Analysis of the spatial characteristics and driving forces determining ecosystem quality of the Beijing-Tianjin-Hebei region

Priority areas and benefits of ecosystem restoration in Beijing

Ecological restoration can significantly improve ecosystem services and human well-being and provide a basis for regional coordinated development and ecological security. To guide restoration efforts, information on the potential benefits of restoration was required to efficiently target investments. Although the number of studies focusing on ecosystem restoration has increased in recent decades, priority areas that integrate ecological and economic benefits have yet to be identified. We developed and applied a prioritization approach to identify potential priority sites in Beijing. We used the historical environmental data on Beijing to identify areas of degradation and to assess the feasibility of restoration. Ecosystem service and quality degradation, low ecosystem quality, and soil erosion were integrated into one index to indicate the restoration importance. Potential restoration benefits were mapped using the monetary value of six ecosystem services. Based on the importance and benefits of restoration, three scenarios were developed to identify priority restoration areas. In Beijing, restoring 30% of the degraded area (1531 km2) in priority areas by 2050 could increase the annual ecological benefit by more than 5 billion yuan, or approximately 787 million USD, and could decrease the ecological degradation index by 50%. By integrating explicit spatial information on restoration importance and restoration benefits, this methodology provides a feasible way to identify restoration priority areas and assess restoration benefits.

Developing a method for assessing environmental sustainability based on the Google Earth Engine platform

Environmental sustainability is the foundation and of great significance for the sustainable development of urban agglomerations. Taking the Beijing-Tianjin-Hebei urban agglomeration as an example, we developed a method to effectively assess long-term regional environmental sustainability based on the Google Earth Engine (GEE) platform. We used the GEE to obtain 5206 Landsat remote sensing images in the region from 1983 to 2016 and developed the comprehensive environmental index (CEI) to assess regional environmental sustainability based on the theme-oriented framework proposed by the United Nations Commission on Sustainable Development. We found that the environmental sustainability of the urban agglomeration showed a trend of first rising, then falling, and then rising again in the past 30 years. The average CEI increased from 0.621 to 0.631 from 1985 to 1990, dropped to the lowest value of 0.618 in 2000, and then rose to the highest value of 0.672 in 2015. In particular, the extent of areas in which environmental sustainability improved (56% of the region) was greater than the extent of areas in which environmental deterioration occurred. The environmental sustainability of Hengshui, Xingtai, and Cangzhou in the southeast of the region has been significantly improved. The method proposed in this study provides an automatic, rapid, and extensible way to assess regional environmental sustainability and provides a scientific reference for improving the sustainability of the regional environment.

The Spatiotemporal Evolution and Prediction of Carbon Storage: A Case Study of Urban Agglomeration in China’s Beijing-Tianjin-Hebei Region

Due to rapid urban expansion, urban agglomerations face enormous challenges on their way to carbon neutrality. Regarding China’s urban agglomerations, 25% of the land contains 75% of the population, and all types of land are used efficiently and intensively. However, few studies have explored the spatiotemporal link between changes in land use and land cover (LULC) and carbon storage. In this work, the carbon storage changes from 1990 to 2020 were estimated using the InVEST model in China’s Beijing–Tianjin–Hebei (BTH) region. By coupling the Future Land Use Simulation (FLUS) model and InVEST model, the LULC and carbon storage changes in the BTH region in 2035 and 2050 under the natural evolution scenario (NES), economic priority scenario (EPS), ecological conservation scenario (ECS), and coordinated development scenario (CDS). Finally, the spatial autocorrelation analysis of regional carbon storage was developed for future zoning management. The results revealed the following: (1) the carbon storage in the BTH region exhibited a cumulative loss of 3.5 × 107 Mg from 1990 to 2020, and the carbon loss was serious between 2000 and 2010 due to rapid urbanization. (2) Excluding the ECS, the other three scenarios showed continued expansion of construction land. Under the EPS, the carbon storage was found to have the lowest value, which decreased to 16.05 × 108 Mg in 2035 and only 15.38 × 108 Mg in 2050; under the ECS, the carbon storage was predicted to reach the highest value, 18.22 × 108 Mg and 19.00 × 108 Mg, respectively; the CDS exhibited a similar trend as the NES, but the carbon storage was found to increase. (3) The carbon storage under the four scenarios was found to have a certain degree of similarity in terms of its spatial distribution; the high-value areas were found to be clustered in the northwestern part of Beijing and the northern and western parts of Hebei. As for the number of areas with high carbon storage, the ECS was found to be the most abundant, followed by the CDS, and the EPS was found to be the least. The findings of this study can help the BTH region implement the “dual carbon” target and provide a leading example for other urban agglomerations.

Convergent community structure of algal-bacterial consortia and its effects on advanced wastewater treatment and biomass production

Microalgal-bacterial consortium is an effective way to meet increasingly stringent standards in wastewater treatment. However, the mechanism of wastewater removal effect has not been properly explained in community structure by phycosphere. And little is known about that the concept of macroecology was introduced into phycosphere to explain the phenomenon. In the study, the algal-bacterial consortia with different ratios of algae and sludge were cultured in same aerobic wastewater within 48 h in photobioreactors (PSBRs). Community structure at start and end was texted by metagenomic analysis. Bray-Curtis similarities analysis based on microbial community showed that there was obvious convergent succession in all consortia, which is well known as "convergence" in macroecology. The result showed that Bray-Curtis similarities at End (overall above 0.88) were higher than these at Start (almost less than 0.66). In terms of community structure, the consortium with 5:1 ratio at Start are the more similar with the consortia at End by which the maximum removal of total dissolved nitrogen (TDN, 73.69%), total dissolved phosphorus (TDP, 94.40%) and NH3-N (93.26%) in wastewater treatment process and biomass production (98.2%) higher than other consortia, according with climax community in macroecology with the highest resource utilization than other communities. Therefore, the macroecology can be introduced into phycosphere to explain the consortium for advanced wastewater treatment and optimization community structure. And the study revealed a novel insight into treatment effect and community structure of algal-bacterial consortia for advanced wastewater treatment, a new idea for to shortening the culture time of consortium and optimize predicting their ecological community structure and predicting ecological community.

Land Use Dynamics and Optimization from 2000 to 2020 in East Guangdong Province, China

Anthropogenic land-use change is one of the main drivers of global environmental change. China has been on a fast track of land-use change since the Reform and Opening-up policy in 1978. In view of the situation, this study aims to optimize land use and provide a way to effectively coordinate the development and ecological protection in China. We took East Guangdong (EGD), an underdeveloped but populous region, as a case study. We used land-use changes indexes to demonstrate the land-use dynamics in EGD from 2000 to 2020, then identified the hot spots for fast-growing areas of built-up land and simulated land use in 2030 using the future land-use simulation (FLUS) model. The results indicated that the cropland and the built-up land changed in a large proportion during the study period. Then we established the ecological security pattern (ESP) according to the minimal cumulative resistance model (MCRM) based on the natural and socioeconomic factors. Corridors, buffer zones, and the key nodes were extracted by the MCRM to maintain landscape connectivity and key ecological processes of the study area. Moreover, the study showed the way to identify the conflict zones between future built-up land expansion with the corridors and buffer zones, which will be critical areas of consideration for future land-use management. Finally, some relevant policy recommendations are proposed based on the research result.