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. 2021 Aug 9;5:100239. doi: 10.1016/j.envc.2021.100239

Effect of COVID-19 pandemic on ambient air quality and excess risk of particulate matter in Turkey

Aysegul Yagmur Goren 1, Mesut Genisoglu 1, Hatice Eser Okten 1, Sait Cemil Sofuoglu 1,⁎
PMCID: PMC8427552  PMID: 38620652

Abstract

The COVID-19 pandemic, which has reached 4 million global cases as of March 10, 2020, has become a worldwide problem. Turkey is one of the most affected (9th in the world) country with 139 771 cases. An intermittent curfew policy that differ for three age groups, and an intercity travel ban varying within the country have been implemented. The effects of changes in social life and industrial activity in terms of environmental pollution are not yet known. The short-term effects on PM2.5, PM10, SO2, NO2, NO, NOx, O3 and CO concentrations measured at 51 air quality measurement stations (AQMS) in 11 cities in March – April period of 2020 were statistically compared with that of the previous year. While PM2.5 (9/14 AQMS) and PM10 (29/35 AQMS) concentrations were not significantly affected, NO (12/24 AQMS), NO2 (20/29 AQMS), NOX (17/25 AQMS) concentrations were decreased, SO2 concentrations at half of the AQMSs (11/25) did not show a significant change. There were stations at which higher pollutant concentrations were measured in the study period in 2020 compared to that of 2019. Excess risks associated with PM2.5 and PM10 were estimated to be variable, albeit with a small difference. In conclusion, the heterogeneous actions taken in response to the COVID-19 pandemic resulted in mixed effects on ambient air quality.

Keywords: Air quality, COVID-19, Excess risk, Turkey

1. Introduction

COVID-19 pandemic has been identified as one of the worst global health crises that human race faced so far. Since the report of the first one, there had been 4,013,728 confirmed cases, 278,993 of which ended in loss of life (WHO 2020). The most affected regions are Americas and Europe, and the most affected countries are listed as United States of America, Spain, Italy, Germany, United Kingdom, and France. After the first report in March 10, number of cases in Turkey has risen to 107,773 as of April 26, 2020. In a short summary, Turkey acted promptly and took action to prevent the spread of the infection. These actions included closing of educational institutions at all levels (March 16), enforcing curfew on citizens older than age of 65 (March 21), enforcing curfew on citizens younger than age of 20 (March 28), travel restriction to enter and leave 30 metropolitan cities and Zonguldak (due to being in a province with coal mining, thermal power plants, and iron-steel industry, and having a higher rate of respiratory diseases) (April 3), enforcing general curfew on weekends (April 11), and continuous stay-at-home calls to the general population. Furthermore, mobility between all cities was gradually decreased to the point of security forces controlling entries and exits. In order to prevent congregation of people in indoor spaces, most of the public sector has started to provide services online, leaving minimum staff in office buildings. Private sector was strongly encouraged to follow the example of the public sector. As a result, a large proportion of the population stayed at home, minimizing use of public transportation services and sustaining only basic commercial activities. Similar to global news reports on nature's regenerative power, Turkish media reported increased air quality based on visibility (Supporting Material, SM, Figure SM-1).

To date, several studies have been conducted on impact of COVID-19 pandemic on air quality in various parts of the world. The restrictions could not prevent spread of COVID-19, but it can improve the air quality due to decrease of transportation, traffic, and industrial production (Mahato et al., 2020, Tobías et al., 2020, Zhu et al., 2020a, Zhu et al., 2020b). For instance, the average air quality index value reduced by 7.8 % in China owing to the travel restrictions (Bao and Zhang, 2020). Dang and Trinh (2020) investigated global concentration of PM2.5 and NO2 before and after the COVID-19 pandemic in 164 countries and they reported that the PM2.5 and NO2 average concentrations reduced by 4 and 5 %, respectively. According to data in Eastern Europe, the concentrations of pollutants were considerably decreased during the COVID-19 pandemic compared with the same period in 2018 and 2019 (Filonchyk and Hurynovich, 2020).

Furthermore, it is widely reported that the CO, NO2, SO2, PM2.5, and PM10 concentrations decreased with COVID-19 pandemic, while the O3 concentrations increased or similar with previous years (Dantas et al., 2020). Furthermore, the air quality is significantly related to the COVID-19 pandemic as pollutants could affect human's immunity system and act as a virus carrier agent (Zhu et al., 2020a, Bianconi et al., 2020). Recently, studies focused on relation between PM2.5 and COVID-19 mortality rates. In a short summary, Chakrabarty et al. (Chakrabarty et al., 2021) investigated association between PM2.5 concentrations and spread of COVID-19 using reproduction ratio (R0) in the United States. They found that an increase of 0.25 in R0 was resulted from an increase of 1 μg/m3 in PM2.5 levels. Moreover, the increase in ammonium, sulfate, and nitrate in PM2.5 resulted in almost 10 % increase in R0 (0.22). They reported that there was a positive relation between long-term exposure to PM2.5 and COVID-19 cases in Canadian health regions. Similarly, the positive association between PM2.5 and COVID-19 pandemic was observed using negative binomial regression models in Canadian health regions by Stieb et al. (2020). The first evidence of the presence of SARS-CoV-2 RNA on outdoor PM samples was reported by Setti et al. (2020) in Italy. Recently, Hadei et al. (2021) reported the presence of SARS-CoV-2 RNA on airborne PM in public places and transportation in 64 % of the samples. The presence of SARS-CoV-2 RNA on ambient PM was also studied countrywide in Turkey (Kayalar et al., 2021). The samples were collected from 13 sites, which are specified as urban, urban background, and hospital gardens in 10 cities. The maximum percentage of virus RNA existence on PM samples, especially in PM2.5, was observed in hospital gardens. Their results showed that SARS-CoV-2 could be transported via PM at locations close to the infection hotspots. However, there is limited study about the association between PM2.5 concentration and COVID-19 cases, spread potential, and mortality rates. Therefore, comprehensive studies were deemed necessary for a better understanding of relation between PM2.5 concentration and COVID-19 infection using regression models or/and PM-related excess health risks determinations.

The major novelty of this paper lies in the determination of PM-associated excess health risk in Turkey before and during COVID-19 pandemic period, which is suspected to be one of the COVID-19 transmission ways. Moreover, this is the first study that investigates air pollution variation and estimates excess risk levels of PM2.5 and PM10 during COVID-19 pandemic period in Turkey. In this study, we investigated the combined effect of the preventive measures taken in COVID-19 pandemic on air quality of 11 cities in Turkey, seven of which were metropolitan cities. Data for the years of 2019 and 2020 were acquired from governmental air quality monitoring network that conduct real-time measurements of PM2.5, PM10, SO2, NO2, NO, NOx, O3, and CO. Concentrations measured in March 1-April 21 period in 2019 and 2020, and PM-associated excess health risks were compared to elucidate the effect of decreased human mobility and activity due to COVID-19 on air quality.

2. Methods

2.1. Study area and air quality parameters

Eleven cities, Ankara (A), Bursa (B), Corum (C), Istanbul (I), Izmir (IZ), Kars (K), Kocaeli (KO), Konya (KON), Kutahya (KU), Trabzon (T), and Zonguldak (Z) were selected for investigating impact of COVID-19 on air quality (Fig. 1). Selected cities represent 42.8 % of Turkey's population. Istanbul, Kocaeli, and Bursa are heavily industrialized zones with energy, steel, automotive, chemical and textile sectors. Metropolitan cities are A, B, I, IZ, KO, KON, and T. Although Zonguldak is not a metropolis, it was included in the travel restriction along with the metropolitan cities, due to having a higher rate of respiratory diseases (Table 1 ). Measured concentrations of air quality parameters (PM2.5, PM10, SO2, NO2, NOX, NO, O3, and CO) were obtained from the Air Quality Monitoring Database of the Ministry of Environment and Urbanization in Turkey (MEU, 2020). Number of Air Quality Monitoring Stations (AQMS) in the selected cities are presented in the descriptive statistic tables for each air quality parameter (Table SM 1-4). Since measured values for any given parameter at a given city can be quite scattered, overall median, minimum and maximum values were used in assessment instead of mean values.

Fig. 1.

Fig 1

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Investigated cities in Turkey (Adopted from Google MapsTM).

Table 1.

Investigated cities in this study.

City Population (n) Provincial Surface Area (km2) Population Density (n/km2) Road Motor Vehicles (n) Industry
Ankara 5639076 25632 220 2064501 Construction, Furniture, Metal, Defence, Printing
Bursa 3056120 10813 283 913154 Automotive, Textile, Cement, Energy, Chemical, Furniture
Corum 530864 12428 43 172622 Tile and brick, Roasted Chickpea
Istanbul 15519267 5343 2905 4222821 Textile, Tourism, Metal, Chemical Printing
Izmir 4367251 11891 367 1440392 Dye, Iron and steel, Petrochemical, Metal, Chemical, Food and beverage, Cement, Tourism
Kars 285410 10193 28 45111 Food, Wood
Kocaeli 1953035 3397 575 403209 Automotive, Pulp and paper, Iron and steel, Cement, Petrochemical, Energy, Aluminum, Waste, Chemical
Konya 2232374 40838 55 729076 Food and beverage, Tourism, Energy, Plastic, Base metal and casting, Automotive, Machinery
Kutahya 579257 11634 50 211463 Ceramic
Trabzon 808974 4628 175 200385 Cement, Printing, Metal and casting, Food
Zonguldak 596053 3342 178 156125 Energy, Cement, Mining
Turkey 82003882 780043 105 23361062
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2.2. Excess risk

Health risks due to change in ambient air PM2.5, PM10, SO2, NO, O3, and CO concentrations between March 1-April 21 in 2019 and 2020 were determined by estimating the excess risk (ER). The relative risk (RR) and ER were calculated using Eqs. 1 and 2, respectively.

RR=exp[β(Ci−Ct)],Ci>Ct (1)
ER(%)=(RR−1)×100 (2)

where, Ci and Ct are contaminant concentration and threshold concentration, respectively, β is the coefficient of the regression derived from meta-analysis by Shang et al. (2013). Threshold concentrations for PM2.5, PM10, SO2, NO2, O3, and CO were 25 µg/m3 (24-h average), 50 µg/m3 (24-h average), 20 µg/m3 (24-h average), 200 µg/m3 (1-h average), 100 µg/m3 (8-h average), and 4000 µg/m3 (1-h average), respectively Sharma et al., 2020, WHO 2005. If the concentration of a pollutant (Ci) is equal or below the threshold concentration (Ct), it has no excess risk. β values were 0.38 % for PM2.5, 0.32 % for PM10, 0.81 % for SO2, 1.30 % for NO, 0.48 % O3, and 3.7 % for CO (Shang et al., 2013).

2.3. Statistical

Shapiro-Wilk normality test was conducted with the significance level of 0.05, which was rejected for most of the air quality parameters at all stations. Therefore, nonparametric Mann-Whitney U-test (M-W test) was used to compare the concentrations. Significance level of M-W test was 0.05. Criterion of inclusion in this study for a pollutant measured at a station was having missing values <25 %.

3. Results and discussion

3.1. Effect of COVID-19 on levels of air quality parameters

Values for air quality parameters (PM2.5, PM10, SO2, NO2, NOX, NO, O3, and CO) were downloaded for the period of March 1 to April 21 in 2019 and 2020 for 11 cities in Turkey. Box-plots for the studied periods at each station are presented in Fig. SM 2-46.

3.1.1. PM2.5

PM2.5 emissions mainly originate from traffic, combustion of fossil fuels and biomass for energy production, and industrial facilities (Sharma et al., 2016, Guo et al., 2019). Exposure to high levels of PM2.5 may cause adverse human health effects, such as respiratory and cardiovascular diseases, premature death, and lung cancer (WHO 2013). Furthermore, since particles comprising PM2.5 may be suspended in ambient air for prolonged periods of time, it may serve as an important vector in spread of infection (Zhu et al., 2020a). Therefore, PM2.5 may be the most important air quality parameter to be investigated.

Overall median concentrations of PM2.5 were in the range of 10.2-23.7 µg/m3 (2019) and 17.3-30.4 µg/m3 (2020) (Table SM1 and Fig. SM2-5). The median values showed a slight increase in Ankara, Bursa, Istanbul, Kocaeli, Kutahya, Trabzon, and Zonguldak, while there was only a slight reduction in Istanbul. The M-W test indicate that the differences in PM2.5 concentrations were either not significant for all stations in Kocaeli and Bursa, and for 3/4 of stations in Istanbul, or higher in 2020 for Ankara, Kutahya, Trabzon, and Zonguldak. There was only one station (in Istanbul) that had a significantly higher PM2.5 median concentration in 2019 compared to 2020.

A significant reduction in PM2.5 concentrations was observed in other countries during the COVID-19 pandemic period due to strict curfew policies. For instance, the average PM2.5 concentration reduction in a northern region of Malaysia was found to be 23.7 % through a ban of business operation except for essentials and suspension of activities in several industries as well as enforcing curfew on citizens (Abdullah et al., 2020). In India, PM2.5 and PM10 concentrations in 22 cities in different regions of the country were analyzed and overall decreases of 43 % and 31 % were reported, respectively (Sharma et al., 2020). With the strict traffic restrictions and self-quarantine implementations, the reduction in PM2.5 concentrations was also reported to be 20-30 % in majority of China during the COVID-19 pandemic period compared with the same period in years 2017, 2018, and 2019 (Zambrano-Monserrate et al., 2020). While the particulate concentration during curfew period in Wuhan was decreased by 56 %, the decrease in European cities (Rome, Valencia, Nice, and Turin) was 8 % (Benchrif et al., 2021). In comparison, curfew policy partly excluding public service and production based working population (ages between 20 and 65) in Turkey allowed continuation of industrial and construction activities, which also necessitated transportation activities. Furthermore, curfew on ages >65 and <20 may have increased residential heating emissions. These could be the main reasons for not observing reductions in the median PM2.5 concentrations. Our results were in good agreement with another study conducted in Turkey (Aydın et al., 2020). They investigated the impact of COVID-19 on air quality based on the air quality index during December 2019, April 2020, and May 2020, and reported that the PM2.5 index increased in Ankara and coastal areas due to the industrial activity in April 2020.

3.1.2. PM10

Diesel engines, industry, resuspension of soil particles, industrial activities and residential fossil fuel heating are the main sources of PM10 pollution (Lenschow et al., 2001). Overall median concentrations of PM10 ranges were 24.2-55.2 µg/m3 (2019) and 27.6-76.5 µg/m3 (2020) (Table SM1 and Fig. SM6-11). Reduction in overall median PM10 concentrations were 13.1 %, 15.0 %, 2.82 %, 11.0 %, 2.77 %, and 8.79 % in Corum, Bursa, Istanbul, Kars, Kocaeli, and Konya, respectively. On the other hand, the overall median PM10 concentrations increased in Ankara (31.8 %), Izmir (38.8 %), Kutahya (9.80 %), and Trabzon (11.6 %). M-W test indicated that, in general, PM10 concentration distributions were not significantly affected by the actions taken against COVID-19 in Turkey. The median PM10 concentrations at all stations in Bursa (n=3), Corum (n=2), Kars (n=1), Kocaeli (n=9), and Kutahya (n=1), 1/3 of the stations in Ankara, 10/11 of the stations in Istanbul, and 2/3 of the stations in Trabzon were not significantly different. There were only five stations with significantly differing concentrations: one in Ankara and Istanbul with 2019>2020, and one in Ankara, Trabzon, and Zonguldak with 2019<2020.

Partial lockdown has decreased the PM10 concentrations in Milan-Italy by 32.7-40.5 % (Collivignarelli et al., 2020). Additional reductions were observed during the total lockdown period. In Turkey, white collar employees were allowed to work home-office and the traffic density decreased due to curfew policies in the business center(s) of the cities, which may be the reason for the reductions observed at two stations in Istanbul and Ankara but the remaining stations (10/11 in Istanbul and 2/3 in Ankara) did not support this observation. Industrial production (for Istanbul, Kocaeli, Bursa, and Ankara,) and shipping traffic (for Istanbul, Kocaeli, and Bursa) were not interrupted during the study period, which probably played a role in the not significantly differing concentrations between 2019 and 2020. Higher PM10 concentrations in Izmir in 2020 might be due to the increase in industrial production and shipping traffic to meet the demand in food sector. The increase in PM10 concentrations at Besirli station in Trabzon might be due to combustion of fossil fuels for residential heating. The median concentration in Zonguldak was tripled from 2019 to 2020. We do not have the data to reasonably explain this sharpest change in PM10 concentrations other than to speculate that an increased residential heating may had a role while emissions of the seven thermal power plants and the iron-steel plant also continued.

3.1.3. NOX

Overall median concentrations of NO2 for seven cities (29 stations) were in the range of 24.9-77.9 µg/m3 (2019) and 23.2-59.1 µg/m3 (2020) (Table SM2 and Fig. SM12-17). Results showed a significant decrease in COVID-19 pandemic period compared with the same period in 2019. The highest reduction was 40.9 % in Trabzon, while the lowest reduction was 6.83 % in Kocaeli. Concentrations did not significantly change from 2019 to 2020 at 1/4, 2/11, 4/6, and 1/4 of the stations in Bursa, Istanbul, Kocaeli, and Trabzon, respectively. On the other hand, they were significantly higher in 2019 at 20 stations (in A, B, I, K, KO, T, and Z). Therefore, station location is a determining factor: NO2 concentrations at stations in heavily industrialized/commercial areas or at transportation connection hubs did not differ significantly, most probably due to emissions from traffic despite preventive measures. Dantas et al. (2020) studied effect of COVID-19 pandemic period on air quality of Rio de Janeiro, Brazil. They found that the median NO2 concentration was 24.1–32.9 % lower when compared with the same period in 2019. They also reported that the least reduction was observed for NO2 most probably due to diesel combustion and industrial activities. The NO2 reductions were found to be 20-30 % in Wuhan, China, Europe, Italy, France, Spain, and USA following lockdown periods (NASA 2020, ESA 2020). Kaplan and Avdan (2020) investigated the effect of COVID-19 on NO2 concentration in Turkey during the March 15-April 15 periods in 2019 and 2020. They reported that the mean concentration of NO2 was found to be in the range of 50 to 220 µmol/m2 in 2019, it was in the range of 40 to 135 µmol/m2 during COVID-19 period in 2020. Furthermore, the highest reduction was found to be 57 % in some cities of the Turkey.

Overall median NO concentrations were in the range of 6.24-31.8 µg/m3 (2019) and 8.57-20.9 µg/m3 (2020) (Table SM2 and Fig. SM18-23). Similar to NO2, a significant decrease was observed in NO concentrations. There were 12 stations at which reduced concentrations were measured (2 in Ankara and Kocaeli, 4 in Istanbul, 1 in Kars, and 3 in Trabzon) during the COVID-19 period. For the remaining stations, the difference in NO concentrations were not significant at 7 stations (2/4 in Bursa, 4/9 in Istanbul, 1/4 in Trabzon) and higher in 2020 at 4 stations (1/4 in Bursa, 1/9 in Istanbul, and 2/4 in Kocaeli). Furthermore, the overall median NOx concentrations were 36.4-89.6 µg/m3 (2019) and 33.8-72.1 µg/m3 (2020) (Table SM3 and Fig. SM24-29). The concentrations were lower in 2020 at 17 stations, no significant difference at 6 stations, and higher in 2020 at 2 stations (2/8 in Kocaeli).

3.1.4. SO2

The overall median concentrations of SO2 were 4.52-34.1 µg/m3 and 4.31-12.6 µg/m3 in 2019 and 2020 for nine cities (Table SM3 and Fig. SM30-36). Furthermore, changes in overall median SO2 concentrations were as follows: 15.4-61.9 % reduction (Trabzon, Zonguldak, Kars, Izmir, Bursa, and Corum) and 7.74-63.7 % increase (Istanbul, Kocaeli, and Ankara). The highest reduction was 61.9 % (from 11.3 µg/m3 to 4.31 µg/m3) in Trabzon while the highest increase was 63.7 % in Istanbul (from 4.90 µg/m3 to 8.02 µg/m3). The M-W test indicated that the concentrations did not significantly change in Corum, Izmir, Ankara (1/2 stations), Bursa (4/5 stations), Istanbul (2/9 stations), and Kocaeli (2/4 stations), whereas, increased concentrations were observed in 2020 in 1/2, 6/9, 2/4, and 1/1 stations in Ankara, Istanbul, Kocaeli, and Zonguldak respectively.

The increase in SO2 concentrations was significant in Ankara, Istanbul, and Kocaeli, which have a large number of industrial facilities and high population density. These results point to continuation of industrial activities and dense population as probable causes for the increased SO2 concentrations during COVID-19 pandemic period. Decreased traffic-sourced particulate, NOx, and SO2 concentrations during curfew period might have been compensated by increased industrial emissions associated with extra production to meet the shifted demand due to the decreased supply from China and suspension of production in some of the European countries (WEB, 2021). Co-emission of PM, NOx, and SO2 during the fuel combustion (Latha and Highwood, 2006) supports the argument that decreased traffic emissions could have been compensated by increased industrial production to meet the shifted demand.

3.1.5. CO

CO concentrations could be analyzed in seven cities because the inclusion criterion was not met at many stations. The overall median concentration ranges were 463-926 µg/m3 and 1.09-2282 µg/m3 in 2019 and 2020, respectively (Table SM4 and Fig. SM37-41). Reduction in overall median CO concentrations were 3.82 %, 15.4 %, and 28.4 %, in Kars, Trabzon, and Zonguldak, respectively. On the other hand, the overall median CO concentrations almost doubled in Ankara, Bursa, and Istanbul. According to the M-W test, the median CO concentrations were higher in 2019 compared to 2020 at 1/2 stations in Kars, 3/4 stations in Kocaeli, and all stations in Trabzon and in Zonguldak. However, the median CO concentrations were lower in 2019 compared to 2020 for all stations in Bursa and Istanbul, while the difference in CO concentrations were not significant in Ankara.

In summary, CO emissions significantly decreased in Kars, Trabzon, and Zonguldak as these cities had fewer industrial activities except for Zonguldak. Ankara, Istanbul, and Bursa are considered as the metropolitan cities with high industrial capacity and registered motor vehicles. No reduction in CO concentrations were observed in these cities during the COVID-19 pandemic period. The reason for the increase and/or no significant change in CO concentrations in these cities might be the continuation of industrial activities and associated transportation. Similar results observed in southern India, such that a significant increase was observed in CO concentration, while a significant decrease was observed in other pollutants concentrations (NO, NO2, and O3) during the COVID-19 pandemic period (Zhu et al., 2020a).

3.1.6. O3

O3 was the pollutant with the least available data. Its concentrations are presented in Table SM4 and Fig. SM42-46. In Bursa, reduction in overall median O3 concentration was 3.08 % (45.5 µg/m3 in 2019 and 44.1 µg/m3 in 2020). Changes in median O3 concentrations were lower during COVID-19 period at 1 of 3 stations in Bursa, while the difference was not significant at the remaining two stations. Studies on atmospheric O3 concentrations revealed that the decrease in NOx concentrations may be attributed to the increase in O3 concentrations (Geraldino et al., 2020, Dantas et al., 2019). Moreover, the decrease in PM concentrations, which results in increased sunlight reaching the Earth, may be attributed the production of O3 with photochemical reactions (Dang and Liao, 2019). During the COVID-19 pandemic period, increase in O3 concentrations may be related to the decrease in PM and NO2 concentrations. For instance, the median O3 concentration increased by 6.34 %, while PM10 and NO2 median concentrations decreased by 14.0 % and 37.5 %, respectively at the mountain (Uludag) station in Bursa. On the other hand, at Kestel station, again Bursa but close to its Organized Industrial Zone, the median O3 concentration decreased by 18.8 %, while the PM10 concentration increased by 6.47 %. While, ozone could be formed with the presence of NOx, VOC, and sunlight (Wang et al., 2019), NO emissions could result in reduction in ozone concentration due to the NO-titration effect, forming NO2 (Zara et al., 2021). Zara et al. (2021) reported that the ozone chemistry plays an important role on NOx column in troposphere: Decreasing NOx concentrations in Netherlands between 2005-2018 contributed the increasing ozone concentration due to the decreasing NO-titration. Wang et al. (2020) reported significant increases in O3 concentrations probably due to lower fine particle loadings, which cause less scavenging by HO2, and thus observation of O3 concentrations for longer periods. A similar trend was reported by Mahato et al. (2020) for megacity Delhi, India. They found that O3 concentrations increased significantly during the COVID-19 pandemic period possibly due to decrease in NOx and NO concentrations, and increase in insolation and temperature.

Table 2 shows the overall median concentrations for the duration of the last five years, i.e. for 2016-18, 2019, and 2020. The medians of 2016-18 and 2019 for O3 and PM2.5 were comparable, i.e. within a difference of 20 % (O3 increased by 11.5 %, PM2.5 decreased by 16.5 %), while NOx, NO2, PM10, CO, and SO2 medians were considerably lower in 2019 compared to the previous three-year period. A detailed description of variation in the medians is presented in the SM (see section entitled Variation in concentrations during 2016 – 2020). The change in the medians from 2019 to 2020 is similar to that in 2016-18 to 2019 for only NOx and NO2, which supports the observations and inferences made for the effect of the pandemic on air pollution levels being not all in the direction of decrease but rather mixed probably due to the heterogeneous actions taken in response to the pandemic. However, the simple approach adopted in this study, that does not allow variables such as wind speed and direction, temperature, relative humidity, mixing height, etc., and the effect of atmospheric chemistry or ongoing long-term trends to be taken into account, is a limitation. Şahin (2020) studied the correlation between COVID-19 cases and meteorological data in Turkey, reporting Spearman Rho coefficient ranges of [-0.32 – -0.48], [-0.30 – -0.40], [-0.32 – 0.02], and [-0.22 – 0.55], respectively for temperature, dew point, humidity, and wind speed (Şahin, 2020), among which the highest correlation coefficient (0.55) belonged to wind speed (14 days ago).

Table 2.

Overall median concentrations (µg/m3) of air pollutants from March 1 to April 21.

2016-2018 2019 2020
NOx 73.0 51.7 45.0
PM2.5 23.1 19.3 20.7
PM10 48.8 37.5 36.8
NO2 47.1 35.5 29.3
SO2 9.84 6.76 6.94
CO 743 572 831
O3 37.7 42.6 36.5
NO N.A. 12.2 11.5
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3.2. Excess risk assessment

Exposure to PM2.5 mainly causes respiratory and cardiovascular system problems. Hence, it may aggravate the COVID-19 infection symptoms and may increase mortality rate. Wu et al. (2020) studied the relationship between air pollution and COVID-19 mortality in the United States and found that comorbidities related to PM2.5 dramatically increased the risk in COVID-19 patients. Overall and city-based excess risks (ER) were compared for PM2.5 and PM10 median concentrations (Fig. 2, Fig. 3 ). Comparisons of ERPM2.5 values revealed decreases for Bursa, Istanbul, and Kocaeli, and increases for Trabzon, Kutahya, and Zonguldak (Fig. 2). Since Bursa, Istanbul, and Kocaeli are densely populated metropolitan cities, decrease in traffic and industrial activities due to progressive prevention measures during the COVID-19 pandemic period resulted in decrease of ER values. For the capital city of Ankara, the median ER values were similar (Table 3 ). The most significant increase in median ER values was calculated for Zonguldak, where coal mining and related activities such as thermal power plants and iron-steel industry are the major sources of livelihood. Furthermore, the overall ER values decreased from 2019 to 2020 (Fig. 2). Sharma et al. (2020) compared the effect of restricted emissions during COVID-19 on air quality in India with previous three years. They reported that there was considerable health risks related to PM2.5 and PM10 in all the regions during the lockdown period of COVID-19 pandemic. However, the mean ER values for PM2.5 and PM10 decreased by almost 52 % on average in India compared with the previous years. Relationship between COVID-19 infection and short-term exposure to PM2.5, PM10, CO, NO2 and O3 were investigated in China (Zhu et al., 2020a), showing that daily counts of confirmed cases increased by 2.24 %, 1.76 %, 6.94 %, and 4.76 % with a 10 μg/m3 increase in PM2.5, PM10, NO2, and O3, respectively. The correlation between seven air quality parameters (CO, NO, NO2, NOx, PM10, O3, and SO2) and COVID-19 cases in Turkey was investigated using Spearman Rho and Pearson correlation analyses (Şahin, 2020). It was reported that a significant correlation (r=0.617) between PM10 and COVID-19 cases was observed.

Fig. 2.

Fig 2

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Excess risks associated with PM2.5. Risk levels estimated for seven cities and the combined dataset before (2019) and during (2020) pandemic are compared based concentrations measured in March 1 – April 21 period. Risk was significantly decreased for Bursa, Istanbul, and Kocaeli, major metropoles with major industry, increased for Trabzon, Kutahya, and Zonguldak, smaller cities with no (T), some (KU), and major (iron-steel, thermal power plants, and coal mining, Z) industry, while the difference was not significant for Ankara, the capital. The change was relatively small (between -1.87% and +3.68%) except for Zonguldak. Overall, there was a significant but relatively small decrease.

Fig. 3.

Fig 3

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Excess risks associated with PM10. Risk levels estimated for 11 cities and the combined dataset before (2019) and during (2020) pandemic are compared based concentrations measured in March 1 – April 21 period. Risk was significantly decreased in Corum, Ankara, Bursa, Kocaeli, and Kutahya, while it increased in Istanbul, Izmir, Kars, Konya, Trabzon, and Zonguldak. The change was relatively small (between -2.01% and +3.21%) except for Zonguldak. Overall, there was a significant but relatively small decrease.

Table 3.

Descriptive statistics of excess risk levels (%) of PM2.5 and PM10.

Parameter City Number of AQMS Year Median Mean Min Max
PM2.5 Ankara 4 2019 3.71 3.85 0.004 8.29
2020 3.96 8.90 0.03 51.4
Bursa 2 2019 5.02 5.65 0.27 20.4
2020 3.15 4.26 0.01 15.9
Istanbul 4 2019 3.28 4.72 0.03 19.3
2020 1.85 2.80 0.01 9.25
Kocaeli 4 2019 3.40 4.13 0.03 14.7
2020 2.84 3.39 0.13 12.7
Kutahya 1 2019 2.59 3.46 1.04 7.16
2020 3.50 3.15 0.28 7.03
Trabzon 1 2019 1.95 2.36 0.09 6.11
2020 2.53 3.06 0.46 12.0
Zonguldak 1 2019 2.49 3.56 0.31 10.0
2020 6.17 6.62 1.18 15.3
PM10 Corum 3 2019 5.31 8.60 0.08 49.4
2020 4.83 7.12 0.06 29.8
Ankara 7 2019 7.04 12.4 0.25 59.4
2020 5.98 8.69 0.05 81.8
Bursa 4 2019 7.33 10.8 0.002 47.2
2020 5.32 7.40 0.11 30.6
Istanbul 11 2019 5.89 8.19 0.03 54.1
2020 6.18 9.76 0.13 53.5
Izmir 1 2019 2.04 1.85 0.54 2.78
2020 5.36 5.01 1.11 10.7
Kars 1 2019 8.05 7.14 0.22 10.1
2020 9.59 7.76 0.88 13.3
Kocaeli 11 2019 5.37 7.25 0.04 31.8
2020 3.87 5.27 0.03 32.9
Konya 2 2019 2.72 4.20 1.08 14.7
2020 3.01 4.77 0.33 18.0
Kutahya 1 2019 8.40 8.38 0.06 24.8
2020 7.03 9.30 1.01 28.9
Trabzon 5 2019 2.91 4.38 0.04 17.7
2020 3.27 4.92 0.04 24.0
Zonguldak 1 2019 1.76 1.43 0.62 1.89
2020 15.7 17.6 1.26 40.8
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The median ER value associated with PM10 decreased in Corum, Ankara, Bursa, Kocaeli, and Kutahya, while it increased in Istanbul, Izmir, Kars, Konya, Trabzon, and Zonguldak from 2019 to 2020. The most pronounced increase was calculated for Zonguldak. It should be noted that although both increases and decreases in concentrations were observed for the studied cities, they were general relatively small changes (for PM10 median ER changed between -2.01% and +3.21% except for Zonguldak; for PM2.5 ER changed between -1.87% and +3.68%). Due to the enforced partial curfews and calls for staying at home, emissions from transportation and industrial activities might have been limited because a portion of the population kept working, while emissions from residential heating were probably increased because the remaining portion of the population were forced to stay at home. In Turkey, 15 °C is generally the threshold temperature for residential heating. For our study period (March 1-April 21), the highest average temperature was measured as 18.9 °C in Izmir, while the lowest average temperature was 9.5 °C in Kars. Despite the extensive infrastructure of natural gas in cities of Istanbul, Ankara, Bursa and Kocaeli, there are parts of these cities that still use coal and fuel oil for residential heating. The probable effect of fossil fuel based residential heating was most readily observed in Zonguldak for PM2.5 and PM10. Overall median ER values for PM2.5 and PM10 decreased slightly during the COVID-19 pandemic period in Turkey based, respectively, on the 7- and 11-city data. In spite of the decreasing ER in 2020, there are still health risks associated with PM2.5 and PM10 as the concentrations are higher than their respective threshold levels, which, along with concentration reductions reported in the literature, implicate that a concerted effort but not mixed measures is needed for better air quality and reduced health effects. Atmospheric SO2, NO2, NOX, NO, O3, and CO concentrations were below the limits recommended by World Health Organization, therefore, the ER levels were not calculated for these pollutants.

4. Conclusion

This study shows the effects of curfew policies on air quality parameters in Turkey. Selected AQMSs represent 42.8 % of the population in Turkey (Ankara, Bursa, Corum, Istanbul, Izmir, Kars, Kutahya, Kocaeli, Konya Trabzon, and Zonguldak). Statistical comparison between March-April periods of 2019 and 2020 shows that, in general there were no significant difference in concentrations of PM, and at half of the stations for SO2, whereas, overall NOx, NO2, and NO concentrations were significantly decreased. While the highest NO2 reduction was determined in a non-industrial city with 40.9 %, the lowest reduction was in a heavily industrialized one with 6.83 %. Similar trends were observed for NO and NOx. While the CO emissions were increased in metropolitan cities, in others a decrease was observed probably due to fewer industrial activities. Current available ozone data was only in Bursa, with an overall insignificant decrease. There were stations at which concentration increases were observed, such as tripling of PM in a non-metropolitan city but close to dense coal mining and thermal power plants, and a 63.7 % in SO2 in Istanbul. Excess risk (ER) associated with PM may be important for the spread of the virus because it may act as a transport media. ER could only be estimated for PM2.5 and PM10 since concentrations of the other pollutants were below their threshold levels. Overall countrywide median ER values for PM2.5 and PM10 decreased slightly during the investigated period. Despite the decrease in PM concentrations, PM associated health risks were continuing due to the atmospheric PM concentrations still being above the threshold levels. In conclusion, the heterogeneous actions taken in response to the COVID-19 pandemic resulted in mixed effects on ambient air quality, which implicate that a concerted effort but not mixed measures is needed for better air quality and human health.

Declarations of Competing Interest

The authors declare that there is no conflict of interest.

Acknowledgment

The Air Quality Monitoring Database of the Ministry of Environment and Urban Urbanization of Turkey is acknowledged for publicly available monitoring concentrations.

Footnotes

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.envc.2021.100239.

Appendix. Supplementary ma

mmc1.pdf (7.2MB, pdf)

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