NOx is a pervasive pollutant in urban environments. This review assesses the current state of the art of photocatalytic oxidation materials, designed for the abatement of nitrogen oxides (NOx) in the urban environment, and typically, but not exclusively based on titanium dioxide (TiO2). Field trials with existing commercial materials, such as paints, asphalt and concrete, in a range of environments including street canyons, car parks, tunnels, highways and open streets, are considered in-depth. Lab studies containing the most recent developments in the photocatalytic materials are also summarised, as well as studies investigating the impact of physical parameters on their efficiency. It is concluded that this technology may be useful as a part of the measures used to lower urban air pollution levels, yielding ∼2% NOx removal in the immediate area around the surface, for optimised TiO2, in some cases, but is not capable of the reported high NOx removal efficiencies >20% in outdoor urban environments, and can in some cases lower air quality by releasing hazardous by-products. However, research into new material is ongoing. The reason for the mixed results in the studies reviewed, and massive range of removal efficiencies reported (from negligible and up to >80%) is mainly the large range of testing practices used. Before deployment in individual environments site-specific testing should be performed, and new standards for lab and field testing should be developed. The longevity of the materials and their potential for producing hazardous by-products should also be considered.
Abstract. Air pollution exhibits hyper-local variation, especially near emissions sources. In addition to people's time-activity patterns, this variation is the most critical element determining exposure. Pollution exposure is time-activity- and path-dependent, with specific behaviours such as mode of commuting and time spent near a roadway or in a park playing a decisive role. Compared to conventional air pollution monitoring stations, nodes containing low-cost air pollution sensors can be deployed with very high density. In this study, a network of 18 nodes using low-cost air pollution sensors was deployed in Newcastle-under-Lyme, Staffordshire, UK, in June 2020. Each node measured a range of species including nitrogen dioxide (NO2), ozone (O3), and particulate matter (PM2.5 and PM10); this study focuses on NO2 and PM2.5 over a 1-year period from 1 August 2020 to 1 October 2021. A simple and effective temperature, scale, and offset correction was able to overcome data quality issues associated with temperature bias in the NO2 readings. In its recent update, the World Health Organization (WHO) dramatically reduced annual exposure limit values from 40 to 10 µg m−3 for NO2 and from 10 to 5 µg m−3 for PM2.5. We found that the average annual mean NO2 concentration for the network was 17.5 µg m−3 and 8.1 µg m−3 for PM2.5. While in exceedance of the WHO guideline levels, these average concentrations do not exceed legally binding UK/EU standards. The network average NO2 concentration was 12.5 µg m−3 higher than values reported by a nearby regional air quality monitoring station, showing the critical importance of monitoring close to sources before pollution is diluted. We demonstrate how data from a low-cost air pollution sensor network can reveal insights into patterns of air pollution and help determine whether sources are local or non-local. With spectral analysis, we investigate the variation of the pollution levels and identify typical periodicities. Both NO2 and PM2.5 have contributions from high-frequency sources; however, the low-frequency sources are significantly different. Using spectral analysis, we determine that at least 54.3±4.3 % of NO2 is from local sources, whereas, in contrast, only 37.9±3.5 % of PM2.5 is local.
In this pilot study, low-cost air pollution sensor nodes were fitted in waste removal trucks, hospital vans and taxis to record drivers’ exposure to air pollution in Central London. Particulate matter (PM 2.5 and PM 10 ), CO 2 , NO 2 , temperature and humidity were recorded in real-time with nodes containing low-cost sensors, an electrochemical gas sensor for NO 2 , an optical particle counter for PM 2.5 and PM 10 and a non-dispersive infrared (NDIR) sensor for CO 2 , temperature and relative humidity. An intervention using a pollution filter to trap PM and NO 2 was also evaluated. The measurements were compared with urban background and roadside monitoring stations at Honor Oak Park and Marylebone Road, respectively. The vehicle records show PM and NO 2 concentrations similar to Marylebone Road and a higher NO 2 -to-PM ratio than at Honor Oak Park. Drivers are exposed to elevated pollution levels relative to Honor Oak Park: 1.72 μ g m − 3 , 1.92 μ g m − 3 and 58.38 ppb for PM 2.5 , PM 10 , and NO 2 , respectively. The CO 2 levels ranged from 410 to over 4000 ppm. There is a significant difference in average concentrations of PM 2.5 and PM 10 between the vehicle types and a non-significant difference in the average concentrations measured with and without the pollution filter within the sectors. In conclusion, drivers face elevated air pollution exposure as part of their jobs.
Accurate calibration of low-cost gas sensors is, at present, a time consuming and difficult process. Laboratory calibration and field calibration methods are currently used, but laboratory calibration is generally discounted due to poor transferability, and field methods requiring several weeks are standard. The Enhanced Ambient Sensing Environment (EASE) method described in this article, is a hybrid of the two, combining the advantages of a laboratory calibration with the increased accuracy of a field calibration. It involves calibrating sensors inside a duct, drawing in ambient air with similar properties to the site where the sensors will operate, but with the added feature of being able to artificially increases or decrease pollutant levels, thus condensing the calibration period required. Calibration of both metal-oxide (MOx) and electrochemical (EC) gas sensors for the measurement of NO2 and O3 (0–120 ppb) were conducted in EASE, laboratory and field environments, and validated in field environments. The EC sensors performed marginally better than MOx sensors for NO2 measurement and sensor performance was similar for O3 measurement, but the EC sensor nodes had less node inter-node variability and were more robust. For both gasses and sensor types the EASE calibration outperformed the laboratory calibration, and performed similarly to or better than the field calibration, whilst requiring a fraction of the time.
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