Optimizing natural boundary definition and functional zoning in protected areas: An integrated framework encompassing species, landscapes and ecosystems

To promote the harmonized development of economic construction and ecological protection, our study introduces an integrated framework that employs various methodologies to delineate natural reserve boundaries and spatial zoning. These methodologies aim to address issues such as insufficient protected area, excessive human-induced influences, and inadequate protection of endangered animals within nature reserve boundaries. Leveraging comprehensive data from diverse sources, including ground surveys and remote sensing detection, we conducted a survey using the Chebaling National Nature Reserve in China and its environs as a case study. Models such as the maximum entropy model (MaxEnt), Fragstats, and the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) were employed to identify areas with highly suitable habitats, significant landscape diversity, and superior ecosystem quality for 16 key species. Subsequently, the irreplaceable value of the research area was calculated using the Marxan model, leading to the establishment of a novel natural boundary and development plan. We propose expanding the original nature reserve to 1344 km², dividing it into a core reserve (321 km², 23.88%) and a general control area (1023 km², 76.12%). Additionally, we recommend further division of the general protected area into several functional zones to facilitate the integration of functional diversity and ecological protection. This contributes to a more scientifically informed and rational management approach for the Chebaling National Nature Reserve. Moreover, this integrated framework offers valuable insights for assessing and identifying animal habitats globally and spatially zoning other nature reserves

Air Quality Scenario Analysis Application of Multi-Domain Linkage Development in the Pearl River Delta

In the background of constructing a wold-class Guangdong-Hong Kong-Macao Great Bay Area (GBA), the growing demand for industrial, transportation and energy development in the Pearl River Delta (PRD) will put considerable pressure on improvement of regional air quality. It is important to choose a scientific development path to achieve both economic goal and air quality improvement target. This study uses scenario analysis method to construct three “industry-transport-energy” development scenarios within the region while the improvement level of air quality is simulated and analyzed. The results show that: (1) Considering the mutual constraints and influence relations between industry, transportation and energy in scenario analysis, the “industry-transport-energy” development scenario can be established to meets the same economic goal but has different development paths. (2) Along the historical track and established policy path, concentration of fine particulate matter (PM2.5) in the PRD can be reduced to 16.2 µg/m3 by 2035 as regional gross domestic product (GDP) reaching about 23.5 trillion. (3) Under the same economic goals, raising the proportion of emerging industries, freight by rail, public transport travel and non-fossil power to 95%, 10%, 73%, and 46% respectively leads to 29.6~49.2% reductions in the emissions of sulphur dioxide (SO2), nitrous oxides (NOx), primary PM2.5 and volatile organic compounds (VOCs) compared with those in 2017 that the regional PM2.5 concentration will further drop to 14.1 µg/m3. The results show that, under the constraints of economic development objectives, deepening structural adjustment can improve air quality, which gives advice for the PRD to choose its development path. Furthermore, this study can provide reference for the PRD to promote the transformation of industrial, transportation and energy development modes and structural adjustment under the dual objective of promoting the world-class bay area economic level and high-quality air level

Assessing Long-Term Trend of Particulate Matter Pollution in the Pearl River Delta Region Using Satellite Remote Sensing

Serious particulate matter (PM) pollution problems in many polluted regions of China have been frequently reported in recent years. Long-term exposure to ambient PM pollution is significantly associated with adverse health effects. Characterizing the long-term trends and variation in PM pollution is a basic requirement for evaluating long-term exposure and for guiding future policies to reduce the effects of air pollution on health. However, long-term, ground-based PM measurements are only available at a few fixed stations. In this study, an algorithm is developed and validated to estimate PM concentrations based on the satellite atmospheric optical depth with 1 km spatial resolution. The long-term trends of PM₁₀ concentrations in the entire Pearl River Delta (PRD) region and different cities are quantified and discussed. From 2001 to 2013, the PM₁₀ pollution of the entire PRD region was dominated by a decreasing trend of −0.15 ± 0.23 μg/m³·yr. This decreasing PM₁₀ trend was apparent over 75% of the PRD area, with the most significant decreases observed in the center of the region. However, the remaining 25%, mostly located in the outskirts of the region, showed an increasing PM₁₀ trend. This overall decreasing trend indicates the effectiveness of the control measures applied in the past decade for the primary pollutants