Trends in ambient air pollution levels and PM2.5 chemical compositions in four Chinese cities from 1995 to 2017
Review Article on Children's Respiratory Health and Air Quality

Trends in ambient air pollution levels and PM2.5 chemical compositions in four Chinese cities from 1995 to 2017

Zixuan Yin1, Xiaofeng Huang1, Lingyan He1, Suzhen Cao2, Junfeng Jim Zhang3,4,5

1Key Laboratory for Urban Habitat Environmental Science and Technology, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China; 2School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China; 3Nicholas School of Environment & Duke Global Health Institute, Duke University, Durham, USA; 4Duke Kunshan University, Kunshan 215316, China; 5Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, China

Contributions: (I) Conception and design: L He, JJ Zhang; (II) Administrative support: None; (III) Provision of study materials or patients: None; (IV) Collection and assembly of data: Z Yin; (V) Data analysis and interpretation: Z Yin, X Huang; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

Correspondence to: Lingyan He. Key Laboratory for Urban Habitat Environmental Science and Technology, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China. Email:

Abstract: An in-depth analysis of the specific evolution of air pollution in a given city can provide a better understanding of the chronic effects of air pollution on human health. In this study, we reported trends in ambient concentrations of particulate matter (PM) and gaseous pollutants [sulfur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3)] from 1995 to 2017 and PM2.5 composition for the period of 2000–2017 in Guangzhou, Wuhan, Chongqing, and Lanzhou. We provided socio-economic indicators to help explain the pollution trends. SO2 and PM (including PM10 and PM2.5) concentrations showed a downward trend in recent years with the most notable reduction in SO2 in Chongqing and PM2.5 in Guangzhou. There was an overall flat trend for NO2, while O3 showed an upward trend in recent years except in Lanzhou. The majority of PM2.5 mass was SO42− (6.0–30 µg/m3) and organic carbon (6.0–38 µg/m3), followed by NO3 (2.0–12 µg/m3), elemental carbon (2.1–12 µg/m3), NH4+ (1.0–10 µg/m3), K+ (0.2–2.0 µg/m3), and Cl (0.2–1.9 µg/m3). Except for secondary inorganic aerosols in Wuhan, annual average concentrations of all PM2.5 constituents showed a declining trend after 2013, corresponding to the trend of PM2.5. The secondary sources in PM2.5 were found to be most prominent in Wuhan, while the most abundant EC and Cl in Lanzhou was attributed to the use of coal. Despite temporal and spatial variabilities across the four cities, coal combustion, traffic emissions, and secondary pollution have been the major sources of PM2.5 pollution. These trends in ambient air pollution levels and PM2.5 composition may help understand changes in health outcomes measured at different times within the time period of 1995–2017 in the four cities.

Keywords: Air pollution; long-term variation; PM2.5; chemical composition; source

Submitted Nov 18, 2019. Accepted for publication Apr 10, 2020.

doi: 10.21037/jtd-19-crh-aq-004


The associations have been well established between ambient air pollutants, such as sulfur dioxide (SO2), nitrogen oxides (NOx), aerosol particulate matter (PM), ozone (O3), and human health (1-4). With rapid economic growth, China has suffered from substantial air pollution, resulting in many studies evaluating the impacts of air pollution on human health (5-8). For example, exposure to NO2 or SO2 has been associated with bronchitis, asthma, and emphysema, all of which were more pronounced in children and asthmatic patients (9). Numerous studies have reported that PM2.5 and its specific chemical constituents were linked to the incidence of respiratory diseases and mortality as well as lung function (10-12).

In the period of 1993–1996, a cross-sectional study of children’s respiratory health in relation to ambient air pollution was conducted based on a gradient in pollutant concentrations across the four Chinese cities of Lanzhou (LZ), Wuhan (WH), Chongqing (CQ), and Guangzhou (GZ) (13-17). The study found that higher air pollution levels were significantly associated with a greater risk for developing symptoms, respiratory disease, and reduced lung function in children. Parents had a greater risk of respiratory diseases. More than 20 years later, with significant changes in many aspects of the society and the population, it is important to understand the extent to which air pollution changes contributed to changes in respiratory health in children in these cities.

In general, heavy air pollution events were highly concentrated in four regions: North China Plain, Yangtze River Delta (YRD), Pearl River Delta (PRD), and Sichuan Basin (18,19). Three of the four cities (WH, GZ, and CQ), located in YRD and PRD, have often been the sites for studying various characteristics of air pollution (20-24). Taking PM pollution as an example, improvement in the PRD region has been substantial in the past decade (making O3 often become the primary pollutant in recent years) (25), while PM2.5 remained the primary pollutant in the YRD region and the Sichuan Basin (26,27). Many studies have also been launched in LZ because of its unique meteorological and geographical conditions (near the desert with four distinct seasons) (28,29). The published reports provided valuable information to understand longitudinal changes in ambient air quality in the four cities.

In the present review, based on the background information of socio-economic development, we aim to systematically examine the changes in air pollution levels and PM2.5 chemical compositions from the 1990s to 2017. Data for air pollutants (PM2.5, PM10, SO2, NO2, and O3) in the four cities were collected from 1995 to 2017 to study the evolution of the air pollution in each city. In addition, spanning more than a decade we analyzed data on the chemical compositions of PM2.5 to identify the temporal and spatial changes in the source apportionments of PM2.5. We anticipate that the findings of this review can provide insights to help understand potential changes in health outcomes attributable to changes in air quality from the time of the original health study to the time of the current health study in the same cities. We also expect that the findings can provide historical perspectives on air quality evolutions to inform new control policies.

Data and methods

Study site description

Based on the studies conducted more than 20 years ago, our current analysis included four Chinese cities of LZ, WH, CQ, and GZ (see Figure 1). Located in the northeastern side of the Qinghai-Tibet Plateau, LZ is situated in a semi-enclosed Yellow River valley basin that narrows in the north and south and extends in the east and west direction. LZ is characterized by windy and arid springs, which is a high season of sand and dust weather, where the climate has clear vertical variation spectrum and transitional characteristics (30-32). WH is geographically situated at the confluence of the Yangtze and Han Rivers and lies in central China, where the north subtropical monsoon climate offers sufficient light and heat and abundant rainfall (33). Moreover, WH is the core city of the Yangtze River Economic Belt, which has developed as an important industrial base and comprehensive transportation hub in China. CQ is characterized as a mountainous city located in the southwestern part of China and the upper reaches of the Yangtze River. With the annual humidity upwards of 70%–80%, CQ is nicknamed the City of Fog (34). As the core city of the Pearl River Delta metropolitan area, GZ is located in the south-central part of Guangdong Province, which is the largest city in South China. GZ belongs to the subtropical monsoon climate zone with an average annual temperature of 20–22 °C.

Figure 1 Map showing the four cities included in this study, including Lanzhou (LZ), Wuhan (WH), Chongqing (CQ), and Guangzhou (GZ).

Data collection

Data on socioeconomic indicators

It is known that air quality is generally associated with economic development stages. To help understand the long-term trend of ambient air pollution, we collected auxiliary data pertaining to the socioeconomic indicators from the Statistical Bulletin on National Economic and Social Development (35-38) in four cities. Annual values of four indicators between 1995 to 2017 included Gross Domestic Product (GDP), resident population, gross industrial output, and domestic car ownership. Measurement units for the indicator values were 100 billion yuan for GDP and gross industrial output, million people for the resident population, and ten thousand vehicles for domestic car ownership.

Data on air pollutants

The official data of air pollutants were annually averaged and extracted from the Report on the State of Environment (25,39-41) for the four cities during 1995 and 2017. Although we collected a significant amount of data, reports documenting annual concentrations of SO2 and NO2 in 1997 and 1998 were not available in WH and GZ (data was missing for CQ in 1997), while data from 1997 to 2001 were not available in LZ. Based on the Chinese Ambient Air Quality Standards formulated in 1996 (GB3095-1996) (42), the state requirement to monitor PM10 data began in 2000, replacing total suspended particulate (TSP). Thus, the PM10 data were first added into the report from 2000 in CQ, and other three cities began keeping records in 2001. Similarly, the PM2.5 monitoring data were first added to the reports in 2012 based on the Chinese Ambient Air Quality Standards revised in 2012 (GB3095-2012) (43). We chose the daily averaged values in maximum 8-hour O3 concentrations from 2014 on the website (44) where the data were collected from China National Environmental Monitoring Centre, due to the inconsistencies in the reports (such as the different year when data were first added and different type of monitoring O3 including daily averaged in maximum 8-hour and one-hour averaged).

Data sources of chemical components and source apportionments of PM2.5

We reviewed articles regarding chemical composition and source apportionment of PM2.5 to summarize spatial and temporal evolution of source emissions in the four cities. We integrated the absolute values and relative proportions of chemical compositions from PM2.5 across different years (from 2000), including major water-soluble ions [sulfate (SO42−), nitrate (NO3), ammonium (NH4+), potassium (K+), and chloride (Cl)], carbonaceous components [elemental carbon (EC), organic carbon (OC)], main toxic and source-characteristic metals [zinc (Zn), manganese (Mn), lead (Pb), copper (Cu), and chromium (Cr)] and others (relative proportion not shown). All relevant studies discussing individual cities are summarized in Table 1. Strict screening throughout the entire reviewed processing for considering the variable methods of data presentation in each document was reflected in the selection of long-term research data for one subject group in a given city. We found that the data for EC and OC were not available before 2013 in LZ based on the above screening principles. Additionally, normalization methods were used to eliminate gaps between the data with a wide range of sources. The model equation can be written as follows:

y % ij = k=1 n (x/P M 2.5 ) ijk /n[1]

Table 1
Table 1 Published studies reporting chemical compositions of PM2.5 in the four cities during 2000 and 2017
Full table

where y%ij is the normalized proportion of one component in PM2.5 of city j in year i; x is the absolute concentrations of component, while n represents the article counts of city j in year i.

To better describe the local pollution characteristics during the examined period, we also reviewed the annual environmental protection regulations and specific implementation methods from the State and Urban Report on the State of Environment in the Environmental Protection Bureau’s official website (25,39-41).

An overview of social and economic development in four cities

Since entering into the 21st century, China has experienced rapid urbanization and an exponential economic growth (77). Based on the available accounting, the four cities presented an obvious gap in the urban development for diverse socioeconomic indicators summarized in Table 2.

Table 2
Table 2 Comparison of social and economic development for four cities between 1995 and 2017
Full table

By 2017, GZ was recognized as one of the first-tier cities with the largest regional GDP (2,150 billion yuan) and gross industrial output (2,269 billion yuan) compared to other cities. Even in 1996, the number of domestic vehicles in GZ reached 871 thousand vehicles, resulting in the lower growth rate compared to other cities. The resident population has increased by 2.51 million people, and the growth rate since 1995 was only second to WH (where the growth rate was up by 53.4%, from 7.10–10.89 million people). The available data suggest that WH experienced very significant development owing to the highest growth rates of GDP by 21 times and resident population growth by 53.4%. Although GZ and CQ were growing at the same rate in GDP (a multiple of 16) from 1995 to 2017, the development strength of CQ ranked number 5 among all large Chinese cities, reflected in approximately a 9.5% increase in GDP growth rate in 2017 compared to 2016 (78), reaching almost 2 trillion yuan, significantly more than GDP growth rate observed for GZ. In contrast, the slowest development was observed for LZ which had the lowest values for all indicators in 2017 compared to the Yangtze River Delta and PRD cities (40).

Long-term variations in major air pollutants

Using available research data on the effects of air pollution on human respiratory health across 20 years (79,80), we analyzed the long-term trends of air pollutants including SO2, NO2, PM10 [1995–2017], PM2.5 and PM2.5/PM10 [2012–2017] and O3 [2014-2017]. The results are summarized in Figure 2.

Figure 2 Temporal variations in five major air pollutants in four cities: (A) SO2, (B) NO2, (D) PM10 for 1995–2017, (C) O3, (E) PM2.5, (F) PM2.5/PM10 for 2012–2017. The black dotted line indicates the second-level concentration standards of pollutants according to the government GB3095-2012 (43) standard. SO2, sulfur; O3, ozone; PM, particulate matter.


Data presented in Figure 2A indicate a significant downward trend for SO2 annual concentrations among the four cities from 1995 to 2017. In 2017, SO2 levels in all the cities dipped below 20 µg/m3, which were approximately one fourth of the values reported in the late 1990s. The SO2 levels in CQ showed the greatest improvement over the years (81), with a 96.4% decrease from 338 µg/m3 in 1995 to 12 µg/m3 in 2017. A similar change was observed in LZ, where the declining rate of SO2 was 80.4% (from 102 µg/m3 in 1995 to 20 µg/m3 in 2017). The trends in SO2 levels were drastically different for GZ and WH which showed gradual rise prior to 2004 and 2008, respectively. Then we saw the values in all four cities descending below the second-level concentrations (60 µg/m3) after 2008. It was related to the rigorous investigation of reducing pollutant emissions in the Eleventh Five-Year Plan (25,39-41). Despite air quality standards revision in 2012, SO2 was still considered as one of the six major pollutants, resulting in sustained efforts put into monitoring of SO2 performed across the country (43). The type of pollution has shifted from soot-pollution (PM10 associated with SO2) to single type of PM (PM2.5 and PM10 pollution) in some cities (e.g., the primary pollutant in LZ was PM10 and PM2.5, while in CQ and WH was PM2.5), which resulted from a series of measures to reduce air pollution, such as the implementation of coal-to-gas projects and clean coal-fired technologies (82).


Based on the data in Figure 2B, the NO2 levels have not really changed between 1995 and 2017, showing a relatively flat trend compared with SO2. Given the NO2 concentration values from 1995, the reductions of 91, 23, and 47 µg/m3 were seen in GZ, CQ and LZ, respectively, while there was a rise of 7 µg/m3 in WH. However, in recent years, the level of NO2 pollution has far exceeded the second-level concentration (standard) after 2014 in all four cities. The main anthropogenic source of nitrogen oxides in cities is the burning of fossil fuels, two-thirds of which were emitted from mobile sources such as motor vehicles, and one-third from fixed sources such as factories and power plants (83). The available data indicate that the popularity of clean fuels has increased over the years, and exhaust emissions of motor vehicles have been continuously reduced (84). Nevertheless, the rapid urbanization has led to a sustained increase in the number of motor vehicles, dramatically increasing the emission of NO2 to some extent (49,64). The evolution of NO2 pollution and factors associated with NO2 emissions remain complicated.


Ozone, with annual mean concentrations between 64 to 102 µg/m3 now, has become the main risk restricting the optimization of urban air quality after PM2.5 level declined in many cities in recent years. Based on the result in Figure 2C, the daily average in maximum 8-hour O3 concentrations showed upward trend since 2015 in GZ, CQ, and LZ. Especially, LZ has experienced a remarkable increase leading to the highest values (101.3 µg/m3) in 2017. It is tangible that volatile organic compounds (VOCs) and NOx provide important precursors for ozone formation (33) largely deriving from process of petroleum refining and vehicle exhaust emissions (85). The rising trend of ozone was also highly consistent with the rise of NO2 (Figure 2B) in the same period, which have been reported in previous studies (86,87). In general, longer daylight hours and stronger solar radiation contribute to ozone levels (22). The PRD region has subtropical climate that favors ozone formation when precursor pollutants are present. This made O3 pollution receiving particular attention in GZ and Shenzhen (88). Although O3 concentration in WH appeared to be on a decreasing trend, it was in a high concentration range (between 80 and 100 µg/m3).


A clear reduction in PM10 levels has been found between 1995 and 2017 in the four cities (see Figure 2D). Compared to 1995, the levels of PM10 in 2017 were 78.2%, 60.7%, 59.3%, and 33.8% lower in GZ, CQ, LZ, and WH, respectively. However, the pollution level in 2017 was still higher than the second-level concentration (70 µg/m3) in CQ, LZ, and WH, while the value in GZ dropped below the standard for the first time in 2014. These reductions are likely a reflection of the active rectification of PM10 carried out at the nationwide level which has achieved good results (44). The exception occurred in 2013, when the concentration of PM10 was significantly increased in all four cities corresponding to the worst smog in China that occurred the same year, which spread to 25 provinces and affected more than 100 different cities (44). Interestingly, LZ was heavily polluted with PM10, which was mainly from the natural and meteorological conditions (89-91). Additionally, LZ suffered from a very dusty weather all year with frequent dust storms in the city resulting in high PM10 concentrations (92). In general, the technological transformation, tightening of environmental management policies and increased funds (25,39-41) for controlling dust and coal emission were efficiently utilized in all four cities.


Monitoring of PM2.5 levels began in 2012 and showed very comparable trends to PM10 pollution. We also calculated the ratio of PM2.5/PM10 that represents the composition of particulate pollution. The larger the ratio, the higher the mass concentration of fine particles (respirable particles) in total inhalable particles (all particles with an aerodynamic diameter ≤10 µm). For the same inhaled mass of PM10, a higher PM2.5/PM10 ratio means that more fine particles can reach and deposit in the deep lung and cause more health damages (93). Specifically, there was a clear downward trend in PM2.5 levels from 2013 in GZ, CQ and WH, with decreases of 18 µg/m3, 25 µg/m3, and 42 µg/m3 respectively (concentrations dropped 18 µg/m3 since 2012 in LZ). Unlike with PM10, the most serious pollution with PM2.5 was observed in WH. Data suggest that the transport of local air masses from the northeast of WH may have contributed the most to PM2.5 pollution, which originated from the cluster of steel plants located in the northeast region of WH (94). As shown in Figure 2F, we observed continuously decreasing trends of PM2.5/PM10 ratio from 2012 in both GZ and WH, while LZ had the lowest value because of serious PM10 pollution (shown in Figure 2D). Although the pollution level was overall reduced, the other three cities did not meet the second-level standard (35 µg/m3) formulated in GB3095-2012 (43), while GZ has reached the value of 35 µg/m3 in 2017. The strict prevention and control during the multi-sport Asian Games played an important role, leading to reductions in PM levels in the southern China compared to other regions of the country (95).

Spatiotemporal variation of chemical composition and sources of PM2.5 in four cities during 2000 and 2017

Based on the available literature, the chemical characteristics of PM2.5 in China are considered to be a mixture of organic and inorganic matter including water-soluble ions, elemental carbon, crustal material, and hydrocarbons (63,96-98), mainly originating from meteorological evolutions and potential human activities, such as transportation, household activities, vehicular movement and industrial sector (99). Due to the regional economic development, changes in industrial and energy structures, and an increasing number of vehicles, the composition ratios of PM2.5 vary with location and time (100). Based on the policy—Air Pollution Prevention and Control Action Plan, introduced by the Chinese government in 2013 (101), we compiled the available data representing the average PM2.5 concentrations and the relative composition of PM2.5 during two periods (2000–2013 and 2014–2017) in the four cities (Figures 3 and 4).

Figure 3 Spatiotemporal variation of mass fractions in major chemical composition of PM2.5 in the four cities prior to and after 2013. Digital label for every sector indicates the corresponding component proportion, and the size of each fan corresponds to the absolute concentration of PM2.5. PM, particulate matter.
Figure 4 Variations in the absolute concentrations (μg/m3) of examined PM2.5 and seven components before and after 2013 in LZ, WH, CQ, and GZ. Solid column represents the first period [20102013] while the dotted line column indicates the second period [20142017] in each component across four cities. PM, particulate matter; LZ, Lanzhou; WH, Wuhan; CQ, Chongqing; GZ, Guangzhou.

Review of PM2.5 concentrations

The averaged PM2.5 concentrations after 2013 were 34.5, 34.4, 19.1 and 2.3 µg/m3 lower than previous values at first periods [2000–2013] in GZ, CQ, WH and LZ, respectively (Figure 3). The data were in agreement with the results presented in Figure 2E. A significant decrease in the average values of PM2.5 occurred geographically from north to south after the overall rectification in 2013, ranging from 39 to 102 µg/m3.

SO42−, NO3, and NH4+

The proportions of three ions, crucial elements of the secondary inorganic component of air pollution, including SO42− (8.4–57%), NO3 (4.2–21%) and NH4+ (2.3–19%), showed different changes across different dimensions. Considered as the first major anthropogenic source, SO42− contributed the most. The data indicate that LZ had the largest absolute levels of sulfates (28±18 µg/m3) prior to 2013, followed by CQ, where the absolute concentration was upwards of 27±15 µg/m3. Given high levels of SO42−, there was a possibility that the sulfides from the coal burning had undergone a secondary conversion, indicating that CQ and LZ experienced more serious coal combustion emission prior to mandatory rectification in 2013. The long-term use of coal-fired heating in LZ and clusters of factories in CQ contributed significantly to high SO42− levels (32,102). Importantly, recent concentrations of SO42− in GZ, CQ and LZ decreased sharply, with average values of 6.5±2.2, 10±3.2 and 11±3.7 µg/m3, respectively.

Based on the literature evidence suggesting that approximately 50% of nitrate mass can be attributed to coal combustion (103), NOx, as the precursor of nitrate, is mainly derived from urban anthropogenic activities such as traffic and factory emissions. The continuously upward trend occurred in WH during the two periods (average values 11–20 µg/m3). A slightly upward trend in the levels of NO3 also occurred in CQ mainly due to the surge in the number of motor vehicles (Table 2), while LZ and GZ showed considerably lower levels of NOx emissions.

The trends of NH4+ in four cities were somewhat comparable to trends seen for SO42− and NO3. Specifically, we observed that the secondary inorganic pollution sources dominated the composition of PM2.5 in WH. Cheng et al. (104) found stronger oxidation process of SO2 and NO2 in the atmosphere from research between 2016–2017. Due to the massive burning of fossil fuels, coal and biomass, the secondary inorganic aerosols accounted for a large proportion in the industrial area of WH, while the soil source dominated the large traffic volume and frequent urban construction throughout the year (29). Notably, in LZ, only 1.3±0.8 µg/m3 of concentration value was recently normalized and similar results were found for ammonium levels which were lower than 3% in Northwest China during 2006–2013 based on a previous study (105). Overall, the data suggest that the secondary source of PM2.5 in the northwest region (like LZ) was relatively small due to the yearly dry climate, which is not conducive to the occurrence of secondary reactions (48).

EC and OC

The levels of OC ranked first or second among the constituents shown in Figure 3 in four cities, accounting for approximately 7–30% in terms of fraction. The proportions of OC were relatively reduced after 2013 in all regions, especially in CQ (from 37±21 µg/m3 in first period to 13±2.2 µg/m3 in second period). Other studies suggested that OC can be used to estimate the organic matters (OM), which is typically obtained by multiplying OC by a specific coefficient (63). Additional indirect data suggest that VOCs, the precursor of organic matter, were recently increasing. Taken together, CQ had the highest organic pollution compared to other cities prior to 2013 and the most effective control over VOC emissions. As a primary burning indicator, EC accounted for approximately 5–9% of emissions in the four cities. There were clear downward trends in WH, CQ and GZ, presenting the absolute concentration changes of 12±7.1 to 6.1 µg/m3, 7.6±3.3 to 4.0±1.3 µg/m3 and 5.4±2.9 to 2.3±0.4 µg/m3, respectively. Geographically, values of EC decreased from north to south. The EC had a similar source like particulate organic carbon (POC), and was not a major chemical fraction in aerosol particles found in China (105).

K+ and Cl

The highest average concentrations of Cl were seen in LZ (6.4±1.9 µg/m3 and 3.3±0.6 µg/m3 before and after 2013, respectively) while the trends for other cities were relatively flat. Combined with the highest proportion of Cl (3–7%) in LZ, the data further suggested that coal burning was the main source of aerosol pollution in this local area. Primary component K+, as a biomass indicator, showed significant decreases in average concentrations across all cities (ranging from 0.5 to 2.1 µg/m3), suggesting that the overall control of biomass burning has achieved very good results.

Trace metal elements

Data summarized in Figure 5 show the comparison of trace metal concentrations in 1996 and in recent years (from 2010 to 2017) in four cities, including Zn, Mn, Pb, Cu, Cr, that are either specific source indicators or trace elements with serious impact on human health (106-109).

Figure 5 Comparisons of concentrations of five major metal elements during two periods [1996 and 2010–2017]. Solid column represents the first period [1996] while the dotted line column indicates the second period [20102017] for each component across four cities.

The concentrations of metal elements were generally low, ranging from 0.003 to 2.8 µg/m3 more than 20 years ago, compared to recent values in the range of 0.012−1.7 µg/m3. Data suggested that Mn, Zn, Pb were mainly derived from metal smelting (110) or combustion processes (111). Additionally, we observed the highest concentration values of Zn in all cities due to background content in soil and supernumerary content of vehicle exhaust emissions and tire wear (112). A small increase in the concentration of Zn and Mn was found in CQ and WH, while LZ and GZ showed an obvious decrease. The levels of Cu in CQ and LZ showed significant rise, while they were relatively flat in WH and GZ. Two toxic metals, Pb and Cr (113), showed variable trend concentrations across the four cities. At present, coal burning and industrial production (such as smelting and sintering process) have become the main sources of Pb due to mandatory use of unleaded gasoline since late 1990s (114). During the 12th Five-Year Plan period for controlling heavy metal pollution, Pb was included as one of the key target pollutants (115). Emission of Pb from factories seem to be effectively controlled in recent years (114). However, emissions of Cr from coal burning and industrial production appear to have increased significantly in WH, possibly due to the specificity of the study site (e.g., near the factory) in the reviewed literatures.

Conclusions and perspectives

Inter-annual variations in five major pollutants across two decades and chemical components of PM2.5 in the recent years in the four cities were comprehensively summarized. It helped to provide a better understanding of the evolution of pollution sources for studying changes in health outcomes related to changes in air quality in populations with similar ages living in the same cities. The findings can be summarized as follows:

  • All four cities experienced rapid growth over the last two decades; however, there were obvious geographical differences. For example, GZ, as one of the first-tier cities, was ranked first in GDP among all cities, while LZ showed slow development. Of note, the growth rate of CQ was the highest as of 2017 from the prior year.
  • The evolution of five conventional pollutants in GZ, LZ, WH and CQ varied with space and over time. Clear downward trends occurred in SO2 and PM (including PM10 and PM2.5) levels. SO2 concentrations in all four cities were below the second-level concentration (standard) of 60 µg/m3 after 2008, while PM2.5 and PM10 were still not up to the standard, except for PM10 in Guangzhou. In particular, the greatest improvement of SO2 pollution occurred in CQ (a decline of 96.4%), and GZ showed the best results for reduction in particulate pollution. The levels of NO2 showed relatively flat trends compared to other pollutants. Importantly, O3 concentrations have been on rise, which should be considered in examining the effects of ambient air pollution on human respiratory health.
  • Among the chemical components of PM2.5, organic carbon and SO42− dominated PM2.5 mass concentration in all cities. The overall levels of pollutants showed decreases after 2013 in LZ, CQ and GZ, but the trend was the opposite in WH showing an upward trend in SO42−, NO3, NH4+, and Cl between 2014 and 2017. Moreover, WH had the highest mass fraction of SO42−, NO3 and NH4+, indicating that the control of coal combustion and vehicle emissions should be stricter in this city. Finally, LZ, among the four cities, had the lowest proportion of secondary components and highest levels of EC and Cl- mainly emitted from perennial coal-fired emissions.
  • The concentrations of different metals showed different long-term trends, ranging from 0.003 to 2.8 µg/m3 more than 20 years ago, compared to recent values in the range of 0.012−1.7 µg/m3.


Funding: This work was supported by the Ministry of Science and Technology of China, China (No. 2017YFC0210004), and National Natural Science Foundation of China (91744202).


Provenance and Peer Review: This article was commissioned by the Guest Editor (Junfengf Zhang, Howard Kipen and Haidong Kan) for the focused issue “Children’s Respiratory Health and Air Quality” published in Journal of Thoracic Disease. The article was sent for peer review organized by the Guest Editors and the editorial office.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at doi: The issue “Children’s Respiratory Health and Air Quality” was commissioned by the editorial office without any funding or sponsorship. JJZ served as the unpaid Guest Editor of the issue. JJZ also serves as an unpaid editorial board member of Journal of Thoracic Disease. The other author has no other conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See:


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Cite this article as: Yin Z, Huang X, He L, Cao S, Zhang JJ. Trends in ambient air pollution levels and PM2.5 chemical compositions in four Chinese cities from 1995 to 2017. J Thorac Dis 2020;12(10):6396-6410. doi: 10.21037/jtd-19-crh-aq-004