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Over the past six decades, carbonyl sulfide (COS) in terrestrial ecosystems has been extensively studied, with research focusing on exploring its ecological and environmental effects, estimating source–sink volume, and identifying influencing factors. The global terrestrial COS sink has been estimated to be about 1.194–1.721 Tg a−1, with the terrestrial sink induced by plants and soils 0.50–1.20 Tg a−1, accounting for 41%–69% of the total. Hence, the role of plants and soils as COS sinks has been extensively explored. Now we know that factors such as the activity of carbonic anhydrase (CA), leaf structural traits, soil microbial activity, and environmental factors play significant roles in the COS budget. Developments in observational techniques have also made important contributions to the COS budget. This paper provides an overview of the research progress made on COS based on a comprehensive review of the literature. Then, it highlights the current research hotspots and issues requiring further exploration. For instance, it has been demonstrated that there are still significant uncertainties in the estimation of COS sources and sinks, emphasizing the need for further exploration of COS measuring techniques. This review aims to provide comprehensive guidance for COS research in terrestrial ecosystems.

Abstract Mitochondria are multifaceted and dynamic organelles regulating various important cellular processes from signal transduction to determining cell fate. As dynamic properties of mitochondria, fusion and fission accompanied with mitophagy, undergo constant changes in number and morphology to sustain mitochondrial homeostasis in response to cell context changes. Thus, the dysregulation of mitochondrial dynamics and mitophagy is unsurprisingly related with various diseases, but the unclear underlying mechanism hinders their clinical application. In this review, we summarize the recent developments in the molecular mechanism of mitochondrial dynamics and mitophagy, particularly the different roles of key components in mitochondrial dynamics in different context. We also summarize the roles of mitochondrial dynamics and target treatment in diseases related to the cardiovascular system, nervous system, respiratory system, and tumor cell metabolism demanding high‐energy. In these diseases, it is common that excessive mitochondrial fission is dominant and accompanied by impaired fusion and mitophagy. But there have been many conflicting findings about them recently, which are specifically highlighted in this view. We look forward that these findings will help broaden our understanding of the roles of the mitochondrial dynamics in diseases and will be beneficial to the discovery of novel selective therapeutic targets.

Rainfall constitutes the primary input in the nutrient flux within forest ecosystems. The forest canopy modulates this flux by partitioning rainfall and selectively absorbing or adding nutrients. In mixed forests, variation in tree species composition regulates rainwater chemical composition, potentially leading to spatial heterogeneity in nutrient distribution and influencing nutrient cycling processes. This study examined the partitioning of rainfall into throughfall and stemflow, as well as their associated nutrient concentrations and fluxes, in a mixed broadleaf and coniferous forest on Changbai Mountain in Northeast China. We observed a rising trend in nutrient contents from rainfall to throughfall and then stemflow. The nutrient contents of stemflow varied largely with tree species due to the differences in canopy structure and bark morphological characteristics. The nutrient input contributed by throughfall and stemflow was 92.30 kg ha−1 during the observation period, and most elements underwent passive leaching through washout except for F− and Na+. We note that the nutrient fluxes in stemflow differed among tree species, with Pinus koraiensis (PK) delivering more acid group anions and Quercus mongolica (QM) providing more cations. Our research provides new insights into nutrient cycling within mixed forest canopies, sparking a transformative advancement in forest management and protection strategies through hydrochemistry-driven solutions.

Urban temperature increase brings a challenge to public health, so urban warming has been widely concerned. Within the central area of Shenyang, a 3 × 3 fishnet with nine grids was built to analyze land surface temperature (LST) and frontal area index (FAI) variations based on the local climate zone (LCZ) classification and to explore relationships among them to generate implications for using wind for urban cooling. The results indicate that LST in the 4# grid (central grid) was the highest (35.11 °C) among the nine grids. In general, a higher LST occurred in the grid with a larger building area and vice versa. LCZ-G underwent the largest temperature reduction among the 17 LCZ types. LCZ-2 had the highest LST, while the LCZ-1 had the lowest LST among the three high and intensive building types, except for the LST in the 2# and 4# grids. The FAI in Shenyang decreased from the center to the surroundings. The FAI value was greatest in the 4# grid and the lowest was in the 2# and 8# grids under the prevailing wind of summer and winter. The FAI variations suggested that prevailing SW, SSW, and S winds in summer were difficult to penetrate the central urban area, and the wind cooling effect could not perform. The prevailing NEN and EEN winds in winter could enter the central urban area, enhancing the wind cooling effect, while it was a disadvantage in winter. Overall, there was a significant positive relationship among LST, FAI, and area of LCZ-building.

The influence of urbanization on the frequent winter aerosol pollution events in Northeast China is not fully understood. The Weather Research and Forecasting Model with Chemistry (WRF–Chem) coupled with urban canopy (UC) models was used to simulate the impact of urbanization on an aerosol pollution process in the Central Liaoning city cluster (CLCC), China. To investigate the main mechanisms of urban expansion and UC on the winter atmospheric environment and the atmospheric diffusion capacity (ADC) in the CLCC, three simulation cases were designed using land-use datasets from different periods and different UC schemes. A comparative analysis of the simulation results showed that the land-use change (LU) and both LU and UC (LUUC) effects lead to higher surface temperature and lower relative humidity and wind speed in the CLCC by decreasing surface albedo, increasing sensible heat flux, and increasing surface roughness, with a spatial distribution similar to the distribution of LU. The thermal effect leads to an increase in atmospheric instability, an increase in boundary layer height and diffusion coefficient, and an increase in the ADC. The LU and LUUC effects lead to a significant decrease in near-surface PM2.5 concentrations in the CLCC due to changes in meteorological conditions and ADC within the boundary layer. The reduction in surface PM2.5 concentrations due to the LU effect is stronger at night than during daytime, while the LUUC effect leads to a greater reduction in surface PM2.5 concentrations during the day, mainly due to stronger diffusion and dilution caused by the effect of urban turbulence within different levels caused by the more complex UC scheme. In this study, the LU and LUUC effects result in greater thermal than dynamic effects, and both have a negative impact on surface PM2.5 concentrations, but redistribute pollutants from the lower urban troposphere to higher altitudes.

Ozone pollution has been growing in the recent decade, becoming a critical urban environmental issue in China. However, Shenyang’s near-surface ozone concentration (ground to 100 m altitude) is of grave concern. To obtain the ozone concentration and the corresponding meteorological conditions from 1 October 2018, to 30 September 2019, we built observatory sites at low (≈15 m) and high (≈90 m) layers in Shenyang, northeast China. Then, we analyzed the temporal variation of ozone concentration and discussed the relationship between ozone concentration and the meteorological factors at low and high layers. Compared with the high layer, the ozone concentration in the low layer is chartered with an earlier peak and higher diurnal range. The ozone concentration in all seasons first peaked at a low-layer height, in early in winter (15:00) and late summer (17:00). Then, the peak at high-layer height lagged for behind 1–2 h, generally occurring between 17:00 and 19:00. The variations in ozone concentration at low and high layers differed in daytime and nighttime. The diurnal ranges of ozone concentrations at the low layer were higher than those at the high layer in the four seasons examined. Overall, ozone concentration correlated significantly with air temperature, having correlation coefficients of 0.814 (p < 0.05) in the low layer and 0.731 (p < 0.05) in the high layer. Inversely, it showed a weak correlation with relative humidity: 0.310 (p < 0.05) and 0.351 (p < 0.05) in the low and high layers, respectively. Also, the correlation coefficients with wind speed were meager at both layers. Generally, ozone pollution is not severe in Shenyang.

Forest canopy closure affects snow processes by changing the redistribution of snowfall, snow interception, accumulation, sublimation, and melt. However, how the forest closure impacts snow processes at different periods has not been well explored. We conducted 3-year measurements of snow density and depth and carried out snow process calculations (i.e., interception, sublimation, and snowmelt) from 2018 to 2021 in four mixed forests with different canopy closures and an open site in the Changbai Mountains, northeast China. We found that the snow density of the five study sites varied greatly (0.14–0.45 g/cm3). The snow depth (SD) at four mixed forests sites was smaller than that of the nearby open site. The SD decreased as the forest canopy closure increased. Additionally, the forest interception effect increased with the canopy closure and decreased as the snowfall intensity increased. The total interception efficiency of the four mixed forests in normal snow years changed from 34% to 73% and increased with forest canopy closure. The averaged sublimation rate (Ss) and snowmelt rate (Sr) of the four mixed forests varied during different periods of snow process. The Ss was 0.1–0.4 mm/day during the accumulation period and 0.2–1.0 mm/day during the ablation period, and the Sr was 1.5–10.5 mm/day during the ablation period. There was a good correlation between Ss, or Sr, and canopy closure, but interannual variation was observed in the correlation. The mean values of the effect of the four mixed forests on understory SWE (snow water equivalent) over the 3 years ranged from −45% to −65%. Moreover, the impact effect was correlated with the forest canopy closure and enhanced with the canopy closure. This study provided more scientific information for studies of snow cover response to forest management.

Accurate modeling of urban climate is essential to predict potential environmental risks in cities. Urban datasets, such as urban land use and urban canopy parameters (UCPs), are key input data for urban climate models and largely affect their performance. However, access to reliable urban datasets is a challenge, especially in fast urbanizing countries. In this study, we developed a high-resolution national urban dataset in China (NUDC) for the WRF/urban modeling system and evaluated its effect on urban climate modeling. Specifically, an optimization method based on building morphology was proposed to classify urban land use types. The key UCPs, including building height and width, street width, surface imperviousness, and anthropogenic heat flux, were calculated for both single-layer Urban Canopy Model (UCM) and multiple-layer Building Energy Parameterization (BEP). The results show that the derived morphological-based urban land use classification could better reflect the urban characteristics, compared to the socioeconomic-function-based classification. The UCPs varied largely in spatial within and across the cities. The integration of the developed urban land use and UCPs datasets significantly improved the representation of urban canopy characteristics, contributing to a more accurate modeling of near-surface air temperature, humidity, and wind in urban areas. The UCM performed better in the modeling of air temperature and humidity, while the BEP performed better in the modeling of wind speed. The newly developed NUDC can advance the study of urban climate and improve the prediction of potential urban environmental risks in China.

The changing climate is worsening the threats to forests, such as insect outbreaks, fires, and drought, especially old-growth forest, which is more susceptible to disturbance. Therefore, it is important to detect the disturbance areas, identify the disturbance agents, and evaluate the disturbance intensity in old-growth forest. We tried to derive the forest disturbance information based on multiple remote sensing datasets (Global Forest Change, MODIS, and ERA5-Land) from 2000 to 2021 in Changbai Mountain, Northeast China, and explored their relationship with climate factors. The results showed that (1) wind damage and insect outbreaks are two main forest disturbance agents, (2) the increasing temperature during overwintering periods and the decreasing precipitation during activity periods increase the risk of insect outbreaks, and (3) disturbances lead to significant changes in forest structure and functional indices, which can be well captured by the remote sensing data. In the study, we creatively combined low-frequency remote sensing images and high-frequency meteorological data to determine the specific time of wind damage. The final results suggested that the vulnerability of old-growth forest to climate change may be mainly reflected through indirect implications, such as the increased risk of strong winds and insect disturbances.

A shelterbelt is an important measure to protect farmland and increase crop yield. However, how a shelterbelt structure affects crop yield is still unclear due to the difficulties accessing sufficient data from traditional field observations. To address this problem, we developed an innovative framework to estimate the shelterbelt structure and crop yield profile at a regional scale based on Google Earth and Sentinel-2 data. Using this method, we quantified the impact of the shelterbelt structure on the corn yield at 302 shelterbelts in the Northeast Plain of China. Generally, the corn yield increased (by 2.41% on average) within a distance of 1.2–15 times the tree height from the shelterbelt. Such an effect was particularly prominent within a distance of two to five times the tree height, where the corn yield was significantly increased by up to 4.63%. The structure of the shelterbelt has a significant effect on the magnitude of increase in yield of the surrounding corn. The increment of corn yields with high-, medium-high-, medium- and low-width-gap grade shelterbelt were 2.01%, 2.21%, 1.99%, and 0.91%, respectively. The medium-high grade shelterbelt achieved the largest yield increase effect. The location of the farmland relative to the shelterbelt also affected the yield, with a yield increase of 2.39% on the leeward side and 1.89% on the windward side, but it did not change the relationship between the yield increase effect and the shelterbelt structure. Our findings highlight the optimal shelterbelt structure for increasing corn yield, providing practical guidance on the design and management of farmland shelterbelts for maximizing yield.

The temperate forests in Northeast China are an important ecological barrier. However, the way in which temperate forests regulate the regional temperature and water cycling remains unclear. In this study, we quantitatively evaluated the role that temperate forests play in the regulation of the regional temperature and precipitation by combining remote sensing observations with a state-of-the-art regional climate model. Our results indicated that the forest ecosystem could slightly warm the annual air temperature by 0.04 ± 0.02 °C and bring more rainfall (17.49 ± 3.88 mm) over Northeast China. The temperature and precipitation modification function of forests varies across the seasons. If the trees were not there, our model suggests that the temperature across Northeast China would become much colder in the winter and spring, and much hotter in the summer than the observed climate. Interestingly, the temperature regulation from the forest ecosystem was detected in both forested regions and the adjacent agricultural areas, suggesting that the temperate forests in Northeast China cushion the air temperature by increasing the temperature in the winter and spring, and decreasing the temperature in the summer over the whole region. Our study also highlights the capacity of temperate forests to regulate regional water cycling in Northeast China. With high evapotranspiration, the forests could transfer sufficient moisture to the atmosphere. Combined with the associated moisture convergence, the temperate forests in Northeast China brought more rainfall in both forest and agricultural ecosystems. The increased rainfall was mainly concentrated in the spring and summer; these seasons accounted for 93.82% of the total increase in rainfall. These results imply that temperate forests make outstanding contributions to the maintainance of the sustainable development of agriculture in Northeast China.

This study investigated monthly variations of surface urban heat island intensity (SUHII) and the applicability of the local climate zones (LCZ) scheme for land surface temperature (LST) differentiation within three spatial contexts, including urban, rural and their combination, in Shenyang, China, a city with a monsoon-influenced humid continental climate. The monthly SUHII and LST of Shenyang were obtained through 12 LST images, with one in each month (within the period between 2018 and 2020), retrieved from the Thermal InfraRed Sensor (TIRS) 10 in Landsat 8 based on a split window algorithm. Non-parametric analysis of Kruskal-Wallis H test and a multiple pairwise comparison were adopted to investigate the monthly LST differentiations with LCZs. Overall, the SUHII and the applicability of the LCZ scheme exhibited spatiotemporal variations. July and August were the two months when Shenyang underwent strong heat island effects. Shenyang underwent a longer period of cool than heat island effects, occurring from November to May. June and October were the transition months of cool–heat and heat–cool island phenomena, respectively. The SUHII analysis was dependent on the definition of urban and rural boundaries, where a smaller rural buffering zone resulted in a weaker SUHI or surface urban cool island (SUCI) phenomenon and a larger urban area corresponded to a weaker SUHI or SUCI phenomenon as well. The LST of LCZs did not follow a fixed order, where in July and August, the LCZ-10 (Heavy industry) had the highest mean LST, followed by LCZ-2 (Compact midrise) and then LCZ-7 (Lightweight low-rise). In comparison, LCZ-7, LCZ-8 (Large low-rise) and LCZ-9 (Sparsely built) had the highest LST from October to May. The LST of LCZs varied with urban and rural contexts, where LCZ-7, LCZ-8 and LCZ -10 were the three built LCZs that had the highest LST within urban context, while LCZ-2, LCZ-3 (Compact low-rise), LCZ-8, LCZ-9 and LCZ-10 were the five built LCZs that had the highest LST within rural context. The suitability of the LCZ scheme for temperature differentiation varied with the month, where from July to October, the LCZ scheme had the strongest capability and in May, it had the weakest capability. Urban context also made a difference to the suitability, where compared with the whole study area (the combination of urban and rural areas), the suitability of built LCZs in either urban or rural contexts weakened. Moreover, the built LCZs had a higher level of suitability in an urban context compared with a rural context, while the land-cover LCZs within rural had a higher level of suitability.

Studies on urban ventilation indicate that urban ventilation performance is highly dependent on urban morphology. Some studies have linked local-scale urban ventilation performance with the local climate zone (LCZ) that is proposed for surface temperature studies. However, there is a lack of evidence-based studies showing LCZ ventilation performance and affirming the reliability of using the LCZ classification scheme to demonstrate local-scale urban ventilation performance. Therefore, this study aims to analyse LCZ ventilation performances in order to understand the suitability of using the LCZ classification scheme to indicate local-scale urban ventilation performance. This study was conducted in Shenyang, China, with wind information at 16 weather stations in 2018. The results indicate that the Shenyang weather station had an annual mean wind speed of 2.07 m/s, while the mean wind speed of the overall 16 stations was much lower, only 1.44 m/s in value. The mean wind speed at Shenyang weather station and the 16 stations varied with seasons, day and night and precipitation conditions. The spring diurnal mean wind was strong with the speeds of 3.56 m/s and 2.21 m/s at Shenyang weather station and the 16 stations, respectively. The wind speed (2.21 m/s at Shenyang weather station) under precipitation conditions was higher than that (1.75 m/s at Shenyang weather station) under no precipitation conditions. Downtown ventilation performance was weaker than the approaching wind background, where the relative mean wind speed in the downtown area was only 0.53, much less than 1.0. The downtown ventilation performance also varied with seasons, day and night and precipitation conditions, where spring diurnal downtown ventilation performance was the weakest and the winter nocturnal downtown ventilation performance was the strongest. Moreover, the annual mean wind speed of the 16 zones decreased from the sparse, open low-rise zones to the compact midrise zones, indicating the suitability of using LCZ classification scheme to indicate local-scale urban ventilation performance. The high spatial correlation coefficients under different seasons, day and night and precipitation conditions, ranging between 0.68 and 0.99, further affirmed that LCZ classification scheme is also suitable to indicate local-scale urban ventilation performance, despite without the consideration of street structure like precinct ventilation zone scheme.

High-density surface networks have become available in recent years in a number of regions throughout the world, but their utility in high-resolution dynamic downscaling has not been examined. As an attempt to fill such a gap, a suite of high-resolution (4 km) dynamical downscaling simulations is developed in this study with the Weather Research and Forecasting (WRF) Model and observation nudging over Liaoning in northeastern China. Three experiments, including no nudging (CTL), analysis nudging (AN), and combined analysis nudging and observation nudging with surface observations (AON), are conducted to downscale the CFSv2 reanalysis with the WRF Model for the year 2015. The three 1-yr regional climate simulations were compared with the independent surface observations. The results show that observational nudging can improve the simulation of surface variables, including temperature, wind speed, humidity, and pressure, more than nudging large-scale driving data with AN alone. The two nudging simulations can improve the cold bias for the temperature of the WRF Model. For precipitation, both the simulations with AN and observation nudging can capture the pattern of precipitation; however, with the introduction of small-scale information at the surface, AON cannot further improve the simulation of precipitation. [ABSTRACT FROM AUTHOR]