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Land is an indispensable factor of production and the basic support for all social and economic activities. The COVID-19 epidemic has a great impact on China's macro-economy and land market. As a unit with a high concentration of economic entities, urban agglomeration is closely related to its land use economic efficiency. Under the impact of epidemic and the rigid constraints of the relative scarcity of land resources, improving the land use economic efficiency is crucial to the sustainable development of urban agglomerations. Taking the 10 major urban agglomerations in China as a case study, this paper constructs a theoretical and empirical analysis framework for the land use economic efficiency and its driving mechanism of urban agglomerations, and measures the land use economic efficiency of urban agglomerations from the aspects of single factor productivity and total factor productivity. The results show that the COVID-19 epidemic has a great impact on the land market of various cities in China's urban agglomerations. Whether single factor productivity or total factor productivity is used to measure land use economic efficiency of urban agglomerations, the driving effects of industrial agglomeration, industrial structure change, technological progress, and transportation infrastructure are all significant. It is necessary to take a series of measures to reform the market-oriented allocation of land elements, and improve a long-term mechanism for the smooth operation of the land market. It is necessary to improve the land use economic efficiency through a combination of industrial agglomeration, industrial structure adjustment, technological progress, and transportation infrastructure., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Wang and Ma.)

Existing studies ignore the importance of information infrastructure development in improving regional health care environment. This paper adopts a spatial difference-in-difference (DID) model to assess the impact of information infrastructure development on urban health care environment based on a quasi-natural experiment of the "Broadband China" city pilots (BCCP). A balanced panel of 259 cities from 2010 to 2019 is selected for empirical analysis in this paper. Our findings show that the implementation of BCCP resulted in a 4.1 and 2.9% improvement in local medical workforce and medical infrastructure. In addition, there is significant spatial spillover effects of the implementation of BCCP, with 7.2 and 12.5% improvement in medical workforce and medical infrastructure in the surrounding areas. Our findings also suggest that information infrastructure development enhances the health care environment by driving industrial upgrading and education levels. Further analysis shows that BCCP has the strongest improvement on medical workforce in the eastern region and non-ordinary prefecture-level cities. For medical infrastructure, BCCP has stronger improvement in central region, western region, and non-ordinary prefecture-level cities. Finally, the paper conducts a series of robustness tests to ensure the reliability of the analysis results, including parallel trend tests, placebo tests, and re-estimation with different methods. Policies to improve the health care environment through information infrastructure development are proposed., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Tu, Zang, Tan, Zhou and Yu.)

Based on the exogenous shock of digital financial development in China in 2013, a difference-in-differences (DID) model is set up in this paper to investigate the causal relationship between digital financial development and haze pollution reduction. The finding of the paper is that a one standard deviation increase in digital finance after 2013 decreases the PM 2.5 concentrations by 0.2708 standard deviations. After a number of robustness checks, like placebo tests, instrumental variable (IV) estimations, eliminating disruptive policies, and using alternative specifications, this causal effect is not challenged. In addition, this paper explores three potential mechanisms of digital finance to reduce haze pollution: technological innovation, industrial upgrading, and green development. Moreover, the heterogeneous effects signify that the usage depth of digital finance works best in haze pollution reduction. Digital finance has more positive effects in cities in the north and those with superior Internet infrastructure and higher levels of traditional financial development. However, the quantile regression estimates suggest that for cities with light or very serious haze pollution, the positive impact of digital finance is limited. These findings supplement the research field on the environmental benefits of digital finance, which provides insights for better public policies about digital financial development to achieve haze pollution reduction., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Zhao and Yan.)

Sponge city special planning represents a basis for sponge city construction in China. It has a leading role in problem-oriented, effect-centered comprehensive, and coordinated construction. In accordance with the Interim Provisions on the Formulation of Sponge City Special Planning , China has gradually established a standardized method for formulating sponge city special planning based on the "four-water" framework. While this method emphasizes the normalization of planning contents, it has limitations when dealing with regional characteristics. The present paper clarifies the purposes and demands of formulating sponge city special planning for semi-arid valley cities in northwestern China. It furthermore highlights the limitations of the standard method and suggests a three-level optimization, i.e., problem identification, target indicators, and system construction. Based on the framework of "mountain management-water management-moist city," this paper proposes a set of ideas for formulating sponge city special planning. In this regard, the discussions are based on the formulation practice of Xining., Competing Interests: Authors YY, JH, and JZ were employed by China Urban Construction Design & Research Institute Co., Ltd. The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Wu, Yang, He and Zhu.)

Health capital investment is an integral aspect of human capital investment, and it is vitally important to improve residents' health by encouraging them to maintain insurance. This paper estimates the potential impact of particulate pollution (PM2.5) on health insurance buyers at the city level. Using PM2.5 as a representative air pollution indicator, we construct a threshold panel model and a spatial econometric model based on 2000-2019 panel data from 256 Chinese cities and the health production function to examine the impact mechanism through which PM2.5 pollution causes changes in the number of health insurance buyers. The results indicate that higher PM2.5 pollution significantly increases health insurance buyers in China. Considering the threshold effect, per capita GDP has a nonlinear relationship with an increasing marginal effect on the higher number of health insurance buyers. Due to spatial spillover effects, PM2.5 pollution has an additional impact on the number of health insurance buyers, indicating that a lack of awareness of the spatial correlation will result in underestimating the impact of PM2.5 pollution on residents' health. The robustness of adjacency and geographic distance matrices demonstrates that the regression results are robust and reliable. The findings of this study provide a practical reference for health insurers' development and policymakers' pollution control efforts., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Song and Xu.)

Air pollution significantly impacts sustainable development and public health. Taking the implementation of China's Environmental Protection Tax Law in China as a quasi-natural experiment, this paper employs the difference-in-differences (DID) and spatial DID models to evaluate the effects of environmental tax reform on urban air pollution. The findings are as follows. (1) Environmental tax reform can significantly reduce urban air pollution, and a series of robustness tests have also been conducted to provide further evidence. (2) Green technology innovation and industrial structure upgrading from a vital transmission mechanism for environmental tax reform to improve air quality. (3) Environmental tax reform significantly inhibits urban air pollution in cities located north of the Qinling-Huaihe line and big cities. (4) Moreover, environmental tax reform not only promotes the improvement of local air quality but also has a significant negative spatial spillover effect, reducing air pollution in neighboring cities. The research conclusions provide theoretical support and policy suggestions for promoting sustainable economic development, rationally optimizing environmental protection tax policies and improving urban air quality., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Guo, Wang, Feng, Liang, Tang, Yao and Hu.)

Traditional urbanization has stimulated economic growth. Meanwhile, it has damaged the natural environment. China has initiated new urbanization to resolve this dilemma. This paper aims to clarify the relationship between new urbanization and environmental pollution and prove new urbanization's superiority in containing environmental pollution. Thus, this paper adopts the static and dynamic spatial Durbin and mediating effect models to estimate the environmental pollution control mechanism of the new urbanization, using the panel data collected from 285 prefecture-level cities in China from 2003 to 2018. Findings show that: (1) Environmental pollution has time inertia and spatial spillover effect. The degree of pollution in an area is related to the environmental quality in the earlier stage and the surrounding areas. (2) The role of new urbanization in containing environmental pollution can take effect in the long run. In the short term, population urbanization can restrain the environmental pollution of both local and surrounding cities. (3) Heterogeneity analysis shows that the higher the level of environmental pollution, the greater the impact of new urbanization on environmental pollution. (4) Mediating effect test shows that technological effect and industrial structure upgrading are two important channels for new urbanization to reduce environmental pollution. (5) Threshold effect test shows that the inhibition effect of new urbanization on environmental pollution is gradually enhanced after crossing the threshold., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Zhang and Cai.)

The coordinated relationship between urban population-land spatial patterns (UPLSPs) and ecological efficiency (EE) is conducive not only to the rational utilization of resources and environment and the sustainable development of society, but also to the provision of a living environment that benefits public health. Identifying the coupling relationship of urban development and EE can provide critical information for urban planning. Previous studies have mainly focused on the coupling relationship between urban population and land, urbanization, and ecological development, while ignoring that between UPLSPs and EE. This study integrates several models to construct a novel framework for coupling UPLSPs and EE. Taking Hubei Province as the research area, we calculate the UPLSPs, EE, and their coupling coordination degree for 12 cities from 2000 to 2019. The paper offers several conclusions. (1) the urban population-land spatial matching degree increased, but the overall matching level was not high; the average value of EE showed an "N"-shaped change trajectory, and its overall level was low, with small changes and obvious regional differences. (2) The average value of the coupling coordination degree between UPLSPs and EE was a slow upward trend, with a radial distribution high in the middle and low in the periphery. There was conflict between the spatial patterns and EE, and the former restricted the development of the latter. (3) There were strong correlations between coordination degree and various indicators of UPLSPs and EE. While we should revitalize the stock of construction land and optimize the upgrading of the industrial structure, we also must coordinate human and land resources and the ecological environment, and narrow regional development differences. This study provides a new framework for urban environmental assessment and urban planning decision-making., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Shan, Jiang, Liu, Zhang, Zhang and Cui.)

With the rapid process of urbanization and global warming, many metropolises are vulnerable to high temperatures in summer, threatening the health of residents. However, green spaces can generate a cooling effect to mitigate the urban heat island effect in big cities. They can also help to improve the living quality and wellbeing of surrounding residents. In this paper, we utilized the radiative transfer equation algorithm, k-means clustering algorithm, big data crawling, and spatial analysis to quantify and map the spatial distribution, cooling capacity, and cooling contribution for surrounding communities of 1,157 green spaces within Beijing Fifth Ring Road, a typical metropolitan area. The findings showed that (1) the area proportion of the heat island in the study area is larger than that of the cooling island. Accounting for only about 30% area in the study area, the green spaces reduce the average land surface temperature by 1.32°C. (2) The spatial features of green space, such as area and shape complexity, have a significant influence on its cooling effect. (3) Four clusters of green spaces with specific spatial features and cooling capacity were identified. And there were differences among these clusters in green space cooling contribution for the surrounding communities. (4) The differences in green space cooling contribution also existed in different urban zones. Specifically, the middle zone performed significantly better than the inner and outer zones. (5) We furthered in finding that some green spaces with medium and high cooling contributions need to improve their cooling capacity soon, and some green spaces with low cooling contributions or no contributions have a good potential for constructing new communities in the future. Our study could help planners and government understand the current cooling condition of green spaces, to improve their cooling capacity, mitigate the urban heat island effect, and create a comfortable and healthy thermal environment in summer., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Liu, Zhao, Sun, Xu, Huang and Zhu.)

In order to explore the determinants of vacant taxi drivers' customer-search behavior, this paper intends to calibrate a time-dependent Multinomial Logit (MNL) model by mining over 1.6 billion GPS records from about 8,400 taxis in Shanghai, China. First, based on the ordering points to identify the clustering structure (OPTICS) algorithm, the downtown area of Shanghai city is divided into 47 hotspots to identify the hot areas of customer delivery and searching. Then, by investigating a typical search delivery process of a vacant taxi, five candidate factors that may affect the customer-search behavior are summarized and defined. Using the maximum likelihood method, the significant factors are finally found. The results reveal that the relative passenger demand, the regional likelihood of pick-ups as well as the expected rate of return are the most significant factors influencing customer-search behavior. Although the impact of traffic situation (i.e., the en-route delay and traffic condition of the target hotspot) is not particularly significant, service providers and policymakers should still take full advantage of it to schedule taxi service and mitigate the traffic congestion caused by the circulation of vacant taxis. Besides, this paper also shows that the customer-search behavior of a vacant taxi driver varies with the time of day. Findings in this paper are expected to provide comprehensive insights about factors that should be considered in the future operation pattern of a taxi service system where human driver taxis and self-driving taxis are mixed., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Yu, Sun, Jin and Chen.)

The COVID-19 pandemic has spread across the country negatively impacting on the economy. This paper uses the panel data of 14 prefecture-level cities from 2015 to 2020 in Hunan to determine the factors and effects of economic downturns based on the spatial econometric model. We calculate the Moran index, so-called the Moran's I, to analyse the impact of each factor on the economy. The results show that the spatial correlation of the cities around Chang-Zhu-Tan is high, and the economic growth of the entire province can be influenced by these cities. These cities should adopt strategies to improve the economy, such as reducing the tax revenues, improving the local financial revenues, and reducing the ineffective educational input. These results can also be helpful for policymakers, who will attempt to retransform the Hunan economy during the post-COVID era., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Pan, Zhonghuan, Shiqi, Siyi, Yanping and Danying.)

This paper examines the relationship between the presence of air pollution and incidence of selected respiratory diseases in the urban population of the Tri-City agglomeration. The study takes into consideration the specific character of the region, relating to coastal, and port-based shipping. Three research hypotheses formulated the study. General regression models were used to identify the health effects of air pollution and developed health costs were calculated in relation to the treatment of diseases. The findings have shown that air pollution and climatic conditions in the Tri-City aggravate the symptoms of bronchial asthma, while also increasing the number of cases of exacerbated chronic obstructive pulmonary disease and pneumonia. The evidence demonstrates the negative impact of shipping on the health condition of the inhabitants. The calculations have shown the extent of financial losses incurred in connection with the treatment of diseases found to have been caused by air pollution. The estimated health costs turned out to be significant for each of the examined diseases. The financial inefficiency of the Polish health care system has also been demonstrated. All the models have been identified for monthly data for the first time., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Czechowski, Piksa, Da̧browiecki, Oniszczuk-Jastrząbek, Czermański, Owczarek, Badyda and Cirella.)

The COVID-19 has wreaked havoc upon the world with over 248 million confirmed cases and a death toll of over 5 million. It is alarming that the United States contributes over 18% of these confirmed cases and 14% of the deaths. Researchers have proposed many forecasting models to predict the spread of COVID-19 at the national, state, and county levels. However, due to the large variety in the mitigation policies adopted by various state and local governments; and unpredictable social events during the pandemic, it is incredibly challenging to develop models that can provide accurate long-term forecasting for disease spread. In this paper, to address such a challenge, we introduce a new multi-period curve fitting model to give a short-term prediction of the COVID-19 spread in Metropolitan Statistical Areas (MSA) within the United States. Since most counties/cities within a single MSA usually adopt similar mitigation strategies, this allows us to substantially diminish the variety in adopted mitigation strategies within an MSA. At the same time, the multi-period framework enables us to incorporate the impact of significant social events and mitigation strategies in the model. We also propose a simple heuristic to estimate the COVID-19 fatality based on our spread prediction. Numerical experiments show that the proposed multi-period curve model achieves reasonably high accuracy in the prediction of the confirmed cases and fatality., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Majeed, Li, Peng and Lin.)