Abrupt changes in environmental temperature, wind and humidity can lead to great threats to human life safety. The Gansu marathon disaster of China highlights the importance of early warning of hypothermia from extremely low apparent temperature (AT). Here a deep convolutional neural network model together with a statistical downscaling framework is developed to forecast environmental factors for 1 to 12 h in advance to evaluate the effectiveness of deep learning for AT prediction at 1 km resolution. The experiments use data for temperature, wind speed and relative humidity in ERA-5 and the results show that the developed deep learning model can predict the upcoming extreme low temperature AT event in the Gansu marathon region several hours in advance with better accuracy than climatological and persistence forecasting methods. The hypothermia time estimated by the deep learning method with a heat loss model agrees well with the observed estimation at 3-hour lead. Therefore, the developed deep learning forecasting method is effective for short-term AT prediction and hypothermia warnings at local areas.

Dust is one of the atmospheric pollutants that have adverse environmental effects and consequences. Dust fall contains particles of 100 microns or even smaller ones, which fall from the atmosphere onto the earth surface. The aim of this study is to determine the concentration of lead in dust fall samples in order to study the pollution level of this element in Zahedan, Sistan and Baluchistan Province, Iran. Therefore, sampling was carried out using 30 marble dust collectors (MDCO) for 3 months in the spring of 2015 to investigate the quantitative variation and spatial analysis of lead content in dust fall. These dust collectors were placed at 30 stations on the building roofs with a height of approximately 1.5 meters across the city. According to the results, the mean lead concentration in the spring was 90.16 mg/kg. In addition, the zoning map of lead content shows that the lowest level of lead was measured at Imam Khomeini station while the highest amount of lead appeared in Mostafa Khomeini station.

Based on Landsat–7ETM + images of 2007 and 2012 and Landsat–8 images of 2018, this study took Fuyang City, Anhui Province (Yingzhou District, Yingdong District, Yingquan District) as the research object, and made a quantitative analysis of land use/cover change in Fuyang City from 2007 to 2018 with the Environment for Visualizing Images (ENVI) software. According to the data of land use types in three phases, the article analyzes the development trend of various land use types and the main reasons for the changes of land use, which provides a certain basis for the urban planning and environmental construction of Fuyang City. The results show that with the rapid economic development and continuous improvement of the urbanization level in Fuyang City during 11 years, the area of various land types in the study area has changed greatly. The area of construction land area changed by 448.27 km², with an increase of 543.57%; the area of arable land changed by 597.52 km², with a decrease of 34.74%; the area of bare land changed by 26.00 km², with a decrease of 80.68%. The changes were closely related to the rapid economic and social development in the study area. Under the influence of environmental protection policies and environmental awareness, the area of forest land changed by 85.00 km², with an increase of 97.58%; the water area changed by 84.35 km², with an increase of 201.39%.

The most crucial factor in producing papaya seedlings successfully is seed germination. The purpose of this study was to investigate the influence of seed priming with growing media on seed germination and seedling growth of papaya from October to December 2022. The experimental treatments included three seed priming treatments: T₀ = control (no seed priming treatments), T₁ = GA₃ (100 ppm), and T₂ = KNO₃ (1%), and four growing media, viz., M₁ = soil + vermicompost (1:1), M₂ = soil + cowdung (1:1), M₃ = soil + cocopeat + vermicompost (1:1:1), and M₄ = soil + cocopeat + cowdung (1:1:1). The treatments showed a significant effect on different parameters such as germination percentage, days to germination, survival percentage, chlorophyll content, seed vigor index, shoot, and root length. GA₃ treated seedlings performed better than non-GA₃-treated seedlings. Among the growing media, M₃ showed the best for seed germination and other growth attributes compared to other growing media. In terms of interaction effects, T₁M₃ showed the highest performance for germination percentage (84.33%), survival percentage (91.0%), and chlorophyll content (44.26%). T₁M₃ also showed the highest seed vigor index, shoot and root growth, and plant biomass. As a result, the combination of GA₃ and growing media containing soil + cocopeat + vermicompost was shown to be the most favorable for papaya seed germination and seedling growth.

Nanotechnology is recognized as one of the high and new technologies in the 21st century. Carbon nanotubes have been widely used in molecular sieve, drug transport and seawater desalination due to their unique mechanical, electrical, optical and other excellent properties. As the main representative of carbon nanotube macroscopic materials, carbon nanotube film not only retains the microscopic properties of carbon nanotube, but also has good mechanical properties and stable chemical properties. The preparation and application of carbon nanotubes (CNTS) have attracted extensive attention from scholars at home and abroad. In this paper, the research on carbon nanotube films in recent years is reviewed. Based on the preparation of carbon nanotube films, chemical vapor deposition, LB (Langmuir-Blodgett) film and electrostatic layer-by-layer self-assembly techniques are briefly described. In addition, the applications of carbon nanotubes in biological field, photoelectric nano devices, water treatment, seawater desalination and other fields are also described.