Inferring pathogen inactivation from the surface temperatures of compost heaps

Area of Science:

• Environmental Science
• Agricultural Engineering
• Microbiology

Background:

• High composting temperatures are essential for inactivating pathogens in animal waste.
• Direct core temperature monitoring in compost heaps is challenging, leading to infrequent monitoring.
• Surface temperature monitoring offers a potential alternative for inferring core conditions.

Purpose of the Study:

• To assess the feasibility of predicting compost core temperatures from surface temperature data.
• To evaluate methods for measuring surface temperatures in composting heaps.
• To develop a model for inferring pathogen inactivation potential from surface temperature readings.

Main Methods:

• Utilized thermal imaging and thermocouples to measure surface temperatures of composting pig farmyard manure (FYM).
• Employed time series analysis to develop a predictive model for core temperatures based on surface data.
• Compared model predictions with actual core temperature measurements in aerated heaps.

Main Results:

• The developed model accurately predicted core temperatures in well-insulated sections of the compost heap for a limited duration.
• Prediction accuracy decreased near the compost heap surface and the aeration pipe.
• Demonstrated a correlation between surface and core temperatures, albeit with spatial and temporal variations.

Conclusions:

• Surface temperature monitoring, combined with predictive modeling, can provide valuable insights into compost core conditions.
• This approach offers a practical method for estimating pathogen inactivation potential in animal waste composting.
• Further refinement of models is needed to improve accuracy across all parts of the compost heap, especially near boundaries and aeration systems.