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Sar and Qsar in Environmental Research - Taylor & Francis | 2024 Impact Factor:2.4 | Cite Score:4.2 | Q3

Sar and Qsar in Environmental Research Journal

Impact Factor and Journal Rank of Sar and Qsar in Environmental Research

  • About: Objective:
    SAR and QSAR in Environmental Research aims to publish high-quality research papers, reviews, and communications that advance the understanding and application of Structure-Activity Relationship (SAR) and Quantitative Structure-Activity Relationship (QSAR) methodologies in environmental research and toxicology.
  • Publication Focus:
    Modeling Approaches: Innovative SAR and QSAR models for predicting environmental fate, behavior, toxicity, and risk assessment of chemicals, pollutants, and contaminants. Data Sources and Methodologies: Advances in data collection, curation, and computational methodologies relevant to SAR and QSAR modeling in environmental sciences. Chemical and Environmental Monitoring: Applications of SAR and QSAR in the monitoring and analysis of chemical pollutants in environmental matrices. Regulatory Applications: Contributions addressing the use of SAR and QSAR in regulatory frameworks, including chemical hazard assessment and environmental management. Case Studies and Applications: Real-world case studies, applications, and validation studies demonstrating the utility and effectiveness of SAR and QSAR models in environmental research.
  • Research Areas:
    Environmental Toxicology: SAR and QSAR models for predicting the toxicity and ecotoxicity of chemicals to aquatic and terrestrial organisms. Chemical Risk Assessment: Quantitative approaches for assessing the environmental and human health risks posed by chemical pollutants. Ecological Modeling: Modeling approaches to understand the ecological impacts and interactions of chemicals in environmental systems. Bioaccumulation and Biomagnification: Predictive modeling of bioaccumulation and biomagnification of chemicals in food webs and ecosystems. Environmental Monitoring and Management: Integration of SAR and QSAR with environmental monitoring data for improved environmental management and decision-making.
  • Contributions:
    SAR and QSAR in Environmental Research welcomes original research articles, reviews, short communications, and technical notes that contribute significant insights and advancements to SAR and QSAR methodologies in environmental science. The journal encourages interdisciplinary research that integrates chemistry, toxicology, environmental science, and computational modeling to address complex environmental challenges.
  • Conclusion:
    SAR and QSAR in Environmental Research serves as a vital platform for researchers, practitioners, regulators, and policymakers to share knowledge, collaborate on solutions, and advance the field of environmental chemistry and toxicology. By promoting innovative research and facilitating dialogue, the journal aims to enhance our understanding of chemical impacts on the environment and support sustainable environmental management practices.

  • Editor-in-Chief:  James Devillers

  • Scope: Structure-activity relationship (SAR) studies in environmental chemistry and toxicology
  • Quantitative structure-activity relationship (QSAR) modeling for environmental pollutants
  • Computational methods and predictive modeling in environmental research
  • Environmental fate and transport modeling of chemicals
  • Bioavailability and bioaccumulation studies
  • Toxicity assessment and risk analysis of environmental contaminants
  • Molecular modeling and simulation approaches in environmental science
  • Case studies and applications of SAR and QSAR methodologies in environmental studies
  • Latest Research Topics for PhD in Computer Science

  • Print ISSN:  1062-936X

    Electronic ISSN:  1029-046X

  • Abstracting and Indexing:  Science Citation Index Expanded, Scopus.

  • Imapct Factor 2024:  2.4

  • Subject Area and Category:  Biology, Health Sciences

  • Publication Frequency:  Monthly

  • H Index:  56

  • Best Quartile:

    Q1:  

    Q2:  

    Q3:  Bioengineering

    Q4:  

  • Cite Score:  4.2

  • SNIP:  0.607

  • Journal Rank(SJR):  0.342