An outbreak of atypical pneumonia, now called COVID-19 and known to be caused by the novel coronavirus SARS-CoV-2, first detected in Wuhan, Hubei Province of the People’s Republic of China in December 2019 and afterwards rapidly spread worldwide. Wuhan and the Yangtze River Delta (YRD) region implemented first-level public health emergency responses to stop the spread of the virus on January 23rd, 2020. We tracked the geographical gravity centre of the disease and calculated spatial autocorrelation to explore the spatiotemporal patterns of distribution of imported and locally disseminated COVID-19 cases under the emergency-response control measure. We also applied polynomial regression analysis to estimate the trend of the COVID-19 in the YRD region before and after the control activities against the spread of the infection were instituted. The results show that the control measures applied have been effective. And, in the YRD region, areas with a large influx of population flow from Wuhan and Hubei Province had high risks of COVID-19. Therefore, identification of the spatiotemporal trends should be the first step when developing effective policies to manage and control any new epidemic. The results are not only informative locally but also useful for the rest of the world.

High-quality development is the theme of China’s economic and social development in the new era, the only way to build a powerful tourism economy, and also the objective demand to solve the practical problems and promote the transformation and upgrading of tourism. However, problems such as inefficient operation, environmental pollution, and slow industrial upgrading have become prominent in the development process of China’s tourism industry in recent years, in which a gap exists with the realization of high-quality development goals. Therefore, scientific control of the gap and deviation between the actual development level and the high-quality development goals of tourism is helpful for promoting the green and sustainable development of regional tourism. This study, taking the Taihu Lake Basin as an example, made a systematic and comprehensive evaluation of the spatial-temporal pattern of high-quality development mismatch of tourism from 2010 to 2019, using the health distance model to analyze its spatiotemporal evolution characteristics, and combining the obstacle degree model and qualitative comparative analysis of fuzzy set to analyze its influencing mechanism. The empirical results show that: (1) the mismatch degree of high-quality development of tourism in the Taihu Lake Basin shows a downward trend, and the regional imbalance is prominent, showing polarization characteristics; (2) among the six systems, only the green system and the cultural and tourism resource system are in the matching type, the dominant system of mismatch type is different in each city, and it shows the characteristics of the transformation from external environmental obstacle to internal environmental obstacle in the process of transition from mismatch type to matching type; (3) the spatiotemporal pattern of high-quality development mismatch of tourism is the result of six systems working together, in which the innovative development system is the core driving force, the coordinated development system is the potential driving force, the green development system is the direct driving force, the open development system has the guiding function, the shared development system is the external driving force, and the literature and tourism resource system is the basic driving force. Therefore, the paper puts forward three types of combination paths and corresponding suggestions that can promote the transformation and upgrading of tourism and achieve coordinated development of the Taihu Lake Basin.

With the development of economic globalization, urban agglomerations have become growth poles and core areas of economic development. By building knowledge innovation networks in urban agglomerations, we can effectively improve the strength of inter-city knowledge innovation links and better realize the integrated and synergistic development of the region. This study selected core cities in the Yangtze River Delta urban agglomeration as the study area, constructed the knowledge innovation network based on inter-city dissertation cooperation data from 2010 to 2020, and analyzed the characteristics and evolution of its knowledge network by combining social network analysis and geospatial analysis. The research results show that: (1) with changes in policies and investment in scientific research and innovation, intra-regional thesis cooperation in the Yangtze River Delta urban agglomeration has been increasing and the scale of the knowledge innovation cooperation network is growing; (2) in addition to the core cities radiating innovation resources outward to drive the development of other node cities, other cities are continuously improving their own innovation capabilities, taking the initiative to strengthen knowledge innovation cooperation with core cities and enhancing their own position in the network; (3) there are no longer isolated cities within the Yangtze River Delta urban agglomeration, and a multi-core knowledge network structure centered on Shanghai, Nanjing, Hangzhou, and Suzhou has initially formed, but the network is still spatially heterogeneous; (4) there are still problems within the Yangtze River Delta urban agglomeration such as uneven development of knowledge innovation and low participation of peripheral cities, which need to be addressed jointly by all regions. The article concludes with some suggestions for countermeasures to provide a reference for the Yangtze River Delta urban agglomeration to continuously strengthen intra-regional knowledge cooperation in the future, enhance regional competitiveness, and ultimately achieve synergistic development among cities.

This paper presents a spatial analysis of likely/potential hotspots of sustainability issues in Mainland China through an empirical investigation of patterns of ecological vulnerability in and of China’s megaregions. To be specific, this paper assesses the level of patterns of the ecological vulnerability of 16 megaregions through an indicator system, which includes soil erosion, desertification, ecosystem vulnerability, key ecological areas, and water and land resources. Empirical results reveal that while most megaregions are located in the less vulnerable areas, there are a couple of megaregions with a vulnerable basis of ecological environment. These megaregions consist of Chengdu-Chongqing, Guanzhong Tianshui Economic Zone, Shandong Peninsula, Wuhan City Circle, Beijing-Tianjin-Hebei, and Liaoning Coastal Belt. Furthermore, a typology of these megaregions is identified based on their development level and ecological vulnerability.

International hot topics such as carbon emission reduction and carbon neutrality and the growing regional ecological problems highlight the importance of low carbon development, and strengthening regional carbon emission research is increasingly important for exploring the path of global sustainable development in the new era. This study uses global and local spatial autocorrelation, geographic Detectors and Gini coefficients to carry out a dynamic comparative analysis of the spatial and temporal patterns of carbon emissions per capita of 41 cities in the Yangtze River Delta (YRD) urban agglomeration from 2006-2018 and to explore the driving forces. The results indicate that: 1) Over the study period, the per capita carbon emissions of the entire YRD urban agglomeration exhibited a “slow and subsequently sharp” continuous increase, while the corresponding Gini coefficient exhibited a “decreasing and subsequently increasing” trend. 2) Per capita carbon emissions at the city scale were spatially divergent from north to south, with the Yangtze River being the dividing line. Shanghai, Nanjing, Hangzhou and other municipalities or provincial capitals had much higher per capita carbon emissions than those of other cities, with the spatial “Matthew effect” being more obvious. 3) Per capita carbon emissions of the YRD urban agglomeration exhibited significant positive spatial correlations during the study period, with the high–high agglomeration cities gradually moving to the northwest and the low–low agglomeration cities remaining basically unchanged and but away from steady states slowly. 4) The gross industrial product, urbanization rate, and road length were the main drivers of increased per capita carbon emissions in this region; therefore, carbon reduction initiatives of local governments should fully consider any urban differences and play exemplary leading roles in developed cities and provincial capitals.

In recent years, the problem of unbalanced and insufficient development in the Yangtze River Delta (YRD) region has become increasingly prominent, posing higher requirements for regional coordinated development. Based on elucidating the connotations of the balanced development of regional coordination, this article constructed an evaluation index system for the balanced development of regional coordination in the YRD region in 12 dimensions, such as people’s living standards, basic public services, and beautiful ecology. It attempted to quantitatively reveal the level of balanced development of regional coordination in the YRD region in 2020 and develop optimization strategies using mathematical models such as the entropy method, spatial autocorrelation, and the Gini coefficient, which have important value for clarifying the inherent contradictions in the balanced development of regional coordination in this region and promoting regional sustainable development. The main conclusions are as follows: (1) At the provincial level, Jiangsu Province won in two sub-categories, coordination and integration; Zhejiang won in the balance sub-category; and Anhui performed better in the integration sub-category. (2) The main reasons for the significant differences between the cities were the public basic services in the equilibrium index, the industrial coordination and human–nature coordination in the coordination index, and the market unity sub-item in the integration index. (3) Based on the coordinated and balanced development level in each city’s regions, four types of regulatory areas were further divided, namely, key development areas, optimized development areas, relatively underdeveloped areas, and important safety barrier areas. Differentiated regulatory policies were proposed for these areas.