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STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT

STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
简称:STOCH ENV RES RISK A
ISSN:1436-3240
EISSN:1436-3240
研究方向:环境科学-工程:环境
自引率:5.60%
五年影响因子:3.6
JCI期刊引文指标 :0.99
h-index:57
Gold OA文章占比:16.69%

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STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT英文简介

Stochastic Environmental Research and Risk Assessment (SERRA) will publish research papers, reviews and technical notes on stochastic and probabilistic approaches to environmental sciences and engineering, including interactions of earth and atmospheric environments with people and ecosystems. The basic idea is to bring together research papers on stochastic modelling in various fields of environmental sciences and to provide an interdisciplinary forum for the exchange of ideas, for communicating on issues that cut across disciplinary barriers, and for the dissemination of stochastic techniques used in different fields to the community of interested researchers. Original contributions will be considered dealing with modelling (theoretical and computational), measurements and instrumentation in one or more of the following topical areas:

- Spatiotemporal analysis and mapping of natural processes.

- Enviroinformatics.

- Environmental risk assessment, reliability analysis and decision making.

- Surface and subsurface hydrology and hydraulics.

- Multiphase porous media domains and contaminant transport modelling.

- Hazardous waste site characterization.

- Stochastic turbulence and random hydrodynamic fields.

- Chaotic and fractal systems.

- Random waves and seafloor morphology.

- Stochastic atmospheric and climate processes.

- Air pollution and quality assessment research.

- Modern geostatistics.

- Mechanisms of pollutant formation, emission, exposure and absorption.

- Physical, chemical and biological analysis of human exposure from single and multiple media and routes; control and protection.

- Bioinformatics.

- Probabilistic methods in ecology and population biology.

- Epidemiological investigations.

- Models using stochastic differential equations stochastic or partial differential equations.

- Hazardous waste site characterization.

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