Particulate matter is a serious source of air pollution in urban areas, where it exerts adverse effects on human health. This article focuses on the study of subduction of shelterbelts for atmospheric particulates. The results suggest that (1) the PM mass concentration is higher in the morning or both morning and noon inside the shelterbelts and lower mass concentrations at other times; (2) the particle mass concentration inside shelterbelt is higher than outside; (3) the particle interception efficiency of the two forest belts over the three months in descending order was PM10 > PM1 > PM2.5; and (4) the two shelterbelts captured air pollutants at rates of 1496.285 and 909.075 kg/month and the major atmospheric pollutant in Beijing city is PM10. Future research directions are to study PM mass concentration variation of shelterbelt with different tree species and different configuration.

Qinghai Lake is the largest inland saline lake on the Tibetan Plateau. Climate change and catchment modifications induced by human activities are the main drivers playing a significant role in the dramatic variation of water levels in the lake (Δh); hence, it is crucial to provide a better understanding of the impacts caused by these phenomena. However, their respective contribution to and influence on water level variations in Qinghai Lake are still unclear and without characterizing them, targeted measures for a more efficient conservation and management of the lake cannot be implemented. In this paper, data monitored during the period 1960–2016 (e.g., meteorological and land use data) have been analyzed by applying multiple techniques to fill this gap and estimate the contribution of each parameter recorded to water level variations (Δh). Results obtained have demonstrated that the water level of Qinghai Lake declined between 1960 and 2004, and since then has risen continuously and gradually, due to the changes in evaporation rates, precipitation and consequently surface runoff associated with climate change effects and catchment modifications. The authors have also pinpointed that climate change is the main leading cause impacting the water level in Qinghai Lake because results demonstrated that 93.13% of water level variations can be attributable to it, while the catchment modifications are responsible for 6.87%. This is a very important outcome in the view of the fact that global warming clearly had a profound impact in this sensitive and responsive region, affecting hydrological processes in the largest inland lake of the Tibetan Plateau.

An in-depth understanding of the dominant factors controlling soil respiration is important to accurately estimate carbon cycling in forest ecosystems. However, information on variations in soil respiration at different soil depths and the influencing factors in forest is limited. This study examined the variations in soil respiration at two soil depths (0–10 and 10–20 cm) as well as the effects of soil temperature, soil water content, litter removal, and root cutting on soil respiration in three typical forest types (i.e., Pinus tabulaeformis Carrière, Platycladus orientalis (L.) Franco, and Quercus variabilis Bl.) in the mountainous area of north China from March 2013 to October 2014. The obtained results show that soil respiration exhibited strong seasonal variation and decreased with soil depth. Soil respiration was exponentially correlated to soil temperature, and soil respiration increased with soil water content until reaching threshold values (19.97% for P. tabulaeformis, 16.65% for P. orientalis, and 16.90% for Q. variabilis), followed by a decrease. Furthermore, interactions of soil temperature and water content significantly affected soil respiration at different soil depths of forest types, accounting for 68.9% to 82.6% of the seasonal variation in soil respiration. In addition to soil temperature and water content, aboveground litter and plant roots affected soil respiration differently. In the three forest types, soil respiration at two soil depths decreased by 22.97% to 29.76% after litter removal, and by 44.84% to 53.76% after root cutting. The differences in soil respiration reduction between the two soil depths are largely attributed to variations in substrate availability (e.g., soil organic content) and soil carbon input (e.g., litter and fine root biomass). The obtained findings indicate that soil respiration varies at different soil depths, and suggest that in addition to soil temperature and water content, soil carbon input and dissolved organic substances may exert a strong effect on forest soil respiration.

Predicting future land use changes and assessing carbon storage remain challenging. Nowadays, how nature and socioeconomics drive changes in carbon storage is a hot topic in research. In this study, through the projection of land use type and the integration of the PLUS, Integrated Valuation of Ecosystem Services and Trade-offs (InVEST), and Geodetector models, we constructed a framework for assessing carbon storage in different land use scenarios. Utilizing this framework, it is possible to project land use change and estimate carbon storage based on different development scenarios. We applied the framework to the Yili Tianshan region and identified the main driving forces for carbon storage change. Further, we estimated the carbon storage in the Yili Tianshan region in 2035 under four scenarios (RE, NE, EP, and CLP). The results showed the following: 1) Between 1990 and 2020, there was an increase in the forest area and water bodies in the Yili-Tianshan region, mainly from bare land. 2) As shown on the time scale, carbon storage increases in the Yili-Tianshan region with a W-shaped fluctuation by converting grasslands and bare land into forests. On a spatial scale, the carbon storage was lower in the center and higher on both sides in the Yili-Tianshan region. 3) In 2035- RE, 2035-ND, and 2035-EP scenarios, the carbon storage was increased by 4.30 Tg, 6.67 Tg, and 12.08 Tg; in the 2035-CLP scenario, it was decreased by 14.63 Tg. The Yili-Tianshan region experienced a notable rise in carbon storage under the 2035-EP scenario compared to the other three scenarios. 4) Soil type played a significant role in the spatial differentiation of carbon storage in Yili-Tianshan (q value 0.5958), followed by population density (0.5394). The changes in carbon storage in the Yili-Tianshan region are the result of synergistic effects of multiple factors, in which the soil type∩soil erosion intensity are the most important. This research could provide a reference method for improving regional carbon storage.