Advancing Methodologies for Investigating PM2.5 Removal Using Green Wall System.

Combustion processes are the primary source of fine particulate matter in indoor air. Since the 1970s, plants have been extensively studied for their potential to reduce indoor air pollution. Leaves can retain particles on their surfaces, influenced by factors such as wax content and the presence of hairs. This study introduces an innovative experimental approach using metal oxide particles in an office-like environment to evaluate the depolluting effect of plant walls. Two plant walls were installed in a controlled room, housing three plant species: Aglaonema commutatum 'Silver Bay', Dracaena fragrans, and Epipremnum aureum. Metal oxide particles were introduced via a compressed air blower positioned between the two walls. The concentration of these particles was monitored using PM2.5 sensors, and the deposition of iron (Fe) on the leaves was quantified through Inductively Coupled Plasma Mass Spectrometry (ICP-MS). This novel methodology effectively demonstrated the utility of both real-time sensors and ICP-MS in quantifying airborne particle concentrations and leaf deposition, respectively. The results revealed that Dracaena fragrans had a 44% higher Fe particle retention rate compared to the control (wallpaper). However, further validation through methodological replication is necessary to confirm the reproducibility of these findings.

How well does your e-nose detect cancer? Application of artificial breath analysis for performance assessment.

Comparing electronic nose (e-nose) performance is a challenging task because of a lack of standardised method. This paper proposes a method for defining and quantifying an indicator of the effectiveness of multi-sensor systems in detecting cancers by artificial breath analysis. To build this method, an evaluation of the performances of an array of metal oxide sensors built for use as a lung cancer screening tool was conducted. Breath from 20 healthy volunteers has been sampled in fluorinated ethylene propylene sampling bags. These healthy samples were analysed with and without the addition of nine volatile organic compound (VOC) cancer biomarkers, chosen from literature. The concentration of the VOC added was done in increasing amounts. The more VOC were added, the better the discrimination between 'healthy' samples (breath without additives) and 'cancer' samples (breath with additives) was. By determining at which level of concentration the e-nose fails to reliably discriminate between the two groups, we estimate its ability to well predict the presence of the disease or not in a realistic situation. In this work, a home-made e-nose is put to the test. The results underline that the biomarkers need to be about 5.3 times higher in concentration than in real breath for the home-made nose to tell the difference between groups with a sufficient confidence.

Upscaling of an electronic nose for completely stirred tank reactor stability monitoring from pilot-scale to real-scale agricultural co-digestion biogas plant.

This study investigated the use of an electronic nose for on-line anaerobic reactor state monitoring at the pilot-scale level and then upscaling to the full-scale level. E-nose indicator was compared to classical state indicators such as pH, alkalinity, volatile fatty acids concentration and to other gas phase compounds. Multivariate statistical process control method, based on principal component analysis and the Hotelling's T(2) statistics was used to derive an indicator representative of the reactor state. At the pilot-scale level, the e-nose indicator was relevant and could distinguish 3 process states: steady-state, transient and collapsing process. At the full-scale level, the e-nose indicator could provide the warning of the major disturbance whereas two slight disturbances were not detected and it gave one major false alarm. This work showed that gas phase relation with anaerobic process should be deeper investigated, as an e-nose could indicate the reactor state, focusing on the gas phase.

Chemical Mass Balance model applied to an olfactory annoyance problematic.

The source-receptor model Chemical Mass Balance (CMB) generally used for air pollution studies is applied for the first time to solve odor signature issues. The olfactory annoyance perceived at a receptor site of an industrial area is often the result of a combination of different smells, emitted by several industrial sources. To identify the main responsible for the inconvenience, tools able to determine the contribution of each source directly where the annoyance is perceived are widely developed and deployed. In this work, the contributions of volatile organic compound sources, coming from a waste treatment plant containing three potential sources of olfactory annoyance (waste storage, production of biogas, and compost piles of green wastes) and perceived at a village located downwind, are studied by chemical analyses. The CMB methodology is applied, and the results are finally compared to olfactometric methods, in order to validate whether it is appropriate to use this model for olfactory problems or not.

Evaluation of an electronic nose for the early detection of organic overload of anaerobic digesters.

This study aimed at analysing the utilization of an electronic nose (e-nose) to serve as a specific monitoring tool for anaerobic digestion process, especially for detecting organic overload. An array of non specific metal oxide semiconductor gas sensors were used to detect process faults due to organic overload events in twelve 1.8-L anaerobic semi-continuous reactors. Three different load strategies were followed: (1) a cautious organic load (1.3 gVS L(-1) day(-1)); (2) an increasing load strategy (1.3-5.3 gVS L(-1) day(-1)) and (3) a cautious organic load with load pulses of up to 12 gVS L(-1) day(-1). A first monitoring campaign was conducted with three different substrates: sucrose, maize oil and a mix of sucrose/oil during 60 days. The second campaign was run with dry sugar beet pulp for 45 days. Hotelling's T(2) value and upper control limit to a reference set of digesters fed with a cautious OLR (1.3 gVS L(-1) day(-1)) was used as indirect state variable of the reactors. Overload situations were identified by the e-nose apparatus with Hotelling's T(2) values at least four times higher in magnitude than the upper control limit of 23.7. These results confirmed that the e-nose technology appeared promising for online detection of process imbalances in the domain of anaerobic digestion.

The use of sensor arrays for environmental monitoring: interests and limitations.

Continuous, in situ monitoring of air, water and land quality is fundamental to most environmental applications. Low cost and non-invasive chemical sensor arrays provide a suitable technique for in situ monitoring. Their ability and performance under realistic conditions is discussed in this paper. Published studies report promising results despite a number of limitations that are associated with both the technology itself and its application in ever changing ambient conditions. Early investigations include the analysis of single substances as well as odour and wastewater organic load monitoring. Reported applications typically highlight the sensitivity of the currently available sensors to changes in temperature, humidity and flow rate. Two types of approaches are recommended to deal with these effects: either working under fixed experimental conditions or measuring the external parameters to numerically compensate for their change. The main challenge associated with the use of non-specific sensor arrays lies in establishing a relationship between the measured multivariate signals and the standards metrics that are traditionally used for quality assessment of gas mixtures. For instance, odour monitoring requires calibration against olfactometric measurements while investigations of wastewater samples still need to be correlated with organic pollution parameters such as BOD, COD or TOC. On the other hand, results obtained in the field have demonstrated how sensor arrays can be readily used as simple alarm devices or as early warning systems based on a general air/water quality index.