Optimal Scale of Urbanization with Scarce Water Resources: A Case Study in an Arid and Semi-Arid Area of China

A complex interwoven relationship exists between water resources and urbanization, which is of much interest in international water science research. To study the urban development in large cities facing water deficiency problems, it is important to identify rational thresholds of urbanization to achieve optimal utilization of limited water resources, and to promote sustainable economic and population growth and social development. A multi-objective optimization model is proposed to search for the optimal scale of urbanization of large cities with limited water resources. To solve a large-dimensional multi-objective optimization problem, the non-dominated sorting genetic algorithm (NSGA-II) is improved to the OENSGA-II based on the orthogonal generation method and the E-optimality method and applied to a typical arid city, Xi’an of China, which underwent rapid urbanization in recent years. For Xi’an, a statistically significant positive correlation is found between urbanization rate (Ur) and gross domestic product (GDP), domestic water, tertiary industry water, and ecological water. However, Ur is negatively correlated with the primary industry water. If the current urbanization trend continues, the water resources available are far from sufficient to support the future city of Xi’an. In this work, it was found that, by implementing restrictive water resources management and water saving measures, the economic threshold of Xi’an could be raised to 1890.3 and 2403.3 billion yuan, while the population threshold could be raised to 11.0 and 13.9 million, and Ur to 79.9% and 85.9% in 2020 and 2030, respectively. The corresponding maximum urban area to be constructed based on the projected population will be 964.81 and 1197.6 km2 in those years. It will be prudent for Xi’an to practice strict water resource management, and to allocate its water resources among various water sectors effectively and equitably to avoid major water shortage problems in the future

Assessment of vegetation growth and drought conditions using satellite-based vegetation health indices in Jing-Jin-Ji region of China

10.1038/s41598-021-93328-zScientific Reports1111377

Imaging Features of Early COVID-19 on Chest Thin-slice Non-Enhanced CT

Objective: To explore the characteristics findings of early COVID-19 on chest thin-slice non-enhanced CT. Materials and methods: From November to December 2022, data from 153 patients with COVID-19 with positive chest CT findings confirmed by the Department of Infectious Diseases of our hospital were collected. All patients had relatively complete clinical data and underwent chest CT 1-14 days after the onset. The patients were divided into two groups according to their age (≤60 years old and >60 years old) and the time interval between the onset and CT examination (≤7 days old and >7 days old), and the differences in CT features between the two groups were compared. Result: Among 153 patients with COVID-19, the lung (100%), blood vessels (93.5%), airways (73.4%), and pleura (70.1%) were involved. The comparison between the age groups showed statistically significant differences in the number, location, size, volume, and band shadow of the lesions. There were statistically significant differences in the shape, density, organization, fibrosis, and pleural involvement of the lesions between the patients in the time interval between the onset and CT examination. Conclusion: Chest thin-slice CT can clarify the location and scope of early COVID-19. Some characteristics findings can help for accurate diagnosis and differentiation, such as the diversity of morphology, intrapleural and perivascular distribution, interstitial lesions with alveoli as a unit, early mixed ground-glass shadow often accompanied by obvious organization and fibrosis, localized thickening of the pleura, and few pleural effusions