Ecological and human health impact assessments based on long-term monitoring of soil PAHs near a coal-fired power plant.

The combustion of coal in power plants releases significant amounts of polycyclic aromatic hydrocarbons (PAHs), which are highly toxic and carcinogenic. This study assesses the ecological and human health impacts of PAHs contamination from a coal-fired power plant over 8 years. The monitoring site selection considered the distance from the power plant and the prevailing wind direction in the investigated area. The results reveal that, during the monitoring period, PAH levels increased on average by 43%, 61%, and 37% in the zone of the prevailing wind direction, in the area proximate to the power plant, and the zone distant from it, respectively. The site, which has a radius of 4.5 km in the prevailing wind direction, exhibited the highest ecological and human health impacts. Additionally, a strong correlation was observed between environmental and human health impacts, depending on the distance from the power plant, particularly in areas with the prevailing wind direction. These insights contribute to a comprehensive understanding of the intricate dynamics linking power plant emissions, PAHs contamination, and their far-reaching consequences on the environment and human health.

An artificial gorilla troops optimizer for stochastic unit commitment problem solution incorporating solar, wind, and load uncertainties.

The unit commitment (UC) optimization issue is a vital issue in the operation and management of power systems. In recent years, the significant inroads of renewable energy (RE) resources, especially wind power and solar energy generation systems, into power systems have led to a huge increment in levels of uncertainty in power systems. Consequently, solution the UC is being more complicated. In this work, the UC problem solution is addressed using the Artificial Gorilla Troops Optimizer (GTO) for three cases including solving the UC at deterministic state, solving the UC under uncertainties of system and sources with and without RE sources. The uncertainty modelling of the load and RE sources (wind power and solar energy) are made through representing each uncertain variable with a suitable probability density function (PDF) and then the Monte Carlo Simulation (MCS) method is employed to generate a large number of scenarios then a scenario reduction technique known as backward reduction algorithm (BRA) is applied to establish a meaningful overall interpretation of the results. The results show that the overall cost per day is reduced from 0.2181% to 3.7528% at the deterministic state. In addition to that the overall cost reduction per day is 19.23% with integration of the RE resources. According to the results analysis, the main findings from this work are that the GTO is a powerful optimizer in addressing the deterministic UC problem with better cost and faster convergence curve and that RE resources help greatly in running cost saving. Also uncertainty consideration makes the system more reliable and realistic.

An in-depth study of the oxidative liquefaction process for polymeric waste reduction and chemical production from wind turbine blades and personal protective equipment used in the medical field.

An in-depth study of the oxidative liquefaction process has been provided to degrade the polymeric waste from personal protective equipment (PPEs) and wind turbine blades (WTBs). Thermogravimetric investigations demonstrate that WTBs have three prominent peaks throughout the degradation, whereas PPEs display solitary peak features. Experiments are carried out employing specific experimental design approaches, namely the Central Composite Face-Centered Plan (CCF) for WTBs and the Central Composition Design with Fractional Factorial Design for PPEs in a batch-type reactor at temperature ranges of 250-350 °C, pressures of 20-40 bar, residence times of 30-90 min, H2O2 concentrations of 15-45 %, and waste/liquid ratios of 5-25 % for WTBs. These values were 200-300 °C, 30 bar, 45 min, 30-60 % and 5-7 % for PPE. A detailed comparison has been provided in the context of total polymer degradation (TPD) for PPE and WTBs. Liquid products from both types of wastes after the oxidative liquefaction process are subjected to gas chromatography with flame ionization detection (GC-FID) to identify the existence of oxygenated chemical compounds (OCCs). For WTBs, TPD was 20-49 % and this value was 55-96 % for PPE while the OCC yield for WTBs (36.31 g/kg - 210.59 g/kg) and PPEs (39.93 g/kg - 212.66 g/kg) was also calculated. Detailed optimization of experimental plans was carried out by performing the analysis of variance (ANOVA) and optimization goals were maximum TPD and OCCs yields against the minimum energy consumption, though a considerable amount of complex polymer waste can be reduced and high concentrations of OCC can be achieved, which could be applied for commercial and environmental benefits.

Natural Seismic Event Analysis Based on Signal and Source Characteristics from two Experiments in Antarctica.

This study presents geophysical data from two passive seismic measurements conducted at two different sites in Antarctica. We analyzed the signals mainly in the frequency domain through the multitaper method to extract some spectral characteristics of the signals that would have been out of reach through the usual FFT approach. The power spectral density of the signals carries information about the processes that generated them, allowing its correlation with their source origin and type, either natural or anthropogenic. We deal with three different source types: calving, wind, and anthropogenic origins. The former is closely related to glacier dynamics, being modulated by the prevailing atmospheric processes. At both locations the wind noise is prevalent, complicating the analysis of other events like calving. We have used data classification, estimation of the source azimuth, and seismic apparent velocity to demonstrate the viability of using geophysical methods to study glacier elastic parameters and dynamics. Moreover, the calving rate can yield a wider and more independent understanding of glacier hydrodynamics and may help to estimate the future response of the polar areas to a changing environment.

Contrasting seasonal responses to wind in migrating songbirds on a globally important flyway.

During spring migration, nocturnal migrants attempt to minimize their travel time to reach their breeding grounds early. However, how they behave and respond to unfavourable conditions during their springtime travels is much less understood. In this study, we reveal the effects of atmospheric factors on nocturnal bird migration under adverse conditions during spring and autumn, based on one of the most detailed bird migration studies globally, using radar data from 13 deployments over a period of seven years (2014-2020) in the Levant region. Using ERA5 reanalysis data, we found that migratory birds maintain similar ground speeds in both autumn and spring migrations, but during spring, when encountering unfavourable winds, they put more effort into maintaining their travel speed by increasing self-powered airspeed by 18%. Moreover, we report for the first time that spring migrants showed less selectivity to wind conditions and migrated even under unfavourable headwind and crosswind conditions. Interestingly, we discovered that temperature was the most important weather parameter, such that warm weather substantially increased migration intensities in both seasons. Our results enhance our understanding of bird migration over the Levant region, one of the world's largest and most important migration flyways, and the factors controlling it. This information is essential for predicting bird migration, which-especially under the ongoing anthropogenic changes-is of high importance.

Similar experimental study on diffusion and distribution of diesel exhaust in confined space of a coal mine.

In the confined space of the underground coal mine, which is dominated by transportation lanes, explosion-proof diesel-powered trackless rubber-wheeled vehicles are becoming the main transportation equipment, and the exhaust gas produced by them is hazardous to the health of workers and pollutes the underground environment. In this experiment, a similar test platform is built to study the effects of wind speed, vehicle speed, and different wind directions on the diffusion characteristics of exhaust gas. In this paper, CO and SO2 are mainly studied. The results show that the diffusion of CO and SO2 gas is similar and the maximum SO2 concentration only accounts for 11.4% of the CO concentration. Exhaust gas is better diluted by increasing the wind speed and vehicle speed, respectively. Downwind is affected by the reverse wind flow and diffuses to the driver's position, which is easy to cause occupational diseases. When the wind is a headwind, the exhaust gases spread upwards and make a circumvention movement, gathering at the top. When the wind speed and vehicle speed are both 0.6 m/s, the CO concentration corresponds to the change trend of the Lorentz function when the wind is downwind and the CO concentration corresponds to the change trend of the BiDoseResp function when the wind is headwind. The study of exhaust gas diffusion characteristics is of great significance for the subsequent purification of the air in the restricted mine space and the protection of the workers' occupational health.

Mathematical modeling and performance evaluation of Ducted Horizontal-axis Helical Wind Turbines: Insights into aerodynamics and efficiency.

With the escalating demand for energy, there is a growing focus on decentralized, small-scale energy infrastructure. The success of new turbines in this context is notable. However, many of these turbines do not follow many of the basic ideas established to evaluate their performance, leaving no precise technique or mathematical model. This research developed a Ducted Horizontal-axis Helical Wind Turbine (DHAHWT). The DHAHWT is a duct-mounted helical savonius turbine with a venturi and diffuser to improve flow. Unlike a vertical axis helical savonius turbine, DHAHWT revolves roughly parallel to the wind, making it a horizontal turbine. This complicates mathematical and theoretical analysis. This study created a DHAHWT mathematical model. COMSOL simulations utilizing Menter's Shear Stress Transport model (SST) across an incoming velocity range of 1m/s to 4m/s were used to evaluate the turbine's interaction with the wind. MATLAB was used to train an artificial neural network (ANN) utilizing COMSOL data to obtain greater velocity data. The Mean Average Percentage Error (MAPE) and Root Mean Square Error (RMSE) of ANN data were found to be 3%, indicating high accuracy. Further, using advanced statistical methods the Pearson's correlation coefficient was calculated resulting in a better understanding of the relationship of between incoming velocity and velocity at different sections of the wind turbine. This study will shed light on the aerodynamics and working of DHAHWT.

Effects of wind speed and wind direction on crop yield forecasting using dynamic time warping and an ensembled learning model.

The cultivation of cashew crops carries numerous economic advantages, and countries worldwide that produce this crop face a high demand. The effects of wind speed and wind direction on crop yield prediction using proficient deep learning algorithms are less emphasized or researched. We propose a combination of advanced deep learning techniques, specifically focusing on long short-term memory (LSTM) and random forest models. We intend to enhance this ensemble model using dynamic time warping (DTW) to assess the spatiotemporal data (wind speed and wind direction) similarities within Jaman North, Jaman South, and Wenchi with their respective production yield. In the Bono region of Ghana, these three areas are crucial for cashew production. The LSTM-DTW-RF model with wind speed and wind direction achieved an R2 score of 0.847 and the LSTM-RF model without these two key features R2 score of (0.74). Both models were evaluated using the augmented Dickey-Fuller (ADF) test, which is commonly used in time series analysis to assess stationarity, where the LSTM-DTW-RF achieved a 90% level of confidence, while LSTM-RF attained an 87.99% level. Among the three municipalities, Jaman South had the highest evaluation scores for the model, with an RMSE of 0.883, an R2 of 0.835, and an MBE of 0.212 when comparing actual and predicted values for Wenchi. In terms of the annual average wind direction, Jaman North recorded (270.5 SW°), Jaman South recorded (274.8 SW°), and Wenchi recorded (272.6 SW°). The DTW similarity distance for the annual average wind speed across these regions fell within specific ranges: Jaman North (±25.72), Jaman South (±25.89), and Wenchi (±26.04). Following the DTW similarity evaluation, Jaman North demonstrated superior performance in wind speed, while Wenchi excelled in wind direction. This underscores the potential efficiency of DTW when incorporated into the analysis of environmental factors affecting crop yields, given its invariant nature. The results obtained can guide further exploration of DTW variations in combination with other machine learning models to predict higher cashew yields. Additionally, these findings emphasize the significance of wind speed and direction in vertical farming, contributing to informed decisions for sustainable agricultural growth and development.

Satellite Tracking Reveals the Speed Up of the Lacustrine Algal Bloom Drift in Response to Climate Change.

Satellite evidence indicates a global increase in lacustrine algal blooms. These blooms can drift with winds, resulting in significant changes of the algal biomass spatial distribution, which is crucial in bloom formation. However, the lack of long-term, large-scale observational data has limited our understanding of bloom drift. Here, we have developed a novel method to track the drift using multi-source remote sensing satellites and presented a comprehensive bloom drift data set for four typical lakes: Lake Taihu (China, 2011-2021), Lake Chaohu (China, 2011-2020), Lake Dianchi (China, 2003-2021), and Lake Erie (North America, 2003-2021). We found that blooms closer to the water surface tend to drift faster. Higher temperatures and lower wind speeds bring blooms closer to the water surface, therefore accelerating drift and increasing biomass transportation. Under ongoing climate change, algal blooms are increasingly likely to spread over larger areas and accumulate in downwind waters, thereby posing a heightened risk to water resources. Our research greatly improves the understanding of algal bloom dynamics and provides new insights into the driving factors behind the global expansion of algal blooms. Our bloom-drift-tracking methodology also paves the way for the development of high-precision algal bloom prediction models.

A trans-oceanic flight of over 4,200 km by painted lady butterflies.

The extent of aerial flows of insects circulating around the planet and their impact on ecosystems and biogeography remain enigmatic because of methodological challenges. Here we report a transatlantic crossing by Vanessa cardui butterflies spanning at least 4200 km, from West Africa to South America (French Guiana) and lasting between 5 and 8 days. Even more, we infer a likely natal origin for these individuals in Western Europe, and the journey Europe-Africa-South America could expand to 7000 km or more. This discovery was possible through an integrative approach, including coastal field surveys, wind trajectory modelling, genomics, pollen metabarcoding, ecological niche modelling, and multi-isotope geolocation of natal origins. The overall journey, which was energetically feasible only if assisted by winds, is among the longest documented for individual insects, and potentially the first verified transatlantic crossing. Our findings suggest that we may be underestimating transoceanic dispersal in insects and highlight the importance of aerial highways connecting continents by trade winds.

The small hive beetle's capacity to disperse over long distances by flight.

The spread of invasive species often follows a jump-dispersal pattern. While jumps are typically fostered by humans, local dispersal can occur due to the specific traits of a species, which are often poorly understood. This holds true for small hive beetles (Aethina tumida), which are parasites of social bee colonies native to sub-Saharan Africa. They have become a widespread invasive species. In 2017, a mark-release-recapture experiment was conducted in six replicates (A-F) using laboratory reared, dye-fed adults (N = 15,690). Honey bee colonies were used to attract flying small hive beetles at fixed spatial intervals from a central release point. Small hive beetles were recaptured (N = 770) at a maximum distance of 3.2 km after 24 h and 12 km after 1 week. Most small hive beetles were collected closest to the release point at 0 m (76%, replicate A) and 50 m (52%, replicates B to F). Temperature and wind deviation had significant effects on dispersal, with more small hive beetles being recaptured when temperatures were high (GLMM: slope = 0.99, SE = 0.17, Z = 5.72, P < 0.001) and confirming the role of wind for odour modulated dispersal of flying insects (GLMM: slope = - 0.39, SE = 0.14, Z = - 2.90, P = 0.004). Our findings show that the small hive beetles is capable of long-distance flights, and highlights the need to understand species specific traits to be considered for monitoring and mitigation efforts regarding invasive alien species.

Wind turbine with line-side PMSG FED DC-DC converter for voltage regulation.

This article represents a novel study of the design and analysis of a wind turbine system that includes a line-side permanent magnet synchronous generator (PMSG) with an ultra-step-up DC-DC converter for voltage regulation. Integrating renewable energy sources such as wind power into the grid requires efficient and reliable power conversion systems to handle fluctuating power and ensure a stable power supply. The wind turbine system utilizes a PMSG, which offers several advantages over traditional induction generators, including higher efficiency, reduced maintenance, and better power quality. The line-side configuration allows for increased control and flexibility, allowing the system to respond dynamically to grid conditions. This wind turbine system involves the integration of a grid-side PMSG-fed DC-DC converter between the PMSG and the grid. The converter enables a seamless flow of electricity between the wind turbine and the grid. By actively controlling the intermediate circuit voltage, the converter efficiently regulates the output voltage of the wind turbine and thus enables constant power generation regardless of fluctuating wind speeds. The simulation outcomes illustrate the efficacy of the proposed system in achieving voltage regulation and seamless integration with the grid. Performance is evaluated under various operating conditions and compared to conventional wind turbines.

Sensitivity analysis of heat and mass transfer at working face in high-temperature mine.

Thermal damage from heat sources severely affects the safety of deep mine production. Heat and mass transfer between heat sources and airflow leads to the increase of the airflow temperature (AFT), moisture content of airflow (AFMC) and relative humidity of airflow (AFRH). This study aims to quantify uncertainty contributions of the working face parameters on AFT, AFMC and AFRH and find their main contributors. The flow, geometric and physical parameters are chosen as uncertainty sources. Subsequently, Sobol indices are obtained using the point-collocation non-intrusive polynomial chaos method, denoting the sensitivity of each input parameter. It was found that the inflow wind temperature and the wind velocity are two top factors influencing AFT and AFMC, while relative humidity of inflow wind and the wind velocity are two top factors influencing AFRH. In the single factor analysis, the uncertainty contributions of the inflow wind temperature on AFT and AFMC, and relative humidity of inflow wind on AFRH can exceed 0.7, which is higher than those of the wind velocity. The geometric parameters of the working face, namely the length, width and height, and ventilation time are also significant quantities influencing AFT, AFMC and AFRH. Compared to AFT and AFMC, two other significant quantities influencing AFRH are the thermal conductivity of coal and the original temperature of the rock.

Effects of aeolian deposition on soil properties and microbial carbon metabolism function in farmland of Songnen Plain, China.

The effects of wind erosion, one of the crucial causes of soil desertification in the world, on the terrestrial ecosystem are well known. However, ecosystem responses regarding soil microbial carbon metabolism to sand deposition caused by wind erosion, a crucial driver of biogeochemical cycles, remain largely unclear. In this study, we collected soil samples from typical aeolian deposition farmland in the Songnen Plain of China to evaluate the effects of sand deposition on soil properties, microbial communities, and carbon metabolism function. We also determined the reads number of carbon metabolism-related genes by high-throughput sequencing technologies and evaluated the association between sand deposition and them. The results showed that long-term sand deposition resulted in soil infertile, roughness, and dryness. The impacts of sand deposition on topsoil were more severe than on deep soil. The diversity of soil microbial communities was significantly reduced due to sand deposition. The relative abundances of Nitrobacteraceae, Burkholderiaceae, and Rhodanobacteraceae belonging to α-Proteobacteria significantly decreased, while the relative abundances of Streptomycetaceae and Geodermatophilaceae belonging to Actinobacteria increased. The results of the metagenomic analysis showed that the gene abundances of carbohydrate metabolism and carbohydrate-activity enzyme (GH and CBM) significantly decreased with the increase of sand deposition amount. The changes in soil microbial community structure and carbon metabolism decreased soil carbon emissions and carbon cycling in aeolian deposition farmland, which may be the essential reasons for land degradation in aeolian deposition farmland.

Enhancement of ANN-based wind power forecasting by modification of surface roughness parameterization over complex terrain.

Wind energy plays an important role in the sustainable energy transition towards a low-carbon society. Proper assessment of wind energy resources and accurate wind energy prediction are essential prerequisites for balancing electricity supply and demand. However, these remain challenging, especially for onshore wind farms over complex terrains, owing to the interplay between surface heterogeneities and intermittent turbulent flows in the planetary boundary layer. This study aimed to improve wind characteristic assessment and medium-term wind power forecasts over complex hilly terrain using a numerical weather prediction (NWP) model. The NWP model reproduced the wind speed distribution, duration, and spatio-temporal variabilities of the observed hub-height wind speed at 24 wind turbines in onshore wind farms when incorporating more realistic surface roughness effects, such as the subgrid-scale topography, roughness sublayer, and canopy height. This study also emphasizes the good features for machine learning that represent heterogeneities in the surface roughness elements in the atmospheric model. We showed that medium-term forecasting using the NWP model output and a simple artificial neural network (ANN) improved day-ahead wind power forecasts by 14% in terms of annual normalized mean absolute error. Our results suggest that better parameterizations of surface friction in atmospheric models are important for wind power forecasting and resource assessment using NWP models, especially when combined with machine learning techniques, and shed light on onshore wind power forecasting and wind energy assessment in mountainous regions.

Factors contributing to the minimum water column stability and timing of the winter turnover in the Ogouchi reservoir.

Turnover in lakes and reservoirs causes circulation in the water column from the bottom to the surface when the water column stability becomes low. Previous studies commonly mentioned that turnover occurs when stratification indices become small, but the threshold is rarely discussed. While turnover phenomena have been extensively studied by evaluating changes in bottom dissolved oxygen (DO), the relationship between the disappearance of hypoxia and water temperature indices has not been determined. This study focused on the factors influencing the minimum thermal gradient (TG) and Schmidt Stability Index (SSI), and the timing of turnover events using DO as an indicator of mixing in the Ogouchi reservoir from 1992 to 2001. The results showed that the occurrence of minimum TG and SSI is mainly driven by inflow retention time and average maximum wind speed. Moreover, minimum air temperature and outflow retention time have few contributions to minimum SSI. It was found that 7 out of 10 years exhibited full winter turnover, while the remaining years showed incomplete mixing with persistent hypoxia at the reservoir bottom. This study identifies four cases based on onset thresholds of 0.0035 °C m-1 for TG and 30 J m-2 for SSI to explain turnover event: Case 1: an ideal state with stratification indices below the threshold, resulting in the disappearance of hypoxia; Case 2: indices above the threshold sustain hypoxia; Case 3: an irregular state where the indices exceed the threshold, yet hypoxia disappears; and Case 4: an unexpected persistence of hypoxia despite being below the threshold. The majority of the years (70 percent) were explained by thresholds. The multiple regression analysis indicated the importance of wind speed on the turnover event. Therefore, the effect of wind shear was analyzed for 30 percent of the years that cannot be explained by thresholds (cases 3 and 4). Case 3 shows turnover occurrence due to strong accumulated wind shear, despite exceeding thresholds. Conversely, Case 4 reveals weak wind shear preventing bottom water upwelling, even below thresholds. In conclusion, the precise TG and SSI thresholds for the onset of turnover event were determined using DO data. The thresholds explained the occurrence and non-occurrence of turnover event in most of the years and wind speed clarified unexplained cases by thresholds. The presented method successfully evaluated the timing of turnover and can be applicable elsewhere.

Response of chlorophyll-a to rainfall event in the basin of the South China sea: Statistical analysis.

Chlorophyll-a (Chl-a) is an essential ecological indicator, and affected by processes such as typhoons, mesoscale eddies, and Rossby waves. However, the impact of more frequent and widespread precipitation events on Chl-a seems to be overlooked. This study utilized remote sensing data and reanalysis data to investigate the response of Chl-a to 240 precipitation events in the central South China Sea from 2005 to 2019. The results indicate that precipitation events have a significant impact on Chl-a concentration. Following a precipitation event in 2019, the Chl-a concentration in the affected area increased by approximately 0.22 mg m-³ from the 3rd to the 7th day. The reasons for the increase in Chl-a concentration were the vertical mixing induced by wind stirring and the upwelling caused by wind stress curl, which transported nutrients to the euphotic zone, lowering the sea surface temperature and triggering a proliferation of phytoplankton. Additionally, dissolved nutrients in precipitation provided a nutrient source for Chl-a growth. The contributions of nutrient supply, wind speed, and wind stress curl to the increase in Chl-a concentration during precipitation events were 18%, 37%, and 45%, respectively. Precipitation events enhanced marine primary productivity, playing a crucial role in deepening our understanding of ocean-atmosphere interactions and their impact on marine ecosystem.

Charge generation by passive plant leaf motion at low wind speeds: design and collective behavior of plant-hybrid energy harvesters.

Energy harvesting techniques can exploit even subtle passive motion like that of plant leaves in wind as a consequence of contact electrification of the leaf surface. The effect is strongly enhanced by artificial materials installed as 'artificial leaves' on the natural leaves creating a recurring mechanical contact and separation. However, this requires a controlled mechanical interaction between the biological and the artificial component during the complex wind motion. Here, we build and test four artificial leaf designs with varying flexibility and degrees of freedom across the blade operating onNerium oleanderplants. We evaluate the apparent contact area (up to 10 cm2per leaf), the leaves' motion, together with the generated voltage, current and charge in low wind speeds of up to 3.3 m s-1and less. Single artificial leaves produced over 75 V and 1µA current peaks. Softer artificial leaves increase the contact area accessible for energy conversion, but a balance between softer and stiffer elements in the artificial blade is optimal to increase the frequency of contact-separation motion (here up to 10 Hz) for energy conversion also below 3.3 m s-1. Moreover, we tested how multiple leaves operating collectively during continuous wind energy harvesting over several days achieve a root mean square power of ∼6µW and are capable to transfer ∼80µC every 30-40 min to power a wireless temperature and humidity sensor autonomously and recurrently. The results experimentally reveal design strategies for energy harvesters providing autonomous micro power sources in plant ecosystems for example for sensing in precision agriculture and remote environmental monitoring.

Characteristics of surface ozone pollution and its correlations with meteorological factors: the case of Xiangtan.

Based on ozone (O3) monitoring data for Xiangtan and meteorological observation data for 2020-2022, we examined ozone pollution characteristics and the effects of meteorological factors on daily maximum 8-h average ozone (O3-8h) concentrations in Xiangtan. Thus, we observed significant increases as well as notable seasonal variations in O3-8h concentrations in Xiangtan during the period considered. The ozone and temperature change response slope (KO3-T) indicated that local emissions had no significant effect on O3-8h generation. Further, average O3-8h concentration and maximum temperature (Tmax) values showed a polynomial distribution. Specifically, at Tmax < 27 °C, it increased almost linearly with increasing temperature, and at Tmax between 27 and 37 °C, it showed an upward curvilinear trend as temperature increased, but at a much lower rate. Then, at Tmax > 37 °C, it decreased with increasing temperature. With respect to relative humidity (RH), the average O3-8h concentration primarily exceeded the standard value when RH varied in the range of 45-65%, which is the key humidity range for O3 pollution, and the inflection point for the correlation curve between O3-8h concentration and RH appeared at ~55%. Furthermore, at wind speeds (WSs) below 1.5 m∙s-1, O3-8h concentration increased rapidly, and at WSs in the 1.5-2 m∙s-1 range, it increased at a much faster rate. However, at WSs > 2 m∙s-1, it decreased slowly with increasing WS. O3-8h concentration also showed the tendency to exceed the standard value when the dominant wind directions in Xiangtan were easterly or southeasterly.

Spatial diffusion of potentially toxic elements in soils around non-ferrous metal mines.

This study focuses on the diffusion patterns of principal ore-forming elements (Pb and Zn) and associated elements (Cd, Cu, Cr, and As) in lead-zinc ore. Sampling points in upwind and downwind directions of lead-zinc ore areas at various densities (1 N/km2 - 4 N/km2) were categorized. This study analyzed the statistical relationship between the content of PTEs in the soil around lead-zinc ore and the source strength and dominant wind direction, constructed one-dimensional and two-dimensional diffusion model, and simulated the EER scope caused by PTEs. The findings indicate that: (1) concerning source strength, the content of PTEs in soils of high-density ore aggregation areas is significantly higher than in low-density ore aggregation areas. However, the impact of source strength decreases with decreasing ore grade, with a difference in Pb content of 1.71 times among principal ore-forming elements and almost consistent Cd content among associated elements. (2) Regarding the transport pathways, for most PTEs, the inverse proportion coefficients downwind are higher than upwind, approximately 1.18-3.63 times, indicating greater migration distances of PTEs downwind due to atmospheric dispersion. (3) By establishing a two-dimensional risk diffusion model, the study simulates the maximum radius of risk diffusion (r = 5.7 km), the 50% probability radius (r = 3.1 km), and the minimum radius (r = 0.8 km) based on the maximum, median, and minimum values statistically obtained from the EER. This study provides a scientific basis for implementing preventive measures for PTEs accumulation in soil within different pollution ranges. Different risk prevention and control measures should be adopted for PTEs accumulation in soil within the three ranges after cutting off pollution sources. Subsequent research should further investigate the impact and contribution of atmospheric transmission and surface runoff on the diffusion of PTEs in areas with high risk near lead-zinc ore.