China's revised ambient air quality standard (GB 3095-2026) tightens limits for major pollutants, increasing attainment pressure in heavily industrialized regions. Using daily observations of fine particulate matter (PM2.5), inhalable particulate matter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3) from 16 cities in Shandong Province during 2015-2025, we developed a relative attainment pressure index (RAPI) combining concentration gaps and additional non-attainment days, and assessed socioeconomic predictors and policy pathways using random forest, Shapley additive explanations (SHAP), and monotonicity-constrained extreme gradient boosting (XGBoost). PM2.5, PM10, SO2, NO2, and CO declined by 41.0-79.6%, whereas O3 remained high at 166-191 μg/m3. Under the transition-stage limits, Heze, Dezhou, and Liaocheng had the highest relative pressure, with RAPI values of 98.7, 91.3, and 89.1, forming a western high-pressure belt. Civilian vehicle ownership and secondary-industry share were the leading model-based predictors of particulate matter and NO2. The selected socioeconomic indicators represented PM2.5 variation better than O3. Scenario analysis indicated that stronger industrial restructuring and energy-efficiency improvement reduced PM2.5, but eight cities remained above the 30 μg/m3 transition-stage limit under the deep-transition pathway in 2030. O3 was less effectively represented by the socioeconomic model; its scenario results are therefore interpreted as screening-level estimates, with eight cities remaining above 160 μg/m3 under the same pathway. The revised standard will sharpen spatial differences in attainment pressure, supporting differentiated structural measures in western industrial cities and source-specific volatile organic compound-nitrogen oxides management.

In order to analyze the effect of environmental factors on the release of negative air ions (NAI) by green tree species, this study conducted an open top chamber (OTC) control test in Beijing. The tree species selected were Acer truncatum, Sophora japonica, Pinus bungeana, and Pinus tabuliformis. The experiment investigated the effects of environmental factors on NAI release under different relative humidity conditions. The results of the study showed that (1) the NAI release contribution (L), NAI release coefficient (n), NAI release rate (s), NAI instantaneous present amount (v), and total NAI release amount (Z) all showed positive responses to humidity. (2) Under constant temperature and light intensity, all five capability indicators increased with the humidity gradient (40-80%) and reached their maximum values at 80% humidity. (3) NAI release was positively correlated with humidity, and the correlation coefficients were: Pinus tabuliformis (R-2 = 0.33) > Sophora japonica (R-2 = 0.17) > Acer truncatum (R-2 = 0.15) = Pinus bungeana (R-2 = 0.15, p < 0.05). (4) Under constant temperature and light intensity, the NAI release contribution (L) and NAI release coefficient (n) responded most strongly to humidity in the 40-60% range, while the total NAI release amount (Z), NAI release rate (s), and NAI instantaneous present amount (v) responded more significantly in the 60-80% range. Acer truncatum showed the strongest response in terms of NAI release contribution (L) and NAI release coefficient (n), while Sophora japonica exhibited the most significant response in terms of NAI release rate (s), NAI instantaneous present amount (v), and total NAI release amount (Z). This study, conducted using an OTC, clarifies the independent role of humidity on NAI released by green tree species, providing a scientific basis for forest recreation and urban green space planning.

Globally, the combined pollution of fine particulate matter (PM2.5) and ground-level ozone (O3) poses severe challenges to public health and sustainable urban development. Recent data indicate that the annual average PM2.5 concentration in the vast majority of cities worldwide fails to meet World Health Organization safety standards, with air pollution causing millions of premature deaths annually. As a nature-based solution, the purification efficacy of vegetation remains poorly quantified due to unclear coupling mechanisms with local meteorological conditions. This study systematically reviewed and synthesized 229 empirical studies published between 2000 and 2025 from Web of Science and China National Knowledge Infrastructure (CNKI), aiming to clarify the quantitative relationships and regulatory mechanisms of plant–meteorological synergistic purification of PM2.5–O3. Following double-blind independent screening (κ = 0.85) and data extraction, a quantitative minimal feasible synthesis approach was adopted due to high data heterogeneity. The results indicated the following. (1) The median canopy purification efficiency of urban vegetation for PM2.5 was 18.2% (IQR: 12.5–30.1%, n = 17), with a median dry deposition velocity (Vd–PM) of 0.05 cm s−1 (0.02–30 cm s−1, n = 15). The median dry deposition velocity (Vd–O3) for O3 was 0.55 cm s−1 (0.12–1.82 cm s−1, n = 8), with non-stomatal deposition contributing approximately 35%. (2) Meteorological factors exhibit nonlinear regulation: relative humidity (RH) > 70% significantly enhances PM2.5 adsorption, wind speeds of 1.5–3.0 m s−1 are optimal for PM2.5 deposition, and temperatures > 30 °C generally inhibit plant uptake of both pollutants (n = 7). (3) Functional traits strongly correlate with purification efficacy: species with high leaf roughness (R2 = 0.8), high stomatal conductance, and low BVOC emissions (e.g., Ginkgo biloba, Platycladus orientalis) exhibit optimal synergistic purification potential. Species with high BVOC emissions (Populus przewalskii, Eucalyptus robusta) can increase daily net O3 pollution equivalents by up to 86 g and must be strictly avoided. Based on quantitative evidence, a green space planning decision matrix indexed by climate zone and pollution type was developed, specifying vegetation configuration patterns, functional group selection, and key design parameters (canopy closure, green belt width, etc.) for different scenarios. This study provides an actionable scientific basis for precision planning and climate-adaptive management of urban green infrastructure.

Following the relaxation of coronavirus disease 2019 restrictions and the subsequent full economic recovery, Shandong Province, China experienced a 4.3% rebound in the air quality index in 2023, with both fine particulate matter (PM2.5) and ozone (O-3) concentrations exhibiting noticeable upward trends. Quantifying the drivers of this rebound is essential for developing targeted air quality management strategies. To this end, the analysis focused on the early spring period (ESP, February to April) and autumn harvest period (AHP, September to October) for PM2.5 pollution and the photochemical season period (PSP, July to October) for O-3 pollution. We developed an interpretable random forest-Shapley additive explanation (RF-SHAP) framework optimized with a tree-structured Parzen estimator (TPE) to assess the impacts of anthropogenic emissions and meteorological factors. The introduction of the TPE optimization technique enhanced RF model performance across these pollution periods. Anthropogenic emissions played the dominant role in PM2.5 pollution rebounds, contributing 14.1% during the ESP and 19.0% during the AHP, for example, industrial recovery (9.2% increase in energy consumption) and agricultural waste burning (70.0% increase in crop residue burning incident). In contrast, O-3 pollution was more strongly influenced by meteorological conditions, which contributed a 5.8% increase during the PSP. Critical meteorological drivers included strengthened atmospheric oxidation capacity, reduced total cloud cover, and changes in boundary layer height, although precursor emissions from the transportation and petrochemical industries remained indispensable for O-3 formation. This study provides an important scientific basis for precise air quality management in Shandong Province in the postpandemic period.

China has implemented a series of national air pollution control policies since 2013, yet the spatiotemporal heterogeneity of pollution dynamics and driving factors across different policy phases remain insufficiently understood. This study developed an integrated framework coupling the Hybrid Single-Particle Lagrangian Integrated Trajectory model, machine learning, and Shapley Additive exPlanation (HYSPLIT-RF-SHAP) to quantify the predictive sensitivity weights of meteorological modulators, local chemical indicators, and regional transport features to fine particulate matter (PM2.5) variations in Shandong Province across three consecutive policy phases (Period I: 2014–2017; Period Ⅱ: 2018–2020; Period Ⅲ: 2021–2024). Province-wide PM2.5 concentrations declined by 43.1% over the study period, with reductions of 26.9% in Period Ⅱ and 22.2% in Period Ⅲ relative to previous phases, yet the spatial pattern of “inland higher than coastal” persisted. The SOR/NOR ratio increased from 0.92 to 1.67, indicating enhanced secondary SO2 transformation under effective NOx controls. Trajectory analysis revealed diversified and stabilized transport pathways across cities. The HYSPLIT-RF-SHAP framework demonstrated a common trend of declining local chemical indicator feature weights (7.1–11.5%) and increasing regional transport feature importance (5.1–8.5%), with relative humidity and temperature as key meteorological drivers. Four representative cities were classified into three typical patterns: Qingdao as a “locally dominated” city, Jinan and Dezhou as “transport-influenced” cities (with Jinan affected by multiple transport directions and Dezhou situated in a major transport passage), and Linyi as a “border-area” city influenced by multiple provinces. This integrated framework provides a scientific basis for formulating differentiated regional air pollution control strategies.

The intensity and frequency of drought are constantly increasing, threatening the ecosystem functions of grasslands. Although drought can generally limit vegetation growth, the effect of drought timings and grassland degradation status remains unclear. We selected three grasslands with different levels of degradation (extremely, moderately and slightly degraded) in northern China and examined the effects of 30-day drought events during different timings (early, middle, and late growing seasons) on soil water content (SWC), vegetation coverages, and aboveground net primary productivity (ANPP). We found that by reducing SWC by approximately 22-75 %, drought events led to significant declines in seasonal vegetation coverage, but weaker effects on ANPP. Among different drought timings, vegetation coverages showed the minimum sensitivity to early-season droughts with positive legacy effects and the maximum sensitivity to mid-season droughts with negative legacy effects. Late season drought can lead to negative legacy effects on next spring, but positive legacy effects on next summer. Vegetation compositions in terms of the proportions of degradation indicator plants play an important role in regulating seasonal drought sensitivities in degraded grasslands. Our findings underscore that, to better understand the performance of grassland ecosystems during drought events, we must consider the impact of drought timing and grassland degradation status.

Fine particulate matter (PM2.5) and ozone (O3) are the primary air pollutants that degrade air quality in China. Reducing precursor emissions reasonably, volatile organic compound (VOC) and nitrogen oxides (NOx), are the keys to achieving effective improvement of air quality. To better tackle this challenge, we revealed the nonlinear response of PM2.5 and O3 concentrations to precursor reduction from various sources in Shandong, China using the Weather Research and Forecasting-Comprehensive Air Quality Model Extensions (WRF-CAMx) models and Empirical Kinetics Modeling Approach (EKMA). VOC reductions from all sources presented a positive effect in reducing PM2.5 and O3 concentrations in four seasons, while both levels showed a trend of first increasing and then decreasing as the proportion of NOx reduction increased, except in summer. Focusing on VOC emissions reduction first is critical for reducing PM2.5 concentrations and the long-term improvement in PM2.5 requires strengthening the deep emission reduction of NOx. The reduction ratios of VOC and NOx emissions from all sources with 3:1 in spring and autumn, and 1:2 in summer were more conducive to reducing O3 concentrations. The reasonable emission reduction ratios of VOCs and NOx from industry, power, transportation, and residential sources were also evaluated. For example, the reduction ratios of VOC and NOx emissions with 2:1 from industry and residential, and 1:2 from power and transportation are beneficial for decreasing PM2.5 concentrations. This study offers valuable insights for formulating rational and effective PM2.5 and O3 control strategies.

Ozone (O3) is the primary air pollutant that degrades air quality in China. However, the combined effects of pollution levels and durations on O3 characteristics, as well as sensitivity variations between months within a season, remain unclear. To address this, we analyzed the spatio-temporal distribution, sensitivity regimes, and sources of O3 pollution in southeastern Shandong Province in 2019-2022. The random forest model indicated that meteorological condition was the dominant factor leading to the variation of O3 concentration decreasing in 2019-2021 but rebounding in 2022. The O3 concentrations increased with the duration of pollution and the concentration of O3 pollution lasting for >= 3 days exhibited a year-on-year increasing trend. The O3 concentrations under the same pollution level have not changed much from 2019 to 2022, while the number of days with mild O3 pollution fluctuated in 2019-2022 influenced by temperature, humidity, and anthropogenic emissions. O3 generation sensitivity exhibits strong monthly variations and spatial distribution, which requires strengthening volatile organic compound emission control during March and April, and NOx emission control in July. The results of O3 sources indicated that trajectories originating from the southeast of Ju County exerted influences on O3 concentration. With the increase in O3 pollution duration, the dominant potential source regions continued to expand. The dominant potential source regions during moderate pollution were larger and more focused than those during mild pollution, mainly in Jiangsu Province. Our findings provide a reference for the precise control of O3 pollution.

Negative air ions (NAIs) have the effect of improving environmental quality and human health. This study for the first time constructed an evaluation system for forest release of NAIs employing five capacity indicators: release contribution rate (L), release coefficient (n), release rate (s), instantaneous standing stock (v), and total release amount (Z). These were applied to evaluate the forest’s ability to release NAIs in the suburban urban green space of Beijing—Xishan National Forest Park. The results showed that: (1) during the growing season of the forest, the value ranges of these indicators were as follows: L: 6.04~9.71%, n: 6.63~11.05%, s: 4.53 × 103~7.49 × 103/cm2/min, v: 4.48 × 104~7.34 × 104/cm2, Z: 2.70 × 105~4.40 × 105/cm2, with the spring and autumn “noon and evening” and summer “morning and evening” forests having the strongest effect and the highest release capacity of NAIs; (2) the daily changes of L, n, s, v, and Z are generally in a “bimodal” pattern, and the overall trend of “rise and fall, rise and fall” among various indicators is consistent, showing a “linkage”; (3) weather characteristics affect release capacity in the order of sunny > rainy > cloudy, with the strongest NAI release ability from forests at 6:00 on cloudy days (0.53%, 1.7%, 877.19/cm2/min, 3.56 × 104/cm2, 9.67 × 104/cm2) and at 18:00 on rainy days (4.58%, 4.83%, 3.16 × 103/cm2/min, 3.16 × 104/cm2, 1.90 × 105/cm2), with poorer NAI release ability in the afternoon on cloudy and rainy days; (4) forests can produce over 100 million levels of NAIs throughout the year, with an average daily production of over one million levels of NAIs. From 2019 to 2021, NAI production showed an increasing trend year by year, and the increase rate increased year by year to 19.6% and 56.5%.; and (5) the five indicators are significantly positively correlated with solar radiation and temperature in the range of 0–200 w/m2 and 5–20 °C, respectively. This study provides a new method to reveal the ability of forests to release NAIs, providing strong evidence for creating a livable ecological environment.

Despite significant progress in air quality improvement, heavy fine particulate matter (PM2.5) pollution events persist in China. The pollution characteristics of PM2.5 vary during different pollution levels, highlighting the necessity for a deeper understanding of its underlying driving factors and regional transport. This study systematically investigated the compositional characteristics, drivers, and regional transport of PM2.5 in Linyi by integrating multi-data fusion analysis, positive matrix factorization-machine learning-shapley additive explanation (PMF-ML-SHAP), and concentration weighted trajectory model. The results revealed that heterogeneous reactions dominated SO42 - formation during polluted periods, while homogeneous reactions drove NO3- formation. In constructing the integrated PMF-ML-SHAP framework, RandomizedSearchCV and KFold techniques significantly enhanced CatBoost model performance. The contribution of local sources increased progressively from 85.6 % to 91.4 % with rising PM2.5 levels, with secondary nitrate formation emerging as the dominant driver of PM2.5 pollution. The influence share of biomass combustion was higher during clean (CP, 20.4 %) and slightly polluted periods (SPP, 17.3 %), while that of firework combustion was higher during heavily polluted periods (HPP, 25.9 %). Among meteorological factors, wind speed and ultraviolet radiation intensity played critical roles in PM2.5 dispersion and secondary aerosol formation. Regional transport analysis indicated that short-range and medium-range transport air masses primarily influenced CP and SPP, whereas local transport air masses dominated during moderately polluted periods (MPP, 54.4 %) and HPP (58.2 %). This study provides new insights into the drivers of PM2.5 pollution during different pollution levels, offering a scientific basis for targeted pollution control strategies in Linyi and similar industrial cities.

To maintain air quality and mitigate pollution during the 24th Olympic Winter Games, strict control measures were implemented in Beijing and surrounding areas, including Linyi. Fine particulate matter (PM2.5) sampling was conducted in the urban area of Linyi between November 10th, 2021, and February 20th, 2022. This sampling period was divided into a no-control period (NCP) and a control period (CP). The PM2.5 concentration decreased by 25.0% during the CP, whereas the atmospheric oxidation increased. This led to the formation of secondary components of PM2.5. Although the conversion rate of the precursors into secondary components was increased during the CP, the nitrate (NO3−) and ammonium (NH4+) concentrations were reduced due to emission reduction. Elemental carbon (EC) and primary organic carbon concentrations were also decreased, whereas the organic carbon (OC)/EC ratio and proportion of secondary organic carbon in PM2.5 increased. Total detected inorganic element concentrations decreased by 23.6% during the CP. The results of source apportionment revealed that secondary sources were the leading PM2.5 contributors during both periods. Vehicle pollution prevention and control should be strengthened as no restrictions on private-car travel during the CP. Controlling combustion and industrial sources had a significant impact on air quality during the CP. Biomass burning and industrial emissions declined from 20.7% to 16.1% (NCP) to 2.0% and 9.1% (CP), respectively. Backward trajectories revealed that air masses largely originated from local regions during both periods, with the highest PM2.5 concentrations found in air masses from the north (NCP) and east (CP) of Linyi. Potential source regions were also identified. The location of these regions showed that local and regional collaborative control of PM2.5 is urgently needed, particularly in northern and southern Linyi (NCP) and eastern Linyi (CP).

Stomatal movement is vital for plants to exchange gases and adaption to terrestrial habitats, which is regulated by environmental and phytohormonal signals. Here, we demonstrate that hydrogen peroxide (H2O2) is required for light-induced stomatal opening. H2O2 accumulates specifically in guard cells even when plants are under unstressed conditions. Reducing H2O2 content through chemical treatments or genetic manipulations results in impaired stomatal opening in response to light. This phenomenon is observed across different plant species, including lycopodium, fern, and monocotyledonous wheat. Additionally, we show that H2O2 induces the nuclear localization of KIN10 protein, the catalytic subunit of plant energy sensor SnRK1. The nuclear-localized KIN10 interacts with and phosphorylates the bZIP transcription factor bZIP30, leading to the formation of a heterodimer between bZIP30 and BRASSINAZOLE-RESISTANT1 (BZR1), the master regulator of brassinosteroid signaling. This heterodimer complex activates the expression of amylase, which enables guard cell starch degradation and promotes stomatal opening. Overall, these findings suggest that H2O2 plays a critical role in light-induced stomatal opening across different plant species. Specific accumulated H2O2 in guard cells under unstressed conditions widely existed among plant species and is required for stomatal opening. H2O2 promotes KIN10, the energy regulator for plant cells, localizing in the nucleus of guard cells to phosphorylate bZIP30 and enhance the heterodimer of bZIP30 and BZR1, thereby facilitating guard cell starch degradation and stomatal opening.

Elucidating the chemical composition, sources, and health risks of fine particulate matter (PM2.5) is crucial for effectively preventing and controlling air pollution. This study collected PM2.5 samples in Linyi from November 10, 2021, to October 15, 2022, spanning the period of the 2022 Winter Olympics and Paralympics. The analysis focused on seasonal variations in the chemical composition of PM2.5, including water-soluble ions, inorganic elements, and carbonaceous aerosols. Results from the random forest model indicated that control measures during the Olympics and Paralympics reduced PM2.5 concentrations by 21.5% in Linyi. Organic matter was the dominant component of PM2.5, followed by NO3- , SO42- , and NH4+. Among secondary inorganic ions, SO4 2exhibited the highest concentration in summer, while NO3- and NH4+ showed the lowest concentrations. The inorganic elements S, K, Fe, and Si had high mean annual concentrations, underscoring the need for targeted control measures for plate production, bulk coal burning, and biomass combustion in Linyi. The organic carbon (OC) to elemental carbon ratio (17.7-20.5) in Linyi was high, highlighting the importance of addressing secondary OC pollution. According to the positive matrix factorization model, coal burning, and the secondary formation processes of sulfate and nitrate were the dominant sources of PM2.5. Backward air mass trajectories revealed substantial contributions from the southeastern, local, and southwestern regions of Linyi. This suggests the need for enhanced regional joint prevention and control efforts between Linyi and neighboring cities, such as Rizhao and Jining in Shandong Province, as well as northern cities in Jiangsu Province. The highest noncarcinogenic and carcinogenic risks (CRs) were associated with As. coal burning posed significant noncarcinogenic risks and a moderate CR, contributing 41.7% and 44.0% of the total health risk, respectively. These findings are crucial for developing effective air pollution prevention and control strategies.

Extreme climate events are hotspots in global change. However, research on the changes in future compound events and population exposure is still limited. Leveraging from the data of the sixth phase of the Coupled Model Intercomparison Project (CMIP6), this paper aims to analyze the temporal and spatial changes of global compound temperature and precipitation extreme events in the future. We also predict the risk of population exposure and quantify the contribution of different factors to exposure. The results show that: (1) In the next 80 years, compound hot-dry event (CHDE) will increase at a rate of 0.02, 0.03, and 0.08 days per decade under the three scenarios of SSP1-2.6, SSP2-4.5 and SSP5-8.5, respectively. By comparison, compound hot-humidity event (CHHE) shows a downward trend under the three scenarios, with a downward rate of 0.01, 0.02, and 0.11 days per decade, respectively. (2) Under the SSP1-2.6 and SSP2-4.5 scenarios, CHDE and CHHE have two or more mutation points. Under the SSP5-8.5 scenario, CHDE shows a significant upward and CHHE shows a significant downward trend in the middle and late 21st century. These two indices exhibit periodic changes in all three scenarios (3) South Asia, West Asia, and Northeast Africa have higher CHDE values, while regions with higher CHHE values are located in North Asia and Greenland. (4) Climate change is a major factor affecting population exposure. For CHDE, climate, population, and their synergistic effects contribute about 75%, 20%, and 5% to the exposure, respectively. For CHHE, the contributions of these three factors are 85%, 10%, and 5% respectively. These findings provide scientific guidance for the rational formulation of population policies, the effective avoidance of climate disaster risks and the protection of human health.

Hairy vetch (Vicia villosa Roth) and smooth vetch (V. villosa Roth var. glabrescens) are important cover crops and legume forage with great economic and ecological values. Due to the large and highly heterozygous genome, full-length transcriptome reconstruction is a cost-effective route to mining their genetic resources. In this study, a hybrid sequencing approach combining SMRT and NGS technologies was applied. The results showed that 28,747 and 40,600 high-quality non-redundant transcripts with an average length of 1808 bp and 1768 bp were generated from hairy vetch and smooth vetch, including 24,864 and 35,035 open reading frames (ORFs), respectively. More than 96% of transcripts were annotated to the public databases, and around 25% of isoforms underwent alternative splicing (AS) events. In addition, 987 and 1587 high-confidence lncRNAs were identified in two vetches. Interestingly, smooth vetch contains more specific transcripts and orthologous clusters than hairy vetch, revealing intraspecific transcript diversity. The phylogeny revealed that they were clustered together and closely related to the genus Pisum. Furthermore, the estimation of Ka/Ks ratios showed that purifying selection was the predominant force. A putative 3-dehydroquinate dehydratase/shikimate dehydrogenase (DHD/SDH) gene underwent strong positive selection and might regulate phenotypic differences between hairy vetch and smooth vetch. Overall, our study provides a vital characterization of two full-length transcriptomes in Vicia villosa, which will be valuable for their molecular research and breeding.

Common vetch (Vicia sativa L.) is an important annual diploid leguminous forage. In the present study, transcriptomic profiling in common vetch in response to salt stress was conducted using a salt-tolerant line (460) and a salt-sensitive line (429). The common responses in common vetch and the specific responses associated with salt tolerance in 460 were analyzed. Several KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways, including plant hormone and MAPK (mitogen-activated protein kinase) signaling, galactose metabolism, and phenylpropanoid phenylpropane biosynthesis, were enriched in both lines, though some differentially expressed genes (DEGs) showed distinct expression patterns. The roots in 460 showed higher levels of lignin than in 429. α-linolenic acid metabolism, carotenoid biosynthesis, the photosynthesis-antenna pathway, and starch and sucrose metabolism pathways were specifically enriched in salt-tolerant line 460, with higher levels of accumulated soluble sugars in the leaves. In addition, higher transcript levels of genes involved in ion homeostasis and reactive oxygen species (ROS) scavenging were observed in 460 than in 429 in response to salt stress. The transcriptomic analysis in common vetch in response to salt stress provides useful clues for further investigations on salt tolerance mechanism in the future.

To explore whether there were differences among the patterns of response of grasslands with different levels of degradation to extreme drought events and nitrogen addition, three grasslands along a degradation gradient (extremely, moderately, and lightly degraded) were selected in the Bashang area of northern China using the human disturbance index (HDI). A field experiment with simulated extreme spring drought, nitrogen addition, and their interaction was conducted during the growing seasons of 2020 and 2021. The soil moisture, aboveground biomass, and composition of the plant community were measured. The primary results were as follows. (1) Drought treatment caused soil drought stress, with moderately degraded grassland being the most affected, which resulted in an 80% decrease in soil moisture and a 78% decrease in aboveground biomass. The addition of nitrogen did not mitigate the impact of drought. Moreover, the aboveground net primary production (ANPP) in 2021 was less sensitive to spring drought than in 2020. (2) The community composition changed after 2 years of drought treatment, particularly for the moderately degraded grasslands with annual forbs, such as Salsola collina, increasing significantly in biomass proportion, which led to a trend of exacerbated degradation (higher HDI). This degradation trend decreased under the addition of nitrogen. (3) The variation in drought sensitivities of the ANPP was primarily determined by the proportion of plants based on the classification of degradation indicators in the community, with higher proportions of intermediate degradation indicator species exhibiting more sensitivity to spring drought. These findings can help to provide scientific evidence for the governance and restoration of regional degraded grassland under frequent extreme weather conditions.

Plants can effectively purify PM2.5 in the air, thereby improving air quality. Understanding the mechanisms of the absorption and distribution of PM2.5 in plants is crucial for enhancing their ecological benefits. In this study, the regularity of uptake and distribution of the water-soluble inorganic compounds ammonium (NH4+) and nitrate (NO3-) ions in PM2.5 by the two native Chinese conifers Manchurian red pine (Pinus tabuliformis) and Bunge’s pine (P. bungeana) were investigated using a one-time aerosol treatment method combined with 15N tracing. The results showed the following: (1) Plants can efficiently absorb NH4+ (0.08~0.21 μg/g) and NO3- (0.03~0.68 μg/g) from PM2.5. Manchurian red pine absorbs these compounds more effectively with increases of 2.01-fold for NH4+ and 1.02-fold for NO3- compared with Bunge’s pine. (2) The aboveground organs of the plants absorb and distribute more 15N than the belowground organs. The branches had the highest unit mass absorption (0.08~1.60 μg/g) and rate of distribution (16.91~53.60%) for NH4+, while the leaves had the highest unit mass absorption (0.15~1.18 μg/g) and rate of distribution (50.78~84.88%) for NO3-. (3) The ability of the aboveground organs to absorb 15N is influenced by the concentration of PM2.5, which showed an overall increase with increasing concentrations with some fluctuations in specific organs. However, the belowground organs were not affected by the concentration of PM2.5. (4) A larger specific leaf area, root-to-shoot ratio, branch biomass ratio, coarse root biomass ratio, and lower trunk biomass ratio favors the absorption of NH4+ from PM2.5, whereas these traits had a minimal influence on the absorption of NO3-. Manchurian red pine absorbed significantly more NH4+ compared with Bunge’s pine, which benefited from the traits described above. These findings provide scientific insights to understand the mechanisms of absorption of PM2.5 by plants and effectively utilize plants to reduce PM2.5 pollution and purify the environment.

Common vetch (Vicia sativa L.) is a leguminous crop used to feed livestock with vegetative organs or fertilize soils by returning to the field. Survival of fall-seeded plants is often affected by freezing damage during overwintering. This study aims to investigate the transcriptomic profiling in response to cold in a mutant with reduced accumulation of anthocyanins under normal growth and low-temperature conditions for understanding the underlying mechanisms. The mutant had increased cold a tolerance with higher survival rate and biomass during overwintering compared to the wild type, which led to increased forage production. Transcriptomic analysis in combination with qRT-PCR and physiological measurements revealed that reduced anthocyanins accumulation in the mutant resulted from reduced expression of serial genes involving in anthocyanin biosynthesis, which led to the altered metabolism, with an increased accumulation of free amino acids and polyamines. The higher levels of free amino acids and proline in the mutant under low temperature were associated with improved cold tolerance. The altered expression of some genes involved in ABA and GA signaling was also associated with increased cold tolerance in the mutant.

Extreme drought events during spring have been predicted to increase and can profoundly threaten the grassland ecosystem through influencing the early growing season stages. However, whether these impacts are recoverable still remain controversial, and the role of grassland degradation status is also unclear. By selecting three grassland fields with different degradation levels (extreme, moderate, and light degradation) on a Leymus chinensis steppe in Northern China, we conducted a simulated extreme drought experiment during the late spring (mid-May to mid-June) using the rainfall shelters, to determine the influences on the vegetation growth. Soil moisture, leaf water potential (LWP), and vegetation cover were measured during the growing season, and aboveground biomass was harvested in autumn. The results showed that although spring drought could significantly reduce soil moisture up to 50 %, the drought effects did not cause a significant decrease in the LWP of L. chinensis. The water stress induced by spring drought had transferred to significant declines in vegetation coverage by approximately 45 % in the end of the simulated drought. However, the vegetation coverage fully recovered at the end of the growing season, with no drought effect on the aboveground biomass for the community as well as L. chinensis. The vegetation growth of degraded grasslands showed a certain degree of resistance to spring drought through compensatory growth. Altogether, the result of this study can be used as a reference for grassland degradation management, especially under extreme climate conditions.