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Volatile organic compounds (VOCs) are crucial precursors in the formation of ozone (O3). The sources of pollution are complex and significantly impact O3 generation. Long-term exposure to high-concentration O3 environments causes serious damage to organisms. High-altitude areas experience continuous high temperatures and strong solar radiation, which can easily produce O3 through photochemical reactions, making these areas prone to frequent air pollution. This study utilizes the National Positioning Station of the Yinchuan Urban Ecosystem in Ningxia to conduct field synchronous observations, gathering data on VOCs, meteorological variables, and O3. By employing machine learning algorithms, we examined the seasonal distribution characteristics of VOCs, their pollution sources, and their impact on O3. The results show that the seasonal distribution of VOCs areas is low in spring and autumn and high in summer and winter. The components with higher volume fraction contribution are m-tolualdehyde in spring and summer, ethane in autumn, and acetylene in winter. The main emission sources of VOCs pollution are hydrocarbon volatile emission in spring and winter, solvent volatilization emission in summer, and industrial sources in autumn. VOCs have a negative effect on O3, with a greater impact in winter and spring, evidenced by standardized effect values of −0.26 and −0.24. The key components affecting O3 in VOCs vary by season. Aromatic hydrocarbons are the key components in spring and winter, with contribution rates of 22 % and 21.3 %. Alkenes are the key components in summer and autumn (24.5 % and 26.8 %). Among meteorological variables, temperature is the key factor affecting O3, while wind speed is the key factor affecting O3 only in winter. This study aims to clarify the sources of VOCs pollution in different seasons and their impact on O3, providing a theoretical basis and technical support for the prevention and control of VOCs and O3 pollution in high-altitude areas.

Air pollution stands as the single largest environmental risk to human health globally, and negative air ions (NAIs) serve as essential indicators for measuring regional air quality. They play a crucial role in alleviating the pressure and risks posed by air pollution. NAIs are notably abundant in forests, where the photosynthesis of vegetation serves as a significant factor influencing their presence. However, a dearth of quantitative research exists regarding the relationship between vegetation photosynthesis and NAIs. Current literature only offers qualitative insights, suggesting that vegetation photosynthesis may foster NAIs production. The mechanisms through which the photosynthetic process influences NAIs and the potential contribution of forest vegetation to NAIs remain unclear, lacking quantitative investigation. In this study, Quercus variabilis, a typical tree species in the warm temperate zone, was chosen as the research subject. We examined the dynamic changes in NAIs and net ecosystem productivity (NEP) from 2019 to 2021. The results demonstrated a strong correlation between NAIs and NEP at the ecosystem scale during the primary vegetation growing season. NEP effectively tracked daily changes in NAIs and exhibited a good fit. Notably, the scatter plots of NAIs and NEP exhibited clear stratification under varying photosynthetically active radiation (PAR) intensities. The correlation between NAIs and NEP was significantly higher under high PAR conditions compared to low PAR conditions, with R2 values of 0.458 and 0.367, respectively. Consequently, NEP emerges as a superior indicator for tracking NAIs variation characteristics at the ecosystem scale compared to PAR. This finding offers a rapid and accurate evaluation method for discerning the spatial and temporal distribution patterns of NAIs within forest ecosystems. Such insights provide a theoretical foundation for further assessing the potential contribution of forest vegetation to NAIs.

Abstract Background Dissolved organic matter (DOM) is the most active component of soil organic matter (SOM), playing a major role in regulating soil fertility and carbon cycling. However, the effects of different wolfberry (Lycium barbarum L.) planting ages on the chemical diversity of DOM and its interaction with soil physicochemical properties have not been comprehensively studied. In this context, we collected soil samples (0–10 cm) from wolfberry orchards at different planting ages (1, 4, 6, 10, and 13 years) and from a corn field (0 years) in the arid region of Northwest Ningxia in China to assess the changes in soil DOM quantity and quality using ultraviolet–visible absorbance, fluorescence spectroscopy, and parallel factor analysis. Results We found that the ages of the wolfberry plantation changed the contents of soil nutrients and SOM. In addition, significantly higher DOM concentrations were observed at wolfberry planting ages of 10 and 13 years than those in the control group (0 years) by 176.6 and 190.2%, respectively. The specific ultraviolet absorbance at 254 nm (SUVA254) and 254 nm to 365 nm ultraviolet absorbance ratio (E2/E3) values were decreased and increased, respectively, after wolfberry planting, indicating low aromatic and molecular weight compounds of soil DOM. The biogenic index (BIX) and fluorescence index (FI) of soil DOM ranged from 0.6 to 0.7 and 1.42 to 1.93, respectively, suggesting a combination of allochthonous and autochthonous sources. The short- and long-term wolfberry cultivations of 1 and 4 years decreased and increased the humification degrees of soil DOM, respectively. The contribution rate of the protein-like (C1) fluorescence intensity decreased, while that of the fulvic acid-like component (C3) increased with increasing wolfberry planting age, suggesting a change in the structure of soil DOM from protein-like to fulvic acids. In this study, total nitrogen (TN) and exchangeable Ca2+ were the main factors affecting the quantity and quality of soil DOM in the wolfberry orchards with different planting ages. Conclusions This study demonstrated that long-term wolfberry plantation enhances the accumulation of soil DOM and more complex compounds, thereby promoting soil organic carbon sequestration under different planting ages and land-use types in terrestrial ecosystems. Graphical Abstract

The end of growing season (EOS) is an effective indicator of annual vegetation growth. Previous studies have revealed the dynamics of the EOS with climate change, while the influence of vegetation growth in preceding stage and peak of growing season (POS) on the EOS has not been thoroughly documented. In this study, we used four smoothing methods to obtain EOS dates from the Normalized Difference Vegetation Index (NDVI) in northeast Inner Mongolia (NIM) between 2001–2017, assessed the differences in the spatiotemporal variations of the EOS obtained by the four smoothing methods, and then investigated the impacts of climate factors, summer/ autumn vegetation growth and POS on the EOS. The results showed that the EOS dates obtained with different smoothing methods were broadly consistent in terms of their spatial patterns and temporal trends. In terms of climate factors, the EOS was driven mainly by preseason precipitation for the majority of vegetation types and advanced with increasing precipitation. For the steppe, both minimum temperature (Tmin) and relative humidity (RHU) played the most important roles in regulating the variation of EOS which was delayed with an increase in Tmin and reduction in RHU. Furthermore, our study found an earlier POS and vigorous vegetation growth in summer would jointly advance the steppe EOS, but these relationships were the opposite of each other in meadow and forest regions. Interestingly, the EOS of NIM was more related with vegetation growth in the most recent period before the EOS. This study highlights the importance of ecological processes in the preceding growth stage for understanding the dynamics of EOS.

Terrestrial ecosystems play a critical role in the global carbon cycle and the feedbacks of carbon cycle will significantly impact future climate change. It's worth noting that semi-arid biomes in the Southern Hemisphere have driven the global carbon sink anomaly over the past 30 years. However, how does the desert/grassland biome transition zone, a part of arid and semi-arid biomes, respond to climate change and anthropogenic activities in carbon use efficiency (CUE) is still unclear. Therefore, based on the CUE of terrestrial ecosystem estimated by the moderate resolution imaging spectroradiometer (MODIS) data from 2001 to 2017, the spatial and temporal characteristics of CUE in Ningxia province, a typical desert/grassland biome transition zone, were studied. The main driving factors in climate and ecosystem were also investigated by partial correlation analysis. Results showed that the CUE of terrestrial ecosystems in desert/grassland biome transition zone is higher than 0.5, a constant value of CUE defined in many ecological models. However, the CUE varies with the ecosystem types even when they are located in the same climatic zone. There is a decreasing trend of annual CUE in the period of 2001–2017 and most of them will persistently decrease in future at pixels scales, which could be mainly caused by the land use change. Comparing the habitat conditions, we found the lower canopy density and water stress could increase the CUE in the same ecosystem, which indicates the plant could increase their efficiency of transforming carbon from the atmosphere to terrestrial biomass in adverse environment. Finally, the CUE significantly correlated to net primary productivity (NPP) and autotrophic respiration (Ra) in ecosystem processes, meanwhile water stress (lower precipitation) and heat stress (higher temperature) could increase the CUE, but the temperature has variable impacts in different ecosystem.

The Temperature Vegetation Dryness Index (TVDI), a drought monitoring index based on an empirical parameterization of the Land Surface Temperature (LST)–Normalized Difference Vegetation Index (NDVI) space, has been widely implemented in a variety of ecosystems worldwide because it does not depend on ancillary data. However, the simulation of dry/wet edges in the TVDI model can be problematic because remote sensing images do not have sufficient pixels to identify the wetness and dryness extremes of different vegetation coverages. In this study, an improvement in dry/wet edge simulation was proposed, and a comparison of the original TVDI and the modified Temperature Vegetation Dryness Index (TVDIm) was performed for drought monitoring in Ningxia Province, which is a typical semi-arid region in China. First, the difference between the land surface temperatures in day and night (∆LST) was used as an alternative to LST when building the TVDIm model. In addition, the wet edges were improved by removing outliers using a statistical method, and the dry edges were optimized by removing the “tail down” points in the NDVI range of 0.0–0.1. Here, the modeling process of TVDIm in 2005, one of recent extreme drought year is illustrated. The results show that both the TVDI and TVDIm can be used to monitor the temporal and spatial variations of drought, and the onset, duration, extent, and severity of drought can be reflected by TVDI and TVDIm maps. However, the magnitude of TVDI is higher than that of TVDIm, which could cause the TVDI-simulated drought condition to be elevated in normal years and underestimated in dry years. The TVDIm has higher coefficients of correlation with in situ meteorological drought index and agricultural drought statistical data than does the original TVDI, and it exhibits better performance in drought monitoring compared to that of the original TVDI in semi-arid regions of China.

This study constructed a time series of the seasonal Temperature Vegetation Dryness Index (TVDI) based on a remotely sensed dataset from the National Oceanic and Atmospheric Administration/Advanced Very High Resolution Radiometer (NOAA/AVHRR) and Earth Observing System/Moderate Resolution Imaging Spectroradiometer (EOS/MODIS). We examined the spatiotemporal variation in drought in the Huang-Huai-Hai region of China during the period from 1981 to 2011. Combined with the El Niño and southern oscillation (ENSO) indicator (i.e., the Sea Surface Temperature Anomaly, SSTA of the El Niño 3.4 area), the spatial and temporal relationship of agricultural drought in this region and ENSO was analyzed. The results showed that drought demonstrated a significant downward trend (95% confidence level) which covered 38.01 ~ 55.13% of the farmland in this region. In addition, the largest area of drought reducing appeared in winter. The significant decreasing tendency of agricultural drought started from the late 20th and early 21st centuries, whose variation cycles were mainly between 2.5 to 5 a (year). TVDI series were closely correlated to the ENSO index sequences at the 2.5 to 7 a cycle, and there was a delay from 0.16 to 1.40 a between them. However, the correlation between TVDI and ENSO index series was less. These findings show that there is a relationship between the spatiotemporal changes of agricultural drought in the Huang-Huai-Hai region of China and ENSO events over the recent 30 years.

Revegetation is one of the most effective ways to combat desertification and soil erosion in semiarid and arid regions. However, the perturbation of ecohydrological processes revegetation remains to be studied, especially its effect on the complex interaction between the hydrological processes and vegetation growth under water stress. This study evaluated the effects of revegetation on the energy, water and carbon fluxes in a desert steppe in Yanchi County, Ningxia Province, Northwest China, by simulating two vegetated scenarios (shrubs-grassland ecosystem and grassland ecosystem) using STEMMUS-SCOPE model. The model was validated by field observations from May to September of 2016-2019. The simulated energy, water and fluxes in 2016 and 2019 were used to evaluate the difference between two vegetated scenarios. Higher leaf area index and root water uptake of C3 shrubs (Caragana Intermedia) resulted in increased carbon fixation (+ 82 %) and transpiration (+ 99 %) in the shrubs-grassland ecosystem compared to C3 grassland ecosystem. In both scenarios, turbulent energy was dominated by latent heat flux, which was stronger in the shrubs-grassland ecosystem (+ 13 %). With the remarkable increase in transpiration, revegetation induced soil water losses, especially the soil water content within the 0-200 cm soil depth (− 19 %), and exaggerated the excess of water consumption over the received precipitation. These results emphasize the importance of accounting for energy and water budget in water-limited ecosystems during ecological restoration, to prevent soil water depletion. As an example, the consequence of increased transpiration should be further examined. [ABSTRACT FROM AUTHOR]

The macropores and rock fragments are the main factors responsible for the soil hydraulic properties However, the characteristics of the macropores and rock fragments that determine the water flow in forest stone soil remain unclear. Intact soil columns were taken from the forest soil of northern china, and all the intact soil columns were scanned using industrial computed tomography (CT) to quantify the 3-D characteristics of the macropores and rock fragments. The Ksat of three soil layers (0- 10 cm, 10-20 cm, 20-30 cm) were determined in all the samples. The results showed that the soil saturated hydraulic conductivity of mixed forest was higher than that of the pure forest; the saturated hydraulic conductivity was significantly correlated with the surface area density, volume density of the rock fragment and mean tortuosity of the macropores in a negative way, but positively correlated with the number density, surface area density, volume density of the macropores. :Macropores and rock fragments co-determine the saturated hydraulic conductivity of the soil; volume and surface area of the macropores and rock fragments have the greatest influence on the saturated hydraulic conductivity of the soil which determines the soil water infiltration capacity. The effect of soil macropores on the water infiltration is greater than that of the rock fragments. It is thus justified to account for the influence of rock fragments and soil macropores on the hydraulic conductivity in related research. [ABSTRACT FROM AUTHOR]