The concentration of negative air ions (NAIs) is an important indicator of air quality. Here, we analyzed the distribution patterns of negative air ion (NAI) concentrations at different time scales using statistical methods; then described the contribution of meteorological factors of the different season to the concentration of NAIs using correlation analysis and regression analysis; and finally made the outlook for the trends of NAI concentrations in the prospective using the auto regressive integrated moving average (ARIMA) models. The dataset of NAI concentrations and meteorological factors measured at the fixed stations in the Mountain Wuyi National Park were obtained from the Fujian Provincial Meteorological Bureau. The study showed that NAI concentrations were correlated with relative humidity spanning all seasons. Water was an important factor affecting the distribution of NAI concentrations in different time series. Compared with other ARIMA models, the outlook value of the ARIMA (0,1, 1) model was closer to the original data and the errors were smaller. This article provided a unique perspective on the study of the distribution of negative air oxygen ions over time series.

Dust particles in the atmosphere play an important role in air pollution, climate change, and biogeochemical cycles. Some of the dominant sources of dust in mid-latitude regions are in Asia. An intense dust storm engulfed Northern China at the beginning of May 2017, and PM₁₀ mass concentrations of 1500–2000 μg m⁻³ were measured near the dust source region. We combined numerical simulations, air quality monitoring data, and satellite retrievals to investigate dust emission and transport during this event. We found that the event was closely related to cold front activity, characterized by increased wind speed, which increased dust emission. We improved the dust scheme using a local dust size distribution to better simulate the dust emission flux. We found that accurate parametrization of the dust size distribution was important to effectively simulate both dust emission and ambient particle concentration. We showed that using a local dust size distribution substantially improved the accuracy of the simulation, allowing both the spatial distribution of pollution caused by the dust storm and temporal variability in the pollution to be captured.

Introduction: Arid and semi-arid regions are climate-sensitive areas, which account for about 40% of the world’s land surface area. Future environment change will impact the environment of these area, resulting in a sharp expansion of arid and semi-arid regions. Cotoneaster multiflorus is a multi-functional tree species with extreme cold, drought and barren resistance, as well as ornamental and medicinal functions. It was found to be one of the most important tree species for ecological restoration in arid and semi-arid areas. However, bioclimatic factors play an important role in the growth, development and distribution of plants. Therefore, exploring the response pattern and ecological adaptability of C. multiflorus to future climate change is important for the long-term ecological restoration of C. multiflorus in arid and semi-arid areas.Methods: In this study, we predicted the potential distribution of C. multiflorus in China under different climate scenarios based on the MaxEnt 2.0 model, and discussed its adaptability and the major factors affecting its geographical distribution.Results: The major factors that explained the geographical distribution of C. multiflorus were Annual precipitation (Bio12), Min air temperature of the coldest month (Bio6), and Mean air temperature of the coldest quarter (Bio11). However, C. multiflorus could thrive in environments where Annual precipitation (Bio12) >150 mm, Min air temperature of the coldest month (Bio6) > -42.5°C, and Mean air temperature of the coldest quarter (Bio11) > -20°C, showcasing its characteristics of cold and drought tolerance. Under different future climate scenarios, the total suitable area for C. multiflorus ranged from 411.199×10⁴ km² to 470.191×10⁴ km², which was 0.8~6.14 percentage points higher than the current total suitable area. Additionally, it would further shift towards higher latitude.Discussion: The MaxEnt 2.0 model predicted the potential distribution pattern of C. multiflorus in the context of future climate change, and identified its ecological adaptability and the main climatic factors affecting its distribution. This study provides an important theoretical basis for natural vegetation restoration in arid and semi-arid areas.

Introduction: Plant physiology response and adaptation to drought stress has become a hotspot in plant ecology and evolution. Cotoneaster multiflorus possesses high ecological, ornamental and economic benefits. It has large root system and tolerance to cold, drought and poor soil. Therefore, C. multiflorus is considered as one of the most important tree species for ecological restoration in arid and semi-arid areas. However, little is known about the physiological mechanisms, molecular mechanisms and drought strategies of how C. multiflorus responds to drought stress. Therefore, exploring the physiological response mechanisms, molecular mechanisms and adaptive strategies of C. multiflorus in response to drought is important for its growth in arid and semi-arid regions.Methods: We investigated the response and coupling mechanisms of water status, photosynthetic properties and chloroplast fluorescence parameters in C. multiflorus in response to drought and rehydrated after drought, especially the importance of nocturnal sap flow and nocturnal water refilling to maintain its own water balance in response to drought stress. In addition, we studied the stress response of C. multiflorus transcriptome factors, and we also discussed drought adaptation strategies of C. multiflorus.Results: C. multiflorus adapted to drought stress by a series of structural and physiological mechanisms, such as promoting closing stomata, increasing nocturnal sap flow. When rehydrated after undergoing severe drought stress, its physiological activities such as photosynthesis, water status, chlorophyll fluorescence parameters and other physiological activities have rapidly resumed. This showed C. multiflorus had strong tolerance to drought. In addition, water status, photosynthetic characteristics, and chloroplast fluorescence parameters of C. multiflorus were highly coupled. Nocturnal sap flow and nocturnal water refilling were very important for C. multiflorus to maintain its own water balance in response to drought stress. Finally, C. multiflorus will strengthen the drought defense mechanism by gene regulation of various metabolisms, such as promoting stomatal closure, reducing transpiration water loss, and vigorously regulating water balance. C. multiflorus responded to drought stress by avoiding or reducing water deficit in plant organs and tissues. Therefore, the shrub C. multiflorus is a drought-tolerant plant.Discussion: We explored the response mechanisms of water status, photosynthetic characteristics, and chloroplast fluorescence parameters of C. multiflorus in drought and rehydrated after drought stress, especially the response mechanisms of nocturnal sap flow and nocturnal water refilling in response to drought stress, and identified the physiological coupling mechanisms, molecular mechanisms and drought types of C. multiflorus in response to drought.

Precipitation (PRE) is an essential factor that affects the negative air ions (NAIs) concentrations. However, the mechanism of NAIs concentrations and their influencing factors on rainy and non-rainy days remains unclear. Here, we used hourly data of NAIs concentrations and meteorological data in 2019 to analyze the distribution of NAIs concentrations and its influencing factors on rainy and non-rainy days in the Wuyi Mountain National Park (WMNP) of China, which was listed as a World Cultural and Natural Heritage Site in 1999. The results indicated that the NAIs concentrations on rainy days were significantly higher than on non-rainy days. However, the NAIs concentrations on rainy days were slightly higher than on the first and second days after rainy days. Then, the NAIs concentrations were significantly reduced on the third day and after that. Thus, rainy days lead to a 2-day lag in the smooth reduction of NAIs on non-rainy days after rainy days. NAIs concentrations were significantly correlated with the relative humidity (RHU) on both rainy and non-rainy days. By analyzing the meteorological factors on NAIs for ranking the feature importance scores on rainy and non-rainy days, PRE was ranked first on rainy days, and sea level pressure (PRS_Sea) and temperature (TEM) were ranked first and second on non-rainy days, respectively. Based on the univariate linear regression model (ULRM), NAIs concentrations responded strongly (higher absolute slope values) to RHU on rainy days and to pressure (PRS), visibility (VIS), water vapor pressure (VAP), TEM, and ground surface temperature (GST) on non-rainy days. The results highlight the importance of PRE in the lag time of NAIs concentrations on rainy and non-rainy days.

Severe air pollution in China has caused significant tourism transformation for pursuing fresh air in microclimate tourism markets. Contemporary practices simply measure the air freshness of destinations and scenic spots using a single index, i.e., primarily negative oxygen ions (O₂⁻). This index cannot comprehensively reveal scenic spots’ air freshness degree and determine the dynamic interactions between air freshness and scenic spots’ tourism development, thus inducing an illusion of air freshness for the target scenic spots. Meanwhile, the current fresh air index primarily ignores connections with the microclimate index of scenic spots and cannot provide a multidimensional index for scenic spots to take advantage of both air and microclimate resources for diverse tourism products and service production. Therefore, this study proposes a multidimensional index, the fresh air–natural microclimate comfort index (FAI-NMCI), connecting the fresh air index with the natural microclimate comfort index of scenic spots together from transdisciplinary and multidisciplinary perspectives. This study utilizes FAI-NMCI to measure four scenic spots of Fujian Province, and reveals in-depth results of scenic spots’ air freshness and natural microclimate comfort degree together. The results demonstrate that the four scenic spots in Fujian province of China had different levels of air freshness degree and natural microclimate comfort degree in 2018. The natural scenic spots were mostly distributed in Healing Fresh, Very Fresh, and Super Fresh levels of FAI with the most comfortable and comfortable levels of NMCI. The cultural scenic spots were mostly distributed in Relatively Fresh and Healing Fresh levels of FAI with the most comfortable and comfortable levels of NMCI. Meanwhile, the FAI-NMCI of natural and cultural scenic spots also had significant differences within 24 Jieqi, which will promote dynamic and creative utilization of those resources in microclimate tourism development.