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Meta Analysis ? AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button. Tier 1 ? Systematic review or meta-analysis. Synthesizes findings across many studies. Strongest evidence. Sign in to save

Dataset for:

Figshare 2026
luyao deng

Summary

Scientists compiled a massive global dataset combining hundreds of studies on how plastic pollution, from microplastics to plastic mulch films, affects soil health, specifically looking at how it changes the release of two gases: nitrous oxide (a powerful greenhouse gas) and ammonia. This matters because soil is the foundation of our food supply, and understanding how plastic waste disrupts the natural nitrogen cycle can help researchers predict impacts on crop growth, air quality, and climate change as plastic pollution continues to build up in farmland worldwide. While this dataset itself doesn't declare a single finding.

Study Type Review

Data Set DescriptionThis data set was compiled for a global meta-analysis designed to investigate the impact of plastic pollution on gaseous losses of soil nitrogen (N), with a particular focus on emissions of nitrous oxide (N₂O) and ammonia (NH₃). The dataset comprises multiple files and supports a variety of analytical methods, including meta-analysis, machine learning, meta-regression and structural equation modelling (SEM).Included data files:Biodegradable.xlsx – N₂O emission data from soil to which biodegradable plastics have been added.Non-biodegradable.xlsx – N₂O emission data from soil to which non-biodegradable plastics have been added.N2O.xlsx – N₂O emission data under plastic treatment conditions.NH3.xlsx – NH₃ emission data under plastic treatment conditions.N2O_add.xlsx – N₂O emission data under conditions where plastics are co-treated with other soil conditioners.NH3_add.xlsx – NH₃ emission data under conditions where plastics are co-treated with other soil conditioners.regression.xlsx – Data used for meta-regression analysis to explore moderating factors.SEM.xlsx – Data used for structural equation modelling to examine causal pathways.model_pred1.csv – Processed dataset used for machine learning model training and spatial prediction of nitrogen emissions.Research Methods:A systematic literature search was conducted in the Web of Science Core Collection and the China National Knowledge Infrastructure (CNKI) databases for peer-reviewed studies published between 2017 and 2026. The search term combination included: (“microplastics” OR “plastic film” OR “plastic mulch”) AND (“N₂O” OR “nitrous oxide” OR “NH₃” OR “ammonia volatilisation”) AND “soil”.Studies were included in the analysis if they met the following criteria: (1) reported paired observational data from plastic-treated and control groups; (2) provided mean values, standard deviations (or standard errors) and sample sizes; (3) were conducted in soil systems (including laboratory incubations, pot experiments and field trials); (4) reported N₂O or NH₃ flux rates or cumulative emissions.Data on gas emission rates, plastic characteristics (polymer type, concentration, particle size and degradation type), experimental conditions (temperature, soil moisture content, pH, soil organic carbon and nitrogen inputs) and study duration were extracted from the main text, tables or figures of the selected literature (using WebPlotDigitizer software). For studies reporting multiple time points, cumulative emissions or average fluxes were prioritised for extraction.Potential uses:This dataset can be used to: (1) compare the differing effects of biodegradable and non-biodegradable plastics on nitrogen emissions; (2) identify key regulators driving plastic-induced changes in the nitrogen cycle; (3) develop and validate predictive models for soil nitrogen emissions under plastic pollution scenarios; and (4) serve as a baseline for future global change studies on emerging pollutants in terrestrial ecosystems.

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