Unit Of Gross Domestic Product Research Articles

Exploring the Dynamic Evolution and Drivers of the Coupled Coordination Relationship of Carbon Emission Efficiency and Economic Benefits in Construction Land Development

In the pursuit of sustainable urban development, construction land development (CLD) not only carries the important mission of promoting economic growth but also needs to actively respond to the environmental requirements of reducing carbon emissions. However, there is a tension and balance between these two objectives. This study explores the evolution characteristics and influencing mechanisms of the synergistic relationship between carbon emission efficiency and economic benefits of CLD based on the undesirable slacks-based measurement, coupling coordination degree (CCD) model, Tapio decoupling model, spatial convergence model, and interpretable machine learning techniques. The main conclusions are as follows: (1) The CCR between CEE and economic benefits of CLD in China shows the characteristic of “improvement-stability-local decline”, and it is higher in the eastern region than in the central and western regions. (2) The decoupling of carbon emission efficiency (CEE) and economic benefits of CLD between 2003 and 2023 shows diverse trends in different provinces and time scales in China. (3) China’s eastern region are consistent with σ-convergence and β-convergence, and the gap in the level of inter-regional coupling co-ordination has narrowed. On the contrary, the central and western regions do not pass the σ and β-convergence tests, and the regional equilibrium needs to be improved. (4) In descending order of influence on CCR, they are ownership structure, urban construction land per capita, energy consumption per unit of gross domestic product, energy structure, industrial structure, and foreign trade investment intensity.

Spatial and temporal variations, and socioeconomic drivers of air quality: case study of the Beijing-Tianjin-Hebei urban agglomeration

Abstract Air pollution poses a serious threat to both economic development and public health in China’s heavily polluted Beijing-Tianjin-Hebei region.Realizing a win-win situation for social development and environmental well-being is a pressing issue.This study analyzed panel data from 199 districts in Beijing-Tianjin-Hebei from 2013 to 2020 using various regression models and found that air quality index values decreased by 48.2%. Spatially, the Beijing-Tianjin-Hebei Air Quality Index had a significantly positively correlated spatial correlation that increased over time. Second, energy consumption per unit of gross domestic product and the proportion of construction land had a positive effect on the AQI values of Beijing-Tianjin-Hebei. This implies that increasing energy consumption exacerbates air pollution, particularly in Baoding. Influenced by the urbanization process, the increase in the construction-land ratio was the most significant positive factor, notably in Baoding and Zhangjiakou. Third, there was a negative influence of Research and Development investment and total social retail sales on the Beijing-Tianjin-Hebei Air Quality Index. This finding indicated that increasing Research and Development investment will alleviate air pollution, with most of the counties in the study area benefitting. The collective findings indicate that more prosperous economic areas (such as Beijing and Tangshan) need to pay more attention to air pollution control and that air pollution in the Hebei cluster of heavy industries will be aggravated by the increase in total social retail sales. Based on these results, long-term measures for air pollution control in Beijing-Tianjin-Hebei should focus on reducing energy consumption, slowing urban expansion, and industrial restructuring.

A multi-objective optimization framework for regional land-use allocation: Fully utilizing terrestrial vegetation to mitigate carbon emissions

A multi-objective optimization framework for regional land-use allocation: Fully utilizing terrestrial vegetation to mitigate carbon emissions

Heterogeneity in carbon intensity patterns: A subsampling approach

Carbon intensity, defined as carbon dioxide (CO2) emissions per unit of gross domestic product (GDP), is a critical metric for assessing the effectiveness of climate policy across nations. This paper presents an analysis of the persistence and stationarity of carbon intensity data across 176 countries and 44 regions from 1990 to 2014, employing subsampling confidence intervals. Subsampling is a robust statistical technique that performs well with finite samples and requires minimal assumptions about the data. Our findings categorize countries into three distinct groups based on their carbon intensity patterns: convergent, persistent, and divergent. We observe that climate mitigation policies in countries with a convergent pattern tend to have only temporary effectiveness, whereas in countries with a divergent pattern, such policies can lead to permanent changes. Additionally, using unsupervised learning methods, we delve into the underlying factors influencing these classifications. This study is particularly significant for understanding the long-term impacts of climate policies, offering valuable insights for policymakers and international bodies. By identifying and analyzing these distinct patterns, our research contributes to the strategic planning and implementation of more effective and sustainable climate policies globally, aligning with the goals of international agreements like the Paris Accord.

Beyond fossil fuels: Considering land-based emissions reshapes the carbon intensity of modern economic growth (Spain, 1860–2017)

One of the main challenges facing our society is to decouple levels of well-being from environmental impacts, particularly greenhouse gas emissions (GHGe). Historical knowledge can provide crucial information on the feasibility of achieving this goal. However, very few studies have evaluated the interactions between GHGe and gross domestic product (GDP) or well-being indicators in the long term. So far this literature has only considered CO2 emissions from fossil fuels, disregarding other gases and activities that, as we now know, have played a key role in driving climate change. In this article, we estimate total GHGe and analyze their relationship with GDP trajectories in Spain between 1860 and 2017. The results demonstrate that land-based emissions have been a significant contributor to overall GHGe in historical perspective. By incorporating these emissions, the carbon intensity of GDP—that is, greenhouse gas emissions per unit of GDP—shifts from an inverted U-curve (as traditionally assumed when only considering CO2 emissions from fossil fuels) to a consistent decline over time.

Analysis of Factors Influencing the Spatial and Temporal Variability of Carbon Intensity in Western China

Understanding the spatio-temporal differentiation of carbon intensity factors is crucial for setting scientific and reasonable carbon emission reduction targets. This study, based on relevant data from the western regions for the years 2010–2019, analyzes the influencing factors of the spatio-temporal distribution differences in carbon intensity in these areas. Additionally, the Grey Forecasting Model was utilized to predict the development trend of average carbon intensity in the western regions. The results indicate the following: (1) The temporal dimension of carbon intensity in the western regions shows an overall declining trend with local rebounds, while the high-value areas of spatial carbon intensity are concentrated in the northern part of the study area. (2) Per capita Gross Domestic Product, energy consumption per unit of Gross Domestic Product and investment in industrial pollution control have a positive impact on carbon intensity, whereas investment in the energy industry and per capita disposable income of residents have a negative impact. (3) Energy consumption per unit of Gross Domestic Product is the factor with the highest degree of explanation in univariate analysis; interaction detection results suggest that the core factors of spatial distribution differences in carbon intensity are energy consumption and urban development. (4) Predictions using the Grey Forecasting Model for the development of carbon intensity in the western regions show a year-by-year decline, consistent with carbon intensity control targets. Based on these conclusions, this paper proposes policy recommendations focusing on improving regional economic coordination mechanisms, increasing investment in industrial pollution control, managing energy industry expenditures, adjusting the proportion of the urban population, and enhancing the per capita disposable income of residents.

ИССЛЕДОВАНИЕ ЭНЕРГЕТИЧЕСКОГО ЛАНДШАФТА РАЗНЫХ СТРАН МИРА В ЭПОХУ ПЕРЕХОДА К ЧИСТОЙ ЭНЕРГИИ

Goals. The purpose of this work is to study the energy landscape in countries around the world through indicators of electricity generation from various sources, taking into account the economic efficiency of some energy processes. Relevance. The relevance of the topic is due to the need to study changes in the energy system that affect the entire world economy. As the cost of renewable energy technologies falls and production capacity expands, the transition from fossil fuels to a cleaner, more sustainable energy system is accelerating and delivering significant socio-economic benefits, and performance analysis in this area remains important and relevant. Research methods. The main research methods are grouping and comparison of indicators. The sample countries were grouped by energy type based on the volume of electricity generated from various sources, and then the indicators of electricity consumption per capita and per unit of Gross Domestic Product were compared and analyzed. Main results. Countries are grouped by energy type in terms of sources of electricity generation, and countries are also compared in terms of electricity consumption per capita and one of the key indicators of the energy intensity of the economy - the ratio of electricity consumption to Gross Domestic Product per capita. Findings for groups of countries are presented in the context of selected indicators for comparison.

Productive and Consumptive Emission Characteristics of Energy-related Nitrogen Oxides in Eastern Chinese Cities

Nitrogen oxides (NO x ) have long been the focus of air pollution control. Examining the spatial and driving characteristics of NO x emissions at the urban scale and from the supply-chain perspective is critical. Using the inventory method and the environmentally extended input–output analysis, energy-related NO x emissions of 90 cities in eastern China were calculated, and the spatial patterns and driving sectors of urban emissions were analyzed from both production- and consumption-based perspectives. The results show that the production-based emissions of eastern Chinese cities are substantially affected by their industrial structure and are higher in the north and lower in the south. The cities with higher consumption-based emissions are mainly those with large populations and relatively developed economies. Production-based NO x emissions per unit gross domestic product (GDP) are higher in the north and lower in the south, and emissions per unit area are generally higher in coastal areas and lower in inland areas. The emission intensities of 5 selected major urban agglomerations differ, due to the influences of industrial structure and population density. The consumption-based NO x emissions per capita are mainly affected by urban affluence and consumption patterns. The sectors that contribute most to the production-based emissions per unit GDP are mainly “mining and processing”, “petroleum, chemical and non-metallic mineral products”, “metal products”, “production and supply of electricity, natural gas and water” and “transportation, storage, and postal services”, while the sector that contributes most to the consumption-based emissions per capita is the construction industry. Emission reduction strategies are proposed for both consumption-oriented and production-oriented cities.

A Bi-Level Optimization Model for Inter-Provincial Energy Consumption Transfer Tax in China

The serious energy crisis and environmental problems resulting from fossil energy excessive consumption have caused severe challenges to the control of energy consumption and intensity (dual controls) and the sustainable development of China’s economy and society. The current territorial management model (TMM) of energy consumption “dual control” needs urgent improvement. Therefore, this study proposes an inter-provincial energy consumption transfer tax model (ECTTM) based on the Stackelberg game and bi-level optimization theory. In this model, the central government is the leader at the upper-level, and provincial governments are the lower-level followers. An optimization algorithm based on NSGA-II was designed to solve this model to obtain the optimal transfer tax rate and provincial energy consumption. The ECTTM aims to maximize the socioeconomic benefits of energy consumption overall and in each province under the premise of achieving the dual control target. The model’s effectiveness and superiority were illustrated through an empirical study of electricity consumption in Shanghai, Zhejiang, Shaanxi, and Guizhou. Compared with the TMM, the socioeconomic benefits under the ECTTM increased by 14.67%, and the electricity consumption per unit of gross domestic product decreased by 12.8%. Policy suggestions on the ECTTM’s implementation are proposed to promote further improvements in dual controls.

Analysis of the characteristics of major pollutants discharged from wastewater in China's provinces.

In recent years, the discharge of major pollutants in China's wastewater has been decreasing but remains at a high level. Controlling the discharge of pollutants in sewage is of great importance for protecting water quality and maintaining ecological balance. Based on data collected from 31 provinces in China from 2011 to 2020 (except 2018), this study analyzes the spatiotemporal variation emissions of the wastewater pollutants: chemical oxygen demand (COD), ammonia nitrogen (NH3-N), total nitrogen (TN), and total phosphorus (TP). The entropy method was used to evaluate the effectiveness of water pollution control in different provinces. Our results revealed that the total emission per gross domestic product (GDP) for COD, NH3-N, TN and TP in China decreased by 50.7%, 81.9%, 65.4% and 70.8%, respectively. In terms of regional annual emission differences, the Northwest region was the lowest compared with other regions, accounting for 4.87%-6.59% of the national pollutant emissions, and the Central China region was the highest, accounting for 22.4%-26.05% of the national pollutant emissions. The average value of pollutant emissions per unit of GDP decreased year-to-year overall, but Guangxi and Tibet showed a trend of first decreasing and then increasing. The correlation results indicated a significant correlation (0.977) between TN and TP emissions in wastewater in China during 2011-2020. Through clustering and Multidimensional Scaling model (MDS) analysis, Beijing and Shanghai have been performing well in controlling water pollution discharge, while the provinces of Tibet and Guangxi must still increase their efforts in water pollution control. Furthermore, these results demonstrate the experience and achievements of the Chinese government in the treatment of wastewater pollution and provide a useful reference for treatment of wastewater pollution in the world.

Relation Between Financial Literacy and Carbon Footprint: Review on Implications for Sustainable Development

Introduction. Financial literacy has been recognized worldwide as a significant element of stability and economic and financial growth. With the evolution of financial instruments, the growing importance of financial inclusion, its correlation with financial literacy, and the effects they have on sustainability, the concept of financial literacy is dramatically changing and getting more inclusive, spreading the focus on sustainability, sustainable consumption, and environmental preservation.
 Aim and tasks. The aim of the study is to examine the connection between the population's financial literacy level and greenhouse gas emissions. The working hypothesis claims that there is a relationship between financial literacy and the carbon footprint.
 Results. The correlation and regression analyses were the main tools in the study, while the dataset for 2014 covered 137 countries, with the main dependent variables being carbon emissions per capita, per unit of gross domestic product, and per unit of energy. The partial correlation coefficients between financial literacy rating and carbon footprint variables were insignificant when controlled for economic development, represented by per capita gross domestic product. Estimated econometric models with financial literacy in quadratic form were adequate and showed a significant connection between financial literacy and carbon emissions per capita and per gross domestic product at the 5% level. The relationship with carbon emissions per unit of energy was significant at the 10% level. In all three models, the relationships followed an inverse U-shape, with low financial literacy increasing the carbon footprint and higher financial literacy decreasing it. The turning numbers for financial literacy were 35.8% for carbon emissions per capita, 41.4% for emissions per unit of gross domestic product, and 32.4% for emissions per unit of energy.
 Conclusions. Financial literacy was indeed associated with carbon emissions in a complex, non-linear way. The effect of energy consumption on carbon emissions was stronger than financial literacy and appeared to be the driving force for the increase in carbon emissions. With low financial literacy observed in underdeveloped countries, the situation was not favorable for the environment. As financial literacy increased, welfare, income, and consumption increased too, leading to an increase in greenhouse gas emissions, i.e., a bigger CO2 footprint. Once a certain stage of economic development was reached, the relationship was reversed, i.e., in developed countries, financial literacy worked towards reducing the carbon footprint and protecting the environment.

Impact of solar energy generation on carbon footprint: Evidence from China

To investigate the impact of solar energy on the carbon footprint, to find effective measures to reduce the carbon footprint and slow global warming as soon as possible, this paper takes 30 provinces in China as an example. First, the inter‐regional input–output model is used to calculate the carbon footprint of each province. Then, the panel quantile regression model is used to investigate the impact of solar energy generation on different quantiles of carbon footprint. The results show that from 2012 to 2020, China's carbon footprint is at a high level, which is not conducive to the achievement of the goal of peaking carbon dioxide emissions. The eastern region has the highest carbon footprint, followed by the western region, the central region has the lowest carbon footprint, and its carbon footprint proportion continues to decline. The increase of solar energy generation can significantly reduce the carbon footprint of high quantile location, but has no significant impact on the carbon footprint of the middle and low quantile locations. Except for the negative impact of afforestation area on carbon footprint, the others control variables are all positive. Therefore, to reduce the carbon footprint of China, it is necessary to upgrade solar technology, increase solar energy generation, reduce energy consumption per unit of GDP (Gross Domestic Product) and the share of coal consumption, strengthen forestry management and reduce reliance on private vehicles.

Rapid decline of carbon monoxide emissions in the Fenwei Plain in China during the three-year Action Plan on defending the blue sky

Rapid decline of carbon monoxide emissions in the Fenwei Plain in China during the three-year Action Plan on defending the blue sky

ECONOMIC ANALYSIS OF ENERGY EFFICIENCY OF CHINA'S AND INDIA'S NATIONAL ECONOMIES

The development of society is highly dependent on energy. However, the extensive use of power causes global problems such as resource exhaustion and climate warming. China and India are typical fast-growing developing countries whose economic advancement relies on traditional energy consumption. To realize the vision of sustainable development for these states, it is necessary to study the nations' economic efficiency of power use. Based on the analysis of energy consumption and gross domestic product trends in China and India from 1990 to 2019, this paper discusses the changes in the energy consumption index per unit of gross domestic product. The authors concluded that the power consumption in China and India is mainly concentrated in the industry, residential, and transport sectors. Divided by resource types, the energy consumed by China comes primarily from coal, oil products, and electricity, while the power consumed by India is mainly from coal, oil products, biofuels and waste. Since both countries mostly use coal and oil products which belong to fossil fuels, they emit large amounts of carbon dioxide, endangering the environment quality. Given this, China and India should focus on green power development. China's total energy consumption is much larger than India's, and China's gross domestic product is much larger than India's. However, China's energy consumption per unit of gross domestic product is less than India's. The higher the energy consumption per unit of gross domestic product is, the higher the dependence of economic development on energy is. The authors' suggestions are to develop non-fossil energy sources and adjust the energy mix, recycle solid wastes, and encourage carbon trading, climate investment and financing in the states to reach sustainable development targets.

IMPROVING THE RELIABILITY OF GAS TRANSMISSION SYSTEMS TO ENSURE THE ENERGY INDEPENDENCE OF THE COUNTRY

The authors of this article made an extensive analysis of the state of the natural gas pipeline transport systems in the territory of the Republic of Kazakhstan. A detailed assessment of the existing gas pipeline of certain regions of Kazakhstan, factors determining the reliability of the system, and ways to improve the efficiency and reliability of natural gas pipeline transport in the near future are given. Natural gas is one of the most important energy resources. Ever-increasing demand increases the value of fossil fuels. Today, the gas industry is one of the country's intensively developing industries, if our country ranks 22nd in the world in terms of reserves, then it ranks 3rd among the CIS countries after Russia and Turkmenistan. There are about 80 gas producing companies operating in the republic, then more than 20 of them send gas to gas pipelines to ensure domestic consumption and realize the export needs of the country. About 98% of the proven gas reserves are located in the west of the country, in turn, about 87% are concentrated in large oil and gas and gas condensate fields. In the country's long-term development programs, special attention is paid to improving the efficiency of the use of natural resources and the development and implementation of measures to reduce energy consumption per unit of gross domestic product (GDP). The gas transmission system organizes uninterrupted supply of natural gas to consumers, maintenance and repair of linear structures, compressor and gas distribution stations and underground gas storage facilities.

Impact of Urban Mining on Energy Efficiency: Evidence from China

Achievement of carbon neutrality requires lowering energy consumption in China. However, only a few studies have focused on the impact of urban mining on the reduction in energy consumption, and the impact of urban mining on reducing energy consumption remains unclear. This study explored the impact of urban mining on energy efficiency by adopting the panel data of 281 prefecture-level cities in China between 2003 and 2016 using the difference-in-difference method, and tested the setting up of urban mining pilot bases on reducing urban energy consumption per unit of gross domestic product (GDP) and channel mechanisms. The empirical findings show that urban mining pilot bases have significantly reduced energy consumption per unit of GDP by 3.67%. The instrumental variable method was used to overcome endogenous problems of the empirical results and related robustness tests. The verification results of the impact mechanism show that urban mining reduces the energy consumption per unit of GDP through three channels: by improving the degree of urban marketization, enhancing the harmony between the government and the market, and increasing the abundance of factor markets. The heterogeneity analysis shows that urban mining has a significant reduction effect on energy consumption per unit of GDP in all four regions of China; however, the energy-saving effect in the northeast is higher than that in the other regions. This study provides an empirical test and policy insights for the contribution of urban mining pilot bases in promoting China’s development of green industry and circular economy. It also offers a new path for cities in developing countries to promote energy conservation and achieve urban sustainability via urban mining.

ASSESSMENT OF STRING INVERTERS FOR LARGE-SCALE SOLAR POWER PLANT IN MALAYSIA’S

Tremendous promotion and growth of Large-Scale Solar Photovoltaic (LSSPV) Power Plant in Malaysia increase the reliability and potentiality of the system in having efficient monitoring, operation and maintenance for the plants. Through the Ministry of Energy, Science and Technology, the government aims to increase the renewable energy in its generation mix in 2025 by 20% and intends to reduce its greenhouse gas (GHG) emission intensity per unit of gross domestic product (GDP) to 45% by 2030. This was followed by the Energy Commission (EC) announcement of 500 MW LSSPV power plants in Malaysia, slated for commercial operation in 2021. Thus, proper monitoring and respectable power generation are crucial to optimising LSSPV for grid interconnection. This paper presents the assessment of string inverters configuration and analysis models to recommend an optimised configuration for maximum harvested power generation in the LSSPV power plant in Malaysia. An analysis of string invert configuration is carried out based on real data measurements of electric generation of a 50 MW LSSPV power plant at the Kuala Ketil site. The test verified that the configuration string inverters offer a reliable outcome for the grid code test (GCT). Besides, the string inverters provide a potential approach to maximising power generation at different climate conditions, thus, reducing the workforce for the operation and maintenance activities. The string system endeavours a feasibility implementation on the suitability of effective configurations for LSSPV in Malaysia without often shutting down the plant generations due to any defect or damage of PV modules.

Research on the synergies between low-carbon pilot city policy and high-speed railways in improving Chinese urban electricity efficiency

PurposeGlobal climate change is a serious threat to the survival and development of mankind. Reducing carbon emissions and achieving carbon neutrality are the keys to reducing greenhouse gas emissions and promoting sustainable human development. For many countries, taking China as an example, the electric power sector is the main contributor to the country’s carbon emissions, as well as a key sector for reducing carbon emissions and achieving carbon neutrality. The low-carbon transition of the power sector is of great significance to the long-term low-carbon development of the economy. Therefore, on the one hand, it is necessary to improve the energy supply structure on the supply side and increase the proportion of new energy in the total power supply. On the other hand, it is necessary to improve energy utilization efficiency on the demand side and control the total primary energy consumption by improving energy efficiency, which is the most direct and effective way to reduce emissions. Improving the utilization efficiency of electric energy and realizing the low-carbon transition of the electric power industry requires synergies between the government and the market. The purpose of this study is to investigate the individual and synergistic effects of China’s low-carbon policy and the opening of urban high-speed railways (HSRs) on the urban electricity consumption efficiency, measured as electricity consumption per unit of gross domestic product (GDP).Design/methodology/approachThis study uses a panel of 289 Chinese prefecture-level cities from the years 1999–2019 as the sample and uses the time-varying difference-in-difference method to test the relationship between HSR, low-carbon pilot cities and urban electricity consumption efficiency. In addition, the instrumental variable method is adopted to make a robustness check.FindingsEmpirical results show that the low-carbon pilot policy and the HSR operation in cities would reduce the energy consumption per unit of GDP, and synergies occur in both HSR operated and low-carbon pilot cities.Research limitations/implicationsThis study has limitations that would provide possible starting points for future studies. The first limitation is the choice of the proxy variable of government and market factors. The second limitation is that the existing data is only about whether the high-speed rail is opened or not and whether it is a low-carbon pilot city, and there is no more informative data to combine the two aspects.Practical implicationsThe findings of this study can inform policymakers and regulators about the effects of low-carbon pilot city policies. In addition, the government should consider market-level factors in addition to policy factors. Only by combining various influencing factors can the efficient use of energy be more effectively achieved so as to achieve the goal of carbon neutrality.Social implicationsFrom the social perspective, the findings indicate that improving energy utilization is dependent on the joint efforts of the government and market.Originality/valueThe study provides quantitative evidence to assess the synergic effect between government and the market in the low-carbon transition of the electric power industry. Particularly, to the best of the authors’ knowledge, it is the first to comprehend the role of the city low-carbon pilot policy and the construction of HSR in improving electricity efficiency.

Variation of Net Carbon Emissions from Land Use Change in the Beijing-Tianjin-Hebei Region during 1990–2020

Global increasing carbon emissions have triggered a series of environmental problems and greatly affected the production and living of human beings. This study estimated carbon emissions from land use change in the Beijing-Tianjin-Hebei region during 1990–2020 with the carbon emission model and explored major influencing factors of carbon emissions with the Logarithmic Mean Divisia Index (LMDI) model. The results suggested that the cropland decreased most significantly, while the built-up area increased significantly due to accelerated urbanization. The total carbon emissions in the study area increased remarkably from 112.86 million tons in 1990 to 525.30 million tons in 2020, and the built-up area was the main carbon source, of which the carbon emissions increased by 370.37%. Forest land accounted for 83.58–89.56% of the total carbon absorption but still failed to offset the carbon emission of the built-up area. Carbon emissions were influenced by various factors, and the results of this study suggested that the gross domestic product (GDP) per capita contributed most to the increase of carbon emissions in the study area, resulting in a cumulative increase of carbon emissions by 9.48 million tons, followed by the land use structure, carbon emission intensity per unit of land, and population size. By contrast, the land use intensity per unit of GDP had a restraining effect on carbon emissions, making the cumulative carbon emissions decrease by 103.26 million tons. This study accurately revealed the variation of net carbon emissions from land use change and the effects of influencing factors of carbon emissions from land use change in the Beijing-Tianjin-Hebei region, which can provide a firm scientific basis for improving the regional land use planning and for promoting the low-carbon economic development of the Beijing-Tianjin-Hebei region.

Drivers of air pollution reduction paradox: Empirical evidence from directly measured unit-level data of Chinese power plants

Drivers of air pollution reduction paradox: Empirical evidence from directly measured unit-level data of Chinese power plants