In the context of increasingly more countries actively advocating and investing in global climate governance actions, accurately examining the carbon emission effect of climate finance is of great significance for promoting sustained assistance from developed countries, laying out the post-2020 climate action, and building a community with a shared future for mankind. Based on the AidData, OECD-DAC CRS, and WDI database, this study obtained a national panel dataset of 77 recipient countries from 1980 to 2014. By constructing static and dynamic panel models, a moderating effect model, and a panel threshold model, this study investigated the impact of global climate finance on carbon emissions of recipient countries, and tested the moderating effect of income level between the above two. The results show that: (1) In general, climate finance had a significant negative impact on recipient countries’ carbon emissions, and the income level of recipient countries had a significant moderating effect on the carbon emission effect of climate finance. (2) With the increase of recipient countries’ income level, the carbon emission effect of climate finance shows a nonlinear characteristic of “from significant carbon reduction to insignificant carbon increase effect”. The recipient countries that achieved carbon reduction were mainly a few African countries. (3) To evaluate whether climate finance can achieve carbon reduction effect, the interaction between climate finance and recipient countries’ production and investment needs to be taken into account. Based on the above results, this study provided policy implications in terms of actively urging the implementation of relevant climate finance commitments, promoting low-carbon economic growth in recipient countries, and fully engaging in global climate governance through China’s dual identity.
Using the Eora database and Multi-Regional Input-Output (MRIO) model, this study calculated the embodied carbon emissions induced by domestic demand, export, and import of 189 countries (regions) in the world in 2000 and 2015. Based on this, net flow networks of embodied carbon emissions in global trade were constructed, carbon emissions flow problem was analyzed globally from the network perspective, and the status and relationship evolution trend of different countries (regions) in the global trade embodied carbon network was revealed. It is found that the net export of embodied carbon emission in trade was one of the key reasons for the rapid growth of carbon emissions in China, India, Iran, Indonesia, Saudi Arabia, South Africa, and other developing countries (regions), while the net import of embodied carbon emission through trade contributed to the decline of carbon emissions in the United States, Japan, Germany, the United Kingdom, France, and other developed countries (regions). Although the total net imports of embodied carbon emission in the United States, Japan, France, and other countries (regions) tend to decline, the embodied carbon emissions they import from China, India, and other major embodied carbon net export places have been increasing, and the sources of net imports are concentrated. In 2000 and 2015, there are four major communities in the global net embodied carbon flow network. The core of community changes from China, Russia, Saudi Arabia and Iraq to China, India, Russia and Saudi Arabia. The core status of China and India is strengthened, the size of their leading communities has continued to expand, while the community radiation capacity of Russia and Saudi Arabia has been weakened. Community core plays an important role in controlling and reducing embodied carbon emissions in global trade. China, India and other core countries (regions) should strive to reduce the carbon content per unit of energy-intensive products. Because the embodied carbon flow of trading countries (regions) in the same community is closer, the member countries of the same community can be the key support object of international response to climate change.
In response to the government’s reform of the energy pricing mechanism, the market should play a fundamental role in allocating resources. Based on the meta-frontier and slacks-based measure (SBM)-undesirable model, provincial data from 2000 to 2017 in 30 selected provinces of China were employed to analyze energy shadow price and energy environment efficiency of group frontier and meta-frontier in this study. Then, a provincial panel data model was used to analyze the influencing factors of shadow energy prices in China. The results indicate that Chinese energy environment efficiency is low, and regional energy environment efficiencies differ. The technology gap ratio of A: B: C group are 1: 0.571: 0.614, which shows clear technological heterogeneity. Second under the group frontier, China’s energy shadow price is rising, indicating that the economic value of China’s energy factors has increased. The potential room for energy shadow price increase in various provinces is different under the meta-frontier,Yunnan has the greatest potential and Beijing has the lowest potential. Third, government intervention, industrial structure, marketization reform, energy endowment, and energy consumption structure all have remarkable impacts on energy shadow price in a country or region, with different influencing mechanisms. Regional marketization reform has significant positive impact on the energy shadow price in A group. Regional government intervention inhibits the promotion of the energy shadow price in B group. Regional industrial structure inhibits the promotion of the energy shadow price in C group. We conclude that a one size fits all approach is inappropriate when promoting energy market reform and that people should consider the heterogeneity of technology when developing different energy pricing mechanism.
The study on carbon emissions of urban wastewater treatment system based on the “water-energy-carbon” nexus can reveal the internal relationship between resource flow, input process, and carbon emissions of a wastewater treatment system, and can provide important references for low-carbon operation and management of wastewater treatment systems. Based on the “water-energy-carbon” nexus, a theoretical framework and accounting method of carbon emissions of urban wastewater treatment system are constructed. The wastewater treatment plant (WWTP) in Zhengzhou City was taken as a case study. Carbon emissions of different links in the operation of the wastewater treatment system were evaluated. Analysis was also made on the factors that affect the dynamic change of carbon emissions in each link of the wastewater treatment system. The research results show that: (1) Among the carbon emissions generated by the operation of the wastewater treatment system, direct carbon emissions are dominant, and indirect carbon emissions (carbon emissions of energy consumption and carbon emissions of material consumption) are relatively small. (2) CH4 and N2O emissions per unit volume of wastewater treatment are mainly affected by wastewater treatment volume and water quality. (3) Carbon emissions of energy consumption and material consumption per unit volume of wastewater treatment decrease with the increase of the wastewater treatment volume. (4) Carbon emissions of urban wastewater treatment system are impacted by many factors, such as, wastewater treatment process, wastewater treatment capacity, operating conditions, post-treatment water quality requirements, treatment rate of returned water, and energy consumption types. It is of great significance for the low carbon operation of wastewater treatment system to strengthen the comprehensive management of resource input and circulation process of urban wastewater treatment system, and to promote synergy between water, energy saving, and carbon emissions reduction.
Evaluating the relationship between protected areas (PAs) and poor households of the surrounding communities accurately is crucial for realizing the dual objectives of biodiversity conservation and coordinated development of local communities. However, limited literature has analyzed the mechanism of the impact of PAs on household multidimensional poverty from the perspective of social capital. This study investigated 787 households around 14 PAs in Sichuan and Shaanxi Provinces, constructed an analytical framework of Protected Areas-Social Capital-Multidimensional Poverty, and analyzed the impact of PAs on multidimensional poverty of surrounding rural households based on an intermediary effect model. The results show that: (1) Households inside the PAs are more likely to fall into multidimensional poverty than those outside the PAs; (2) The establishment of protected areas impairs social capital to some extent, further leading to multidimensional poverty of rural households; (3) The intermediary effect of social capital shows significant differences at different administrative levels (national and provincial), between different provinces, and between PAs with and without ecotourism. Specifically, in PAs at the provincial level, PAs of Shannxi Province, and PAs having ecotourism, social capital has larger intermediary effects. Therefore, PA management should extend rural household social networks, enhance their social trust, and mobilize their social participation to improve the quality of rural household social capital and further develop their livelihoods.
Improving urban ecological efficiency is an important aspect of high-quality development of the Yangtze River Economic Belt. In this study, the minimum distance to strong efficient frontier data envelopment analysis (MinDS) model was used to measure the ecological efficiency of the cities in the Yangtze River Economic Belt. The Dagum Gini coefficient, Kernel density estimation, and Markov chain analysis were used to examine its spatial pattern and temporal trend, and the key influencing factors were tested using quantile regression. The study found that: (1) The level of ecological efficiency in downstream cities was significantly higher than that in the upper and middle reaches. (2) The overall difference in urban ecological efficiency was large but gradually decreasing. The intraregional difference in urban ecological efficiency was always the largest in the downstream areas, and the largest regional difference was between the upstream and the downstream regions. With the improvement of the level of ecological efficiency, the impact coefficients of factors such as technological innovation and public awareness of environmental protection had gradually decreased, which is an important reason for the reduction of the overall and intraregional differences. The influencing factors in different regions and their roles and directions were different, which provides a certain explanation for the regional differences in urban ecological efficiency. (3) Factors such as technological innovation and economic development level had relatively greater impact on cities of low-level and high-level urban ecological efficiency, which resulted in the trend of polarization and multi-polarization in the downstream and upstream regions, respectively. Factors such as economic development level, resource endowment, and industrial structure had low positive impact coefficients on cities of low, medium, and high levels of urban ecological efficiency, and the trend of urban ecological efficiency shift was not obvious, resulting in the overall and regional “club convergence” and “Matthew effect.” This study used the MinDS model to measure the urban ecological efficiency level, effectively avoided the defects of the traditional DEA model, further decomposed the source of the difference on the basis of its overall spatial difference identification, and predicted its long-term transfer trend. This deepened the understanding of the pattern of spatial and temporal change of ecological efficiency in the Yangtze River Economic Belt, which provides some reference for the coordinated promotion of green development of the Yangtze River Economic Belt.
High-quality industrial development is an important part of the strategy of ecological protection and high quality development in the Yellow River Basin. In order to study the spatial differentiation of high-quality industrial development in the Yellow River Basin in the past decade, this paper uses EFTP (ecological total factor productivity) as the measurement standard, measures and analyzes the industrial development level of the main cities and urban agglomerations in the Yellow River Basin from 2006 to 2016 through super efficiency DEA and Malmquist index model, and finds that: the industrial development quality level of the Yellow River Basin is uneven, with the overall performance of East > West > Middle, In particular, the productivity of Shandong Peninsula urban agglomeration is much higher than other regions. The neighbor effect of industrial EFTP in different cities is significant, showing the characteristics of aggregation distribution. During the study period, the industrial EFTP in the Yellow River Basin increased at an average annual rate of 7.5%, the growth rate in the western region was faster, the late development advantage was fully reflected, and the growth in the eastern and central regions was slower. The central region has always been at a low level of development. It is urgent to adjust industrial development strategies and improve technical efficiency in order to promote the overall high-quality development of industry in the Yellow River Basin.
In this study, based on ecosystem service theory, the contribution rate of ecosystems was introduced to improve the ecological well-being accounting method. On this basis, the spatial and temporal characteristics of per capita ecological well-being and ecological-economic efficiency were analyzed. In order to further clarify the policy implication of the evaluation results, a classification model of ecological well-being based on the perspective of relative equity and efficiency was proposed, ecological well-being was classified by relative well-being index and relative efficiency index, and the spatial and temporal distribution patterns of different types of ecological well-being was analyzed from 2000 to 2015 for 337 cities at prefecture-level and above in China. The research results can provide some references for promoting the construction of ecological civilization in China. The results indicate that during the study period the spatial distribution of per capita ecological well-being and ecological-economic efficiency of the 337 cities was very different in the two regions northwest and southeast of the “HU line,” their centers were located in Yushu Prefecture of Qinghai Province and Xinyang City of Henan Province, respectively, and moved to the northeast and southwest directions. A negative spatial correlation between ecological-economic efficiency and per capita ecological well-being was identified by the bivariate spatial autocorrelation method. The high-low clusters were mainly located in the eastern coastal cities of Hebei, Shandong, Jiangsu, Shanghai, and some cities of Anhui and Henan; the low-high groups were mainly gathered in the western cities; the low-low clusters were mainly located in Shanxi, Henan, and Anhui Provinces. The relative well-being and relative efficiency indices were used to classify the study area into four categories: the high efficiency-low well-being zone was mainly distributed in Hebei, Shandong, Shanxi, Henan, and Jiangsu Provinces; the low efficiency-high well-being zone was mainly distributed in western cities, most cities in the northeast, and cities in the southeast; the low efficiency-low well-being zone was mainly located at the junction of high efficiency-low well-being zone and low efficiency-high well-being zone; the high efficiency-high well-being zone was scattered. To realize the construction of ecological civilization in all regions of China, it is necessary to enhance the ecological-economic efficiency in the western region and the per capita ecological well-being in the eastern region.
Based on the intertemporal technical attributes, this study systematically explored the influence of age on farmers’ adoption of intertemporal green agricultural technology, and conducted an empirical test by employing the survey data of 1,372 farmers in Hebei, Shandong, Anhui, and Hubei Provinces and using a mediating effect model. The results show that, first, the effect of age on farmers’ adoption of intertemporal green agricultural technology is inverted U-shaped. Second, human capital and risk preference are two important mediating variables for the influence of age, whose mediating effects explain 71.94% of the effect of age. Third, information and scale of land parcels play an important role in promoting the younger farmers’ adoption of intertemporal green agricultural technology, while economic value cognition, poverty, water supply, subsidies, and punishment policies have a positive impact on the adoption of intertemporal green agricultural technology by older farmers. Social capital has a negative impact on the adoption of green technology of young farmers, but it is beneficial for old farmers to take action. In the long run, speeding up the cultivation of new professional farmers, improving the new agricultural management system, and further developing the agricultural insurance system are important ways and necessary guarantee for the adoption of intertemporal green agricultural technology.
Housing price has been a closely concerned issue of the government and the people. High vacancy rate under the high housing price is a common phenomenon, causing many concerns. However, whether the high vacancy rate can restrain the rise of housing price remains to be studied. For this reason, the authors took the average selling price of commercial housing in 35 key cities of China from 2007 to 2016 as the research object. By constructing a variable coefficient model with fixed influence, we analyzed the influence of housing vacancy rate and control variables on the fluctuation of housing price. The results are as follows. Vacancy rate is the main factor that caused the fluctuation of housing price in China, and the rise of vacancy rate restrained the rise of housing price to a certain extent. At the same time, housing price was also affected by other factors. The increase of land selling price was an important factor that induced the rise of housing price. Per capita income had a certain impact on housing price. The impact of population density on housing price in built-up areas was different. The fluctuation of housing price in different classes of cities was very different, which was mainly affected by vacancy rate. The vacancy rate of the first tier cities, second tier developed cities, and third tier cities had a greater negative effect on housing price. The land transfer price in the third tier cities had no significant effect on housing price. The population density of the first tier cities caused an upward thrust on the housing price. In conclusion, high vacancy rate was the main factor to restrain the rise of house price, and it was also the main reason for the difference of housing price fluctuation in different class of cities.
The integrative development of industry and tourism is a new trend. Studying the spatial distribution pattern of industrial tourism demonstration sites and causes has important practical significance for promoting industrial tourism to achieve high quality development. Taking 31 provinces and municipalities in China’s mainland as the research object, this study explored the spatial pattern of industrial tourism demonstration sites and influencing factors applying the nearest neighbor analysis, Kernel density estimation, spatial autocorrelation analysis, and hotspot analysis. The results show that: (1) Industrial tourism demonstration site density is greater in the eastern part of China than the west, which is highly consistent with the “Hu Line.” (2) Industrial tourism demonstration sites and urban agglomerations have a high degree of convergence, the spatial distribution pattern of multi-core-grouping based on urban agglomeration is presented with significant spatial agglomeration effects. (3) The neighboring regions of areas with higher concentration of industrial tourism demonstration sites have higher concentration of such sites, showing a certain level of spatial autocorrelation. The correlation degree is east > central > west; the hotspots and cold spots presented a circular pattern from east to west, and there is a typical Matthew effect. (4) There is a significant correlation between industrial development level, transportation conditions, resource endowment, and the spatial distribution of industrial tourism demonstration sites in China. In addition, national policies and local industrial cultural identity are also important factors that led to the spatial differences in industrial tourism demonstration sites. Provinces should leverage on the radiation capabilities of inter-provincial city clusters, metropolitan areas, and urban belts to promote the cross-regional and cross-industry development of industrial tourism, form industrial tourism clusters, and promote the green development of industrial tourism.
Exploring the impact of air quality on public outings based on big data not only can enrich the practical research on air quality issues, but also have important significance for strengthening air pollution control and promoting the development of tourism industry. Taking Harbin City as the research object, this study used the data of 16,554 Ctrip online reviews, the Ministry of Environmental Protection’s air quality index data, and historical weather data and constructed the number of public outings and satisfaction models based on negative binomial regression and ordered Probit regression to quantitatively assess the influences and degrees of air quality on public outings. The findings are as follows. (1) Controlling for other influencing factors such as temperature, wind speed, and holidays, air quality significantly affected the number of public outings and the satisfaction of outings. (2) The number of public outings decreased significantly with the increase of air pollution. Compared with excellent air quality, the number dropped by 40.1% when the air quality was severe, and by 15.1% when the air quality was good. (3) For the tourist attractions in Harbin City, severe air pollution significantly reduced satisfaction of public outings, while lower levels of air pollution did not significantly affect satisfaction of public outings. This research not only provides a new perspective with an accurate assessment of the influences of air quality on public outing behavior, but also provides references for relevant air pollution prevention and tourism policy formulation.
Under global warming conditions, artificial snowmaking has proved to be an effective adaptation measure to climate change for ski resorts. Based on the surface climate dataset (1981-2010) and new Intergovernmental Panel on Climate Change (IPCC) RCPs scenarios, this study assessed the impact of snow-making technology improvement (snow could be produced at -2℃ rather than -5℃) on ski season length in China under climate change using the SkiSim 2.0 model. The results show that average ski season length in China would increase by 3%~12% with improved snowmaking machine, and 78% of ski areas in China could maintain a ski season of over 100 days even under the RCP 8.5 scenario in the 2080s. Ski resorts that are highly affected by climate change (for example, north, east and central regions) would receive more benefits from new technology than slightly affected areas (for example, northeast and northwest). Furthermore, geographical environmental conditions are the fundamental factors that affect the length of ski season. No matter whether snow-making technology is improved or not, the dividing line for 100-day ski season in China under climate change is Changbai Mountain-Yinshan Mountain-Qilian Mountain-Tianshan Mountain. For mitigating and adapting to climate change, more attention should be paid to technological innovation in artificial snowmaking to ensure sustainable development of China’s ski industry from the supply side.
The cooperative governance of international rivers has become an important way to promote China’s neighborhood diplomacy. Many scholars have stressed that China should attach importance to inter-regional water resources cooperation mechanisms. However, China lacks the corresponding experience in designing such international river basin organizations. Therefore, China needs to understand the successful experiences and lessons of failure of international river basin organizations while continuously reviewing its own practical experiences. Based on these requirements, this study took the international river basin organization data collected by the Transboundary Freshwater Dispute Database (TFDD) as the research object, and expounded their development history, current situation, and other basic issues. The results show that the history of the international river basin organizations can be divided into three stages. International river basin organizations differ in organizational function, organizational category, structural characteristics, and governance mechanism. This study also reviewed the situation of the international river basin organizations in China and identified three key points with reference to international experiences. The design and selection of international river basin organization in China should fully respect the regional differences of the northeast, the northwest, and the southwest regions. At the same time, it is necessary to improve the daily management and emergency management capabilities of river basin organizations in China from the perspective of organizational structure and governance mechanism. However, the establishment and improvement of international river basin organizations is a long-term endeavor. It needs to adapt to the development stage of China’s cooperative development of international river basins. In particular, it needs to learn from the failure of many developing countries and establish a new type of international river basin organization under the vision of one community.
Global warming is accelerating the reshaping of the global natural and ecological environments. Water resources conflicts are intensifying, and hydro-political relations have become one of the most urgent and complex geo-relationships that countries and the international community need to face and handle. From the perspective of social networks, states’ hydro-political power is determined not only by the location, but also by the position of the hydro-political network. Based on the data of the International Water Event Database (IWED) from 1948 to 2008, the global hydro-political relationship was deconstructed from the perspective of conflict and cooperation and “embedded”, and the dynamics of global hydro-political structure were clarified from two aspects: network relationship characteristics and spatial evolution characteristics. The results show that: (1) Water conflict network and water cooperation network hotspots showed a significant spatial displacement. Water conflict network hotspots shifted from Central Asia to South Asia and Southeast Asia, while South Asia and Southeast Asia have gradually become the hotspots for water cooperation; (2) The inter-country water conflict network and the inter-country water cooperation network both showed obvious core-periphery structure, and there were obvious replacing processes among different circles; (3) The inter-country hydro-political relation network can be divided into several communities compared with the community agglomeration mode of water conflict among countries, the inter-country water cooperation network community structure is more compact, showing a broader geographical span; (4) The situation of international water political relations can be roughly divided into three stages: the tense stage of the 1940s and the 1970s, the quiet stage of the 1980s, and the stage of violent fluctuations after the 1990s. According to the value of inter-country hydro-political relations, the hydro-political bilateral relationship can be divided into in tension relationship, friendly relationship, and relatively stable relationship. International water events are mainly based on cooperation, and friendly relationships are the mainstream of bilateral relations in hydro-political relations.
In the recent decades, increased climate change and human activities have been affecting the spatial and temporal distribution of water resources and water balance components in the inland region of Northwest China. This study used a remote sensing cloud computing platform, Google Earth Engine (GEE), to explore the spatial and temporal dynamics of water balance components in this area at both basin and sub-basin scales with both interannual and intraannual analyses over the last two decades. Multi-source remote sensing datasets were employed to fulfill this purpose. The study tried to reveal the spatial distribution characteristics and temporal change of key water balance components, including terrestrial water storage, precipitation, soil moisture, evapotranspiration, and surface water. The results show that: (1) At the whole basin scale, due to the increasing trend of air temperature, glaciers and snow in high altitude areas were melting with an increasing speed, which provides more water supply to the low altitude basins. Therefore, the terrestrial water storage exhibit a pattern of “decreasing at high altitude and increasing at low altitude”. Meanwhile, surface water area, soil moisture and evapotranspiration also showed a certain increasing trend accordingly. (2) At temporal scale, except for the desert areas, different water balance components exhibited different seasonal variations. The value of each component generally reaches the maximum in the summer and the autumn, and becomes the lowest in the spring and the winter. (3) At sub-basin scale, due to the different combinations of water sources, the variation patterns between different water balance components differ from sub-basin to sub-basin. In the ice and snow water dominated sub-basins, each component showed a similar variation pattern as the terrestrial water storage, while in the precipitation dominated sub-basins, the variation of each component is more closely related to precipitation fluctuation. In conclusion, different water balance components exhibit different characteristics at different spatial and temporal scales in the inland area. This study provides valuable reference for further understanding the co-evolution pattern of these components.