Emergy Accounting and Monte Carlo Uncertainty Data for Date Palm Production, Sistan and Baluchestan Province, Iran
Description
This dataset accompanies a study on the sustainability of date palm (Phoenix dactylifera L.) production in five counties of Sistan and Baluchestan Province, southeastern Iran (Iranshahr, Saravan, Nikshahr, Sib va Suran, and Sarbaz), using emergy accounting combined with Monte Carlo uncertainty analysis. The data span the full analytical chain: farm-level raw input and yield quantities collected per hectare from structured farmer interviews and regional meteorological and soil-loss records; the unit emergy value (UEV) coefficients and unit-conversion assumptions used to convert these inputs into solar emjoules (sej), with literature sources for each coefficient; the resulting emergy table, broken down into renewable environmental inputs, non-renewable environmental inputs, and purchased inputs split into renewable and non-renewable fractions; and the deterministic emergy-based sustainability indicators (Transformity, Emergy Yield Ratio, Environmental Loading Ratio, Emergy Sustainability Index, and related measures) computed from them. Because a single point estimate cannot convey the parametric uncertainty inherent in emergy models, the dataset also includes the configuration and results of a 500-iteration Monte Carlo simulation, in which all 21 UEV coefficients (±20%, triangular distribution) and all 21 raw per-hectare inputs (±10%, triangular distribution) were perturbed independently and the full emergy chain recomputed at each iteration. Distribution summary statistics (mean, standard deviation, coefficient of variation, percentiles, and the probability of falling below the conventional sustainability threshold) are provided for the Emergy Sustainability Index, Environmental Loading Ratio, Emergy Yield Ratio, renewable emergy share, and total emergy, by county. The full set of 500 simulated Emergy Sustainability Index values per county is included as raw iteration-level data to allow independent verification or re-analysis. Files are provided as CSV tables (the primary data records) and as a single Excel workbook combining the same tables for convenience. A README file documents each table's contents, units, and the methodological conventions used in the underlying emergy accounting (e.g., treatment of co-product environmental flows, renewable/non-renewable splits for purchased inputs).
Files
Steps to reproduce
Raw data collection. Farm-level input and yield data were collected per hectare through structured, face-to-face interviews with randomly selected date palm growers in each of the five counties, during a single production year. Environmental inputs (solar radiation, wind kinetic energy, rainfall chemical potential energy) and non-renewable environmental losses (soil erosion, soil organic matter loss, nitrogen loss) were derived from regional meteorological records and standard soil-loss equations. These values are recorded in 01_Base_Raw_Data.csv. Emergy conversion. Each raw input was multiplied by its corresponding Unit Emergy Value (UEV), listed with its literature source in 02_UEV_Coefficients_and_Assumptions.csv, to express it in solar emjoules (sej/ha). Renewable environmental inputs (solar, wind, rain) were combined as their maximum, following standard emergy convention for co-product flows, rather than summed. Non-renewable environmental losses were summed. Purchased inputs (labor, seed, fertilizers, machinery, biocides, electricity, fuel) were converted using their respective UEVs, with labor, seed/seedling, manure, and electricity split into renewable and non-renewable fractions as documented in the same file. This step reproduces 03_Emergy_Table.csv. Sustainability indicators. Total emergy and its components (R, N, FR, FN) were used to compute Transformity, Specific Emergy, % Renewable Emergy, Emergy Yield Ratio, Emergy Investment Ratio, Environmental Loading Ratio, and the Emergy Sustainability Index for each county, using the standard formulas of emergy accounting (Odum, 1996). Results are given in 04_Sustainability_Indices.csv. Monte Carlo simulation. Using Python, all 21 UEV coefficients and all 21 raw per-hectare inputs were treated as uncertain parameters and independently resampled 500 times from triangular distributions (mode equal to the baseline value; ±20% range for UEVs, ±10% range for raw inputs), as specified in 05_MonteCarlo_Configuration.csv and 05b_MonteCarlo_Uncertainty_Ranges.csv. At each of the 500 iterations, the full calculation chain in steps 2 and 3 was rerun to obtain Total Emergy, %R, EYR, ELR, and ESI. The simulation was validated by confirming that the zero-perturbation run reproduced the deterministic baseline in 04_Sustainability_Indices.csv exactly. Summary statistics. For each of the five tracked outputs and each county, the mean, standard deviation, coefficient of variation, minimum, percentiles (P5, P25, median, P75, and for ESI also P95 and maximum), and, for ESI, the proportion of iterations falling below the sustainability threshold of 1.0, were computed across the 500 iterations. These are reported in 06_MonteCarlo_Summary_Statistics.csv, with the underlying 500 simulated ESI values per county provided separately in 07_MonteCarlo_ESI_RawIterations.csv for independent recalculation of any statistic.
Institutions
- Zabol UniversitySistan and Baluchestan, Zabol