Search

Clean air actions (CAAs) in China have been linked to considerable benefits in public health. However, whether the beneficial effects of CAAs are equally distributed geographically is unknown. Using high-resolution maps of the distributions of major air pollutants (fine particulate matter [PM2.5] and ozone [O3]) and population, we aimed to track spatiotemporal changes in health impacts from, and geographic inequality embedded in, the reduced exposures to PM2.5 and O3 from 2013 to 2020. We used a method established by the Global Burden of Diseases Study. By analyzing the changes in loss of life expectancy (LLE) attributable to PM2.5 and O3, we calculated the gain of life expectancy (GLE) to quantify the health benefits of the air-quality improvement. Finally, we assessed the geographic inequality embedded in the GLE using the Gini index (GI). Based on risk assessments of PM2.5 and O3, during the first stage of CAAs (2013 to 2017), the mean GLE was 1.87 months. Half of the sum of the GLE was disproportionally distributed in about one quarter of the population exposed (GI 0.44). During the second stage of CAAs (2017 to 2020), the mean GLE increased to 3.94 months and geographic inequality decreased (GI 0.18). According to our assessments, CAAs were enhanced, from the first to second stages, in terms of not only preventing premature mortality but also ameliorating health inequalities. The enhancements were related to increased sensitivity to the health effects of air pollution and synergic control of PM2.5 and O3 levels. Our findings will contribute to optimizing future CAAs. [ABSTRACT FROM AUTHOR]

Continuous efforts are needed to combat air pollution-related diseases in China, requiring a combination of health-oriented strategies in addition to emission control measures.Theses strategies include the revision of air quality standards, the pursuit of carbon neutrality, and the enhancement of air pollution resilience in alignment with the Healthy China 2030 initiative. [Display omitted] [ABSTRACT FROM AUTHOR]

• The Carbon sink capacity of a typical ecotypic county was precisely estimated. • STARFM was employed to estimate interannual NEP at county scale. • The NEP dataset at a 30 m grid scale from 2000 to 2020 was generated. • Spatio-temporal dynamics of NEP in ecotype county were grasped. Net ecosystem productivity (NEP) serves as a pivotal metric for quantitatively elucidating the carbon sink function of terrestrial ecosystems. As a prototype county for the development of an ecological civilization in China, the quantitative estimation of the ecotypic county's ecosystem carbon sink capacity holds immense significance in comprehending the carbon cycle and facilitating the sustainable advancement of regional ecosystems. This study undertook the estimation of NEP in Wuning County from 2000 to 2020, employing a fusion of multi-source remote sensing data, the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), the improved Carnegie-Ames-Stanford Approach model, and the soil respiration model. Furthermore, we delved into the differences in NEP across various types of land cover. In addition, we employed the Theil-Sen Median trend analysis and Mann-Kendall test to discern the spatio-temporal trends of NEP. The findings indicated the following: (1) The downscaled NDVI generated by STARFM exhibited a remarkable consistency with Landsat NDVI overall (R 2 > 0.95, P < 0.01, 0 < RMSE < 0.1). (2) The gross NEP from 2000 to 2020 in the study area ranged from 542.78 to 720 Gg C, with a multi-year average NEP of 183.84 g C m−2 yr−1. The simulated NEP demonstrated higher accuracy when compared to the measured data (R 2 = 0.79, P < 0.01). (3) The NEP exhibited a spatial pattern characterized by lower values in the central area and higher values in the north and south. Approximately 89.60 % of the total area demonstrated an increase in NEP, with woodland acting as the primary contributor, while 4.50 % of the total area displayed a decreasing trend, predominantly due to the expansion of built-up land. (4) Notable variations in NEP existed among different types of land cover. In terms of vegetation types, the annual average NEP ranked as follows: woodland > grassland > cropland. The application of STARFM has provided valuable insights into the methodology for precise delineation of spatio-temporal dynamics of NEP at the county scale. The outcomes of this study have furnished support for implementing climate change mitigation strategies in ecologically-oriented counties and the bottom-up promotion of China's carbon peaking and carbon neutrality goals. [ABSTRACT FROM AUTHOR]

Exploring the spatiotemporal characteristics of ecosystem services (ESs) and their drivers is crucial for managers to develop significant scientific policies that further sustainable development. We used the Yangtze River Economic Belt (YREB) to explore the trends, hotspots, and drivers of water yield (WY), soil conservation (SC), carbon sequestration (CS), and food supply (FS) between 2000 and 2020. Similarly, we analyzed relationships among ESs and drivers of the multiple ecosystem services landscape index (MESLI). We used the self-organizing map method to obtain the types and distribution of the ES bundles, revealing the bundles, trade-offs, and synergies among ESs. The four ESs had an increasing trend, with CS having the highest increase; ES hotspot analysis showed differences among upper, middle, and lower reaches. Constraint lines among ESs and drivers were diverse; the corresponding SC and WY reached thresholds when CS values were 1477.81 and 460.5 t km−2, respectively. When FS values were 67.34 and 86.17 × 104 Yuan·km−2, CS and WY reached their thresholds. All critical drivers of the four ESs were natural factors. The thresholds that the MESLI reached with driver status were 1000 mm (evapotranspiration), 2121 mm (precipitation), 2.42° (slope), 1.46% (soil organic matter), 36.08% (sand), 30.75% (proportion of non-agricultural population), 18.57% (cropland proportion), 1.05 × 104 persons·km−2 (population density), and 84.84% (proportion of non-agricultural industries in total gross domestic product), respectively. FS, water supply, and ecological conservation bundles changed over the 20 years, and trade-offs and synergies among ESs within bundles differed. We revealed the complexity of ESs from multiple perspectives, which will enable the development of ecosystem management and conservation recommendations for the YREB and large-scale economic zones worldwide. [Display omitted] • Four types of ESs and MESLI showed an overall increasing trend from 2000 to 2020. • Characteristics and relationships of multi-ES were analyzed from multi-perspectives. • Thresholds were obtained between ES-ES, and ES-drivers. • Precipitation was the most important driver of MESLI. [ABSTRACT FROM AUTHOR]

[Display omitted] • Exhibited spatial heterogeneity of ecosystem services (ESs). • Drivers of ESs had clear spatial distribution zoning rules. • Revealed threshold curves for the transform of ESs drivers. • Proposed an EEs-enhancing ecological conservation strategy. Investigating large-scale spatial patterns of ecosystem services (ESs) and their underlying drivers can greatly contribute to policies-making and regional sustainability development. With water yield (WY), soil conservation (SC), and carbon sequestration (CS) as representative ESs, we aim to quantify their spatial patterns in the Yangtze River Economic Belt, China, and to identify their driving factors, and to formulate sound environmental management strategies. Spatial geography and socioeconomic data from 2000 to 2020 were mined and a range of research methods, including multiscale geographic weighted regression, self-organizing maps, and linear discriminant analysis, were employed for such a purpose. Annual average WY, SC, and CS were 403 mm, 9897 t·km−1, and 1071 g·CO 2 ·m−2. The three ESs examined exhibit spatial heterogeneity. WY exhibited significant patterns of variation along the north–south gradient, while SC and CS exhibited significant variation along the topographic gradient. In the context of high correlation of driving factors among ESs, WY and SC exhibited a greater sensitivity to natural factors (such as precipitation), while CS demonstrated a height sensitivity to human activities in addition to vegetation cover. Spatial heterogeneity is pronounced among the main driving factors of ESs. Three threshold equations were established to describe the manner in which driving factors of different regional ecosystem services undergo transformations, equations possessed a high level of credibility in this study (coincidence > 80 %). This study reveals spatial variations in ecosystem services and their natural and socio-economic drivers. More specifically, we quantitatively validated the threshold in the expression of ecosystem service drivers, establishing a strong scientific foundation for regional ecosystem conservation and management. [ABSTRACT FROM AUTHOR]