(Section A: Planning Strategies and Design Concepts)

This paper uses four years of ecosystem classification data, from 2000, 2005, 2010 and 2015, to analyse the spatiotemporal variation characteristics of the ecosystems of counties and cities in the Min Delta urban agglomeration over 15 years across four aspects, including changes in the ecosystem area for each period, a transfer matrix of the counties and cities, the comprehensive dynamic ecosystem index, and the forces driving these changes. The results show that: (1) from 2000 to 2015, the total area of farmland, forest and shrub ecosystems in the Min Delta urban agglomeration decreased, while the total area of urban, wetland and grassland ecosystems has increased. There are spatiotemporal differences and patterns in the area change and transfer of various ecosystems. The series of scales and proportion of ecosystem types in the counties and cities of the Min Triangle show that there is a two-way transfer between farmland and urban ecosystems. In addition, there are spatiotemporal differences in the transfer of these two ecosystems. Forest ecosystems are transferred into farmland, urban and grassland ecosystems at different levels. In the eastern part of the Min Triangle, wetlands are mostly transferred to urban ecosystems, and the western regions are mostly transferred to forests and farmland. (2) For the comprehensive dynamic index of the Min Delta urban agglomeration, from 2000 to 2015, the degree of ecosystem dynamics was higher in each period than the previous, and the dynamics in the eastern and central parts were higher than those in the west and south for the same period. From 2000 to 2005, the comprehensive dynamic index was below 0.2%. The dynamic index of Longhai in Xiamen and Zhangzhou increased significantly from 2005 to 2010 from that of the previous period, and their values all exceeded 0.9%. From 2010 to 2015, the area with a large change in the dynamic index expanded to the east and south from the central area of Xiamen. The dynamics in the northwest did not sufficiently increase. (3) The GDP, value of agricultural production, forestry, and fisheries, secondary and tertiary industries, urbanization rate, and permanent residents are important factors influencing ecosystems. The driving effects of these socioeconomic indicators and urban population development have different degrees of significance on farmland, urban, forest and wetland ecosystems during different periods of the Delta\u27s urban agglomeration

Mapping theorems on countable tightness and a question of F. Siwiec

summary:In this paper $ss$-quotient maps and $ssq$-spaces are introduced. It is shown that (1) countable tightness is characterized by $ss$-quotient maps and quotient maps; (2) a space has countable tightness if and only if it is a countably bi-quotient image of a locally countable space, which gives an answer for a question posed by F. Siwiec in 1975; (3) $ssq$-spaces are characterized as the $ss$-quotient images of metric spaces; (4) assuming $2^\omega<2^{\omega_1}$, a compact $T_2$-space is an $ssq$-space if and only if every countably compact subset is strongly sequentially closed, which improves some results about sequential spaces obtained by M. Ismail and P. Nyikos in 1980

Research on Driving Factors of Low-Carbon Development in Fujian Province

Based on the data related to carbon emissions in Fujian Province from 2000 to 2021, factor analysis and regression analysis were used to explore the key factors affecting low carbon development in Fujian Province. The results show that carbon emissions in Fujian Province are closely related to a variety of factors, including the consumption level of residents, international trade, urbanization, population size, fixed asset investment, energy intensity and economic development level, which have a relatively large impact on carbon emissions in Fujian Province, while the energy structure and industrial structure have a relatively small impact. Through the empirical analysis, we propose corresponding solutions to the current problems in order to promote the low-carbon development of Fujian Province

Estimates of Daily PM2.5 Exposure in Beijing Using Spatio-Temporal Kriging Model

Excessive exposure to ambient (outdoor) air pollution may greatly increase the incidences of respiratory and cardiovascular diseases. Accurate reports of the spatial-temporal distribution characteristics of daily PM2.5 exposure can effectively prevent and reduce the harm caused to humans. Based on the daily average concentration data of PM2.5 in Beijing in May 2014 and the spatio-temporal kriging (STK) theory, we selected the optimal STK fitting model and compared the spatial-temporal prediction accuracy of PM2.5 using the STK method and ordinary kriging (OK) method. We also reveal the spatial-temporal distribution characteristics of the daily PM2.5 exposure in Beijing. The results show the following: (1) The fitting error of the Bilonick model (BM) model which is the smallest (0.00648), and the fitting effect of the prediction model of STK is the best for daily PM2.5 exposure. (2) The cross-examination results show that the STK model (RMSE = 8.90) has significantly lower fitting errors than the OK model (RMSE = 10.70), so its simulation prediction accuracy is higher. (3) According to the interpolation of the STK model, the daily exposure of PM2.5 in Beijing in May 2014 has good continuity in both time and space. The overall air quality is good, and overall the spatial distribution is low in the north and high in the south, with the highest concentration in the southwestern region. (4) There is a certain degree of spatial heterogeneity in the cumulative duration at the good, moderate, and polluted grades of China National Standard. The areas with the longest cumulative duration at the good, moderate and polluted grades are in the north, southeast, and southwest of the study area, respectively

Demystifying the Economic Growth and CO₂ Nexus in Fujian’s Key Industries Based on Decoupling and LMDI Model

Faced with peaking carbon emissions and carbon neutrality goals, low-carbon transformation has become an important part of China’s current economic construction. Fujian is one of the provinces with the fastest economic development in China and the core area of the 21st Century Maritime Silk Road. Therefore, its low-carbon economic development path is of great significance to China. This study focused on the key carbon emission industries in Fujian Province, using energy and carbon emission data from industrial sectors in Fujian Province from 2005 to 2019 to establish the Tapio decoupling model. Then, we decomposed the carbon emission drivers of each industry using the LMDI decomposition method, and finally analyzed the decoupling efforts made by each carbon emission driver on the basis of the Tapio decoupling model and LMDI decomposition model. The results showed that (1) carbon emissions in Fujian Province were mainly concentrated in the manufacturing industry and the electricity, heat, gas, water production and supply industries; (2) to date, some industries in Fujian Province have achieved the decoupling of carbon emissions, but the decoupling status was not stable; and (3) both energy structure and energy intensity have facilitated increasing decoupling efforts for carbon emissions. Industrial structure has contributed less to decoupling, and population size has not yet to make an impact on decoupling. Therefore, in the future, Fujian Province should increase expenditure on green technology research and development to improve energy efficiency and gradually use renewable energy to replace fossil energy, continue to adjust the industrial structure, and increase the government’s supervision on corporate carbon emissions

Regional Differences, Temporal Evolution, and Drivers of Rural Hollowing in Coastal Provinces: A Case Study of Fujian Province

This research delves into the spatial and temporal evolution characteristics of rural areas, focusing on understanding the phenomenon of rural hollowing in Fujian Province and other coastal regions. By analyzing data from the Fujian Province Statistical Yearbook and the Social Development and National Economy Statistical Bulletin (2010–2020), employing methodologies such as Pearson correlation and the natural interruption point method in ArcGIS, this study seeks to provide both theoretical and practical groundwork for rural revitalization efforts. The findings of this study yield significant insights. Firstly, a pronounced geographical differentiation emerges in the context of rural hollowing in Fujian province, characterized by a distinctive “high inland and low coastal” spatial pattern. Secondly, despite its coastal location, Fujian Province continues to confront substantial rural hollowing challenges. Although the overall pace of rural hollowing development has been moderate, the persistence of population and economic hollowing is noteworthy. Consequently, the issues of depopulation and economic decline in rural areas remain pressing concerns for Fujian Province. Lastly, the investigation identifies key driving forces behind the phenomenon of rural hollowing, encompassing factors such as arable land area, rural population settlement rate, economic development level, and farmers’ net income. These drivers significantly influence the dynamics of rural hollowing. Drawing from the research findings, this study proposes several strategic recommendations to counteract rural hollowing in coastal regions. These include tailoring management approaches to address geographical disparities, enhancing resource allocation and land utilization practices, orchestrating shifts in industrial structure to foster integrated urban–rural development, and emphasizing the revitalization of talent to sustain the progress of rural areas