Light Wind Speed Research Articles

Microhabitat selection and niche overlap: Drivers of spider coexistence in a tropical limestone cave

AbstractStable temperature, humidity, and oligotrophy may be essential in microhabitat selection, shaping niche overlap and species coexistence within cave ecosystems. To explore this hypothesis, we assessed the distribution and microhabitat preferences of four non‐obligate cave‐dwelling spiders: Loxosceles anomala, Scytodes itapevi, Philoponella vittata, and the exotic Oecobius navus. Using 1‐m2 quadrats, we surveyed spider distribution and abundance in a limestone cave, considering environmental conditions and prey availability during wet and dry periods. Significant differences were observed between moist and dry periods regarding light intensity, wind speed, air temperature and moisture, potential prey, and the abundance of L. anomala. The exotic spider O. navus was more specialist, preferred brighter habitats, and showed lower niche overlap. Conversely, the three native species displayed greater niche overlap and preferred darker and more humid environments. Spatial disparities, rather than temporal variation, in species distribution underscored the influence of cave habitat conditions on species segregation. Furthermore, our findings highlighted the limited ability of the non‐native O. navus to occupy more illuminated cave areas, thereby potentially safeguarding these habitats against biological invasion by this species.

Environmental Factors and Management Strategies Influencing Sungkai (Peronema canescens Jack.) Population Dynamics in City Forest, West Wales, Universitas Indonesia Campus, Depok

Sungkai (Peronema canescens), commonly used as an ornamental plant for household demarcation due to its aesthetic appeal, also offers medicinal benefits, effectively utilized in treating diverse ailments encompassing diseases, infections, and inflammations. This study aims to investigate the population dynamics and growth parameters of sungkai in the City Forest, West Wales, Universitas Indonesia Depok, we are focusing on various environmental factors and management practices affecting their development. Measurements of light intensity, temperature, humidity, soil pH, moisture, and wind speed were conducted to assess their impact on sungkai growth. The acquired data undergoes analysis through established formulas, and the outcomes are depicted in diagrams and tables. Results revealed congruence in altitude and light intensity with ideal growth conditions, while discrepancies in air humidity, soil pH, and moisture posed potential limitations to sungkai plant development. Analysis of sungkai tree diameters showcased varied growth rates, possibly influenced by plant spacing and nutrient competition. Furthermore, proposed intensive care practices such as pruning, thinning, and pest management are suggested as vital strategies to optimize sungkai growth. Overall, addressing these environmental factors and employing suitable management practices could significantly contribute to sustaining and enhancing the sungkai population within the City Forest, West Wales, Universitas Indonesia Depok.

Enhancement of Mosquito Collection for Ultraviolet Light-Emitting Diodes Trapping System Using Cavity Reflectors

This research explores novel avenues for optimizing mosquito-catching efficiency using a multifaceted approach. While previous studies have primarily focused on singular parameters, such as light intensity or wind speed, this study delves into the intricate interplay between various factors. Experiment 1 challenges conventional wisdom by revealing a wider light divergence angle. When the reflective plate combined with the airflow board was set to 0 cm in length, the effectiveness of capturing mosquitoes was lower than that of the 3 cm unit, suggesting overlooked variables at play. Experiment 2 introduces a novel perspective by demonstrating the superior efficiency of the 5 cm unit, even with reduced wind speed and luminous area under optimized conditions, showcasing the significance of a holistic approach. Moreover, Experiment 3 uncovers nuanced insights, showcasing the differential performance of units in capturing small insects versus mosquitoes and moths, highlighting the need for tailored strategies. By integrating these findings, the study pioneers the development of two distinct mosquito collection units, emphasizing the critical importance of balancing diverse parameters for optimal results. The innovation lies in the thorough investigation of multifaceted optimization strategies, providing valuable insights to propel advancements in mosquito control technologies.

The diversity of aerial insect in coffee agroforestry, Dampit and Purwodadi district East Java Indonesia

Coffee is one of the export commodities in Indonesia. East Java is one of the largest Coffee supplies with land that is widely spread, such as in Malang and Pasuruan Regencies. The agroforestry system is applied in coffee cultivation, the system has different management from plantations for example the use of shade trees which will affect the structure of aerial insect diversity. Aerial insects play an important role in maintaining the balance of the ecosystem. The research objective was to determine the diversity and dominance of aerial insects in coffee agroforestry in East Java. The research method is exploratory, taking aerial insects using a yellow pan trap. The abiotic factors observed were light intensity, wind speed, temperature and humidity, and data analysis with past 4.03 program. The results of the study found 407 individuals in Dampit coffee agroforestry and 470 individuals in Purwodadi coffee agroforestry. The diversity and dominance index values were found to be the highest in Dampit coffee agroforestry. From the results of the analysis of abiotic factors, it is found that temperature and humidity in Dampit coffee agroforestry have higher values while wind speed and sunlight intensity of Purwodadi coffee agroforestry have higher values. The differences in the number and types of insects as well as the differences in the diversity and dominance index obtained, explained that the two study sites had differences in abiotic factors and shade trees.

Community Structure of Dragonflies (Odonata) at Garahan Resort, Sempolan, Perhutani, Forest Management Unit (KPH) Jember

A community is a conglomeration of diverse groups coexisting within a shared geographical location and temporal framework. Different approaches can be used to explain community structure, focusing on species diversity, species interactions, and functional organization. The biodiversity of dragonflies in Indonesia is significantly abundant. Dragonflies play multiple ecological roles and inhabit diverse habitats, as evidenced by recent research conducted in January 2023. This study aimed to investigate the composition and organization of the dragonfly community. The research design employed in this study is exploratory and descriptive. The identification of station sites through the purposive sampling method. The sampling locations consisted of a pine forest and the Garahan jungle. The road sampling approach utilizes the sweeping technique. The investigation yielded a total of thirteen distinct species of dragonflies. The study reveals the presence of two endemic species, Paragomphus reinwardtii and Heliocypha fenestrata, with a diversity index value (H’) of 1.653, falling into the medium group. The dominance index (D) exhibits a value of 0.263, indicating its classification within the low group. The evenness index (E) value at 0.401 falls into the medium group. A species similarity index (SI) of 75% is categorized as high. Canonical Corresponding Analysis (CCA) reveals a positive correlation between the species Ortherum Sabina, Orthetrum glaucum, Vestalis luctuosa, Diplacodes trivialis, Euphaea variegata, Coeliccia membranipes, Gynacantha subinterrupta, Paragomphus reinwardtii, and Zygonix ida with light intensity, air humidity, and wind speed.

Scalable, Green, and Cost-Effective Carbonized Sand for Efficient Solar Desalination.

Nowadays, sweet and drinkable water shortage is a global issue which has attracted widespread attention. Desalination of seawater as the greatest source of water on our planet using solar energy as the most abundant and green energy source for producing fresh water can help us address this issue. Interfacial solar desalination is a state-of-the-art, sustainable, green, and energy-efficient method that has been studied lately. One of the key parameters for researching this method with reasonable efficiency is a photothermal material. Herein, carbon-coated sand was synthesized using abundant, green, and low-cost materials (sand and sugar), and its performance as a photothermal material is investigated and reported. In this work, a three-dimensional (3D) system is introduced to develop the performance and efficiency of the system under real sun irradiation and natural circumstances. The salt rejection ability of the system is another important thing we should notice due to the high salinity of seawater that we want to desalinate. The superhydrophilic carbonized sand demonstrated a good evaporation rate of 1.53 kg/m2h and 82% efficiency under 1 sun irradiation and upright salt rejection ability, which exhibited its capability to be used in green solar-driven water vaporization technology for sweet water production. The effects of important parameters, including light intensity, wind speed, and environment temperature, on the evaporation rate using carbonized sand as a solar collector in a solar desalination system were studied in both laboratory and real systems.

Contributions of meteorology and nutrient to the surface cyanobacterial blooms at different timescales in the shallow eutrophic Lake Taihu

Quantitative assessments of the contributions of various environmental factors to cyanobacterial blooms at different timescales are lacking. Here, the hourly cyanobacterial bloom intensity (CBI) index, a proxy for the intensity of surface cyanobacterial biomass, was obtained from the geostationary satellite sensor Geostationary Ocean Color Imager (GOCI) over the years 2011–2018. Generalized additive model was applied to determine the responses of monthly and hourly CBI to the perturbations of meteorological factors, water stability and nutrients, with variation partitioning analysis used to analyze the relative importance of the three groups of variables to the inter-monthly variation of diurnal CBI in each season. The effects of environmental factors on surface cyanobacterial blooms varied at different timescales. Hourly CBI increased with increasing air temperature up to 18 °C but decreased sharply above 18 °C, whereas monthly CBI increased with increasing air temperature up to 30 °C and stabilized thereafter. Among all the environmental factors, air temperature had the largest contribution to the intra-daily variation in CBI; water stability had the highest explanation rate for the inter-monthly variation of diurnal CBI during summer (42.3 %) and autumn (56.9 %); total phosphorus explained the most variation in monthly CBI (18.5 %). Compared with cyanobacterial biomass (CB) in the water column, high light and low wind speed caused significantly lower CBI in July and higher CBI in November respectively. Interestingly, cyanobacterial blooms at the hourly scale were aggravated by climate warming during winter and spring but inhibited during summer and autumn. Collectively, this study reveals the effects of environmental factors on surface cyanobacterial blooms at different timescales and suggests the consideration of the hourly effect of air temperature in short-term predictions of cyanobacterial blooms.

Data generation method for power system operation considering geographical correlations and actual operation characteristics

Data generation methods for power system operation are the basis for many studies such as linear power flow models and data-driven models. On the one hand, the generated data can be used to test the performance of the model. On the other hand, the generated data can be used to train the model. In actual power systems, the operating data is not completely random, but conforms to certain operating laws, and has some typical characteristics, including geographic correlations and actual operation characteristics of thermal units. Taking the geographic correlations of renewable outputs as an example, the light density or wind speed in a certain area has similar characteristics. For another example, restricted by the unit cost of generating electricity, thermal unit outputs are at a relatively stable level rather than completely random. However, existing studies have not sufficiently considered these geographic correlations and actual operation characteristics. Therefore, this paper proposes a new data generation method considering geographic correlations and actual operation characteristics of thermal units. Specifically, the proposed method includes four steps: parameter estimation, sampling, generation benchmark settings, and system operation data calculation. To accurately characterize geographic correlations and actual operation characteristics of thermal units, the Eigendecomposition and unit commitment model are introduced into the proposed method. Numerical tests verify that the proposed method can guarantee the geographical correlations and actual operation characteristics of generated data.

An evaluation of meteorological data prediction over Washington, D.C.: Comparison of DCNet observations and NAM model outputs

This study presents an example of how outputs of operational and readily-available mesoscale numerical models can be adapted to initialize dispersion calculations within the urban surface roughness layer. Three years of urban meteorological observations from central Washington, DC, are compared against forecast outputs of the North American Mesoscale (NAM) model. NAM wind speed predictions underestimate the observations in light winds and overestimate the measurements in high winds. Average wind directions are consistent. However, an adjustment of the predicted direction of the plume by −20° is needed. The uncertainty associated with this adjustment is large in light NAM wind speed with no evident variation by season. The values of the standard deviation of the wind direction, σθ derived from NAM model outputs underestimate the observations by a small amount (about −1.5 to −2.5°). The results presented here indicate that mesoscale numerical model outputs can provide information adequate for dispersion calculations. However, levels of uncertainty associated with implementation of the suggested procedures increase with decreasing wind speed, causing considerable uncertainty in the implementation of adjustments as low wind speed conditions are approached. Results and recommendations reported here should not be extended to other numerical models or other cities without further testing.

IoT Based Renewable Energy Practicum Kit Design to Support learning and research

In the era of the industrial revolution 4.0, various industries are required to implement internet of things technology, one of which is in the energy industry, so that internet of things technology becomes knowledge that must be mastered by electrical engineering program students. The implementation of internet of things technology in education is the development of a renewable energy practicum kit design to support the learning of renewable energy power plant practices in small-scale field laboratories. The internet of things-based practicum device will make it easier for students or researchers to observe and analyze any changes in data due to changes in weather parameters or changes in load. This practicum kit can be used for the practice and research of Renewable Solar Power plant and Wind Power plant. The observable data are data on the generated side and the usage side. The generated side is in the form of parameters of weather and climate conditions such as light intensity and wind speed, electrical parameters such as current, voltage, power and energy while the usage side is in the form of parameters such as current, voltage, power, energy, power factor and frequency. With the practicum kit with Internet of Things technology, it is hoped that students or a researcher can prove practical results with existing theories quickly and easily.

How Vulnerable Are Patients with COPD to Weather Extremities?-A Pilot Study from Hungary.

Chronic obstructive pulmonary disease (COPD) is one of the most common causes of death globally, with increasing prevalence and years lived with disability (YLD). We aimed to investigate how extreme weather conditions were associated with the number of daily COPD-related emergency visits. We collected data regarding the number of daily emergency department (ED) visits made by patients with COPD in 2017, along with all relevant daily meteorological data for the same year. An analysis of the relationship between the number of COPD-related ED visits and extreme meteorological events was carried out. Extremely low temperatures (OR = 1.767) and dew points (OR = 1.795), extremely high atmospheric pressure (OR = 1.626), a high amount of precipitation (OR = 1.270), and light wind speed (OR = 1.560) were identified as possible risk factors for a higher number of COPD-related ED visits. In contrast, extremely high temperatures (OR = 0.572) and dew points (OR = 0.606) were found to be possible protective factors for COPD-related ED visits. By determining the meteorological risk factors for a high number of COPD-related ED visits, our study may help provide invaluable data for identifying vulnerable patient groups based on weather events, thus making more optimal capacity planning at the ED possible.

Modification of the microclimate and water balance through the integration of trees into temperate cropping systems

Climate change scenarios predict an increased occurrence of droughts and heatwaves, as well as extreme rainfall events in Central Europe. Alley cropping, which is the inclusion of rows of trees and shrubs in agricultural land, could enhance the resilience of cropping systems, as these systems are expected to positively modify the microclimate and water balance of croplands. This review analyses the effect of alley cropping on the microclimate and water balance, based on the available evidence from temperate alley cropping systems. Within alley cropping systems, the tree rows generate gradients in microclimatic variables, whereby strongest effects are observed in or close to the tree rows. Field-scale studies on light intensity (n=20), wind speed (n=4) and surface runoff (n=3) all reported a reduction compared to sole cropping systems. Effects on air temperature (n=10), relative humidity (n=5) and evapotranspiration (n=6) varied among studies, with the majority reporting a decrease in daytime temperatures (50% of studies), variable effects on relative humidity (60%) and an increase in evapotranspiration (50%) due to higher evapotranspiration by trees. Highest variation among studies was found for soil moisture, with 41% of studies reporting temporal and spatial differences within the system. This variation among studies likely depends on the purpose of the trees (short rotation coppice vs. fruit and/or timber trees) and design of the system. Also site context, such as topography, landscape diversity and climate, could play a role, but these factors are rarely taken into account. Only few studies investigated landscape-scale effects (n=3), such as groundwater recharge and moisture recycling. Future research should investigate the role of site context in the functioning of alley cropping systems and quantify landscape-scale effects. The process understanding gained from those studies will contribute to designing alley cropping systems that enhance the climate change resilience of current central European cropping systems.

Soybean performance under moisture limitation in a temperate tree-based intercropping system

CONTEXTTree-based intercropping (TBI) systems show promise in reducing the vulnerability of field crops to increasing water stress. TBI can generate several above- and belowground interactions between trees and crops. These interactions remain poorly documented, especially in the context of moisture limitation. OBJECTIVEThe objective of this study was to determine the performance of soybean within a TBI system under moisture limitation. We hypothesized that TBI generates both positive (near the alleyway centre) and negative (near the trees) effects on soybean performance and that these effects are accentuated when moisture availability decreases. METHODSA partial rainfall interception treatment (50% of the soil surface) in a soybean crop (stages R1 to R7) was installed for two years (2018 and 2019) in a TBI (50 trees/ha planted in 2012) in southern Quebec. TBI was composed of hybrid poplars (Populus deltoides × P. nigra) and different high-value hardwood species that were planted alternately within rows. A tree root-pruning treatment was also applied to understand belowground effects of tree roots on soybean growth under moisture limitation. Various microclimatic (light availability, wind speed and soil moisture) and soybean performance variables (leaf traits, 100-grain weight and yield) were measured at four distances from the tree row (4, 12 and 20 m, and control). RESULTS AND CONCLUSIONSRainfall exclusion decreased soil moisture and had a negative effect on soybean yield (−14%). The effect of the rain exclusion treatment on soybean performance was similar across all tree row distances and in both root-pruning treatments, which is contrary to our prediction. In 2018, an abnormally dry and warm season, yield near the alley centres was higher than near the tree row and tended to outperform the control. In 2019, a season with normal rainfall and temperature, soybean yield within the alleys was consistent among the different measured distances and did not differ from that in the control. Moderate shading at 4 m (−26% of PAR) was not associated with a change in soybean yield or leaf traits compared to other distances where shading was negligible or absent. Root pruning negatively affected soybean yield in 2018 (−14%) and 2019 (−22%), which is contrary to our prediction. SIGNIFICANCEThis case study adds to our knowledge regarding interactions between crops and trees in widely spaced TBI systems. TBI effects on spatial patterns of crop yield may vary substantially depending upon inter-annual variation in climatic conditions. This study suggests that more facilitative effects would prevail in dryer and warmer years, in contrast to near neutral effects in normal years.

Optimal scheduling strategy of electricity‐heat‐hydrogen integrated energy system under different operating modes

With the increasing penetration level of renewable energy in the integrated energy system (IES), water electrolysis for hydrogen production (WEHP) technology has become an effective solution to increase the capacity of renewable energy utilization. Therefore, this paper proposes to take WEHP and hydrogen fuel cell (HFC) as flexible resources to participate in the optimal scheduling of IES under grid-connected/off-grid operation mode. Firstly, focusing on the production, storage and utilization of hydrogen energy, a unified operation model of WEHP module is built by analyzing the differences of the three WEHP technologies. And then, “co-generation” model of HFC, the residual capacity and transportation cost model of hydrogen storage device (HSD) are built. Second, by analyzing the uncertainty of light intensity and wind speed, a prediction error correction method is proposed to improve the prediction data accuracy of renewable energy power generation. Third, taking the lowest daily operation cost as the objective function, the optimal scheduling model of electricity-heat-hydrogen integrated energy system under grid-connected/off-grid operation mode is constructed. On this basis, the operation scheduling model of electricity-heat-hydrogen integrated energy system is transformed into a mixed integer linear model by piecewise linearization method, and the model is solved by CPLEX solver. Finally, an example is given to verify the rationality of the proposed scheduling model in the grid-connected/off-grid operation mode. On one hand, reasonable optimal scheduling of multiple WEHP combination is helpful to reduce the daily operation cost of IES. On the other hand, by correcting the prediction data deviation of renewable energy power generation, the equipment output of electricity-heat-hydrogen integrated energy system can be more reasonable, which is helpful to reduce the daily operation cost and improve the operation reliability. The effects of sensitive factors such as the penetration level of renewable energy, the relative fluctuation of electricity price and hydrogen price on the operation cost of optimal scheduling scheme are further analyzed, which provides a theoretical reference for the optimal scheduling of IES.

Uji Efektifitas Sistem Smart Green House Bertenaga Surya Untuk Budidaya Tanaman

A greenhouse is one form of optimal environmental controlled monitoring for plant growth. Light intensity, air temperature, humidity, wind speed, and heat transfer, and mass transfer are microclimate parameters that are generally observed. Greenhouses can be integrated with the Internet of Things (IoT) to facilitate monitoring called smart greenhouses in real-time. Previously, a solar-powered IoT integrated plant monitoring system has been designed but its effectiveness is not yet known. The purpose of this study was to test the smart greenhouse system for plant cultivation including watering and providing light by utilizing solar panels as a source of electrical energy for the system. The research was carried out in several stages, namely system design, timer testing, pump testing, and watering and lighting. The effectiveness of the greenhouse system has been successfully tested. The test results show good accuracy. There is a slight difference between the test results and the comparison. However, the difference is still tolerable. The smart greenhouse systems can be used for plant cultivation.

Development of Artificial Intelligence Model to Forecast Photovoltaic Power Generation Including Airborne Particulate Matter

Purpose : This study aims to suggest an optimal model for predicting photovoltaic (PV) power generation by comparing single and hybrid models that include particulate matter in the atmosphere as input parameters.Methods : From December 2016 to December 2019, 1 MW-class PV power generation data in Jindo-gun, Jeollanam-do and meteorological data and particulate matter data from Mokpo were used. Radiation, sunshine time, pressure, temperature, humidity, wind speed, wind direction, snow load, precipitation, PM10, and PM2.5 were used as input parameters. We used single models such as random forest (RF), artificial neural network (ANN), long short-term memory (LSTM), and gate recurrent unit (GRU) and hybrid model such as LSTM-ANN and GRU-ANN. Coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE) were used to compare and evaluate the prediction performance of the models.Results and Discussion : The variable importance through RF was as follows: radiation (77.66%), day light hours (4.85%), pressure (4.16%), temperature (3.98%), humidity (2.25%), wind speed (2.21%), PM10 (2.72%), PM2.5 (1.65%), wind direction (1.44%), snow cover (0.05%), and precipitation (0.02%). GRU-ANN showed the highest R2 (0.838) among the models and lower epoch (8) than GRU using the early stop.Conclusion : The GRU-ANN model was the most suitable for forecasting PV power generation including particulate matter.

Spatial analysis of outdoor wet bulb globe temperature under RCP4.5 and RCP8.5 scenarios for 2041–2080 across a range of temperate to hot climates

Wet bulb globe temperature (WBGT) is commonly used to assess human physical activity limits and risk exposure to heat-related injury. Using Australia as a case study location, rates of change in WBGT across a range of temperate to hot and dry to humid climates in response to selected projected climate scenarios were investigated. An established physics-based method for estimating WBGT using standard meteorological data was incorporated into a spatial modelling framework to map WBGT for a baseline period (1986–2005) for mid-summer daytime, mid-summer early morning and mid-winter daytime scenarios, under clear sky conditions and both light (0.5 ms−1) and moderate (3.0 ms−1) wind speeds at a nominal resolution of 0.05 decimal degrees. The resulting maps of WBGT revealed significant spatial variability in the range and pattern of increased WBGT across the three baseline scenarios in response to projected change under RCP4.5 and RCP8.5 for 2041–2060 and 2061–2080 generated by the ACCESS1.0 climate model. Moderate wind speed scenarios produced significantly cooler WBGTs than the equivalent low wind speed scenarios, reducing mean modelled summer daytime WBGT by 3.2 °C, summer morning WBGT by 0.8 °C, and winter daytime WBGT by 3.0 °C. Projected future summer daytime WBGT under unshaded clear atmospheric conditions with light wind speeds can be expected to exceed the range of the commonly used heat categorisation system used to inform recommended restrictions on physical activity and regularly exceed 35 °C in northern Australia's equatorial and tropical climates by mid-century under RCP4.5 and RCP8.5. Summer early morning WBGT and winter daytime WBGT were projected to reach heat categories that would result in recommended restrictions in physical activity continuously (across consecutive 24-h periods) in summer and intermittently (for at least part of the day) year-round by 2050 with more severe conditions by 2070 and/or under RCP8.5 scenarios. Investigations into physical activity limits beyond the current highest heat category and the efficacy of the employed methodology to estimate WBGT above 35 °C using standard meteorological data are required to prepare for the projected warmer climate.

FAKTOR-FAKTOR YANG MEMPENGARUHI PRODUKTIVITAS KELAPA SAWIT (Elaeis guineensis jacq) PADA BERBAGAI AFDELING DI KEBUN BAH JAMBI PT. PERKEBUNAN NUSANTARA IV

North Sumatra Province, where the second-highest oil palm productivity in Indonesia, has successfully reached fresh fruit bunches (FFB) production of 5,775,631.82 tons in 2016. However, the level of oil palm productivity tends to be unstable and low. The purpose of this study was to identify and analyze factors influencing the level of oil palm productivity at the Bah Jambi Plantation PTPN IV, Simalungun Regency, North Sumatra Province. The method used in this study was the qualitative descriptive analysis method by collecting secondary data at research locations at 4 Afdeling Kebun Bah Jambi PT. Nusantara IV Plantation. The results of correlation and regression analysis showed that soil factor such as organic C, soil pH, cation exchange capacity and the availability of soil N, P, K and Mg is the most dominant factors in influencing the amount of oil palm productivity which have determination coefficient (R2) more than 90%. Meanwhile, climate factors such as evapotranspiration, duration of light exposure, wind speed and rainfall have the most role in influencing oil palm productivity which has a coefficient of determination (R2) of 95%, 94%, 88% and 33%.

PEMANFAATAN PANAS MATAHARI PADA DINDING LUAR BANGUNAN SEBAGAI SUMBER ENERGI LISTRIK MENGGUNAKAN GENERATOR TERMOELEKTRIK

This research utilizes solar thermal energy that absorbed by the outer wall of the building which facing north. The heat energy is converted into electrical energy using a thermoelectric generator type TEC 12706. To maintain the cold side area of TEC 12706 heatsinks are circulated with circulating water cooling fluid with a discharge of 1.8 lpm and the temperature is not more than 3oC. The study was conducted with a simulation tool composed of several materials such as glass, aluminum, styrofoam and heatsink. The test is conducted from 06.00 WIB until 18.00 WIB for 3 days. The parameters measured are light intensity, wind speed, water flow, temperature, electric voltage and electric current contained in the test equipment. The research results get a maximum output power of 0.0024 W, thermoelectric efficiency and system efficiency.

Computer Mathematical Statistics and Comparative Analysis of Meteorological Conditions in the Bohai Rim Region through Big Data Digitization

Based on the data of environmental monitoring stations and meteorological stations in typical city in the Bohai Rim region in June 2021 and June 2020. The air quality in June 2021 was better than that in the same period in 2020. Ozone (O3) was the primary pollutant in June 2021 and June 2020. The overall meteorological conditions in May 2021 were relatively favorable. In June 2021, the number of light wind days and wind speed had no significant impact on air quality compared with the same period last year. The dominant wind direction in June 2021 was southeast wind, which was not conducive to the increase of ozone concentration compared with the southwest wind frequency in the same period in 2020; the relative humidity in June 2021 was slightly higher year-on-year, which was slightly conducive to the hygroscopic growth of pollution; the static stability index in June 2021 was lower year-on-year, and the weather conditions for comprehensive pollution diffusion were preferred year-on-year; the height of the mixed layer in June 2021 was lower year-on-year, the vertical diffusion weather conditions were deviated year-on-year; the average temperature, sunshine hours and total radiation in June 2021 were all low, which was not conducive to the generation of ozone.