Changes In Meteorological Factors Research Articles

Epidemiological study of the relationship between meteorological factors and onset of acute aortic dissection in Japan.

Several factors influence the onset of acute aortic dissection (AAD). However, few studies have examined AAD onset, weather conditions, and meteorological factors in Japan. This study aimed to identify meteorological factors associated with the onset of AAD in Japan. In this self-controlled study, patients diagnosed with AAD onset from May 1, 2012, to April 30, 2021, at Shizuoka City Shizuoka Hospital (Shizuoka, Japan) were included. Meteorological data from the Shizuoka District Meteorological Office were used. Control days were randomly selected from a 29-day period centered on the day of onset. Conditional logistic regression models were used to obtain odds ratios (ORs) and 95% confidence intervals (CIs) for the onset of AAD relative to the control day due to changes in meteorological factors. In total, 538 patients were included. The meteorological factors associated with the onset of AAD were identified as the daily mean temperature (OR = 1.10; 95% CI = 1.04-1.16), daily minimum temperature (OR = 1.09; 95% CI = 1.03-1.14), daily maximum temperature (OR = 1.05; 95% CI = 1.00-1.10), and the mean of the daily mean temperatures for the previous 7 days (OR = 1.17; 95% CI = 1.07-1.28) with a 1°C decrease in the temperature. The results of this study are expected to help raise awareness in clinical practice and among the general public about the increased risk of AAD associated with a drop in temperature.

Prediction of Temperature Variability on Power Transmission Line Parameters using Intelligent Approaches

Due to changes in meteorological factors, the instability in the power at the end of the transmission system demands considerable attention. The temperature of the transmission line varies, which has a significant impact on the line parameters. An accurate prediction of line parameters behaviour is necessary to ensure system reliability. The present study is a step towards predicting variations in line parameters with respect to temperature variation. In addition, power loss and voltage drop due to variations in resistance are also predicted. Support Vector Machine (SVM) and ElasticNet, a machine learning algorithm, predict line parameters such as resistance, inductance, capacitance, voltage drop, and power losses. Furthermore, different seasons-based SVM and ElasticNet models for these parameters are considered. Seasons-based models are divided into two types, namely, summer and winter. 220-Kilovolt transmission data and weather information are used as model inputs. Predicted results of transmission line parameters are described in the form of RMSE and MRE. Moreover, the performance results of SVM and ElasticNet are also compared to show better prediction results. The result shows that the minimum prediction error of line parameters are 0.0511, 0.301, 0.426, 0.913, and 0.1501 in RMSE and 4.212, 0.518, 2.888, 0.097, and 0.615 percentages in MRE. This research work may provide technical guidance to transmission line engineers on enhancing the performance of transmission systems.

Climate and Kidney Injury: A Look at the Impact of Meteorological Factors on Kidney Function within Colorado

Abstract Acute kidney injury (AKI) and chronic kidney disease (CKD) are serious health conditions with an enormous global health burden. There is evidence to suggest that CKD rates are increasing within the United States despite declines in traditional risk factors for kidney injury and disease, disproportionately impacting certain populations. Changes in meteorological factors because of climate change may be partially responsible for this increase in kidney injury. This study evaluated the association between AKI and meteorological factors controlling for demographic and health factors among adults within the San Luis Valley, Colorado, a rural, biethnic agrarian community at increased risk for health impacts from climate change, over a 15-yr period. Relative humidity was a significant predictor of AKI controlling for age, sex, history of hypertension, and history of diabetes. Changing weather patterns may increase the risk of AKI and the subsequent development of CKD within the United States. These findings may help public health practitioners and medical professionals to identify populations at risk of incurring acute or chronic kidney injury as seasonal weather patterns change. Further research should investigate the role of heat, heat stress, and dehydration in developing CKD in the United States.

Comparison of Air Pollutants during the Two COVID-19 Lockdown Periods in Winter 2019 and Spring 2022 in Shanghai, China

During the winter of 2019, the global outbreak of COVID-19 prompted extensive research on urban air pollution under lockdown measures. However, these studies predominantly focused on winter conditions, thereby limiting investigations into changes in urban air pollutants during other seasons that were also subject to lockdown restrictions. Shanghai, China, has undergone two COVID-19 lockdown periods in two seasons: winter 2019 and spring 2022. The seasonal variations and human activities were represented by meteorological factors and nighttime light brightness in this paper, respectively. The reduction in human-related emissions during the two lockdown periods was estimated based on the targets outlined in China’s Air Pollution Prevention and Control Action Plan. The results showed significant reductions in NO2 and PM particles during the two lockdown periods, both accompanied by a notable increase in O3 concentration. In comparison to the winter lockdown, there was an approximate 40% decrease in the NO2 and PM2.5 concentrations in the spring, while the O3 concentration exhibited an increase of 48.81%. Furthermore, due to shifting wind patterns during the two lockdowns from winter to spring, the high-pollution core areas shifted 20–25 km southeastward in the spring. The PM particles and NO2 concentrations exhibited a considerable impact from human activities, whereas the O3 concentration was affected mostly by seasonal change and interactions among air pollutants. Compared to the corresponding non-lockdown condition, the concentration of CO decreased during the winter lockdown; however, it increased during the spring lockdown. The different change in CO concentration during the two lockdown periods was found to have a lower effect on the O3 concentration than that caused by changes in meteorological factors and nitrogen oxide (NO, NO2) concentrations. In summary, the impact of COVID-19 lockdown periods on urban air pollutants was more pronounced in spring compared to winter, and the interactions among air pollutants also underwent alterations.

Regional to global distributions, trends, and drivers of biogenic volatile organic compound emission from 2001 to 2020

Abstract. Biogenic volatile organic compounds (BVOCs) are important precursors to ozone and secondary organic aerosols in the atmosphere, affecting air quality, clouds, and climate. However, the trend in BVOC emissions and driving factors for the emission changes in different geographic regions over the past 2 decades has remained unclear. Here, regional to global changes in BVOC emissions during 2001–2020 are simulated using the latest Model of Emission of Gases and Aerosols from Nature (MEGANv3.2) with the input of time-varying satellite-retrieved vegetation and reanalysis meteorology data. Comparison of model simulations with the site observations shows that the model can reasonably reproduce the magnitude of isoprene and monoterpene emission fluxes. The spatial distribution of the modeled isoprene emissions is generally comparable to the satellite retrievals. The estimated annual average global BVOC emissions are 835.4 Tg yr−1 with the emissions from isoprene, monoterpenes, sesquiterpenes, and other BVOC comprised of 347.7, 184.8, 23.3, and 279.6 Tg yr−1, respectively. We find that the decrease in global isoprene emissions (−0.07 % per year) caused by the increase in CO2 concentrations (−0.20 % per year) is stronger than that caused by changes in vegetation (−0.03 % per year) and meteorological factors (0.15 % per year). However, regional disparities are large. Isoprene emissions increase significantly in Europe, East Asia, and South Asia (0.37 % per year–0.66 % per year). Half of the increasing trend is contributed by increased leaf area index (LAI) (maximum over 0.02 m2 m−2 yr−1) and tree cover. Changes in meteorological factors contribute to another half, with elevated temperature dominating in Europe and increased soil moisture dominating in East and South Asia. In contrast, in South America and Southeast Asia, shifts in vegetation type associated with the BVOC emission capacity, which partly results from the deforestation and agricultural expansion, decrease the BVOC emission and offset nearly half of the emission increase caused by changes in meteorological factors. Overall, isoprene emission increases by 0.35 % per year and 0.25 % per year in South America and Southeast Asia, respectively. In Central Africa, a decrease in temperature dominates the negative emission trend (−0.74 % per year). Global monoterpene emissions show a significantly increasing trend (0.34 % per year, 0.6 Tg yr−1) compared to that of isoprene (−0.07 % per year, −0.2 Tg yr−1), especially in strong greening hotspots. This is mainly because the monoterpene emissions are more sensitive to changes in LAI and are not subject to the inhibition effect of CO2. The findings highlight the important roles of vegetation cover and biomass, temperature, and soil moisture in modulating the temporal variations of global BVOC emissions in the past 2 decades.

Short-Term Changes in Weather Conditions and the Risk of Acute Coronary Syndrome Hospitalization with and without ST-Segment Elevation: A Focus on Vulnerable Subgroups.

Background and Objectives: Acute coronary syndrome (ACS), a prevalent global cardiovascular disease and leading cause of mortality, is significantly correlated with meteorological factors. This study aims to analyze the impact of short-term changes in meteorological factors on the risk of ACS, both with and without ST-segment elevation, and to identify vulnerable subgroups. Materials and Methods: Daily ACS admissions and meteorological variables were collected from October 2016 to December 2021. A generalized linear model (GLM) with a Poisson distribution was employed to examine how short-term fluctuations in meteorological parameters influence ACS hospitalizations. Subgroup analyses were conducted to identify the populations most vulnerable to climate change. Results: Multiple regression analyses showed that short-term fluctuations in atmospheric pressure (≥10 mbar) and air temperature (≥5 °C) seven days prior increased the number of ACS hospitalizations by 58.7% (RR: 1.587; 95% CI: 1.501-1.679) and 55.2% (RR: 1.552; 95% CI: 1.465-1.644), respectively, notably impacting ST-segment elevation myocardial infarctions (STEMIs). The least pronounced association was observed between the daily count of ACS and the variation in relative air humidity (≥20%), resulting in an 18.4% (RR: 1.184; 95% CI: 1.091-1.286) increase in the risk of hospitalization. Subgroup analysis revealed an increased susceptibility among men and older adults to short-term variations in weather parameters. Conclusions: The findings indicate that short-term changes in weather conditions are associated with an increased risk of ACS hospitalizations, particularly STEMIs. Male and older adult patients exhibit heightened susceptibility to variations in climatic factors. Developing effective preventive strategies is imperative to alleviate the adverse consequences of these environmental risk factors.

Environmentally Induced Diseases Caused by Changes in Meteorological Factors: Diagnosis and Ways to Counteract

Environmentally Induced Diseases Caused by Changes in Meteorological Factors: Diagnosis and Ways to Counteract

Quantifying influence of rainfall events on outdoor thermal comfort in subtropical dense urban areas

Existing research on outdoor thermal comfort in urban areas focuses on meteorological factors such as temperature, relative humidity, wind speed, and radiation on sunny or cloudy days. However, climate conditions before, during, and after rainfall events can cause changes in meteorological factors in subtropical regions. Rainfall is an atmospheric condition with a large influence on thermal comfort, particularly in subtropical areas with abundant rain. Big data on temperature, relative humidity, wind speed, precipitation, and total cloud cover from the Taipei Weather Station under the Central Weather Administration from June to August each year from 2011 to 2020 were analyzed, dividing the data into categories based on precipitation. Using a k-means clustering algorithm, we quantified the relationships between meteorological factors and apparent temperature as well as physiological equivalent temperature in different rainfall scenarios. The results indicate that rainfall in the summers of subtropical oceanic climates indeed influence outdoor thermal comfort in urban areas: 37.7% of the rainfall weather patterns improved thermal comfort and 62.3% of the rainfall weather patterns reduced thermal comfort. RWP 46 represent the weather conditions that most significantly improve thermal comfort, at 1:00 PM, with a rainfall of 15 mm, there is a decrease in ΔAT by 14.4 °C and ΔPET by 22.1 °C. With the hot, humid, and rainy climate conditions in Taiwan, apparent temperature is the most accurate index of thermal comfort. KEY POLICY HIGHLIGHTS Rainfall events may affect outdoor thermal comfort in subtropical cities. Different rainfall weather patterns have different impacts on urban outdoor thermal environments. 62.3% of rainfall weather patterns resulted in worsened thermal comfort, for low and concentrated rainfall resulting in a stuffier thermal environment.

КОЛИЧЕСТВЕННАЯ ОЦЕНКА ВЛИЯНИЯ ИЗМЕНЕНИЙ КЛИМАТА НА ПРОДУКТИВНОСТЬ ЗЕРНОВОГО ПРОИЗВОДСТВА НА ЮГЕ СИБИРИ

The result of the numerical assessment of the agroclimatic potential influence on the productivity indicators of the Siberia’s grain production is presented on the basis of retrospective meteorological data (1985-2020) and the data on grain production (2007-2020). To predict the productivity of grain-producing territories, an artificial intelligence method was used: a linear cellular automaton, which allows constructing a long-term forecast (with a lead time of more than a year) based on the revealed memory depth of the bonitet time series. The results of the forecast models are confirmed by the testing of nonlinear dynamics methods: phase analysis, R/S-analysis. The error in the forecast of the climate bonitet varied within 7-16%. The proposed methodology makes it possible to obtain the grain production productivity forecasts depending on the cycle of changes in meteorological factors. These forecasts can be applied in the development of management decisions in order to increase the productivity of grain production, in particular, for organic farming and to reduce the risks associated with future climate change.

Potential Impacts of Climate Change on the Al Abila Dam in the Western Desert of Iraq

The potential impacts resulting from climate change will cause significant global problems, particularly in underdeveloped nations where the effects are felt the most. Techniques for harvesting water such as small dams provide an alternative supply of water and are adaptive solutions to deal with water scarcity in the context of future climate change. However, it is difficult to determine how rainwater harvesting (dams) may be impacted by climate change since general circulation models (GCMs), widely utilized for predicting potential future climate change scenarios, work on an extremely large scale. The primary aim of this research was to quantify the effect of climate change on water availability at the catchment scale by statistically downscaling temperature and rainfall from the GCMs. Then, using a water harvesting model, the performance of the Abila Dam in Iraq’s western desert was evaluated in both the current climate (1990–2020) and various future climate change scenarios (2020–2100). Precipitation generally decreases as the annual temperature increases. To simulate future water availability, these changes in meteorological factors were incorporated into the water harvesting model. In total, 15% or less of net storage might fulfil the whole storage capacity during the baseline period, whereas it is 10% in RCP 2.6 in 2011–2040 for future scenarios. In contrast, RCP 8.5 will be able to meet water needs at a pace of 6% in 2011–2040. The findings of this study proved that the Al Abila dam will be unable to supply the necessary water for the area surrounding the Al Abila dam in the future scenarios.

ФЕНОЛОГИЯ СОРТОВ МАЛИНЫ В УСЛОВИЯХ ЛЕСОСТЕПНОЙ ЗОНЫ БАШКОРТОСТАНА

The purpose of the study is to study the timing of the onset of phenological phases and assess the adaptive abilities of introduced raspberry varieties to changes in meteorological factors in the Cis-Ural forest-steppe zone of Bashkortostan. The results of studying the phenological phases of 11 raspberry varieties of different ripening periods are presented. The research was carried out at the Kushnarenkovskiy Breeding Center of the BNIISH UFITs RAS in 2016-2021. Observations were carried out in accordance with the "Program and methodology for the study of variety of fruit, berry and nut crops". It has been established that the timing and duration of the passage of the phenological phases of raspberries are significantly affected by weather conditions. It is noted that all studied varieties show low resistance to return frosts. The beginning of vegetation in the studied varieties, on average, was noted in the first decade of May. Raspberry blossom took place from 6 to 17 June. The ripening of raspberries began in the first decade of July. The fastest rates of raspberry development were noted in 2021 at an average daily air temperature of 18.8ºС, flowering took place on May 18, ripening on June 16, 15-24 days ahead of multi-year periods, the duration of flowering, ripening and interphase periods also decreased. The sum of effective temperatures for the onset of the "beginning of flowering" phenological phase was 524ºС; the onset of the phase "beginning of maturation" 1063ºС. It was revealed that raspberry varieties Novosti Kuzmina, Barnaulskaya, Chelyabinskaya krupnoplodnaya, Brigantina had the highest resistance to changes in environmental factors in the conditions of the republic.

The Effect of Meteorological Factors on the COVID-19 Pandemic in Northeast Turkiye.

Introduction Although various studies have been conducted on the relationship between meteorological factors and coronavirus disease 2019 (COVID-19), this issue has not been sufficiently clarified. In particular, there are a limited number of studies on the course of COVID-19in the warmer-humidity seasons. Methods Patients presenting to the emergency departments of health institutions and to clinics set aside for cases of suspected COVID-19 in the province of Rize between 1 June and 31 August 2021 and who met the case definition based on the Turkish COVID-19 epidemiological guideline were included in this retrospective study. The effect of meteorological factors on case numbers throughout the study was investigated. Results During the study period, 80,490 tests were performed on patients presenting to emergency departments and clinics dedicated to patients with suspected COVID-19. The total case number was 16,270, with a median daily number of 64 (range 43-328). The total number of deaths was 103, with a median daily figure of 1.00 (range 0.00-1.25). According to the Poisson distribution analysis, it is found that the number of cases tended to increase at temperatures between 20.8 and 27.2°C. Conclusion It is predicted that the numberof COVID-19 cases will not decrease with the increase in temperature in temperate regions with high rainfall. Therefore, unlike influenza, there may not be seasonal variation in the prevalence of COVID-19. The requisite measures should be adopted in health systems and hospitals to manage increases in case numbers associated with changes in meteorological factors.

Spatial and temporal variations of grassland vegetation on the Mongolian Plateau and its response to climate change

The Mongolian Plateau is an arid and semi-arid region with grassland as its main vegetation. It has a fragile ecosystem and is a sensitive area for global warming. The study is based on MODIS NDVI data and growth season meteorological data from 2000 to 2018, this study examined the spatial and temporal variation characteristics of grassland vegetation on the Mongolian Plateau during the growing season using trend analysis, partial correlation analysis, and residual analysis, and it explores the dual response of NDVI changes to climate and human activities. The study’s findings demonstrated that the growing season average NDVI of grassland vegetation on the plateau gradually increased from southwest to northeast during the growing season; the growing season average NDVI demonstrated a significant overall increase of 0.023/10a (p < 0.05) from 2000 to 2018, with an increase rate of 0.030/10a in Inner Mongolia and 0.019/10a in Mongolia; the area showing a significant increase in NDVI during the growing season accounted for 91.36% of the entire study area. In Mongolian Plateau grasslands during the growing season of 2000–2018, precipitation and downward surface shortwave radiation grew significantly at rates of 34.83mm/10a and 0.57 W/m2/10a, respectively, while average air temperature decreased slightly at a rate of −0.018°C/10a. Changes in meteorological factors of grassland vegetation varied by region as well, with Inner Mongolia seeing higher rates of precipitation, lower rates of average air temperature, and lower rates of downward surface shortwave radiation than Mongolia. On the Mongolian Plateau, the NDVI of grassland vegetation in the growing season showed a significant positive correlation with precipitation (0.31) and a significant negative correlation with average air temperature (−0.09) and downward surface shortwave radiation (−0.19), indicating that increased in NDVI was driven by an increase in precipitation paired with a decrease in air temperature and a decrease in surface shortwave radiation. The overall increase in NDVI caused by human activity in the grasslands of the Mongolian Plateau was primarily positive, with around 18.37% of the region being beneficial. Climate change and human activity both affect NDVI variations in Mongolian Plateau grasslands, which are spatially heterogeneous. Moderate ecological engineering and agricultural production activities are crucial for vegetation recovery. This work is crucial to further understanding surface–atmosphere interactions in arid and semi-arid regions in the context of global climate change.

Distribution and Potential Sources of Surface Aerosol Particles in the Yangtze River Delta Region, China

AbstractBased on meteorological and pollution data from January 2017 to December 2019, in this paper the long‐term distribution of surface aerosol particles, and the interaction between aerosol pollution and meteorological factors in four cities of the Yangtze River Delta (YRD) region is investigated. The long‐term observation shows the law of typical aerosol pollution characteristics. Meteorological factors are significantly different during aerosol‐polluted and nonpolluted days. The effect of each meteorological factor on aerosol pollution may vary by different seasons and cities. The changes in meteorological factors are not completely consistent during aerosol fine‐mode and coarse‐mode polluted days. To distinguish the possible sources of surface aerosol particles, the potential source contribution function and concentration‐weighted trajectory models are applied to study transport sources. Based on the detailed analyses, this study will provide a reliable basis for further pollution control in the YRD.

Changes in particulate matter concentration and meteorological variables after changing forest structure in oak-dominated forests nearby highway tollgate

Oak species are the major dominant tree species of deciduous forests, but the little study was conducted to understand the change of particulate matter concentration after changing the forest structure. This study analyzed the effects of changing forest structure (CFS) on the changes in meteorological factors and air particulate matter (PM) concentration after leaf emergence in oak-dominated forests nearby highway pollutants’ sources. In June 2019, 33% of the total trees were removed from the CFS of oak forests in the vicinity of the tollgate of Misiryeong in Goseong-gun, Gangwon-do, Korea. To understand the changes in leaf emergence between the treatment site (TRS is the site changing forest structure) and control site (CS), we investigated the foliage height profile (FHP, %) at each class of tree height in December 2019 and June 2020. The results showed that FHP (%) was lower in TRS than in CS in both months, and the FHP of the middle canopy class increased after TRS while that of the upper canopy class decreased. The correlation was significant with temperature in March (p < 0.01) and with wind speed in June (p < 0.01), indicating that CFS improved the airflow. There was no significant difference in the PM concentration between CS (PM10: 37.7 µg/m3, PM2.5: 21.1 µg/m3) and TRS (PM10: 37.5 µg/m3, PM2.5: 20.8 µg/m3) in March; however, the PM concentration in TRS (PM10: 65.0 µg/m3, PM2.5: 26.2 µg/m3) was lower than that in CS (PM10: 73.9 µg/m3, PM2.5: 29.1 µg/m3) in June. The rate of PM reduction (%) in TRS was higher in June (PM10: 11.3%, PM2.5: 10.0%) than in March (PM10: 2.3%, PM2.5: 4.0%). The low value of PM concentration in June could be related to the leaf emergence. Overall, the results indicated that meteorological factors and PM concentrations had changed in the inner part of the forest after leaf emergence and that the temperature and wind speed were strongly correlated with the PM concentration. These results suggest that CFS can change the forest structure and the airflow in oak-dominated forests, which PM can flow and settle down into the inner forest's nearby pollutants sources of a tollgate. The results provide basic information for understanding the reduction effect of PM by CFS in oak-dominated deciduous forests nearby highway pollutants source.

Are There Differences in Thermal Comfort Perception of Children in Comparison to Their Caregivers’ Judgments? A Study on the Playgrounds of Parks in China’s Hot Summer and Cold Winter Region

Playgrounds in urban parks are important for children’s physical and mental health, but global warming has led to a worsening outdoor environment and children’s outdoor activities have been affected. Improving the outdoor thermal comfort (OTC) of playgrounds can encourage children to engage in more and safer outdoor activities. However, there are a limited number of studies focusing on preschoolers’ outdoor thermal comfort (OTC) and most of them have substituted children’s thermal comfort with caregivers’ evaluations. To investigate the differences between children’s and caregivers’ evaluations of thermal sensation, thermal benchmarks and thermal adaptive behavior for children, we conducted meteorological measurements on representative playgrounds in three parks in Wuhan, China, and administered thermal perception questionnaires to preschool children and their caregivers. In addition, the Physiological Equivalent Temperature (PET) was used to establish evaluation criteria for children’s OTC and to make recommendations for the improvement of the playground environment. We draw five conclusions by analyzing 719 valid questionnaires: (1) Children were less sensitive to changes in meteorological factors than caregivers and had better tolerance of cold environments. (2) The NPET for preschoolers was evaluated by children and by caregivers, respectively, as 22.9 °C and 22.3 °C in summer and 10.6 °C and 11.2 °C in winter. (3) Playgrounds in Wuhan’s parks are uncomfortable for a long time in summer and a short time in winter. (4) Both children and caregivers want to improve summer comfort by lowering the temperature and winter comfort by increasing solar radiation. At the same time, children and caregivers show different preferences in adaptive behavior choices. (5) Adding deciduous trees and water play facilities can improve the site thermal environment. Furthermore, the OTC of humans can be improved by adding more service facilities on playgrounds.

Verification of sap flow characteristics and measurement errors of Populus tomentosa Carr. and Salix babylonica L. based on the liquid level equilibrium method.

This study clarified the characteristics and influencing factors of sap flow in Populus tomentosa Carr. and Salix babylonica L., and verified the applicability of Granier’s original formula for measuring the sap flow of the two species, aimed to provide a basis for the accurate assessment of tree transpiration. P. tomentosa and S. babylonica were used as research objects, their sap flow was measured by the thermal dissipation probe method (TDP), together with changes in meteorological factors and soil water content. Meanwhile, the transpiration of both species was measured by the liquid level equilibrium method (LLE) to verify the applicability of Granier’s original formula. We found that: (1) the sap flow velocity of P. tomentosa and S. babylonica under typical sunny and cloudy conditions showed unimodal or bimodal changes, which were highly significantly correlated with meteorological factors (P < 0.01), but they were all small and poorly correlated with meteorological factors on rainy days. (2) The sap flow velocity of both species was significantly and negatively correlated (P < 0.05) with the daily change in stem and soil water content at 10–20 cm. (3) Compared to that calculated with the LLE method, the sap flows of the two species calculated by the TDP technique using Granier’s original formula were seriously underestimated, with error rates of -60.96% and -63.37%, respectively. The Granier’s correction formulas for P. tomentosa and S. babylonica established by the LLE method were Fd = 0.0287K1.236 (R2 = 0.941) and Fd = 0.0145K0.852 (R2 = 0.904), respectively, and the combined correction formula was Fd = 0.0235K1.080 (R2 = 0.957). It was verified that the errors of sap flow calculated by the specific correction formulas for P. tomentosa and S. babylonica were -6.18% and -5.86%, and those calculated by the combined correction formula were -12.76% and -2.32%, respectively. Therefore, the characteristics of the sap flow velocity of P. tomentosa and S. babylonica on sunny, cloudy and rainy days were different and significantly influenced by meteorological factors. The original Granier’s formula for calculating their sap flow resulted in a large error, but can be measured more accurately by constructing specific correction and combination formulas through the LLE method.

Assessment of the effect of meteorological and emission variations on winter PM2.5 over the North China Plain in the three-year action plan against air pollution in 2018–2020

Air quality in Beijing-Tianjin-Hebei and its surrounding regions has been significantly improved during the Three-Year Action Plan for Winning the Battle Against Air Pollution from 2018 to 2020. The PM2.5 concentration can be significantly influenced by meteorological conditions, and the effectiveness of anthropogenic emissions reduction on PM2.5 over the North China Plain remains unclear. In this study, the Nested Air Quality Model System (NAQPMS) and observations were used to quantitatively examine the contribution of meteorological and emission variations to autumn-winter (November to February) PM2.5 concentrations in Beijing and its surrounding regions from 2018 to 2020. The model reproduced the temporal evolution of atmospheric pollutants and components well. The results showed that the observed mean PM2.5 concentrations during the winter were reduced by 15% and 29% in 2019 and 2020, respectively, compared with that in 2018. In 2019, the meteorological conditions over the Beijing-Tianjin-Hebei (BTH) region were poor, causing an increase of PM2.5 by 7.6% in BTH and 11% in Beijing; therefore, the control of air pollutant emission compensated for the unfavorable influence of meteorology and emission reduction was the decisive factor for PM2.5 reduction; In 2020, the meteorological conditions were relatively favorable, and the changes in meteorological factors and emission reduction led to a decrease in PM2.5 concentration by 18.6% and 10.5%, respectively, compared to 2018. Emission reduction also contributed to decrease in nitrate, ammonium, organic matter, element carbon and precursors. This work confirmed the obvious environmental benefit of pollution control measures from 2018 to 2020. There was obvious regional heterogeneity in the effect of meteorology and the impact of adverse meteorological conditions should be considered during the formulation of air pollution control measures. The results can serve as a reference for the formulation of air quality objectives or the evaluation of the environmental effect of pollution control schemes.

Using a mechanistic model to explain the rising non-linearity in storage discharge relationships as the extent of permafrost decreases in Arctic catchments

The relationship between groundwater and discharge in Arctic and sub-Arctic regions is strongly controlled by permafrost. Previous work has shown that catchments with thawing frozen soils due to the warming climate are expected to show changes in their storage-discharge relationship. In this study, we use a mechanistic modelling approach to demonstrate that a thawing catchment underlain with continuous permafrost undergoes a dramatic change in storage-discharge relationship. We demonstrate that the effect of permafrost thaw, conceptualized as a reduction of an impermeable layer in the subsurface, will likely only be clearly observable as a change in slope of the recession curve of catchments with hillslope gradients>5 %. For flat catchments (<1% hillslope gradient), we find no relation with permafrost extent and change in recession curve slope will likely be dominated by changes in active layer parameters, such as in shallow surface permeability (Hydraulic Conductivity, above permafrost) and shallow surface and subsurface water retention (Specific Yield of Groundwater & Specific Yield of Surface). For mildly sloped Arctic catchments (5 % hillslope gradient), change in recession curve slope is controlled both by changes in permafrost extent and the subsurface flow length and subsurface hydraulic properties for the shallow flow, with minimal impact from overland flow properties and changes in meteorological factors. For moderately sloped Arctic catchments (10 % hillslope gradient), change in recession curve slope change is dominated by changes in permafrost extent, and secondly by changes in the subsurface flow length and subsurface hydraulic properties, with no impact from meteorological factors or changes in overland flow properties. Several of the parameters found to be driving shifts in recession curve slopes in our modeling, such as changes in active layer thickness and the formation of taliks, are more likely than others to evolve with the ongoing Arctic climate change in hillslopes, helping us understand what drives the real-world increases in non-linearity of storage-discharge relationships.

Spatio-Temporal Analysis of Changes in Winter Wheat Cold Damage with Meteorological Elements in Huang-Huai-Hai Plain from 2011 to 2020

The Huang-Huai-Hai Plain is one of the typical agri-ecosystems in China, which suffers from cold damage frequently resulting in substantial economic losses. In order to monitor the changes in the occurrence of cold damage in an effective and large-scale manner, and to determine their meteorological causes, this paper collected low temperature data from the agricultural meteorological stations and remote sensing data of MODIS from 2005 to 2015, and constructed a monitoring model of cold damage to winter wheat in Huang-Huai-Hai Plain based on the Logistic regression model. This model was used to analyze the spatio-temporal changes of cold damage of winter wheat in Huang-Huai-Hai Plain from 2011 to 2020, and correlation analysis was performed with the spatio-temporal changes of meteorological factors to ascertain how they affect cold damage. The results show that the harm from cold damage in winter wheat has been gradually decreasing from 2011 to 2020, and the cold damage areas with high probability and high frequency are moving from north to south. The meteorological elements with the greatest impacts on the degree of cold damage from stronger to weaker are heat, precipitation and sunshine duration, whose influence has spatial variability.