Quantification of greenhouse gas emissions from pilot sludge treatment reed beds and unplanted drying beds under a hot and arid climate.

Sludge Treatment Reed Beds (STRB) are an established sustainable technology for sludge dewatering and stabilization. The investigation and optimization of these systems are still ongoing under various climates; however, most studies focus on the dewatering efficiency and the optimum sludge loading rate (SLR), and little attention has been given so far to the related greenhouse gas emissions (GHG). Thus, this study investigates the intricate dynamics of GHG emissions (CO2, CH4, NO, NH3) in pilot-planted STRB and conventional unplanted sludge drying beds under a hot and arid climate, testing three different SLRs: 75, 100, and 125 kg/m2/yr. The findings revealed that CO2 and CH4 emissions were virtually absent in both systems. On the other hand, significant differences were observed in nitrogen oxide (NO) and ammonia (NH3) emissions. STRB exhibited higher NO concentrations, while unplanted drying beds displayed elevated NH3 levels. The data indicate that the highest mean emissions were observed at different sludge loading rates (SLRs) across the different treatments: NO emissions peaked at 75 SLR in the reed bed (2.50 kg/m2/year) and at 100 SLR in the unplanted bed (0.54 kg/m2/year), while NH3 emissions peaked at 125 SLR in the reed bed (2.76 kg/m2/year) and at 100 SLR in the unplanted bed (6.16 kg/m2/year). This disparity can be attributed to the nitrification taking place in the aerobic STRB and the moisture-driven NH3 production in the unplanted drying beds. The statistical analysis confirmed the significant impact of SLR on NO and NH3 emissions. Furthermore, a positive correlation was found between temperature fluctuations and GHG emissions, underscoring the influence of climate on GHG release during sludge treatment. These findings provide critical insights for environmental scientists and engineers seeking to optimize GHG management in wastewater and sludge treatment processes while considering various load conditions and environmental factors.