ABSTRACT
Sulfonamide antibiotics in the environment not only disrupt the ecological balance but can also enter the human or animal body in various forms and cause harm. Therefore, exploring efficient methods to degrade sulfonamide antibiotics is crucial. In this study, we prepared biochar (BC) using corn straw, and TiO2/BC was obtained by doping different proportions of TiO2 into biochar with varying carbonization temperatures using the sol-gel method. Next, we investigated the degradation of sulfamethoxazole (SMX) in solution using the generated TiO2/BC under ultraviolet irradiation and studied the effects of various experimental parameters, such as the type of composite material, composite material addition, solution pH, and initial antibiotic concentration on SMX degradation. Under an initial SMX concentration of 30 mg/L, the composite with the best photocatalytic degradation performance was TiO2/BC-5-300 (i.e., 5 mL of TiO2 doping; 300 °C calcination temperature), with an addition amount of 0.02 g and a solution pH of 3. The degradation efficiency increased from 22.3% to 89%, and the most significant degradation effect occurred during the initial stage of photocatalytic degradation. In the TiO2/BC-5-300 treated SMX solution, the average rhizome length of bean sprouts was significantly higher than that of the untreated SMX solution and slightly lower than that of the deionized aqueous solution (3.05 cm < 3.85 cm < 4.05 cm). This confirmed that the photocatalytic degradation of SMX by the composite was effective and could efficiently reduce its impact on the growth of bean sprouts. This study provides essential data and theoretical support for using TiO2/BC in the treatment of antibiotic-contaminated wastewater.
ABSTRACT
Forest roads are a major source of and transport pathway for eroded sediments in mountainous watersheds. When rills develop on these roads' surfaces, they amplify sediment erosion. Best management practices can decrease sediment erosion, but in order to efficiently implement these practices it is necessary to determine which factors have the most influence on rill development on forest roads. Despite this need, there is scarce literature on rill development on forest roads. To fill this gap in knowledge, based on field survey and multivariate statistical methods including redundancy analysis (RDA) and variation partitioning analysis (VPA), we investigated unpaved forest roads in the Xiangchagou watershed in China and quantified the extent to which various factors influenced rill formation. Specifically, we studied how rill erosion intensity (REI) and rill morphological characteristics (like rill length, mean width and depth, density, and severity of fragmentation) varied along the slope of a forest road. We also introduced the concept of a road's hydrological constituents (its upslope catchment, surface, and cutslopes), and determined how much each constituent contributed to REI. We found that REI and morphological characteristics decreased moving from the upper portion of road segment downward, implying that rills developed more intensely uphill. Additionally, REI increased exponentially with rill width, density, and severity of fragmentation, and increase linearly with length and depth. Conversely, REI decreased exponentially with rill width-depth ratio. These relationships suggest that the morphological characteristics of rills could be used to predict the REI of a given road segment. Finally, we found that the road characteristics that best predicted rill formation included catchment area, cutslope area, and gravel bareness. Correspondingly, the upslope catchment, cutslopes, and road surface contributed 11.56%, 30.83%, and 8.23% of the variation in REI and morphological characteristics. The interaction between upslope catchment and road surface explained 19.89% of the variation. These results suggest that when best management practices are implemented to decrease erosion caused by forest roads in mountainous watersheds, they should integrate these hydrological constituents of a road.
Subject(s)
Forests , Geologic Sediments , ChinaABSTRACT
Taking the Guangdong-Hong Kong-Macao Greater Bay Area as the research area, this paper used OD cluster analysis based on Baidu migration data from January 11 to January 25 (before the sealing-off of Wuhan) and concluded that there is a significant correlation 1the migration level from Wuhan to the GBA and the epidemic severity index. This paper also analyzed the migration levels and diffusivity of the outer and inner cities of the GBA. Lastly, four evaluation indexes were selected to research the possibility of work resumption and the rating of epidemic prevention and control through kernel density estimation. According to the study, the amount of migration depends on the geographical proximity, relationship and economic development of the source region, and the severity of the epidemic depends mainly on the migration volume and the severity of the epidemic in the source region. The epidemic risk is related not only to the severity of the epidemic in the source region but also to the degree of urban traffic development and the degree of urban openness. After the resumption of work, the pressure of epidemic prevention and control has been concentrated mainly in Shenzhen and Canton; the further away a region is from the core cities, the lower the pressure in that region. The mass migration of the population makes it difficult to control the epidemic effectively. The study of the relationship between migration volume, epidemic severity and epidemic risk is helpful to further analyze transmission types and predict the trends of the epidemic.
