Experimental Investigation and Component-Level Modelling of a Self-Regulating Small-Scale Vapour-Compression Atmospheric Water Generator

Atmospheric water harvesting using small-scale vapour-compression systems offers a decentralised water source, but performance varies strongly with ambient psychrometric conditions. This study experimentally evaluates a compact propane (R290) atmospheric water generator with series-coupled evaporator and condenser airflow and develops a component-level model of its partially wet fin-and-tube evaporator. Three extended tests were used to characterise operation. Model predictions were compared with cumulative collected water using a dry–wet coil formulation and refrigerant-side capacity matching. The simulated cumulative water production differed from the measured value by 6%. In the two 24 h tests, the unit produced 7.0 L outdoors and 4.5 L indoors using 7.2 kWh in each case, corresponding to specific energy consumptions of 1.03 and 1.60 kWh L−1, respectively. Water production was higher under the more humid inlet conditions. The model predicted higher water production at the lower nominal fan setting, reaching approximately 0.50–0.54 L h−1. Predicted compressor power also increased. The analysed outdoor profile showed its highest production during the nocturnal high-humidity period; this is a profile-specific result rather than an annual operating window. The model provides a basis for comparing operating trends under different inlet conditions

Authors

Institutions

Publication Details

Journal
Artificial Intelligence for Sustainable Cities
Published
2026-10-29
DOI
https://doi.org/10.65582/aifsc.2026.015
Primary Topic
Solar-Powered Water Purification Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Experimental Investigation and Component-Level Modelling of a Self-Regulating Small-Scale Vapour-Compression Atmospheric Water Generator

Emmanuel Tapia-Brito, Mehmet Tahir ERDİNÇ, Çağrı Kutlu
1 links
Artificial Intelligence for Sustainable Cities
Solar-Powered Water Purification Methods
article

Experimental Investigation and Component-Level Modelling of a Self-Regulating Small-Scale Vapour-Compression Atmospheric Water Generator

Emmanuel Tapia-Brito, Mehmet Tahir ERDİNÇ, Çağrı Kutlu
article en

Abstract

Atmospheric water harvesting using small-scale vapour-compression systems offers a decentralised water source, but performance varies strongly with ambient psychrometric conditions. This study experimentally evaluates a compact propane (R290) atmospheric water generator with series-coupled evaporator and condenser airflow and develops a component-level model of its partially wet fin-and-tube evaporator. Three extended tests were used to characterise operation. Model predictions were compared with cumulative collected water using a dry–wet coil formulation and refrigerant-side capacity matching. The simulated cumulative water production differed from the measured value by 6%. In the two 24 h tests, the unit produced 7.0 L outdoors and 4.5 L indoors using 7.2 kWh in each case, corresponding to specific energy consumptions of 1.03 and 1.60 kWh L−1, respectively. Water production was higher under the more humid inlet conditions. The model predicted higher water production at the lower nominal fan setting, reaching approximately 0.50–0.54 L h−1. Predicted compressor power also increased. The analysed outdoor profile showed its highest production during the nocturnal high-humidity period; this is a profile-specific result rather than an annual operating window. The model provides a basis for comparing operating trends under different inlet conditions

Artificial Intelligence for Sustainable CitiesVol. 1
University of Nottingham (GB), Necmettin Erbakan University (TR), Tarsus University (TR)
Affordable and clean energy, Climate action, Clean water and sanitation
Openalex Percentile: Top 35%
Solar-Powered Water Purification Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon
Experimental Investigation and Component-Level Modelling of a Self-Regulating Small-Scale Vapour-Compression Atmospheric Water Generator — Emmanuel Tapia-Brito, Mehmet Tahir ERDİNÇ, et al. · Artificial Intelligence for Sustainable Cities (2026) | TGRS Research Map | TGRS