Irrigated and flooded rice is associated with methane (CH₄) emissions. CH₄ is one of the most important anthropogenic greenhouse gases (GHG) in the atmosphere. Nowadays, mapping CH₄ content at a global scale is possible using satellite sensors. Sample of such a sensor is TROPOspheric Monitoring Instrument (TROPOMI) placed on the Sentinel-5 Precursor (Sentinel-5P) satellite board. In this study, the evaluation of spatial-temporal changes in CH₄ content in the atmosphere for selected countries and regions with high CH₄ emissions from rice cultivation in 2019–2021 was performed. Visual evaluation of the spatial variability on CH₄ content for the total study period indicates higher CH₄ content for almost all areas with high rice concentration. This was confirmed by positive correlations between CH₄ content in the atmosphere and estimated GHG emissions from croplands analyzed separately for each studied country/region. In addition, seasonal changes in CH₄ content in the atmosphere were observed. The lowest CH₄ content was observed at the beginning of the year (for the first quarter of the year) and the highest for the third quarter of the year. Moreover, a long-term increase in CH₄ was noticed. Regression analysis revealed that the mean increase in CH₄ content in most of the studied regions/countries was about 15 ppb per year. CH₄ content evaluated with the use of satellite data from Sentinel-5P is a reliable data source and can be used for the analysis of temporal changes at various spatial scales, including regions and countries.

Methane (CH₄) emissions from agricultural sources contribute significantly to the total anthropogenic greenhouse gas emissions, which cause climate change. According to the guidelines of the International Panel on Climate Change (IPCC) for calculating greenhouse gas emissions, agriculture is responsible for approximately 10% of total CH₄ emissions from anthropogenic sources. CH₄ is primarily emitted from livestock farming, particularly from cattle production during enteric fermentation and from manure. This article describes the results of multivariate statistical analyses carried out on data collected from 1961 to 2020 for thirty countries with the largest cattle populations. The study evaluated the trends in temporal changes in cattle populations and identified groups of countries with similar patterns during the study period. The global cattle population was highly correlated with CH₄ emissions from the enteric fermentation of cattle and their manure. The countries experiencing the largest increase in cattle population were primarily developing countries located in South America, Africa and Southeastern Asia. The cattle population in these countries showed a strong correlation with the human population. On the other hand, the countries where the cattle population remained stable during the study period were mainly highly developed countries. The correlations between most of the examined variables associated with cattle production and the cattle population in these countries were inconsistent and relatively weak. In the near future, further increase in the cattle population and the associated CH₄ emissions are expected, mainly in developing countries with high population growth.

Methane (CH4) emissions from agricultural sources make a significant contribution to the total anthropogenic greenhouse gas emissions that contribute to climate change. According to the International Panel on Climate Change (IPCC) guidelines for calculating greenhouse gas emissions, agriculture is responsible for approximately 10% of total CH4 emissions from anthropogenic sources. CH4 is mainly emitted from livestock farming, especially from cattle production during enteric fermentation and from manure. The article describes the results of multivariate statistical analyzes carried out on data collected in 1961–2020 based on the data for 30 countries with the largest cattle population. The trends of temporal changes in cattle population were evaluated and groups of countries with similar patterns in the study period were distinguished. Variables which are correlated with changes in the number of cattle were indicated. Forecasts of cattle population and CH4 emission related to cattle for the coming years are presented.