Average Annual Density Research Articles

Interactive and lag effects of environmental factors on the density of schistosome-transmitting Oncomelania hupensis: A twelve-year monthly repeated survey.

Schistosomiasis is a significant public health threat, and Oncomelania hupensis is the only intermediate host for schistosoma japonicum. We conducted 12-year monthly repeated surveys to explore the interactive and lag effects of environmental factors on snail density and to monitor their long-term and seasonal trends in a bottomland around the Dongting Lake region in China. Relevant environmental data were obtained from multiple sources. A Bayesian kernel machine regression model and a Bayesian temporal model combined with a distributed lag model were constructed to analyze interactive and lag effects of environmental factors on snail density. The results indicated the average annual snail density in the study site exhibited an increasing and then decreasing trend, peaking in 2013. Snail densities were the highest in October and the lowest in January in a year. Normalized Difference Vegetation Index (NDVI) and water level were the most effective predictors of snail density, with potential interactions among temperature, precipitation, and NDVI. The mean minimum temperature in January, water level, precipitation and NDVI were positively correlated with snail density at lags ranging from 1 to 4 months. These findings could serve as references for relevant authorities to monitor the changing trend of snail density and implement control measures, thereby reducing the occurrence of schistosomiasis.

A decision support model for planning of spatial large extent biomass to bioenergy procurement network

This study presents a strategic-tactical decision model with two main objectives: (i) identifying the spatial distribution and estimating the harvestable biomass potential of agricultural farms within a complex landscape; and (ii) optimizing the placement of bioenergy facilities to minimize total transportation costs. Remote sensing techniques combined with spatial analyses were utilized to discriminate agricultural lands from other land-cover types. Field-data measurements were then employed to estimate the quantity of available biomass. Subsequently, a bi-level optimization model was developed to determine optimal bioenergy facility locations and calculate transportation costs. The model was applied to a 20000 km2 region in northeastern Iran. The results revealed an average annual biomass density of 4.20 Mg ha−1 from agricultural lands, corresponding to 1867 Gg of biomass across the region. The optimal solution involved placing two bioenergy facilities within a 75 km radius to collect residues biomass, resulting in a delivery cost of $16 kWh−1.

Assessment of wind energy resource in the western region of Somaliland

As the population of Somaliland continues to grow rapidly, the demand for electricity is anticipated to rise exponentially over the next few decades. The provision of reliable and cost-effective electricity service is at the core of the economic and social development of Somaliland. Wind energy might offer a sustainable solution to the exceptionally high electricity prices. In this study, a techno-economic assessment of the wind energy potential in some parts of the western region of Somaliland is performed. Measured data of wind speed and wind direction for three sites around the capital city of Hargeisa are utilized to characterize the resource using Weibull distribution functions. Technical and economic performances of several commercial wind turbines are examined. Out of the three sites, Xumba Weyne stands out as the most favorable site for wind energy harnessing with average annual power and energy densities at 80 m hub height of 317 kW/m2 and 2782 kWh/m2, respectively. Wind turbines installed in Xumba Weyne yielded the lowest levelized cost of electricity (LCOE) of not more than 0.07 $/kWh, shortest payback times (i.e., less than 7.2 years) with minimum return on investment (ROI) of approximately 150%.

Variation pattern of crustacean zooplankton in a bigheaded carps-dominated reservoir

The relationship between crustacean zooplankton and (planktivorous) fish has not been well clarified in bigheaded-carps-dominated reservoirs, for most of the past studies to explore that kind of knowledge above are often obtained from the studies in temperate lakes and/or shallow lakes. The limitation of these studies is that crustacean zooplankton lack of either large grazers such as the bigheaded carps or the vertical migrating space for zooplankton to avoid predation by planktivorous fish. Reservoirs are more and more important drinking water source for human consumption, so a better environmental management of reservoirs will rely on a better understanding on the relationship between zooplankton and fish in bigheaded carp dominated reservoirs. To help reach that goal, we investigated the structure and variation of zooplankton and studied the relationship between zooplankton and fish in Tangpu reservoir, Zhejiang province, China. Our results showed that the species of crustacean zooplankton were richer. A total of 59 species of crustacean zooplankton were detected, including 33 species of copepods and 26 species of cladoceran, and dominated by larger species. The density of crustacean zooplankton varied between 15.5–68.5 ind./L with an annual average density of 24.9 ± 14.4 ind./L, it is higher in this planktivorous carps dominated deep reservoir than in many carp-less-dominated reservoirs or in shallow lakes. We also found that zooplankton and fish had a differential vertical distribution, i.e., zooplankton occurred 5 m–10 m but fish occurred 0.5 m–10 m in many months of the year. This could well explain why zooplankton were not reduced and not dominated by small species in bigheaded carps dominated reservoir, so we concluded that in planktivorous carp dominated deep reservoir ecosystems, zooplankton might not compete directly with planktivorous carps for phytoplankton, instead by distributing or migrating to deeper water column, they may survive and thrive on the phytoplankton in deeper column and the detritus resulted from the feces of planktivorous fish, thus might be able to coordinately improve water quality with planktivorous fish.

Ecological characteristics and seasonal changes of macrozoobenthos in the waters of Miaodao Archipelago, China

To understand the macrozoobenthic community composition and spatial-temporal distribution characteristics of macrobenthos in the waters of Miaodao Archipelago, Yantai, Shandong and its response to habitat changes, we conducted surveys of macrobenthos and environmental elements in the waters of Miaodao Islands in May (spring), August (summer), and October (autumn) in 2022. Results showed that a total of 127 macrozoobenthic species were recorded, with Mollusca and Annelida (Polychaeta) as the dominant taxa, consisting of 47 and 45 species, respectively. The key dominant species included Sternaspis chinensis, Glycinde bonhourei, Moerella hilaris, and Amphioplus (Lymanella) japonicus. The average annual density and biomass of macrozoobenthos were 190 ind·m-2 and 28.69 g·m-2, respectively. There was no significant seasonal differences in density and biomass. The Shannon diversity index (H), evenness index (J), and richness index (D) averaged 3.10, 0.90, and 2.40, respectively. Cluster analysis results showed low similarity coefficients of community among the three seasons, suggesting a distinct distribution pattern. Factors such as bottom seawater temperature, chlorophyll a, nutrient, sediment grain size, and organic matter content could significantly influence the structure and diversity of macrozoobenthic community. Compared with historical research data, the Changdao National Wetland Nature Reserve and the implementation of enclosure aquaculture have led to notable changes in the dominant species of macrobenthos. Specifically, there was a noticeable decline in both density and H, and an increase in biomass and J. Additionally, body size of benthic fauna was transitioning from small to big.

Spatiotemporal dynamics and driving factors of green-blue space in High-Density Cities: Evidence from central Nanjing

Urban green–blue space (UGBS) plays a crucial role in Chinese cities, occupying more than half of the built-up areas. Understanding the spatiotemporal dynamics and driving factors of UGBS in central Nanjing during rapid urbanization is important for studying UGBS evolution in high-density urban-area environments, providing a fundamental basis for related research and policy formulation. This study utilized remote sensing images to estimate the extent of UGBS from 2000 to 2020 and analyzed the evolution using the intensity of area change, a land transfer matrix, the multi-order adjacency index, and a boosted regression tree model. This study revealed the spatiotemporal dynamics and driving factors of UGBSs in central Nanjing from 2000 to 2020: (1) between 2000 and 2020, there was a 4.0% net increase in the total area of UGBSs in central Nanjing. (2) UGBS primarily showed marginal-type expansion, accompanied by proximity-type expansion. Spatially, new green–blue patches tended to cluster around large pre-existing natural green–blue patches. Furthermore, the expansion of UGBS shifted from the urban periphery to the urban interior. (3) Natural factors exerted a greater influence (88.3%) than socioeconomic factors (11.7%) on the expansion of UGBS. Average annual radiation (43.4%), elevation (16.5%), slope (15%), aspect (13.4%), and population density (2.8%) were the primary driving factors. Our results contribute to understanding changes in UGBS and the driving factors behind these changes, thereby providing support for the future planning, protection, and sustainable development of UGBS.

Environmental factors influencing biomass and bulbil production of Nitellopsis obtusa in Lake Koronis, Stearns County, Minnesota

Starry stonewort [Nitellopsis obtusa (Desvaux) J. Groves] is a green macroalga in the family Characeae that is native to Eurasia. In the United States it has invaded many waterbodies across the northern tier from New York to Minnesota. In Minnesota, starry stonewort often grows later into the growing (September to December) season than most native species; however, the environmental factors that influence this life history trait are not well understood. Starry stonewort was harvested every 3 wk from May to November in 2020 and 2021 from four locations in Lake Koronis, Stearns County, MN. Light, water pH, and water temperature were also collected to correlate these variables to starry stonewort growth. Rhizoid biomass had weak negative correlations with temperature (rs ¼ 0.19) and pH (rs ¼ 0.14). Bulbil biomass had weak negative correlations with temperature (rs ¼ 0.24), pH (rs ¼ 0.31), and light transmittance (rs ¼ 0.11). Bulbil density had weak negative correlations with temperature (rs ¼ 0.23), pH (rs ¼ 0.29), and light transmittance (rs ¼ 0.10). Bulbil production was highest between October and November of each year. Bulbil biomass and density was lower in 2020 (4.6 g m2 and 1,229 bulbils m2) thanin2021(14.7gm2 and 5,211 bulbils m2). The average annual bulbil density was 1,537 bulbils m2 and ranged from 0 to 157,000 bulbils m2. The ability of starry stonewort to grow in dense mats and produce large quantities of bulbils contributes to the difficulty of controlling infestations. Bulbils are a method of spatial and temporal distribution that can allow for recolonization of previously treated areas.

Wind Power Potential of Kaniga Region, Rwanda

The purpose of this study was to investigate the potential of wind power in Kaniga, Rwanda. Wind speed and wind direction are the most important characteristics for assessing wind energy potential of a location using suitable probability density functions. In this study, a hybrid-Weibull probability density function was used to analyze data from Kaniga station. Kaniga is located in Gicumbi District, in the Northern Province of Rwanda. Onsite hourly wind speed and wind direction data for the year 2022 were analyzed using Computer programmes. The research was conducted to reveal the wind power potential of Kaniga and other major wind stations in the country as an approach to address energy shortage problem in the country. It was found that the average annual wind speed for Kaniga, Nyarwambu, and Byumba were 4.5m/s, 3.7m/s and 4.1m/s respectively, while corresponding dominant wind directions for the stations were 3200, 1800 and 1500 respectively. The average annual wind power density of Kaniga was found to be 1,285.4W/m2, while the annual power densities for Nyarwambu and Byumba were determined as 689.4W/m2 and 805.4W/m2 respectively. The other stations in Rwanda have the average annual power densities ranging from 6.99 W/m2 to 138.2W/m2. From these findings, it is clear that Kaniga has the greatest wind power potential among all other studied wind stations in the country.

Assessment of Tidal Current Energy Resources in the Pearl River Estuary Using a Numerical Method

In this paper, a numerical method is employed to assess tidal current energy resources in the Pearl River Estuary, China. The numerical model for tidal current simulation in the estuary is developed based on the MIKE 21 model, which enables numerical simulations in estuaries, coastal areas, and oceans. The model has a grid resolution that varies from about 2500 m at the open boundary to 500–1000 m inside the estuary. Extensive model validation is performed by comparing the model predictions with field observations of tidal level and velocity at various stations in the Pearl River Estuary. The tidal characteristics are thoroughly analyzed. Energy fluxes and power densities are calculated along selected cross sections to evaluate the feasibility of tidal energy development in the Pearl River Estuary. The results indicate that the distribution of annual average tidal current power density in the Pearl River Estuary generally aligns with the spatial distribution of tidal currents. The annual average power density of tidal energy is typically below 0.10 kW/m2. The theoretical potential of tidal current energy resources in the Pearl River Estuary is assessed to be approximately 11,000 kW.

Spatiotemporal Analysis of Landscape Ecological Risk and Driving Factors: A Case Study in the Three Gorges Reservoir Area, China

Landscape ecological risk is considered the basis for regional ecosystem management decisions. Thus, it is essential to understand the spatial and temporal evolutionary patterns and drivers of landscape ecological risk. However, existing studies lack exploration of the long-term time series and driving mechanisms of landscape ecological risk. Based on multi-type remote sensing data, this study assesses landscape pattern changes and ecological risk in the Three Gorges Reservoir Area from 1990 to 2020 and ranks the driving factors using a geographical detector. We then introduce the geographically weighted regression model to explore the local spatial contributions of driving factors. Our results show: (1) From 1990 to 2020, the agricultural land decreased, while forest and construction land expanded in the Three Gorges Reservoir Area. The overall landscape pattern shifted toward aggregation. (2) The landscape ecological risk exhibited a decreasing trend. The areas with relatively high landscape ecological risk were primarily concentrated in the main urban area in the western region of the Three Gorges Reservoir Area and along the Yangtze River, with apparent spatial aggregation. (3) Social and natural factors affected landscape ecological risk. The main driving factors were human interference, annual average temperature, population density, and annual precipitation; interactions occurred between the drivers. (4) The influence of driving factors on landscape ecological risk showed spatial heterogeneity. Spatially, the influence of social factors (human interference and population density) on landscape ecological risk was primarily positively correlated. Meanwhile, the natural factors’ (annual average temperature and annual precipitation) influence on landscape ecological risk varied widely in spatial distribution, and the driving mechanisms were more complex. This study provides a scientific basis and reference for landscape ecological risk management, land use policy formulation, and optimization of ecological security patterns.

Urticating macromedusae and stinging bathers on the South Atlantic coast: Oceanographic and climatological conditions of Olindias sambaquiensis (Müller, 1861) outbreaks

Incidents of bathers being stung by jellyfish on the coast of southern Brazil have been monitored from 2012 to 2022 to identify the species involved and to search for patterns of behavior in different summer seasons. For 10 years of monitoring, data on occurrence, density and the crossing with the abiotic variables of temperature and salinity of the water and wind direction were obtained. During the investigated period, seven species of macro jellyfish were recorded out, four of them were urticating species, in wich Olindias sambaquiensis was the most frequent and abundant. Based on physical-chemical data on the seawater in this area, the cohorts, and consequently the success in the recruitment and the density of the O. sambaquiensis, may be related with years of low salinity of these Coastal Water. This hydrozoan was also the only species that showed a correlation between average annual density values and incidents of bathers being stung in subsequent summers. Likewise, on a monthly time scale, incidents of stings were correlated with winds from the south quadrant that could promote the transport of organisms to the beach region. A predictive model of the occurrence of jellyfish stinging events is presented and applied for the summer of 2023.

The Density of Aedes albopictus in a High-Latitude and High-Risk Dengue Fever Transmission Region in Shandong Province, Northern China.

Background: A total of 79 cases of dengue fever were reported in Jining County in 2017, which is currently the northernmost focal point of local cases of dengue fever diagnosed in China. This study aimed to evaluate the density of mosquito vectors before and after the outbreak of dengue fever and provide novel reference data for the prevention and control of the disease. Methods: The light traps were set to collect mosquitoes in 2017 and 2018 to assess adult mosquito density and species composition. We used the human-baited double net trap to determine the biting rate. In addition, the Breteau index (BI) was calculated to evaluate the density of Aedes albopictus in Jining, Shandong Province. The annual average densities of Ae. albopictus in 2017 and 2018 were 0.046 and 0.066 f/t/h, respectively. Results: The average biting rate was 0.69 f/m/h in 2018. There was no significant difference found in Ae. albopictus density and biting rate in the various months. The average BI of Jining was 38.67 and 11.17, respectively. There was a statistically significant difference observed in the BI between 2017 and 2018 (Kruskal-Wallis test, χ2 = 16.926, df = 1, p < 0.001). Conclusion: BI can serve as an important indicator to determine the spread of dengue fever. The findings indicted that the growing density of adult Aedes mosquitoes should be focused on, with biting rates being a potential indicator of future outbreaks. Overall, the various control measures that were implemented were effective and should be introduced in other high-risk areas.

Environmental heterogeneity affecting spatial distribution of phytoplankton community structure and functional groups in a large eutrophic lake, Lake Chaohu, China

The growth and development of phytoplankton are influenced by physico-chemical parameters, which can also affect the spatial distribution of phytoplankton community structure. However, it is unclear whether environmental heterogeneity caused by multiple physico-chemical factors can affect the spatial distribution of phytoplankton and its functional groups. In this study, we investigated the seasonal variation and spatial distribution of phytoplankton community structure and its relationships with environmental factors in Lake Chaohu from August 2020 to July 2021. We recorded a total of 190 species from 8 phyla, which were divided into 30 functional groups, including 13 dominating functional groups. The average annual phytoplankton density and biomass were (5.46 ± 7.17) × 107 cells/L and 4.80 ± 4.61 mg/L, respectively. The density and biomass of phytoplankton were higher in summer ((14.64 ± 20.34) × 107 cells/L, 10.61 ± 13.16 mg/L) and autumn ((6.79 ± 3.97) × 107 cells/L, 5.57 ± 2.40 mg/L), with the M and H2 of dominant functional groups. The dominant functional groups were N, C, D, J, MP, H2, and M in spring, whereas functional groups C, N, T, and Y dominated in winter. The distribution of phytoplankton community structure and dominant functional groups exhibited significant spatial heterogeneity in the lake, which was consistent with the environmental heterogeneity of the lake and could be classified into four locations. Location I had higher phytoplankton density and biomass than the other three locations. Additionally, dominant functional groups M, C, and H2 were present throughout the lake, and all 13 dominant functional groups were observed in Location II. Our findings suggest that environmental heterogeneity is a key factor influencing the spatial distribution of phytoplankton functional groups in Lake Chaohu.

Green Energy: An Ideal Energy Solution for Sustainable Development of Afar Region, Ethiopia

Green energy is the primary concern for the sustainable development of Ethiopia’s Afar region. The study’s goals are to present scientific evidence of the Afar region’s energy potential to researchers and industry sectors. We used solar shortwave, radiation transfer model, miniscale meteorological model for the Weather Research Forecast (WRF), and spatial and temporal simulation as research techniques. The data show that the Afar region has an energy potential of 239.9 W/m2 average solar radiation flux, 2.102 MW·h/m2 average annual solar density, 131.18 W/m2 average wind power density at h = 10 m , and 204.5 W/m2 average wind power density at h = 50 m . We discovered that solar energy and wind energy are potential energy sources in the Afar region for energy consumption such as solar cooking, solar lighting, and small DC applications.

Three-dimensional Tidal Dynamic Characteristics and Tidal Current Energy Evaluation in the Southern Sea Area of Hainan Island

Tidal current energy is a kind of marine renewable energy. It has broad application prospects. In this paper, a three-dimensional tidal current numerical model was established, and the model was verified by the measured data of the tide level station. Based on the numerical model, the tidal current feature and tidal current energy distribution were accurately simulated and analyzed in the southern sea area of Hainan Island. The results showed that the annual average velocity of the current was evenly distributed among the space in the study area. But the annual cumulative time of typical velocity in different sea areas was different in space. C2 had more accumulative time for the low-velocity range (<0.4m/s) of the surface, while C1 had more accumulative time for the low-velocity range (<0.3m/s) of the water depth of 8.5m. C3 sea area had more accumulative time in the high-velocity range at the surface (0.4~2.0m/s) and water depth of 8.5m (>0.3m/s). And the area with the highest annual average tidal current energy density at the water depth of 8.5m was C3, which is up to 128.40w/m2. C2 sea area had the smallest energy, only 62.63w/m2. Compared with C1 and C2 sea areas, the C3 area should be developed emphatically when developing tidal current energy resources in this sea area.

Effects of Land Use and Physicochemical Factors on Phytoplankton Community Structure: The Case of Two Fluvial Lakes in the Lower Reach of the Yangtze River, China

Potential changes in phytoplankton community structure in shallow lakes due to land use could pose a serious threat to ecosystem sustainability and functioning. Nevertheless, this effect has not been analyzed in detail. In this study, we chose two adjacent lakes, the main land use types around them are farmland and forest, respectively. We investigated the spatial differences in the phytoplankton community structure, water quality physicochemical parameters, and land use patterns in the two lakes. The results indicated that the annual average cell density and biomass of phytoplankton in the former were 1.84 times and 2.38 times that of the latter, respectively. The results of Pearson correlation and Redundancy analysis showed that total nitrogen (TN), total phosphorus (TP), water depth (WD), and water temperature (WT) were the main environmental factors influencing the structural changes of phytoplankton communities in the two lakes. The results indicated that different land use patterns, such as farmland and towns around the lake, increase the nitrogen (N) and phosphorus (P) content of the lake, while the forests distributed around the lake can reduce the N and P entering the lake, which is probably the main reason for the spatial difference in the characteristics of phytoplankton communities in the two lakes. Our results highlight that land use significantly affects the community structure of phytoplankton by influencing physicochemical factors in water bodies. Our study can provide guidance for pollution control and water quality management of shallow lakes.

Phytoplankton community structure and water ecological assessment in the Three Gorges Reservoir

2020年是长江禁渔开局之年,三峡库区作为长江的重要生态屏障,其水生态环境健康对长江大保护的实施具有重要意义。本文于2020年8月、11月及2021年1月、4月在三峡库区干支流共设置19个断面探究浮游植物群落结构特征,并利用生物量、多样性指数、综合营养状态指数和浮游植物Q指数等多种评价方法评价三峡库区水生态健康并分析其影响因素。结果表明:(1)三峡库区共鉴定出浮游植物8门105属266种,年平均丰度为6.4×10⁴ cells/L,年平均生物量为0.038 mg/L。不同季节优势种组成不同,变异直链藻(Melosira varians Agardh)、骨条藻(Skeletonema spp.)、脆杆藻(Fragilaria spp.)为全年优势种。(2)三峡库区共划分24个功能群,B、D、MP、S1、P、Y为优势功能群。RDA分析表明,电导率、总氮、化学需氧量、总磷、pH、总溶解性固体与三峡库区四季功能群呈现显著关系。(3)相较于丰度、生物量和多样性水质评价结果,浮游植物Q指数更适用于三峡库区水生态评价,显示三峡库区干流水生态环境总体较好,但春、夏两季支流浮游植物丰度、生物量显著升高和浮游植物Q指数的降低在一定程度上影响了干流水生态健康,成为三峡库区面临的主要风险。因此更应充分做好支流水华监测、预警,充分利用干流水生态调度,保障三峡库区水生态环境健康。;The year 2020 is the first year of the 10-year fishing ban in the Yangtze River. As an important ecological barrier of the Yangtze River, the water ecological environment health of the Three Gorges Reservoir (TGR) is of great significance to the implementation of the Yangtze River protection. Nineteen sites were set in the main and tributaries of the TGR in year 2020 (August and November) and 2021 (January and April) to explore the composition of phytoplankton community, and multiple assessment methods such as biomass, diversity index, comprehensive trophic status index and phytoplankton Q index were used to evaluate the water ecological health of the TGR area and analyze its influencing factors. The results showed that: (1) The 266 taxa of phytoplankton belonging to 105 genera in 8 phyla were identified,the average annual density was 6.4×10⁴ cells/L and an average annual biomass was 0.038 mg/L. The composition of dominant species varied seasonally. Melosira varians Agardh, Skeletonema spp. and Fragilaria spp. were the dominant species all year round. (2) The phytoplankton in the TGR was classified into 24 functional groups, of which B, D, MP, S1, P and Y were the dominant functional groups. Redundant analysis showed that Cond, total nitrogen, COD, total phosphorus, pH and total dissolved solid were the main environmental factors affecting the functional groups in the TGR. (3) Compared with the assessment results of density, biomass and the diversity of water quality, phytoplankton Q index were more suitable for the assessment of water ecology in the TGR. Results showed that the water ecological environment of the main stream in the TGR area was generally good. However, the significant increases of the density, biomass and the decrease of phytoplankton Q index in spring and summer tributaries would affect the water ecological health of the main stream to a certain extent, which had become the main risks for the TGR area. Therefore, we should make full use of the monitoring and early warning of tributary bloom and take advantage of the water ecological dispatch of the main stream to ensure the water ecological environment health of the whole TGR area.

WIND ENERGY POTENTIAL AND WIND CHARACTERISTICS FOR THE DISTRICTS OF THE CENTRAL DEVELOPMENT REGION OF THE REPUBLIC OF MOLDOVA

The poor energy security worldwide and especially at the national level, requires all entities to look for effective solutions to rectify the current situation by turning to renewable energy sources and energy efficiency. The purpose of this paper is to study the wind energy potential and wind characteristics for second-level administrative-territorial entities (districts) from the Central Development Region, Republic of Moldova, which includes 13 districts: Anenii Noi, Călărași, Criuleni, Dubăsari, Hâncești, Ialoveni, Nisporeni, Orhei, Rezina, Străseni, Șoldănesti, Telenesti and Ungheni. The Wind Atlas Method accompanied by the special Wind Atlas Analysis and Application Program, data on wind speed and direction measured by the Technical University and the orographic map of the Republic of Moldova was used for the research. For each individual district there were: calculated and presented the maps of the average annual wind speed and wind power density at the height of 100 m above ground level; classified the district territory according to the power density value and also calculated the theoretical wind power possible to install. Following the calculations made for the thirteen analyzed districts, it was found that the average annual wind speed at the height of 100 m is between 6.70 and 7.40 m/s, and the wind power density -between 287 and 398 W/m2. The highest average annual speed equal to 7.40 m/s and windpower density equal to 398 W/m2 was identified in Nisporeni district and the lowest inIaloveni, Rezina, Șoldănești and Dubăsari districts.

Spatial Distribution Characteristics of Traditional Villages and Influence Factors Thereof in Hilly and Gully Areas of Northern Shaanxi

In recent traditional village studies, spatial distribution characteristics have gained importance as a basis for rural revitalization and holistic protection; however, the total number of such studies remains small, and these studies do not account for the specific geographical area of China’s Loess Plateau. Contributing to recent efforts, the primary objective of this study was to evaluate the spatial distribution characteristics of the traditional villages in the hilly and gully areas of northern Shaanxi and to link their distribution patterns to the conservation and development of the traditional villages. ArcGIS and GeoDetector software were used to analyze the correlation between the village distribution characteristics and the influencing factors, as well as the differences in the influence of each factor. The research results show the following: (1) The traditional villages in the hilly and gully areas of northern Shaanxi present an uneven agglomeration distribution. The Mizhi, Suide, and Jiaxian areas are the main core agglomeration areas, and Yanchuan is a secondary core agglomeration area. An outward radiation forms with the “dual-core” as a center. (2) The spatial distribution of the traditional villages is positively correlated with slope, average annual temperature, solar radiation, and population density and is negatively correlated with the distance from a river and the GDP per capita; it has a median distribution for elevation, aspect, terrain undulation, and rainfall, and the distribution of the urbanization rate fluctuates. (3) The factor detection results of GeoDetector showed that the socio-economic factors had the strongest influence, followed by the climatic factors. The influence of the geographical factors was weak; the interaction between the influencing factors was enhanced, and the interaction between the population density and the climatic factors was the most obvious. (4) In terms of the influence mechanism, this study supports the claim that “natural environmental factors are the basis for the formation of traditional villages, and socio-economic factors determine the direction of development”. However, it is worth noting that the unique natural and human characteristics of the hilly and gully areas of northern Shaanxi are the fundamental reasons for the differences in the spatial distribution compared to the other regions.

Thunderstorm Activity and Extremes in Vietnam for the Period 2015–2019

Within a meteorological capacity building project in Vietnam, lightning location data and manual (human-observed) thunderstorm day observations were analyzed for the period 2015–2019. The lightning location dataset, based on the global lightning detection system Vaisala GLD360, consists of a total of 315,522,761 lightning strokes. The results indicate that, on average, 6.9 million lightning flashes per year occur in the land areas of Vietnam; this equals a lightning flash density of 20 flashes km−2 yr−1. The largest average annual flash density values occur in three regions in North, Central and South Vietnam. The majority of lightning occurs in the monsoon season (April–September), peaking in May, while in October–March, the lightning activity is very modest. During individual intense thunderstorm days, the flash density may exceed 12 flashes km−2 day−1. Thunderstorms in Central Vietnam are generally more intense, i.e., more lightning is expected on average per one thunderstorm day in Central Vietnam than in other regions. This study is a continuation of several years of meteorological capacity building in Vietnam, and the results suggest that large socio-economic benefits can be received by understanding the local thunderstorm climatology in high detail, especially in a country such as Vietnam, where lightning causes substantial socio-economic losses annually.