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Due to budget and sensor technology constraints, a single sensor cannot simultaneously provide observational images with both a high spatial and temporal resolution. To solve the above problem, the spatiotemporal fusion (STF) method was proposed and proved to be an indispensable tool for monitoring land surface dynamics. There are relatively few systematic reviews of the STF method. Bibliometrics is a valuable method for analyzing the scientific literature, but it has not yet been applied to the comprehensive analysis of the STF method. Therefore, in this paper, we use bibliometrics and scientific mapping to analyze the 2967 citation data from the Web of Science from 1991 to 2023 in a metrological manner, covering the themes of STF, data fusion, multi-temporal analysis, and spatial analysis. The results of the literature analysis reveal that the number of articles displays a slow to rapid increase during the study period, but decreases significantly in 2023. Research institutions in China (1059 papers) and the United States (432 papers) are the top two contributors in the field. The keywords "Sentinel", "deep learning" (DL), and "LSTM" (Long Short-Term Memory) appeared most frequently in the past three years. In the future, remote sensing spatiotemporal fusion research can address more of the limitations of heterogeneous landscapes and climatic conditions to improve fused images' accuracy. [ABSTRACT FROM AUTHOR]

With China's rapid industrialization and urbanization in the process of socio-economic development, the extensive use of energy has resulted in a large amount of CO2 emissions, which puts great pressure on China's carbon emission reduction task. Through multivariate socio-economic data, this paper proposes an extraction and screening method of multivariate variables based on land-use types, and the downscaled spatial decomposition of carbon emissions at different scales was carried out by using the spatial lag model (SLM). This paper makes up for the shortcomings of previous studies, such as an insufficient modeling scale, simple modeling variables, limited spatio-temporal span of spatial decomposition, and no consideration of geographical correlation. Based on the results of the spatial decomposition of carbon emissions, this paper explores the spatial and temporal dynamics of carbon emissions at different scales. The results showed that SLM is capable of downscaling the spatialization of carbon emissions with high precision, and the continuity of the decomposition results at the provincial scale is stronger, while the differences of the decomposition results at the municipal scale are more obvious within the municipal units. In terms of the spatial and temporal dynamics of CO2 emissions, carbon emissions at both scales showed a significant positive correlation. The dominant spatial correlation types are "Low–Low" at the provincial level, and "Low–Low" and "High–High" at the municipal level. The smaller spatial scope is more helpful to show the geographic dependence and geographic differences of China's carbon emissions. The findings of this paper will help deepen the understanding of the spatial and temporal changes of carbon emissions in China. They will provide a scientific basis for the formulation of feasible carbon emission reduction policies. [ABSTRACT FROM AUTHOR]

Most Penman-Monteith-Leuning (PML) evapotranspiration (ET) modeling studies are dominated by consideration of meteorological, energy, and land use information, etc., but the dynamic coupling of soil moisture content (SM), especially in terms of improving accuracy through assimilation, lacks sufficient attention. This paper proposes a research framework for the dynamic coupling simulation of PML model and SM based on data assimilation, i.e., the remote sensing monitored SM is combined with soil evaporation of PML to obtain high-precision time-continuous SM data through data assimilation; simultaneously, dynamical soil evaporation coefficients are generated based on the assimilated SM to improve the simulation accuracy of the PML model. The new scheme was validated at a typical irrigation zone in north China and showed obvious improvements in both SM and ET simulations. Moreover, the effect of the assimilation of SM on the simulation accuracy of ET for different crop growth periods is further analyzed. This research provides a new idea for the coupling simulation of the SM and PML models. [ABSTRACT FROM AUTHOR]

The PIESAT-01 constellation is the world's first multi-baseline distributed synthetic aperture radar (SAR) constellation with a "Cartwheel" formation. The "Cartwheel" formation is a unique formation in which four satellites fly in companion orbits, ensuring that at any given moment, the main satellite remains at the center, with three auxiliary satellites orbiting around it. Due to this unique configuration of the PIESAT-01 constellation, four images of the same region and six pairs of baselines can be obtained with each shot. So far, there has been no imaging and interference research based on four-satellite constellation measured data, and there is an urgent need to explore algorithms for the "Cartwheel" configuration imaging and digital surface model (DSM) production. This paper introduces an improved bistatic SAR imaging algorithm under the four-satellites interferometric mode, which solves the problem of multi-orbit nonparallelism in imaging while ensuring imaging coherence and focusing ability. Subsequently, it presents an interferometric processing method for the six pairs of baselines, weighted fusion based on elevation ambiguity from different baselines, to obtain a high-precision DSM. Finally, this paper selects the Dingxi region of China and other regions with diverse terrains for imaging and DSM production and compares the DSM results with ICESat-2 global geolocated photon data and TanDEM DSM data. The results indicate that the accuracy of PIESAT-01 DSM meets the standards of China's 1:50,000 scale and HRTI-3, demonstrating a high level of precision. Moreover, PIESAT-01 data alleviate the reliance on simulated data for research on multi-baseline imaging and multi-baseline phase unwrapping algorithms and can provide more effective and realistic measured data. [ABSTRACT FROM AUTHOR]

As global warming intensifies, reducing carbon emissions has become a global common mission. Tourism transportation is one of the important sources of carbon emissions, and reducing its carbon emissions is a key part of achieving China's carbon reduction goals. Based on the panel data of various provinces and cities in North China from 2000 to 2022, this paper calculates the carbon emissions of tourism transportation by using the carbon emission coefficients of different transportation modes in different segments. Moreover, the temporal and spatial evolution of the tourism economy is systematically analyzed. The Tapio decoupling model and LMDI addition decomposition model are used to analyze the relationship between carbon emissions and tourism economic growth and the effects of 11 influencing factors on carbon emissions. The results show that: (1) The carbon emission of tourism transportation in North China has experienced four stages: a steady growth period, a transitional adaptation period, a stable equilibrium period, and a drastic decline period. The overall carbon emission level of tourism transportation is as follows: Hebei Province > Shanxi Province > Inner Mongolia Autonomous Region > Beijing City > Tianjin City. (2) The decoupling coefficient between tourism traffic carbon emissions and economic development fluctuates but mainly shows a weak decoupling state. (3) In terms of influencing factors, passenger size and passenger density have the greatest impact on the carbon emissions of tourism transportation. [ABSTRACT FROM AUTHOR]

Airborne wind measurement is of great significance for understanding atmospheric motion and meteorological monitoring. In this paper, we present the development and verification of an airborne Doppler wind lidar (ADWL), featuring an approach proposed to integrate a real-time wind retrieval method with an intelligent processing method for automatic adaptive wind detection. Several verification experiments were conducted to evaluate the measurement effectiveness, including comparisons with a calibrated ground-based Doppler wind lidar (GDWL) and a sounding balloon. Compared with the sounding balloon, the ADWL demonstrated mean errors of 0.53 m/s for horizontal wind velocity and 4.60° for wind direction. The correlation coefficients consistently exceeded 0.98 in all linear analyses. Employed in multiple airborne wind detection events in North China at altitudes up to 6600 m, the ADWL provided effective wind field results with a vertical resolution of 50 m and a data rate of 2 Hz. The wind field results obtained during the detection events validate the ADWL's capabilities in diverse environments and underscore its potential for the comprehensive detection of meteorological information. [ABSTRACT FROM AUTHOR]

The physical parameterizations have important influence on model performance in precipitation simulation and prediction; however, previous investigations are seldom conducted at very high resolution over Hebei Province, which is often influenced by extreme events such as droughts and floods. In this paper, the influence of parameterization schemes and analysis nudging on precipitation simulation is investigated using the WRF (weather research and forecasting) model with many sensitivity experiments at the cumulus "gray-zone" resolution (5 km). The model performance of different sensitivity simulations is determined by a comparison with the local high-quality observational data. The results indicate that the WRF model generally reproduces the distribution of precipitation well, and the model tends to underestimate precipitation compared with the station observations. The sensitivity simulation with the Tiedtke cumulus parameterization scheme combined with the Thompson microphysics scheme shows the best model performance, with the highest temporal correlation coefficient (0.45) and lowest root mean square error (0.34 mm/day). At the same time, analysis nudging, which incorporates observational information into simulation, can improve the model performance in precipitation simulation. Further analysis indicates that the negative bias in precipitation may be associated with the negative bias in relative humidity, which in turn is associated with the positive bias in temperature and wind speed. This study highlights the role of parameterization schemes and analysis nudging in precipitation simulation and provides a valuable reference for further investigations on precipitation forecasting applications. [ABSTRACT FROM AUTHOR]

Using multiple observational and reanalysis data, this paper investigates the impact of the interdecadal shift in summer Arctic Oscillation (AO) on precipitation in East Asia, by removing ENSO influences. The results indicate that the lower-layer activity center of summer AO in Atlantic shifted eastward after the mid-1980s. This regime shift of summer AO has a significant impact on precipitation in East Asia. Before the mid-1980s, the key regions in which precipitation was affected by AO in East Asia were northern East Asia and Northeastern China and adjacent regions. After the mid-1980s, the key regions in which precipitation was affected by AO in East Asia were central Inner Mongolia and Southern China. The mechanism of precipitation changes can be attributed to changes in atmospheric circulation and water vapor transport related to AO changes. After the mid-1980s, the influence of AO on geopotential height over northern East Asia weakened; meanwhile, the impact of AO on geopotential height over China increased. Consistent with the changes in atmospheric circulation, water vapor transport in East Asia also underwent interdecadal changes before and after the mid-1980s. The differences in atmospheric circulation and water vapor transport in East Asia can be traced back to the North Atlantic. Before the mid-1980s, wave activity flux related to summer AO tended to propagate in high latitudes and subtropics; after the mid-1980s, the wave activity flux changed in its subtropical path and propagated eastward from the North Atlantic through the Middle East to China, significantly affecting the summer precipitation in China. [ABSTRACT FROM AUTHOR]

Severe convection is a disastrous mesoscale weather system. The early detection of such systems is very important for saving peoples' lives and properties. Previous studies address the issue mainly based on thresholding methods, which are not robust and accurate enough. In this paper, we propose a novel semantic segmentation method (Dugs-UNet) to solve the problem. Our method is based on the well-known U-Net framework. As convective clouds mimic fluids, its detection faces two important challenges. First, the shape and boundary features of clouds need to be carefully exploited. Second, the positive and negative samples for convection detection are very imbalanced. To address the two challenges, our method was carefully developed. Regarding the importance of the shape and boundary features for convective target detection, we introduce a shape stream module to extract these features. Also, a data-dependent upsample operation is adopted in the decoder of U-Net to effectively utilize the features. This is one of our contributions. To address the imbalance issue for convective target detection, the a focal loss function is employed to train our method, which is another contribution. Experimental results of 2018 Fengyun-4A satellite observations in China demonstrate the effectiveness of the proposed method. Compared to conventional thresholding-based methods and deep semantic segmentation algorithms such as SegNet, PSPNet, DeepLav-v3+ and U-Net, the proposed approach performs the best. [ABSTRACT FROM AUTHOR]

China has experienced significant urbanization during the past 40 years, which exerts impacts on regional climates through changing land surface properties. Previous studies mainly focused on the Pearl River Delta, the Yangtze River Delta, and the Beijing-Tianjin-Hebei areas, while less attention has been paid to central China. In this paper, the regional climate effects of urbanization around the greater Wuhan area were investigated using the WRF model. High resolution, satellite-derived, impervious datasets were used to generate two realistic scenarios representing urban surface states of the years 1986 and 2018. By comparing the simulation results of two sensitivity experiments from 1 July 2015 to 12 July 2015, the spatial and diurnal changes in surface air temperature, surface skin temperature, and surface energy budget were analyzed. Our results reveal that urban expansion leads to 2 m air temperature and surface skin temperature increases by approximate 0.63 °C and 0.83 °C, respectively. Surface sensible heat flux increases, while latent heat flux decreases, with much greater effects in daytime than nighttime. The planetary boundary layer height (PBLH) increases with its maximum value over 100 m, and a 2 m water vapor mixing ratio decreases with a peak value around −2 g/kg. These findings provide knowledge to improve the understanding of land–atmospheric interactions and pave the way to studying urban expansion effects under future climate change scenarios. [ABSTRACT FROM AUTHOR]

The FY-3E satellite plasma analyzer marks China's first detection of the characteristics, occurrence, and development of the typical plasma environment in the dawn–dusk orbit space. It provides data source support for operational space weather alerts and forecasts, helps ensure the in-orbit safety of the satellite, and accumulates space environment detection data for space environment modeling and space physics research. This paper gives a detailed introduction to the detection technology adopted by the FY-3E satellite plasma analyzer. We calibrated its performance through a calibration experiment and then analyzed and compared it with similar instruments in China. It is indicated that the instrument is capable of measuring an ion energy spectrum of 24 eV~32 keV and an electron energy spectrum of 23.7 eV~31.6 keV, its field of view reaches 180° × 90°, and the inversed measurement range of spacecraft absolute potential is better than −30 kV~+30 kV. All these contribute to a notably improved technology for plasma and satellite potential detection of China's LEO satellites. [ABSTRACT FROM AUTHOR]

Growing global concern over greenhouse gas emissions has led to a demand for understanding and addressing carbon emissions, with China being one of the main contributors to global carbon emissions, committed to reach the carbon peak by 2030. As a result, much previous research has delved into the drivers of carbon emissions in China; however, few studies have included new energy factors in the extended STIRPAT model when analysing the data, employed more advanced visualisation techniques such as force-directed diagrams, and explored factors outside of the industrial and energy sectors in determining China's ability to reach their environmental goals. In this study, we use the extended STIRPAT model to analyse a more diverse range of drivers for carbon emissions in China and discuss methods to reach peak carbon emissions through the implementation of environmental policies. Using data from China's 14th Five-Year Plan and Vision 2035 to set up two simulation scenarios, we predict China's carbon emissions, introducing ridge regression to ensure validity, and employing big data and visualisation techniques to aid in interpreting results. Our findings suggest that China needs to implement more stringent environmental policies to meet its commitment to reach peak carbon emissions by 2030, revealing that factors such as per capita arable land area, per capita GDP, the proportion of people living in extreme poverty, the level of tourism development, the use of fossil fuels, and new energy technologies have a significant impact on China's carbon emissions. As such, we can recommend more stringent policies relating to the agricultural, energy, and tourism sectors to help China achieve their goal of carbon peak by 2030. [ABSTRACT FROM AUTHOR]

To evaluate the detection performance of ozone lidars, the first comprehensive vertical ozone observation experiment in China was conducted at the Xilinhot National Climate Observatory in Inner Mongolia from August to December 2023. The ozone profiles and concentrations of four ozone lidars were systematically compared and assessed with ozone radiosonde measurements and ozone analyzer observations both at ground-based stations and on an Unmanned Aerial Vehicle. The results show that the relative deviations of four ozone lidars are less than 20% compared with ozone radiosonde measurements at a height between 150 and 400 m. Ozone lidars have better behavior between 400 m and 2000 m than the lower altitude, with the deviation within 10% and the correlation coefficient around 0.8. However, relative deviations of lidars increased with altitude above 2000 m. The surface ozone concentrations observed using ozone lidars agreed well with the ground-based ozone analyzer, especially during periods with ozone concentrations higher than 40 µg·m−3. The correlation coefficients for most models of ozone lidar are higher than 0.53. A further investigation of the influence of precipitation events on ozone lidar measurement has been conducted, which revealed that thick cloud layers, low cloud base, and an intensive precipitation event with large raindrop particles can result in high anomalies and reduce the inversion accuracy of the ozone lidar. During the experiment, four ozone lidars were assessed quantitatively according to the comprehensive performance, which could help to improve inversion algorithms and the system design of this promising technique. [ABSTRACT FROM AUTHOR]

Ecosystem carbon use efficiency (CUE) is a key parameter in the carbon cycling of terrestrial ecosystems. The magnitude of CUE reflects the ecosystem's potential for CO2 sequestration. China's grasslands play an important role in the carbon cycle. Here, we aimed to investigate the comparation of CUE and its environmental regulation among different grassland in Northern China based on eddy covariance carbon fluxes measurements of 31 grassland sites. The results showed that the average CUE of grassland in Northern China was 0.05 ± 0.22, with a range from −0.42 to 0.66. It was demonstrated that there were significant differences in CUE among different grassland types, and CUE values were ranked by type as follows: alpine grassland > temperate meadow steppe > temperate typical steppe > temperate desert steppe, driven by a combination of climatic, soil, and biological factors, with net ecosystem productivity (NEP) having the greatest impact on them. Except for meadow steppes, moisture had a greater impact on grassland CUE in Northern China than temperature. While temperate desert grassland CUE decreased with increasing soil water content (SWC), the CUE of other grassland types increased with higher precipitation and SWC. These findings will advance our ability to predict future grassland ecosystem carbon cycle scenarios. [ABSTRACT FROM AUTHOR]

With increasing air and sea temperatures, the thermodynamic environments over the oceans are becoming more favourable for the development of intense tropical cyclones (TCs) with rapid intensification (RI). The South China coastal region consists of highly densely populated cities, especially over the Pearl River Delta (PRD) region. Intense TCs maintaining their strength or the RI of TCs close to the coastal region can present substantial forecasting challenges and have significant potential impacts on the coastal population. This study investigates the effect of sea-surface and sub-surface temperatures and salinity on the intensification of five TCs, namely Super Typhoon Hato in 2017, Super Typhoon Mangkhut in 2018, and Typhoon Talim, Super Typhoon Saola, and Severe Typhoon Koinu in 2023, which have significantly affected the South China coastal region and triggered high TC warning signals in Hong Kong in the past few years. This analysis utilised the Hong Kong Observatory's TC best-track and intensity data, along with sea temperature and salinity profiles generated using the China Ocean ReAnalysis version 2 (CORA2) product from the National Marine Data and Information Service of China. It was found that high sea-surface temperatures (SST) of 30 °C or above for a depth of about 20 m, low sea-surface salinity (SSS) levels of 33.8 psu or below for a depth of at least 20 m, and strong salinity stratification of at least 0.6 psu per 100 m depth might offer useful hints for predicting the RI of TCs over the western North Pacific and the South China Sea (SCS) in operational forecasting, while noting other contributing environmental factors and synoptic flow patterns conducive to RI. This study represents the first documentation of sub-surface salinity's impact on some intense TCs traversing the SCS during 2017–2023 based on an observational study. Our aim is to supplement operational techniques for forecasting RI with some quantitative guidance based on upper-level ocean observations of temperatures and salinity, on top of well-known but more rapidly changing dynamical factors like low-level convergence, weak vertical wind shear, and upper-level divergent outflow, as forecasted with numerical weather prediction models. This study will also encourage further research to refine the analysis of quantitative contributions from different RI factors and the identification of essential features for developing AI models as one way to improve the forecasting of TC RI before the TC makes landfall near the PRD, with due consideration given to the effect of freshwater river discharge from the Pearl River. [ABSTRACT FROM AUTHOR]

On 31 July 2021, Ningbo, an eastern coast city in China, experienced a severe convective rainstorm, characterized by intense short-duration precipitation extremes with a maximum rainfall rate of 130 mm h−1. In this research, we first analyzed this rainstorm using Doppler radar and precipitation observation and then conducted high-resolution simulation for it. A three-dimensional precipitation diagnostic equation is introduced to quantitatively analyze the microphysical processes during the rainstorm. It is shown that this rainstorm was triggered and developed locally in central Ningbo under favorable large-scale quasi-geostrophic conditions and local conditions. In the early stage, the precipitation increase is mainly driven by the strong convergence of water vapor, and a noticeable increase in both the intensity and spatial extent of uplift promotes the upward transportation of water vapor. As the water vapor flux and associated convergence weaken in the later stage, the precipitation reduces accordingly. Cloud microphysical processes are also important in the entire precipitation process. The early stage updraft supports the escalations in raindrops, with the notable fluctuations in raindrop concentrations directly linked to variations in ground precipitation intensity. The behavior of graupel particles is intricately connected to their melting as they fall below the zero-degree layer. Although cloud water and snow exhibit changes during this period, the magnitudes of these adjustments are considerably less pronounced than those in raindrops and graupels, highlighting the differentiated response of various condensates to the convective dynamics. These results can help deepen the understanding of local severe rainstorms and provide valuable scientific references for practical forecasting. [ABSTRACT FROM AUTHOR]

The permafrost in Northeast China is experiencing rapid degradation due to the influence of climate change and human activities, profoundly impacting the local ecological environment and engineering construction. Understanding the spatiotemporal dynamics of long-term permafrost in this region is crucial; however, systematic research on this topic remains scarce. This study combines meteorological station data, MODIS land surface temperature (LST) datasets, and borehole locations to apply the surface frost number (SFn) model. This approach enables the simulation and estimation of the spatial distribution and changes in the area of the surface frost number without vegetation effects (SFnv) and permafrost temperature (PT) in Northeast China from 1971 to 2020. The area of the SFnv > 0.49 within the permafrost region decreased substantially from approximately 44.353 × 104 km2 to 19.909 × 104 km2 between 1971 and 2020, with a notable change in 1988. The area of permafrost calculated using PT < 0 was slightly smaller, declining from 39.388 × 104 km2 to 29.852 × 104 km2. There was also a significant increase in the area with PT ranging from −1 °C to 0 °C, indicating a decline in permafrost stability. Approximately 10.926 × 104 km2 of stable permafrost has been transformed into semi-stable and unstable permafrost. Moreover, from 1982 to 2020, the NDVI was negatively correlated with the area of stable permafrost and positively correlated with the area of transitional or unstable permafrost. Vegetation cover decreased as transitional or unstable permafrost degraded. These findings provide valuable information for permafrost research and engineering development in cold regions, as well as for future planning and adaptation strategies. [ABSTRACT FROM AUTHOR]

Previously, the types of impacts of land–atmosphere interactions have scarcely been clarified systematically. In this article, we present a classification of these impacts based on modeling boundary layer variables/parameters, which is grouped into local, regional, and remote impacts. In the narrow sense, land surface processes (LSPs) influence the atmospheric state via vertical land–atmosphere coupling at local scales, which is referred to as local LSP impacts. However, local LSP impacts can lead to the advection effect due to the horizontal heterogeneity in the parameters over a region, which can be defined as regional LSP impacts. Furthermore, remote LSP impacts on the regional atmospheric state are induced by some land/sea surface variables/parameters over remote key areas of the Earth's surface, which are conventionally taken as strong signals of climate variation. Of the three impacts, local impacts are the most important essential, as the other two types of impacts are derived from these impacts. We describe the quantification of local impacts based on our previous studies from the perspective of modeling approaches, and we discuss some issues related to these impacts. Previous investigations showed that local LSP impacts are mostly stronger than regional LSP impacts, e.g., the diabatic process is dominant in the physical processes responsible for daily maximum temperatures, and two first-order physical processes including vertical diffusion largely induce changes in surface wind speed in China. Finally, some aspects for future research are noted. This study provides insights into the research on land–atmosphre interactions at different scales. [ABSTRACT FROM AUTHOR]

As the predominant pollutant in North China during the summer months, ozone (O3) exhibits strong oxidizing capabilities. Long-term exposure of crops to ozone will cause a decrease in various physiological indicators, affect crop yields, and pose a serious threat to food security. The North China Plain, the primary region for summer maize production in China, is afflicted by ozone pollution. In order to explore the effects of increasing O3 concentration on the physiological characteristics and photosynthetic characteristics of summer maize, this study took summer-sown maize as the research object and carried out the ozone exposure experiment with open-top chamber (OTCs). The response of maize to O3 exposure was studied by measuring the damage, physiological indexes and photosynthetic indexes in the silking stage (late July to late August) and filling stage (late August to mid-September). The results indicated the following: (1) Prolonged exposure to high O3 concentrations exacerbated leaf chlorosis and damage. (2) The increase in O3 concentration caused lipid peroxidation. The content of malondialdehyde was significantly increased by 32.6%~122.56%. At the same time, chlorophyll was destroyed and decreased by 2.17% to 4.86%. Under ozone exposure, ascorbic acid content was significantly increased by 7.58%~35.69%. The antioxidant indexes of maize were more sensitive during the filling stage. (3) Under O3 exposure, photosynthetic rate, stomatal conductance and intercellular carbon dioxide concentration decreased significantly, indicating that the influence of O3 on maize was mainly due to stomatal limitation. Water use efficiency and transpiration rate decreased significantly. The water use efficiency decreased by 12.84%~35.62%, which led to the weakening of the carbon fixation ability of maize and affected the normal growth and development of maize. [ABSTRACT FROM AUTHOR]

It is of great scientific value to study the spatial differences and influencing factors of carbon emission intensity (CEI) in urban agglomerations (UAs), and it also has reference significance for China in formulating energy-saving and emission-reduction policies to achieve the target of carbon neutrality. Taking 165 prefecture-level cities in 19 UAs in China from 2007 to 2019 as the research object, this study investigated the spatial differences of CEI in UAs using exploratory spatial data analysis and explored the influencing factors of CEI via Geodetector. The results showed the following: (1) The CEI of the UAs showed a downward trend. (2) The CEI of the UAs has typical spatial agglomeration characteristics, where the North comprises mainly high-high and low-high types, whereas the South is primarily high-low and low-low types. (3) The influencing factors of CEI have undergone a transformation from industrial structure to population urbanization. [ABSTRACT FROM AUTHOR]

Atmospheric ice nucleation particles (INPs) play a crucial role in influencing cloud formation and microphysical properties, which in turn impact precipitation and Earth's radiation budget. However, the influence of anthropogenic activities on the properties and concentrations of INPs remains an area of significant uncertainty. This study investigated the physical and chemical characteristics of atmospheric ice nucleation particles in Huangshan, China during the May Day labor holiday period (spanning 8 days, from April 27th to May 5th). INP concentrations were measured at temperatures from −17 °C to −26 °C and relative humidities (RHw) from 95% to 101%. Average INP concentrations reached 13.7 L−1 at −26 °C and 101% RH, 137 times higher than at −17 °C and 95% RH. INP concentrations showed exponential increases with decreasing temperature and exponential increases with increasing RH. Concentration fluctuations were observed over time, with a peak of ~30 L−1 (t = −26 °C, RHw = 101%) around the start and end of the holiday period. Aerosol number concentrations were monitored simultaneously. The peak in aerosols larger than 0.5 μm aligned with the peak in INP concentrations, suggesting a link between aerosol levels and INPs. Chemical composition analysis using SEM–EDX revealed the distinct elemental makeup of INPs based on the activation temperature. INPs active at warmer temperatures contained N, Na, and Cl, indicating possible biomass and sea salt origins, while those active at colder temperatures contained crustal elements like Al and Ca. [ABSTRACT FROM AUTHOR]

A new algorithm is proposed to estimate the cooling amplitude over North China induced by each Ural blocking event. Taking full account of potential transient temperature rises during the cooling process and the lag time of cooling relative to the blocking, this algorithm provides more detailed analysis which should not be possible by using former methods. The amplitude of the Ural blocking-related cooling events is found to have a broad distribution. Further, although most Ural blocking events lead to severe cold surges over North China, the number of Ural blocking events that do not induce significant cooling over North China cannot be ignored. The possible reasons for the wide range in cooling amplitude are explored in terms of the lifetimes and geographical centers of the blocking highs, the circulation patterns preceding the onset of the cooling events, and the snowfall associated with cooling events. Larger amplitude cooling events occur in Ural blocking highs that have longer lifetimes and northwestward displacements of their geographical centers. The northward displacement of a Ural blocking center favors the advection of extremely cold air from the Arctic regions, which accumulates in West Siberia and subsequently gives rise to the most severe cold surges over North China. The lack of activities of cold surges before the blocking-related cooling events not only amplifies the cooling amplitude directly, but also increases the occurrence probabilities of snowfalls through its modulation on the local specific humidity. The increased albedo and subsequent snow-melt induced cooling further amplify the cooling amplitude. [ABSTRACT FROM AUTHOR]

Wind shear is one of the crucial parameters in wind resource assessment and also serves as a vital parameter and basis for determining wind turbines' selection and hub height. Existing studies have only focused on typical underlying surface areas, but a relatively limited comprehensive analysis of wind shear characteristics in different complex environments remains. This study analyzes the daily and monthly variations in wind shear index (α) at the station scale based on the observations from 754 wind measurement towers across land surfaces in China. The distribution and empirical values of wind shear in different wind regions and underlying surface types are also investigated. The research findings indicate that the wind shear index derived from fitting the complete annual average wind speeds at multiple height levels of meteorological towers can accurately characterize the stratification state of the atmospheric boundary layer. The variation pattern of solar radiation influences the daily α value in typical regions. In mountainous and desert areas, the monthly variation tends to be higher in autumn and winter and lower in spring and summer. However, its monthly variation shows relatively smaller fluctuations in plain regions. The comprehensive α value over land regions in China is 0.135. The α values for I, II, III, and IV wind fields are 0.111, 0.163, 0.1, and 0.153, respectively. Its values for mountainous, plains, grassland, and desert regions are 0.12, 0.273, 0.123, and 0.104, respectively. By conducting statistical analysis on α values across different wind regions, guidance is provided for extrapolating surface wind speeds to hub-height wind speeds. This serves as a reference for wind energy resource assessment, wind turbine selection, and hub height determination in the atmospheric boundary layer of China. [ABSTRACT FROM AUTHOR]

Most studies on Chinese dormitories are carried out in summer, while few focus on a transition season or winter. This study evaluated the air quality of a student dormitory in a university in the Beijing area by using a questionnaire survey and on-site measurements. The CO2 concentration was used as an indoor air quality evaluation index to characterize the freshness of the air, and different window opening conditions in the dormitory were simulated, with corresponding improvement plans proposed. The results of this study revealed that the air quality and thermal comfort of the student dormitories during a transition season and winter fell short of expectations. According to the survey, students who opened their windows frequently had a better subjective perception of the air quality. However, due to the large temperature difference between day and night, more than 80% of the students felt too cold when opening the windows. For daytime conditions, the area of unilateral ventilation window opening should not be less than 0.39 m2, the area of bilateral ventilation window opening should not be less than 0.13 m2, and the time taken to close the windows and doors should not exceed the maximum ventilation interval. Empirical equations were fitted for nighttime conditions based on the CO2 concentration, number of people in the room, and window opening area, resulting in a reasonable window opening area of 0.349 m2~0.457 m2. In sum, this study assessed the air quality status within typical university dormitories across varying seasons, gaining a clear understanding of how different ventilation strategies and occupant densities influence air freshness and thermal comfort. Based on these insights, a practical and optimized window area recommendation was formulated to enhance the indoor environmental quality in these dormitories. [ABSTRACT FROM AUTHOR]

Regional haze often occurs after the New Year holiday. To explore the characteristics of PM2.5 pollutions under the influence of the New Year's Day effect, this study analyzed the spatiotemporal changes relating to PM2.5 during and around the New Year's Day holiday in China from 2015 to 2022, and used the Weather Research and Forecasting-Community Multiscale Air Quality (WRF-CMAQ) model to study the effects of human activities and meteorological factors on PM2.5 pollutions, as well as the differences in the contributions of different industries to PM2.5 pollutions. The results show that for the entire study period (i.e., before, during, and after the New Year's Day holiday) from 2015 to 2022, the average concentrations of PM2.5 in China decreased by 41.9% overall. In 2019~2022, the New Year's Day effect was significant, meaning that the average concentrations of PM2.5 increased by 18.9~46.8 μg/m3 from before to after the New Year's Day holiday, with its peak occurring (64.3~74.9 μg/m3) after the holiday. In terms of spatial differences, the average concentrations of PM2.5 were higher in the Beijing–Tianjin–Hebei region, the Yangtze River Delta, and central China. Moreover, the Beijing–Tianjin–Hebei region and its surrounding areas, the Chengdu–Chongqing region, the Fenwei Plain, and the middle reaches of the Yangtze River region were greatly affected by the New Year's Day effect. Human activities led to higher increases in PM2.5 in Henan, Hubei, Hebei, and Anhui on 3 and 4 January 2022. If the haze was accompanied by cloudy days or weak precipitation, the accumulation of surface water vapor and atmospheric aerosols further increased the possibility of heavy pollution. It was found that, for the entire study period, PM2.5 generated by residential sources contributed the vast majority (60~100 μg/m3) of PM2.5 concentrations, and that the main industry sources that caused changes in time distributions were industrial and transportation sources. [ABSTRACT FROM AUTHOR]

Precise water management is essential for the efficient development of irrigated agricultural crops in the Hetao Irrigation Area of Inner Mongolia. Given the severe water scarcity in the region and the significant use of intercropping as a cropping method, the development of rational irrigation scheduling is crucial. The objective of this work was to combine the ISAREG model with wheat–sunflower intercropping crops in order to enhance the effectiveness of irrigation scheduling in intercropping systems. This was achieved by changing and verifying crucial parameters for simulating irrigation patterns in intercropping. We conducted an assessment of nine irrigation schedules for a wheat–sunflower intercropping system in order to provide a range of irrigation scenarios that effectively fulfill the water requirements of the system. In light of this, we suggested implementing restrictions on the dates and volumes of irrigation based on the demand for agricultural irrigation. This approach aimed to establish irrigation schedules that are highly efficient and tailored to the specific crops in the area. As a result, we achieved a water use efficiency rate of 100%, saved 28.78% of water resources, optimized crop irrigation schedules, and enhanced crop economics by 6.7%. This study presents a novel and efficient method to optimize agricultural irrigation schedules, boost agricultural water use efficiency, and maximize crop yields in order to promote sustainable agricultural development. [ABSTRACT FROM AUTHOR]

The transport and dispersion (T&D) of catalyst particles seeded by weather modification aircraft is crucial for assessing their weather modification effects. This study investigates the capabilities of the Chinese geostationary weather satellite FY-4A for identifying the physical response of cloud seeding with AgI-based catalysts and continuously monitoring its evolution for a weather event that occurred on 15 December 2019 in Henan Province, China. Satellite measurements are also used to verify an operational catalyst T&D algorithm. The results show that FY-4A exhibits a remarkable capability of identifying the cloud-seeding tracks and continuously tracing their evolution for a period of over 3 h. About 60 min after the cloud seeding, the cloud crystallization track became clear in the FY-4A tri-channel composite cloud image and lasted for about 218 min. During this time period, the cloud track moved with the cloud system about 153 km downstream (northeast of the operation area). An operational catalyst T&D model was run to simulate the cloud track, and the outputs were extensively compared with the satellite observations. It was found that the forecast cloud track closely agreed with the satellite observations in terms of the track widths, morphology, and movement. Finally, the FY-4A measurements show that there were significant differences in the microphysical properties across the cloud track. The effective cloud radius inside the cloud track was up to 15 μm larger than that of the surrounding clouds; the cloud optical thickness was about 30 μm smaller; and the cloud-top heights inside the cloud track were up to 1 km lower. These features indicate that the cloud-seeding catalysts led to the development of ice-phase processes within the supercooled cloud, with the formation of large ice particles and some precipitation sedimentation. [ABSTRACT FROM AUTHOR]

Northern and southern fog events are identified over eastern China across 40 winters from 1981 to 2021. By performing composite analysis on these events, this study reveals that the formation of fog events is controlled by both dynamic and thermodynamic processes. The fog events were induced by Rossby wave trains over the Eurasian continent, leading to the development of surface wind and pressure anomalies, which favor the formation of fog events. The Rossby wave trains in northern and southern fog events are characterized by their occurrence in northern and southern locations, respectively, with different strengths. The water vapor fluxes that contribute to the enhancement of the northern fog events originate from the Yellow Sea and the East China Sea, whereas the southern fog events are characterized by water vapor from the East China Sea and the South China Sea. In both northern and southern fog events, dew point depression and positive A and K index anomalies are found in northern and southern regions of eastern China, which are indicative of supersaturated air and the unstable atmospheric saturation from the low to the middle troposphere, thus providing favorable conditions for the establishment of fog events in northern and southern regions of eastern China. [ABSTRACT FROM AUTHOR]

Knowledge of the quantitative importance of the moisture transport pathways and mutual moisture exchange of the source regions of the Yangtze (SYZR) and Yellow (SYR) rivers' basins, the adjacent origins of China's two longest rivers, can provide insights into the regional atmospheric branch of the hydrological cycle over the source regions. The method with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model and a Lagrangian moisture source diagnostic to identify the major moisture transport pathways quantifies their importance to two types of daily precipitation events—daily precipitation more than 10 mm (PM) events and daily precipitation less than 10 mm (PL) events—for the two rivers' regions during the summer (June–August, 1986–2015) and finds the characteristics of mutual moisture exchange. The results indicated that both the Bay of Bengal group pathway and the northwest China group pathway play significant roles in PM and PL events over the SYZR, contributing 41.87% and 39.12% to PM events and 41.33% and 33.16% to PL events, respectively. The SYR has five main moisture path groups; the Bay of Bengal group pathway, the northwest China group pathway, and the southeast China group pathway play significant roles in PM and PL events over the SYR, contributing 32.34%, 23.28%, and 34.36% to PM events and 34.84%, 36.18%, and 19.83% to PL events, respectively. The volume of moisture passing from the SYZR to the SYR is approximately 60 times that of the reverse, constituting about 6.9% of the total moisture released in SYR precipitation. It is worth noting that the moisture release was concentrated in the nearer west group pathway, and the main moisture uptake locations were beyond the source region of the two rivers (remote sources) in the PM events. The aggregate moisture release high-frequency moisture transport path groups are found in the southeastern parts of Zhiduo County and the southeast of Zaduo County. [ABSTRACT FROM AUTHOR]

The ozone (O3) variations in southeast China are largely different between mountainous forest areas located inland, and lowland urban areas located near the coast. Here, we selected these two kinds of areas to compare their similarities and differences in surface O3 variability from diurnal to seasonal scales. Our results show that in comparison with the lowland urban areas (coastal areas), the mountainous forest areas (inland areas) are characterized with less human activates, lower precursor emissions, wetter and colder meteorological conditions, and denser vegetation covers. This can lead to lower chemical O3 production and higher O3 deposition rates in the inland areas. The annual mean of 8-h O3 maximum concentrations (MDA8 O3) in the inland areas are ~15 μg·m−3 (i.e. ~15%) lower than that in the coastal areas. The day-to-day variation in surface O3 in the two types of the areas is rather similar, with a correlation coefficient of 0.75 between them, suggesting similar influences on large scales, such as weather patterns, regional O3 transport, and background O3. Over 2016–2020, O3 concentrations in all the areas shows a trend of "rising and then falling", with a peak in 2017 and 2018. Daily MDA8 O3 correlates with solar radiation most in the coastal areas, while in the inland areas, it is correlated with relative humidity most. Diurnally, during the morning, O3 concentrations in the inland areas increase faster than in the coastal areas in most seasons, mainly due to a faster increase in temperature and decrease in humidity. While in the evening, O3 concentrations decrease faster in the inland areas than in the coastal areas, mostly attributable to a higher titration effect in the inland areas. Seasonally, both areas share a double-peak variation in O3 concentrations, with two peaks in spring and autumn and two valleys in summer and winter. We found that the valley in summer is related to the summer Asian monsoon that induces large-scale convections bringing local O3 upward but blocking inflow of O3 downward, while the one in winter is due to low O3 production. The coastal areas experienced more exceedance days (~30 days per year) than inland areas (~5-10 days per year), with O3 sources largely from the northeast. Overall, the similarities and differences in O3 concentrations between inland and coastal areas in southeastern China are rather unique, reflecting the collective impact of geographic-related meteorology, O3 precursor emissions, and vegetation on surface O3 concentrations. [ABSTRACT FROM AUTHOR]

Located in the central part of the arid regions of Northwest China, the Heihe River Basin (HRB) plays an important role in wind prevention, sand fixation, and soil and water conservation as the second largest inland river basin. In the context of the warming and wetting climate observed in Northwest China, the situation of the ecological environment in the HRB is of significant concern. Using the data from meteorological observation stations, grid fusion and hydrological monitoring, this study analyzes the multi-scale climate changes in the HRB and their impacts on runoff. In addition, predictive models for runoff in the upper and middle reaches were developed using machine learning methods. The results indicate that the climate in the HRB has experienced an overall warming and wetting trend over the past 60 years. At the same time, there are clear regional variabilities in the climate changes. Precipitation shows decreasing trends in the northwestern part of the HRB, while it shows increases at rates higher than the regional average in the southeastern part. Moreover, the temperature increases are generally smaller in the upper reaches than those in the middle and lower reaches. Over the past 60 years, there has been a remarkable increase in runoff at the Yingluo Gorge (YL) hydrological station, which exhibits a distinct "single-peak" pattern in the variation of monthly runoff. The annual runoff volume at the YL (ZY) hydrological station is significantly correlated with the precipitation in the upper (middle) reaches, indicating the precipitation is the primary influencing factor determining the annual runoff. Temperature has a significant impact only on the runoff in the upper reaches, while its impact is not significant in the middle reaches. The models trained by the support vector machines and random forest models perform best in predicting the annual runoff and monthly runoff, respectively. This study can provide a scientific basis for environmental protection and sustainable development in the HRB. [ABSTRACT FROM AUTHOR]

Quantifying the atmospheric water balance is critical for the study of hydrological processes in significant regions. This study quantified atmospheric water balance closure at 205 stations in mainland China on a monthly timescale from 2009 to 2018 using datasets from ground- and satellite-based observations and reanalysis data. The closure performances were firstly quantified using the mean and root mean square (RMS) of the residuals, and the possible influencing factors were explored, as well as the influence of different water balance components (WBCs) using different datasets. In the closure experiment using ERA5, the mean and residuals were 6.26 and 12.39 mm/month, respectively, on average, which indicated a closure uncertainty of 12.8%. Using ERA5 analysis as a reference, the closure experiment using different combinations revealed average mean residuals of 8.73, 11.50, and 15.89 mm/month, indicating a precipitation closure uncertainty of 22.0, 23.7, and 24.4% for the ground- and satellite-based observations and reanalysis data, respectively. Two possible influencing factors, station latitude and the climatic zone in which the station is located, were shown to be related to closure performance. Finally, the analysis of the impact from different WBCs showed that precipitation tended to have the most significant impact, which may have been due to larger observation uncertainties. Generally, the atmospheric water balance in mainland China can be closed using datasets from different observational techniques. [ABSTRACT FROM AUTHOR]

Amidst global climate change and unsustainable human exploitation of water resources, water has emerged as a critical factor constraining global agricultural food production and ecological environments. Particularly in agricultural powerhouses like China, irrigation water accounts for a significant portion of freshwater resource utilization. However, the inefficiency of irrigation water usage has become a weak link in water resource management. To better assess irrigation water efficiency, an accurate estimation of regional irrigated areas is urgently needed. This study proposes a method for identifying actual irrigated areas based on remote sensing-derived evapotranspiration (ET) to address the challenge of accurately interpreting irrigated areas in tropical regions. Using Yunnan Province's Yuanmou irrigation district as a case study, this research combined ground monitoring data and remote sensing data to identify actual irrigated areas through ET inversion and downscaling methods using the Penman–Monteith–Leuning (PML) model. In 2023, the total irrigated area interpreted from remote sensing in the study area was approximately 15,000 hm2, with a comparison against validation points revealing an extraction error of 16%. The small error indicates that this method can effectively enhance the reliability of monitoring actual irrigated areas, thus providing valuable data support for agricultural irrigation water management. [ABSTRACT FROM AUTHOR]

Climate is one of the key factors driving changes in vegetation, and the response of the vegetation to climate often occurs with a time delay. However, research on the cumulative lagged response of the vegetation to meteorological factors in large-scale regions is limited. Therefore, this study first evaluated the performance of the Gross Primary Productivity (GPP) products provided by Moderate Resolution Imaging Spectroradiometer (MODIS) and Penman–Monteith–Leuning (PML) over the past 20 years in China and then determined the lagged relationships between the GPP and major meteorological factors in different regions and land-use types in China based on a partial correlation analysis. The results indicate that (1) GPP_PML outperforms GPP_MODIS products in the regional context of China; (2) China's regional GPP has shown a fluctuating upward trend over the past 20 years, with a stepwise increase in the multi-year average from the northwest inland to the southeast coastal regions, and a higher contribution from the southern regions than the northern ones; (3) unlike the recent upward trend in regional temperatures, both precipitation and radiation have decreased, with these two factors showing completely opposite multi-year trends in most regions; and (4) the proportion of regions with lagged effects of the GPP on meteorological factors is higher than those with cumulative effects in China. Among these, GPP exhibits a higher proportion of a 3-month lagged response to precipitation, which is particularly pronounced at altitudes between 500 and 2500 m and above 5500 m. the proportion of the areas with no lag cumulative response to temperature and radiation with GPP in China is the highest due to the influence of more barren land and grassland in the northwest interior. Simultaneously, grassland and barren land have a higher proportion of the non-lagged cumulative responses to temperature and precipitation. This study contributes to our understanding of vegetation dynamics in the context of global climate change and provides a theoretical foundation for regional ecological conservation and high-quality coordinated development. [ABSTRACT FROM AUTHOR]

In this study, we investigate the seasonal and diurnal variations in cloud occurrence frequency, as well as cloud vertical structure (CVS) characteristics under different seasons and precipitation intensities over the Guangzhou region in South China, based on the analysis of millimeter-wave cloud radar (MMCR) and ground automatic weather station rainfall observations from May 2019 to August 2021. The results showed that the occurrence frequency of clouds exhibits a bimodal distribution throughout the year, with peaks in March to June and October, reaching its highest occurrence in May at approximately 80% and its lowest from December to February at around 40%. Additionally, there are distinct diurnal variations in occurrence frequency, with the lowest rates occurring around 0005 LST, rapidly increasing after 0006 LST, and peaking during the afternoon to evening hours. Cloud top height (CTH) shows bimodal distributions during the pre-flood and post-flood seasons. The most frequently occurring range of CTH during the pre-flood season is below 3 km, accounting for approximately 43%, while during the post-flood season, it ranges from 11 to 14 km, constituting about 37%. For precipitation clouds, CTH can extend beyond 12 km, with the radar reflectivity decreasing gradually with increasing height. The highest frequencies of radar echoes are observed below 2 km and between 4 and 7 km, exhibiting clear diurnal variations, with echoes mainly below 2 km and between 4 to 6 km during the early morning, intensifying and shifting to higher altitudes during the day and reaching their maximum below 4 km during the afternoon to nighttime hours, while both the frequency and intensity increase in the height range of 4 to 12 km. Vertical profiles of radar reflectivity and cloud ice/liquid water content (IWC/LWC) exhibit similar trends under different precipitation intensities. The main differences are observed below 4 km, where both radar reflectivity and IWC/LWC generally increase with increasing precipitation intensity. These findings contribute to a better understanding of cloud characteristics in the South China region, enhance the accuracy of model simulations, and provide a scientific basis for accurate forecasting and warning of meteorological disasters. [ABSTRACT FROM AUTHOR]

In recent years, nocturnal ozone enhancement (NOE) events have emerged as a prominent research focus in the field of the atmospheric environment. By using statistical analysis methods, we conducted a comparative investigation of nocturnal ozone concentrations and NOE events in Dongying, the central city of the Yellow River Delta, China, in 2022 and 2023, and further explored the effects of NOE events on O3 and PM2.5 on the same night and the subsequent day. The results showed that from 2022 to 2023, in Dongying, the annual average nocturnal ozone concentrations increased from 51 μg/m3 to 59 μg/m3, and the frequency of NOE events was higher in the spring, summer, and autumn, and lower in the winter. The NOE events not only exhibited promoting effects on nocturnal O3 and Ox, and on the daily maximum 8 h average concentration of O3 (MDA8-O3) on the same day (comparatively noticeable in summer and autumn), but also demonstrated a clear impact on nocturnal PM2.5 and PM2.5-bounded NO3− and SO42− (especially in winter). Additionally, the NOE events also led to higher concentrations of O3 and Ox, as well as higher MDA8-O3 levels during the subsequent day, with more observable impacts in the summer. The results could strengthen our understanding about NOE events and provide a scientific basis for the collaborative control of PM2.5 and O3 in urban areas in the Yellow River Delta in China. [ABSTRACT FROM AUTHOR]

This study focuses on the real-time precipitation forecast products of the GRAPES_MESO regional ensemble forecast model, which is developed by the Numerical Weather Prediction Center of the China Meteorological Administration and is initialized 1–3 days in advance at 12:00 UTC. Using a national-level homogenized precipitation grid dataset from surface meteorological stations as observational data, a frequency matching method (FMM) is employed to correct precipitation forecasts for different precipitation intensity levels, including light rain, moderate rain, heavy rain, and torrential rain. Case studies and statistical tests (TS scores) are conducted to compare the forecast performance before and after correction. The results indicate that the model's Cumulative Distribution Function (CDF) curves deviate from observations, and the longer the lead time, the more significant the error. The correction coefficients (CCs) show an increasing trend with the growth of precipitation intensity, indicating that for larger precipitation amounts and longer lead times, larger CCs are needed, highlighting the necessity of correction. Analyzing two precipitation events in South China in July 2019, the FMM results in an increase in precipitation intensity and a widening of the range of heavy precipitation. The corrected precipitation magnitudes are closer to the observations. The statistical tests using TS scores reveal that the FMM has a certain correction effect on the overall precipitation forecast in the South China region, especially for longer lead times and higher precipitation intensities, where the correction effect is more significant. The necessity of frequency matching correction becomes more apparent for heavier precipitation, and the correction effect becomes more significant with longer lead times. [ABSTRACT FROM AUTHOR]

Occupational health risk assessments of exposure to VOCs still need to be extensively studied to improve the safety standards in the industry. Based on the monitoring of organic pollutants at various workstations in a truck tire factory in Jiangsu Province, both semi-quantitative and quantitative health risk assessment methods were employed to assess health risk levels. The findings indicated that VOCs were categorized into five classes, which included alkanes, aromatics, halocarbons, carbon disulfide, and oxygenated volatile organic compounds (OVOCs). The highest concentration of total volatile organic compounds (TVOCs) was found in shaping workshop; alkanes were the most abundant class (74.2%), followed by aromatics (24.02%) and OVOCs (1.96%). Although the results of the semi-quantitative risk assessment showed that most of the organic compounds had low R values, various kinds of VOCs were detected; particularly, many harmful organic compounds (such as toluene, ethyl benzene) were detected in all the sampling sites. The quantitative risk in the calendering and vulcanizing workshop exceeded the acceptable level; both the carcinogenic risk of ethylbenzene in the tire-strip storage room, and trichloroethylene and perchloroethylene in the calendering workshop were unacceptable. Thus, the calendering and vulcanizing processes in rubber tire manufacturing should be priority-controlled processes. [ABSTRACT FROM AUTHOR]

Poyang Lake is the largest freshwater lake in China and forms an essential component of the hydrological, nutrient, and carbon cycles, providing various ecosystem services to the local environment. Since changes in Poyang Lake's water temperature can significantly affect the surrounding environment and social development, continuous monitoring of lake temperature changes is required. Traditional water monitoring methods are resource intensive and cannot simultaneously conduct extensive water monitoring. Remote sensing of temperature inversion has the advantages of all-weather, efficient, and large-scale real-time monitoring. Six Landsat 8 images from August to October in 2020 and 2021 were utilized to extract lake surface temperature (LST), and the variations in LST over the two years were analyzed to determine the impact of global climate anomalies on inland lakes. The results indicate that the LST in August and October 2021 was significantly higher than that in the same periods of the previous year, and the temperature difference in October reached 8 °C. In contrast to the overall normal distribution pattern of the water temperature in 2020, 2021 exhibited a relatively concentrated, unimodal distribution pattern. A trend analysis of the driving factors suggests that the LST of Poyang Lake is influenced by the global climate, and the artificial heat sources around the lake clearly alter the distribution characteristics of the LST simultaneously. [ABSTRACT FROM AUTHOR]

Though the impact of urban vegetation on air quality and the microclimate has attracted increasing attention, there have been few studies quantitatively assessing this impact in North China, where air pollution is severe. In this study, we investigated the impact of urban forests and urban parks on air quality and the microclimate in Jinan, northern China. Six sites were chosen to represent urban forest, urban park, and downtown areas, respectively. The results indicate that urban forest can effectively reduce PM2.5 and ozone (O3) concentrations in the warm season, when temperatures are higher and plants are lush. The PM2.5 and O3 concentrations in the urban forest areas were 6.3–6.5 μg m−3 and 21–23 μg m−3 lower than those in downtown areas during the period of 10:00–15:00. In contrast, urban park areas can reduce PM2.5 concentrations but have little impact on gaseous pollutants such as nitrogen dioxide and O3. Furthermore, both urban forest and urban park areas reduced temperatures, by approximately 4.1–6.8 °C and 1.36 °C, respectively, and increased relative humidity, by about 13.4–12.9% and 0.9%, promoting a more comfortable thermal environment for residents. Therefore, this study highlights the crucial role of urban vegetation in improving air quality and creating a comfortable environment for residents. [ABSTRACT FROM AUTHOR]

Brown carbon (BrC) is a new term for organic aerosol (OA) with strong absorption ability from the visible to ultraviolet (UV) wavelengths, which plays a vital role in atmospheric visibility and climate change. Herein, we report field measurements from 1 March 2020 to 28 February 2021, sampled at urban Suzhou, Yangtze River Delta (YRD), China, to investigate the optical properties and sources of BrC. By analyzing the seasonal characteristics of the absorption of BrC at 370 nm (babs370), babs370 was found to be the highest (9.0 ± 7.2 Mm−1) in winter and the lowest (5.1 ± 3.3 Mm−1) in summer, respectively. The absorption Ångström exponent (AAE) value of BrC in winter was 1.22 ± 0.05, followed by 1.21 ± 0.05, 1.20 ± 0.05, and 1.19 ± 0.05 for fall, spring, and summer, respectively. The mass absorption cross-section (MAC) of secondary organic carbon (SOC) was 3.3 ± 0.2 m2g−1 in spring, 2.9 ± 0.1 m2g−1 in summer, 4.3 ± 0.1 m2g−1 in fall, and 2.8 ± 0.2 m2g−1 in winter, significantly lower than that of primary organic carbon (POC) at 370 nm, suggesting the aging process could weaken the light absorption of BrC. Five different BrC factors were identified by the positive matrix factorization (PMF) analysis, including biomass-burning-related, vehicle-related, sulfate-related, nitrate-related, and dust-related factors, which on average account for 7.4%, 73.4%, 11.9%, 1.9%, and 5.4% of babs370, respectively. Potential Source Contribution Factor (PSCF) analysis showed that those high babs370 periods were mainly contributed by air mass from the south. Moreover, for the influence degree of the potential source areas, the sequence was winter > spring > fall > summer. Our results improve the understanding of BrC in an important industrial city in YRD, which could reduce the uncertainty of the prediction of its climate effect in this region. [ABSTRACT FROM AUTHOR]

Vehicle emissions belong to the category of near-surface sources, occur close to human activity areas, and pose a greater threat to human health than other anthropogenic pollution sources. Furthermore, the study of the spatiotemporal characteristics of near-road traffic pollution is of great significance to urban and regional ambient air quality management, and is also an important basis for vehicle emission inventories, as well as the assessment of ambient air impact. Most previous studies have analyzed the spatiotemporal characteristics of hydrocarbons (HCs), carbon monoxide (CO), nitrogen oxides (NOx), and carbon dioxide (CO2) in urban vehicle emissions over a certain time, without considering the synergistic effect of mobile source particulate matter, NOx, and volatile organic compounds (VOCs). In this study, we analyze the composition of vehicles with different emission standards from road mobile sources in Anqing City, China. National category III and IV vehicles are the main contribution sources of various pollutants, accounting for more than 60% of emissions. Although national category I and II vehicles accounted for less than 1% of the total number of vehicles, their contribution to emissions cannot be ignored, especially for CO and HCs, the contribution of which from such vehicles can reach about 7%. This is mainly due to the low level of pollution control arising from the larger emission factor and greater age of these vehicles. Furthermore, eliminating old cars and increasing the proportion of national category VI vehicles can effectively reduce vehicle pollutant emissions. In terms of the spatiotemporal distribution characteristics, highways around urban areas are also the main sources of heavy vehicles, and the emission intensity of these pollutants is also higher on national roads and highways surrounding urban areas. In addition, the presence of m/p-xylene and toluene solvent-using species is detected, which indicates that petrol vehicle emissions, LPG and petrol volatilization, and solvent-using sources contribute significantly to ozone formation in the ozone pollution process. Comparing weekdays and non-weekdays, the PM2.5 peaks on non-weekdays are significantly higher than those on weekdays, and there is no "weekend effect", which indicates that traffic emissions have little influence on PM2.5 emissions, and may be related to energy use and industrial pollution. Overall, this study strengthens the understanding of the relationship between emissions, traffic volumes, and vehicle types on spatial and temporal scales, and emphasizes the need for further investigation and comprehensive measures to mitigate pollution from these emissions. [ABSTRACT FROM AUTHOR]

On 6 June 2017, four severe clear-air turbulence (CAT) events were observed over northern China within 3 h. These events mainly occurred at altitudes between 8.1 and 9.5 km. The characteristics and possible mechanisms of the CAT events in the different regions are investigated here using the weather research and forecasting (WRF) model. The simulated wind and temperature fields in a 27 km coarse domain were found to be in good agreement with those of the ERA5 (European Centre for Medium-Range Weather Forecasts Reanalysis v5) and the observed soundings of operational radiosondes over northern China. In terms of synoptic features, the region where the turbulence occurred is characterized by a southwest–northeast upper-level jet stream. The upper-level jet stream observed at an altitude of 10.4 km consistently moved eastwards, with a maximum wind speed of 61.7 m/s. Simultaneously, the upper-level front–jet system on the cyclonic shear side of the upper-level jet stream also exhibited an eastward motion. The developed upper-level front–jet system induced significant vertical wind shear (VWS) and tropopause folding in the vicinity of these CAT events. Despite the high stability resulting from tropopause folding, the presence of strong VWS (1.90 × 10−2 s−1–2.55 × 10−2 s−1) led to a low Richardson number (Ri) (0.24–0.88) and caused Kelvin–Helmholtz instability (KHI), which ultimately induced CAT. Although a standard numerical weather forecast resolution of tens of kilometers is adequate to capture turbulence for most CAT events, it is still necessary to use high-resolution numerical simulations (such as 3 km) to calculate more accurate CAT indices (such as Ri) for CAT prediction in some specific cases. [ABSTRACT FROM AUTHOR]

Trace metals from natural and anthropogenic sources impact the atmospheric environment and enter the soil through dry and wet atmospheric deposition, ultimately affecting human health. In this study, we established an emission inventory of Pb, As, Cr, and Cd in East Asia (80° E–140° E, 15° N–50° N) for the year 2017, including dust and anthropogenic sources from both land and marine. We modified the Community Multiscale Air Quality (CMAQ) model to provide gridded data on concentrations, as well as dry and wet atmospheric deposition fluxes of metals, with a focus on mainland China. The emissions of Pb, As, Cr, and Cd in East Asia were 19,253, 3415, 3332, and 9379 tons, respectively, in 2017, with 55%, 69%, 25%, and 58% distributed in the fine mode. The spatial distribution of atmospheric concentrations and dry deposition of trace metals was similar to that of emissions, while the spatial distribution of precipitation-related wet deposition was further east and greater in the south than in the north. In mainland China, the average bulk-deposition fluxes of Pb, As, Cr, and Cd were 1036.5, 170.3, 465.9, and 185.0 μg·m−2·year−1, respectively. Our study provides gridded data on trace metals in mainland China, which can be used for assessing air quality, human exposure risks, and metal inputs to soils. [ABSTRACT FROM AUTHOR]

High-temperature and drought events significantly impact crop growth and development. In the soybean-producing region of the Guanzhong Plain in China, understanding the dynamics of these climatic phenomena is vital for soybean yield preservation. Through a fixed-position observation experiment that analyzed four growth stages, nine agronomic traits, and soybean yield per unit area from 1998 to 2023, this research evaluated the characteristics of high-temperature and drought processes in various growth stages. It also examined the influence of high-temperature processes, drought processes, and their combined effects on agronomic traits and yield. The results indicate the following: (1) High temperature was a constant factor during the soybean growth period, with temperature-related indices markedly surpassing those related to drought. Notably, the occurrence of high-temperature and drought events was more prevalent during the flowering–podding stage than at the podding or grain-filling stages. (2) High temperature profoundly affected soybean yield components, primarily through a decrease in the number of grains per plant during the flowering–podding stage, subsequently impacting the grain weight per plant and yield. In years with extremely high temperatures, the soybean plant height was reduced by 6.1 to 15 cm, the main stem node number decreased by 0.1 to 2.9, the branch number decreased by 0.2 to 0.6, the number of pods per plant decreased by 4.8 to 13.7, the number of grains per pod decreased by 0.1 to 0.3, the number of grains per plant decreased by 13.5 to 32.6, the grain weight per plant decreased by 3.8 to 6.9 g, and the 100-grain weight decreased by 0.1 to 4.5 g. The common impact of high temperature combined with drought processes in different growth stages was reflected in the reduction in the number of branches by 0.1 to 1.4 and the reduction in the number of grains per pod by 0.02 to 13.7. This study underscores the importance of addressing the quantitative effects of climate change and extreme weather on soybean yield, which could help to develop effective adaptation and mitigation strategies. [ABSTRACT FROM AUTHOR]

Emerging research indicates that ground-level ozone (O3) has become a leading contributor to air quality concerns in many Chinese cities, with the Yangtze River Delta (YRD) region facing particular challenges. This study investigated the characterization of air pollutants in Wujiang, which is located within the YRD demonstration zone, during the warm season (April–September) of 2022. The contributions of emission and meteorology to O3 were identified, the O3-NOX-VOC sensitivities were discussed, and the VOC sources and their contributions to O3 formation were analyzed. A random forest model revealed that the high O3 concentration was mainly caused by a combination of increased emission intensity due to the resumption of work and production after the COVID-19 pandemic, along with adverse meteorological conditions. The results revealed more than 92% of the pollution days were related to O3 during the warm season, and the impact of O3 precursor emissions was slightly greater than that of the meteorological conditions. O3 formation was in the VOC-limited regime, and emission reduction strategies targeting VOCs, particularly aromatics such as toluene and xylene, have been identified as the most effective approach for mitigating O3 pollution. Changes in O3-NOX-VOC sensitivity were also observed from the VOC-limited regime to the transitional regime, which was primarily driven by variations in the NOX concentrations. The VOC source analysis results showed that the contributions of gasoline vehicle exhaust and diesel engine exhaust (mobile source emissions) were significantly greater than those of the other sources, accounting for 20.8% and 16.5% of the total VOC emissions, respectively. This study highlights the crucial role of mobile source emission control in mitigating O3 pollution. Furthermore, prioritizing the control of VOC emission sources with minimal NOX contributions is highly recommended within the VOC-limited regime. [ABSTRACT FROM AUTHOR]

Precise regional ionospheric total electron content (TEC) models play a crucial role in correcting ionospheric delays for single-frequency receivers and studying variations in the Earth's space environment. A particle swarm optimization neural network (PSO-NN)-based model for ionospheric TEC over China has been developed using a long-term (2008–2021) ground-based global positioning system (GPS), COSMIC, and Fengyun data under geomagnetic quiet conditions. In this study, a spatial gridding approach is utilized to propose an improved version of the PSO-NN model, named the PSO-NN-GRID. The root-mean-square error (RMSE) and mean absolute error (MAE) of the TECs estimated from the PSO-NN-GRID model on the test data set are 3.614 and 2.257 TECU, respectively, which are 7.5% and 5.5% smaller than those of the PSO-NN model. The improvements of the PSO-NN-GRID model over the PSO-NN model during the equinox, summer, and winter of 2015 are 0.4–22.1%, 0.1–12.8%, and 0.2–26.2%, respectively. Similarly, in 2019, the corresponding improvements are 0.5–13.6%, 0–10.1%, and 0–16.1%, respectively. The performance of the PSO-NN-GRID model is also verified under different solar activity conditions. The results reveal that the RMSEs for the TECs estimated by the PSO-NN-GRID model, with F10.7 values ranging within [0, 80), [80, 100), [100, 130), [130, 160), [160, 190), [190, 220), and [220, +), are, respectively, 1.0%, 2.8%, 4.7%, 5.5%, 10.1%, 9.1%, and 28.4% smaller than those calculated by the PSO-NN model. [ABSTRACT FROM AUTHOR]

To evaluate the impact of different momentum control variable (CV) schemes (CV5, the momentum control variable option with ψχ and CV7, the momentum control variable option with UV) on radar data assimilation (DA) in weather research and forecasting model data-assimilation (WRFDA) systems, a heavy snowfall in central and eastern regions of China, which started on 6 February 2022, was taken as a case in this study. The results of the wind-field increments from the single observation tests indicated that the wind-field increments had a larger range of influence when stream function and velocity potential (ψχ) were used as momentum control variables in CV5. Some spurious increments were also generated in the wind-field analysis, since CV5 tended to maintain the integrated value of the wind field. When U-wind and V-wind were used as control variables in CV7, the wind-field increments had a smaller impact range, and there was less dependence among different locations on the wind increments. For the heavy snow case, the CV7 schemes displayed some improvements in simulating the composite reflectivity compared to the other two experiments, since the composite reflectivity in the CV5 and control experiments were overestimated to some level. It was also found that the RMSEs were lower in the CV7 compared to those in the CV5 in the short-term forecasts during the data-assimilation cycles. Results also indicated that the CV7 had a more significant effect on the 6 h accumulated precipitation forecasts. Meanwhile, the experiment Exp_CV7 achieved the best ETS and FSS scores among the three groups of experiments, while Exp_CV5 appeared to be generally superior to the CTRL. In summary, the precipitation of Exp_CV7 yielded the rainfall intensity and location most close to the observation compared to those from both the CTRL and Exp_CV5 experiments. [ABSTRACT FROM AUTHOR]

Based on the 24 meteorological stations in the Weihe River Basin (WRB) from 1951 to 2013, as well as the runoff data from the mainstream of the Weihe River, the temporal and spatial variations in water balance in the WRB and its relationships with runoff, the drought index, and the climate index were analyzed. The results indicate that the water balance in the WRB has been in a deficit state over the past 63 years, showing a weak declining trend with a decreasing rate of −20.04 mm/decade. Water balance is closely related to potential evapotranspiration (ET0) and precipitation (P). At the annual time scale, P plays a dominant role in water balance for 6–8 months in the WRB. The distribution of the water deficit (WD) in the WRB is uneven throughout the year, with the largest deficit occurring in June and the smallest values generally occurring in September. Furthermore, there are significant multi-scale correlations between water deficit and climate indices such as Arctic Oscillation (AO), Pacific Decadal Oscillation (PDO), and Sea Surface Temperature (SST) in the WRB. In addition, water deficit is also influenced by human activities, such as irrigation, as well as climate factors and socio-economic factors. Studying the temporal and spatial variation characteristics of water deficit and its influencing factors in the WRB is helpful toward deeply understanding the supply and demand dynamics of water resources in the basin and providing a theoretical basis and scientific guidance for the rational utilization of water resources and the high-quality development of the basin. [ABSTRACT FROM AUTHOR]

An extreme high-temperature event occurred in North China on 22 June 2023, with the maximum temperature reaching 41.8 °C. The high-temperature centers preferentially occurred at the foothills of the Taihang and Yanshan Mountains, indicating an important role of the underlying orography. In the present work, we study the orographic effects of this extreme high-temperature event according to high-resolution numerical simulations using the Weather Research and Forecasting model. The results show that the presence of the mountains in North China contributed notably to the high-temperature event, which can enhance the 2 m air temperature by up to 3 °C. In the daytime, the enhancement of temperature is primarily due to the diabatic heating of sensible heat flux at the terrain surface caused by solar shortwave radiation, whereas the well-known foehn effect has little contribution. Indeed, the dynamically forced downslope flow of foehn is totally suppressed by the upslope flow of the thermally driven mountain-plain circulation. In the nighttime, the sensible heat flux at the terrain surface changes to weakly negative, given the cooling of land surface longwave radiation. As a result, the enhancement of near-surface temperature at the terrain foothill is dominated by the adiabatic warming of downslope flow. Yet, the near-surface temperature far away from the mountain is enhanced by the subsidence warming of a synoptic anomalous anti-cyclone, which is induced by the diabatic heating over the mountains in the daytime. These findings help improve the understanding of the thermal and dynamical effects of orography on the occurrence of high-temperature events. [ABSTRACT FROM AUTHOR]