Ying Li

The coordinated advancement of cultural, tourism and ecological industry construction is of great significance to the high-quality development of the Yellow River Basin. Based on culture-tourism-ecology panel data of the nine provinces and autonomous regions in the Yellow River Basin from 2012 to 2022, a modified coupling model was constructed using the entropy method to measure the development levels of culture, tourism, and ecology across the provinces and autonomous regions in the basin. Separately, the modified gravity model, social network analysis, and Dynamic QAP were employed to examine the structural characteristics and influencing factors of the spatial correlation network. The results show that from 2012 to 2022, the development levels of culture, tourism and ecology in the Yellow River Basin have trended upward with fluctuations, with the relative development levels being ecology>culture>tourism, and the comprehensive development has spatial heterogeneity. Regionally, the coupling coordination degree follows a clear spatial pattern that is generally higher in the east and south, and lower in the west and north of the basin. The spatial correlation network within the Yellow River Basin is growing in density and complexity, and it is characterized by multi-threaded interconnections. Shanxi Province occupies a central position in this network, as it maintains strong linkages with other provinces, while Sichuan Province is in a marginal position in the network and has weak connections with other provinces. Inner Mongolia, Shandong, Gansu and Sichuan are “central provinces” in the spatial correlation network, and they are controlling and influencing the external radiation and spatial spillover of culture, tourism and ecology in the basin, while Qinghai and Ningxia are relatively marginalized. Among the factors influencing the spatial network structure, spatial adjacency and economic development level have significant impacts. Infrastructure differences have changed from being “irrelevant” to being “important drivers”. Differences in human capital and government macro-control have changed from marginally significant to having no impact.

This research based on the Stimulus‐Organism‐Response (SOR) theory and from the perspective of tourists' “presence”, this paper takes “Dark Ride (DR)” recreation facility in Universal Beijing Resort as the research object to analyze factors that affect tourists' production of “presence” as well as the process that “presence” generated by virtual environment affects tourists' destination behavior intention. The results show that: (1) Great quality of tourists' DR experience in virtual environment and engagement in DR recreation facility let them feel more “immersive” in DR, thereby enhancing them produce DR “presence”; (2) The DR “presence” has a positive impact on the tourist destination behavior intention. The mechanism is that tourist's DR “presence” promotes their positive destination behavior intention by triggering their emotional response and then promoting their attitude change toward the destination. The paper enriches the application research of VR in the tourism field.

With the continuous growth of China′s national economy, the people′s spiritual and cultural consumption needs are strong. Cultural and leisure venues are one of the most important spaces for meeting people's increasing needs for a better life. Taking 5625 cultural and leisure venues in Beijing as the research object, we analyzed the spatial and temporal distribution characteristics of the cultural and leisure venues in Beijing from 1994–2019, and the factors influencing them, by using the analysis methods of barycentric coordinates, standard deviation ellipse, kernel density analysis, spatial autocorrelation and Geodetector. The results show four main aspects of this system. (1) The spatial distribution of cultural and leisure venues in Beijing is uneven and shows a “core-edge” pattern. In the long run, there has been a tendency for cultural and leisure venues to spread into the northern and southern suburbs. (2) Beijing's cultural and leisure venues have evolved from a “single-core cluster” in the central city to a “dual-core coexistence” in both the central city and Tongzhou District, in addition to a spatial trend of spreading throughout the whole city. (3) Located in the central city, Xicheng, Dongcheng, Chaoyang and Fengtai form the HH agglomeration of cultural and leisure venues in Beijing, while Huairou and Miyun constitute the LL agglomeration. (4) The spatial distribution of cultural and leisure venues in Beijing is affected by many factors, such as the economy, population, transportation, education and policies, and the main driver is changing from a combination of “economy” and “demand” to the single factor of “economy”.

The condition of the tourism environment is the key factor that affects the tourism experience. A comprehensive evaluation of the tourism environmental suitability score is of great significance for guiding tourism planning and decision-making, improving the suitability score of the tourism environment in a targeted manner and guaranteeing the sustainable development of tourist cities. By adopting various indicators, such as the Universal Thermal Climate Index, the amount of precipitation, the vegetation index, the concentration of fine particulate matter in the atmosphere, and the ultraviolet radiation intensity index, this study quantifies the comfort level of weather, the weather impacts, the vegetation status, the atmospheric environment, ultraviolet radiation, and other key factors. Based on employing the AHP-TOPSIS algorithm, this study then conducts a comprehensive evaluation of China's tourism environmental suitability score and a comprehensive comparative analysis of the tourism environmental suitability scores of three typical tourist areas: the Beijing-Tianjin-Tangshan area, the Yangtze River Delta and the Pearl River Delta. The results show that the tourism environmental suitability score in China has obvious characteristics of spatial differentiation: the scores in East and South China are the highest while the score in the north-west inland area is the lowest. Among the three typical tourist areas, the Pearl River Delta region has the highest tourism environmental suitability score, followed by the Yangtze River Delta region, and the Beijing-Tianjin-Tangshan region has the lowest score. The northern regions of the Beijing-Tianjin-Tangshan area, the southern regions of the Yangtze River Delta and the surrounding areas of the Pearl River Delta are more suitable for the sustainable development of the tourism industry. PM2.5 is the main factor limiting the tourism environmental suitability scores in the Beijing-Tianjin-Tangshan area and the Yangtze River Delta, so atmospheric environment management will be an effective way to improve their tourism environmental suitability scores.

Zhangjiakou is a northern Chinese city that hosted the Beijing 2022 Winter Olympic Games. As an important ice and snow tourist destination, it is essential to investigate Zhangjiakou's rate of landscape pattern change, the landscape ecological security level, and ecosystem service value, particularly the tourism ecological service value during its construction. With land use data from 2000 to 2020, this study comprehensively analyzed the dynamic changes in Zhangjiakou, including land use dynamics, the land use transfer matrix, landscape vulnerability, landscape disturbance, ecosystem service value, tourism ecological service value, and other aspects. The results show that the landscape pattern in Zhangjiakou was greatly disturbed from 2015 to 2018, and the landscape ecological security was threatened in the process of landscape pattern adjustment. By 2020, after the landscape pattern was adjusted and stabilized, the landscape ecological security was restored, and the ecosystem service value was significantly improved, especially the tourism ecological service value. The results of this study will play an important role in promoting the optimization of Zhangjiakou's ice and snow landscape pattern and the improvement of tourism ecological value. In addition, it provides important lessons for the development of other ice and snow tourist destinations.

With the aim of guaranteeing the interests and health of tourists, this study comprehensively evaluates the suitability of the environment in different cities in China for tourism by considering the impacts of climate, vegetation and environmental factors on health. The Universal Thermal Climate Index (UTCI), total precipitation (PREC), Vegetation Leaf Area Index (LAI), concentration of particulate matter with a diameter of less than 2.5 μm (PM_2.5), and the downward UV radiation at the surface (UVB) are used as indices. In addition, the Delphi–AHP–TOPSIS algorithm is introduced and is used for the comprehensive evaluation of the environmental suitability of 684 cities in China for tourism in 2019. It is found that Chinese cities vary greatly in terms of the suitability of their environments for tourism. Among the factors that affect the environmental suitability, the LAI is important, with an increase in the LAI generally being advantageous. In contrast, an increase in the PM_2.5 concentration is a key factor that limits the environmental suitability of an area. Thus, urban landscaping and control of the atmospheric quality are essential and effective ways of improving the suitability of the environment of cities in China for tourists.

The variation of NO₂ concentrations in mainland China is analyzed on different timescales, from decadal to weekly, using both satellite data and data from ground-based monitoring networks. TROPOMI (TROPOspheric Monitoring Instrument) data were used to study the spatial variations of tropospheric NO₂ vertical column densities (TVCDs) over the study area during 16–20 weeks after the Chinese Spring Festival (25 January 2020). These data were used to select 11 regions for more detailed analysis of the variation of NO₂ TVCDs on a decadal timescale. In this analysis, monthly and annual averaged NO₂ TVCDs derived from OMI (Ozone Monitoring Instrument) observations were used for the years 2011 to 2019. The results show the NO₂ TVCD trends for different regions, all decreasing in response to emission reduction policies but with a different onset and a possible halt of the decrease in recent years; trends and period in the south of the study area are different from those in the north. Variations of NO₂ TVCDs on shorter timescales, monthly and weekly, were analyzed using TROPOMI data. In addition, the variations of weekly-averaged ground-based NO₂ concentrations in 11 major cities were analyzed together with those for O₃ and PM_2.5. In particular these data were used to determine their effect on the air quality as expressed by the air quality index (AQI). For quantitative estimates, the use of weekly concentrations is more accurate than the use of monthly values, and the effects of long-term trends and their reversal needs to be taken into account for the separation of effects of the lockdown and the Spring Festival. Neglecting the possible reversal of the trends leads to overestimation of the lockdown effect in the south and underestimation in the north. The ground-based data confirm earlier reports, based on satellite observations, that the expected improvement of air quality due to the reduction of NO₂ concentrations was offset by the increase of the concentrations of O₃ and the different effects of the lockdown measures on PM_2.5, as well as effects of meteorological influences and heterogeneous chemistry. The AQI seems to be mostly influenced by PM_2.5 rather than NO₂. A qualitative comparison between time series of satellite and ground-based NO₂ observations shows both similarities and differences. The study further shows the different behaviors in city clusters in the north and south of China, as well as inland in the Sichuan and Guanzhong basins. Effects of other holidays and events are small, except in Beijing where the air quality in 2020 was notably better than in previous years. This study was undertaken for China, but the methodology and results have consequences for air quality studies in other areas, and part of the conclusions are generally applicable.

The air pollution in China is among the highest in the world. However, legislation to reduce pollutant emissions have been successful and concentrations of SO₂ (since 2007), aerosols (since 2011) and NO₂ (since 2012) have decreased substantially as deduced from satellite and ground-based observations. The strong reduction of the emissions by the end of January 2020, first caused by the Spring Festival holidays and enhanced and extended by the COVID-19 lockdown, offered an opportunity to study the effects on air quality across the country. In particular the reduction of NO₂ concentrations observed using the TROPOspheric Monitoring Instrument (TROPOMI) on board the Copernicus Sentinel-5 Precursor satellite was used to quantitatively estimate the lockdown effect. To determine a baseline for the expected concentrations in 2020, we used Ozone Monitoring Instrument (OMI) NO₂ TVCD time series from 2011 to 2019 and determined trends for different regions, noticing a possible halt of the decrease in recent years, but for different periods in the south than in the north of east China. Neglecting this leveling leads to overestimation of the lockdown effect on the concentrations in the south, neglecting the trends may lead to underestimation in the north. We also looked at the temporal resolution used in studies on the reduction of the concentrations and noticed the gradual decrease ahead of the Spring Festival, which actually continued during 3 weeks into the lockdown. Using satellite observations of other species and ground-based monitoring data, it was noticed that the expected improvement of air quality due to the reduction of NO₂ concentrations was offset by the increase of the concentrations of aerosols and O₃ ascribed to meteorological influences and complex chemistry. In the current study we use TROPOMI tropospheric NO₂ vertical column densities (TVCDs) together with ground-based monitoring data for NO₂, SO₂, CO, O₃, PM_2.5 and PM₁₀ in 11 regions around large cities to evaluate the evolution of their concentrations during 19 weeks after the Spring Festival and their effect on air quality. For comparison, and in an attempt to average out short term (e.g., meteorological) influences, ground based monitoring data were used for the same period in 2015–2019. The results confirm that the strong reduction of NO₂ does not always imply good air quality because concentrations of other pollutants may increase. The study shows the different behavior in city clusters in the north and south of China, and inland in the Sichuan and Guanzhong basins. Effect of other holidays and events are small, except in Beijing where the air quality in 2020 was notably better than in previous years. This study was undertaken for east China, but the methodology can also be used for other areas and part of the conclusions are generally applicable.

The outbreak of the COVID-19 virus in Wuhan, China, in January 2020 just before the Spring Festival and subsequent country-wide measures to contain the virus, effectively resulted in the lock-down of the country. Most industries and businesses were closed, traffic was largely reduced, and people were restrained to their homes. This resulted in the reduction of emissions of trace gases and aerosols, the concentrations of which were strongly reduced in many cities around the country. Satellite imagery from the TROPOspheric Monitoring Instrument (TROPOMI) showed an enormous reduction of tropospheric NO₂ concentrations, but aerosol optical depth (AOD), as a measure of the amount of aerosols, was less affected, likely due to the different formation mechanisms and the influence of meteorological factors. In this study, satellite data and ground-based observations were used together to estimate the separate effects of the Spring Festival and the COVID-19 containment measures on atmospheric composition in the winter of 2020. To achieve this, data were analyzed for a period from 30 days before to 60 days after the Spring Festivals in 2017–2020. This extended period of time, including similar periods in previous years, were selected to account for both the decreasing concentrations in response to air pollution control measures, and meteorological effects on concentrations of trace gases and aerosols. Satellite data from TROPOMI provided the spatial distributions over mainland China of the tropospheric vertical column density (VCD) of NO₂, and VCD of SO₂ and CO. The MODerate resolution Imaging Spectroradiometer (MODIS) provided the aerosol optical depth (AOD). The comparison of the satellite data for different periods showed a large reduction of, e.g., NO₂ tropospheric VCDs due to the Spring Festival of up to 80% in some regions, and an additional reduction due to the COVID-19 containment measures of up to 70% in highly populated areas with intensive anthropogenic activities. In other areas, both effects are very small. Ground-based in situ observations from 26 provincial capitals provided concentrations of NO₂, SO₂, CO, O₃, PM_2.5, and PM₁₀. The analysis of these data was focused on the situation in Wuhan, based on daily averaged concentrations. The NO₂ concentrations started to decrease a few days before the Spring Festival and increased after about two weeks, except in 2020 when they continued to be low. SO₂ concentrations behaved in a similar way, whereas CO, PM_2.5, and PM₁₀ also decreased during the Spring Festival but did not trace NO₂ concentrations as SO₂ did. As could be expected from atmospheric chemistry considerations, O₃ concentrations increased. The analysis of the effects of the Spring Festival and the COVID-19 containment measures was complicated due to meteorological influences. Uncertainties contributing to the estimates of the different effects on the trace gas concentrations are discussed. The situation in Wuhan is compared with that in 26 provincial capitals based on 30-day averages for four years, showing different effects across China.