journal article·2025-12Open access

Degradation of concrete panels in air scrubbers

Marie Giroudon, Marlène Fourré, Isabelle Frigout, Alexandra Bertron

Abstract

Air scrubbers installed in livestock buildings play a critical role in mitigating ammonia and particulate emissions, thereby improving air quality and helping to meet environmental regulations. However, concrete structures within these systems exhibit premature degradation, posing financial risks to farmers. The mechanisms behind this degradation, as well as the composition of the runoff water, remain poorly understood. This study aims to analyse runoff water compositions over 12 months and to evaluate the degradation mechanisms of two types of altered concrete: XA2 (exposed for 12 months) and XF1 (exposed for 10 years), through microstructural, chemical, and mineralogical analyses. Techniques used include inductively coupled plasma/optical emission spectrometry (ICP/OES), high-performance ion chromatography (HPIC), scanning electron microscopy (SEM), and X-ray diffraction (XRD). Results showed that the runoff water contained ammonium in large amount (up to 995 mg/L), sulphates (up to 338 mg/L), and magnesium (up to 54.5 mg/L), all of which are aggressive to concrete. These components led to leaching and carbonation of the panels, with the XF1 concrete also suffering from sulphate attack (expansive secondary ettringite) and magnesium attack. The XF1 and XA2 type concretes exhibited degraded depths of 15 mm and 5 mm, respectively, after 10 years and 12 months of exposure. The findings indicate that air scrubbers create highly aggressive environments for concrete, highlighting the need for more suitable materials, such as calcium aluminate cement coatings, to improve durability and prevent structural failure.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Recycled Aggregate Concrete Performance · Odor and Emission Control Technologies · Recycling and Waste Management Techniques

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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