Achieving Decentralized, Electrified, and Decarbonized Ammonia Production.

The rapid reduction in the cost of renewable energy has motivated the transition from carbon-intensive chemical manufacturing to renewable, electrified, and decarbonized technologies. Although electrified chemical manufacturing technologies differ greatly, the feasibility of each electrified approach is largely related to the energy efficiency and capital cost of the system. Here, we examine the feasibility of ammonia production systems driven by wind and photovoltaic energy. We identify the optimal regions where wind and photovoltaic electricity production may be able to meet the local demand for ammonia-based fertilizers and set technology targets for electrified ammonia production. To compete with the methane-fed Haber-Bosch process, electrified ammonia production must reach energy efficiencies of above 20% for high natural gas prices and 70% for low natural gas prices. To account for growing concerns regarding access to water, geospatial optimization considers water stress caused by new ammonia facilities, and recommendations ensure that the identified regions do not experience an increase in water stress. Reducing water stress by 99% increases costs by only 1.4%. Furthermore, a movement toward a more decentralized ammonia supply chain driven by wind and photovoltaic electricity can reduce the transportation distance for ammonia by up to 76% while increasing production costs by 18%.

The Imperial College Storm Model (IRIS) Dataset.

Assessing tropical cyclone risk on a global scale given the infrequency of landfalling tropical cyclones (TC) and the short period of reliable observations remains a challenge. Synthetic tropical cyclone datasets can help overcome these problems. Here we present a new global dataset created by IRIS, the ImpeRIal college Storm model. IRIS is novel because, unlike other synthetic TC models, it only simulates the decay from the point of lifetime maximum intensity. This minimises the bias in the dataset. It takes input from 42 years of observed tropical cyclones and creates a 10,000 year synthetic dataset of wind speed which is then validated against the observations. IRIS captures important statistical characteristics of the observed data. The return periods of the landfall maximum wind speed are realistic globally.

Influence of building spatial patterns on wind environment and air pollution dispersion inside an industrial park based on CFD simulation.

The "spatial pattern-wind environment-air pollution" within building clusters is closely interconnected, where different spatial pattern parameters may have varying degrees of impact on the wind environment and pollutant dispersion. Due to the complex spatial structure within industrial parks, this complexity may lead to the accumulation and retention of air pollutants within the parks. Therefore, to alleviate the air pollution situation in industrial parks in China and achieve the circular transformation and construction of parks, this study takes Hefei Circular Economy Demonstration Park as the research object. The microscale Fluent model in computational fluid dynamics (CFD) is used to finely simulate the wind flow field and the diffusion process of pollutants within the park. The study analyzes the triad relationship and influence mechanism of "spatial pattern-wind environment-air pollution" within the park and studies the influence of different spatial pattern parameters on the migration and diffusion of pollutants. The results show a significant negative correlation between the content of pollutants and wind speed inside the industrial park. The better the wind conditions, the higher the air quality. The spatial morphology parameters of the building complex are the main influences on the condition of its internal wind environment. Building coverage ratio and degree of enclosure have a significant negative correlation with wind conditions. Maintaining them near 0.23 and 0.37, respectively, is favorable to the quality of the surrounding environment. Moreover, the average height of the building is positively correlated with the wind environment condition. The rate of transport and dissipation of pollutants gradually increases as the average building height reaches 16 m. Therefore, a reasonable building planning strategy and arrangement layout can effectively improve the wind environment condition inside the park, thus alleviating the pollutant retention situation. The obtained results serve as a theoretical foundation for optimizing morphological structure design within urban industrial parks.

Risk assessment of deep-sea floating offshore wind power projects based on hesitant fuzzy linguistic term set considering trust relationship among experts.

The development of deep-sea floating offshore wind power (FOWP) is the key to fully utilizing water resources to enhance wind resources in the years ahead, and then the project is still in its initial stage, and identifying risks is a crucial step before promoting a significant undertaking. This paper proposes a framework for identifying risks in deep-sea FOWP projects. First, this paper identifies 16 risk criteria and divides them into 5 groups to establish a criteria system. Second, hesitant fuzzy linguistic term set (HFLTS) and triangular fuzzy number (TFN) are utilized to gather and describe the criterion data to ensure the robustness and completeness of the criterion data. Third, extending the method for removal effects of criteria (MEREC) to the HFLTS environment through the conversion of TFNs, under the influence of subjective preference and objective fairness, a weighting method combining analytic network process (ANP) and MEREC is utilized to calculate criteria weights, and the trust relationship and consistency between experts are used to calculate the expert weights to avoid the subjective weighting given by experts arbitrariness. Fourth, the study's findings indicated that the overall risk level of the deep-sea FOWP projects is "medium." Fifth, sensitivity and comparative analyses were conducted to test the reliability of the assessment outcomes. lastly, this research proposes risk management measures for the deep-sea FOWP project's establishment from economic, policy, technology, environment, and management aspects.

The genomic history and global migration of a windborne pest.

Many insect pests, including the brown planthopper (BPH), undergo windborne migration that is challenging to observe and track. It remains controversial about their migration patterns and largely unknown regarding the underlying genetic basis. By analyzing 360 whole genomes from around the globe, we clarify the genetic sources of worldwide BPHs and illuminate a landscape of BPH migration showing that East Asian populations perform closed-circuit journeys between Indochina and the Far East, while populations of Malay Archipelago and South Asia undergo one-way migration to Indochina. We further find round-trip migration accelerates population differentiation, with highly diverged regions enriching in a gene desert chromosome that is simultaneously the speciation hotspot between BPH and related species. This study not only shows the power of applying genomic approaches to demystify the migration in windborne migrants but also enhances our understanding of how seasonal movements affect speciation and evolution in insects.

Applicability of the generalized wind profile model over mountainous forests.

The analytical equation based on Monin-Obukhov (M-O) similarity theory (i.e., wind profile equation) has been adopted since 1970s for using in the prediction of wind vertical profile over flat terrains, which is mature and accurate. However, its applicability over complex terrains remains unknown. This applicability signifies the accuracy of the estimations of aerodynamic parameters for the boundary layer of non-flat terrain, such as zero-displacement height (d) and aerodynamic roughness length (z0), which will determine the accuracy of frequency correction and source area analysis in calculating carbon, water, and trace gas fluxes based on vorticity covariance method. Therefore, the validation of wind profile model in non-flat terrain is the first step to test whether the flux model needs improvement. We measured three-dimensional wind speed data by using the Ker Towers (three towers in a watershed) at Qingyuan Forest CERN in the Mountainous Region of east Liaoning Province, and compared them with data from Panjin Agricultural Station in the Liaohe Plain, to evaluate the applicability of a generalized wind profile model based on the Monin-Obukhov similarity theory on non-flat terrain. The results showed that the generalized wind profile model could not predict wind speeds accurately of three flux towers separately located in different sites, indicating that wind profile model was not suitable for predicting wind speeds in complex terrains. In the leaf-off and leaf-on periods, the coefficient of determination (R2) between observed and predicted wind speeds ranged from 0.12 to 0.30. Compared to measured values, the standard error of the predicted wind speeds was high up to 2 m·s-1. The predicted wind speeds were high as twice as field-measured wind speed, indicating substantial overestimation. Nevertheless, this model correctly predicted wind speeds in flat agricultural landscape in Panjin Agricultural Station. The R2 between observed wind speeds and predicted wind speed ranged from 0.90 to 0.93. The standard error between observed and predicted values was only 0.5 m·s-1. Results of the F-test showed that the root-mean-square error of the observed and predicted wind speeds in each secondary forest complex terrain was much greater than that in flat agricultural landscape. Terrain was the primary factor affecting the applicability of wind profile model, followed by seasonality (leaf or leafless canopy). The wind profile model was not applicable to the boundary-layer flows over forest canopies in complex terrains, because the d was underestimated or both the d and z0 were underestimated, resulting in inaccurate estimation of aerodynamic height.

[Analysis of the Spatiotemporal Distribution of Algal Blooms and Its Driving Factors in Chaohu Lake Based on Multi-source Datasets].

Eutrophication and harmful algae blooms are one of the common ecological and environmental problems faced by freshwater lakes all over the world. As a typical inland freshwater lake, Chaohu Lake exhibits a high level of eutrophication and algae blooms year-round and shows a spatiotemporal difference in different regions of the lake. In order to understand the basic regularity of the development and outbreak of algal blooms in Chaohu Lake, the data from the comprehensive water observation platform and remote sensing were integrated to obtain the spatiotemporal distribution of algal blooms from 2015 to 2020. Then, an evaluation model based on Boosted Regression Trees (BRT) was constructed to quantitatively assess the importance and interactions of various environmental factors on algal blooms at different stages. The results indicated that:① The occurrence of algal blooms in Chaohu Lake exhibited significant seasonal variations, with the cyanobacteria beginning to recover in spring and bring about a light degree of algal blooms in the western and coastal areas of Chaohu Lake. The density of cyanobacteria reached its maximum in summer and autumn, accompanied by moderate and severe degrees of algal bloom outbreaks. ② During the non-outbreak period, the variation in the cyanobacteria density was greatly affected by physical and chemical factors, which explained 80.3% of the variance in the change in cyanobacteria density. The high concentrations of dissolved oxygen content in the water column and the weak alkalinity (7.2-7.6) and appropriate water temperature (about 3℃) provided a favorable environmental condition for the breeding and growth of cyanobacteria. In addition, the onset of algal blooms was closely related to the air temperature steadily passing through the threshold. According to the statistics, the date of first outbreak of algal blooms in Chaohu Lake was 11 days or so after the air temperature steadily remained above 7℃. ③ During the outbreak period, the occurrence of algal blooms was influenced by the combination of cyanobacterial biomass and meteorological conditions such as temperature, wind speed, and sunshine duration. The cumulative contribution ratio of the four factors was as high as 95%, and each factor had an optimal interval conductive to the outbreak of algal blooms. Furthermore, the results of multi-factor interaction analysis indicated a larger probability of the outbreak of algal blooms in Chaohu Lake under the combined effect of high cyanobacteria density, suitable temperature, and the breeze. This study analyzed and revealed the spatiotemporal characteristics and the dominant influencing factors of algal blooms in Chaohu Lake at different stages, which could provide the scientific basis for the prediction, early warning, and disposal of algal blooms under the context of climate change.

Revisiting the contribution of different factors in determining the changes in potential evapotranspiration over China.

In this paper, a daily gridded observation data across China from 1961 to 2022 were used to calculate daily potential evapotranspiration (PET). The observed variables included daily temperature, sunshine hours, average wind speed, and average relative humidity. PET was determined using the Penman-Monteith method recommended by the Food and Agriculture Organization (FAO). The long-term trend of PET was investigated in six regions of China during different seasons. To further compressed the influence of various meteorological factors on the PET trend, the contribution of each meteorological element to the long-term trend of PET was analyzed. The results indicate the following: (1) PET reaches its peak during summer which values from 145 to 640 mm, while it is lowest during winter from 21 to 244 mm. (2) The spatial patterns of PET trend changes are relatively similar across the four seasons, characterized by a decrease in the eastern regions and an increase in the western regions. The reduction is most significant during the summer and the range of trend is from -2.04 to 1.48 mm/day, while the increase becomes more pronounced in the winter which trend is from -0.34 to 0.53 mm/day. (3) The contribution of factors varies significantly across different regions. In spring and autumn, RH and U have little difference in contribution from other factors. But tsun is varies different from regions, the contribution value is largest in the northwest and smallest in the northeast. However, during summer, tsun become the most significant contributor in the YZ and SE regions, while in winter, Tm emerges as the most significant contributor to the PET trend in all six subregions. In SW, the contribution from U2 is the smallest in all seasons, with RH and Tm being the two crucial factors determining the PET trend in this region.

Enhancing the control of doubly fed induction generators using artificial neural networks in the presence of real wind profiles.

This study tackles the complex task of integrating wind energy systems into the electric grid, facing challenges such as power oscillations and unreliable energy generation due to fluctuating wind speeds. Focused on wind energy conversion systems, particularly those utilizing double-fed induction generators (DFIGs), the research introduces a novel approach to enhance Direct Power Control (DPC) effectiveness. Traditional DPC, while simple, encounters issues like torque ripples and reduced power quality due to a hysteresis controller. In response, the study proposes an innovative DPC method for DFIGs using artificial neural networks (ANNs). Experimental verification shows ANNs effectively addressing issues with the hysteresis controller and switching table. Additionally, the study addresses wind speed variability by employing an artificial neural network to directly control reactive and active power of DFIG, aiming to minimize challenges with varying wind speeds. Results highlight the effectiveness and reliability of the developed intelligent strategy, outperforming traditional methods by reducing current harmonics and improving dynamic response. This research contributes valuable insights into enhancing the performance and reliability of renewable energy systems, advancing solutions for wind energy integration complexities.

Improving new energy subsidy efficiency considering learning effect: A case study on wind power.

Subsidy policies are instrumental in driving the development of new energy. However, the effective allocation of new energy subsidies over time is challenging given fiscal constraints. This study addresses this challenge by considering the learning effect associated with the new energy industry. A two-stage dynamic programming model is proposed to capture the investment decision-making process of companies under new energy subsidy policies and government subsidy setups. Theoretical findings suggest that company investment decisions in new energy are influenced by a guiding principle: The subsidy rate should be negatively correlated with the variation rate of production scale increment (VRPSI). We calibrate this investment decision principle using wind power data from 14 countries. According to this principle, excessive subsidy rates may result in a low VRPSI, thereby diminishing future investment profitability in the new energy industry and leading to subsidy inefficiency. Upon investigating the efficiency of annual subsidy allocation, we find that the subsidy rates were potentially set too high in 2014, 2016, and 2017. Furthermore, the government should exercise caution regarding an inefficient subsidy pattern whereby companies invest in new energy only when the subsidy rate exceeds a certain threshold, neglecting traditional power sources. It is crucial to note that although this study uses wind power industry data for calibration and simulation, the theoretical model can be broadly applied to other new energy industries and emerging industries with increasing marginal net profit.

Shifting from techno-economic to socio-ecological priorities: Incorporating landscape preferences and ecosystem services into the siting of renewable energy infrastructure.

This study examines the siting scenarios for renewable energy installations (REI) in a mountainous region of Europe (Switzerland), incorporating the external costs of ecosystem services and, innovatively, social preferences. This approach challenges the prevalent techno-economic siting paradigm, which often overlooks these externalities. To minimize the external costs of the scenarios while maximizing energy yield, Marxan, an optimization software, was employed. The energy target for all scenarios is set at 25 TWh/a, stemming from the energy gap anticipated due to the phase-out of Swiss nuclear reactors by 2050. This target is met using renewable energy infrastructure such as wind, roof-mounted photovoltaic, and ground-mounted photovoltaic systems. By integrating social preferences into the optimization, this study showcases a promising implementation that transcends the software's intended applications. It complements techno-economic approaches and offers alternative decision-making avenues. The conventional "roof first" strategy proved ineffective in preventing extensive land use for the development of new renewable energy infrastructure. Strategies incorporating ground-mounted photovoltaic infrastructure were more spatially, ecologically, and socially efficient than those without. The strategy optimized for energy yield exhibited the highest spatial efficiency but incurred significant ecosystem service costs and, surprisingly, had low social costs. In contrast, the strategy prioritizing ecosystem services was the most efficient in terms of ecosystem service costs but had elevated social costs and was spatially less efficient than other strategies. The strategy optimized for social preferences incurred the lowest social costs and excelled in spatial efficiency and ecosystem service costs. Notably, this strategy employed a limited number of planning units linked to both high ecosystem service and social costs. The findings underscore that incorporating social preferences significantly enhances the evaluation of siting options. This inclusion allows for the social acceptance of investments to be factored into costs, facilitating more informed and inclusive decisions.

Research on the dust-control technology of a double-wall attached-ring air curtain on an excavation face.

On the basis of the jet theory of airflow fields and the gas-solid two-phase flow theory, we studied the law of dust migration in a simulated dusting space. We used the control variable method and numerical simulation software to explore the airflow field and dust concentration distribution on the working surface of the dusting under different inlet wind speeds and different attached blades of the double-walled annular air curtain. We determined the speed of the inlet of the annular air curtain to be 30 m/s. When the angle of the attached blade was 30°, the dust concentration of the driver and other workers was controlled below 100 mg/m3, which produced the best dust control effect is the best. Using real data, we built a similar test platform to test the airflow field and dust concentration. Through data measurement and analysis, we proved that a dust control system with a double-wall attached-ring air curtain formed a circulating airflow field that could shield dust and effectively reduce dust concentration in the simulated space. The dust removal efficiency of total dust and exhaled dust reached 98.5% and 97.5%, respectively. We compared the test data and simulation results and concluded that the double-wall attached-ring air curtain could effectively ensure the safety of mine production and provide a better underground working environment for operators.

A decentralized approach for the aerial manipulator robust trajectory tracking.

This paper introduces a new decentralized control strategy for an unmanned aerial manipulator (UAM) constrained to the vertical plane. The control strategy comprises two loops: the first compensates for the aerial vehicle's impact on the manipulator; and the second one implements independent controllers for the aerial vehicle and the manipulator. The controller for the aerial vehicle includes an estimator to compensate for the dynamic influence of the manipulator, even if it is affected by external wind-gust disturbances. The manipulator has two revolute joints; however, it is modeled as an dynamically equivalent manipulator, with one revolute and one prismatic joint. The proposed control strategy's performance is evaluated using a simulator that includes the vehicle's aerodynamics and the manipulator's contact force and moment.

Effect of the modified painless blistering moxibustion with wheat-grain sized moxa cone on cough variant asthma of pathogenic wind attacking the lung: a randomized controlled trial. / æ”¹è‰¯æ— ç—›éº¦ç²’åŒ–è„“ç¸æ²»ç–—é£Žé‚ªçŠ¯è‚ºåž‹å’³å—½å˜å¼‚æ€§å“®å–˜ï¼šéšæœºå¯¹ç §è¯•éªŒ.

OBJECTIVES: To observe the clinical effect of the modified painless blistering moxibustion with wheat-grain sized moxa cone on cough variant asthma (CVA) differentiated as pathogenic wind attacking the lung and explore the influences on eosinophil count (EOS) in the peripheral blood and the content of interleukin-4 (IL-4) and tumor necrosis factor-α (TNF-α) in the serum of patients. METHODS: Ninety-two patients with CVA of pathogenic wind attacking the lung were randomly divided into an observation group and a control group, 46 cases in each group. In the observation group, the modified painless blistering moxibustion with wheat-grain sized moxa cone was applied to the unilateral Feishu (BL 13), Gaohuang (BL 43) and Zusanli (ST 36) in each session of treatment, once every 3 days. In the control group, budesonide and formoterol powder inhaler was delivered, 4.5 µg per inhalation, once every half an hour after breakfast and dinner; one more time of inhalation needed if the symptoms were not well controlled, but less than 6 times of inhalation per day. The duration of treatment was 8 weeks in both groups. Separately, before and after treatment, and during the 1-month follow-up after treatment completion, the score of the symptoms of traditional Chinese medicine (TCM) was observed in the two groups; using the lung function detector, the indexes of pulmonary function (forced expiratory volume in one second [FEV1], FEV1/forced vital capacity [FVC] and peak expiratory flow [PEF]) were determined, and the count of EOS in the peripheral blood and the content of IL-4 and TNF-α in the serum were determined before and after treatment; and the clinical effect was compared between the two groups. RESULTS: After treatment and in follow-up, the TCM symptom scores were decreased compared with those before treatment in the two groups (P<0.05), and the score in the observation group was lower than that of the control group in follow-up (P<0.05). After treatment, FEV1, FEV1/FVC and PEF were increased when compared with those before treatment in the two groups (P<0.05), and the count of EOS in the peripheral blood and the content of IL-4 and TNF-α in the serum were reduced (P<0.05); there was no statistical difference in these indexes between the two groups (P>0.05). After treatment, the total effective rate of the observation group was 95.7% (44/46), which was not different statistically in comparison with the control group (93.5% [43/46], P>0.05). In the follow-up, the total effective rate of the observation group was 95.7% (44/46), which was higher than that of the control group (78.3% [36/46], P<0.05). CONCLUSIONS: The modified painless blistering moxibustion with wheat-grain sized moxa cone may ameliorate the symptoms of CVA of pathogenic wind attacking the lung and improve the pulmonary functions, which is probably related to the regulation of the count of EOS in the peripheral blood and the content of IL-4 and TNF-α in the serum, thereby, reducing the inflammatory response.

Rainfall as a driver for near-surface turbulence and air-water gas exchange in freshwater aquatic systems.

Gas fluxes from aquatic ecosystems are a significant component of the carbon cycle. Gas exchange across the air-water interface is regulated by near-surface turbulence and can be controlled by different atmospheric forcing conditions, with wind speed and surface buoyancy flux being the most recognized drivers in empirical studies and modeling approaches. The effect of rainfall on near-surface turbulence has rarely been studied and a consistent relationship between rain rate and near-surface turbulence has not yet been established. In this study, we addressed some limitations still present in the quantitative understanding of the effect of rain rate on near-surface turbulence and on the resulting gas transfer velocity in freshwater. We performed controlled laboratory experiments over a wide range of rain rates (7 to 90 mm h-1) and estimated gas transfer velocities from high-resolution measurements of O2 concentration, while rain-induced turbulence was characterized based on particle image velocimetry. We found that the rain-induced dissipation rates of turbulent kinetic energy declined with depth following a consistent power-law relationship. Both energy dissipation rates and gas transfer velocity increased systematically with the rain rate. The results confirm a causal relationship between rainfall, turbulence, and gas exchange. We propose a power-law relationship between near-surface turbulent dissipation rates and rain rate. In combination with surface renewal theory, we derived a direct relationship between gas transfer velocity and rain rate, which can be used to assess the importance of short-term drivers, such as rain events, on gas dynamics and biogeochemical cycling in aquatic ecosystems.

Site selection optimization for 100% renewable energy sources.

The increase in the use of Renewable Energy Sources (RES) provides many advantages such as reducing the environmental problems and sustainability. In this study, a long-term optimum RES settlement strategic plan is conducted for 81 provinces in Turkey by considering real data. Biomass energy, solar energy, hydroelectric energy, geothermal energy, and wind energy are considered RES sources. Energy consumption until the 2050 year is estimated with the regARIMA method, and then a weighted goal programming model was developed in which the outputs of the regARIMA method and risk analysis are integrated. The results of the regARIMA method are tested, and the test results indicate that an R2 value close to 1 indicates that the model is suitable, a low and negative MPE value is neutral, and a MAPE value below 4% indicates high accuracy of the model. Using GAMS 23.5 optimization software program, the developed weighted goal programming model is solved optimally. In this integrated model developed, the objectives of minimizing the installation time, minimizing the investment cost, minimizing the annual cost, maximizing the carbon emission reduction, maximizing the usage time, and minimizing the risk are considered. When the results obtained regarding the number of installations according to the model are examined, the decisions are made for 53% wind energy, 23% biomass energy, 13% hydroelectric energy, 9% solar energy, and 2% geothermal energy. Computational results show that the effective solutions are obtained by minimizing the sum of goals values, covering all provinces in Turkey, and considering real data.

Effective-diode-based analysis of industrial solar photovoltaic panel by utilizing novel three-diode solar cell model against conventional single and double solar cell.

Currently, the majority of the country has moved to renewable energy sources for electricity generation, and power companies are concentrating their efforts on renewable resources. Solar, wind, hydropower, and biomass are examples of renewable resources; of these, due to a lack of non-renewable resources, the solar industry is expanding. All year long, solar electricity is available, and it creates a calm, quiet atmosphere. The majority of large and small companies, as well as individual consumers, have shifted to PV solar cells for electricity generation. A trustworthy and precise simulation design of a photovoltaic system prior to installation is required to predict a photovoltaic system's performance. The current research aims to build models for solar PV systems with one, two, and three diodes and determine which model is most appropriate for each environmental circumstance to forecast performance accurately. By contrasting the experimental data of solar panel with simulated results of single-, double-, and triple-diode models, this study examines the accuracy of each model. These models' comparative performance study has been done using the MATLAB/Simulink, taking into account the influence of changing model parameters and the performance of the models under varying climatic circumstances. These models, despite their simplicity, are quite sensitive and react to even a little change in temperature and irradiance. Under conditions of low solar irradiance or shading conditions, three-diode photovoltaic models are shown to be more accurate. We can forecast the power output of solar photovoltaic systems under changeable input circumstances by understanding the I-V curves with the help of the performance assessment of the models used in this work.

Wind-driven hydrodynamic characteristics of Lake Taihu, a large shallow lake in China.

As an essential drinking water source and one of the largest eutrophic shallow lakes in China, the management of Lake Taihu requires an adequate understanding of its hydrodynamic characteristics. Studying the hydrodynamic characteristics of Lake Taihu based on field observations is limited owing to its large area and the lack of flow field stability. Previous studies using hydrodynamic models experienced challenges, such as dimensionality and lack of dynamic response analysis between flow field and realistic wind; therefore, the results were still inconclusive. In this study, a 3D model of Lake Taihu, calibrated and validated based on field observations, was used to simulate and compare three scenarios: windless, steady wind, and realistic wind. The hydrodynamic characteristics of Lake Taihu were analyzed as close to the actual conditions as possible. The results showed that wind-driven currents dominated the flow field in Lake Taihu, and the horizontal velocity driven by wind was more than 6 times that without wind. Observing a stable flow field in Lake Taihu was difficult because of the variability of realistic wind. The hydrodynamic characteristics of Lake Taihu were defined as "strongly affected by wind," "higher on the surface and smaller at the bottom," and "difference between the surface and the bottom." Vertical turbulent kinetic energy can be used to characterize the variable flow field of a wind-driven lake and has a positive correlation with wind speed. Therefore, it could be used as a key component to predict water blooms with practical implications.

Identification of particle distribution pattern in vertical profile via unmanned aerial vehicles observation.

Below the boundary layer, the air pollutants have been confirmed to present the decreasing trend with the height in most situaitons. However, the disperiosn rate of air pollutants in the vertical profile is rarely investigated in detail, especially through in-situ measurement. With this consideration, we employed an unmanned aerial vehicle equipped with portable monitoring equipments to scrutinize the vertical distribution of PM2.5. Based on the original data, we found that PM2.5 concentration decreases gradually with altitude below the boundary layer and demonstrated an obvious linear correlation. Therefore, the vertical distribution of PM2.5 was quantified by representing the distribution of PM2.5 with the slope of PM2.5 vertical distribution. We used backward trajectories to reveal the causes of outliers (PM2.5 increasing with altitude), and found that PM2.5 in the high altitude came from the southwest. Besides, the relationship between the vertical distribution of PM2.5 and various meteorological factors was investigated using stepwise regression analysis. The results show that the four meteorological factors most strongly correlated with the slope values are: (a) the difference in relative humidity between the ground and the air; (b) the difference in temperature between the ground and the air; (c) the height of the boundary layer; and (d) the wind speed. The slope values increase with increasing the difference in relative humidity between ground and air and the difference in temperature between the ground and the air, and decrease with increasing boundary layer height and wind speed. According to the Random Forest calculations, the ground-to-air relative humidity difference is the most important at 0.718; the wind speed is the least important at 0.053; and the ground-to-air temperature difference and boundary layer height are 0.140 and 0.088, respectively.

Quantifying the physical demands undertaken by offshore wind technicians during a working day and casualty evacuations.

BACKGROUND: Offshore wind technicians (WTs) have been identified as having an occupation with high physical demands. OBJECTIVE: To characterise the physical demands of WTs, during the working day and when performing casualty rescues. METHODS: Data collection consisted of two components. Component A, 14 WTs (n = 13 male, 1 female) were monitored over three consecutive working days. The data collected consisted of: a questionnaire; heart rate and movement data; and accelerometer data. Component B, 5 WTs (n = 5 male) were assessed undertaking two simulated casualty evacuations. Heart rate and metabolic data were collected. RESULTS: A working day lasted 7.5 hrs to 9 hrs, with WTs covering, on average, 4.7 km on the turbine. WTs spent 28% of their time undertaking "light activity", 69% "moderate activity" and 3% working "vigorously". The greatest amount of time in a day was spent working on manual handling tasks such as torque and tensioning (up to 4 hours in total). Both rescues were performed largely aerobically, with similar cardiac and metabolic demands (14.56 (4.84) mL.kg-1.min-1 vs. 17.07 (3.54) mL.kg-1.min-1). Higher RPE values were reported for the rescue from within the Hub (median (range), 13 (12-14)) compared to down the ladder (11 (7-12)), likely due to a greater requirement to manoeuvre the casualty in tight spaces. CONCLUSION: The results presented characterise the physical requirements of WTs during the working day and two casualty evacuations. These data play an important role in supporting the job task analysis for WTs working in the offshore wind industry.