Early evidence that governmental responses to COVID-19 reduce urban air pollution

There is no doubt that the global spread of COVID-19 represents the defining crisis of the last decade. Governments around the world have scrambled to try to reduce person-to-person spread and deal with pressures on public health infrastructure. Regions with community spread have almost universally faced restrictions on travel, business and social activities. These restrictions are designed to reduce the exponential spread of COVID-19 (that is, to flatten the curve), these restrictions will also have a large number of other economic, social and environmental repercussions. Here, I ask a simple question: Has reductions in economic activity and movement caused by governmental responses to COVID-19 improved air quality in cities? I compare February 2019 and 2020 air quality measures and show that six cities that were impacted early by government restrictions in response to COVID-19 show consistent declines in five of six major air pollutants compared to cities that were impacted later (the text in this post has been modified from Cadotte 2020).

One of the most pernicious and inevitable consequences of urbanization and industrialization is the release of air pollutants. The WorldHealth Organization (WHO) estimates that about 90% of urban residents experience air pollution that exceeds WHO guidelines and that air pollution is responsible for more than four million premature deaths annually (World Health Organization 2018). Air quality is adversely affected by the aerosol release of a number of chemical compounds from agriculture, manufacturing, combustion engines and garbage incineration, and is usually assessed by measuring the atmospheric concentrations of six key pollutants: fine particulate matter (PM_2.5), course particulate matter (PM₁₀), ground-level ozone (O₃), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and carbon monoxide (CO). These pollutants have a number of serious human health impacts (Table 1). Reducing inputs of these pollutants into urban areas requires a combination of technological advancement and behaviour change that can be stimulated by governmental regulations and incentives.

Table 1: The six commonly measured air pollutants in cities and their human health impacts.

Alterations of human, transport and industrial activity are usually the result of long-term economic and behavioural change and difficult to legislate under normal situations. However, the recent emergence of the global COVID-19 pandemic has had clear epidemiological impacts with, as of March 25, 2020, almost half a million confirmed infections and close to 20,000 deaths (World Health Organization 2020). This pandemic has resulted in emergency measures attempting to reduce transmission rates that limit activity, movement and commerce in jurisdictions around the world. While these emergency measures are critically important to limit the spread and impact of the coronavirus, they also provide a glimpse into how governmental calls for behavioural change can alter air pollution levels in cities.

Early evidence reveals that pollution levels have dropped in places that have undergone COVID-19 shutdowns. As Marshall Burke showed in a blog post,  PM_2.5 and PM₁₀, levels are lower than expected in parts of China. Here I examine January and February 2020 AQI levels for the six pollutants in Wuhan to what would be expected under normal circumstances. I further compare the change in February air pollution levels over the past two years in six cities that instituted emergency measures by the end of February (early impacted cities) to 11 cities that did not declare states of emergency until March (later impacted cities) using freely available air monitoring data (World Air Quality Index Project 2020) -see Table 2 for a list of cities.

Table 2: The eleven cities used in this analysis, the month that emergency measures were enacted and two- to six-year AQI averages of the pollutants

City-data come from monitoring agencies listed at the end of this post

Wuhan, China was the epicenter for the December 2019 emergence and the first person-to-person spread of the novel coronavirus.  In response, authorities initiated a series drastic measures limiting human movement and activity in Wuhan and large parts of Hubei province by the end of January. Three air pollutants: PM_2.5, PM₁₀ and NO₂ all showed substantial January and February declines in Air Quality Index (AQI) (U.S.Environmental Protection Agency 2014) values over 2019 levels for those months and what would be expected from long-term trends (Fig. 1). These long-term declining air pollution trends do reveal that China’s recentpollution reduction and mitigation efforts are steadily paying off, but the government-enforced restrictions further reduced pollution levels. The expected air pollution values predicted by temporal trends (red dashed lines in Fig. 1) are all substantially higher than the observed levels, with observed values being between 13.85% lower than expected for January PM_2.5 and 33.93% lower for January NO₂. Further, the reductions in the pollutants shown in Fig. 1 increased the number of days where pollutant concentrations were categorized as ‘good’ (0 < AQI < 50) or ‘moderate’ (51 < AQI < 100) according to the AQI. The three other pollutants: SO₂, O₃ and CO, all showed idiosyncratic or non-significant changes, mostly because their levels have already reduced significantly over time or appear quite variable (Fig. 2). 

Fig. 1. Temporal patterns of Air Quality Index (AQI) PM_2.5, PM₁₀ and NO₂ values in Wuhan, China. Both January and February, 2020 values show significant declines compared to 2019 levels and to that predicted from long-term trends (red dashed line).

Fig. 2. Temporal patterns of Air Quality Index (AQI) SO₂, O₃ and CO values in Wuhan, China.

Once COVID-19 moved to other jurisdictions, and confirmations of community spread emerged in February 2020, emergency measures, like those in Hubei province, were instituted to limit human movement and interaction. The cities subjected to February restrictions include, in addition to Wuhan, Hong Kong, Kyoto, Milan, Seoul and Shanghai, and the AQI values from these cities were compared to other cities that did not see the impacts of the novel coronavirus or have emergency restrictions in place until well into March. Log-response ratios between the air concentrations of pollutants observed in February 2020 to those from February 2019 reveal that all air pollutants except O₃ show a decline in the 2020 values for the early impacted cities (Fig. 3). For later impacted cities, there is no overall trend in changes in the concentrations of pollutants between 2020 and 2019 and the individual cities in this group showed less consistency in the differences between years (Fig. 3). 

Fig. 3. Log response ratios for Air Quality Index (AQI) PM_2.5, PM₁₀, NO₂, O₃, SO₂ and CO values between February 2019 and February 2020 values. Negative values indicate a decline in 2020. The green symbols indicate values from an assortment of cities that did not have emergency measures in place until March, 2020 (later impacted cities) and orange symbols are for cities that were impacted by the end of February.

These results indicate consistent air pollution reduction in cities impacted early by the spread of the novel coronavirus. However, the analyses presented here require further investigation as governments increasingly restrict activity world-wide, and some are discussing the possibility of prematurely lifting restrictions in order to spur economic growth. Further, the data analyzed here present point estimates of air quality but air pollution impacts are not homogeneous through urban landscapes and is influenced by spatial variation in industrial activities and transportation (Adams & Kanaroglou 2016). Thus, as higher resolution spatial air pollution data become available, it would be valuable to see how reduced activity affects air quality in different parts of cities.

This analysis of early data indicates that governmental policies that directly reduce human activity, commercial demand and transportation can effectively and quickly reduce urban air pollution. While the COVID-19 pandemic represents a serious risk for health and wellbeing of populations globally, especially those living in high density urban areas, the impacts of air pollution are equally consequential. If governments are willing to expend trillions of dollars in direct funding and indirect economic costs to combat this disease, then why do these same governments permit or even subsidize activities that emit air pollution? Maybe the lessons learned with COVID-19 can serve as the impetus for further action. Perhaps mandating changes to economic or transportation activity or investing in clean technology would better protect human health from the effects of air pollution.

Cited sources

Adams, M.D. & Kanaroglou, P.S. (2016) Mapping real-time air pollution health risk for environmental management: Combining mobile and stationary air pollution monitoring with neural network models. Journal of environmental management, 168, 133-141.
Cadotte, M. W. (2020) Early evidence that COVID-19 government policies reduce urban air pollution. Retrieved from eartharxiv.org/nhgj3

Cesaroni, G., Forastiere, F., Stafoggia, M., Andersen, Z.J., Badaloni, C., Beelen, R., Caracciolo, B., de Faire, U., Erbel, R. & Eriksen, K.T. (2014) Long term exposure to ambient air pollution and incidence of acute coronary events: prospective cohort study and meta-analysis in 11 European cohorts from the ESCAPE Project. Bmj, 348, f7412.

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Raaschou-Nielsen, O., Andersen, Z.J., Beelen, R., Samoli, E., Stafoggia, M., Weinmayr, G., Hoffmann, B., Fischer, P., Nieuwenhuijsen, M.J. & Brunekreef, B. (2013) Air pollution and lung cancer incidence in 17 European cohorts: prospective analyses from the European Study of Cohorts for Air Pollution Effects (ESCAPE). The lancet oncology, 14, 813-822.

U.S. Environmental Protection Agency (2014) AQI: Air Quality Index. Office of Air Quality Planning and Standards, Research Triangle Park, NC.

World Air Quality Index Project (2020) https://waqi.info/.

World Health Organization (2018) Ambient (outdoor) air pollution: https://www.who.int/news-room/fact-sheets/detail/ambient-(outdoor)-air-quality-and-health.

World Health Organization (2020) Coronavirus disease 2019 (COVID-19), Situation Report –65.

City air quality monitoring agencies:

¹ Division of Air Quality Data, Air Quality and Noise Management Bureau, Pollution Control Department, Thailand (http://aqmthai.com).

² Delhi Pollution Control Committee (http://www.dpccairdata.com).

³ Hong Kong Environmental Protection Department (http://www.epd.gov.hk).

⁴BMKG | Badan Meteorologi, Klimatologi dan Geofisika (http://www.bmkg.go.id).

⁵South African Air Quality Information System - SAAQIS (http://saaqis.environment.gov.za).

⁶ Japan Atmospheric Environmental Regional Observation System (http://soramame.taiki.go.jp/).

⁷ UK-AIR, air quality information resource - Defra, UK (http://uk-air.defra.gov.uk).

⁸ South Coast Air Quality Management District (AQMD) (http://www.aqmd.gov/).

⁹ INECC - Instituto Nacional de Ecología y Cambio Climático (http://sinaica.inecc.gob.mx).

¹⁰ Agenzia Regionale per la Protezione dell'Ambiente della Lombardia (http://ita.arpalombardia.it).

¹¹ CETESB - Companhia Ambiental do Estado de São Paulo (http://cetesb.sp.gov.br).

¹² Department of Public Health of the Sarajevo Canton (http://mpz.ks.gov.ba/).

¹³ Air Korea Environment Corporation (http://www.airkorea.or.kr).

¹⁴ Shanghai Environment Monitoring Center (http://sthj.sh.gov.cn).

¹⁵ Israel Ministry of Environmental Protection (http://www.svivaaqm.net).

¹⁶ Air Quality Ontario - the Ontario Ministry of the Environment and Climate Change (http://www.airqualityontario.com/).

¹⁷ Wuhan Environmental Protection Bureau (http://www.whepb.gov.cn/).