Secondary Industry Research Articles

Innovation policy and ecological welfare performance: evidence from a quasi-natural experiment of China.

The National Innovative City Pilot Policy (NICPP) is a policy implemented by the Chinese government to create an environment conducive to innovation, optimize industrial structure, promote economic development, and stimulate green innovation. The impact of this policy on ecological welfare performance is a question worth exploring. Based on panel data from 285 cities from 2007 to 2021, this paper uses the multi-period difference-in-difference (DID) model, propensity score matching method, and spatial DID model to study the impact of NICPP on ecological welfare performance and spatial spillover effects. The results show that (1) NICPP can significantly improve ecological welfare performance. (2) The mechanism analysis found that NICPP mainly improves ecological welfare performance through technological innovation investment, industrial structure upgrading, and increasing government attention. (3) The heterogeneity analysis found that NICPP has a more substantial driving effect on the ecological welfare development of cities in the eastern and western regions, cities with higher administrative levels, and cities with lower secondary industry agglomeration. (4) Further research has found that NICPP not only promotes the development of local ecological welfare but also has a positive spatial spillover effect on the ecological welfare performance of neighboring regions. This paper enriches the research on the effects of NICPP and provides policy references for the sustainable development of cities.

Spatiotemporal Variation and Development Stage of CO2 Emissions of Urban Agglomerations in the Yangtze River Economic Belt, China

As the world’s largest developing country, China has played an important role in the achievement of the global CO2 emissions mitigation goal. The monitoring and analysis of CO2 emissions in the Yangtze River Economic Belt (YREB) urban agglomerations is strategic to the carbon peak and carbon neutrality in China. In this paper, we revealed the spatial and temporal variations of CO2 emissions in Cheng-Yu urban agglomeration (CY-UA), Yangtze River Middle-Reach urban agglomeration (YRMR-UA), and Yangtze River Delta urban agglomeration (YRD-UA) in YREB and investigated the carbon emission development stage of YREB urban agglomerations. Particularly, a carbon emission development stage framework that considered the relationship between economic growth and carbon emissions was built based on Environmental Kuznets Curves (EKCs). Meanwhile, multiscale geographically weighted regression (MGWR) was used to analyze the impact of different influencing factors, including population (POP), GDP per capita (GDPPC), the proportion of secondary industry (SI), carbon emission intensity (CI), and urbanization (UR), on the CO2 emissions of three urban agglomerations. The results illustrate the following: (1) The CO2 emissions of YREB urban agglomerations decreased, with YRD-UA having the highest CO2 emissions among the three urban agglomerations and contributing 41.87% of YREB CO2 emissions in 2017. (2) CY-UA, YRMR-UA, and YRD-UA reached the CO2 emissions peak in 2012, 2011, and 2020, respectively, all of which are at the low-carbon stage. (3) POP and GDPPC show the greatest impact on the CO2 emissions of the three YREB urban agglomerations.

Analysis of the non-linear impact of digital economy development on energy intensity: Empirical research based on the PSTR model

With the rapid development of digital technologies, digital economy (DE) gradually plays a crucial role in changing the pattern of economic and social development. However, the relationship between the DE and energy intensity is still unclear. To fill this gap, this investigation firstly evaluates the development level of the DE of 30 provincial regions in China from 2013 to 2021. Then the non-linear relationship between the DE development and energy intensity is investigated based on the panel smooth transition (PSTR) model taking real GDP, urbanization rate, the proportion of the secondary industry in GDP, R&D funds for industrial enterprises above designated size, and foreign direct investment as transformation variables. The empirical analysis testifies that the DE development can promote the energy intensity and the relationship between the DE development and energy intensity tends to be an invert U shape under the influence of five transformation variables. Values of conversion variables in most provincial regions have not cross thresholds. Especially, the influence coefficients of the DE development on energy intensity have great space to decline under the impact of urbanization rate and the proportion of the secondary industry in GDP. Therefore, the industrial structure should be continuously optimizing and the process of green urbanization should be accelerating. Moreover, it is necessary to stimulate the integration of digitalization technologies and energy system so as to improve energy allocation efficiency and realize energy conservation and emissions reduction.

The Promoting Role of Rural Collective Property Right System Reform on Farmers' Income Increase

Document No. 1 of the Central Committee in 2023 pointed out that it is necessary to give farmers fuller property rights and interests, consolidate and improve the results of the reform of the rural collective property rights system, build an operating mechanism with clear property rights, scientific governance structure, sound management and reasonable distribution of proceeds, explore diversified ways to develop a new type of rural collective economy such as contracting out of resources, renting out of properties, providing intermediary services, and participating in assets, continue to deepen the reform of the collective forest rights system, and deepen the pilot demonstration of comprehensive rural reforms. system reform, and further promote the pilot demonstration of comprehensive rural reform. This paper starts from the reform of rural collective property right system, takes Anhui Province as an example, and studies the promotion effect of the reform of rural collective property right system on farmers' income in Anhui Province. The study concludes that: First, the reform of the rural collective property right system clarifies the ownership of collective assets, quantifies the collective assets into shares, and increases the property income of farmers. Secondly, the reform has led to changes in the structure of rural employment, with a large number of rural residents shifting their employment from the primary industry to the secondary and tertiary industries, and increasing their wage income. Third, the reform has broadened the farmers' business mode, optimized the business model, making the farmers' operating income increase. At the same time on the implementation of the reform of collective property rights system in Anhui Province and the actual situation of Anhui Province's own economic development, put forward relevant policy recommendations.

Carbon Emission Efficiency and Reduction Potential Based on Three-Stage Slacks-Based Measure with Data Envelopment Analysis and Malmquist at the City Scale in Fujian Province, China

Increased carbon emissions led to extreme weather, global warming, and other environmental problems. In order to control energy input and reduce carbon emissions, this study first combines a three-stage Slacks-Based Measure with Data Envelopment Analysis (SBM-DEA) and uses the Malmquist index to quantify energy consumption at the city scale and the related carbon emission efficiency in Fujian Province for the period 2015–2020. Second, we explore the carbon reduction potential on the city scale from the perspective of improving carbon emission efficiency. Our results demonstrate that (i) the carbon emission efficiency of the nine cities increases overall in the first stage, when technical efficiency approaches the efficiency frontier state and efficiency shortage is mainly caused by the lack of pure technical efficiency. (ii) Regression by stochastic frontier analysis in the second stage reveals that the secondary industry correlates positively at 1% significance with fossil energy consumption and power consumption, indicating that the carbon emission efficiency decreases as the secondary industry increases. (iii) Putian and Xiamen reduced their carbon emission efficiency in the third stage due to (a) the input redundancy of fossil energy and social power consumption and (b) excessive undesirable output carbon emissions. (iv) There were improvements in carbon emission efficiency peaks in 2015, with Longyan, Ningde, and Sanming improving by about 50%. This improvement then decreased up to the year 2020, when the improvement in the carbon emission efficiency of Ningde and Zhangzhou was 6.02% and 9.50%, respectively, and that of all other cities was less than 1%. Therefore, we suggest that carbon emission reduction in the future can be further improved by improving technology, optimizing industrial structure, and various other ways to further improve carbon emission efficiency.

The Rural Shift Towards a Learning Society: A Study on the Transformation

Based on the current national strategy of rural revitalization and the reality of rural areas, this paper presents a preliminary exploration of the transformation towards a learning society in rural areas. It points out that contemporary rural society has the characteristics of interactivity. The agricultural transformation in rural China, as well as the innovation and development of the secondary and tertiary industries, the exploration of cultural values in rural areas, and the participation of diverse stakeholders are all new opportunities for the construction of a rural learning society under the background of urban-rural integration.

Inferring the role of fiscal decentralization and carbon taxes through the ARDL approach

Abstract This paper first introduces the algorithmic steps of the ARDL model, explores the long-run relationship of variables using the cointegration test and estimates the long-run relationship, and then builds an error correction model to explore the short-run relationship in the model to estimate the model coefficients. Finally, we analyze the changes in carbon emissions and the relationship between carbon emissions and economic growth in China in time and space, respectively, and use the ARDL model to empirically test the correlation between fiscal decentralization and carbon tax Between 1978 and 2004, the growth rate of the economy remained above 10%, and the growth rate of carbon emissions also increased rapidly at this time, and carbon emissions were positively correlated with economic growth, and the growth rate of economic growth was positively correlated with the growth rate of carbon emissions. The growth rate of carbon emissions is positively correlated with economic growth, and the trend of the growth rate of economic growth and carbon emissions is roughly the same. The coefficient of fiscal decentralization degree on carbon tax expenditure is inhibited at a 1% significant level. The coefficient of the industrial structure plays a catalytic role in carbon tax expenditure at a 1% significant level, and for every 1% unit decrease in the proportion of secondary industry to GDP, carbon tax expenditure decreases by 2.473%. The implementation of a carbon tax can achieve the goal of energy saving and emission reduction, but we should also pay attention to the possible counter-effects of a carbon tax on economic development and reasonably levy carbon tax to make the economy and environment reach a balanced state.

High-Speed Rail and Industrial Agglomeration: Evidence from China’s Urban Agglomerations

This paper explores the relationship between high-speed rail (HSR) and industrial agglomeration within urban agglomerations. The paper selects the data of the Beijing–Tianjin–Hebei Urban Agglomeration (BJHUA) and Central Plains Urban Agglomeration (CPUA) from 2002 to 2016 as the research object. The time-varying difference-in-difference (TVDID) model is innovatively applied to analyze the impact of HSR on the agglomeration of secondary and tertiary industries in urban agglomerations, and the industrial agglomeration effects of the two urban agglomerations are compared. The results show that the influence of high-speed railways on the industrial agglomeration of urban agglomerations is heterogeneous. In the BJHUA, the impact of HSR on the agglomeration of secondary and tertiary industries is not particularly significant. On the other hand, in the CPUA, HSR does not have a significant impact on the agglomeration of secondary industry. However, it does have a significant negative effect on the agglomeration of tertiary industry. In addition, further analysis reveals significant variations in the impact of HSR on the agglomeration of industries within urban agglomerations after excluding the central cities. It is important to note that the impact of HSR on regional industries can be complex and multifaceted. The findings enrich the theoretical understanding of the relationship between HSR and industrial agglomeration.

Cooperation and Competition

Abstract This paper discusses relations between South Africa and Southern Rhodesia from 1939 to 1948. The article begins in 1939 when the outbreak of the Second World War brought mixed fortunes for the two neighbours. For Southern Rhodesia, which relied mainly on imported manufactured goods from the United Kingdom, the war induced shortages resulting in huge domestic demand. Shortages stimulated calls for local industry to fill the vacuum. Consequently, an import substitution industrialisation (ISI) drive developed. In addition to the ISI, South Africa, which had a comparatively established secondary industry by the time the war broke out, increasingly became an essential source for Southern Rhodesian imports. This, however, was not without its challenges. Southern Rhodesia’s economic interest groups often raised complaints against South Africa’s economic competition and its threat to the Rhodesian economy. Nonetheless, Pretoria and Salisbury worked closely and found ways to ease the challenges. By 1948, the end date of the paper, Southern Rhodesia and South Africa’s relationship had resulted in the signing of a Customs Union Agreement. Thus, the article demonstrates, thematically and chronologically, that relations between the two countries evolved through cooperation and competition during the Second World War until the onset of Apartheid in South Africa and the Customs Agreement. The paper relies on primary material from the Zimbabwean and South African archives comprised of correspondences of Customs Agreements negotiations, economic policies and relations, and Parliamentary debates.

Crossing the cross-subsidy: Evidence from China's electricity sector

Electricity cross-subsidy poses a challenge to the reform of China's electricity system in terms of marketization. This paper measures the size of electricity cross-subsidy in China and examines the impact of eliminating it using the CGE model. In addition, we calculate a compensation variance so that household welfare is not affected. The results show the sum of cross-subsidy was 392.34 billion CNY, of which the subsidies from secondary and tertiary industries were 308.73 and 83.61 billion CNY. If the cross-subsidy were eliminated, GDP, exports, interest rates, and most sectors' output would increase, but the price level would also rise.

Digitalization Driving High-Quality Converged Development of Rural Primary, Secondary, and Tertiary Industries: Mechanisms, Effects, and Paths

The convergence of rural primary, secondary, and tertiary industries is an effective way to establish a modern rural industrial system. The digital transformation of rural industries is a new idea to promote high-quality converged development. This paper focuses on the converged development of China’s rural industries, trying to explore the impact of digitalization on the high-quality converged development of China’s rural industries. Firstly, the mechanisms of digitalization driving rural industrial convergence are revealed. Secondly, we use panel data of 30 provinces (autonomous regions, municipalities) in China from 2011 to 2020 to empirically test the impact of digitalization on rural industrial convergence. Finally, considering the regional differences in industrial structure, the non-linear impact of digitalization on rural industrial convergence is examined. The results indicate digitalization has a significant positive effect on rural industrial convergence, and the impact of the latter has a dual threshold effect with regional heterogeneity based on industrial structure. Therefore, it is suggested to accelerate the construction of digital infrastructure, strengthen digital application, promote regional coordinated development, and improve the institutional system, which are expected to contribute to a deeper connection between digitalization and rural industries.

Asymmetric role of natural resources dependence, industrialization, and foreign direct investment in China’s economic growth

China’s industrial sector is performing continuously in economic activity, aiding its share in the economy's progression. This study aims to analyze the asymmetric positive-negative shocks' influence of industrial value-added, foreign direct investment, technological innovation and natural resources on China's economic growth. We take the data of the concerned indicators from 1986 to 2019 and apply N-ARDL on the model for empirical short and long-run asymmetric estimation. The findings illustrate the positive effect of industrial value-added on economic growth during positive shock and adverse during negative shock. Similarly, technological innovation is affirmative in the acquisition of economic growth in both conditions of positive-negative shock. In contrast, foreign direct investment and natural resource rents have no growth implication during positive shock, while adversative during negative shock in the short and long run. The error correction term has stabilized the error that arises from the short to the long run. At the same time, asymmetric multiplier plots demonstrate a new equilibrium equation of asymmetric adaptations of economic growth after the positive-negative shocks. In the end, result-based suggestions recommend government and policymakers' attention toward heavy and secondary industries, technology-intensive policies, and adaptation of sustainable resources.

Forecasting China’s marine scientific research and education, marine industrial structure upgrading and marine economy growth based on the AWBO-MGM(1,m) model

PurposeThe purpose of this paper is to explore the internal interaction mechanism of marine scientific research and education, industrial structure upgrading and marine economic growth from a systematic perspective, based on which this work forecasts their future development trends.Design/methodology/approachIn this study, a multivariate grey model is applied to the prediction of marine scientific research and education, industrial structure upgrading and marine economic growth. Considering the impact of the COVID-19 on marine development, this paper introduces the weakening buffer operator into MGM(1,m) and constructs the AWBO-MGM(1,m) model. To verify the validity and accuracy of the new model, this paper uses AWBO-MGM(1,m), MGM(1,m), GM(1,N), GM(1,1), back propagation neural network and linear regression models for simulation and prediction based on the data from 2010 to 2021, respectively.FindingsFrom the theoretical perspective, the development of marine scientific research and education can accelerate industrial upgrading and promote marine economic growth by providing high-quality talents, promoting marine science and technology progress and reducing transaction costs; while the upgrading of marine industrial structure and marine economic growth can promote the development of marine scientific research and education by guiding social capital, enhancing talent demand and stimulating market vitality. From the empirical analysis, the AWBO-MGM(1,m) model can effectively deal with epidemic shocks and has higher fitting and prediction accuracy than the other five comparative models.Practical implicationsThe government should pay attention to the construction of marine scientific research and education, so as to provide high-quality talents and advanced scientific research results for the high-quality development of marine economy. On the basis of using science and technology to firmly build the primary and secondary marine industries, the government should actively guide the labor, capital and other factors of production to the tertiary industry, thereby promoting the optimization and upgrading of marine industrial structure.Originality/valueOn the one hand, the interplay mechanism of marine scientific research and education, industrial structure upgrading and marine economic growth is analyzed from a systematic perspective; on the other hand, the enhanced AWBO-MGM(1,m) possesses higher forecasting performance and is applicable to the systemic multivariate forecasting problem in the presence of outstanding external shocks.

GC-MS Analysis and Bioactivity Screening of Leaves and Fruits of Zanthoxylum armatum DC.

Zanthoxylum armatum DC. is a plant that has been homologated for medicine and food by the Chinese for three thousand years. In this study, the essential oils of fresh leaves and fruits were extracted by hydrodistillation, the aromas of fresh leaves and fruits were extracted by headspace solid-phase microextraction and their chemical compositions were analyzed by gas chromatography mass spectrometry. The main components of the leaf essential oils were linalool (62.01%), 2-undecanone (9.83%) and 2-tridecanone (5.47%); the fruit essential oils were linalool (72.17%), limonene (8.05%) and sabinene (6.77%); the leaf aromas were limonene (39.15%), β-myrcene (15.8%), sabinene (8.17%) and linalool (5.25%); the fruit aromas were limonene (28.43%), sabinene (13.56%), linalool (11.47%) and β-myrcene (8.64%). By comparison, it was found that the composition of leaf essential oils and fruit essential oils were dominated by oxygenated monoterpenes, while the composition of their aromas were both dominated by monoterpenes; the relative content of non-terpene components in leaf essential oil and leaf aroma is second only to oxygenated monoterpenes, while their content in fruits is low; the chemical composition of leaf aromas and fruit aromas were richer than those of essential oils. In this study, we reported for the first time that the antitumor, tyrosinase inhibition, HMGR inhibition and nitric oxide production inhibition activity of leaf essential oils were stronger than those of fruit essential oils in in vitro tests. The results of the study can provide a reference for the recycling and green low-carbon transformation of the leaves, and also help to deepen the understanding of the value of the volatile chemical constituents of this plant in “forest medicine” or “aromatherapy”, and provide new ideas for the transformation of the value of the plant in the secondary and tertiary industry chain.

The impact of ultra-high voltage projects on carbon emissions in China.

The inter-regional ultra-high voltage (UHV) projects are crucial for power systems. Carbon emissions associated with the power sector cannot be ignored. In this paper, based on the panel data of 198 prefecture-level cities in China from 2009 to 2019, a multi-period difference-in-difference model is developed for the first time to examine the impact of UHV projects on carbon emissions. Empirical results show that UHV projects increase overall carbon emissions. This impact can also be achieved through the mechanisms of the scale of power generation and the level of economic development. Heterogeneity research demonstrates that the carbon emissions issue of UHV projects is more significant in cities with low levels of economic development and a large proportion of secondary industries. Extensibility research shows that UHV projects have a more significant impact on carbon emissions in power-sending cities than that in power-receiving cities. The more clean power the UHV transmission lines transmit, the less impact on carbon emissions. This study not only enhances our understanding about the impact of UHV projects on carbon emissions, but also provides inspiration for the low-carbon pathway transition.

Spatial-temporal evolution patterns and drivers of PM2.5 chemical fraction concentrations in China over the past 20 years.

The quantitative assessment of the spatial and temporal variability and drivers of fine particulate matter (PM2.5) fraction concentrations are important for pollution control and public health preservation in China. In this study, we investigated the spatial temporal variation of PM2.5 chemical component based on the PM2.5 chemical component datasets from 2000 to 2019 and revealed the driving forces of the differences in the spatial distribution using geodetector model (GD), multi-scale geographically weighted regression model (MGWR), and a two-step clustering approach. The results show that: the PM2.5 chemical fraction concentrations show a trend of first increasing (2000-2007) and then decreasing (2007-2019). From 2000 to 2019, the change rates of PM2.5, organic matter (OM), black carbon (BC), sulfates (SO2- 4), ammonium (NH+ 4), and nitrates (NO- 3) were -0.59, -0.23, -0.07, -0.15, -0.02, and 0.04μg/m3/yr in the entirety of China. The secondary aerosol (i.e., SO2- 4, NO- 3, and NH+ 4; SNA) had the highest fraction in PM2.5 concentrations (55.6-68.1% in different provinces), followed by OM and BC. Spatially, North, Central, and East China are the regions with the highest PM2.5 chemical component concentrations in China; meanwhile, they are also the regions with the most significant decrease in PM2.5 chemical fraction concentrations. The GD and MGWR model shows that among all variables, the number of enterprises, disposable income, private car ownership, and the share of secondary industry non-linearly enhance the differences in the spatial distribution of PM2.5 component concentrations. Electricity consumption has the strongest influence on NH+ 4 emissions in Northwest China and BC and OM emissions in Northeast China.

Literature Review on Smart Manufacturing Upgrades for Manufacturing Enterprises

Smart manufacturing is an important way to achieve a strong manufacturing country and a power engine to promote the rapid development of the country's secondary industry economy. As smart manufacturing enters the stage of comprehensive promotion, there is an urgent need to put forward reasonable suggestions for the measurement of capability elements and their evolution. This paper compares the research results about the leap of smart manufacturing hierarchy in recent years, summarizes the issues related to smart manufacturing from the connotation, development paradigm, role mechanism, capability elements and hierarchy, and discusses the future research directions about the leap of smart manufacturing hierarchy.

Implications of the COVID-19 Pandemic on China's Power Consumption: A comprehensive Analysis Derived from Monthly Electricity Consumption Forecasts

The COVID-19 pandemic profoundly altered the total and pattern of electricity consumption across Chinese industries and households. However, current research has not fully and accurately measured the impact of the pandemic. This paper builds a novel discrete gray seasonal model (referred to as the FDDGSM model) to predict the scenario of different domestic electricity-consuming sectors and residential electricity consumption without a pandemic backdrop, by comparing it with the actual electricity consumption in 2020, the impact of the COVID-19 pandemic on China's electricity consumption is better revealed. Through empirical analysis, the following conclusions are reached in this study: (1) The novel discrete grey season model shows more stable and accurate characteristics in forecasting time series with seasonal trends. (2) The pandemic did not significantly impact electricity consumption in primary industries and households, while actual usage in secondary and tertiary industries was significantly lower than expected in a non-pandemic scenario. (3) The impact on secondary and tertiary industries varied in magnitude and duration, and they differed in the rate of recovery in electricity consumption.

Spatial Equilibrium Evaluation of the Water Resources in Tai’an City Based on the Lorenz Curve and Correlation Number

Water resource spatial equilibrium evaluations provide the bases for water resource utilization and allocation. To analyze the regional spatial water resource matching balance, this study constructed a water resource spatial matching model based on the Gini coefficient and Lorenz curve methods. To further reflect the influence of each subregion on the whole region, we combined the correlation number and Gini coefficient methods to propose the water resource spatial balance evaluation method. Herein, we constructed nine Lorenz curve pairs that matched the total water resources and total water use with cultivated land area, population, GDP (Gross Domestic Product) of the secondary industry, GDP (Gross Domestic Product) of the tertiary industry, and agricultural irrigation water consumption. Set pair analysis theory was applied to calculate sample correlation numbers and determine equilibrium levels, which were then compared to Gini coefficient method-based results for Tai’an city evaluation. The results showed that the total water consumption spatial equilibrium in Tai’an city from 2011 to 2020 was favorable, while the total water resource results for Tai’an city greatly differed, especially the balance between total water resources and GDPs of the secondary and tertiary industries, which should be further improved. In practice, quantitative analysis of the water resource spatial equilibrium state in Tai’an city is important for efficient water resource utilization and coordinated development of water resources and economic and social environments.

Comparative Study on the Influencing Factors of the Greenhouse Gas Budget in Typical Cities: Case Studies of Beijing and Shenzhen

Clarifying the pattern of the urban greenhouse gas (GHG) budget and its influencing factors is the basis of promoting urban low-carbon development. This paper takes Beijing and Shenzhen—the capital city and the most rapidly developing city in China, respectively—as case studies, comprehensively accounts their GHG budgets from 2005 to 2020, and investigates and compares the factors affecting their GHG budgets. The total GHG emissions in Beijing were lowest in 2005 (160.3 TgCO2 equivalents) and peaked at 227.7 TgCO2 equivalents in 2019, and then decreased to 209.1 TgCO2 equivalents in 2020. Meanwhile, the total GHG emissions in Shenzhen gradually increased from 36.0 TgCO2 equivalents in 2005 to 121.4 TgCO2 equivalents in 2019, and then decreased to 119.1 TgCO2 equivalents in 2020. The energy activity sector was the greatest contributor to GHG emissions in this period, accounting for 82.5% and 76.0% of the total GHG emissions in Beijing and Shenzhen, respectively. The carbon sink of the ecosystems of these two cities could absorb only small parts of their emissions, and the neutralization rates of sinks ranged from 1.7% to 2.3% in Beijing and from 0.3% to 1.5% in Shenzhen. The enhancement of population, economic product, and consumption increased the greenhouse gas emissions in both cities. A 1% increase in population size, per capita GD (gross domestic product), and residential consumption level would increase total GHG emissions by 0.181%, 0.019%, and 0.030% in Beijing, respectively. The corresponding increases in Shenzhen would be 0.180%, 0.243%, and 0.172%, respectively. The household size had opposite effects on the two cities, i.e., a 1% increase in household size would increase GHG emissions by 0.487% in Shenzhen but reduce them by 2.083% in Beijing. Each 1% increase in secondary industry and energy intensity would reduce GHG emissions by 0.553% and 0.110% in Shenzhen, respectively, which are more significant reductions than those in Beijing.