Search Results (13)

In order to explore the variation law and causes of the humidity effect of local water bodies, this paper selects the data of encrypted automatic weather stations (encrypted stations) and national conventional meteorological stations (conventional stations) in Nanjing from 2014 to 2020, and systematically studies the humidity effects and influencing factors of urban water bodies by constructing the humidity effect intensity (E) based on the conventional stations. The results show that the humidity effect of urban water has significant diurnal and monthly variation characteristics, and is extremely sensitive to temperature change, and compared to nighttime, the daytime period is generally more humid. The humidity effect is mostly normal in winter, while the humidification and humidity reduction effects in summer are particularly significant. There are also significant differences in the humidity effect between different typical water stations, which are mainly influenced by the background environment of urban and suburban areas, macro wind field, and local wind field configuration around the water body due to the dense building density in the main urban area, which is characterized by dry humidification, while the suburbs are characterized by humidity. When the water body is located on the side of a large water body (river or lake), the influence of local water–land wind field and macro wind field on the humidity effect is particularly significant, and the water wind will significantly enhance the humidity effect, while the land breeze will weaken the humidity effect. The research results can provide a reference for the urban planning and the design of the surrounding environment of water bodies in Nanjing. Full article

To avoid the spread of COVID-19, China has implemented strict lockdown policies and control measures, resulting in a dramatic decrease in air pollution and improved air quality. In this study, the air quality model WRF-Chem and the latest MEIC2019 and MEIC2020 anthropogenic emission inventories were used to simulate the air quality during the COVID-19 lockdown in 2020 and the same period in 2019. By designing different emission scenarios, this study explored the impact of the COVID-19 lockdown on the concentration of air pollutants emitted by different sectors (industrial sector and transportation sector) in Nanjing for the first time. The results indicate that influenced by the COVID-19 lockdown policies, compared with the same period in 2019, the concentrations of PM_2.5, PM₁₀, and NO₂ in Nanjing decreased by 15%, 17.1%, and 20.3%, respectively, while the concentration of O₃ increased by 45.1% in comparison; the concentrations of PM_2.5, PM₁₀ and NO₂ emitted by industrial sector decreased by 30.7%, 30.8% and 14.0% respectively; the concentrations of PM_2.5, PM₁₀ and NO₂ emitted by transportation sector decreased by 15.6%, 15.7% and 26.2% respectively. The COVID-19 lockdown has a greater impact on the concentrations of PM_2.5 and PM₁₀ emitted by the industrial sector, while the impact on air pollutants emitted by the transportation sector is more reflected in the concentration of NO₂. This study provides some theoretical basis for the treatment of air pollutants in different departments in Nanjing. Full article

NH₃ emissions are an environmental issue that is of wide concern in livestock production. In intensive livestock farming, it is necessary to study outdoor ammonia concentrations under various conditions to maximize the protection of livestock caretakers’ health in and around the facilities. In this study, the ammonia concentrations outside smart broiler chambers in 60 scenarios, with conditions including 4 broiler chamber densities, 3 wind directions, and 5 outlet emission intensities, were simulated based on computational fluid dynamics (CFD) technology. The results show that (1) outdoor ammonia tends to accumulate near the outlet when the wind direction angle is small, while it has a wider range of influence when the angle is vertical; (2) building a smart broiler chamber cluster for intensive livestock farming is environmentally friendly; and (3) keeping the ammonia outlet perpendicular to the local dominant wind direction can effectively prevent high concentrations of ammonia around the chambers. In practical applications, the conclusions of this study can be used to arrange the layout and direction of smart broiler chamber clusters. Full article

Using traditional tea frost hazard risk assessment results as sample data, the four indicators of minimum temperature, altitude, tea planting area, and tea yield were selected to consider the risk of hazard-causing factors, the exposure of hazard-bearing bodies, and the vulnerability of hazard-bearing bodies. The random forest algorithm was used to construct the frost hazard risk assessment model of Hangzhou tea, and hazard risk assessment was carried out on tea with different cold resistances in Hangzhou. The model’s accuracy reached 93% after training, and the interpretation reached more than 0.937. According to the risk assessment results of tea with different cold resistance, the high-risk areas of weak cold resistance tea were the most, followed by medium cold resistance and the least strong cold resistance. Compared with the traditional method, the prediction result of the random forest model has a deviation of only 1.57%. Using the random forest model to replace the artificial setting of the weight factor in the traditional method has the advantages of simple operation, high time efficiency, and high result accuracy. The prediction results have been verified by the existing hazard data. The model conforms to the actual situation and has certain guiding for local agricultural production and early warning of hazards. Full article

Tea is a special economic crop that is widely distributed in tropical and subtropical areas. Timely and accurate access to the distribution of tea plantation areas is crucial for effective tea plantation supervision and sustainable agricultural development. Traditional methods for tea plantation extraction are highly dependent on feature engineering, which requires expensive human and material resources, and it is sometimes even difficult to achieve the expected results in terms of accuracy and robustness. To alleviate such problems, we took Xinchang County as the study area and proposed a method to extract tea plantations based on deep learning networks. Convolutional neural network (CNN) and recurrent neural network (RNN) modules were combined to build an R-CNN model that can automatically obtain both spatial and temporal information from multitemporal Sentinel-2 remote sensing images of tea plantations, and then the spatial distribution of tea plantations was predicted. To confirm the effectiveness of our method, support vector machine (SVM), random forest (RF), CNN, and RNN methods were used for comparative experiments. The results show that the R-CNN method has great potential in the tea plantation extraction task, with an F1 score and IoU of 0.885 and 0.793 on the test dataset, respectively. The overall classification accuracy and kappa coefficient for the whole region are 0.953 and 0.904, respectively, indicating that this method possesses higher extraction accuracy than the other four methods. In addition, we found that the distribution index of tea plantations in mountainous areas with gentle slopes is the highest in Xinchang County. This study can provide a reference basis for the fine mapping of tea plantation distributions. Full article

Poultry breeding is one of the most significant components of agriculture and an essential link of material exchange between humans and nature. Moreover, poultry breeding technology has a considerable impact on the life quality of human beings, and could even influence the survival of human beings. As one of the most popular poultry, broiler has a good economic benefit due to its excellent taste and fast growing cycle. This paper aims to improve the efficiency of raising broilers by understanding the impact of ammonia concentration distribution within a smart broiler breeding chamber, and the rationality of the system’s design. More specifically, we used computational fluid dynamics (CFD) technology to simulate the process of ammonia production and identify the characteristics of ammonia concentration. Based on the simulation results, the structure of the broiler chamber was reformed, and the ammonia uniformity was significantly improved after the structural modification of the broiler chamber and the ammonia concentration in the chamber had remained extremely low. In general, this study provides a reference for structural optimization of the design of broiler chambers and the environmental regulation of ammonia. Full article

The shifts in dry-wet climate regions are a natural response to climate change and have a profound impact on the regional agriculture and ecosystems. In this paper, we divided China into four dry-wet climate regions, i.e., arid, semi-arid, semi-humid, and humid regions, based on the humidity index (HI). A comparison of the two 30-year periods, i.e., 1960–1989 and 1990–2019, revealed that there was a shift in climate type in each dry-wet climate region, with six newly formed transitions, and the total area of the shifts to wetter conditions was more than two times larger than that of the shifts to drier conditions. Interestingly, the shifts to drier types were basically distributed in the monsoon region (east of 100${}^{\circ }$ E) and especially concentrated in the North China Plain where agricultural development relies heavily on irrigation, which would increase the challenges in dealing with water shortage and food production security under a warming climate. The transitions to wetter types were mainly distributed in western China (west of 100${}^{\circ }$ E), and most areas of the Junggar Basin have changed from arid to semi-arid region, which should benefit the local agricultural production and ecological environment to some extent. Based on a contribution analysis method, we further quantified the impacts of each climate factor on HI changes. Our results demonstrated that the dominant factor controlling HI changes in the six newly formed transition regions was P, followed by air temperature (Ta). In the non-transition zones of the arid and semi-arid regions, an increase in P dominated the increase of HI. However, in the non-transition zones of the semi-humid and humid region with a more humid background climate, the thermal factors (e.g., Ta, and net radiation (Rn)) contributed more than or equivalent to the contribution of P to HI change. These findings can provide scientific reference for water resources management and sustainable agricultural development in the context of climate change. Full article

The merging of a fast-moving bow echo with a convective cell of a hook-echo signature was studied by using polarimetric radar detections. Gusts with wind speeds near 35 m s⁻¹ were recorded by the surface station, which caused significant damage. A convective cell with a mesovortex signature, which is hereafter referred to as a mini-supercell, was observed over the northeast of the bow echo before the convective merging. It was found that the mesovortex possessed cyclonic circulation and resembled a supercell-like feature. The merging of the bow echo and the mini-supercell strengthened the updraft near the apex of the bow echo. The enhanced updraft was also demonstrated by the appearance of a differential reflectivity (Z_DR) column with a topmost height of 4 km above the melting layer (~4 km). The bow was separated into northern and southern sectors after merging with the mini-supercell, leading to the gusty wind over the surface of the south sector. Full article

Terrain plays an important role in the formation, development and distribution of local precipitation and is a major factor leading to locally abnormal weather in weather systems. Although small-scale topography has little influence on the spatial distribution of precipitation, it interferes with precipitation fitting. Due to the arbitrary combination of small, medium and large-scale terrain, complex terrain distribution is formed, and small-scale terrain cannot be clearly defined and removed. Based on the idea of bidimensional empirical mode decomposition (BEMD), this paper extracts small-scale terrain data layer by layer to smooth the terrain and constructs a macroterrain model for different scales in Central China. Based on the precipitation distribution model using multiple regression, precipitation models (B0, B1, B2 and B3) of different scales are constructed. The 18-year monthly average precipitation data of each station are compared with the precipitation simulation results under different scales of terrain and TRMM precipitation data, and the influence of different levels of small-scale terrain on the precipitation distribution is analysed. The results show that (1) in Central China, the accuracy of model B2 is much higher than that of TRMM model A and monthly precipitation model B0. The comprehensive evaluation indexes are increased by 3.31% and 1.92%, respectively. (2) The influence of different levels of small-scale terrain on the precipitation distribution is different. The first- and second-order small-scale terrain has interference effects on precipitation fitting, and the third-order small-scale terrain has an enhancement effect on precipitation. However, the effect of small-scale topography on the precipitation distribution is generally reflected as interference. Full article

The urban wind environment is an important element of urban microclimates and plays an important role in the quality of the urban environment. The computational fluid dynamics (CFD) simulation method is an important means for urban wind field research. However, CFD simulation has high requirements for computer hardware and software. In this paper, based on geographic information system (GIS) technology, a new building data generalization method was developed to solve the problems of a huge amount of data and calculations in urban-scale CFD wind field simulations. Using Fluent software and high-precision urban building geographic information data with elevation attributes, the method was applied to Jinjiang City, Fujian Province, China. A CFD simulation of the wind field of Jinjiang City was implemented, and detailed, intuitive wind field information was obtained, which were compared with the measured data. The results show that the building data generalization method could effectively improve the efficiency of the city's overall wind field CFD simulation. The simulated wind speed was significantly correlated with the measured data, but it was overestimated. The simulated wind direction was consistent with the measured data of most stations. The simulation results were reasonable and could provide reference for application and subsequent research. Full article

In this paper, a CFD (computational fluid dynamics) numerical calculation was employed to examine whether the ventilation system of the self-designed smart broiler house meets the requirements of cooling and ventilation for the welfare in poultry breeding. The broiler chamber is powered by two negative pressure fans. The fans are designed with different frequencies for the ventilation system according to the specific air temperature in the broiler chamber. The simulation of ventilation in the empty chamber involved five working conditions in this research. The simulation of ventilation in the broiler chamber and the simulation of the age of air were carried out under three working conditions. According to the measured dimensions of the broiler chamber, a three-dimensional model of the broiler chamber was constructed, and then the model was simplified and meshed in ICEM CFD (integrated computer engineering and manufacturing code for computational fluid dynamics). Two models, i.e., the empty chamber mesh model and the chamber mesh model with block model, were imported in the Fluent software for calculation. In the experiment, 15 measurement points were selected to obtain the simulated and measured values of wind velocity. For the acquired data on wind velocity, the root mean square error (RMSE) was 19.1% and the maximum absolute error was 0.27 m/s, which verified the accuracy of the CFD model in simulating the ventilation system of the broiler chamber. The boundary conditions were further applied to the broiler chamber model to simulate the wind velocity and the age of air. The simulation results show that, when the temperature was between 32 and 34 °C, the average wind velocity on the plane of the corresponding broiler chamber (Y = 0.2 m) was higher than 0.8 m/s, which meets the requirement of comfortable breeding. At the lowest frequency of the fan, the oldest age of air was less than 150 s, which meets the basic requirement for broiler chamber design. An optimization idea is proposed for the age of air analysis under three working conditions to improve the structure of this smart broiler chamber. Full article

In this paper, we propose a remote sensing model based on a 1 × 1 km spatial resolution to estimate the spatio-temporal distribution of sunshine percentage (SSP) and sunshine duration (SD), taking into account terrain features and atmospheric factors. To account for the influence of topography and atmospheric conditions in the model, a digital elevation model (DEM) and cloud products from the moderate-resolution imaging spectroradiometer (MODIS) for 2010 were incorporated into the model and subsequently validated against in situ observation data. The annual and monthly average daily total SSP and SD have been estimated based on the proposed model. The error analysis results indicate that the proposed modelled SD is in good agreement with ground-based observations. The model performance is evaluated against two classical interpolation techniques (kriging and inverse distance weighting (IDW)) based on the mean absolute error (MAE), the mean relative error (MRE) and the root-mean-square error (RMSE). The results reveal that the SD obtained from the proposed model performs better than those obtained from the two classical interpolators. This results indicate that the proposed model can reliably reflect the contribution of terrain and cloud cover in SD estimation in Ghana, and the model performance is expected to perform well in similar environmental conditions. Full article

As the traditional methods for the recognition of air visibility level have the disadvantages of high cost, complicated operation, and the need to set markers, this paper proposes a novel method for the recognition of air visibility level based on an optimal binary tree support vector machine (SVM) using image processing techniques. Firstly, morphological processing is performed on the image. Then, whether the region of interest (ROI) is extracted is determined by the extracted feature values, that is, the contrast features and edge features are extracted in the ROI. After that, the transmittance features of red, green and blue channels (RGB) are extracted throughout the whole image. These feature values are used to construct the visibility level recognition model based on optimal binary tree SVM. The experiments are carried out to verify the proposed method. The experimental results show that the recognition accuracies of the proposed method for four levels of visibility, i.e., good air quality, mild pollution, moderate pollution, and heavy pollution, are 92.00%, 92%, 88.00%, and 100.00%, respectively, with an average recognition accuracy of 93.00%. The proposed method is compared with one-to-one SVM and one-to-many SVM in terms of training time and recognition accuracy. The experimental results show that the proposed method can distinguish four levels of visibility at a relatively satisfactory level, and it performs better than the other two methods in terms of training time and recognition accuracy. This proposed method provides an effective solution for the recognition of air visibility level. Full article