rural labors’ orderly migration between urban and rural areas and to materialize agricultural scale and modernization, that the second industry needs to be upgraded to reach and maintain an independent and complete industrial system, to inputs more in basic research to outbreak western technical blockage, that the third industry be focusing on financing and scientific education, increasing Hongkong, Shanghai and Beijing’s positions in world financing center, using financial innovation to avoid unfavorable constraints and impacts from global financing system, practicing the strategy for invigorating the country through science and education and exploring educational modes appropriate China’s situation from primary school to university stages.

THE ECONOMIC IMPACTS AND VARIATIONS IN ENERGY STRUCTURE ADJUSTMENT UNDER CARBON NEUTRALITY TARGET IN THE YANGTZE RIVER DELTA REGION

WANG Lixiang, WANG Jianmin

2024, 26(1):  25-34.  DOI: 10.13776/j.cnki.resourcesindustries.20240016.001

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The 20^th Report presented an objective of carbon peaking and neutralization. Energy structural adjustment is a vital means to reach carbon neutralization. This paper, based on their symbiosis of carbon emission and economic growth, incorporates economic quality development into carbon neutralization objective. In terms of their 2017 inputs/outputs of three province and one city in Yangtze River delta, this paper establishes a regional macro- and microscopic SAM table and CGE model, and sets up a macroscopic economic closed system, which are used to study the impacts and variance of energy structural adjustment on Yangtze River delta’s economy. As energy structural transformation advances, its economic impacts vary. In Jiangsu province, when clean energy has been replaced at 5%, 10%, 15% and 20%, the economic impacts of multiple indicators gain a biggest loss at 5%, loss at 10% less than at 5% and 15%. Economic dependance on fossil fuels varies with location, less in Anhui and Shanghai, then Jiangsu, and Zhejiang receives the biggest impacts. Economic impacts waves as energy structural adjustment moves forward. When Jiangsu’s clean energy is replaced at 10%, economic impacts of most indicators from agricultural, manufacturing, servicing, GDP and governmental income are less than when clean energy is replaced at 5% and at 15%. Energy structural adjustment is a critical approach to carbon neutralization in Yangtze River delta and even nationwide.

IMPACTS OF NEW ENERGY VEHICLE INDUSTRIAL AGGLOMERATION ON REGIONAL GREEN ECONOMIC EFFICIENCY BASED ON A CASE STUDY ON YANGTZE RIVER ECONOMIC ZONE

YANG Kaijun, CAO Anqi, FANG Cihui

2024, 26(1):  35-49.  DOI: 10.13776/j.cnki.resourcesindustries.20231213.002

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This paper incorporates industrial agglomeration, green technical innovation and green economic efficiency to study the impact of new energy vehicle industrial agglomeration on green economic efficiency in Yangtze River economic zone, aiming at offering references for China to reach strategic objectives of manufacturing power and to develop new energy vehicles in Yangtze River economic zone under the dual-carbon settings. This paper, based on 11 provinces/cities’ 2012 to 2020 panel data along Yangtze River economic zone, uses super-efficiency SBM and locality entropy to establish a measuring model, which is employed to study impacts of new energy vehicle industrial agglomeration on green economic efficiency. And discusses mediating effects of green technical innovation. The spatial overflowing effects and regional heterogeneity of new-energy vehicle industrial agglomeration on green economic efficiency also were analyzed. The entire Yangtze River economic zone has become a zoned new energy vehicle industrial agglomeration area, with its agglomerating level fluctuating up over years, and increasing from down- to upper-stream with growing variance. New energy vehicle industrial agglomeration promotes the green economic efficiency in Yangtze River economic zone through consolidating internal network resources and boosting external entire capabilities. Development of industrial agglomeration promotes green technical innovation through competition and cooperation, and development of green technical innovation can also boost economic drives and efficiency, proving its mediation between industrial agglomeration and green economic efficiency. New energy vehicle industrial agglomeration has spatial overflowing on green economic efficiency, varying among upper-, middle- and down-stream. This paper presents suggestions on enhancing industrial clustering construction to play a role in the long-term mechanism of new energy vehicle industry, boosting green technical innovation system and advancing regional heterogeneity of new energy vehicle.

NEW URBANIZATION AND GRAIN SECURITY IN MAJOR GRAIN PRODUCING AREAS BASED ON MEADIATING EFFECTS OF LAND SCALING OPERATION

HUA Jian, YANG Mengyi, CAO Huimin

2024, 26(1):  50-60.  DOI: 10.13776/j.cnki.resourcesindustries.20231213.001

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New urbanization has become the key means to reform urban-rural dual structural and to transform agricultural producing ways in major grain-producing areas under the new era developing background. This paper, based on 2007 to 2021 provincial panel data of China’s 13 major grain-producing areas, uses entropy to estimate China’s grain security level from perspective of industrial chain, applies new urbanization contents to establish a multiple-dimensional index system that is composed of population, economy, society and space, which is employed to estimate the new urbanization level and to study its impacts on grain security, and applies land scaling operation as mediating variable to study the mechanism of new urbanization and its dimensions on grain security. New urbanization largely boosts grain security in major grain-producing areas, and land scaling operation plays a mediating effect amid new urbanization works on grain security. Dimensional heterogeneity suggests that population urbanization and spatial urbanization play an outstandingly positive role on grain security, during which land scaling operation plays a partial or total mediating effect. This paper presents suggestions on boosting new urbanization, and encouraging land scaling operation, and making appropriate strategy from population, economy, society and spatial urbanization as a long-term approach for the major grain-producing areas.

TEMPORAL-SPATIAL EVOLUTION OF WATER WORKS RESORTS AND SPATIAL STRUCTURAL OPTIMIZATION OF WATER WORKS TOURISM IN YELLOW RIVER STREAM

GUO Suting, DONG Shuxia, WU Yining

2024, 26(1):  61-74.  DOI: 10.13776/j.cnki.resourcesindustries.20240016.002

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This paper, aiming at promoting a coordinated development of water works tourism in Yellow River stream, uses gravity center standard deviation ellipse, kernel density and exploring spatial data analysis method to study the temporal-spatial evolution of water works resorts in 2009, 2014, and 2021 in Yellow River stream, and combines “point-axis” theory with central function index and gravity model to define the development nodes, axis and plates in water works tourism. Development of water works resorts in Yellow River stream has 3 stages. Resorts are spreading along E-W and S-N with gravity center shifting to southwest. Their distributing density shows scattering in the upper-stream and concentrating in the middle- and down-stream, high density concentrating areas are located along banks of Yellow River, Weihe River, Fenhe River and Qinhe River. Their spatial distribution generally displays a strongly positive correlation, “high-high” concentrating in Shandong province, “low-low” in Hehuang valley and partial Gansu province. Hotspots in Yellow River stream remain unchanged, while the cold spots are concentrating toward the upper-stream, and the sub-hotspots migrating to the northwestern middle-stream. Spatial structure after being optimized is composed of three levels of water works tourism development nodes, two levels of development axes and five development domains. This paper presents suggestions on differentiating domain variance, optimizing spatial pattern of water works tourism from construction status, water resources, geographic characteristics and social-cultural environment. And improving transportation, consolidating water works tourism, boosting radiation of node cities.

GREEN CREDIT POLICY, ESG PERFORMANCE AND CAPITAL STRUCTURAL ADJUSTMENT OF HIGHLY-POLLUTING FIRMS

DONG Yue, PAN Haiying

2024, 26(1):  75-85.  DOI: 10.13776/j.cnki.resourcesindustries.20231219.002

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Green credit policy as a vital means to remove structural leverage is much helpful for highly-polluting firms to upgrade their capital structures. ESG focusing on environment, social and governance can impact highly-polluting firms’ capital structure adjustment. This paper, based on China’s A-listed 2011 to 2020 highly-polluting firms’ ESG performance, studies the effects of green credit policy on capital structural adjustment of highly-polluting firms. Green credit policy largely promotes the capital structural adjustment of highly-polluting firms, more for high debit firms than low debit firms. Green credit policy can enhance highly-polluting firms’ ESG performances, which can weaken the effects of green credit policy on capital structural adjustment of highly-polluting firms. Implementing effects of heterogeneity of financing constraints and commercial credit on green credit policy show that green credit policy can largely boost their capital structural adjustment of highly-polluting firms with strong financing constraints and low commercial credits compared to with weak financing constraints and high commercial credits. Relation between green credit policy and capital structural adjustment of highly-polluting firms plays a big role in optimizing credit resource allocation and pushing green transformation of highly polluting firms.

TEMPORAL-SPATIAL EFFECTS OF DIGITAL ECONOMY ON HIGH-QUALITY ECONOMIC DEVELOPMENT BASED ON GTWR MODEL

YIN Qingmin, LIN Yinyin

2024, 26(1):  86-99.  DOI: 10.13776/j.cnki.resourcesindustries.20231219.005

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As digital technologies and digital industries are advancing, digital economy becomes a new drive to a high-quality economic development. Study on their relation is of strategic importance in promoting provincial high-quality economic development. This paper, by means of China’s 30 provinces/cities’ 2014 to 2020 panel data, uses entropy weighted TOPSIS to comprehensively score digital economy and high-quality economic development, applies spatial auto-correlation test and hotspot to analyze their spatial distribution on the basis of their temporal-spatial instability, and employs GTWR model to discuss their temporal-spatial response law between digital economy and China’s provincial high-quality economic development, and analyzes the path of digital economy to a provincial high-quality economic development. Digital economy has a strong spatial auto-correlation with high-quality economic development, with their hotspots concentrating on central and eastern China, and cold spots on western China. The spatial concentrating intensity of digital economy is diminishing while that of the high-quality development is maintained at a high level. Digital economy can outstandingly promote a high-quality economic development with impacting factor of temporal-spatial heterogeneity, showing a declining trend from south-eastern coastal to northwestern continent spatially, and a diminishing provincial difference to regional coordinated development. Digital economy variably drives the sub indicators of high-quality economic development, weakest on innovative development. This paper presents suggestions on further advancing regional coordinated development of digital economy in western China, promoting high-quality economic development through innovation, and promoting provincial high-quality development through digital economy. 

MECHANISM OF ECONOMIC TRANSFORMATION ON INCREASING GREEN DEVELOPMENT EFFICIENCY IN RESOURCES-BASED AREAS: A CASTE STUDY ON SHANXI PROVINCE

LI Huitao

2024, 26(1):  100-112.  DOI: 10.13776/j.cnki.resourcesindustries.20240018.001

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Chinese-style modernization requires resources-based areas improve green development efficiency through economic transformation. This paper gives a summary of contents of economic transformation and green development efficiency in resources-based areas, and uses economic growth theory to study the mechanism and impacts of economic transformation on green development efficiency in resources-based areas, and employes non-desired-output super-efficiency SBM-Malmquist model and broken-tail regression model to study Shanxi’s 2004 to 2020 green development efficiency changes, and its mechanism of economic transformation on green development efficiency. It concludes that Shanxi’s economic transformation promotes its green development efficiency, mainly through adjusting industrial structure, saving energy and reducing consumption and advancing technology, little though its private economic development and infrastructures. This paper presents suggestions on enhancing & supervising private firms’ green transformation, implementing leading roles of transportation and communication, optimizing green technical innovation system and deepening market reform and management.

SPATIAL IMBALANCE AND DYNAMIC EVOLUTION OF CHINA’S LOW-CARBON ENERGY CONSUMPTION STRUCTURE

MA Hailiang, GAO Jie, JIN Ruiqi et al.

2024, 26(1):  113-123.  DOI: 10.13776/j.cnki.resourcesindustries.20231212.001

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It is a key step to study China’s low-carbon energy consumption structural trend and to measure its spatial imbalance in advancing energy reform and green development. This paper, based on 2003 to 2020 energy consumption panel data of Chinese provinces/cities, uses Theil Index and spatial auto-correlation to study spatial imbalance and dynamic evolution of China’s low carbon energy consumption structure. The low carbon index of China’s energy consumption structure generally shows a rising trend, up 5.862 in 2020 from 5.298 in 2003. The spatial imbalance of China’s low carbon energy consumption structure is weak, in a rising-then-declining trend indicated by Theil Index. Regional low-carbon energy consumption structure variance largely impacts the overall difference. China’s low-carbon energy consumption structure is of obvious spatial positive correlation with spatial concentrating effect, relatively stably in overall spatial pattern, high-high concentrating in Jiangsu-Zhejiang-Shanghai, weak-weak in southwest and central China. This paper presents suggestions on constructing regional interest union by mutually cooperation, on advancing industrial structure to stimulate social innovation and market, and on optimizing energy industry structure to push energy consumption transformation.

VIEWS AND PRACTICES FROM CONSTRUCTING “MOUNTAIN-RIVER-FOREST-FARMLAND-MICROORGANISM” LIFE COMMUNITY TO PROMOTE LIQUOR-MAKING INDUSTRY’S QUALITY DEVELOPMENT

DING Xiongjun, WANG Li, WEI Yuan et al.

2024, 26(1):  124-132.  DOI: 10.13776/j.cnki.resourcesindustries.20240026.002

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This paper innovatively incorporates microorganism in life community of “mountain-river-forest-farmland-lake-grassland-sand”, combines with regional features and liquor-making industry, and presents the concept of “mountain-river-forest-farmland-microorganism” through the path of “increasing water-improving atmosphere-protecting soil-preserving microorganisms-maintaining ecosystem balance”. Scientifically establishing “water use and management system” in the source to create Maotai Water Circulation Mode of Chishui River. Systematically maintain biodiversity in the source areas to construct a sound management system. Protect soil resources in the brewing areas and key functioning areas to improve ecological barrier. Boost microorganisms test and research in the core area and strictly control inputs of external microorganisms. Implement microscopic eco-environmental carrying capacity in the core area to prevent environmental pollution and to thoroughly protect “mountain-river-forest-farmland-microorganism” ecosystem balance, and to increase ecosystem stability in the producing areas. This paper studies the situation and issues in ecological harness in Maotai’s core brewing areas, presents path and zonation plans, and puts forward 87 detailed restoring projects of 5 categories for the brewing industry and Chishui river’s ecological protection. This paper is a good attempt and practice to the life community of  “mountain-river-forest-farmland-lake-grassland-sand”, helpful to construct an eco-environmental flagship in the liquor-making industry, and offers references for high standard protection and quality development of liquor-making industry.

ECOLOGICAL FOOTPRINT DYNAMIC MODELLING AND MEASUREMENT OF LOESS PLATEAU VALLEY BASED ON ARIMA MODEL: A CASE STUDY ON LANZHOU CITY

YU Wenbao

2024, 26(1):  133-140.  DOI: 10.13776/j.cnki.resourcesindustries.20231219.004

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To explore the causes of eco-footprint dynamic changes from perspective of economic development, this paper measures the developing path of the per capita ecological footprint from 2002 to 2014 in Lanzhou, a loess plateau valley city, uses ARIMA model to forecast its ecological footprint changing trend from 2015 to 2020. The per capita ecological footprint is rising from 2.70 hm² in 2002 to 4.25 hm² in 2014, increase of 1.57 times. And the rising rate of the per capita ecological footprint reaches to 4.04%, 7.84% lower than its GDP’s growing rate 11.88%, suggesting Lanzhou’s economic development speed is higher than speed of resources and environmental consumption. The per capita ecological footprint of Lanzhou from 2015 to 2020 still shows a rising trend, forecasted to reach up to 4.48 hm², 4.61 hm², 4.75 hm², 4.89 hm², 5.02 hm² and 5.17 hm², with an enlarging ecological deficit. Lanzhou’s gross ecological footprint is 19.59 times of the total area of urban land use, indicating a strong correlation between economic growth and ecological demands,indicating the inflection point of Environmental Kuznets curve doesn’t take place, implying a unsustainable status. This paper presents a path to decreasing Lanzhou’s ecological footprint from adjusting industrial structure, decreasing ecological deficit to promote economic quality and sustainable capacity, advancing green development, and constructing an ecological network of ecological diversity, appropriate layout, full-functional integration of natural ecosystems and rural-urban union to increase eco-environmental capacity.

MEASUREMENT AND TEMPORAL-SPATIAL PATTERN EVOLUTION OF CARBON SEQUESTRATION AND VALUES OF SHAANXI’S ECO-SYSTEM

HUANG Xin, HAN Ling, MA Chaoqun

2024, 26(1):  141-153.  DOI: 10.13776/j.cnki.resourcesindustries.20231219.001

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Functional carbon sequestration of eco-system is one of key ways to carbon neutralization. This paper, from perspective of land use, uses carbon sequestration rating to estimate the 2000 and 2020 carbon sequestration and values of Shaanxi’s county-level forest, grasslands and wetlands ecosystems, and applies spatial statistics to reveal its temporal-spatial evolution. During 2000 to 2020, their carbon sequestration has increased at different levels, of which forest increased the most as the biggest contributor to Shaanxi’s eco-system. Carbon sequestration of Shaanxi’s county-level forests and grasslands is of outstandingly spatial clustering, carbon sequestration hotspots of forests are concentrating in Qinling mountainous area, that of grasslands in northern Shaanxi’s Great Wall Windy & Sandy Area, cold spots are all concentrating in Guanzhong plain. Southern Shaanxi’s Qinba mountainous area has the most capability in carbon sequestration, while northern Shaanxi’s loess hilly valley has the biggest increment. All cities have increased their carbon sequestration except Xi’an, Yan’an and Yulin are the top two in growth. The top 5 cities in carbon sequestration values in Shaanxi’s eco-system are Hanzhong, Yan’an, Ankang, Baoji and Shangluo, amounting to 78.33% of the entire province.

EVOLUTIONARY GAMING ANALYSIS ON ECOLOGICAL COMPENSATION OF WATER TRANSFERRING PROJECTS BASED ON MULTIPLE STAKEHOLDERS

LIU Linling, LIU Hongqin, TAN Lifeng

2024, 26(1):  154-161.  DOI: 10.13776/j.cnki.resourcesindustries.20240026.001

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Highly-frequent extreme weather catches all eyes on eco-environment. A coordinated and sustainable development between human and nature is an unavoidable way to China’s high-quality development. Water transferring projects are designed to mitigate water resource imbalance among areas, and water transferring projects trans-streams may involve multiple stakeholders, that makes ecological compensation a necessary guarantee for their sustainable development. This paper, based on a case study on Niulan River-Dianchi Water Replenishing Project, establishes a gaming model, macroscopically and microscopically, to study multiple stakeholders’ gaming mechanism regarding ecological compensation situation and issues. Macroscopically, spontaneous gaming between water-supplying areas and water-receiving areas can not reach a ecologically evolutionary balance, which needs to be intervened by upper administration on complaining cost, allowance and anticipated valuation of water-supplying areas. Microscopically, evolutionary gaming among governments, firms and the public is influenced by harness fee, governmental compensation and punishment strength. Simulation of Niulan River-Dianchi Water Replenishing Project indicates an evolutionary trend of protection of Niulan River, uncompensated Dianchi, and no supervision from upper administration. Dianchi is impacted by its compensation and complaining, and upper administration is impacted by punishment fines for Dianchi and higher administration’s and costs. This paper presents suggestions on widening financing ways, improving complaining-responding system, adopting governmental supervision and control amid water-transferring projects’ ecological compensation for their sustainable development.

HEILONGJIANG’S INDUSTRIAL CARBON EMISSION SCENARIOS AND PEAKING PREDICTION BASED ON STIRPAT MODEL

HE Letian, YANG Yongqi, LI Rong, et al.

2024, 26(1):  162-172.  DOI: 10.13776/j.cnki.resourcesindustries.20231212.003

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Study on carbon emission factors and scenario prediction of Heilongjiang’s industrial sectors is of significance to reach Heilongjiang’s green low-carbon development under the background of carbon peaking and carbon neutralization. This paper uses IPCC to estimate Heilongjiang’s historical industrial carbon emission, and applies extended STIRPAT model to determine the six variables from population, economy and technology, square of GDP per capita, population scale, gross industrial production, industrial energy consumption, energy consuming efficiency and energy structure, and employes ridge regression to establish a carbon emission factor model by removing the multi-collinearity of independent variables. This paper also studies Heilongjiang’s social and economic reality from economic development, population scale, energy consumption and energy consumption efficiency, and determines the increment of independent variables combined with macroscopic policies, and predicts its 2020 to 2050 Heilongjiang’s appropriate industrial carbon emission under three scenarios, benchmark, low-carbon and highly-energy-consuming. Heilongjiang’s industrial low-carbon development is facing a huge demand for fossil energy and insufficient energy conversion efficient. Among the six factors impacting industrial carbon emission, square of GDP per capita, gross industrial production, industrial energy consumption and energy structure promote its industrial carbon emission, of which industrial energy consumption works the most, while population scale and energy consuming efficiency play on the contrast. Heilongjiang’s industrial carbon emission shows an increasing-then-decreasing evolutionary trend under the all three scenarios, varying in peaking time and heights, 71.35 millions tons in 2030 under the low-carbon scenario, 89.97 millions tons in 2035 under the benchmark scenario, and 123.68 millions tons in 2045 under the highly-energy-consuming scenario. This paper presents suggestions on largely adjusting industrial energy use structure, focusing on energy technical conversion and upgrade, and perfecting low-carbon green policies.

TEMPORAL-SPATIAL ANALYSIS AND OPTIMIZATION STRATEGIES OF HIDDEN CARBON EMISSION OF SHANXI CROSS-PROVINCIAL TRADE

LIANG Jinghua

2024, 26(1):  173-181.  DOI: 10.13776/j.cnki.resourcesindustries.20231219.003

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Hidden carbon emission in cross-provincial trade has vital impacts on regional gross carbon emission and coordinated development, a key factor needed to be considered when planning carbon trade and reaching “carbon peaking” and “carbon neutralization” objectives. This paper uses multiple regional input/output model on hidden carbon in cross-provincial trade and China’s 2012 and 2017 input/output data to study the temporal-spatial changes of hidden carbon emission of Shanxi cross-provincial trade, and employes carbon-transferring-responsibility-sharing to estimate Shanxi’s responsibilities in hidden carbon emission amid its cross-provincial trade, and applies structural method to analyze the factors impacting hidden carbon emission changes in Shanxi’s cross-provincial trade. Shanxi’s net-transferred-in hidden carbon emission has increased by 12.490 kt during 2012 to 2017, while its net-transferred-in provinces numbers dropped to 25 from 28. Those having less net-transferred-out are concentrating in northwestern and southwestern China. Structural analysis suggests scaling effect be the leading factor increasing transferred-in and -out of Shanxi’s hidden carbon emission. This paper presents suggestions on optimizing Shanxi’s hidden carbon emission policies of its cross-provincial trade.