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

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

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

Large amounts of wastewater discharge have emerged as a burden in the process of industrialization and urbanization. In this study, a dynamic wastewater-induced input-output model is developed to systematically analyze the related situation. The developed model is applied to Guangdong Province, China to analyze its prominent characteristics from 2002 to 2015. Combining input-output analysis, ecological network analysis and structural decomposition analysis, the developed model reveals issues of direct and indirect discharges, relationships among various discharges, and driving forces of wastewater discharges. It is uncovered that Primary Manufacturing and Advanced Manufacturing dominate the system because of significant temporal and spatial variations in wastewater discharge. In addition, Manufacturing of paper, computer and machinery and Services are the key industries responsible for large amounts of wastewater discharge and unhealthy source-discharge relationships. The largest wastewater discharge occurred in 2005 and indirect wastewater discharge is the main form. Furthermore, final demand is found to be the biggest driving force of wastewater discharge. Finally, a three-phase policy implementation system implemented in stages proposes solutions to wastewater problems. Image 1 • Developing a wastewater-induced input-output model for Guangdong province, China. • Proposing a three-phase policy implementation system for discharge mitigation. • Dynamic wastewater-induced environmental and economic analyses are analyzed. • Final demand is the largest driving force of wastewater discharge. [ABSTRACT FROM AUTHOR]