Sludge Pasteurization¶

QSDsan: Quantitative Sustainable Design for sanitation and resource recovery systems

This module is developed by:

Yalin Li <mailto.yalin.li@gmail.com>

Shion Watabe <shionwatabe@gmail.com>

Hannah Lohman <hlohman94@gmail.com>

Tori Morgan <vlmorgan@illinois.edu>

This module is under the University of Illinois/NCSA Open Source License. Please refer to https://github.com/QSD-Group/QSDsan/blob/main/LICENSE.txt for license details.

class qsdsan.sanunits._sludge_pasteurization.SludgePasteurization(ID='', ins: Sequence[Stream] | None = None, outs: Sequence[Stream] | None = (), thermo=None, init_with='WasteStream', include_construction=True, if_biogas=True, heat_loss=0.1, target_MC=0.1, sludge_temp=283.15, temp_pasteurization=343.15, if_combustion=False, biogas_loss=0.1, biogas_eff=0.55, lhv_lpg=48.5, lhv_methane=52.5, ppl=100, baseline_ppl=100, user_scale_up=1, exponent_scale=1, if_sludge_service=True, **kwargs)¶

Unit operation for the pasteurization of sludge using liquid petroleum gas (LPG) or biogas.

Cost and environmental impacts of this unit are based on the hydronic heat exchanger and dryer in the biogenic refinery.

The following impact items should be pre-constructed for life cycle assessment: StainlessSteel, Steel, HydronicHeatExchanger, Pump.

Note

Cost and environmental impacts of this unit are fixed (i.e., they DO NOT scale with mass or energy flows).

Parameters:

ins (Iterable(stream)) – biogas: biogas input from the AnMBR and used for pasteurization (biogas combusted). air: used for combustion, from atmosphere. sludge: sludge produced from the AnMBR in the NEWgenerator. LPG: purchased LPG to supplement heat requirement for pasteurization.
outs (Iterable(stream)) – used: biogas used in combustion. lost: biogas lost in combustion (e.g., leaked as fugitive biogas). wasted: biogas wasted in combustion. treated sludge: sludge treated from pasteurization.
if_combustion (bool) – If include combustion reaction during simulation.
biogas_loss (float) – Fraction of biogas loss is 0.1 (e.g., leaked).
biogas_eff (float) – Combustion efficiency of biogas as a fraction of CH4.
temp_pasteurization (float) – Pasteurization temperature is 70°C or 343.15 K.
sludge_temp (float) – Temperature of sludge is 10°C or 283.15 K.
target_MC (float) – Target moisture content is 10%
heat_loss (float) – Heat loss during pasteurization process is assumed to be 10%
if_biogas (bool) – If biogas is used for sludge pasteurization, otherwise LPG is used and biogas combusted.
lhv_lpg (float) – Lower heating value of LPG at 298.15K is 46-51 MJ/kg based on World Nuclear Organization.
lhv_methane (float) – Lower heating value of methane at 298.15K is 50-55 MJ/kg based on World Nuclear Organization.
hhx_heat_recovery (float) – Heat recovery efficiency of the heat exchanger.
ppl (int) – Total number of users for scaling of costs.
baseline_ppl (int) – Baseline capacity of the unit for scaling of costs.
user_scale_up (float) – Scaling factor (calculated based on the number of users as in ppl compared to the capacity as in baseline_ppl) for consumables, electricity demand, capital parts, and replacement parts. If not given (or set to None), will be calculated based on the user number and the capacity of this unit (i.e., the baseline_ppl attr).
exponent_scale (float) – Exponential factor for the scaling up of capital costs.
if_sludge_service (bool) – If share sludge pasteurization unit among multiple septic tanks (assume 1,000 users per sludge pasteurization unit, or 10 septic tanks serving a population of 100 users per septic tank).

References

[1] Shoener et al., Design of Anaerobic Membrane Bioreactors for the Valorization of Dilute Organic Carbon Waste Streams. Energy Environ. Sci. 2016, 9 (3), 1102–1112. https://doi.org/10.1039/C5EE03715H.

[2] Turek et al., Proposed EU Legislation to Force Changes in Sewage Sludge Disposal: A Case Study. Front. Chem. Sci. Eng. 2018, 12 (4), 660–669. https://doi.org/10.1007/s11705-018-1773-0.

[3] Rowles et al., Financial viability and environmental sustainability of fecal sludge treatment with Omni Processors, ACS Environ. Au, 2022, https://doi.org/10.1021/acsenvironau.2c00022