Terrestrial ecosystem carbon storage (TECS) could significantly affect the concentration of atmospheric CO₂, which is critical for climate change prediction. Along these lines, the Integrated Valuation of Ecosystem Services and Trade-offs model was employed to determine the TECS of Hainan Island (HN) from 2015 to 2050 accurately. Besides, the Future Land-use Simulation model combined with natural and anthropogenic factors was used to forecast the land-use types from 2025 to 2050 in HN by considering different Shared-socioeconomic pathway-Rrepresentative concentration pathway (SSP-RCP) scenarios. Finally, the geographical detector explored the influence mechanism concerning the TECS. Under the SSP1-RCP1.9 scenario, the TECS of HN will be gradually increased to 388.10 million tons in 2050, mainly due to the increase in forest areas and the fact that the majority of grassland in the western part of HN is being converted into forest. Under different SSP-RCP scenarios except for SSP1-RCP1.9, HN's TECS is expected to gradually decrease from 2015 to 2050, mainly due to the loss of grassland and forest in coastal low-altitude areas. From the single/pair factor perspective influenced mechanism concerning the TECS, the elevation (DEM) and DEM∩Slope were found to be the dominant single/pair factor under the SSP1-RCP1.9, SSP1-RCP2.6 and SSP2-RCP4.5 scenarios. The least distance to residential area (LDP) and LDP∩LDR (i.e. LDP and least distance to roads or railways) were found to be the dominant factors under the SSP3-RCP7.0, SSP4-RCP3.4, SSP4-RCP6.0, SSP5-RCP3.4 and SSP5-RCP8.5 scenarios. Besides, the pair factors provided a higher determinant power for TECS than a single factor. Given the results of the TECS and the influence mechanism concerning the TECS under different SSP-RCP scenarios, we suggest reasonably planning the transportation network and limiting the disorderly expansion of construction land.

Data on particulate matter, gaseous pollutants, and AQI values from three cities (Haikou, Sanya, and Danzhou) between January 2018 and December 2022 were obtained in order to analyze the spatiotemporal distribution characteristics of air pollution, the correlation between pollutants with meteorological conditions, and the potential sources in Hainan Island. The spatiotemporal distribution’s characteristics demonstrated that the annual mean concentrations of SO₂, NO₂, CO, O₃, PM₁₀ and PM_2.5 were 4.34 ± 1.11 μg m⁻³, 9.87 ± 1.87 μg m⁻³, 0.51 ± 0.06 mg m⁻³, 73.04 ± 6.36 μg m⁻³, 27.31 ± 3.63 μg m⁻³, and 14.01 ± 2.02 μg m⁻³, respectively. The yearly mean concentrations were trending downward in the past few years and were below the National Ambient Air Quality Standard (NAAQS) Grade II. Summer was the season with the lowest concentrations of all pollutants (3.84 μg m⁻³, 7.34 μg m⁻³, 0.42 mg m⁻³, 52.80 μg m⁻³, 18.67 μg m⁻³ and 8.67 μg m⁻³ for SO₂, NO₂, CO, O₃, PM₁₀ and PM_2.5, respectively), and afternoons were the time with the lowest concentrations of pollutants (except for 78.04 μg m⁻³ for O₃). The influence of meteorological conditions on pollutants was examined: there was a prominent positive correlation between temperature and O₃ in summer, and relative humidity largely influenced the concentrations of PM. The pollution in Hainan was affected more by regional transport; according to the backward trajectory results, Hainan is susceptible to air masses from Guangdong and Fujian to the northeast, the Indochina Peninsula to the southwest, and the South China Sea to the southeast. The results of PSCF and CWT analyses indicated that Guangdong, Jiangxi, Hunan, and Fujian were the primary potential sources of PM_2.5 and O₃.

As global climate change intensifies, arid land ecosystems face increasing challenges. Vegetation, a key indicator of climate variation, is highly responsive to meteorological factors such as temperature (Tem), precipitation (Pre), and soil moisture (SM). Understanding how fractional vegetation cover (FVC) responds to climate change in arid regions is critical for mitigating its impacts. This study utilizes MOD13Q1-NDVI data from 2000 to 2022, alongside corresponding Tem, Pre, and SM data, to explore the dynamics and underlying mechanisms of SM and FVC in the context of climate change. The results reveal that both climate change and human activities exacerbate vegetation degradation, underscoring its vulnerability. A strong correlation between FVC and both Tem and Pre suggests that these factors significantly influence FVC variability. In conclusion, FVC in the lower reaches of the Heihe River is shaped by a complex interplay of Tem, Pre, SM, and human activities. The findings provide a scientific basis and decision-making support for ecological conservation and water resource management in the lower reaches of the Heihe River, aiding in the development of more effective strategies to address future climate challenges.

The intensification of global climate change has made the study of greenhouse gas (GHG) emissions increasingly important. To gain a deeper understanding of the emission characteristics and driving factors of nitrous oxide (N₂O), carbon dioxide (CO₂), and methane (CH₄) from rubber plantation soils, this study conducted a 16-month continuous observation in a rubber plantation in Danzhou, Hainan, employing the static chamber method for the monthly sampling and measurement of GHG emissions while analyzing the soil’s physical and chemical properties. The results indicated that the N₂O flux exhibited no significant diurnal variation between the dry and rainy seasons, with an average emission rate of 0.03 ± 0.002 mg·m⁻²·h⁻¹. A clear seasonal trend was observed, with higher emissions in summer than in winter, resulting in an annual flux of 3 kg·hm⁻²·a⁻¹ (equivalent to 1.9 kg N·hm⁻²·a⁻¹). N₂O emissions were significantly correlated with soil temperature and moisture, explaining 46% and 40% of the variations, respectively, while soil ammonium nitrogen content also significantly influenced N₂O and CO₂ emissions. The rubber plantation soil acted as a source of N₂O and CO₂ emissions and a sink for CH₂, with lower emissions of N₂O and CO₂ during the daytime compared to nighttime, and higher CH₄ uptake during the daytime. In the dry season, there was a significant positive correlation between N₂O and CO₂ emissions (R² = 0.74, p < 0.001). This study reveals the diurnal and seasonal patterns of GHG emissions from rubber plantation soils in Hainan and their interrelationships, providing a scientific basis for the low-carbon management of rubber plantations and GHG mitigation strategies, thereby contributing to attempts to reduce the impact of rubber cultivation on climate change.