Health Risk Assessment of PM2.5-bound Components in Beijing, China during 2013–2015

Received: March 21, 2020
Revised: June 30, 2020
Accepted: July 21, 2020

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

Cite this article:

Zhang, T., Chen, Y. and Xu, X. (2020). Health Risk Assessment of PM_2.5-bound Components in Beijing, China during 2013–2015. Aerosol Air Qual. Res. 20: 1938–1949. https://doi.org/10.4209/aaqr.2020.03.0108

HIGHLIGHTS

• Lifetime cancer risk & noncancer hazard quotients (HQ) estimated in Beijing 2013–2015.
• Lifetime cancer risk (1.9E-4) and HQ (18) were much higher than acceptable levels.
• Fossil fuel combustion and vehicle exhaust are major courses to risks and HQ.
• Seasonal variations in PM_2.5 risks and sources due to more coal combustion in winter.
• Respiratory system was most vulnerable, contributing 82% to HQ.

Keywords: Cancer risk; Non-cancer hazard quotient; PM2.5; Element; Polycyclic aromatic hydrocarbons; Seasonal variation.

INTRODUCTION

Beijing is the capital city, and the political, economic, and cultural center of China. In 2017, the population of Beijing reached 22 million (MBS, 2018) with 5.6 million registered vehicles (MEE, 2018). Owing to rapid economic development and urbanization, Beijing and surrounding regions (i.e., Tianjin and Hebei province) have experienced serious air pollution in recent years, including fine particulate matter (PM_2.5) (Zhang et al., 2016; Chang et al., 2018). Although annual PM_2.5 mass concentrations decreased from 90 µg m^–3 in 2013 to 80 µg m^–3 in 2015 in Beijing, the 2015 level is still two times higher than the Chinese National Ambient Air Quality Standard of 35 µg m^–3 and eight times higher than World Health Organization’s guideline of 10 µg m^–3 (UNEP, 2019).

A number of scientific studies have investigated associations between exposure to high concentrations of PM_2.5 and human health issues, including lung cancer, heart attacks, and premature death (Li et al., 2018; U.S. EPA, 2018). An exposure assessment study in China used the Shape Constrained Health Impact Function to estimate the PM_2.5-related premature deaths during 2013–2015. It was estimated that premature deaths due to long-term exposure to PM_2.5 were 2.19, 1.94, and 1.65 million in 2013, 2014, and 2015, respectively. Over half of these premature deaths were caused by stroke, followed by ischemic heart disease (20.5%), chronic obstructive pulmonary disease (16.8%), and lung cancer (9.5%) (Li et al., 2018). A PM_2.5 health effects study in Beijing estimated that the premature mortality rate due to exposure to PM_2.5 reached 22,000–30,000 per year during 2001–2012 (Zheng et al., 2015).

Assessment of the health risk of ambient PM_2.5 provides valuable information on the major sources and major PM_2.5 components causing adverse health effects, and helps to identify environmental health issues and to set effective air pollution control targets (Hu et al., 2017; Liu et al., 2017). Health risk assessment of PM_2.5 components has been carried out in some Chinese cities in recent years, for example, in the Pearl River Delta region using data collected in 2014 (Zhou et al., 2018). This study used the concentrations of six elements (As, Cr, Ni, Mn, Pb, Si) in PM_2.5 to estimate the cancer risks and hazard quotients (HQ) through the inhalation pathway. The cancer risk was 3.7E-3 and the HQ was 2.1. Both cancer risks and HQ were high (Zhou et al., 2018). In Beijing, risk assessment studies have been limited to short time periods. For example, Wan et al. (2016) used 12 elements in PM_2.5 to estimate cancer risk and HQ in Beijing during spring 2015. Given the large seasonal variability of PM_2.5 mass and component concentrations, a health risk assessment using multiple-year data is warranted.

As such, the current study provides information about long-term cancer risks and HQ associated with airborne PM_2.5 exposure in Beijing during 2013 to 2015. The specific objectives of this study are to 1) estimate lifetime cancer risk and HQ in Beijing using ambient PM_2.5 mass concentrations collected during 2013–2015, 2) identify which elements or sources had major contributions to risk or HQ, 3) identify which target organs are at greatest risk, and 4) investigate seasonal variability of cancer risk and HQ by element, by source, and by target organ. This information will inform health risk managers about which elements in PM_2.5 have the greatest impact on human health, from which sources, and in which seasons.

METHODOLOGY

Study Area and Period

The study area is the city of Beijing (Fig. 1). The study period is from 2013 to 2015, because the proportions of PM_2.5-bound elements and PAHs in total PM_2.5 mass concentration were estimated using data from previous studies in Beijing from 2006 to 2014. After 2015, there have been a number of air pollution control policies implemented in Beijing, such as, eliminating coal-fired boilers to phase out coal consumption, and eliminating 389,000 outdated vehicles (Clean Air Asia, 2016). Therefore, the proportions of elements and PAHs in the previous studies of 2006–2014 may not be representative of the proportions in 2016–2018.

Fig. 1. The 12 monitoring stations in Beijing. Red star: urban stations; black star: suburban stations. (Base map from Google map, locations of the 12 stations from Shanghai Qingyue (2019))

Data Source

Hourly ambient PM_2.5 mass concentrations at 12 monitoring stations (Fig. 1) in Beijing during 2013–2015 were downloaded from the Qing Yue Open Environmental Data Center (Shanghai Qingyue, 2019). Eight of those stations were in urban areas close to the city center, and the other four were in suburban settings. Detailed information for the 12 monitoring stations can be found in Table S1. Proportions of PM_2.5-bound elements and PAHs in total PM_2.5 mass concentrations were obtained from previous studies in Beijing from 2006 to 2014 (see supplemental Tables S2 and S3). 

Daily, Seasonal, and Three-year PM2.5 Mass Concentrations

Daily PM_2.5 concentrations were calculated by averaging hourly PM_2.5 mass concentrations for each of the 12 stations in Beijing, when at least 20 hourly concentrations are available on that day/site during 2013–2015 (MEP and AQSIQ, 2012). City-wide daily PM_2.5 mass concentrations were calculated by averaging daily PM_2.5 mass concentrations from all stations with available daily PM_2.5 mass concentrations. There were 331, 357, and 353 days with daily concentrations available in 2013, 2014, and 2015, respectively. Seasonal and three-year average PM_2.5 mass concentrations were calculated using daily PM_2.5 mass concentrations, with the seasons defined as, spring: March-May; summer: June-August; fall: September-November; winter: December-February.

Cancer Risk and HQ

The PM_2.5 mass and component concentrations from previous studies (2006–2014) in Beijing (Tables S2 and S3) were used to calculate average proportions of each PM_2.5-bound element and PAHs in total PM_2.5 mass on an annual basis and in each of the four seasons. This allowed us to estimate overall and seasonal cancer risk/HQ. The exposure concentrations of each element and PAH in PM_2.5 were estimated using the average proportions of each element (Table S4) and PAH (Table S5) and the observed seasonal or three-year PM_2.5 mass concentrations.

Six PM_2.5-bound elements (As, Cd, Co, Cr, Ni, Pb) and 16 priority PAHs defined by U.S. EPA (2002) were used to estimate the lifetime cancer risk based on data collected during 2013–2015. These six elements and 16 PAHs were selected because they are carcinogenic (U.S. EPA, 2019), and their proportions in PM_2.5 mass concentrations are available from previous studies in Beijing from 2006 to 2014. The cancer risk for the six elements (CR_E) was calculated using Eq. (1) following the U.S. EPA method (U.S. EPA, 2005).

where ECE_i is the exposure concentration of the ith element (µg m^–3), and UR_i is inhalation unit risk (µg m^–3)^–1) for the ith element, as listed in Table S6. The UR for Cr(VI) is available instead of Cr (U.S. EPA, 2019). Therefore, Cr concentrations were used to estimate Cr(VI) concentration which is one seventh (1/7) of Cr concentration as in Perišić et al. (2017).

Cancer risk for the 16 PAHs (CR_P, referred to as risks by total PAHs hereafter) was calculated using Eq. (2) following the U.S. EPA method (U.S. EPA, 1993).

where ECP_j is the exposure concentration of the j^th PAH (µg m^–3), and TEF_j is the toxic equivalency factor for the j^th PAH, as listed in Table S7, where the higher TEF values indicate higher toxicity. UR_BaP is the inhalation unit risk of exposure to BaP at 1.1E-3 (µg m^–3)^–1 (OEHHA, 2019).

The total cancer risk is the summation of the cancer risks for the six PM_2.5-bound elements (CR_E) and the cancer risks for the PM_2.5-bound 16 U.S. EPA priority PAHs (CR_P). According to the U.S. EPA guideline, cancer risks within the range of 1E-4 to 1E-6 indicate an acceptable or tolerable risk for regulatory purposes; cancer risks above 1E-4 suggest high cancer risk and remedial actions are required; and cancer risks below the 1E-6 suggest cancer risks to human health are negligible (U.S. EPA, 2000).

Eleven PM_2.5-bound elements (As, Ba, Cd, Cl, Co, Cr, Mn, Ni, P, Pb, and Se) were used to estimate HQ in Beijing based on data collected during 2013–2015. These elements were selected because they pose significant non-carcinogenic health effects to humans (U.S. EPA, 2019), and their proportions in PM_2.5 mass concentrations are available from previous studies in Beijing from 2006 to 2014. The HQ was calculated using Eq. (3) following the U.S. EPA method (U.S. EPA, 2015).

where RfC_i is the reference concentration (mg m^–3) for the i^th element, as listed in Table S8. The RfC for Cr(VI) is available instead of Cr (U.S. EPA, 2019). Therefore, Cr(VI) concentrations were estimated as one seventh of Cr concentrations as in Perišić et al. (2017). HQ equal to or less than 1 indicates that exposure to these elements has insignificant non-cancer health effects to humans, while HQ greater than 1 suggests exposure to these elements might pose significant non-cancer health effects, and remedial actions are needed (U.S. EPA, 2000).

Risks and HQ by each of the PM_2.5-bound elements and total PAHs were estimated in Beijing during 2013–2015. Similarly, lifetime risks and HQ by season from each of the components were estimated.

Lifetime risks and HQ from each of the seven sources were estimated using the source profiles (Table S9) from the study of Yu et al. (2013). The source profiles contain percentage contributions by each of the 11 elements to each of the seven sources. The seven sources are secondary sulphur, vehicle exhaust, soil dust, road dust, biomass burning, fossil fuel combustion, and metal processing. For example, cancer risk from soil dust is the summation of 100% of cancer risk of Co, 21% of cancer risk of P, and 19% of cancer risk of Se. HQ by target organ was estimated using Table S8. For example, lifetime HQ to respiratory system is the summation of lifetime HQ from all elements involved, i.e., Cl, Co, Cr(VI), Ni, and P.

Assumptions

As in almost all risk assessment studies, lifetime personal exposure levels are not available in this study. Therefore assumptions were made, including 1) three-year average PM_2.5 concentration represents lifetime average exposure concentration; 2) ambient concentrations represent personal exposure concentration; 3) proportions of elements and PAHs in PM_2.5 from previous studies (2006–2014) in Beijing (Tables S4 and S5) represent proportions of elements and PAHs in PM_2.5 in Beijing during 2013–2015; 4) source profiles from a previous study in Beijing (Table S9) represent source profiles in 2013–2015, and 5) independence of effect by the compounds involved, i.e., there are no synergistic or antagonistic chemical interactions (U.S. EPA, 1993).

RESULTS AND DISCUSSION

PM2.5 Mass Concentrations, Lifetime Cancer Risk and HQ

The PM_2.5 mass concentrations decreased slightly from 84 µg m^–3 in 2013 to 81 µg m^–3 in 2015, with a three-year average of 82 µg m^–3 (Fig. 2), much higher than the Chinese National Ambient Air Quality Standard of 35 µg m^–3. The lifetime cancer risk from exposure to PM_2.5-bound elements and PAHs in Beijing during 2013-2015 was 1.9E-4, which is nearly twice as high as the U.S. EPA acceptable level of 1E-4, suggesting the risk is sufficiently large that some sort of remediation is desirable (U.S. EPA, 2000). Similar values of cancer risks have been reported in the nearby city of Baoding (141 km southwest of Beijing), China in 2016 (Liu et al., 2018). The PM_2.5 samples were collected from September 25^th to December 26^th. The lifetime cancer risks for men and women were 1.8E-4 and 1.03E-4, respectively, during the non-heating period (September 25^th to November 14^th), and 2.2E-4 and 1.23E-4, respectively, during the heating period (November 15^th to December 26^th). Thus, the cancer risks in Baoding exceeded the U.S. EPA acceptable level of 1E-4 for both periods and both genders.

Fig. 2. Annual and three-year PM_2.5 mass concentrations in Beijing (average of 12 monitoring stations).

The lifetime HQ from exposure to PM_2.5-bound elements in Beijing during 2013-2015 was 18, which is much higher than the U.S. EPA acceptable level of 1, suggesting that a non-carcinogenic effect is likely to appear (U.S. EPA, 2000). A similarly high HQ value of 11 was reported in Xi’an, China during winter in 2008 and summer in 2009 (Liu et al., 2017). Concentrations of the eight elements (As, Cd, Cr, Cu, Mn, Ni, Pb, and Zn) were used in the study to estimate HQ through inhalation exposure.

Seasonal PM_2.5 Mass Concentrations, and Contributions to Cancer Risk and HQ

Seasonal PM_2.5 mass concentrations, and their contributions to cancer risks and HQ in Beijing during 2013–2015 are shown in Fig. 3 and Table 1. PM_2.5 mass concentrations and cancer risks had similar seasonal variations: i.e., higher in winter (109 µg m^–3, 30% of risk), medium in spring and fall (80 µg m^–3, 25%), and lower in summer (68 µg m^–3, 20%). High PM_2.5 mass concentrations in winter were because of increased local emission due to space heating and a decreased mixing height (Li et al., 2015). HQ showed a different seasonal pattern in comparison with those of PM_2.5 mass concentrations and cancer risk. HQ in winter alone contributed more than half (51%) of lifetime HQ, followed by spring (22%) and fall (19%), with a small contribution (8%) in summer. This is mainly attributable to the higher proportion of Cl in PM_2.5 mass in winter (3.2%) than those in other seasons (0.36%–1.4%) (Table S4), and the relatively high RfC value of Cl (Table S8). Similar results were reported in a health risk assessment study in Baoding, China, from January to December 2015 (Liang et al., 2019). Cancer risks and HQ for children, male adults, and female adults were all higher in the heating period (November 15–March 15) than those in the non-heating period (March 16–November 14).

Fig. 3. (a) PM2.5 mass concentrations, (b) lifetime cancer risk, and (c) HQ by season in Beijing.

By normalizing the seasonal cancer risks with corresponding PM_2.5 mass concentrations, the normalized CR in winter became lower than in the other seasons, while the normalized CR for spring, summer, and fall were similar to one another (Table 1(a)). This indicates that higher PM_2.5 mass concentrations in winter would have increased CR, however there is diminishment in elements and PAH species with high unit risks (Table S6). The net effect is an increased winter CR but to a lesser degree.

The normalized HQs exhibited greater seasonality with a much higher value in winter and much lower value in summer (Table 1(a)), suggesting more enrichment in winter but diminishment in summer in elements with higher reference concentrations. The winter/summer ratio of HQ was 6.6, higher than that of the normalized HQ of 4.5, indicating that the winter-high summer-low pattern of HQ is attributable to both higher winter PM_2.5 mass and enrichment in elements with high reference concentrations (Table S8) in winter.

The ratios of seasonal HQ to summer HQ were much higher than the ratios of seasonal CR (Table 1(b)); this further demonstrates that HQ values are much more sensitive to the seasonal compositions of elements in PM_2.5. For both CR and HQ, the seasonal variability is primarily due to changes in PM_2.5 compositions, i.e., diminishment in elements with high cancer risks but enrichment in elements with high reference concentrations in winter, while changes in PM_2.5 mass played a lesser role. More analysis and discussion on the seasonal variation of CR and HQ are presented in the following sections

Cancer Risk by Element

Fig. 4 and Table 2 depict the individual contribution of six PM_2.5-bound elements and total PAHs to lifetime cancer risk, and in summer and winter in Beijing during 2013–2015. Lifetime risks by PM_2.5 components were, in descending order, As, Cr(VI), total PAHs, Pb, Co, Ni, and Cd. Among these PM_2.5 components, As had a risk of 1.1E-4, being the only element where the cancer risk is above 1E-4. Similar results were reported by a health risk assessment study in Jinan (377 km south of Beijing), China (Du et al., 2019). The measurements of elements in PM_2.5 were conducted from January 2014 to January 2015. The concentrations of five elements (As, Cd, Cr, Ni, and Pb) in PM_2.5 were used to estimate the lifetime cancer risks through the inhalation pathway, and the results showed that the cancer risks of Cr contributed 72% of total cancer risk, followed by As (22%), Ni (3%), Cd (2%), and Pb (1%).

Fig. 4. Lifetime cancer risk by element and in summer and winter. 

Fig. 5 demonstrates proportions of PAHs and each of the six elements in PM_2.5 mass. For all elements, the proportions are similar in spring and fall. Cr(VI) had significantly higher proportion in summer than in winter (winter/summer ratio of 0.1, Table S10), which had the highest unit risk among all components considered (Fig. 5). All other components had higher proportions in winter (winter/summer ratios of 1.2–4, Table S10). Overall, the winter profile is diminished in elements with higher unit risks, as evidenced by a lower normalized CR than in other seasons (Table 1(a)).

Fig. 5. Seasonal proportions of the six elements and total PAHs in total PM2.5 mass (#s in parentheses are unit risks).

Contributions to cancer risk by PM_2.5-bound elements and total PAHs were overall similar in spring and fall (Fig. S1), but different between summer and winter (Fig. 4). The seasonal variability in contributions of PM_2.5-bound elements and total PAHs are consistent with changes in the proportions of the elements to PM_2.5 mass (Fig. 5). Contributions of Cr(VI) were much lower in winter (6%) than in summer (44%). Higher contributions in winter were observed for As (72% in winter vs. 43% in summer), PAHs (15% vs. 5%), Pb (8% vs. 5%), and Co (5% vs. 1%). Contributions of Ni and Cd were similar between summer and winter

Cancer Risk by Source

Fig. 6 and Table 3 show the contributions by each of the seven PM_2.5 emission sources to lifetime, summer, and winter cancer risks from exposure to PM_2.5-bound elements and PAHs in Beijing during 2013–2015. Among the seven sources considered, road dust contributed the highest lifetime cancer risk (39%). This is because nearly 40% of As and 70% of Cr(VI) originated from road dust (Table S9) and the unit risks from As and Cr(VI) were high, 4.3E-3 per (µg m^–3) and 1.2E-2 per (µg m^–3), respectively (Table S6). Fossil fuel combustion contributed the second-highest cancer risk (24%), followed by vehicle exhaust (21%), because 35% of As originated from fossil fuel combustions and 20% of As was from vehicle exhaust (Table S9). The remaining four sources (soil dust, secondary sulphur, metal processing, and biomass burning) each contributed no more than 10% of cancer risks. Somewhat similar contributions to cancer risks by source were reported in the study in Jinan, China in 2014 (Du et al., 2019). The result showed that vehicle exhaust contributed 55% of total cancer risks, followed by coal combustion (27%), the smelting industry (11%), and the soil dust (7%).

Fig. 6. Lifetime cancer risks by source and in summer and winter.

The contributions of emission sources to cancer risks are somewhat similar in the four seasons in terms of rank order of contributions (Fig. S2). However, there is a significant summer (49%) and low contributions in winter (33%) because of higher proportion of Cr(VI) (0.008% in summer vs. 0.001% in winter, Table S4). Contribution of metal processing was high in summer (10%) and low in winter (1%), because of higher proportion of Cr(VI) (0.008% in summer vs. 0.001% in winter, Table S4). Contributions of biomass burning were high in summer (4%) and low in winter (3%). This is not unexpected because the North China Plain experienced more agricultural residual burning emissions in harvest seasons (Yin et al., 2019). Winter-high and summer-low contributions were observed for fossil fuel combustion (26% vs. 16%), vehicle exhaust (28% vs. 16%), soil dust (5.1% vs. 1.2%), and secondary sulphur (4.6% vs 3.1%). For fossil fuel combustion and vehicle exhaust, this seasonal pattern was attributable to higher proportion of As in winter (0.031% vs. 0.023, Table S4). For soil dust, the seasonal pattern was due to higher proportions of Co in winter (0.001% vs. 2.9E-6%, Table S4). Beijing experienced higher relative humidity (70%) in summer than that in winter (45%) (Time and Date, 2020), which increased soil particle cohesion (Csavina et al., 2019) resulting in less soil dust.

HQ by Element

Fig. 7 and Table 4 illustrate the contributions of each of the 11 PM_2.5-bound elements to lifetime HQ, and in summer and winter in Beijing during 2013–2015. The breakdown of lifetime HQ by PM_2.5-bound elements were, in descending order, Cl, As, Pb, P, Cd, Mn, Ni, Ba, Cr(VI), Co, and Se. Co and Se are not shown in Fig. 7, because the contributions were less than 0.1% each. Among the 11 elements, Cl (HQ = 14) and As (1.8) were the only two elements where the HQ was greater than 1. The contribution of Cl to HQ was 76%. In comparison, the health risk assessment study in Jinan, China, in 2014 used five elements (As, Cd, Cr, Mn, and Ni) in PM_2.5 to estimate HQ via the inhalation pathway (Du et al., 2019). Results showed that As was the largest contributor to HQ (38%), followed by Mn (35%), Ni (13%), Cr (11%), and Cd (2%).

Fig. 7. Lifetime non-cancer HQ by PM_2.5-bound element and in summer and winter.

Fig. 8 demonstrates proportions of each of the 11 elements in PM_2.5 mass by season. Ba and P had the same proportions in the four seasons. For the other nine elements, the proportions were overall similar in spring and fall. Cr (VI) had significantly higher proportions in summer than in winter (winter/summer ratio of 0.1, Table S11), which had medium-high reference concentrations among all elements considered (Fig. 8). The other eight elements had lower proportions in summer (winter/summer ratios of 1.2–9, Table S11). In comparison with the transition seasons of spring and fall, the winter profile was greatly enriched while the summer profile was greatly diminished in elements with higher reference concentrations (Fig. 8), evident by the normalized HQ being much higher in winter and lower in summer (0.27 per µg m^–3 in winter vs. 0.06 per µg m^–3 in summer, Table 1(a)). The wider range of winter/summer ratios in HQ profiles than in CR profiles (0.1–9 vs 0.1–4, Tables S10 and S11) suggests more distinct seasonality.

Fig. 8. Seasonal proportions of 11 elements in total PM_2.5 mass (#s in parentheses are reference concentrations)

HQ in spring and fall showed similar contributions by the 11 PM_2.5-bound elements (Fig. S3). The seasonality was more pronounced between summer and winter (Fig. 7). Contributions of Cl were high in winter (81%) and low in summer (37%). Contributions of all other elements were high in summer and low in winter, inconsistent with lower proportions of those elements in summer (Fig. 8). This is because HQ values of Cl reduced by 14 times in summer (1.6 in summer vs. 23 in winter), leading to increased contributions in summer of As (24% in summer vs. 7.9% in winter), Pb (14% vs. 5.1%), P (15% vs. 3.7%), Mn (2.3% vs. 0.8%), Cd (2.1% vs. 1.0%), Ni (0.45% vs. 0.19%), Ba (2.0% vs. 0.47%), and Cr(VI) (1.3% vs. 0.04%) 

HQ by Source

The contributions to lifetime HQ by source, and in summer and winter in Beijing during 2013-2015 are shown in Fig. 9 and Table 5. Among the seven sources considered, fossil fuel combustion and vehicle exhaust were the top two sources contributing to lifetime HQ at 67% and 10%, respectively, and the remaining five sources (road dust, metal processing, biomass burning, secondary sulphur, and soil dust) combined contributed 23% of HQ. Somewhat similar results were reported by the health risk assessment study in Jinan, China, in 2014, where coal combustion contributed 34% of HQ, followed by the smelting industry (25%), vehicle exhaust (22%), and soil dust (19%) (Du et al., 2019).

Fig. 9. Lifetime non-cancer HQ by source and in summer and winter.

Contributions to HQ by source were similar in spring and fall (Fig. S4), but different between summer and winter (Fig. 9). Fossil fuel combustion had higher contributions in winter (69%) and lower contributions in summer (46%), due to higher proportions of Cl (3.2% vs. 0.36%, Table S4). Higher contributions of vehicle exhaust (17% in summer vs. 10% in winter), road dust (17% vs. 5.5%), secondary sulphur (7.2% vs. 4%), and soil dust (3.4% vs. 0.8%) were observed in summer, in spite of lower HQ values in summer (Table S12). This is because the proportion of Cl reduced greatly from winter to summer (3.2% vs. 0.36%, Table S4), as discussed in Section HQ by Element. Lower contributions were observed in summer for metal processing due to lower proportions of Cl (0.36% in summer vs. 3.2% in winter, Table S4). Contributions of biomass burning were high in summer and low in winter, as expected.

HQ by Target Organ

Fig. 10 and Table 6 show the contributions to lifetime, summer, and winter HQ by target organ in Beijing during 2013–2015. Among the six target organs considered, respiration was the most vulnerable system, contributing 82% of lifetime HQ. This is because the respiratory system was affected by five elements (Cl, Co, Cr(VI), Ni, and P), and Cl alone contributed 76% of lifetime HQ (Fig. 7), followed by reproductive (10%), and nervous system (6%), and the remaining three target organs (renal, fetus, and alimentary) together contributed 2% of HQ. Alimentary system is not shown in Fig. 10, because the contributions were less than 0.001%.

Fig. 10. Lifetime non-cancer HQ by target organ and in summer and winter.

Among the four seasons, the contributions by organ were similar in the transition seasons of spring and fall (Fig. S5), but dissimilar in summer and winter (Fig. 10). The contribution of respiratory system was high in winter (85%) and low in summer (54%). This is because Cl was the largest contributor to HQ (Fig. 7) and the proportions of Cl were much higher in winter than in summer (3.2% vs. 0.36%, Table S4). The HQ of the nervous system depends on Pb and Mn. For the reproductive, renal, fetus, and alimentary system, the HQ values depend on As, Mn, Cd, Ba, and Se, respectively. Among the six elements, five had higher proportions in winter (As: 0.031% in winter vs. 0.023% in summer; Mn: 0.064% vs. 0.044%; Cd: 0.003% vs. 0.002%; and Se: 0.05% vs. 0.007%; Pb: 0.204% vs. 0.138%, Table S4). Although Ba had the same proportions in the four seasons (Table S4), PM_2.5 mass concentration was higher in winter (Fig. 3), leading to higher Ba concentration. However, the contribution by each of these five organs were lower in winter (Fig. 10). This is because the proportion of Cl reduced greatly from winter to summer (3.2% vs. 0.36%, Table S4), leading to increased contributions of other organs in summer, as discussed in Section HQ by Element

Uncertainties

The health risk assessment methods developed by the US EPA were employed in this study for the estimation of cancer risks and non-cancer HQ from PM_2.5-bound elements and PAHs in Beijing. The results reveal seasonality and identify sources with large contributions. However, there are several possibilities for uncertainty.

Proportions of PM_2.5-bound elements and PAHs estimated from prior locally-conducted studies (2006–2014) may not represent the PM_2.5 compositions in the current study (2013–2015) very well. This is because proportions of PM_2.5-bound elements and PAHs in prior studies were averaged over the relatively long period of 2006–2014, during which the study region experienced rapid industrialization and economic growth.

The uncertainty in PM_2.5 mass determination is considered small (< 5%, e.g., Zheng et al., 2005). By using estimated proportions of PM_2.5 compositions from previous studies (2006–2014), the cancer risks and HQ results in this study are likely biased high. This is because, by switching to cleaner fuels and enforcing emission controls in recent years (UNEP, 2019), the proportions of fossil fuel combustion related-elements (i.e., As and Cl) in PM_2.5 mass should be lower than before. These two elements were the largest contributors to CR (60%) and HQ (76%), respectively.

The risks and HQ results in this study were calculated based on the 11 PM_2.5-bound elements and 16 PAHs. In reality, exposures are not limited to these species. If considering other toxic elements/PAHs, such as mercury and benzo(e)pyrene, the health risks of toxic components in PM_2.5 will increase.

Greater inherent uncertainty accrues by assigning source-based risk/HQ estimates based on metals composition in the source profiles from a source apportionment study (Yu et al., 2013). Our study focuses on city-wide PM_2.5 concentrations in Beijing and the associated health risks. However, there exists intra-city variability in PM_2.5 mass and component concentrations and, therefore, in risk levels. A study of PM_2.5 spatial and temporal variability during 2013–2018 in Beijing reported that the 6-year PM_2.5 mass concentrations varied from 59 to 77 µg m^–3 among the 12 monitoring stations (Xu and Zhang, 2020). The proportions of PM_2.5-bound elements in total PM_2.5 mass also differed significantly between urban and suburban stations, especially for As and Cr(VI), which are the major contributors to cancer risks (Chen, 2017)

CONCLUSIONS

Lifetime cancer risks and HQ due to inhalation exposure to elements and PAHs in PM_2.5 were estimated in Beijing, China, based on data collected during 2013–2015. The three-year PM_2.5 mass concentration was 82 µg m^–3, much higher than the Chinese National Ambient Air Quality Standard of 35 µg m^–3.

During 2013–2015, the lifetime cancer risk in Beijing from exposure to ambient PM_2.5-bound elements and ambient PM_2.5-bound PAHs was 1.9E-4, nearly twice the U.S. EPA acceptable level of 1E-4; while the lifetime HQ from exposure to ambient PM_2.5-bound elements was 18, much higher than the U.S. EPA acceptable level of 1. Among the six target organs considered, the respiratory system was the most vulnerable, contributing 82% to HQ. Fossil fuel combustion (risk: 24%, HQ: 67%), road dust (risk: 39%, HQ: 7%) and vehicle exhaust (risk: 21%, HQ: 10%) were the top three sources. Consequently, element As from coal combustion and road dust and Cr(VI) from road dust are the largest contributors to cancer risk (totaling 78%), while Cl from coal combustion and As accounted for 86% of HQ.

Among the four seasons, PM_2.5 mass concentrations were highest in winter (109 µg m^–3) and lowest in summer (68 µg m^–3). Winter also accounted for the largest share of total lifetime cancer risk (30%) and total HQ (51%), with less contributions in summer (risk: 20%, HQ: 8%). Contributions of cancer risks or HQ by PM_2.5-bound elements or by source were similar in spring and fall but dissimilar in winter and summer primary. The seasonal variability is primarily driven by changes in PM_2.5 compositions, especially As and Cl which are mainly from coal combustion and less coal was used in summer.

One of the limitations of this study is the use of proportions of elements and PAHs in PM_2.5 mass from the literature to estimate health risks due to exposure to ambient PM_2.5. Long-term monitoring of PM_2.5 components should be conducted at government stations in all major Chinese cities, and the data should be made available. This would allow the evaluation of health benefits of emission control and changes in energy sourcing, and facilitate investigations of the spatial distribution of source impacts and risk levels throughout the city.

This study identifies major PM_2.5 sources and PM_2.5-bound elements that have the greatest impact on human health in Beijing, as well as their seasonality. Our findings may help develop mitigation measures in the region. Since 2016, coal combustion and industrial emission have been largely eliminated within the capital. However, those two types of sources still emit a large quantity of PM_2.5 in regions surrounding the city. An analysis of fall 2016 field samples collected in Beijing indicated that secondary aerosols, dust, vehicle, and coal combustion were the major sources of PM (Zhang et al., 2018). In order to reduce the health burden on Beijing residences due to inhalation exposure to ambient PM_2.5, the government should take measures to lower PM_2.5 mass concentrations. Particularly, emissions from road dust, fossil fuel combustion, and vehicle exhaust should be reduced significantly because they contributed the most to cancer risks and HQ. Control measures should be taken to reduce As and Cl emissions released to the atmosphere. This is because As and Cl ranked number one in cancer risk and HQ, respectively, during the study period, and resulted in cancer risk or HQ values greater than the U.S. EPA’s acceptable levels. Residences of Beijing are encouraged to wear PM_2.5 filtration face masks especially in winter to reduce inhalation exposure. There is a wide range of face masks on the market, and only some of these are effective at filtering the PM_2.5 size fraction and thus having a notable effect on the CR and HQ risks estimated in this study. A field test of nine types of face masks indicated that the filtration efficiency of PM_2.5 ranged from 14–96%, with a median value of 48% (Pacitto et al., 2019). People with respiratory diseases should be cautious because the respiratory system was the most vulnerable.

ACKNOWLEDGMENTS

This work was funded by Ontario Ministry of Economic Development, Job Creation and Trade (Canada), and the Natural Sciences and Engineering Research Council of Canada. The authors would like to thank Dr. Don Dourne, Ms. Lisa Salfi, Mr. Saman Kazemi, and Ms. Xin Liu at University of Windsor for their assistance.

CONFLICTS OF INTEREST

The authors declare no conflict of interest. The founding sponsors had no role in the design of the study, in the collection, analyses, or interpretation of data, in the writing of the manuscript, or in the decision to publish the results. 

Aerosol Air Qual. Res. 20 :1938 -1949 . https://doi.org/10.4209/aaqr.2020.03.0108