Digital economy exhibits varying degrees of mitigation of air pollution in China: Total cities-economic subdivisions-urban agglomerations.

Air pollution is a challenge for many cities. The digital economy enhances support for environmental pollution management, while the mechanisms and scaling heterogeneity remain unclear. This study explored the contribution of digital economy development to PM2.5 concentrations control in China and driving mechanisms in different economic subregions and urban agglomerations. Results show that the spillover transfer effect on air pollution mitigation far exceeded the direct effect at different scales. At the national scale, the air pollution mitigation effect of digital economy was mainly through empowering industrial structure optimization and green technology innovation, while it also affected economic subregions and urban agglomerations through varying scenario combinations of pathways with structural optimization, green production, resource allocation, and technology innovation. Research findings provide support for cross-regional joint management strategies of digital economy and air quality and designing regionally differentiated pollution control pathways in the digital economy dimension.

Design and simulation of a cross-regional collaborative recycling system for secondary resources: A case of lead-acid batteries.

In emerging economies, a significant amount of secondary resources are recycled by the informal sector, which can seriously harm the environment. However, some previous studies of industry management policy design ignored geographical factors. This paper introduces Geographic Information Systems into an agent-based cross-regional recycling model, and employs lead-acid batteries as an example. The model quantitatively displays the evolution of recycling markets in 31 provinces in Mainland China. Results show that: (1) High subsidies can significantly increase the number of formal enterprises in the short term, but their effectiveness decreases when the proportion of government funds in subsidies is above 80% in the long run; (2) The number of illegal recycling enterprises increases by 294% in eight inland provinces (e.g., Ningxia, Xinjiang) when all funds are invested in supervision, but this number is quite small in subsidy policy scenarios; (3) In four eastern regions, including Beijing and Tianjin, the number of illegal recycling enterprises decreases by 84% if supervision is more favored than subsidy; (4) In the optimal case where spatiotemporal factors are considered in all 31 regions, illegal recycling enterprises and waste lead emissions can be reduced by 95.59% and 45.85% nationwide. Our proposed recycling model offers a detailed simulation of multiple regions and diverse stakeholders, and serves as a useful reference for targeted recovery policies. Governments in inland regions like Ningxia and Xinjiang should implement subsidy policies, while supervision policies should be implemented in developed regions like Beijing and Tianjin.

Nonlinear effects of socio-economic factors on urban haze in China: Evidence from spatial econometric smooth transition autoregressive regression approach.

In recent years, China has achieved numerous economic miracles but it has also been plagued by severe air pollution. The frequent hazy weather has severely restricted China's sustainable development. To investigate the nonlinear threshold effect of socio-economic factors on urban haze in China, this study constructs a spatial econometric Smooth Transition Autoregressive Regression (STAR) model based on the STIRPAT theory by using the remote sensing inversion PM2.5 data of 223 prefecture-level and above cities in China mainland during 2004-2016. In this study, the ARAR-STAR model is estimated by quasi-maximum likelihood estimation, and the accuracy of parameter estimation is verified by Monte Carlo simulation, which proves that the ARAR-STAR model constructed in this study is robust. It is concluded that: there is a complex spatial nonlinear relationship between socio-economic factors such as economic development level, population density, advanced industrial structure, energy consumption, opening-up, and haze pollution. The effect of socio-economic factors on haze emission reduction under the spatial influence has complex heterogeneity with the smooth transition between high and low regimes with economic development. The ARAR-STAR model constructed in this paper, which has both individual fixed effects and time fixed effects, expands the form of existing spatial panel nonlinear models and enriches and implements the application of spatial panel smooth transfer threshold models in the environmental field. Not only can it provide policy recommendations for China to achieve "coordinated efficiency in pollution reduction and carbon reduction" as soon as possible, but it also contributes to China's plan to address global climate change and promote global sustainable development.

Research on the impact and mechanism of financial development on new urbanization: A case study of the Yangtze River Economic Belt.

Based on panel data of 108 cities in China's Yangtze River Economic Belt from 2003 to 2019, a multiple mediation model is used in this study to assess the impact and mechanism of financial development on new urbanization. The main conclusions are that financial development can directly promote the improvement of new urbanization and indirectly improve the level of new urbanization by increasing infrastructure investment, optimizing industrial structure, and enhancing human capital. Further, the financial development of middle-upstream cities has a stronger promoting effect on new urbanization. Whereas the financial development of downstream cities mainly promotes the construction of new urbanization through both infrastructure investment and industrial structure optimization, middle-upstream cities rely more solely on infrastructure investment.

The impact of transportation accessibility on industrial investment in the urban agglomeration around Poyang Lake in China-based on the perspective of ecological security constraints.

Based on the perspective of ecological security constraints, this research takes panel data of 42 counties (cities) in the urban agglomeration around Poyang Lake in China from 2000 to 2020 and uses a spatial econometric model to investigate the impact of transportation accessibility on industrial investment. The findings herein present an obvious spatial relationship between industrial investment among cities under ecological security constraints and reveal how transportation accessibility has a significant spatial effect on industrial investment in this area. Transportation accessibility has promoted industrial investment in the local region but restrained industrial investment in the surrounding areas. A series of endogenous and robustness tests strengthen this conclusion. Lastly, the effect of transportation accessibility on industrial investment in the UAAPYL is influenced by the lake's circle structure and shows obvious heterogeneity.

An infinite life cycle assessment model to re-evaluate resource efficiency and environmental impacts of circular economy systems.

Challenges exist in life cycle assessment (LCA) to evaluate resource efficiency and environmental impacts of circular economy systems. Rules attributing recycling benefits/burdens are inconsistent, causing system boundary ambiguity. Besides, LCAs covering one or several life cycles fail to capture the complete resource path, which leads to unfair assessment results for the primary life cycle. This paper develops an infinite life cycle assessment model, which integrates LCA, substance flow analysis, and a state transition matrix into an infinite-life-cycle framework. On this basis, algorithms are formulated to quantify the resource efficiency and attribute environmental impacts following the principle of whole first, then allocation. Our model is demonstrated by a case study of lead-acid batteries. Results show that the resource efficiency of lead in the infinite life cycle assessment model is at least 118.75% higher than that of primary lead derived from the typical finite life cycle models. Measured by the index of environmental toxicity potential, environmental impacts are transferred from the primary product life cycle to recycled product life cycles, with the range fluctuating from 66.26% to 68.12%. Our model enables scholars to make more reasonable assessments for circular economy systems based on traditional LCA adjustment. From the infinite-life-cycle perspective, sustainable production policies should focus on increasing the recycling rate of waste products rather than limiting the exploitation of natural resources.

Design and simulation of a secondary resource recycling system: A case study of lead-acid batteries.

The recycling of secondary resources is complicated as consumers, recyclers and governments are all involved in this process. In developing countries, compared to legal recyclers, illegal recyclers not only have cost advantages but also create serious pollution. Inappropriate management policies may cause disorder in the recycling market or inefficient fiscal management. This paper takes China's lead-acid batteries (LABs) from 2000 to 2015 as an example to construct a model of a secondary resource recovery system based on heterogeneous groups and analyzes the environmental and economic impacts of used LAB recycling. By simulating the implementation of different tax cuts, subsidies and regulatory policies by the government in each year, we observe the overall environmental impact of the recycling industry. This study finds that when the total amount of government expenditures is limited, the optimal policy combination emphasizes tax reduction and subsidy policies during the growth period of the recycling industry and uses more funds for supervision in the mature period. Under the balance of fiscal revenues and expenditures, the optimal policy combination can reduce the number of illegal recycling companies and waste lead emissions from the recycling market by 97.9% and 45.8%, respectively. Compared to research conducted using mathematical models and system dynamics models, this result is more in line with the actual situation, and the content is more intuitive. The government needs to adopt different policy combinations in different periods according to the state of the recycling market so that the recycling of secondary resources can achieve the optimal effect.

Does technology advancement reduce aggregate carbon dioxide emissions? Evidence from 66 countries with panel threshold regression model.

The influence of technology advancement on carbon dioxide (CO2) emissions is complex and controversial, yet existing literature ignores the level of economic development in regard to its influential effect. With the panel threshold regression model, this research investigates the marginal and non-linear impacts of technology advancement on CO2 emissions along with the changes of economic development and presents the heterogeneity between different countries. The results are as follows: First, technology advancement and CO2 emissions have a non-linear inverted U-shaped relationship, which is significantly affected by different levels of economic development. When economic development exceeds a certain threshold, the impact turns from positive to negative. Second, the impact varies remarkably among different countries. We provide evidence for inverted U-shaped and N-shaped correlations in the Organization for Economic Co-operation and Development (OECD) countries and high-income countries (non-OECD), respectively. Although technology advancement always promotes CO2 emissions in middle- and low-income countries, its marginal effect is decreasing. This study not only indicates the dynamic impacts of technology advancement on CO2 emissions in different countries, but also contributes to policymakers' understanding of the "common but differentiated responsibilities" involved in mitigating CO2 emissions.

Integrating the MCR and DOI models to construct an ecological security network for the urban agglomeration around Poyang Lake, China.

The development of urban agglomeration in aquatic areas is premised on ecological security. The construction of ecological security network is an effective measure to reduce ecological resistance and guarantee economic development. In this study, a comprehensive ecological security network (ESN) evaluation approach is developed by integrating the Minimum Cumulative Resistance (MCR) model and Duranton and Overman Index (DOI). Taking the urban agglomeration around Poyang Lake in 2015 as a case, the MCR model showed the ecological landscape pattern of discrete connection and large overall ecological resistance. The DOI model indicated that the industries of moderately polluted were global localization, while heavily polluted were small-scale localization and large-scale dispersion. Accordingly, the ESN consisting of 35 ecological sources, 34 ecological corridors, 57 artificial corridors, and 39 eco-economic strategic nodes can avoid the threat of industrial layout to the ecological landscape. The results of this study complemented the guidance of industrial agglomeration theory on the basis of "source-sink" theory. The dual evaluation approach of landscape ecology and economic agglomeration proposed in this study explores interdisciplinary data fusion of different scales, and also provides a reference for inter-municipal coordinated ecological management and restraining urban excessive expansion.