Greenhouse Gas Modeling: A Simplified Approach.

Monitoring of greenhouse gases (GHGs) emissions is an inevitable and supplimental information for climate change debates and for plant or crop life cycle assessment. GHGs emission information can be useful in predicting soil health of an ecosystem that involved in a variety of intensive agricultural activities and pastoral-animal production system. GHGs measurements are labor intensive, time consuming, and an expensive procedure. The objective of the study was to develop a simplified method for GHGs modeling software for predicting emissions from agricultural systems. Two lines of emission data were generated; first, measured from experimental fields using Gas Chromatography (GC) and second, predicted from GHGs emission modeling software. Measured and predicted data sets showed 85% similarity (R² = 0.852; y = 0.9006x + 1.5856). The Chi-Square (χ²) test-critical value obtained at degree of freedom (39) was 0.62 which is far less than the table value of 55.76. This signifies that there is not significantly any differences found between these two data sets although they are coming from two different sources. Such analysis, at this point, was performed using Carbon dioxide (CO₂) data sets only, mainly because the site was not the sources for Nitrous oxide (N₂O) and Methane (CH₄) emissions.