Ecotourism in Potatso National Park has been developing for more than 15 years, which has had important guiding significance for the development of China’s national parks. This paper analyzes ecotourism practices in Potatso by extracting related travel notes and adopting the ground theory and content analysis method. The results show that the current ecotourism practices in Potatso include 5 dimensions and 15 elements. The five dimensions are the natural environment, environmental education, community participation, ecotourism experience and socioeconomic background. The five most important elements are the ecosystem elements, sensory and behavioral ecotourism experience, ecological facilities and interpretation systems. There are also three contradictions: between tourists’ environmental awareness and lack of environmental behaviors, between community participation and residents’ reception capacity, and between environmental education and tourists’ experiences. Regarding the future development of Potatso, conservation will always come first. A breakthrough is needed to strengthen the conversion of environmental education to the environmental behavior of tourists, adjust the participation model of communities dynamically, and continue innovating in the form of environmental education.

Winning the battle against pollution and strengthening ecological protection in all respects are vital for promoting green development and building a moderately prosperous ecological civilization in China. Using the entropy weight method, this paper establishes and evaluates a comprehensive industrial pollution index that contains and synthesizes six major industrial pollutants (wastewater, COD, waste gas, SO₂, NO_x, and solid waste) in the 2006–2015 period. Subsequently, this paper studies the spatiotemporal characteristics and influencing factors of industrial pollution via the Moran index and spatial econometric analysis. The empirical results indicate that (1) the temporal evolution of the industrial pollution index is characterized by an overall trend of first decreasing and then increasing. (2) The industrial pollution index of each county has certain geographical disparities and significant spatially polarized characteristics in 2006, 2009, 2012, and 2015. (3) The Moran test shows that there is a relatively significant spatial autocorrelation of the industrial pollution index among counties and that the geographical distribution of the industrial pollution index tends to show clustering. (4) Spatial regression models that incorporate spatial factors better explain the influencing factors of industrial pollution. The economic development level, technological progress, and industrialization are negatively correlated with industrial pollution, while population density and industrial production capacity are positively correlated. (5) Consequently, as relevant policy recommendations, this paper proposes that environmental cooperation linkage mechanisms, environmental protection credit systems, and green technology innovation systems should be established in different geographical locations to achieve the goals of green county construction and sustainable development.

Background: Previous studies indicate that migrant integration is associated with migrants’ characteristics as well as restrictions and opportunities in receiving cities. However, the effect of receiving cities and the relationship between migrants and receiving cities have not been fully explored due to the lack of large samples from cities. The objective of this study is to examine the effects of receiving cities alone and their regulating role in the interaction with individual characteristics. Methods: Cross-city data on 154,044 Chinese domestic migrants above 15 years old in 289 cities from the 2017 China Migrants Dynamic Survey are used. Migrant integration is assessed by a four-dimensional model proposed by Esser, which is slightly adjusted according to the characteristics of Chinese migrants. A hierarchical linear model is used to measure the proportion of effects of city factors in migrant integration as well as the effects when city factors are considered alone and in interaction with individual factors. Results: The individual-level and city-level factors are responsible for 69.81% and 30.19% of the effect on migrant integration, respectively. City political factors do not affect migrant integration directly, and cities with larger sizes and higher wages can directly and significantly improve integration, while higher housing prices will directly inhibit integration. From the cross-level interaction of city and individual, different social, economic and political factors at the city level have an indirect impact on migrant integration by inhibiting or strengthening the effect of individual-level factors on migrant integration. Conclusion: This study is one of the first to show the effect of cities and the relationship between receiving cities and migrants on migrant integration by keeping the national context constant. It is necessary to weaken the social and economic privileges associated with a city’s administrative level and reduce the negative impact of cities’ social and economic conditions by implementing city agglomeration, developing advantageous industries and optimizing the industrial structure. It is also essential to improve migrants’ socioeconomic capital through social support, occupation training and contiguous education.