Energy Consumption and Carbon Dioxide Emissions of China’s Non-Metallic Mineral Products Industry: Present State, Prospects and Policy Analysis

As a vital resource endowment area and ecological barrier area in China, low‐carbon development in the upper reaches of the Yangtze River is of great significance. This paper compiled the emission inventory in the Upper Yangtze River Economic Zone in the IPCC regional emission accounting method framework and used the Environmental Kuznets Curve (EKC) model to evaluate economic development and carbon emissions. Finally, this paper used the time series method to predict carbon emissions to 2030. We find that carbon dioxide (CO2) emissions increased rapidly from 2004 to 2012. The average annual growth rate reached 9.16%. After 2012, carbon emissions in the region no longer grow steadily but fluctuate or even decline. The secondary industry contributed 79.77%, the tertiary industry contributed 17.78%, and the primary industry only 2.45% from 2000 to 2015. From the industrial sector and energy consumption, thermoelectricity production and supply division and nonmetallic mineral products industry are the sectors with the most CO2 emissions, accounting for 35.54% and 13.34%, respectively. Raw coal and coke are the main factors causing emissions. Nearly 61.32% of the carbon dioxide produced by raw coal comes from the electricity production sector. However, from 2011 to 2015, the CO2 emissions of raw coal decreased year by year, down by 23.32%. The impact of economic growth on carbon dioxide emissions supports the EKC hypothesis. The CO2 emissions in the Upper Yangtze River Economic Zone will decline after 2020, but Chongqing has shown an upward trend. With the above results, provinces and cities can optimize the regional industrial structure based on sectoral carbon emissions. The study area needs to develop clean energy to optimize the coal‐led energy consumption structure. Provinces and cities in the district can learn from each other's advanced emission reduction experience. © 2021 The Authors. Greenhouse Gases: Science and Technology published by Society of Chemical Industry and John Wiley & Sons Ltd.

Analysis of energy-related CO2 (carbon dioxide) emissions and reduction potential in the Chinese non-metallic mineral products industry

Climate change is increasingly serious, and analysing the determinants of carbon emissions and studying carbon emission reduction is significant. The research used additive decomposition method of LDMI to build a factor decomposition model of carbon emissions from the energy consumption and conducted an empirical analysis of above scale industrial industries from five aspects including energy intensity, industrial structure, energy structure, economic output and the employed population scale. The results revealed that energy intensity and industrial structure had significant negative effects on carbon emissions; while economic output and the employed population scale had strong positive effects; energy structure had no significant negative effect on carbon emissions. Of the industrial industries in Anhui, electricity and heat production and supply industry, coal mining and dressing industry, petroleum processing, coking and nuclear fuel processing industry, ferrous metal smelting and rolling processing industry, non-metallic mineral products industry were the main industries affecting industrial carbon emissions. To reduce carbon emissions, policy suggestions on, reducing energy intensity, adjusting industrial structure and reducing the proportion of five industries were proposed. ［Ch, 4 fig. 5 tab. 14 ref.］

Purpose: China is confronting with tremendous pressure in carbon emission reduction. While logistics industry seriously relies on fossil fuel, and emits greenhouse gas, especially carbon dioxide. The aim of this article is to estimate the carbon dioxide emission in China ’ s logistics sector, and analyze the causes for the change of carbon dioxide emission, and identify the critical factors which mainly drive the change in carbon dioxide emissions of China ’ s logistics industry . Design/methodology/approach: The logarithmic mean Divisia index (LMDI) method has often been used to analyze decomposition of energy consumption and carbon emission due to its theoretical foundation, adaptability, ease of use and result interpretation. So we use the LMDI method to analyze the changes in carbon dioxide emission in China ’ s logistics industry in this paper . Findings: By analyzing carbon dioxide emission of China ’ s logistics, the results show that the carbon dioxide emission of logistics in China has increased by 21.5 times, from 45.1 million tons to 1014.1 million tons in the research period. The highway transport is the main contributor to carbon dioxide emission in logistics industry. The energy intensity and carbon dioxide emission factors were contributing to the reduction of carbon dioxide emission in China ’ s logistics industry in overall study period. Originality/value: Although there are a lot of literature analyzed carbon dioxide emission in many industry sectors, for example manufacturing, iron and steel , pulp and paper, cement, glass industry, and so on. However, few scholars researched on carbon dioxide emission in logistics industry. This the first study is in the context of carbon dioxide emission of China ’ s logistics industry.

Urban planning and energy consumption management gradually play an increasingly significant role in carbon dioxide (CO2) emissions reduction. However, the current studies related to the nexus among them are insufficient, which need to be explored. This article focuses on quantifying the nexus among CO2 emissions, economic development, energy consumption, and urbanization according to data collected from top six provinces (Shanxi, Shaanxi, Shandong, Hebei, Jiangsu, and Inner Mongolia) of CO2 emissions in China between 1997 and 2015 using multi‐variate panel data model (PDM). According to the coefficients in PDM, the energy consumption of Shanxi, Inner Mongolia, Hebei, and Shaanxi make the greatest contribution to CO2 emissions and the economic development of Jiangsu and Shandong are deemed as the greatest contributor to CO2 emissions. The Granger causality results illustrate a bi‐directional causality exists between economic progress and CO2 emissions and between energy consumption and CO2 emissions for six provinces. Finally, the pathways to handle with the contradictions between economic development and CO2 mitigation of top six provinces are proposed, namely decreasing fossil fuels based energy consumption, giving impetus to renewable energy development, exploring a new evaluation system to judge low carbon economy progress, and increasing investment on equipments to improve energy efficiency.

Carbonization and atmospheric pollution in China: The asymmetric impacts of forests, livestock production, and economic progress on CO2 emissions

Under the background of energy conservation and emission reduction, how to rationally and scientifically utilize the non-renewable resources of northeastern farmland is particularly important. In this study, the carbon emission coefficient method is used to select six major carbon sources with energy consumption, including energy consumption in the process of fertilizer production, agricultural machinery use, irrigation, and agricultural waste treatment, to measure the spatial and temporal carbon emissions from the utilization of farmland resources in Northeast China during 2012–2021. A gray prediction model is constructed to predict the carbon emissions from the utilization of farmland resources in the next 10 years, and the logarithmic mean Divisia index model is used to analyze the effects of the various influencing factors on the carbon emissions from farmland utilization. The results show the following: (1) Between 2012 and 2021, carbon emissions from farmland use in Northeast China show a fluctuating development trend of rising and then falling, and the distribution of carbon emissions within the region is characterized by a decreasing trend of “high-middle-low” from the north to the south. (2) Carbon emissions from farmland use in the next 10 years will maintain a gently decreasing trend. (3) The industrial structure of farmland, the level of economic development and the level of urbanization play a contributing role in carbon emissions. The industrial structure of farmland, the level of economic development, and the level of urbanization contribute to carbon emissions from the use of farmland resources. (4) The efficiency of farmland use, the regional industrial structure, and the size of the labor force inhibit the carbon emissions from the use of farmland. This study provides a scientific basis and strategic recommendations for optimizing the use of farmland resources, adjusting the structure of energy use, and realizing the balanced development of land and energy resources under the goal of energy conservation and emission reduction in Northeast China.

Tracing the CO2 emissions embodied in Chinese mainland's exports with multinational enterprises: From source to sink

An analysis of the driving forces of energy-related carbon dioxide emissions in China’s industrial sector

Objective: To analyze the distribution characteristics of new pneumoconiosis in different industries in Tianjin from 2009 to 2018, in order to provide a theoretical basis for the prevention and treatment of pneumoconiosis. Methods: In November 2019, the data of new pneumoconiosis cases in Tianjin from 2009 to 2018 were collected and classified according to difference industries. The epidemiological characteristics of new pneumoconiosis in different industries were analyzed based on time, type of pneumoconiosis, type of work, age, and working age. Results: A total of 4657 new cases of pneumoconiosis were reported in Tianjin from 2009 to 2018, 4640 cases (99.63%) in the first stage, 13 cases (0.28%) in the second stage, and 4 case (0.09%) in the third stage. The number of new cases increased with time and then decreased. Among them, there were 3482 males (74.77%) and 1175 females (25.23%) . The proportion of women with new pneumoconiosis in the non-metallic mineral products industry was the highest, and the differences were statistically significant (P<0.05) . There are differences in the distribution of new pneumoconiosis species in different industries (χ(2)=4920.11, P<0.05) . Silicosis is mainly distributed in non-metallic mineral products industry, metal smelting and rolling processing industry, petroleum processing coking and nuclear fuel processing industries. Foundry worker's pneumoconiosis is mainly distributed in the general equipment manufacturing industry and special equipment manufacturing industry, and cement pneumoconiosis is mainly distributed in the non-metallic mineral products industry. The types of work are mainly distributed in smelting, casting, raw materials and forming workers, and the sum of the three accounts for 36.46% (1689/4657) . The M (P(25), P(75)) of diagnosis age was 56.0 (50.0, 63.0) years, and the M (P(25), P(75)) of working age was 19.0 (16.0, 26.0) years. The working age of new pneumoconiosis patients in the petroleum processing, coking and nuclear fuel processing industries is 19.0 (16.0, 26.0) years, which is shorter than that of other industries (P<0.05) ; The diagnostic age of the general equipment manufacturing industry is 54.0 (49.0, 59.0) years, which is less than that of other industries (P<0.05) . New pneumoconiosis is mainly distributed in large and medium-sized enterprises. New cases of pneumoconiosis in non-metallic mineral products industry, metal smelting, calendar processing industry and general equipment manufacturing industry are mainly distributed in large and medium-sized enterprises. New cases of pneumoconiosis in the metal products industry, special equipment manufacturing industry and petroleum processing, coking and nuclear fuel processing industries are mainly distributed in large enterprises. Conclusion: The work of preventing and controlling pneumoconiosis in Tianjin has a long way to go. We should implement targeted measures according to the characteristics of pneumoconiosis industry, strengthen the supervision of hazard industries, and effectively control the occurrence of pneumoconiosis.

A high level of carbon dioxide (CO2) emission has become a global issue due to extensive production and energy usage that needs regulators’ attention and researchers’ emphasis. Hence, the study aims to explore the effectiveness of energy production and usage on carbon dioxide emission in China. The current study has taken the electricity production from oil, coal and nuclear as the measurement of energy production, while fossil fuel energy consumption and energy use have been taken as the measurement of energy usage, and energy import has been taken as the control variable. The secondary data has been gathered using a secondary source like World Bank from 1991 to 2020. The Quantile Autoregressive Distributed Lag (QARDL) was employed by the study to examine the linkage among variables, while the Augmented Dickey–Fuller (ADF) test was adopted to check the stationarity. The results revealed that electricity production from oil, coal and nuclear has a positive connection with CO2 emission. The findings also exposed that the FFEC, energy import, and energy use also have a positive linkage with CO2 emission. This study monitors the policymakers while establishing regulations to control CO2 emissions by limiting the country's energy production and usage.

In the globalized world, water utilization and carbon emissions are two important indicators for water and energy resources evaluation. This paper investigates the inter-sectoral linkage and external trade of virtual water (water embodied in products) and embodied carbon emissions in China based on input–output tables during 1997–2015. Results indicate that: inside China, agriculture, the electric and water industry are major virtual water suppliers, while heavy industrial sectors including the metal products industry, the petrochemical industry, other nonmetallic mineral products industry, and the mining industry are major embodied carbon emissions suppliers. China is the net exporter of virtual water (137.15 × 109 m3) and embodied carbon emissions (16.05 × 108 t). From the perspective of industrial chain, about 81% of virtual water export come from agriculture, the electric and water industry ultimately, and about 85% of embodied carbon emissions export come from the mining industry, the petrochemical industry, other nonmetallic mineral products industry, the metal products industry, and the electric and water industry ultimately.

Transport is a significant sector that contributes to the increasing carbon dioxide emissions in China. Most related studies have utilized global models to investigate the factors influencing transport sector carbon dioxide emissions from the provincial level to the national level. However, this approach cannot depict the spatial nonstationary characteristics of the influencing factors. Taking the taxi subsector in Eastern China as a case study, we employed exploratory spatial data analysis to examine the spatial heterogeneity of carbon dioxide emissions from taxis (CDET) at the city level and a local model (geographically weighted regression, GWR) to observe the spatial variation in the factors influencing emissions. The results showed that the spatial distribution of CDET was uneven across the study region; the provincial-level cities and metropolises had the highest level of carbon dioxide emissions. The variables gross domestic product (GDP), total population (TP) and urban built-up area (UBA) were among the most significant determinants of emissions. Moreover, using the GWR technique instead of conventional global models, we successfully detected variation in the relationships between emissions and factors at the city level. The GWR results revealed that the positive correlation between CDET and GDP was distributed throughout the study area in 2005 and 2014, but the value of the regression coefficient did not remain the same across the study area. Both positive and negative effects of TP and UBA on CDET were identified and mapped in both study years. Based on the results, we strongly recommend that differentiated mitigation measures be adopted to reduce CDET emissions for different cities according to the spatial variation in emissions and the factors that impact them.

Efficiency and convergence of China’s export trade embodied carbon emissions

Urbanisation, energy consumption, and carbon dioxide emissions in China: A panel data analysis of China’s provinces