کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5750345 1619696 2017 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Epidemiological analysis of ozone and nitrogen impacts on vegetation - Critical evaluation and recommendations
ترجمه فارسی عنوان
تجزیه و تحلیل اپیدمیولوژیک اثرات ازن و نیتروژن بر روی گیاهان - ارزیابی و توصیه های انتقادی
کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم محیط زیست شیمی زیست محیطی
چکیده انگلیسی


- Epidemiology of air pollution impacts on vegetation is under strong development.
- Epidemiological data analysis is a good tool to validate dose-response relationships.
- It allows analysis of interactions between environmental impacts and site factors.
- It contributes to the understanding of ecological processes.
- Recommendations on mapping of predictors and on the statistical analysis are made.

For human health studies, epidemiology has been established as important tool to examine factors that affect the frequency and distribution of disease, injury, and other health-related events in a defined population, serving the purpose of establishing prevention and control programs. On the other hand, gradient studies have a long tradition in the research of air pollution effects on plants. While there is no principal difference between gradient and epidemiological studies, the former address more one-dimensional transects while the latter focus more on populations and include more experience in making quantitative predictions, in dealing with confounding factors and in taking into account the complex interplay of different factors acting at different levels. Epidemiological analyses may disentangle and quantify the contributions of different predictor variables to an overall effect, e.g. plant growth, and may generate hypotheses deserving further study in experiments. Therefore, their use in ecosystem research is encouraged. This article provides a number of recommendations on: (1) spatial and temporal aspects in preparing predictor maps of nitrogen deposition, ozone exposure and meteorological covariates; (2) extent of a dataset required for an analysis; (3) choice of the appropriate regression model and conditions to be satisfied by the data; (4) selection of the relevant explanatory variables; (5) treatment of interactions and confounding factors; and (6) assessment of model validity.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Science of The Total Environment - Volumes 603–604, 15 December 2017, Pages 785-792
نویسندگان
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