DOI: 10.5061/dryad.wh70rxx1n
title: The interplay between climate warming driven by greenhouse gas emissions and the ecotoxicological effects of microplastics: Insights from a meta-analysis

description: An increasing number of studies have revealed the interconnections and
 interactions between global warming and microplastics. However, research
 in this field is still in its early stages, with fragmented content and
 inconsistent conclusions. Therefore, this paper adopts a meta-analysis
 method to summarize and analyze the relevant literature in this area.
 After screening, a total of 39 research papers and 730 data points related
 to the interactions between global warming and microplastic pollution were
 obtained. The research results indicate that, on one hand, soil
 microplastic pollution significantly increases greenhouse gas CO2
 emissions by 140.20%, N2O emissions by 195.27% and Global Warming
 Potential by 172.10%, thereby exacerbating global warming. By introducing
 explanatory variables for analysis, it was found that microplastic type,
 soil type, and soil dissolved organic carbon are important influencing
 factors. On the other hand, the study also explains that the rise in water
 temperature due to global warming amplifies the biological toxicity
 effects of microplastics. By collecting data and conducting a
 meta-analysis on key physiological indicators of aquatic organisms, such
 as survival rate and predation rate, as well as critical enzymatic markers
 like CAT and EROD. Increasing water temperature can lead to oxidative
 damage and poisoning in aquatic animals. The bidirectional interaction
 mechanism between microplastic pollution and global warming may form a
 vicious cycle, further increasing the vulnerability of ecosystems. This
 study provides a theoretical basis and research direction for addressing
 the dual threats of microplastic pollution and global warming.
description: # The interplay between climate warming driven by greenhouse gas emissions
 and the ecotoxicological effects of microplastics: Insights from a
 meta-analysis Dataset DOI:
 [10.5061/dryad.wh70rxx1n](10.5061/dryad.wh70rxx1n) ## Description of the
 data and file structure We selected the Web of Science Core Collection as
 the primary source of literature. The search keywords were set as follows:
 "ALL= (("microplastic*" OR "nanoplastic*") AND
 ("warm*" OR "climate*" OR "greenhouse gas*"
 OR "GHG*" OR "CO2*" OR "CH4*" OR
 "N2O*" OR "temperature*"))". This search was
 limited to the period from January 1, 2004, to December 5, 2024, resulting
 in a total of 2945 relevant publications. To ensure the reliability of the
 research, the selected literature had to meet the following stringent
 criteria: (1) The study contains the emissions of major greenhouse gases
 (CO2, N2O, CH4) or GWP values before and after the addition of
 microplastics. (2) The study is required to incorporate data on the
 physiological activities (survival rate, predatory performance, growth) of
 aquatic animals and key functional enzymes or markers (CAT, GST, LPO,
 EROD, AChE) under different temperatures, both in the presence and absence
 of microplastics. (3) The experiment was designed to be a replicated
 controlled experiment, with a minimum of two replications and a blank
 control group, which is a group without the addition of microplastics. (4)
 The raw data had to be presented in the form of mean ± standard deviation
 (SD) or mean ± standard error (SE). (5) The study is required to include
 relevant influencing factors (soil pH, DOC, types of microplastics, and
 whether they are aged). ### Files and variables #### File: data.zip
 **Description:** The data includes both raw data and processed data The
 raw data includes map data, soil data, and toxicity data. The soil data
 contains information on three greenhouse gases as well as Global Warming
 Potential (GWP). The toxicity data includes data on eight physiological
 and key enzymatic indicators, organized according to different analytical
 requirements. The processed data consists of the results from a
 meta-analysis on the relationship between soil microplastic pollution and
 greenhouse gas emissions, including effect sizes and 95% confidence
 intervals. It also includes the results of meta-analysis reliability
 tests, such as the fail-safe number and Egger's test. The temperature
 unit is degrees Celsius (°C), and DOC and TOC units are mg/kg soil. The
 empty cells in the uploaded table are filled with “N/A”, representing that
 the value is not available or not applicable. All variables (column names)
 in the Meta-analysis Data. Detailed annotation information is provided
 below: Abbreviations Corresponding full forms | **Abbreviations** |
 **Corresponding full forms** | | :---------------- |
 :--------------------------- | | GWP | Global Warming Potential | | DOC |
 Dissolved Organic Carbon | | TOC | Total Organic Carbon | | EROD |
 Ethoxyresorufin-O-deethylase | | GST | Glutathione S-transferase | | LPO |
 Lipid Peroxidation | | AChE | Acetylcholinesterase | | CAT | Catalase | |
 V | virgin | | A | aged | | sd | Standard error | | main | Arithmetic mean
 | ## Code/software Effect sizes and 95% confidence intervals (CIs) were
 calculated using the “metafor” package in R Studio (version 4.3.3). A
 mixed-effects model was employed to assess heterogeneity, and subgroup
 analyses were conducted to evaluate how different soil parameters and
 microplastic characteristics influence greenhouse gas emissions. To assess
 publication bias, funnel plots were used, which help visualize the
 distribution of studies in a meta-analysis. Symmetry in the funnel plot is
 a key indicator of the absence of publication bias. Specifically, if the
 plot is symmetrical and the studies are evenly distributed around the
 central axis, it suggests no publication bias. In contrast, asymmetry may
 indicate the presence of such bias. Egger’s regression test was applied
 for a quantitative assessment. A P-value (P) greater than 0.05 indicates
 no publication bias, whereas a P-value less than 0.05 suggests its
 presence. Additionally, the fail-safe number was used as a robustness
 check. If the fail-safe number exceeds “5N + 10” (where N is the number of
 studies), the results are considered robust. ## Access information Data
 was derived from the following sources: References for Meta-Analysis: An,
 Z., Chen, F., Hou, L., Chen, Q., Liu, M., & Zheng, Y. (2024).
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