Background
Ground-level ozone, as a secondary pollutant, is harmful to human health and crop yields. It is one of the six criteria air pollutants regulated by the U.S. Environmental Protection Agency [
1,
2]. Generally, this gaseous pollutant is formed by the photochemical reaction of the precursors volatile organic compounds (VOCs) and nitrogen oxides (NO
x), driven by solar radiation and temperature [
3]. There are two primary sources of precursor material, including anthropogenic (e.g. transportation, coal burning, residential) and natural sources (e.g. plant, lightning, biochemical reactions in soil) [
4]. In addition to emission sources, meteorological factors, the VOCs/NO
x ratio, and solar radiation can affect the formation of ozone [
5‐
7]. Therefore, the diversity of sources and the uncertainty of influencing factors increase the difficulty of controlling ozone pollution.
In the past decades, with the development of China’s economy and urbanization, air pollution has become a public health issue of social concern. PM
2.5 control, rather than ozone control, has become a national priority. In 2013, Chinese state council issued Air Pollution Prevention and Control Action Plan, which aims to solve the problem of particulate air pollution within five years by adopting ten strict measures, prioritizing the establishment of ten key city clusters, and setting specific limits for PM
2.5 concentration in the Beijing-Tianjin-Hebei region (BTH), the Yangtze River Delta (YRD) and the Pearl River Delta (PRD) [
8]. After five years of efforts, the PM
2.5 mean concentration in China, the BTH, the YRD, the PRD region decreased by 39.4, 34.3, 27.7 and 39.6% from 2013 to 2017 [
9]. In contrast, there is a continued increase in ground-level ozone concentration [
10]. From 2013 to 2017, the annual ozone concentration in China, the BTH, the YRD, the PRD region increased by 20.4, 29.9, 22.1 and 8.6% respectively, while gaseous pollutant such as sulfur dioxide, nitrogen dioxide and carbon monoxide decreased by 12, 11 and 30% respectively during the same period in China [
11]. In fact, ozone replaced particulate matter as the primary pollutant in the BTH, the YRD and the PRD region in 2016 [
12]. Compared with Japan, South Korea, Europe and the United States, the magnitude and frequency of high-ozone events in China are much more significant [
13].
In recent years, a series of epidemiological studies reported that short-term exposure to ozone is strongly associated with increased mortality risk of all-cause [
14,
15], cardiovascular disease [
16,
17] and respiratory disease [
18]. Meanwhile, health burden assessment has been introduced to estimate the premature mortality and economic losses associated with ozone exposure. For example, Lin et al. estimated the number of COPD-related premature deaths attributable to long-term exposure to ozone in China in 2014, which was 89,391 (95% CI: 32,225 – 141,649) [
19]. Liu et al. reported that the COPD deaths caused by long-term ozone exposure in China ranged from 55,341 to 80,280 in 2015 [
12]. Maji et al. found that the national ozone attributable all-cause mortality was 69.6 (95% CI: 16.2–115) to 74.2 (95% CI: 16.7–127) thousand in 2016 [
20]. Liang et al. estimated that 120 (95% CI: 67–160) thousand premature deaths could be avoided if China’s ground-level ozone concentration was reduced to the 100 μg/m
3 [
21]. Most of the existing studies focused on the long-term effects of chronic ozone exposure, while ignored the health impacts caused by short-term exposure, perhaps due to the long-term exposure effects is far significant than the short-term [
22‐
27]. However, in China, even small short-term effects may cause huge health and economic burden due to the large population and high-intensity ozone exposure and it is still unclear the extent of the impact across the country. If this is a considerable number, then when considering the overall health burden related to ozone in China, the portion due to short-term exposure should be included and the corresponding economic losses should not be ignored. In addition, although existing studies have analyzed the spatial hotspots of ozone-related health and economic burden, for example, Maji et al. found that Beijing, Shanghai and Chengdu were the three cities with the highest number of premature deaths [
20], these studies are limited to a single space dimension, and few explored the spatiotemporal patterns of health and economic burden caused by short-term exposure to ozone.
In epidemiological studies, exposure-response functions are used to link pollutant concentrations to their health effects, which are calculated based on exposure-response coefficients [
28]. Therefore, accurate exposure-response coefficients can improve the accuracy of health burden estimation. In China, the exposure-response coefficient may vary depending on the local population, social and economic characteristics. However, most of the existing nationwide studies have set a single exposure-response coefficient for each health endpoint, which may bias the result [
6,
29‐
31]. In addition, monetizing mortality attributable to air pollutants most commonly used the value of statistical life (VSL), while the willingness to pay (WTP) is the preferred method to calculate [
32]. However, the spatial resolution of VSL in existing research can only be limited to the provincial level [
20,
21,
30,
33]. Due to the economic imbalance in Chinese cities, the economically-developed cities may have higher VSL and dense population, and the coarse spatial resolution may not be conducive to the embodiment of economic loss differentiation between cities. As far as we know, no study introduced city-level VSL to estimate the economic loss attributable to air pollutants.
Exposure parameters are used to describe the amount or rate of human exposure to external pollutants (e.g. inhalation rate) as well as the basic characteristics of the human body (e.g. inhalation rate) and environment (e.g. floor area), which are important factors for accurate exposure assessment.
Due to the variety of local human activities, environment and social characteristics, the regional differences of exposure parameters may exist. If the exposure parameters are ignored, the spatial diversity of exposure dose on the inter-regional scale may be covered up. Therefore, the inclusion of localized exposure parameters in the health burden assessment can remedy this weakness. The first manual of exposure parameters was published in the United States as early as 1989 [
34], while China did not publish the first edition until 2013. Most of the existing studies adopted the parameters of the United States [
35,
36] or did not consider the modification effect of the parameters on outcomes at all [
37,
38],which may lead to unreliable conclusions. For example, Wang et al. had found that if the inhalation rates of the United States were used directly in China, the error would be 2.6 to 30.9%, which would increase the uncertainty of health risk assessment results [
39]. Zou et al. estimated the health burden of long-term exposure to PM
2.5 and found that if exposure parameters were not taken into account, the number of premature deaths in China would have been overestimated by 12,434 to 14,684 cases [
40].
Therefore, in order to estimate the spatiotemporal trend of health and economic burden caused by ozone short-term exposure in China in recent years, and to compensate the roughness of exposure-response coefficients selection and economic valuation in previous studies, as well as the estimation bias caused by ignoring exposure parameters. This study first estimated the premature deaths associated with short-term ozone exposure in 334 cities of China in 2015–2018 based on the Log-linear exposure-response function with the localized exposure-response coefficients. Second, we introduced localized exposure parameters to recalibrate the estimated number of premature deaths. Finally, we used the city-level VSL to convert the health burden into economic loss, and calculated the impact on local GDP. Our objectives are as follows: (1) to estimate city-specific health burdens and corresponding economic loss attributable to short-term O3 exposure; (2) to reveal the spatial and temporal dynamics of health and economic burden associated with short-term exposure to O3; (3) to propose enlightening information for decision-makers to develop ozone prevention and control strategies.
Discussion
As a strong oxidant, ozone is harmful to human health and agricultural production, in addition, as an important greenhouse gas, ozone plays an important role in global climate change [
84,
85]. Due to its dual harm to health and climate, ozone has been paid close attention by environmental scientists and regulators in the past decades [
86‐
88]. In China, economic development and urbanization have brought about serious environmental problems. Air pollutants have become an essential factor endangering the health of residents, and the government has begun to take intervention measures against pollutants [
8,
89]. The previous control strategies always put priority on particulate matter and acid rain [
90]. Actually, the concentration of particles in China has been decreasing year by year, but the problem of ozone pollution has become worse. Our study found that the national ozone concentration has increased significantly in mainland China from 2015 to 2018 and maintained at a high level, although the concentration of ozone in some regions decreased from 2017 to 2018. Especially from 2016 to 2017, cities in the BTH and YRD region, Xinjiang Province and Tibet Province increased by more than 50 μg/m
3. In addition to the North China Plain, the YRD, the PRD, the Shandong Peninsula and Chengdu-Chongqing areas were facing high annual average concentration, we found that the ozone pollution in the Qinghai-Tibet Plateau and Gansu area was also severe, which was manifested in the high proportion of nonattainment days (even higher than North China Plain) that cannot be reflected by the annual average ozone concentration. Various reasons might explain the long-term nonattainment ozone concentration on the Qinghai-Tibet Plateau. One of them is because the precursor material from the long-distance transport is the basis of the formation of ozone in the Tibetan Plateau, and the unique strong near-surface convergence and upper layer divergence driven by elevated surface heating and low air density over the Qinghai-Tibet Plateau provides the driving force for this transport [
91,
92]. As for Sichuan Basin, a large number of VOCs and NO
x were emitted, the topography of the surrounding the mountains and the unique atmospheric circulation generated a high concentration of ozone [
93]. In other regions, such as the BTH region, the effect of long-distance transport is not apparent due to the high local emissions, while the transport in the adjacent regions aggravates the rise of local ozone concentration [
94]. From 2006 to 2011, the emission rate of precursors in Beijing has actually decreased. However, the VOCs from nearby areas still make the surface ozone concentration rise [
95]. In a previous research, the CMAQ model was used to evaluate the possible emission reduction measures, and it was found that if only the local emissions in Beijing were reduced (even 90%), it could not even meet the CNAAQS Grade II (160 μg/m
3). Only by reducing the emissions in Beijing, Tianjin and Hebei simultaneously by 60 to 80% could the significant effect be achieved [
96]. Therefore, the government needs to take specific preventive measures according to the unique causes of local ozone pollution in order to achieve the desired results.
Although there is a lack of national all-cause mortality studies, Wang’s study reported the number of disease-specific mortality caused by long-term ozone exposure in China from 2013 to 2017, with an average of 0.31 million premature mortality per year from cardiovascular and respiratory diseases [
97]. In our study, an average of 0.22 million people died of cardiovascular and respiratory diseases caused by short-term ozone exposure every year, accounting for 70.96% of the long-term exposure related deaths reported by Wang [
97]. This shows that China’s ozone burden is mainly caused by short-term exposure. Therefore, in China, we cannot ignore the health impacts caused by short-term exposure to O
3. From 2015 to 2017, the national O
3 exposure related health burden generally increased, especially in the North China Plain, Shandong Peninsula, Central-Liaoning, the YRD, the PRD and Chengdu-Chongqing region. This is consistent with the trend of ozone concentration, suggesting that the increase in health burden over the past 2015–2017 is probably due to the aggravation of ozone pollution. During 2017–2018, ozone pollution in priority areas such as the BTH region, the YRD, the PRD and the Shandong peninsula has been generally improved, and government intervention measures have avoided 40,000 premature deaths, suggesting that local policymakers have begun to pay attention to ozone pollution and formulate targeted intervention measures.
Due to the lack of nationwide short-term ozone health burden assessment studies in China, only a few studies were used for uncertainty analysis. Some scholars have comprehensively evaluated the health burden of long-term exposure to ozone in China, but the results show heterogeneity, which may be caused by the estimation of exposure, the selection of outcomes and the setting of thresholds. At present, most studies use chemical transport models or ground monitoring stations to estimate ozone exposure. In 2016, Madaniyazi combined two chemical transport models to estimate the ozone health burden in East China in 2030 [
75]. The results show that the number of premature deaths without intervention ranges from 40,000 to 260,000. In 2018, Lin and Liu used the WRF-CMAQ model to estimate the number of COPD premature deaths due to ozone exposure in 2014 and 2015 respectively, and the results show that the value was 32.22–141.65 thousand and 55.34–80.28 thousand respectively [
12,
19]. In 2019, Maji estimated that 74.2 thousand people died of long-term exposure to ozone in China in 2016 using ground monitoring station data [
20]. In the same period, Liang estimated the avoidable all-cause mortality from short-term exposure to ozone in 2016, and the results showed that if the DMA8 dropped to CNAAQS Grade I (100 μg/m
3), the premature death of 120 (95% CI: 67–160) thousand people could be avoided [
21]. Theoretically, because air pollution monitoring stations are mainly distributed in city areas and densely populated areas, there is great uncertainty in the estimated value of the sites in the sparsely populated areas such as rural areas. For the chemical transport model, there are some limitations, such as the uncertainty of the input emission list and the coarse resolution of the model, which may lead to too high simulation results. Therefore, future research should focus on combining the advantages of the two methods to make mutual correction between the ground data and the model results. In addition, there is no definite conclusion about the choice of threshold. Madaniyazi et al. chose WHO AQG standard (100 μg/m
3) as threshold [
75], Lin et al. chose 37.6 ppb as threshold [
19], Liu et al. and Maji et al. use 75.2 μg/m
3 and 112 μg/m
3 as threshold [
12,
20], Yao et al. used 0 μg/m
3 as threshold [
30]. In this study, we chose zero as the threshold because studies conducted in China [
15,
18,
98] and North America [
99‐
101] found that a threshold did not exist in the acute effect of short-term O
3 exposure.
For the economic burden, our study found that its spatiotemporal trend is almost the same as that of premature death, but the GDP loss presents different spatial characteristics. We found in northwest Xinjiang, Gan-Ning city belt, Guan Zhong city belt and Central-Liaoning city belt have a considerable loss of GDP, whose economic development lags behind that of BTH, YRD, PRD area. Severe pollution has been caused because the local government has neglected to protect the local environment in pursuit of rapid economic development. The decision-makers of these areas should simultaneously develop the economy considering the protection of environment, so as to achieve the coordinated development of both sides. In addition, uncertainty can also be introduced in estimating economic loss. In our study, ozone related all-cause deaths in China caused economic losses of 387.77 (95% CI: 195.99–904.50) to 594.08 (95% CI: 303.34–1140.65) billion Yuan during 2015–2018, accounting for 0.52 to 0.69% of the total GDP. The study of Xie et al. estimates that by 2030, the economic loss caused by ozone may range from 200 to 230 billion Dollars, accounting for 2.3 to 2.7% of GDP loss in that year [
33]. This estimate is slightly higher than our studies because the outcome considers both mortality and morbidity. Maji et al. estimated that China’s ozone related premature death in 2016 caused an economic burden of 760 million Yuan, while Yao et al. pointed out that the economic loss due to ozone short-term exposure in 2017 was 49.6 billion Yuan [
20,
30]. In addition to the types of health endpoints, another reason for the differences in economic valuation is the different valuation methods. For example, Liang used two valuation methods, VSL and AHC, to estimate the avoidable economic loss due to short-term ozone exposure in 2016, and the result showed that if the ozone concentration reduce to the expected value, the economic loss can be avoided by 36 and 64 billion Yuan respectively [
21].
Moreover, the influence of exposure parameters on the results should not be neglected and should be considered in future research. We conducted a sensitivity analysis and calculated the percentage of the difference between the provinces with and without exposure parameters in the various health impacts, as shown in Table.
S5 and Fig.
S11. Overestimation mainly occurs in Guangdong (− 1242 to − 1500), Jiangsu (− 1564 to − 2315), which indicates that the actual daily exposure of residents tends to be lower due to the introduction of exposure parameters. Underestimation mainly occurs in Henan (1160 to − 1615), Xinjiang (663 to 1453), Gansu (616 to 755), which indicates that the actual daily exposure of residents tends to be higher. We can find that Eastern provinces are overestimated and Western provinces are underestimated, which reflects the exposure differences caused by the differences of living habits and environmental conditions between the East and the West of China (Fig.
S11). Since this error was not considered in previous studies, the daily average concentration of monitoring stations was used to represent the actual daily exposure of residents, which may lead to the bias of the results, especially in some local studies [
37,
75,
102]. Future research should not only consider the concentration of pollutants in the environment, but also refine the actual daily exposure to obtain more unbiased disease burden estimates.
However, there are several uncertainties. Firstly, using single permeability coefficient to simulate indoor exposure in this study may lead to deviation from the actual indoor exposure dose: In fact, there are few studies on permeability of ozone in China, and the existing research is conducted in single city [
103‐
105], and there are not enough nationwide studies to show how these coefficients differ across regions. The data of single study [
80] used in this paper may lead to the bias of indoor exposure dose. More importantly, there is still no effective exposure-response function simultaneous estimate indoor and outdoor exposure of ozone. Indoor-sources ozone exposure has not been genuinely estimated in this study, which is also a problem to be solved in future studies. Second, in this study, we assume that ozone is an independent pollutant. In other words, we do not consider the interaction caused by other pollutants (such as PM
2.5) when estimating the health effects of ozone. In fact, past studies have shown that the negative effects of ozone can be enhanced when multiple pollutants coexist [
106‐
109]. Estimating the health burden caused by ozone separately may overlook this synergistic effect and result in underestimation. Thirdly, due to the unavailability of mortality rate data, we can only distribute the monthly baseline mortality rate evenly to every day after getting the monthly mortality baseline rate at the city level (Table.
S6), which ignored the original temporal trend of incidence rates, leading to bias in the estimation of actual health impact. Previous studies have shown that haze events can cause fluctuations in mortality: light, medium and heavy dust-haze days were associated with increased mortality of 3.4, 6.8 and 10.4% respectively [
110]. Future studies should try to get the daily mortality rates of each city as accurately as possible to get the actual fluctuations to calculate more reliable results. Fourth, although we know that individual exposure has high space-time variation, this study used uniform monitoring station data to represent the exposure level and static population data, which may affect the estimation accuracy of this study. Fifth, as mentioned above, we believe that there is no threshold in the acute exposure reaction curve of ozone, so the minimum ozone concentration is set to zero, but the reality of ground-level ozone falling to zero is almost non-existent. In GBD 2019, the minimum risk exposure level was specified as a uniform distribution between 29.1 and 35.7 ppb (57.1 and 70.1 μg/m3) [
111]. Moreover, Anenberg et al. found that worldwide, anthropogenic emissions accounted for only 37% of ozone attributable asthma related impacts [
112]. This indicates that the economic burden calculated in this study include the ozone concentration below the achievable minimum concentration and that emitted by non-anthropogenic, which has no practical significance for the government’s financial investment. Finally, although the calculation is simplified by using excess risk instead of traditional attributable fraction in Formula
1, the best approximation can be achieved only when the pollutant concentration is relatively low (about 10 μg/m
3). With the relative increase of ozone concentration, the overestimation of the result will gradually increase. For example, in 2015, Beijing, the city with the highest ozone concentration (201.30 μg/m
3), will have the most serious overestimation. According to the all-cause mortality exposure response coefficient
RR = 1.0037 for Beijing, the all-cause premature death will be overestimated by 7.4%.
Although there are some limitations in this study, it is the first time to analyze the spatiotemporal distribution of the health and economic burden caused by short-term exposure to ozone in China, and to make up for the shortcomings of previous studies by using refined methods to make the estimation results more accurate. The results of the study provide policy makers with the changing trend of ozone concentration and burden in China, and provide enlightening information for the formulation of new priority areas for prevention and control. Although the uncertainty affects the estimation accuracy, this study presents a reliable overall temporal trend and spatial hot spots.