Sunny Conditions Research Articles

Heat storage and release performance experiment of externally hung phase change solar greenhouse in severe cold regions of Northeast China - Taking Fuxin City as an example

The traditional solar greenhouses in severe cold regions of northeast China have poor heat storage and thermal insulation performance, and the abundant solar energy resources cannot be utilized rationally. Phase change energy storage is considered to be one of the effective ways to cope with this problem. The price, encapsulation leakage and arrangement of PCM are the bottleneck problems restricting its practical application. This paper used the modified calcium chloride hexahydrate-based phase change material as the energy storage medium. A PVC-U tube was used for encapsulation and external hanged on the inner surface of the north wall of the partitioned greenhouse. Based on the 51 days of field comparison test, the comparative greenhouse heat storage and release performance under typical sunny, cloudy and snowy conditions was discussed. Through the experiments, it was found that the externally hung phase change energy storage device increased the effective accumulated temperature by 21.1 %, changing the dynamic heat transfer relationship between the envelope structure and indoor air. It confirmed the feasibility of promoting the externally hung phase change energy storage device in the severe cold region of Northeast China.

Daily Rhythmicity of Hepatic Rhythm, Lipid Metabolism and Immune Gene Expression of Mackerel Tuna (Euthynnus affinis) under Different Weather

In order to investigate the rhythmic changes in gene expression in the liver of mackerel tuna (Euthynnus affinis) under sunny and cloudy conditions, this experiment had four sampling times (6:00, 12:00, 18:00 and 24:00) set on sunny and cloudy days to determine the expression of their immune, metabolic and rhythmic genes. The results showed that daily rhythmicity was present within most of the rhythm genes (CREB1, CLOCK, PER1, PER2, PER3, REVERBA, CRY2 and BMAL1), metabolic genes (SIRT1 and SREBP1) and immune genes (NF-kB1, MHC-I, ALT, IFNA3, ISY1, ARHGEF13, GCLM and GCLC) in this study under the sunny and cloudy condition (p < 0.05). The expression levels of CREB1, PER1, PER3, RORA, REVERBA, CRY1 and BMAL1 within rhythm genes were significantly different (p < 0.05) in the same time point comparison between sunny and cloudy conditions at 6:00, 12:00, 18:00 and 24:00; metabolic genes had the expression levels of LPL at 6:00, 12:00, 18:00 and 24:00 in the same time point comparison (p < 0.05); immune genes only had significant differences in the expression levels of IFNA3 at 6:00, 12:00, 18:00 and 24:00 (p < 0.05). This study has shown that rhythm, lipid metabolism and immune genes in the livers of mackerel tuna are affected by time and weather and show significant changes in expression.

Experimental Performance Evaluation of an Integrated, LCPV/T Membrane Distillation System for Electricity and Seawater Desalination

In this paper, an integrated system based on low-concentrated photovoltaic/thermal (LCPV/T) technology and efficient vacuum membrane distillation (VMD) seawater desalination utilizing the energy of solar is established. Through a theoretical analysis and a series of experiments, this paper explores the temperature change of a single VMD process, and the variation trend of single-day membrane flux with solar irradiation and temperature parameters. In addition, the changes in solar irradiation, temperatures of the integrated system, membrane flux, and thermoelectric properties in different seasons are also analyzed. A mathematical model was established to calculate the relationship between membrane flux and temperature difference. The experimental results show that the membrane flux of VMD is 2.73 L/(m2·h); the simulated seawater can achieve a desalination rate of 99.9%. After economic analysis, the operating incomes of the system under sunny weather conditions in different seasons were all positive.

Evaluating optimal control of active insulation and HVAC systems in residential buildings

Recently, active insulation systems (AIS) have been conceptualized in building envelopes to optimally modulate thermal resistance in response to changing environmental conditions. Building flexibility can further be improved if the building is also equipped with optimized heating, ventilating, and air conditioning (HVAC) control. In this work, we investigate the annual potential benefits of jointly optimizing AIS and HVAC system controls in both heating and cooling days over all climate zones (CZs) in the U.S. To reduce the computational complexity of applying model predictive control (MPC) to annual operations and detailed whole-building energy models, timeseries clustering was used to identify a set of representative days for optimizing in each climate zone. To isolate the increase in benefits from this joint optimization, we compare the performance to cases where the AIS and HVAC controls are optimized separately. Results indicate savings potential in all CZs, with the largest annual average savings of 9.02% and 4.02% observed in the cooling days with large daily temperature swings and heating days with cold sunny conditions, respectively. Savings patterns across climate zone, day types, and HVAC modes (i.e., heating or cooling) are also discussed along with the implications of important system design variables.

Overview of Latent and Active Failure Factors in Indonesian Road Transportation Accidents in 2019 – 2021

Road transportation accidents are the eighth leading cause of death worldwide, reaching 1.35 million people annually (WHO, 2021). Data from the NTMC Korlantas Polri for 2019-2021 shows that the number of road transportation accidents in Indonesia is above 100 thousand every year. This study identifies latent and active failure factors contributing to Indonesia's land transportation accidents to determine the causes of accidents comprehensively. This study uses secondary data with 320,084 traffic accident case reports in 2019-2021 belonging to the NTMC Korlantas Polri. The method used is qualitative by analyzing based on the Swiss Cheese Model. The results of this study indicate latent failure factors in road transportation accidents in Indonesia in 2019-2021, namely the initial condition of the brake vehicle not functioning (5.7%), occurring on roads with suitable conditions (92.5%), occurring in sunny weather conditions ( 92.3%), and bright/clear lighting conditions (79.1%). Active failure factors in land transportation accidents in Indonesia in 2019 - 2021 are the age of drivers aged 22 – 29 years (15.7%), drivers with a senior high school education/equivalent (48.4%), drivers who do not have a driver's license (28.3 %), and drivers who are careless towards traffic from the front (19.0%).

Dissipation kinetics of some pesticides applied singly or in mixtures in/on grape leaf.

Grape and leaf quality are often severely reduced by fungi such as grey rot Botrytis cinerea Pers., powdery mildew Erysiphe necator Schwein, and downy mildew Plasmopara viticola (Berk. & M.A.Curtis) Berl. & De Toni and by insects such as Otiorhynchus spp., European grapevine moth Lobesia botrana Den.-Schiff., vine mealybug Planococcus citri Risso, and grape erineum mite Colomerus vitis Pgst. Various pesticides are often applied to mitigate these pest problems. These chemicals used singly as well as in the form of a mixture can leave residues on or in the crop. It is therefore of great importance to study the dissipation of the pesticides applied alone and in mixtures to this crop to protect consumers. The dissipation kinetics of cypermethrin, boscalid, deltamethrin, kresoxim-methyl, lambda-cyhalothrin, metalaxyl-M, metrafenone, and triadimenol residues were studied in vine leaves grown under sunny conditions in Turkey. The dissipation rate for singly applied pesticides followed first-order kinetics, with half-lifes in grape leaves in the range of 1.85-7.22 days. Changes in the degradation process of pesticide residues were determined after application, as both single applications and mixtures. The degradation of boscalid, cymoxanil, deltamethrin and metalaxyl-M accelerated while the degradation of cypermethrin, kresoxim-methyl, and lambda-cyhalothrin slowed down in mixtures of pesticides. The use of pesticides in mixtures leads to slower degradation and higher residues for some active ingredients and faster degradation and fewer residues for other active ingredients. Therefore, pesticide mixtures should not be applied in the field without having detailed information about their ingredients. © 2022 Society of Chemical Industry.

Sub-ambient cooling effect and net energy efficiency of a super-amphiphobic self-cleaning passive sub-ambient daytime radiative cooling coating applied to various buildings

In this study, a super-amphiphobic passive sub-ambient daytime radiative cooling (PSDRC) coating was applied to various buildings in different climatic regions in China. Irrespective of sunny, cloudy, and rainy weather conditions, the roof and west-facing wall surfaces coated with the PSDRC coating exhibited distinct sub-ambient cooling effects. Compared with the cool-white and grey roof surface temperatures, the roof surface temperature due to PSDRC coating was lower by 10.1 °C and 33.1 °C, respectively. Consequently, the room interior temperatures of different buildings were lower than the ambient air temperature during the day because of heat conduction and convection. The room with a window coated by the PSDRC coating had 18.2 °C lower interior temperature than that with a west-facing glass window. Thus, the PSDRC coating decreased the cooling energy consumption of buildings in the summer but increased the heating energy consumption in the winter. However, the net energy savings were considerable because of low solar irradiance and high heating energy demand when the sub-ambient cooling effect was diminished, which minimised the difference between the roof surface and room interior temperatures of the PSDRC and control buildings. After five-cycle dirt resistance tests, the solar reflectance of the super-amphiphobic PSDRC coating was reduced only by 0.0051. After 2000 h of artificial accelerated weathering tests, the solar reflectance of the superamphiphobic PSDRC coating was attenuated by 0.021 on average. This indicates the significance of the super-amphiphobic self-cleaning capability, which endowed the coating with a long-term sub-ambient cooling effect.

Deep Learning Based Infrared Thermal Image Analysis of Complex Pavement Defect Conditions Considering Seasonal Effect.

Deep learning techniques underpinned by extensive data sources encompassing complex pavement features have proven effective in early pavement damage detection. With pavement features exhibiting temperature variation, inexpensive infra-red imaging technology in combination with deep learning techniques can detect pavement damages effectively. Previous experiments based on pavement data captured during summer sunny conditions when subjected to SA-ResNet deep learning architecture technique demonstrated 96.47% prediction accuracy. This paper has extended the same deep learning approach to a different dataset comprised of images captured during winter sunny conditions to compare the prediction accuracy, sensitivity and recall score with summer conditions. The results suggest that irrespective of the prevalent weather season, the proposed deep learning algorithm categorises pavement features around 92% accurately (95.18% in summer and 91.67% in winter conditions), suggesting the beneficial replacement of one image type with other. The data captured in sunny conditions during summer and winter show prediction accuracies of DC = 96.47% > MSX = 95.24% > IR-T = 93.83% and DC = 94.14% > MSX = 90.69% > IR-T = 90.173%, respectively. DC images demonstrated a sensitivity of 96.47% and 94.20% for summer and winter conditions, respectively, to demonstrate that reliable categorisation is possible with deep learning techniques irrespective of the weather season. However, summer conditions showing better overall prediction accuracy than winter conditions suggests that inexpensive IR-T imaging cameras with medium resolution levels can still be an economical solution, unlike expensive alternate options, but their usage has to be limited to summer sunny conditions.

Accelerated Sea Ice Loss from Late Summer Cyclones in the New Arctic

Abstract Synoptic-scale cyclones in the Arctic are an important source of short-term sea ice variability during the melt season. This study examines whether recent changes to the Arctic environment have made Arctic cyclones during the summer months more destructive to sea ice on short time scales. We compare the 1–7-day changes in sea ice area and thickness following days in each month with and without cyclones from two decades: 1991–2000 and 2009–18. Only in August do cyclones locally accelerate seasonal sea ice loss on average, and the ability of August cyclones to accelerate ice loss has become more pronounced in the recent decade. The recent increase in ice loss following August cyclones is most evident in the Amerasian Arctic (140°E–120°W), where reanalyses indicate that the average upper-ocean temperature has increased by 0.2°–0.8°C and the average ice thickness has decreased by almost 1 m between the two decades. Such changes promote cyclone-induced ocean mixing and sea ice divergence that locally increase the likelihood for rapid ice loss near cyclones. In contrast, June cyclones in both decades locally slow down seasonal sea ice loss. Moreover, the 7-day sea ice loss in June has increased from the early to the recent decade by 67% more in the absence of cyclones than in the presence of cyclones. The largest increases in June ice loss occur in the Eurasian Arctic (0°–140°E), where substantial reductions in average surface albedo in the recent decade have allowed more of the abundant insolation in the absence of cyclones to be absorbed at the sea surface. Significance Statement This study determines whether Arctic storms during summer have become more destructive to sea ice in recent years. In comparing storms from two periods (1991–2000 vs 2009–18), we find that only storms in August have become more destructive to sea ice in the recent period, because of warmer upper-ocean temperatures and thinner ice, which strong winds move around more easily. In June, clear-sky conditions have become more destructive to sea ice in recent years because declining ice cover has allowed more sunlight to be absorbed at the sea surface, favoring further ice melt. These results suggest that sunny conditions in June followed by stormy conditions in August could cause the first ice-free summer in the Arctic.

Acceptability modeling of autonomous mobility on-demand services with on-board ride sharing using interpretable Machine Learning

Research on the factors that may affect the future uptake of autonomous Mobiliyt on Demand (MoD) services are today more than ever relevant. In this paper, we attempt to investigate all aspects of acceptability of a proposed Autonomous-MoD service (AMoD). More specifically, we develop mode choice models and identify the factors that affect it in both sunny and rainy weather conditions, using state-of-the-art Machine Learning models and interpretation techniques, such as the permutation feature importance and partial dependence. Furthermore, we estimate the willingness of the service’s potential users to pay for reduced travel time and propose an on-board negotiation scheme of the travel time and cost for sharing one’s ride. For the above purposes, we conducted a questionnaire survey with 1600 participants in the city of Athens, Greece just after alleviation of the lockdown and measures related with the COVID-19 first wave. The models developed are capable of predicting the mode choice and acceptability of the negotiation scheme with an accuracy of over 80%. Except for the cost, travel and walking time of each alternative mode, the users’ mobility profile, attitude towards autonomous vehicles and demographic characteristics are identified as the most important factors affecting the respondents’ choices. Moreover, the willingness to pay for reduced travel time varies from 0.18 to 0.62€, depending on the mode and about 0.53€ for the on-board negotiation.

Investigation of a Solar Space Heating System Based on an Evacuated Tube Collector for Baghdad Climatic Conditions

The current work aims at evaluating the overall experimental performance of the solar space heating system regarding the local meteorological conditions of Baghdad. Two types of systems have been considered, namely, the thermal radiator with and without a fan. Indeed, a thermal radiator is connected to evacuate the tube solar collector through a circulating pump to distribute the heat into a room with dimensions of (3×3 m2). The experimental measurements for the current research were carried out during a period of six days in February and March, i.e., under mild conditions where the weather ranged between sunny and cloudy during the day. In order to find out the system performance, the solar radiation intensity, wind speed, inlet and outlet temperatures from solar collectors, inlet and outlet temperatures from thermal radiators, room temperature, and ambient temperature have been measured using specific instruments. The results revealed that, under sunny conditions, the room temperature of the system without a fan changes from 16.2 oC to 23.9 oC with a temperature difference of 7.7 oC. However, when a fan is used, the temperature difference reaches 10 oC. Such an improvement in the performance of the solar heating system that characterized the current work in comparison with its counterpart research is a direct result of the adoption of two main ideas. The first of them is the use of a modern metal heat exchanger that contains vertical and horizontal tubes. In addition to that, it is equipped with a fan that helps to increase the heat exchange between the heat radiator and the room space due to forced convection. Furthermore, the fan works to distribute the heat homogeneously inside the room, thus increasing the efficiency of the system. The second idea, however, is the use of a modern system represented by software that analyzes the results and evaluates the values of solar radiation and wind speed.

PV-EV integrated home energy management using vehicle-to-home (V2H) technology and household occupant behaviors

The Vehicle-to-Home (V2H) topic is considered a promising and potential field of research due to its ability to address a variety of issues related to smart household electricity consumption and consumer energy demand. Therefore, as the population grows and their habits change, so does the need for domestic energy. Consequently, the provision of electricity poses increasingly difficult problems. To this end, the Home Energy Management System (HEMS) is being implemented to avoid similar problems. To maximize the utilization of various home appliances under energy demand and a predetermined timetable, we propose a precise Home Centralized Photovoltaic (HOCP) System, which includes V2H technology, Solar Photovoltaic (SPV), and a Green Electric Vehicle (GEV). The suggested design is aimed at reducing residential energy demand by providing for optimal automation of appliances. The recommended HOCP design will cover household electricity demand under sunny and rainy conditions without requiring additional electricity. On the other hand, the combination of electricity transmission SPV and V2H is sufficient to meet the demand for residential load in cloudy and sunny conditions. In this vein, HEMS with various constraints is implemented to perform proper system operations and satisfy load demand. The proposed algorithm attempts to characterize and perceive the situation of sources through the use of energy demand. The results show that H2V in combination with a renewable energy source can effectively reduce energy use and future residential applications during peak periods.

Extracting High-Precision Vehicle Motion Data from Unmanned Aerial Vehicle Video Captured under Various Weather Conditions

At present, there are many aerial-view datasets that contain motion data from vehicles in a variety of traffic scenarios. However, there are few datasets that have been collected under different weather conditions in an urban mixed-traffic scenario. In this study, we propose a framework for extracting vehicle motion data from UAV videos captured under various weather conditions. With this framework, we improve YOLOv5 (you only look once) with image-adaptive enhancement for detecting vehicles in different environments. In addition, a new vehicle-tracking algorithm called SORT++ is proposed to extract high-precision vehicle motion data from the detection results. Moreover, we present a new dataset that includes 7133 traffic images (1311 under sunny conditions, 961 under night, 3366 under rainy, and 1495 under snowy) of 106,995 vehicles. The images were captured by a UAV to evaluate the proposed method for vehicle orientation detection. In order to evaluate the accuracy of the extracted traffic data, we also present a new dataset of four UAV videos, each having 30,000+ frames, of approximately 3K vehicle trajectories collected under sunny, night, rainy, and snowy conditions, respectively. The experimental results show the high accuracy and stability of the proposed methods.

Propagation Model for Ground-to-Aircraft Communications in the Terahertz Band with Cloud Impairments

By operating over a large bandwidth, the terahertz (THz) frequency band (0.3–3 THz) promises to deliver extremely high data rates. While the use of this band in cellular communications systems is not expected to happen within the next decade, various other use-cases such as wireless backhauling and point-to-point wireless access are on the immediate horizon. In this study, we develop an analytical propagation model for the case of ground-to-aircraft communications by explicitly accounting for THz-specific propagation phenomena including path loss, attenuation by different types of clouds, and atmospheric absorption at different altitudes. To this aim, we first exhaustively characterize the geometric, molecular, and structural properties of clouds for different weather conditions and Earth regions. Then, by applying the tools of stochastic geometry, we present the closed-form expression for received power at the aircraft. Our numerical results show that the type of weather forming different compositions of clouds provides a major impact on the overall path losses and thus the attained data rates. Specifically, the difference between sunny and rainy conditions may reach 30–50 dB. The overall path loss also heavily depends on the region time and the difference may reach 10–30 dB. The worst conditions are logically provided by rain, where the additional attenuation on top of sunny conditions reaches 50 dB over the whole THz band. The Middle Earth zone is also the worst out of the considered regions with additional attenuation reaching 30 dB. The developed model can be used as a first-order approximation for ground-to-aircraft THz channel modeling.

Optimal scheduling for unit commitment with electric vehicles and uncertainty of renewable energy sources

The unit commitment (UC) problem is a typical mixed integer nonlinear programming problem related to power systems. As electric vehicles (EVs) and renewable energy sources (RESs; e.g., wind and solar power) have become integrated into the power system, the UC problem has become increasingly complex. With the continuous growth of the proportion of renewable energy based on wind and solar energy in the power supply structure on the supply side in the future, the random characteristics of the supply and demand sides of the power system will become more obvious, which will inevitably bring about the safety, stability and economic operation of the power system. The study of UC not only has great academic value, but also has important practical significance. The optimal scheduling of UC, including thermal, wind, solar, and EV power units was investigated. The objective function of optimal scheduling was to minimize the operating cost of the unit and optimize the charging and discharging costs of EVs. In view of power generation characteristics of RESs, an interval number was introduced to describe the uncertainties in the outputs of wind and solar power generation. The enhanced-interval linear programming is introduced to deal with the UC problem including EVs and uncertainty of RES. For better accuracy, wind power was considered for each of the four seasons (spring, summer, autumn, and winter) and solar power was divided into sunny, cloudy, and rainy conditions. To reflect the influence of EV charging and discharging on UC, three different charging and discharging pricing schemes were considered. Various scenarios were simulated using the CPLEX solver. The results showed that costs can be affected by season and climate. The interval number solution sets of the total cost and of the charging and unit costs were obtained by using interval number theory to describe the uncertainty of output in RESs; this provides a new approach for solving the UC optimization problem by integrating RESs. The charging and discharging of EVs can also affect costs. By encouraging the orderly charging and discharging of EVs, power load fluctuations could be reduced and peak-load shifting could be achieved. Different pricing schemes had different impacts on cost. The pricing scheme can not only effectively reduce the charging cost borne by EV owners, but could also make EVs profitable. This discovery provides a theoretical basis for guidance on the charging and discharging of EVs through charge and discharge price schemes. The simulation results reflect the relationship between economic cost and seasons/climate and confirm the suitability of using an interval number to describe uncertainty in energy generation.

Semi-Transparent Water-Based Trombe Walls for Passive Air and Water Heating

Trombe walls provide a passive source of heating and ventilation for buildings. However, Trombe walls can also cause overheating during hot and sunny weather conditions. In this work, we investigate the potential of a multifunctional Trombe wall design, comprising a tinted acrylic sheet submerged in a water wall that functions as a thermal storage medium. The tinted acrylic sheet absorbs incident light, which is then converted to heat and absorbed by the water. The proposed Trombe wall can function as a tinted semi-transparent window to add aesthetic value. Furthermore, heated water rises to the top of the Trombe wall where it can be removed, which provides the dual benefit of preventing overheating and providing a source of preheated water for applications within the building. Experimental results performed on a laboratory-scale Trombe wall prototype showed that the percentage of solar-simulated light energy incident onto the Trombe wall prototype, over a period of five hours, that was stored as thermal energy in the water increased from 60.3% to 83.2% when tinted glass was inserted in the water storage wall. Furthermore, the temperature of the water at the top of the Trombe wall reached ~56 °C, which is suitable to be used as pre-heated water in building applications.

Migratory hoverflies orientate north during spring migration.

Migratory hoverflies are long-range migrants that, in the Northern Hemisphere, move seasonally to higher latitudes in the spring and lower latitudes in the autumn. The preferred migratory direction of hoverflies in the autumn has been the subject of radar and flight simulator studies, while spring migration has proved to be more difficult to characterize owing to a lack of ground observations. Consequently, the preferred migratory direction during spring has only been inferred from entomological radar studies and patterns of local abundance, and currently lacks ground confirmation. Here, during a springtime arrival of migratory insects onto the Isles of Scilly and mainland Cornwall, UK, we provide ground proof that spring hoverfly migrants have an innate northward preference. Captured migratory hoverflies displayed northward vanishing bearings when released under sunny conditions under both favourable wind and zero-wind conditions. In addition, and unlike autumn migrants, spring individuals were also able to orientate when the sun was obscured. Analysis of winds suggests an origin for insects arriving on the Isles of Scilly as being in western France. These findings of spring migration routes and preferred migration directions are likely to extend to the diverse set of insects found within the western European migratory assemblage.

СЕЗОННАЯ ИЗМЕНЧИВОСТЬ ПОТОКОВ ДИОКСИДА УГЛЕРОДА, ЯВНОГО И СКРЫТОГО ТЕПЛА В СЕВЕРОТАЕЖНОМ ЛИСТВЕННИЧНОМ ЛЕСУ СРЕДНЕЙ СИБИРИ ПО ДАННЫМ ПУЛЬСАЦИОННЫХ ИЗМЕРЕНИЙ

The seasonal and daily variability of sensible and latent heat and carbon dioxide (CO2) fluxes, as well as the sensitivity of the fluxes to changing environmental conditions were derived by the eddy covariance flux measurements in an undisturbed northern-taiga larch forest on continuous permafrost in Central Siberia from the end of May to the end of September in 2013 and 2015. The measurements showed a high seasonal and daily variability of CO2, sensible and latent heat fluxes. It was found that whereas dry and sunny weather conditions of June and July in 2013 and 2015 resulted in lower daily latent heat fluxes as compared to sensible ones, mostly cloudy and rainy weather in the second half of the summer led to the reduced net radiation and increased latent heat fluxes. The daily values of gross primary production from the beginning of June to mid-August in 2013 and 2015 exceeded the values of the ecosystem respiration, and the forest ecosystem was the sink of CO2 from the atmosphere. The maximum CO2 uptake was observed in late June and early July, primarily due to high photosynthesis rates influenced by high incoming solar radiation, optimal air temperature, and soil moisture conditions. Since mid-August, the balance between the CO2 uptake and release was close to zero. The total net ecosystem CO2 exchange during the growing season of 2013 was -76.5 g C/m2, while it was slightly higher (-103.6 g C/m2) during the growing season of 2015, primarily due to higher air temperatures in June and greater precipitation in the summer months of 2015.

Time lag effect on solar radiation of tree sap flux density for different DBH ofLarix olgensis

AbstractTo clarify the role of tree characteristics and slope positions in the time lag between tree stem sap flux density (Js) and solar radiation (Rs). Plants of different diameter classes in a Larix olgensis near-mature forest (31 years old) in the hilly area of the Sanjiang Plain were used. The relationships between the time lag Js–Rs and tree characteristics, adjacent tree characteristics and slope positions were evaluated. Though both Js and Rs exhibited diurnal variation, they were not synchronized, thus leading to a time lag between Js and Rs. During the growing season, the change in Js lagged behind the change in Rs by 21.1 ± 6.9 min. Compared with tree height and crown width, the time lag Js–Rs was more dependent on diameter at breast height (DBH). The time lag between Js and Rs showed a linear increase with DBH. Compared with the characteristics of neighboring trees, the time lags Js–Rs were more dependent on their own tree characteristics. A significant relationship was not observed between the time lag Js–Rs and soil volumetric water content. The effects of tree characteristics, adjacent tree characteristics and slope positions on the formation of the time lag Js–Rs were compared. The time lag of Js on Rs was mainly controlled by the tree characteristics (DBH). DBH is an important factor that affects the time lag between Js and Rs under sunny conditions during the growing season of L. olgensis.

Pedestrian-injury severity analysis in pedestrian-vehicle crashes with familiar and unfamiliar drivers

Pedestrian injury in pedestrian-vehicle crash is significantly related to the driver, pedestrian, vehicle, crash and environment characteristics. Driver’s route familiarity has been found greatly associated with driving behaviours. Two-year pedestrian-vehicle crash data in Yunnan Province were studied to investigate the factors that affect pedestrian-injury severities in crashes with familiar and unfamiliar drivers by employing mixed logit models. Eight variables were found significant only in the familiar driver model. And six variables were found significant only in the unfamiliar driver model. Estimation findings indicate that the factors of early morning and sunny weather condition will be better modelled as random parameters in the model for familiar drivers and the same with the factors of rainy weather condition and afternoon peak in the model for unfamiliar drivers. Some more effective and targeted countermeasures are put forward for familiar drivers, unfamiliar drivers and transportation managers to reduce pedestrians’ injury severities.