Spatial-temporal Variations Research Articles

Spatial-temporal variations of cultivated land compensation and its compensation mechanism in mainland China

Cultivated land compensation can alleviate the conflict between cultivated land protection and socio-economic development. Exploring the spatial-temporal trends of cultivated land compensation, and formulating a scientific and reasonable compensation mechanism are important to achieve sustainable development. To analyze the spatial-temporal changes of the area, comprehensive non-market value, and compensation amount of cultivated land in mainland China, this paper constructed a comprehensive non-market value evaluation framework including positive ecological, negative ecological, and social values, and designed a feasible cultivated land compensation model. In terms of cultivated land area, the cultivated land area indicated an overall surplus condition, and the total net surplus area during 2000–2021 was 54.4 million hectares per year. On a spatial scale, the net surplus districts were concentrated in the north and the center of China, while the net deficit districts were in the developed areas along the southeast coast. In terms of comprehensive non-market value, except for negative ecological value, all other non-market values had increased. On a spatial scale, the coupling relationship between comprehensive non-market value and regional economic development was obvious, presenting a higher value observed in the southeastern coastal developed provinces, and a lower one in the developing inland provinces. In terms of compensation amount, the total payment amount of the payment districts was difficult to cover the total compensation amount of the compensated districts, a certain compensation gap between the two appeared, averaging 6.03 trillion RMB during 2000–2021. On a spatial scale, the payment districts were mainly distributed in the southeastern coastal area, and the number of the payment districts was smaller than that of the compensated area. It is suggested that we should clarify the subject of cultivated land compensation and identify its rights and responsibilities, highlight the leading role of the central government and give full play to the main role of all levels of government, adopt diversified market financing instruments according to local conditions, and formulate relevant supporting security systems.

Variations of phosphorus in sediments and suspended particulate matter of a typical mesotrophic plateau lake and their contribution to eutrophication

Internal phosphorus loading (IPL), as an important part of lake phosphorus cycle and the key to solve the eutrophication problem, is still an important cause of regional and seasonal algal blooms for some mesotrophic lakes located in plateau areas. We investigated the composition, distribution of P fractions in sediments and suspended particulate matter (SPM) of Erhai Lake, southwest China, and explored the relationships between environmental variables and spatial-temporal variations of P fractions. The total P (TP) in surface sediments ranged from 817 to 1216 mg/kg, with inert Ca-P (32%) and Res-P (24%) predominating, at a moderate level. The comparison of short-term release fluxes (0.08 mg/(m2·d)) and long-term release fluxes (0.09 mg/(m2·d)) reflected that the northern region was recovering slowly from the previous P pollution. Mobile-P (the sum of loosely adsorbed P, iron bound P, and organic P) accounted for 52.3% of the TP in SPM and showed high spatial-temporal variations, which were closely related to the growth of algae throughout the investigation. The results suggested that sediments could make a sustained contribution to IPL, and that the P in SPM was highly active and significantly contributed to eutrophication in Erhai Lake especially at the time of seasonal alternations. Our data provided important theoretical bases for the relationship between internal phosphorus loading and eutrophication in plateau lakes.

Machine learning-based modelling of zenith wet delay using terrestrial meteorological data in the Brazilian territory

Abstract. The Zenith Total Delay (ZTD) is one of the primary error sources derived from the neutral atmosphere associated with the GNSS (Global Navigation Satellite Systems) technique. Zenith Wet Delay (ZWD) is the smallest part of the ZTD, but the high variability is caused by spatial-temporal variation, making the modelling of this component a challenging task. Although ZWD is considered an error in GNSS positioning, it is also a variable composed mainly of water vapour and can, therefore, be used for atmospheric investigations, and assists in climate studies for precipitation events. In this work, a model was trained to estimate the delay wet component from surface atmospheric parameters. The training data comes from 29 radiosonde stations around Brazil, for a six-year period (2017 to 2022), with data collected at 12 h UTC (Universal Time Coordinated). The model was validated using the holdout technique, with 70% of the data used in training and 30% for validation (cross-validation analysis). The generated model achieved a RMSE (Root Mean Squared Error) of approximately 38 mm, with an 81% of determination coefficient.

Investigating spatial and temporal characteristics and elements influencing running among residents of Nanchang city in green open areas

Understanding the exercise behaviors of urban residents in green open spaces is crucial for optimizing future urban spatial planning and improving residents’ quality of life. This study provides an in-depth analysis of residents’ running behaviors across 87 green open spaces in Nanchang City. Running data collected from the exercise platform Keep, coupled with urban geographic data and field research, reveals the spatial distribution and temporal variations of running activities, including running flow, distance, time, and pace. A set of indicator systems, such as total area, landscape form index, surrounding residential land area, and road conditions, is used to analyze its relationship with the environmental elements of green open spaces. The research results show that the running flow, running distance, and running time in green open spaces in Nanchang City are significantly influenced by different objective elements, while running pace shows little correlation with these environmental elements. Specifically, the study highlights the significant impact of elements such as total area and road length, as well as the number of nearby bus stops and population density, on residents’ running behaviors in Nanchang City’s green open spaces.

Influence of Model Resolution on Wind Energy Simulations over Tibetan Plateau Using CMIP6 HighResMIP

The assessment of wind energy resources is critical for the transition from fossil fuel to renewable energy sources. Using the outputs from high-resolution global climate models (GCMs), such as the High Resolution Model Intercomparison Project (HighResMIP) of the Coupled Model Intercomparison Project Phase 6 (CMIP6), has become one of the most important tools in wind energy research. This study evaluated the reliability of the 22 GCMs available in the HighResMIP-PRIMAVERA project by simulating the wind energy climatology and variability over the Tibetan Plateau (TP) with reference to observations and investigated the differences in performance of the GCMs between high-resolution (HR) and low-resolution (LR) simulations. The results show that most models performed relatively well in simulating the probability distribution of the observed wind speed over the TP, but nearly half of the models generally underestimated the wind speed, whereas the others tended to overestimated the wind speed. Compared with the wind speed, the GCMs showed larger biases in reproducing the wind power density (WPD) and other wind energy resources, whereas the biases in multi-model ensembles were relatively smaller than those in most individual models. With respect to interannual variability, both the HR and LR models failed to capture interannual variations in WPD over the TP. Furthermore, more than half of the HR GCMs had a reduced bias relative to the corresponding LR GCMs, indicating the good performance of most HR models in simulating wind energy resources over the TP in terms of spatial pattern and temporal variability. However, the overall performance of HR GCMs varied among models, which suggests that solely improving the horizontal resolution is not sufficient to completely solve the uncertainties and deficiencies in the simulation of wind energy over complex terrain.

Greater plasticity in CTmax with increased climate variability among populations of tailed frogs.

Temporally variable climates are expected to drive the evolution of thermal physiological traits that enable performance across a wider range of temperatures (i.e. climate variability hypothesis, CVH). Spatial thermal variability, however, may mediate this relationship by providing ectotherms with the opportunity to behaviourally select preferred temperatures (i.e. the Bogert effect). These antagonistic forces on thermal physiological traits may explain the mixed support for the CVH within species despite strong support among species at larger geographical scales. Here, we test the CVH as it relates to plasticity in physiological upper thermal limits (critical thermal maximum-CTmax) among populations of coastal tailed frogs (Ascaphus truei). We targeted populations that inhabit spatially homogeneous environments, reducing the potentially confounding effects of behavioural thermoregulation. We found that populations experiencing greater temporal thermal variability exhibited greater plasticity in CTmax, supporting the CVH. Interestingly, we identified only one site with spatial temperature variability and tadpoles from this site demonstrated greater plasticity than expected, suggesting the opportunity for behavioural thermoregulation can reduce support for the CVH. Overall, our results demonstrate one role of climate variability in shaping thermal plasticity among populations and provide a baseline understanding of the impact of the CVH in spatially homogeneous thermal landscapes.

Temporal and Spatial Variations in Microplastic Concentrations in Small Headwater Basins in the Southern Blue Ridge Mountains, North Carolina, USA

Microplastics (MPs) are ubiquitous contaminants of emerging concern that require additional study in freshwater streams. We examined the spatial-temporal variations in MP concentrations and characteristics within two headwater basins in the Southern Appalachian Mountains of western North Carolina over ~1 year. Atmospheric samples were also collected to determine the significance of atmospheric MP deposition to these relatively small streams. MP concentrations in both basins were within the upper quartile of those reported globally, reaching maximum values of 65.1 MPs/L. Approximately 90% of MPs were fibers. MP composition was dominated by polystyrene, polyamides, and polyethylene terephthalate. Spatially, concentrations were highly variable and increased with development, indicating anthropogenic inputs from urbanized areas. MP concentrations were also elevated in forested tributary subbasins with limited anthropogenic activity, suggesting atmospheric deposition was an important MPs source. Significant atmospheric inputs are supported by high atmospheric depositional rates (ranging between 7.6 and 449.8 MPs/m2/day across our study sites) and similarities in morphology, color, and composition between atmospheric and water samples. Temporally, MP concentrations during storm events increased, decreased, or remained the same in comparison to base flows, depending on the site. The observed spatial and temporal variations in concentrations appear to be related to the complex interplay between precipitation and runoff intensities, channel transport characteristics, and MP source locations and contributions.

Spatial-temporal variations and Attribution analysis of SO2 concentration in Beijing-Tianjin-Hebei regions from 2013 to 2022

Based on the monitoring data of air pollutants in Beijing-Tianjin-Hebei regions from 2012 to 2022, the spatial-temporal distribution of SO2 concentration and main influencing factors were analyzed through multi-methods of Daniel trend test, KZ filtering and WRF/CMAQ model simulations. From 2013 to 2022, the annual averaged concentrations of SO2 in Beijing, Tianjin and Hebei regions were all in obvious downward trends, and all passed the Daniel trend test (α=0.01). The annual averaged concentration of SO2 in Beijing, Tianjin and Hebei regions decreased from 26.6~114.3μg·m-3 in 2013 to 3.0~11.0μg·m-3, with the decline rates fluctuating from 2.62~11.81μg/(m3·yr) while the decrease rate of SO2 in Beijing was the lowest. The average annual concentration of SO2 in Tangshan city decreased the most, reaching 92.3% and it changed to be the smallest, about 78.2% in Chengde City. The reduction of coal consumption in the Beijing-Tianjin-Hebei regions significantly reduced atmospheric SO2 emissions and directly reduced the regional average concentration of SO2. Meteorological factors were generally conducive to the diffusion of SO2 concentration during 2013~2022, and the meteorological factors contributed about 0.4~5.5% in 13 cities in Jingjinji area while the contribution of anthropogenic emission reduction was 94.5~99.6%. The inter-annual variation of meteorological factors in summer from 2013 to 2022 was not conducive to the diffusion of SO2 concentration on the whole, and the contribution changed to -52.6 ~ -1.0% in 13 cities. From June to August in summer under the easterly and southerly winds, the SO2 concentration in Beijing was basically twice that of the northerly and westerly winds. The contribution of southwest transport channel to SO2 concentration in Beijing was 33.5%, while it changed to 38.9% in the southeast transport channel. Therefore, strengthening the management and control of air pollutants in surrounding area of Beijing is helpful for Beijing to further reduce the levels of air pollutants and achieve targets of air quality improvement in the 14th Five-Year Plan period.

Spatial–Temporal Variation and the Influencing Factors of NO2 Column Concentration in the Plateau Mountains of Southwest China

Given the complex terrain and economic development status of Guizhou Province, research on tropospheric NO2 column concentration using satellite remote sensing is still insufficient. Observing the spatial–temporal evolution characteristics of tropospheric NO2 column concentration can ensure the stable development of air quality. Based on the Google Earth Engine (GEE) platform, NO2 column concentration data retrieved from Sentinel-5P TROPOMI were analyzed using spatial autocorrelation, hotspot analysis, and geographic detector methods (Geodetector). The results show that NO2 column concentration in Guizhou Province exhibits seasonal variation, characterized by higher levels in winter and lower levels in summer, with transitional values in spring and autumn. The annual average concentration was highest in 2021 at 3.47 × 10−5 mol/m2 and lowest in 2022 at 2.85 × 10−5 mol/m2. Spatially, NO2 column concentration displays a distribution pattern of “high in the west, low in the east; high in the north, low in the south”, with significant spatial clustering. The distribution of cold and hot spots aligns with areas of high and low values. NO2 column concentration is primarily influenced by socio-economic factors, with the interaction between any two factors enhancing the explanatory power of individual factors on NO2 column concentration.

Study on Spatiotemporal Characteristics and Influencing Factors of High-Resolution Single-Season Rice

Single-season rice describes the area under rice cultivation from May–October of the year. Many scholars have used lower-resolution data to study single-season rice in different regions, but using high-precision and high-resolution single-season rice data can reveal new phenomena. This paper uses a long-time-series, high-precision, and high-resolution single-season rice cultivation dataset to conduct an in-depth analysis of the spatial–temporal variability characteristics of single-season rice in Jiangsu Province, China, from 2017 to 2021. It explores the correlation between meteorological factors and greenhouse gasses for single-season rice. It analyzes the driving role of social factors on single-season rice. The results showed that single-season rice was mainly grown in the central and northeastern regions of the study area. The single-season rice cultivation was significantly reduced in 2020 due to the impact of COVID-19. Single-season rice strongly correlates with meteorological factors in time but shows a weak spatial correlation. This is because human factors largely dominate the area under single-season rice cultivation. Methane emissions in the study area are mainly influenced by anthropogenic activities rather than single-season rice. Social factors are essential in controlling single-season rice cultivation in the study area. This study was conducted in Jiangsu Province, China. Still, the methodology and results have important implications for agricultural production and environmental management studies in other regions, and some findings have general applicability.

The impact of cryosphere service change on the social-ecological systems resilience: Evidence from the Qilian Mountains Area in China

Research on changes in cryosphere services is crucial for the responsible management of cryospheric resources and for fostering sustainable development in Social-Ecological Systems (SESs) impacted by the cryosphere. While previous research has primarily focused on quantifying cryospheric change through Cryosphere Service Value (CSV), the impact of cryosphere service change on Social-Ecological Systems Resilience (SESR) remains unclear. This study considers the Qilian Mountains as a cryosphere system and assesses the changes in its service value from 2000 to 2020. It also establishes a framework to analyze the spatial-temporal variations in resilience within the Qilian Mountains Area in China (QMAC) and investigates the impact of changes in cryosphere services on SESR. The findings indicate that (1) the CSV exhibited a decreasing trend followed by an increase from 2000 to 2020, with minor increases observed in the three northern inland river basins and substantial increases in other areas; (2) the resilience in QMAC improved consistently, establishing a spatial pattern characterized by higher resilience in the west and lower resilience in the east, as well as higher resilience in the north and lower resilience in the south; (3) the effects of changes in cryosphere services on SESR demonstrate significant spatial-temporal patterns, the decline in climate regulation service has a notably negative impact on ecological resilience, while the increase in value from aesthetic appreciation and tourism service positively boosts economic resilience; and (4) changes in cryosphere services affect social resilience by influencing residents’ livelihoods, with more pronounced effects on SESs in areas with high land use intensity. This research provides a research avenue for examining how cryosphere service change impacts SESR and offers practical experience for promoting the stability of SESs and developing sustainable development policies in regions affected by the global high-mountain cryosphere amid climate change.

Aerosol particle number concentration, ultrafine particle number fraction, and new particle formation measurements near the international airports in Berlin, Germany – First results from the BEAR study

Studies revealed airports as a prominent source of ultrafine particles (UFP), which can disperse downwind to residential areas, raising health concerns. To expand our understanding of how air traffic-related emissions influence total particle number concentration (PNC) in the airport’s surrounding areas, we conduct long-term assessment of airborne particulate exposure before and after relocation of air traffic from “Otto Lilienthal” Airport (TXL) to Berlin Brandenburg Airport “Willy Brandt” (BER) in Berlin, Germany. Here, we provide insights into the spatial–temporal variability of PNC measured in 16 schools recruited for Berlin-Brandenburg Air Study (BEAR).The results show that the average PNC in Berlin was 7900 ± 7000 cm−3, consistent with other European cities. The highest median PNC was recorded in spring (6700 cm−3) and the lowest in winter (5100 cm−3). PNC showed a bi-modal increase during morning and evening hours at most measurement sites due to road-traffic emissions. A comparison between measurements at the schools and fixed monitoring sites revealed good agreement at distances up to 5 km. A noticeable decline in this agreement occurred as the distance between measurement sites increased. After TXL was closed, PNC in surrounding areas decreased by 30 %. The opposite trend was not seen after BER was re-opened after the COVID-lock-down, as the air traffic has not reached the full capacity yet. The analysis of particle number size distribution data showed that UFP number fraction exhibit seasonal variations, with higher values in spring and autumn. This can be explained by nucleation events, which notably affected PNC.The presented findings will play a pivotal role in forthcoming source attribution and epidemiological investigations, offering a holistic understanding of airports’ impact on airborne pollutant levels and their health implications. The study calls for further investigations of air-traffic-related physical–chemical pollutant properties in areas found further away (> 10 km) from airports.

Quantitative identification of moisture sources over the Tibetan Plateau: spatial distributions and temporal variabilities

Abstract The imbalanced hydrological cycles and water resource instability over the Tibetan Plateau (TP) are a topic of wide concern. Moisture sources affected by large-scale circulations are the main controls of precipitation and water resource distributions; as such, the quantitative identification of moisture sources is key to the changes in precipitation or water-related environments, further aids efficient water management over the TP and in downstream regions of Asia. In this study we primarily identified the spatial distributions and temporal variabilities of TP’s varied moisture sources, using Hysplit modeling and spatially dense precipitation isotopes (δ18O). Results showed that: (1) moistures from the Westerlies (West), the western arm of Indian Summer Monsoon (ISM) (ISM1), the eastern arm of ISM (ISM2), and the inner TP are the TP’s main moisture sources, with highest proportional contributions being >70%, ~40%, >80%, and ~10–20% at northwest, southwest, southeast sectors of the study area, and the central TP region; (2) each moisture has its own region where it predominates, and shows specific trends during 1951–2020 (West-northwest sector-increase, ISM1-southwest sector-increase, ISM2-southeast sector-decrease, TP-central TP region-increase); (3) each of the moisture proportions and their temporal trends varied with different days of back trajectories (days 02-04-06-08-10), while their spatial patterns are similar; and (4) when verifying the modeled moisture proportions, precipitation δ18O is positively correlated or co-vary with dry sources such as the West or TP moisture, and inversely for humid ISM (ISM1 or ISM2) moisture. This work will improve our understanding of moisture-related hydrological, meteorological, and ecological studies in the ‘Asian Water Tower’ region.

Spatiotemporal Analysis of Open Biomass Burning in Guangxi Province, China, from 2012 to 2023 Based on VIIRS

Open biomass burning has significant adverse effects on regional air quality, climate change, and human health. Extensive open biomass burning is detected in most regions of China, and capturing the characteristics of open biomass burning and understanding its influencing factors are important prerequisites for regulating open biomass burning. The characteristics of open biomass burning have been widely investigated at the national scale, with regional studies often focusing on northeast China, but few studies have examined regional discrepancies in spatiotemporal variations over a long timescale in Guangxi province. In this study, we used the Visible Infrared Imaging Radiometer Suite (VIIRS) 375 m active fire product (VNP14IMG), combined with land cover data and high-resolution remote sensing images, to extract open biomass burning (crop residue burning and forest fire) fire points in Guangxi province from 2012 to 2023. We explored the spatial density distribution and temporal variation of open biomass burning using spatial analysis methods and statistical methods, respectively. Furthermore, we analyzed the driving forces of open biomass burning in Guangxi province from natural (topography, climate, and plant schedule), policy, and social (crop production and cultural customs) perspectives. The results show that open biomass burning is concentrated in the central, eastern, and southern parts of the study area, where there are frequent agricultural activities and abundant forests. At the city level, the highest numbers of fire points were found in Baise, Yulin, Wuzhou, and Nanning. The open biomass burning fire points exhibited large annual variation, with high levels from 2013 to 2015 and a remarkable decrease from 2016 to 2020 under strict control measures; however, inconsistent enforcement led to a significant rebound in fire points from 2021 to 2023. Forest fires are the predominant type of open biomass burning in the region, with forest fires and crop residue burning accounting for 76.82% and 23.18% of the total, respectively. The peak period for crop residue burning occurs in the winter, influenced mainly by topography, planting schedules, crop production, and policies, while forest fires predominantly occur in the winter and spring, primarily influenced by topography, climate, and cultural customs. The results indicate that identifying the driving forces behind spatiotemporal variations is essential for the effective management of open biomass burning.

The spatial-temporal variations and influencing factors of COVID-19 case fatality rate: a worldwide study in 30 countries from February 2021 to May 2022.

To evaluate the variations in COVID-19 case fatality rates (CFRs) across different regions and waves, and the impact of public health interventions, social and economic characteristics, and demographic factors on COVID-19 CFRs, we collected data from 30 countries with the highest incidence rate in three waves. We summarized the CFRs of different countries and continents in each wave through meta-analysis. Spearman's correlation and multiple linear regression were employed to estimate the correlation between influencing factors and reduction rates of CFRs. Significant differences in CFRs were observed among different regions during the three waves (P<0.001). An association was found between the changes in fully vaccinated rates (r s =0.41), population density (r s =0.43), the proportion of individuals over 65years old (r s =0.43), and the reduction rates of case fatality rate. Compared to Wave 1, the reduction rates in Wave 2 were associated with population density (β=0.19, 95%CI: 0.05-0.33) and smoking rates (β=-4.66, 95%CI: -8.98 - -0.33), while in Wave 3 it was associated with booster vaccine rates (β=0.60, 95%CI: 0.11-1.09) and hospital beds per thousand people (β=4.15, 95%CI: 1.41-6.89). These findings suggest that the COVID-19 CFRs varied across different countries and waves, and promoting booster vaccinations, increasing hospital bed capacity, and implementing tobacco control measures can help reduce CFRs.

Evaluating the spatiotemporal patterns of drought characteristics in a semi‐arid region of Limpopo Province, South Africa

Drought is a complex phenomenon resulting from below-average rainfall and is characterized by frequency, duration, and severity, occurring at a regional scale with dire consequences, especially in semiarid environments. This study used the Reconnaissance Drought Index (RDI) to assess drought severity in two district municipalities in Limpopo Province. Rainfall and air temperature data from 12 stations covering 1970–2020 were obtained from the Agricultural Research Council. The calculation of RDI relies on the monthly accumulation ratio of total rainfall to potential evapotranspiration (PET). For this study, PET was estimated using the Hargreaves and Samani temperature-based approach. The RDI results showed a high spatial–temporal variation in drought characteristics over the study area. All stations experienced extreme drought conditions in different years, with the maximum drought severity (-3.40) occurring from 2002–2003 in the western parts of the study area, indicating extreme drought. Furthermore, the results revealed continuous drought conditions over various periods, including severe droughts between 1995 and 1998 and between 2014 and 2016, with the severity varying between mild and moderate drought conditions. The results reveal notable but nonuniform drought patterns as the climate evolves, with potential implications for water availability and livelihoods. The study's findings underscore the significance of adopting multidimensional approaches to drought assessment that encompass meteorological and hydrological factors to inform strategies for adaptive water management and policy formulation in the face of a changing climate.

Spatial–Temporal Variations in Water Use Efficiency and Its Influencing Factors in the Li River Basin, China

As a vital indicator for measuring the coupled carbon–water cycle of an ecosystem, water use efficiency (WUE) can also reflect the adaptive capacity of plants in different ecosystems. Located in Southwest China, the Li River Basin has a representative karst landform, and the uneven rainfall in the region leads to severe water shortage. In this study, we analyzed the spatial–temporal transformation characteristics of the WUE of the basin and its relationship with different influencing factors from 2001 to 2020 based on a correlation analysis and trend analysis. The main conclusions are as follows: (1) The average value of WUE in the Li River Basin was 1.8251 gC· mm−1·m−2, and it kept decreasing at a rate of 0.0072 gC· mm−1·m−2·a−1 in the past 20 years. With respect to the spatial distribution of the multi-year average of WUE, it exhibits a gradual increasing trend from west to east. (2) Between gross primary productivity (GPP) and evapotranspiration (ET), it was found that ET was the primary influencing factor of WUE. Precipitation was positively correlated with WUE in the Li River Basin, accounting for 67.22% of the total area of the basin. The air temperature was negatively correlated with WUE, and the area was negatively correlated with WUE, accounting for 92.67% of the basin area. (3) The normalized difference vegetation index (NDVI) and leaf area index (LAI) were negatively correlated with WUE, and the proportions of negatively correlated areas to the total area of the basin were similar; both were between 60 and 70%. The growth of vegetation inhibited the increase in WUE in the basin to a certain extent. Regarding Vapor Pressure Deficit (VPD), the proportions of positive and negative correlation areas with WUE were similar, accounting for 49.58% and 50.42%, respectively. (4) The occurrence of drought events and the enhancement in its degree led to a continuous increase in WUE in the basin; for different land cover types, the correlation of the standardized precipitation evapotranspiration index (SPEI) was in the following order from strongest to weakest: grassland &gt; cropland &gt; forest &gt; shrubland.

A New NDSA (Normalized Differential Spectral Attenuation) Measurement Campaign for Estimating Water Vapor Along a Radio Link

The Normalized Differential Spectral Attenuation (NDSA) technique was proposed years ago as an active method for measuring integrated water vapor (IWV) along a Ku/K-band radio link immersed (totally or partially) in the troposphere. The approach is of the active kind, as it relies on the transmission of a couple of sinusoidal signals, whose power is measured at the receiver, thus providing the differential attenuation measurements from which IWV estimates can be in turn derived. In 2018, a prototype instrument providing such differential attenuation measurements was completed and set up for a first measurement campaign aimed at demonstrating the NDSA method. By the end of June 2022, the instrument was profoundly modified and upgraded so that a second measurement campaign could be carried out from 1 August to 30 November 2022. The transmitter was placed on the top of Monte Gomito (44.1277°lat, 10.6434°lon, 1892 m a.s.l.) and the receiver on the roof of the Department of Information Engineering of the University of Florence (43.7985°lat, 11.2528°lon, 50 m a.s.l.). The resulting radio link length was 61.15 km. Four ground weather stations of the regional weather service were selected among those available. In this paper, we describe the upgraded instrument and present the outcomes of the new measurement campaign, whose purpose was mainly to compare the IWV estimates provided by the instrument with the ground sensor measurements of air temperature, air humidity, barometric pressure, and rainfall. In particular, we show that the temporal trends of the two IWV estimates are qualitatively consistent, and that the instrument is able to provide IWV estimates also in the presence of fog and rainfall. Conversely, a quantitative evaluation through comparison with IWV data from point weather station measurements appears challenging due to the significant spatial variability in temperature and relative humidity, even between couples of stations that are quite close to each other.

Validation and Spatial–Temporal Variability of Particulate Matter in Urban area Using WRF-Chem with Local and Global Emission Inventories

Validation and Spatial–Temporal Variability of Particulate Matter in Urban area Using WRF-Chem with Local and Global Emission Inventories

Mitigating Intermittent Connectivity Problems in Vehicle-to-Vehicle Communication (V2VC): A Sparse Network Computational Model (SNCM)

INTRODUCTION: Wireless communication has made remarkable progress, by the rapid development of wireless technology in Artificial Intelligence (AI). Intelligent Transportation Systems (ITS), and Vehicular Ad Hoc Networks (VANETs) have received significant attention to ensure safety. However, V2V communication in VANETs faces uncontrollable challenges due to frequent intermittent connectivity issues in infrastructure-less networks. Addressing these problems in both safety and non-safety applications is a complex task.OBJECTIVES: To mitigate the intermittent connectivity problems, a novel Sparse Network Computational Model (SNCM) was proposed.METHODS: Extensive simulations using MATLAB to analyze the impact of spatial-temporal variations under different traffic flow densities. We varied the sensitivity factor (λ) at different time intervals while maintaining a constant traffic density. RESULTS: The findings indicate that there is no need to increase λ beyond certain thresholds for each level of service. The simulation results provide valuable guidelines for designing sparse networks, effectively mitigating frequent intermittent disconnections. Simulation experiments revealed an optimal threshold for the sensitivity factor λ for each level of service. Increasing λ beyond certain thresholds did not yield significant improvements in mitigating disconnections in V2V communication.CONCLUSION: The results provide valuable insights and guidelines for designing sparse networks to enhance connectivity and address intermittent disconnection issues. This paper presents a groundbreaking endeavor, and therefore, direct comparisons with existing protocols to evaluate its overall performance are beyond the scope of this paper. Instead, the SNCM protocol is intended to set a standard for future researchers to benchmark their research contributions against.