Abstract
Background
Air pollution is the largest environmental health risk in the United Kingdom, and an issue of concern amongst outdoor workers. Road transport is a major source producing the largest amount of nitrogen dioxide (NO2) and ozone (O3) (as a secondary pollutant). Hundreds of vehicles enter and exit the Tidworth Camp’s main gate daily, potentially producing these pollutants. However, the air pollution exposure experienced by personnel on guard duty is unknown. This study aimed to determine and compare background NO2 and O3 levels experienced by personnel on guard duty.
Methods
Cross-sectional data was collected using a static sampling technic on randomly selected days of the week. Data analysis was done using IBM-SPSS-26 and a p-value of <0.05 was considered statistically significant.
Results
The background concentration of NO2 and O3 pollutants were within recommended limits. There was no significant difference between mean morning and afternoon exposure levels for both pollutants. However, NO2 and O3 levels were significantly higher during weekdays compared to weekends (M = -0.022, SD = 0.007, t(6) = -8.672, p <0.0001 and M = -0.016, SD = 0.008, t(6) = -5.040, p = 0.002 respectively). Both pollutants showed no significant differences in exposure levels when only weekdays were compared. NO2 levels showed a weak positive correlation during weekdays (r = 0.04) and a strong positive correlation during weekends (r = 0.96). O3 levels had a positive correlation on both weekdays and weekends; however, levels on Monday showed a negative correlation (r = -0.55). Linear regression analysis showed that outside temperature was a significant predictor of O3 levels (p = 0.026).
Conclusion
Personnel on guard duty experienced higher pollution levels during weekdays compared to weekends; however, air pollution levels for both pollutants were within recommended limits. Further studies are recommended over hotter months using a personal sampling technic to measure personal air pollution exposure levels in order to minimise any health and safety risks.
Introduction
Air pollution is a common issue worldwide and is the largest environmental health risk in the United Kingdom (UK) [1]. In 2016, 91% of the global population lived in polluted areas, and out door air pollution caused 4.2 million premature deaths [2]. According to the European Environment Agency (EEA), Nitrogen dioxide (NO2) and Ozone (O3) were amongst the top three air pollutants producing the most serious health effects to humans and deaths in Europe [3]. People from lower socio-economic groups are the most exposed; while the elderly, children and those with underlying medical conditions are more susceptible [4]. NO2 and O3 are two main air pollutants of concern in the UK, with road transport being the main source, causing both environmental and health effects [4–7]. Health effects include diseases such as asthma, lung cancer, heart disease and stroke [2]. A study by the British Safety Council showed that 36,000 early deaths occur every year from outdoor air pollution in the UK, with 9,400 premature deaths in London alone [8].
The European Union (EU) Ambient Air Quality Directive (2008/50/EC) established legal limits for concentrations of major air pollutants (including NO2, and O3), and the UK adopted these limits into the Air Quality Standards Regulations 2010, which is monitored regularly. The Health and Safety Executive (HSE) published a document (EH40/2005 Workplace exposure limits—WELs) which contains British occupational exposure limits, with the aim of protecting health by ensuring that people are not exposed to harmful quantities of hazardous substances in the workplace [9]. The HSE’s EH40 workplace exposure limit for NO2 (8-hr TWA) is 0.96 mg/m3 and for O3 (15-min TWA) is 0.4mg/m3 [9]. However, there is a growing concern about health effects from outdoor air pollution in the UK, with recommended limits being exceeded. For example, in 2019, 76.7% (33 out of 43) monitoring zones exceeded the limit for annual mean NO2 air pollution in the UK [7]. In a report published by The Royal College of Physicians, people who work near busy roads (such as traffic police, street cleaners, road maintenance workers, and security guards) were identified as one of the most vulnerable groups [10]; and are at highest risk of exposure to unhealthy levels of air pollution. Several studies have shown an increase in different health effects as a result of NO2 and O3 pollution [11–16]. Occupational exposure to outdoor air pollution have been reported amongst commercial drivers of buses, cars, and motorcycles [17].
Tidworth camp is part of the Tidworth, Netheravon and Bulford garrison (TidNBul) and one of the largest military garrison in the UK, located in the Southwest Region of England. It is home to more than 15000 military and civilian personnel. Hundreds of vehicles (including small cars, buses, and armoured trucks) enter and exit the Tidworth Camp’s main gate daily. Personnel on guard duty carry out security checks on all these vehicles as they drive into the Camp. These vehicles could be seen queuing-up at the main gate during busier hours (mornings– 7:00 to 9:00 am, launch time– 11:00 am to 13:00 pm and afternoons– 15:00 to 17:00 pm); thereby increasing the risk of air pollution exposure to personnel on guard duty. No studies have been conducted on military bases in the UK to determine air pollution exposure experienced by personnel on guard duty despite the variety of military vehicles entering and exiting military Camps. This study aimed to determine background workplace contaminant concentrations of NO2 and O3 exposure, and to compare the daily exposure levels experienced by personnel on guard duty at the Tidworth Camp’s main gate.
Methods
Tidworth Camp is part of the Tidworth, Netheravon and Bulford garrison located in the Southwest Region of England and hosts thousands of military and civilian personnel. The number of personnel is expected to increase due to an influx of troops withdrawn from Germany [18]. The study was conducted in February 2021 using a cross-sectional design. NO2 and O3 levels were collected using the AQY1-Micro Air Quality Monitor [19]. Data collection was done on randomly selected days–three days were selected using a computer-generated simple random selection tool (Monday and Tuesday to represent weekdays, and Sunday to represent weekends).
Data validity was achieved through equipment calibration and setup following the manufacturer’s instructions [20]. Two-hourly NO2 and O3 data (from 7:00am to 19:00pm) were extracted from the equipment and double checked for any errors before analysis. The two-hourly data was selected to mimic the guard duty shift pattern. The extracted data was then entered into IBM SPSS version 26 for further analysis. Data analysis involved calculating means and standard deviation to provide a summary of the data set; t-test to compare exposure levels; correlation analyses to check for any existing relationships and a regression analyses to identify which variables had an impact on the air pollution level.
Ethics
This study was guided by the Helsinki Declaration as revised in 2013. The study did not involve any human participants; however, ethical approval was provided by Leeds Beckett University ethics committee. A letter of permission (Gate keeper letter) was also provided by the Tidworth Camp for the study. As the study was conducted during the COVID-19 period, all UK government guidance on COVID-19 social distancing were observed.
Results
Table 1 shows the descriptive statistics for the study. The daily maximum and minimum temperatures were 10.5°C and -1.41°C and an average maximum and minimum wind speed of 3.1m/s and 0.9m/s, respectively. NO2 and O3 exposure levels varied from day to day partly due to variability in weather conditions (mostly windspeed) and traffic flow. Standard deviations (SD) showed that the two-hourly exposure levels for each day did not deviate much from the daily mean. The mean exposure level for NO2 and O3 was highest on Monday and Tuesday respectively; while Sunday had the lowest mean exposure level for both pollutants.
Table 1. Daily NO2 and O3 exposure levels.
| Time (2 hrly) | Sunday | Monday | Tuesday | ||||||
|---|---|---|---|---|---|---|---|---|---|
| NO2 (mg/m3) | O3 (mg/m3) | Temp (°C) | NO2 (mg/m3) | O3 (mg/m3) | Temp (°C) | NO2 (mg/m3) | O3 (mg/m3) | Temp (°C) | |
| 07:00 | 0.0400 | 0.0306 | 0.87 | 0.0599 | 0.0565 | -1.41 | 0.0601 | 0.0526 | -1.15 |
| 09:00 | 0.0408 | 0.0341 | 2.59 | 0.0700 | 0.0602 | -0.46 | 0.0683 | 0.0501 | -1 |
| 11:00 | 0.0412 | 0.0456 | 10.5 | 0.0649 | 0.0609 | 0.01 | 0.0665 | 0.0559 | -0.54 |
| 13:00 | 0.0441 | 0.0466 | 7.8 | 0.0693 | 0.0558 | -0.08 | 0.0718 | 0.0554 | 0.2 |
| 15:00 | 0.0442 | 0.0528 | 7.18 | 0.0675 | 0.0555 | -0.81 | 0.0645 | 0.0692 | 0.89 |
| 17:00 | 0.0478 | 0.0408 | 4.45 | 0.0710 | 0.0564 | -0.85 | 0.0700 | 0.0628 | -0.8 |
| 19:00 | 0.051 | 0.0378 | 2.99 | 0.0591 | 0.0554 | -1.1 | 0.06 | 0.0562 | -0.95 |
| Mean | 0.0442 | 0.0412 | 5.20 | 0.0660 | 0.0572 | -0.67 | 0.0659 | 0.0575 | -0.48 |
| SD | 0.004 | 0.0077 | 3.42 | 0.0048 | 0.0023 | 0.52 | 0.0046 | 0.0065 | 0.75 |
| WS | 0.9m/s | 2.8m/s | 3.1m/s | ||||||
Note: SD = standard deviation; Temp = temperature; °C = degree Celsius; WS = average daily wind speed; mg/m3 = milligrams per metres cube; hrly = hourly.
Paired t-test analysis showed that there were no significant differences between the average morning (am) and afternoon (pm) exposure levels for both pollutants. However, exposure levels were significantly higher during weekdays (Monday and Tuesday) compared to weekends (Sunday) for both pollutants. No significant difference was found in exposure levels for both pollutants when only weekdays (Monday and Tuesday) were compared. See Table 2 and Fig 1 below.
Table 2. Paired sample t-test analysis.
| Paired Samples | Mean | Std. Deviation | Std. Error Mean | 95% Confidence Interval | t | df | p value | |
|---|---|---|---|---|---|---|---|---|
| Lower | Upper | |||||||
| NO2 Sun (am)—NO2 Sun (pm) | -.0047000 | .0016823 | .0009713 | -.0088790 | .0000210 | -4.839 | 2 | .060 |
| NO2 Mon (am)—NO2 Mon (pm) | -.0043333 | .0061436 | .0035470 | -.0195948 | .0109281 | -1.222 | 2 | .346 |
| NO2 Tue (am)—NO2 Tue (pm) | -.0038000 | .0077544 | .0044770 | -.0230629 | .0154629 | -.849 | 2 | .485 |
| O3 Sun (am)—O3 Sun (pm) | -.0099667 | .0128594 | .0074244 | -.0419111 | .0219778 | -1.342 | 2 | .312 |
| O3 Mon (am)—O3 Mon (pm) | .0033000 | .0022539 | .0013013 | -.0022990 | .0088990 | 2.536 | 2 | .127 |
| O3 Tue (am)—O3 Tue (pm) | -.0096000 | .0084788 | .0048952 | -.0306625 | .0114625 | -1.961 | 2 | .189 |
| NO2 Sun—NO2 Mon | -.0218000 | .0066513 | .0025140 | -.0279514 | -.0156486 | -8.672 | 6 | .00013* |
| NO2 Sun—NO2 Tue | -.0217286 | .0064376 | .0024332 | -.0276823 | -.0157748 | -8.930 | 6 | .00011* |
| NO2 Mon—NO2 Tue | .0000714 | .0019371 | .0007322 | -.0017201 | .0018630 | .098 | 6 | .925 |
| O3 Sun—O3 Mon | -.0160571 | .0084295 | .0031860 | -.0238531 | -.0082612 | -5.040 | 6 | .002* |
| O3 Sun—O3 Tue | -.0162714 | .0051919 | .0019623 | -.0210731 | -.0114697 | -8.292 | 6 | .00017* |
| O3 Mon—O3 Tue | -.0002143 | .0078671 | .0029735 | -.0074901 | .0070616 | -.072 | 6 | .945 |
| NO2 Sun—O3 Sun | .0029714 | .0081061 | .0030638 | -.0045255 | .0104683 | .970 | 6 | .370 |
| NO2 Mon—O3 Mon | .0087143 | .0049181 | .0018589 | .0041658 | .0132628 | 4.688 | 6 | .003* |
| NO2 Tue—O3 Tue | .0084286 | .0077448 | .0029273 | .0012658 | .0155913 | 2.879 | 6 | .028* |
Note: am–morning; pm–afternoon; Sun–Sunday; Mon–Monday; Tue–Tuesday; t–t-test; df–degree of freedom
*significant p-value of <0.05.
Fig 1. Average NO2 and O3 exposure levels.
NO2 exposure levels had a strong positive correlation during weekends (Sunday–r = 0.96), and a weak positive correlation during weekdays (Monday–r = 0.04 and Tuesday–r = 0.02). O3 exposure levels had a strong positive correlation during weekends (Sunday–r = 0.42) and weekdays (Tuesday–r = 0.59); however, O3 levels had a strong negative correlation on Monday (r = -0.55). See Fig 2.
Fig 2. NO2 and O3 levels showing weekly correlation.
A paired sample correlation analysis was done to determine the relation between NO2 level and outside temperature (To) (independent variables–IV) and O3 level (dependant variable–DV). The results showed that both NO2 and O3 levels had weak positive correlations (r = 0.16, r = 0.20, and r = 0.06), while To and O3 level had a stronger positive correlation (r = 0.84, r = 0.55, and r = 0.71) on Sunday, Monday, and Tuesday, respectively. A linear regression analysis was performed to predict O3 level (DV) from NO2 level (IV1) and To (IV2). A significant regression equation was observed {F(2, 4) = 6.22, p = 0.026), with an R2 of 0.757. The predicted O3 level was 0.011 + 0.002 (To) (To measured in °C). O3 level increased 0.002mg/m-3 for each °C of To. Outside temperature was a significant predictor of O3 level (p = 0.026), while NO2 level was not (p = 0.397) (see Table 3).
Table 3. Effect of NO2 level and outside temperature on O3 levels.
| Independent variable | Coefficient |
|---|---|
| Outside temperature | .002 (.001)* |
| NO2 level | .450 (.474) |
| Constant | .011 |
| R | .870 |
| R Square | .757 |
| Adjusted R Square | .635 |
| F-ratio | 6.22* |
| n | 7 |
Note
* = p < 0.05; coefficients are unstandardised with standard errors in brackets.
Discussion
The aim of this study was to determine background workplace contaminant concentrations of NO2 and O3, and to compare the daily exposure levels experienced by personnel on guard duty at the Tidworth camp’s main gate. Exposure levels were first compared to check for differences between morning (07:00–11:00 am) and afternoon exposure (13:00–19:00 pm). The mean afternoon exposure for both pollutants was marginally higher than the mean morning exposure levels; however, the difference was not significant. Similar results have been reported in other studies where afternoon exposure levels were higher than morning exposure levels, but with no statistically significant differences [7,21]. However, some studies have also found contradictory results, with significantly higher pollution exposure levels during morning periods [22]. Higher exposures during working hours increases the risk to health of personnel.
When the mean daily NO2 and O3 exposure levels for weekdays and weekends were compared, the results showed significant higher exposure levels for both pollutants during weekdays. The differences in exposure levels during weekdays and weekends were consistent with findings from an air quality report by Defra, showing a peak in NO2 pollution levels during weekdays, with concentrations being 20% greater compared to weekends [23]. As was the case in this study, Defra attributed this difference to high traffic seen during weekdays compared to weekends. This implies that personnel on guard duty may be exposed to higher pollution levels and are at higher risk of developing health effect during weekdays compared to weekends. No significant difference in mean exposure levels were observed for both pollutants when only weekdays were compared.
Correlation analyses showed a direct proportional relationship between NO2 exposure levels and daily hours on weekends; that is NO2 levels had a strong positive correlation during weekends. However, during weekdays, NO2 exposure levels showed a weak positive correlation. The weak positive correlation could be seen to exhibit spikes in NO2 levels at specific times of the day (usually busier hours). These spikes were observed at 7:00–9:00, 11:00–13:00 and 15:00–17:00; and these hours represented periods of high traffic at the Camp’s main gate as personnel went to work (7:00–9:00); went for lunch breaks (11:00–13:00); and went home after work (15:00–17:00). These findings are consistent with those of a report by Defra showing high air pollution levels during morning and evening rush hours, as a result of traffic congestion [24].
O3 showed a positive correlation on both weekdays and weekends, but exposure levels on one of the weekdays (Monday) showed a negative correlation which could be attributed to the very low temperatures observed on that day (see Table 1). As seen from this findings and in line with a report by Defra [23], the amount of O3 produced is dependent on the amount of NO2 and temperature available. Our findings were consistent with those of a similar study that showed a positive correlation of daily averaged O3 with air temperature [25].
Linear regression analysis showed a strong relationship between the To and O3 level. From the adjusted R square value obtained, 63.5% of the variance in O3 level could be attributed to To. The linear regression analysis model showed that To was a significant predictor of O3 level while NO2 level was not a significant predictor of O3 level. This implies that personnel on guard duty during hotter days are potentially exposed to high amounts of O3 and are at high risk of its health effects. Other studies have shown similar findings [25]; however our findings contradicted those of a study showing NO2 as a predictor of O3 level [22].
Overall, the exposure levels of both pollutants were low and within recommended levels [9]. However, because this study used a static sampling technic and not a personal sampling technic to collect data; therefore, results could not be directly compared to the workplace exposure limits provided by the Health and Safety Executive (HSE). Nonetheless, the exposure levels obtained from this study could be used as a baseline background workplace exposure level because the HSE has recommended static sampling as a suitable technics for determining background workplace contaminant concentrations [26].
This study had the following limitations: personal sampling technic could not be used due to COVID-19 social distancing measures; the study was conducted over COVID-19 period when a small amount of traffic entered and exited the Camp (as many personnel were working from home) and did not reflect the actual traffic situation on a normal day; the study was conducted over the winter period (February) when weather conditions such as temperature, rainfall and wind speed is known to affect pollution levels [21].
Conclusion
This study analysed background workplace contaminant concentrations of NO2 and O3 exposure levels and compared the daily exposure levels experienced by personnel on guard duty at the Tidworth Camps’ main gate. The results showed that the mean NO2 and O3 exposure levels for all days measured were within recommended levels. When the NO2 and O3 exposure levels were compared, the results showed no significant difference between mean morning and mean afternoon exposure levels for both pollutants. However, the mean exposure levels for both pollutants were significantly higher during weekdays compared to weekends; implying that personnel on guard duty were exposed to higher levels of air pollution during weekdays. During weekdays, NO2 exposure levels increased with high traffic at busier hours. Outside temperature was the only significant predictor of O3 levels. While this study provided background air pollution levels for personnel on guard duty at the Tidworth Camp’s main gate and daily trends in exposure levels which were unknown, it is recommended that further studies be conducted using personal sampling technic, over hotter months and on a larger scale and the results compared with those of this study.
Acknowledgments
We would like to acknowledge the indispensable effort and endless support provided by the staff at DEOH and colleagues in RC–EH Tid Det throughout this work.
Data Availability
All relevant data are within the manuscript and its Supporting Information file.
Funding Statement
The author(s) received no specific funding for this work.
References
- 1.Defra. Clean Air Strategy 2018. 2018;104.
- 2.WHO. Ambient (outdoor) air pollution [Internet]. Ambient (outdoor) air pollution. 2018 [cited 2020 Dec 4]. Available from: https://www.who.int/news-room/fact-sheets/detail/ambient-(outdoor)-air-quality-and-health.
- 3.EEA. Air quality in Europe—2020 report [Internet]. 2020.
- 4.EEA. Emissions of the main air pollutants in Europe—European Environment Agency [Internet]. 2019 [cited 2020 Dec 7]. Available from: https://www.eea.europa.eu/data-and-maps/indicators/main-anthropogenic-air-pollutant-emissions/assessment-6.
- 5.Smith H, Jones L, Thistlethwaite G, Richardson J, Raoult J, Richmond B, et al. Air Pollutant Inventories for England, Scotland, Wales, and Northern Ireland: 1990–2018. 2020Oct;127. [Google Scholar]
- 6.Barnes JH, Chatterton TJ, Longhurst JWS. Emissions vs exposure: Increasing injustice from road traffic-related air pollution in the United Kingdom. Transp Res Part Transp Environ [Internet]. 2019. Jun 17 [cited 2020 Dec 4];73. Available from: https://uwe-repository.worktribe.com/output/1491851/emissions-vs-exposure-increasing-injustice-from-road-traffic-related-air-pollution-in-the-united-kingdom. [Google Scholar]
- 7.Defra. Air Pollution in the UK 2019 [Internet]. 2020. Available from: file:///D:/Air%20pollution%20research/EHT%20Research%20-%20Air%20pollution/literature/vital/air_pollution_uk_2019_issue_1.pdf.
- 8.BSC. It’s time to recognise air pollution as an occupational health hazard | British Safety Council [Internet]. 2019 [cited 2020 Dec 7]. Available from: https://www.britsafe.org/about-us/press-releases/2019/it-s-time-to-recognise-air-pollution-as-an-occupational-health-hazard/.
- 9.HSE. WORKPLACE EXPOSURE LIMITS: containing the list of workplace exposure limits for use with the… control of substances hazardous to health regulati. Place of publication not identified: HSE Books; 2020.
- 10.Every breath we take: the lifelong impact of air pollution [Internet]. RCP. 2016 [cited 2020 Dec 7]. Available from: https://www.rcplondon.ac.uk/projects/outputs/every-breath-we-take-lifelong-impact-air-pollution.
- 11.Bhaskaran K, Hajat S, Armstrong B, Haines A, Herrett E, Wilkinson P, et al. The effects of hourly differences in air pollution on the risk of myocardial infarction: case crossover analysis of the MINAP database. BMJ. 2011Sep20;343:d5531. doi: 10.1136/bmj.d5531 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Kulkarni N, Pierse N, Rushton L, Grigg J. Carbon in Airway Macrophages and Lung Function in Children [Internet]. 10.1056/NEJMoa052972. Massachusetts Medical Society; 2009. [cited 2020 Dec 10]. Available from: https://www.nejm.org/doi/full/10.1056/nejmoa052972. [DOI] [Google Scholar]
- 13.Lange P, Celli B, Agustí A, Boje Jensen G, Divo M, Faner R, et al. Lung-Function Trajectories Leading to Chronic Obstructive Pulmonary Disease. N Engl J Med. 2015Jul9;373(2):111–22. doi: 10.1056/NEJMoa1411532 [DOI] [PubMed] [Google Scholar]
- 14.Morales E, Garcia-Esteban R, Asensio de la Cruz O, Basterrechea M, Lertxundi A, Martinez López de Dicastillo MD, et al. Intrauterine and early postnatal exposure to outdoor air pollution and lung function at preschool age. Thorax. 2015Jan;70(1):64–73. doi: 10.1136/thoraxjnl-2014-205413 [DOI] [PubMed] [Google Scholar]
- 15.Hwang B-F, Chen Y-H, Lin Y-T, Wu X-T, Leo Lee Y. Relationship between exposure to fine particulates and ozone and reduced lung function in children. Environ Res. 2015Feb1;137:382–90. doi: 10.1016/j.envres.2015.01.009 [DOI] [PubMed] [Google Scholar]
- 16.Tager IB, Balmes J, Lurmann F, Ngo L, Alcorn S, Künzli N. Chronic Exposure to Ambient Ozone and Lung Function in Young Adults. Epidemiology. 2005;16(6):751–9. doi: 10.1097/01.ede.0000183166.68809.b0 [DOI] [PubMed] [Google Scholar]
- 17.Lawin H, Ayi Fanou L, Hinson AV, Stolbrink M, Houngbegnon P, Kedote NM, et al. Health Risks Associated with Occupational Exposure to Ambient Air Pollution in Commercial Drivers: A Systematic Review. Int J Environ Res Public Health. 2018Sep;15(9):2039. doi: 10.3390/ijerph15092039 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Britain’s new super-garrisons [Internet]. openDemocracy. [cited 2020 Dec 4]. Available from: https://www.opendemocracy.net/en/opendemocracyuk/britains-new-super-garrisons/.
- 19.AQY-MICRO AIR QUALITY MONITOR [Internet]. Campbell Associates | Dunmow,Essex, UK. [cited 2021 Apr 17]. Available from: https://www.campbell-associates.co.uk/product/aqy-micro-air-quality-monitor.
- 20.f49e71_145b6388df1e44509957839282e713ca.pdf [Internet]. [cited 2021 Apr 17]. Available from: https://86a1cc79-ba21-4dcb-9a72-05618fbb1c59.filesusr.com/ugd/f49e71_145b6388df1e44509957839282e713ca.pdf.
- 21.Dirks KN, Wang JYT, Khan A, Rushton C. Air Pollution Exposure in Relation to the Commute to School: A Bradford UK Case Study. Int J Environ Res Public Health. 2016Nov;13(11):1064. doi: 10.3390/ijerph13111064 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Pénard‐Morand C, Charpin D, Raherison C, Kopferschmitt C, Caillaud D, Lavaud F, et al. Long-term exposure to background air pollution related to respiratory and allergic health in schoolchildren. Clin Exp Allergy. 2005;35(10):1279–87. doi: 10.1111/j.1365-2222.2005.02336.x [DOI] [PubMed] [Google Scholar]
- 23.Defra. Air quality statistics in the UK 1987 to 2018- Defra, UK [Internet]. Department for Environment, Food and Rural Affairs (Defra), Nobel House, 17 Smith Square, London SW1P 3JR helpline@defra.gsi.gov.uk; 2019 [cited 2021 Feb 19]. Available from: https://uk-air.defra.gov.uk/news?view=252.
- 24.Defra. Air Quality in the UK—Air pollution episodes [Internet]. 2021 [cited 2021 Feb 19]. Available from: https://uk-air.defra.gov.uk/assets/documents/reports/empire/brochure/day.html.
- 25.Zoran MA, Savastru RS, Savastru DM, Tautan MN. Assessing the relationship between ground levels of ozone (O3) and nitrogen dioxide (NO2) with coronavirus (COVID-19) in Milan, Italy. Sci Total Environ. 2020Oct20;740:140005. doi: 10.1016/j.scitotenv.2020.140005 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.HSE. Monitoring strategies for toxic substances. Sudbury: HSE; 2006.
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
All relevant data are within the manuscript and its Supporting Information file.