Study on the Relationship between Acid Rain Characteristics and Weather Conditions in Nanchang

Based on the rainfall monitoring data and high altitude meteorological data,the present situation of acid rain pollution in Nanchang City was analyzed and the forming factors of acid rain were revealed. The results showed that acid rain in Nanchang had the characteristics of high acidity and frequency,and the pH value of rainfall reduced in recent years,belonging to sulfuric acid type,and the most serious acid rain pollution appeared in autumn and winter. The pH value of rainfall went up with the improvement of rainfall grade,and the increase of rainfall quantity had diluting effect on the rainfall acidity. High altitude meteorological conditions affected acid rain obviously,when the upper wind velocity was below 7 m/s,the frequency of acid rain was higher and its pH value was lower,with serious acid rain pollution,and it showed that upper wind had diluting effect on the horizontal transport of pollutants. The frequency of acid rain became higher with stronger inversion intensity. Moreover,the surrounding industrial areas had obvious effect on the formation of acid rain. Unstable meteorological conditions were beneficial to the horizontal and vertical diffusion of pollution in the lower atmosphere,reducing the effect of induced-acidity pollutants on a region.

Maize kernel weight responses to sowing dateassociated variation in weather conditions

Variation in weather conditions during grain filling has substantial effects on maize kernel weight(KW). The objective of this work was to characterize variation in KW with sowing date-associated weather conditions and examine the relationship between KW, grain filling parameters, and weather factors. Maize was sown on eight sowing dates(SD) at 15–20-day intervals from mid-March to mid-July during 2012 and 2013 in the North China Plain. With sowing date delay, KW increased initially and later declined, and the greatest KW was obtained at SD6 in both years. The increased KW at SD6 was attributed mainly to kernel growth rate(Gmean), and effective grain-filling period(P). Variations in temperature and radiation were the primary factors that influenced KW and grain-filling parameters. When the effective cumulative temperature(AT) and radiation(Ra)during grain filling were 950 °C and 1005.4 MJ m-2, respectively, P and KW were greatest. High temperatures(daily maximum temperature [Tmax] > 30.2 °C) during grain filling under early sowing conditions, or low temperatures(daily minimum temperature [Tmin] < 20.7 °C) under late sowing conditions combined with high diurnal temperature range(Tmax-min> 7.1 °C) decreased kernel growth rate and ultimately final KW. When sowing was performed from May 25 through June 27, higher KW and yield of maize were obtained. We conclude that variations in environmental conditions(temperature and radiation) during grain filling markedly affect growth rate and duration of grain filling and eventually affect kernel weight and yield of maize.

A Trend towards a Stable Warm and Windless State of the Surface Weather Conditions in Northern and Northeastern China during 1961–2014

This study investigates the trends in the mean state and the day-to-day variability （DDV） of the surface weather conditions over northern and northeastern China （NNEC） during 1961-2014 using CN05.1 observational data. In this study, we show that the surface temperature （wind speed） has increased （decreased） over NNEC and that the DDV of the surface temperatures and wind speeds has decreased, indicating a trend towards a stable warm and windless state of the surface weather conditions over NNEC. This finding implies a trend towards more persistent hot and windless episodes, which threaten human health and aggravate environmental problems. The trends are also examined in reanalysis data. Both the ERA-40 and the NCEP data show an increasing （decreasing） trend in the mean state of the surface temperatures （wind speeds）. However, the reanalysis data show a consistent decreasing trend in the DDV of the surface weather conditions only in the spring. The underlying reason for the decreased DDV of the surface weather conditions is further analyzed, focusing on the spring season. Essentially, the decreased DDV of the surface weather conditions can be attributed to a decrease in synoptic-scale wave activity, which is caused by a decrease in the baroclinic instability. There is a contrasting change in the baroclinic instability over East Asia, showing a decreasing （increasing） trend north （south） of 40°N. This contrasting change in the baroclinic instability is primarily caused by a tropospheric cooling zone over East Asia at approximately 40°N, which influences the meridional temperature gradient over East Asia.

The relationship between ischemic stroke and weather conditions in Duzce, Turkey

BACKGROUND: Weather conditions are thought to increase the risk of stroke occurrence. But their mechanism has not yet been clarified. We investigated possible relationships between ischemic stroke and weather conditions including atmospheric pressure, temperature, relative humidity, and wind speed.METHODS: One hundred and twenty-eight patients with ischemic stroke who had been admitted to our hospital between January 1 and December 31, 2010 were enrolled in this study. We investigated the relationship between daily cases and weather conditions the same day or 1, 2, and 3 days before stroke.RESULTS: A negative correlation was found between maximum wind speed and daily cases 3 days before stroke. As the relationship between daily cases and changes of weather conditions in consecutive days was evaluated, a negative correlation was found between daily cases and change of atmospheric pressure in the last 24 hours.CONCLUSIONS: The maximum wind speed 3 days before stroke and change of atmospheric pressure in the last 24 hours were found to increase the cases of ischemic stroke. We recommend that individuals at risk of ischemic stroke should pay more attention to preventive measures, especially on days with low maximum wind speed, on subsequent 3 days, and on days with low atmospheric pressure in the last 24 hours.

Modeling differential car-following behavior under normal and rainy conditions: A memory-based deep learning method with attention mechanism

In order to analyze and learn the difference in car-following behavior between normal and rainy days, we first collect car-following trajectory data of an urban elevated road on normal and rainy days by microwave radar and analyze the differences in speed, relative speed, acceleration, space headway, and time headway among data through statistics. Secondly, owing to the time-series characteristics of car-following data, we use the long short-term memory(LSTM) neural network optimized by attention mechanism(AM) and sparrow search algorithm(SSA) to learn the different car-following behaviors under different weather conditions and build corresponding models(ASL-Normal, ASL-Rain, where ASL stands for AM-SSA-LSTM), respectively. Finally, the simulation test shows that the mean square error(MSE) and reciprocal of time-to-collision(RTTC) of the ASL model are better than those of LSTM and intelligent diver model(IDM), which is closer to the real data. The ASL model can better learn different driving behaviors on normal and rainy days. However,it has a higher sensitivity to weather conditions from cross test on normal and rainy data-sets which need classification training or sample diversification processing. In the car-following platoon simulation, the stability performances of two models are excellent, which can describe the basic characteristics of traffic flow on normal and rainy days. Comparing with ASL-Rain model, the convergence time of ASL-Normal is shorter, reflecting that cautious driving behavior on rainy days will reduce traffic efficiency to a certain extent. However, ASL-Normal model produces a more severe and frequent traffic oscillation within a shorter period because of aggressive driving behavior on normal days.

Innovation of the double-maize cropping system based on cultivar growing degree days for adapting to changing weather conditions in the North China Plain

Double-maize cropping system is an effective option for coping with climate change in the North China Plain. However, the effects of changes in climate on the growth and yield of maize in the two seasons are poorly understood. Forty-six cultivars of maize with different requirements for growing degree days (GDD), categorized as high (H), medium (M) or low (L), and three cultivar combinations for two seasons as LH (using JD27 and DMY1 from category L in the first season;and YD629 and XD22 from category H in the second season), MM (using JX1 and LC3 from category M in the first season;and ZD958 and JX1 from category M in the second season) and HL (using CD30 and QY9 from category H in the first season;and XK10 and DMY3 from category L in the second season) were tested to examine the eco-physiological determinants of maize yield from 2015 to 2017. The correlations between the combinations of cultivars and grain yield were examined. The combination LH produced the highest annual grain yield and total biomass, regardless of the year. It was followed, in decreasing order, by MM and HL. Higher grain yield and biomass in LH were mainly due to the greater grain yield and biomass in the second season, which were influenced mainly by the lengths of the pre- and post-silking periods and the rate of plant growth (PGR). Temperature was the primary factor that influenced dry matter accumulation. In the first season, low temperatures during pre-silking decreased both the duration and PGR in LH, whereas high temperatures during post-silking decreased the PGR in MM and HL, resulting in no significant differences in biomass being observed among the three combinations. In the second season, high temperatures decreased both the PGR and pre- and post-silking duration in MM and HL, and consequently, the biomass of those two combinations were lower than that in LH. Moreover, because of lower GDD and radiation in the first season and higher grain yield in the second season, production efficiency of temperature and radiation (Ra) was the highest in LH. More importantly, differences in temperature and radiation in the two seasons significantly affected the rate and duration of growth in maize, and thereby affecting both dry matter and grain yield. Our study indicated that the combination of LH is the best for optimizing the double-maize system under changing climatic conditions in the North China Plain.

Geochemistry of Cretaceous Mudrocks and Sandstones from Douala Sub-Basin, Kumba Area, South West Cameroon: Constraints on Provenance, Source Rock Weathering, Paleo-Oxidation Conditions and Tectonic Environment

Geochemical data of fifteen Cretaceous sediment samples from Kumba area in the Douala sub-basin are presented to determine the provenance, source rock weathering, tectonic setting and paleo-oxidation conditions of the depositional setting of these rocks. For this purpose, the whole-rocks were analyzed for their major and trace element, including rare earth elements (REEs), contents by ICP-AES and ICP-MS methods respectively. On the basis of their major element composition, the rocks have been classified mainly as Fe-shale, shale, arkose and Fe-sandstone. For the provenance, the plot of Zr vs. TiO2, Y/Ni vs. Cr/V, TiO2 vs. Al2O3 diagrams, high LREE/HREE ratios (5.84 to 20.91) and negative and positive Eu anomalies (Eu/Eu*= 0.87 to 1.62) suggest that the studied rocks were mainly derived from felsic igneous rocks with lesser contribution of mafic components. The higher values of paleo-weathering indices such as Plagioclase Index of Alteration (PIA) and Chemical Index of Weathering (CIW), ranging from 79.63 to 99.90 and 87.57 to 99.92 respectively, suggest that the sediments and their potential source rocks experienced intense weathering. Whereas the variable Chemical Index of Alteration (CIA) values (63.01 to 99.50) coupled with high content of K2O (up to 7.5) in most samples could be indicative of K-addition diagenetic processes. The A-CN-K plot also suggests a possible K-addition. The redox conditions during the sedimentation were suboxic to oxic as evidenced by the Ce anomalies of 0.88 to 1.03. This is also confirmed by the values of Ni/Co (less than 7), U/Th (less than 1.25) and Cu/Zn (mostly less than 1). Tectonic discrimination diagrams (e.g., SiO2-K2O/Na2O and Th-Sc-Zr/10) show that these rocks were deposited mainly in an active continental margin setting, and in various tectonic environments. This reflects probably the recycling effect experienced by the samples studied.

Modeling of Artificial Intelligence Based Traffic Flow Prediction with Weather Conditions

Short-term traffic flow prediction (TFP) is an important area inintelligent transportation system (ITS), which is used to reduce traffic congestion. But the avail of traffic flow data with temporal features and periodicfeatures are susceptible to weather conditions, making TFP a challengingissue. TFP process are significantly influenced by several factors like accidentand weather. Particularly, the inclement weather conditions may have anextreme impact on travel time and traffic flow. Since most of the existing TFPtechniques do not consider the impact of weather conditions on the TF, it isneeded to develop effective TFP with the consideration of extreme weatherconditions. In this view, this paper designs an artificial intelligence based TFPwith weather conditions (AITFP-WC) for smart cities. The goal of the AITFPWC model is to enhance the performance of the TFP model with the inclusionof weather related conditions. The proposed AITFP-WC technique includesElman neural network (ENN) model to predict the flow of traffic in smartcities. Besides, tunicate swarm algorithm with feed forward neural networks(TSA-FFNN) model is employed for the weather and periodicity analysis. Atlast, a fusion of TFP and WPA processes takes place using the FFNN modelto determine the final prediction output. In order to assess the enhancedpredictive outcome of the AITFP-WC model, an extensive simulation analysisis carried out. The experimental values highlighted the enhanced performanceof the AITFP-WC technique over the recent state of art methods.

Early warning for geo-hazards based on the weather condition in China

According to national early warning practice for geo-hazards from 2003 to 2005,it is systematically concluded that the basic characteristics of geo-hazards,early warning method and forecast result based on the geological maps of China in a scale 1∶6 000 000.With the contrast of different characters between sustained rainfall and typhoon rainfall inducing geo-hazards,the disaster reduction result and some problems are preliminarily analyzed.Some basic recognition is that early warning to geo-hazards is feasible,national scale forecast is only to call attention,but can't immediately be used to disaster reduction decision-making.And,the future direction is to build a united disaster reduction framework of early warning system including national,provincial and county levels based on weather factors in different scale of area.

Influence of Weather Conditions on the Surface Morphology and Wetting Behaviour of Superhydrophobic Quaking Aspen Leaves

The effects of different environmental conditions on the wetting properties and surface morphology of surperhydrophobic quaking aspen leaves harvested during the 2011 growth season are examined. During this particular season quaking aspen leaves were not able to retain their superhydrophobic properties and associated surface structure features as they have usually been able to do in other years. Representative scanning electron microscopy images and wetting property measurements of quaking aspen leaf surfaces harvested throughout this season are presented and discussed with the objective of linking weather induced environmental stresses that occurred in 2011 to the sudden and unusual reduction in non-wetting properties and drastic changes in leaf surface structure. Erosion and regeneration rates of leaf wax crystals and the impact that environmental factors can have on these are considered and used to explain the occurrence of these unexpected changes.

EXPERIMENTAL STUDY OF THE ROLE OF INITIAL AND BOUNDARY CONDITIONS IN MESOSCALE NUMERICAL WEATHER PREDICTION

Based on the real case of a frontal precipitation process affecting South China, 27 controlled numerical experiments was made for the effects of hydrostatic and non-hydrostatic effects, different driving models, combinations of initial/boundary conditions, updates of lateral values and initial time levels of forecast, on model predictions. Features about the impact of initial/boundary conditions on mesoscale numerical weather prediction (NWP) model are analyzed and discussed in detail. Some theoretically and practically valuable conclusions are drawn. It is found that the overall tendency of mesoscale NWP models is governed by its driving model, with the initial conditions showing remarkable impacts on mesoscale models for the first I0 hours of the predictions while leaving lateral boundary conditions to take care the period beyond; the latter affect the inner area of mesoscale predictions mainly through the propagation and movement of weather signals (waves) of different time scales; initial values of external model parameters such as soil moisture content may affect predictions of more longer time validity, while fast signals may be filtered away and only information with time scale 4 times as large as or more than the updated period of boundary values may be introduced, through lateral boundary, to mesoseale models, etc. Some results may be taken as important guidance on mesoseale model and its data a.ssimilation developments of the future.

A Study on Palaeogeography and Metallogenic Conditions of Early Carboniferous Bauxite Deposits of Old Weathered Crust in Guizhou, Sichuan, Hunan and Hubei Provinces

There are four subtypes. namely, Ia, Ib, Ic and Id of the Early Carboniferous bauxite deposits of the old weathered crust type in Guizhou, Sichuan, Hunan and Hubei provinces. They are all distributed in the Upper Yangtze old land. As a result of the Hunan-Guizhou palaeo-faulting, the crust on the northern side of the fault was uplifted and became land, thus suffering denudation. The bauxitic substances left in the weathered crust evolved and were reworked into bauxite. On the other hand, the crust on the southern side of the fault sank and remained to be part of an ocean. The bauxite deposits of Ia and Ib subtypes were formed by in-situ enrichment of residual bauxitic substances in the weathered crust of the old land, but bauxite deposits of Ic and Id subtypes resulted from transportation, accumulation and sedimentation of allothogenous bauxitic substances on the weathered crust of the old land. The processes of transportation may be distinguished as dry transportation and wet transportation, both of which proceeded under atmospheric conditions.

The Effect of Weather Conditions on Pediatric Supracondylar Humerus Fractures

Background: Environmental conditions are effective on childhood supracondylar humerus fractures. In this study, we evaluated the relationship between weather conditions and these fractures. Materials and Methods: We started this study following the approval of a non-interventional research ethics committee. Patients (<16 years) who applied to the hospital between January 2013 and July 2018 with supracondylar humerus fractures were included in the study. The hospital’s PROBEL system was used to diagnose (International Classification of the Diseases, ICD, S42.4) radiological images and patient information. Information on the weather conditions in the day and time period, in which supracondylar humerus fracture occurred, was obtained from TR (Turkey) Ministry of Agriculture and Forestry General Directorate of Meteorology. The relationship between supracondylar fracture and daily weather conditions (wind, air temperature, cloudiness, and season) was analyzed. Results: Most of the patients (n = 76, 40.6%, p < 0.05) were fractures occurring under cloudless weather conditions. Fractures were concentrated with a second frequency in cloudy weather over 60%, except for cloudless weather conditions (n = 51, 27.3%, p < 0.05). In the summer months when the air temperature was high, the number of fractures was higher (n = 62, 33.2%, p < 0.05) and less in the winter months (n = 24, 12.8%, p < 0.05). In hot weather conditions where the daily average temperature was above 20°C, supracondylar humerus fractures were observed more (n = 101, 54%) and less than 10°C (n = 43, 23%, p < 0.05). Increased incidence of fractures was observed in the presence of wind (n = 4, 2.1%, p < 0.05). Conclusion: Supracondylar humerus fractures are common in children. Environmental conditions (temperature, wind, and season) can be effective in the occurrence of these fractures.

Problems and Opportunities for Biometeorological Assessment of Conditions in Cold Season

The article is devoted to a discussion of the possibilities of biometeorological assessment of the severity of weather conditions during the cold season.The relevance of the study is ensured not only by the fact that residents of a number of states,whose total number is more than 27 million people,live in these extreme climatic conditions,but also by the need to improve biometeorological approaches to assessing the impact of these conditions on the body and health of the population.This study examined biometeorological characteristics that illustrate a measure of cold stress.These include the Siple wind-chill index;Bodman winter severity index;Arnoldi weather hardness coefficient;Mountain wind chill index;weather hardness coefficient according to I.M.Osokin.The results of a comparison of winter severity assessments based on the values of the calculated Siple and Bodman indices made it possible to establish that the Bodman index is more acceptable when assessing mildly severe winters.The most adequate for assessing the“severity”of the cold period against the background of a decrease in air temperature and an increase in wind speed is the Siple index.The need to provide the countries of the world with high-quality hydrometeorological and biometeorological forecast information is justified and relevant.In this regard,these studies are very promising.

Selection of Weather Parameters for Air-Conditioning System Design for Buildings with Long Thermal Lag

Two building factors-a longer thermal lag of more than one hour for building envelops and a lag of indoor radiation to convert into cooling load-have impact on the instantaneous heat input and instantaneous cooling load.So the two factors should be taken into account when selecting the weather parameters for air-conditioning system design.This paper developed a new statistic method for the rational selection of coincident solar irradiance,dry-bulb and wet-bulb temperatures.The method was applied to historic weather records of 25 years in Hong Kong to generate coincident design weather data.And the results show that traditional design solar irradiance,dry-bulb and wet-bulb temperatures may be significantly overestimated in many conditions,and the design weather data for the three different constructions is not kept constant.

Performance analysis of continuous-variable measurement-device-independent quantum key distribution under diverse weather conditions

The effects of weather conditions are ubiquitous in practical wireless quantum communication links.Here in this work,the performances of atmospheric continuous-variable measurement-device-independent quantum key distribution(CV-MDI-QKD)under diverse weather conditions are analyzed quantitatively.According to the Mie scattering theory and atmospheric CV-MDI-QKD model,we numerically simulate the relationship between performance of CV-MDI-QKD and the rainy and foggy conditions,aiming to get close to the actual combat environment in the future.The results show that both rain and fog will degrade the performance of the CV-MDI-QKD protocol.Under the rainy condition,the larger the raindrop diameter,the more obvious the extinction effect is and the lower the secret key rate accordingly.In addition,we find that the secret key rate decreases with the increase of spot deflection distance and the fluctuation of deflection.Under the foggy condition,the results illustrate that the transmittance decreases with the increase of droplet radius or deflection distance,which eventually yields the decrease in the secret key rate.Besides,in both weather conditions,the increase of transmission distance also leads the secret key rate to deteriorate.Our work can provide a foundation for evaluating the performance evaluation and successfully implementing the atmospheric CV-MDI-QKD in the future field operation environment under different weather conditions.

Modeling of the Photovoltaic Module Operating Temperature for Various Weather Conditions in the Tropical Region

The operating temperature is a critical factor affecting the performances of photovoltaic(PV)modules.In this work,relevant models are proposed for the prediction of this operating temperature using data(ambient temperature and solar irradiance)based on real measurements conducted in the tropical region.For each weather condition(categorized according to irradiance and temperature levels),the temperatures of the PV modules obtained using the proposed approach is compared with the corresponding experimentally measured value.The results show that the proposed models have a smaller Root Mean Squared Error than other models developed in the literature for all weather conditions,which confirms the reliability of the proposed framework.

Crop Yield Estimation with Farmers＇ Appraisal on Weather Condition

Crop yield is mainly affected by weather condition, inputs, and agriculture policies. In the crop yield estimation, farmers＇ perception on weather conditions lead to the assessment of how well yield would be compared to the previous seasons. This paper applies Bayesian estimation method to estimate crop yield with farmers＇ appraisal on weather condition. The paper shows that crop yield estimation with farmers＇ appraisal on weather condition takes into account risk proportionally to climate change. In light of the United Nations efforts aimed to build a consolidated agriculture statistical system across countries, the statistical model developed here should provide an important tool both for the crop yield estimation and food price analysis.

Paleo-environmental conditions,paleoclimatic significance and effects of weathering on clay deposits in the Lower Benue Trough,Nigeria.Mineralogical approach

Combined methods for mineralogical identifications were used to characterise the clay deposits within the Lower Benue Trough of Nigeria to interpret paleo-environmental conditions,the paleoclimatic significance of the trough,and effects of weathering on the minerals as factors that favour its deposition/accumulation within the trough which host other important industrial minerals like coal,barite,limestone etc.Bulk-sample random-powder XRD data and data for clay fractions deposited onto zero-background quartz plates were measured.The samples contained kaolinite,vermiculite,and traces of smectite,and the non-clay phases included quartz,microcline,and muscovite.All samples were unaffected after glycolation,confirming the absence of significant smectite.Muscovite was characterized by the nature of its 10Åbasal peak with a width of<0.10°2θ,which was very sharp.DTA/TGA results support the presence of kaolinite,and the characteristic kaolinite O-H,Al-OH,Si-OH and Si-O-Al FTIR bands also confirmed its presence.Vermicular and book-like morphologies were observed under the SEM,typical of kaolinitic clay from in situ alteration.High kaolinite abundance in these sediments is consistent with intense weathering of parent rocks rich in Al under wet/tropical paleo-climatic conditions with fresh and/or brackish water conditions in a continental setting.The variety of observed morphologies suggests that the deposits suffered more of chemical weathering.The clay deposits in Lower Benue Trough are quartz-rich,kaolinitic and derived from the chemical weathering of Al-rich source rocks.

Analysis of Weather Conditions for Aerial Security and Optimization in Maroua-Salak

In this study, the weather conditions of the accident at Maroua-Salak airport on 02 August 2020 are analyzed. This C130 aircraft accident took place under bad weather conditions. This bad weather is diagnosed using the models as CFS, GFS and GEFS that reanalyze outputs of the results. At the end of this re-analysis, the result obtained shows that the event which took place at the Maroua-Salak airport was predictable. However, the analysis of these results has made it possible to present the rainfall cumul between 05 and 10 mm for this day. In addition, a comparative study of the rainfall cumul obtained by the CFS, GFS and GEFS models and that estimated by the satellites has been carried out. These models can significantly improve the prevention of such disasters in the region.