Dataset on the effects of artificial humic substances and straw incorporation on greenhouse gas emissions and soil properties in cold-region paddy soils

1. Research hypothesis
This dataset was generated as part of a study testing the hypothesis that artificial humic substances (A-HS), as redox-active organic amendments, can reduce CH₄ and N₂O emissions in cold-region paddy fields by modifying soil redox potential (Eh) and reducing labile carbon availability, and that their effects differ from or interact with conventional straw incorporation.

2. Description of data
The dataset includes time-series measurements of greenhouse gas (GHG) fluxes (CO₂, CH₄, and N₂O), soil physiochemical properties (Eh, pH, dissolved organic carbon, ammonium and nitrate nitrogen), and rice biomass components under eight different treatments. Treatments included A-HS alone (at 0.1%, 0.2%, and 0.3% w/w), straw incorporation alone, and combined applications. Data were recorded at multiple time points across the rice growing season and organized in Excel sheets corresponding to individual figures and results sections of the manuscript.

3. Data collection method
The data were obtained through a pot experiment conducted at the Northeast Agricultural University in Harbin, China, using Mollisol soil. Greenhouse gas fluxes were measured using a static chamber–gas chromatography system. Soil samples (0–20 cm) were collected every 7 days, and analyzed for Eh (using a redox electrode), DOC (via TOC analyzer), and mineral nitrogen (via UV spectrophotometry). CO₂, CH₄, and N₂O concentrations were measured weekly during the rice growing season using gas chromatography. Rice biomass was recorded at maturity.

4. Interpretation and usage
These data enable researchers to reproduce the trends reported in the manuscript, verify analytical conclusions, or perform meta-analysis on the effects of organic amendments on GHG emissions and soil chemistry. Each column in the Excel file is clearly labeled with variable name, unit, treatment code, and sampling date. The dataset supports the interpretation that A-HS can reduce CH₄ and N₂O emissions via redox regulation and substrate limitation, and provides numeric support for calculating GWP and GHGI metrics under different treatment conditions.