Understanding the relative contributions of climate change and human activities to changes in runoff is important for sustainable management of regional water resources. In this study, we systematically review ten commonly used quantitative methods drawn from three main categories-empirical statistics, elasticity-based methods, and hydrological modeling. We explain the calculation processes for the different methods and summarize their applications and characteristics. Then, using the Yanhe River basin as a case study, we employ all ten methods to separate out the effects of climate change and human activities on changes in runoff. The results show that climate change played a dominant role in the decline in runoff in the Yanhe River basin. Climate change was estimated to account for 46.1%-60.8% (mean 54.1%) of the total decrease in runoff, whereas human activities accounted for 39.1%-53.9% (mean 45.9%). Elasticity-based methods and hydrological modeling produced similar estimates, but the estimates made using empirical statistics were different. Empirical statistics were not a suitable method for the Yanhe River basin. We also discuss the factors that influence the different methods and the applicable conditions for each methodological category.
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http://dx.doi.org/10.1016/j.scitotenv.2017.02.010 | DOI Listing |
Environ Sci Technol
January 2025
School of Ecology and Environmental Science, Yunnan University, Kunming 650504, China.
Safer chemical alternatives to bisphenol (BP) have been a major pursuit of modern green chemistry and toxicology. Using a chemical similarity-based approach, it is difficult to identify minor structural differences that contribute to the significant changes of toxicity. Here, we used omics and computational toxicology to identify chemical features associated with BP analogue-induced embryonic toxicity, offering valuable insights to inform the design of safer chemical alternatives.
View Article and Find Full Text PDFArch Microbiol
January 2025
Institute for Tropical Biology and Conservation, Universiti Malaysia Sabah, Jalan, UMS, 88400, Kota Kinabalu, Sabah, Malaysia.
The agricultural productivity and world-wide food security is affected by different phytopathogens, in which Fusarium is more destructive affecting more than 150 crops, now got resistance against many fungicides that possess harmful effects on environment such as soil health, air pollution, and human health. Fusarium fungicide resistance is an increasing concern in agricultural and environmental contexts, requiring a thorough understanding of its causes, implications, and management approaches. The mechanisms of fungicide resistance in Fusarium spp.
View Article and Find Full Text PDFNeuropsychopharmacol Rep
March 2025
National Center of Neurology and Psychiatry, National Institute of Mental Health, Kodaira, Tokyo, Japan.
Aim: The Internet Gaming Disorder Scale is a 9-item screening instrument developed based on the diagnostic criteria for Internet Gaming Disorder (IGD) in the DSM-5. This study aimed to examine the reliability and validity of the Internet Gaming Disorder Scale for children (IGDS-C) in Japanese clinical and nonclinical populations.
Methods: The study included clinical outpatients aged 9-29 with problematic game use and nonclinical adolescents aged 12-18 who played online games at least once a week.
Health Phys
January 2025
Atmospheric Technologies Group, Savannah River National Laboratory, Aiken, SC.
Pollutants from anthropogenic activities including industrial processes are ubiquitous to the environment. To understand the impact from industrial aerosol on climate and human health, industrial aerosol needs to be better characterized. In this study, particle number concentrations were used as a proxy for atmospheric pollutants, which include both particles and gases.
View Article and Find Full Text PDFCells
December 2024
Department of Herbal Pharmacology, College of Korean Medicine, Gachon University, 1342 Seongnamdae-ro, Sujeong-gu, Seongnam-si 13120, Republic of Korea.
The NLRP3 inflammasome, plays a critical role in the pathogenesis of rheumatoid arthritis (RA) by activating inflammatory cytokines such as IL1β and IL18. Targeting NLRP3 has emerged as a promising therapeutic strategy for RA. In this study, a multidisciplinary approach combining machine learning, quantitative structure-activity relationship (QSAR) modeling, structure-activity landscape index (SALI), docking, molecular dynamics (MD), and molecular mechanics Poisson-Boltzmann surface area MM/PBSA assays was employed to identify novel NLRP3 inhibitors.
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