Air pollution monitoring: Development of ammonia (NH₃) dynamic reference gas mixtures at nmol/mol levels for improving the lack of traceability of measurements

The measurement of ammonia (NH3) in ambient air is a sensitive and priority topic due to its harmful effects on human health and ecosystems. NH3 emissions have continuously increased over the last century in Europe, because of intensive livestock practices and enhanced use of nitrogen-based fertilizers. European air quality monitoring networks monitor atmospheric NH3 amount fractions. However, the lack of stable reference gas mixtures (RGMs) at atmospheric amount fractions to calibrate NH3 analyzers is a common issue of the networks, which results in data that are not accurate, traceable and, thus, geographically comparable. In order to cover this lack, LNE developed, in close collaboration with the company 2M PROCESS, a gas reference generator to generate dynamically NH3 RGMs in air. The method is based on gas permeation and further dynamic dilution to obtain an amount fraction range between 1 and 400 nmol/mol. The calibration of the elements of the generator against LNE primary standards ensures the traceability of the RGMs to the international system of units. Furthermore, the highly accurate flow and oven temperature measurements of the reference generator, together with the associated calibration procedure defined by LNE, guarantee relative expanded uncertainties of the calibration of the NH3 analyzer calibrations lower than 2 % (coverage factor = 2). This result is very satisfactory considering the low NH3 amount fraction levels (1 to 400 nmol/mol) and the phenomena of adsorption and desorption, especially in the presence of traces of water on the surfaces in contact. A bilateral comparison was organized between METAS and LNE, consisting on the calibration of a PICARRO G2103 gas analyzer by both national metrology institutes (NMI). The results highlighted the good agreement between the NH3 reference generators developed by the two institutes and allowed to validate both LNE’s reference generator and calibration procedure. The development of the NH3 reference generator has already raised great interest within the French air quality monitoring networks (AASQA). Since the end of 2020, LNE calibrated several NH3 analyzers of the networks. These requests shows the interest of the AASQA in the development of this new gas reference generator to guarantee the traceability of measurements carried out on the French territory.

Air Quality Measurements in Kitchener, Ontario, Canada Using Multisensor Mini Monitoring Stations

The Region of Waterloo is the third fastest growing region in Southern Ontario in Canada with a population of 619,000 as of 2019. However, only one air quality monitoring station, located in a city park in Kitchener, Ontario, is currently being used to assess the air quality of the region. In September 2020, a network of AQMesh Multisensor Mini Monitoring Stations (pods) were installed near elementary schools in Kitchener located near different types of emission source. Data analysis using a custom-made long-distance scaling software showed that the levels of nitrogen oxides (NO and NO2), ground level ozone (O3), and fine particulate matter (PM2.5) were traffic related. These pollutants were used to calculate the Air Quality Health Index-Plus (AQHI+) at each location, highlighting the inability of the provincial air quality monitoring station to detect hotspot areas in the city. The case study presented here quantified the impact of the 2021 summer wildfires on the local air quality at a high time resolution (15-min). The findings in this article show that these multisensor pods are a viable alternative to expensive research-grade equipment. The results highlight the need for networks of local scale air quality measurements, particularly in fast-growing cities in Canada.

Establishing A Sustainable Low-Cost Air Quality Monitoring Setup: A Survey of the State-of-the-Art

Low-cost sensors (LCS) are becoming popular for air quality monitoring (AQM). They promise high spatial and temporal resolutions at low-cost. In addition, citizen science applications such as personal exposure monitoring can be implemented effortlessly. However, the reliability of the data is questionable due to various error sources involved in the LCS measurement. Furthermore, sensor performance drift over time is another issue. Hence, the adoption of LCS by regulatory agencies is still evolving. Several studies have been conducted to improve the performance of low-cost sensors. This article summarizes the existing studies on the state-of-the-art of LCS for AQM. We conceptualize a step by step procedure to establish a sustainable AQM setup with LCS that can produce reliable data. The selection of sensors, calibration and evaluation, hardware setup, evaluation metrics and inferences, and end user-specific applications are various stages in the LCS-based AQM setup we propose. We present a critical analysis at every step of the AQM setup to obtain reliable data from the low-cost measurement. Finally, we conclude this study with future scope to improve the availability of air quality data.

Air Pollution Exposure and Risk of Spontaneous Pneumothorax in Children: A Longitudinal, Nationwide Study

Spontaneous pneumothorax (SP) involves the spontaneous appearance of air in the pleural space. Atmospheric pressure, temperature change, and seasonal factors may precipitate SP, but its association with air pollution remains unclear. Therefore, we conducted this nationwide, retrospective population-based study to evaluate the risk of SP in Taiwanese children exposed to air pollution. We collected data on SP incidence from the Longitudinal Health Insurance Database; the Taiwan Air Quality-Monitoring Database provided daily concentrations of nitric oxide (NO), nitrogen dioxide (NO2), and hydrocarbons in 2000–2012. SP risk was evaluated for four quartiles (Q1, Q2, Q3, Q4). The NO adjusted hazard ratios (aHRs) for Q2, Q3, and Q4 compared to Q1 were 1.11 (95% confidence interval (CI): 0.77–1.61), 1.24 (95% CI: 0.88–1.76), and 1.66 (95% CI: 1.17–2.34), respectively. The NO2 aHRs for Q2, Q3, and Q4 were 1.12 (95% CI: 0.77–1.64), 1.31 (95% CI: 0.0.90–1.90), and 1.51 (95% CI: 1.04–2.19), respectively. Hydrocarbons aHRs for Q2, Q3, and Q4 were 0.87 (95% CI: 0.64–1.18), 1.16 (95% CI: 0.90–1.49), and 1.40 (95% CI: 1.06–1.85), respectively. Increased exposure to NO, NO2, and hydrocarbons is associated with increased SP risk in Taiwanese children.