Introduction

Atmospheric particulate matter (PM) is a mixture of direct emissions from natural and anthropogenic sources and secondary particles formed through gas-to-particle conversion processes. PM can adversely affect the local environment and human health1,2,3,4. Water-soluble ions are the main components of PM. Therefore, analyzing the water-soluble ions in PM can provide evidence to elucidate their source contributions, physical and chemical properties, and transportation processes5.

Many domestic and international studies6,7,8 analyzed the sources and components of particulate matter based on Positive Matrix Factorization (PMF) and potential source contribution function (PSCF). A PMF-based source analysis study in Athens, Greece9 showed that road traffic and sulfate-rich regional aerosols were the main sources of roadside traffic and urban background, respectively. A study in Lecce, southern Italy10 demonstrated that organic and inorganic secondary aerosols accounted for 43% of PM2.5 with little seasonal variation, while secondary organic carbon (SOC) was larger during cold periods and sulfate was larger in the summer. A study in Chengdu, China11 indicated that the main sources of PM2.5 are secondary aerosols and coal combustion, with the southern, southeastern and eastern Sichuan basin being the most likely potential sources of PM2.5.

The physical processes of air pollutants, such as their diffusion, transport, and settlement, can be influenced by weather processes, such as wind speed and direction, turbulence, and precipitation12,13. Weather conditions and their progression can affect the spatial distribution and temporal variation of pollutants, which can directly influence the duration and severity of the pollution process14. Shen et al. indicated that the Polar Jet and the Bermuda High streams considerably influence the ozone concentrations in the eastern United States15. Hou et al. demonstrated that uniform high-pressure and eastern high-pressure weather types were more likely to cause fine particulate pollution in China16. To achieve a scientific understanding of the air pollution formation mechanism and accurate air pollution forecasting, the influence of different weather conditions on pollutant transport and diffusion must be analyzed.

In the spring of 2021, China experienced its most intense and wide-reaching dust storm in 10 years, which affected most parts of northern China17. The storm began on the night of March 14 and continued until March 18, when it gradually disappeared, affecting the North, Northwest, Northeast, and Jianghuai regions of China18. Lanzhou, a key comprehensive transportation hub and industrial base in northwest China, belongs to an arid and semi-arid climatic region and is severely influenced by dust storms6. Lanzhou is industrialized, with petroleum and chemical refining, machinery, and metallurgy as its main industries; it has become the main production base for heavy chemicals, energy, and raw materials in China19,20. Because of its unique valley–basin topography, industrial structure, and geographical location, Lanzhou has become one of the most polluted cities in the country21. In recent years, Lanzhou has implemented measures, such as emissions reduction, dust suppression, and vehicle control programs, to control air pollution levels, which has greatly improved the air quality of the city22. However, the spring sandstorms remain a pollution control problem in Lanzhou.

In this study, we analyzed the mass concentration and content of water-soluble PM2.5 (particulate matter with a diameter ≤ 2.5 μm) ions in Lanzhou in the spring of 2021. Furthermore, we investigated the origin and sources of these ions and their contributions. Moreover, we categorized the influences of different weather types on pollution. Our study can enable an in-depth understanding of the spring atmospheric environmental quality in Lanzhou and provide a scientific basis for environmental governance and efforts to improve the environmental quality.

Data and methods

Sampling site and description

The sampling site was an upper floor of a building (55-m height) at Lanzhou University, located in the southwest area of Lanzhou City (Fig. 1). The site is surrounded by residential areas and some shopping malls, with no significant pollution sources; the site is representative of a typical environment of mixed urban traffic, residential areas, and commercial areas. Twenty-three hourly PM2.5 samples (10 am to 9 am) were collected from March 1, 2021, to May 31, 2021, on a quartz filter (Whatman, 90-mm diameter) using a TH-150 medium flow sampler (Tianhong, Wuhan, China) operating at a flow rate of 100 L/min. A total of 88 samples were collected, including 15 samples on dust storm days and 73 samples on normal days.

Figure 1
figure 1

Location of sampling site (The statellite imagery was created on ArcGIS 10.3 platform (http://www.esri.com/software/arcgis/arcgis-for-desktop) and the map of Asia was created by MeteoInfo 3.1.7 (http://www.meteothink.org/downloads/index.html)).

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The meteorological Physical Sciences Laboratory reanalysis data were obtained from the National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) data set (https://www.psl.noaa.gov/data/gridded/data.ncep.reanalysis.html), including 850 hPa 4 × daily geopotential height reanalysis data and 850 hPa 4 × daily u-wind and v-wind reanalysis data (2.5° × 2.5° grids).

Water-soluble ion analysis

Ultrasonic techniques were used to extract inorganic ions from the samples; typically, more than 98% of sulfate, ammonium, and nitrate ions can be extracted through ultrasonic treatment23. A quarter of each filter sample was immersed in a sealed vial containing 50 mL of ultrapure water and was extracted three times with ultrasonic treatment for 15 min. The water-soluble ion content in the PM2.5 was determined using Metrohm 925 Eco IC (Switzerland) ion chromatography. Anion (F−, Cl−, NO3−, and SO42−) concentrations were determined using a Metrosep C 6-150/4.0 (Metrohm) column with a mixture of 3.2 mMol/L Na2CO3 and 1 mMol/L NaHCO3 as an eluent. Cation (Na+, NH4+, K+, Ca2+, and Mg2+) concentrations were determined using a Metrosep A Supp 5-150/4.0 (Metrohm) column with 4 mMol/L HNO3 as an eluent. The detection limits for these ions were in the range of 0.01–0.03 μg/m3. The samples of 7 days were selected for repeat testing and the standard error was found to be less than 5%. To evaluate the recovery efficiency of the method, the sample solution was spiked with a known amount of ions and the measurement found that the recovery was 95.6–102.0%.

Positive matrix factorization analysis

A positive matrix factorization (PMF) receptor model was used as a multivariate factor analysis approach to analyze the contribution of different sources to the samples on the basis of the components and speciation of these sources24. PMF was used to sort the specific sample data matrix into factor contribution (G) and factor profile (F) matrices25,26. The PMF equation is as follows:

$${x}_{ij}=\sum_{n=1}^{p}{g}_{in}{f}_{nj}+{e}_{ij} ,$$

where i is the number of the samples, j represents the types of chemical species, n is the number of factors, x is the measured concentration, g indicates the amount of mass contributed by the factors, f represents the species profile of the sources, and eij represents the residual of the species.

In PMF, nonnegativity constraints are used on the matrices to reduce the rotational degrees of freedom27; furthermore, Q is minimized in the analysis process to obtain the optimal solution. The equation for Q is as follows:

$$\mathrm{Q}=\sum_{i=1}^{m}\sum_{j=1}^{k}{\left(({x}_{ij}-\sum_{n=1}^{p}{g}_{in}{f}_{nj})/{u}_{ij}\right)}^{2}$$
$$u\_ij=5/6*MDL x\_ij<MDL$$
$${u}_{ij}=\sqrt{{\left(RSD*{x}_{ij}\right)}^{2}+{\left(0.5*MDL\right)}^{2}*{x}_{ij} } {x}_{ij}>MDL,$$

where uij represents the estimated uncertainty values, MDL is the method detection limit, and RSD is the error fraction. In this study, the RSD was set to 0.128. The water-soluble ion samples were added to the Environmental Protection Agency PMF 5.0 (United States Environmental Protection Agency) for analysis of the contribution of sources. The signal-to-noise (S/N) criterion was used to classify the input variables, and the species Na+, NH4+, K+, Ca2+, Mg2+, Cl−, NO3−, and SO42− were classified as “strong variables” and F− as “weak variables” for which a triple uncertainty was used. And the displacement (DISP) method was used to assess the uncertainty in profiles and contribution of the estimated factors. Results showed that the drop of Q value was less than 0.1% and no factor swapped for the smallest dQmax, indicating that the results were credible.

Potential source contribution function analysis

Potential source contribution function (PSCF) analysis is a method for identifying potential source areas of air pollution by using backward trajectory analysis14. In this study, reanalysis data with a resolution of 1 × 1° provided by the NCEP Global Data Assimilation System was used as the initial meteorological field. The Hybrid Single-Particle Lagrangian Integrated Trajectory model was used to calculate the backward trajectory of Lanzhou in spring. The PSCF model was based on the ratio of the cumulative probability of pollution trajectories passing through each grid to all trajectories29. The equation is as follows:

$$\mathrm{PSCF}=\frac{(\frac{{m}_{ij}}{N})}{(\frac{{n}_{ij}}{N})}=\frac{{m}_{ij}}{{n}_{ij}} ,$$

where N represents the total number of trajectory points counted in the modeling, mij represents the pollution trajectory points in the ij grid, and nij represents all trajectory points in the ij grid. In this study, the trajectories with PM2.5 concentrations over 35 μg/m3 were considered pollution tracks. The 96-h backward trajectories were calculated four times per day at 00:00, 06:00, 12:00 and 18:00 LT. The grid layer was from 30 to 60° N and 70 to 120° E, including more than 95% of the area covered by all the trajectories. And the grid size of the geographic region was designed to be 0.25 × 0.25°.

Classification of synoptic weather patterns

Spring synoptic weather patterns were classified using the T-model principal component analysis (T-PCA) method improved upon by Huth et al.30 in the PCA aspect. The basic purpose of T-PCA is to sort original high-dimensional data Z into two low-dimensional matrices F and A (Z = FAT, with F as the principal component and A as the load). All principal components were sorted according to their contributions to the original data, and the corresponding principal component F was filtered and dimension reduced on the basis of the cumulative contribution of the original data30,31,32. T-PCA has temporal and spatial stability and can accurately reflect the characteristics of the original weather circulation33. In this study, regions 80°E to 120°E and 30°N to 60°N were selected for the analysis of prevailing weather circulation. T-PCA was performed using COST733 class software, which was developed through an initiative within the Earth System Science and Environmental Management domain of the European Cooperation in Science and Technology framework (http://cost733.met.no/).

Results and discussion

The average PM2.5 and water-soluble ion concentrations for whole spring and the dust storm and normal days of March 1 to May 31, 2021, in Lanzhou are listed in Table 1. The daily average PM2.5, Na+, NH4+, K+, Mg2+, Ca2+, F−, Cl−, NO3−, and SO42− concentrations for the entire spring were 54.3, 0.91, 1.28, 0.35, 0.21, 2.56, 0.10, 0.66, 3.29 and 3.87 μg/m3, respectively. During the dust storm days, the PM2.5, Na+, K+, Mg2+, Ca2+, Cl−, and SO42− concentrations increased significantly (Fig. 2), with concentrations of 158.1, 1.36, 0.59, 0.75, 8.73, 0.91 and 6.18 μg/m3, respectively. By contrast, the NH4+ and NO3− concentrations decreased, with concentrations of 1.20 and 3.05 μg/m3, respectively. During the normal days, the average PM2.5 concentration was 33.0 μg/m3, which is lower than the China National Ambient Air Quality Standard (35 μg/m3). Concentrations of NH4+ and NO3− increased, and other water-soluble ions remained at low levels. During the dust storm days, the concentration of F− only increased by 0.01 μg/m3.

Table 1 Average PM2.5 and water-soluble ion concentrations for whole spring, dust storm days, and normal days in the spring of 2021 in Lanzhou, China.
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Figure 2
figure 2

Time series of PM2.5 and the water-ion concentrations from March 1, 2021, to May 31, 2021, in Lanzhou, China (colored bars indicate dust storm days).

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Compared with previous years22,34, the concentrations of PM2.5 and water-soluble ions in spring 2021 had been further reduced. PM2.5 concentrations in 2021 spring decreased by 38.9% and 33.2% compared to 2014 and 201835,36, respectively. In recent years, Lanzhou has committed to environmental management and implemented measures such as emission reduction, dust reduction and vehicle control to improve air quality22. And the reduction in anthropogenic emissions from industry and transportation due to COVID-19 lockdown also led to the reduction of air pollutants in Lanzhou in the spring of 202137. During dust storm days, PM2.5 concentrations increased rapidly, as well as the concentrations of Na+, Mg2+, Ca2+, K+, Cl−, and SO42−. Previous studies also showed that PMs and crustal material increased rapidly during dust storm days. A study in Xi’an38, northwest China, showed that Ca2+, SO42− and NO3− were the most abundant ions in TSP samples during dust storm days, but the concentration of secondary aerosols was lower than those during normal days. A study in Riyadh, Saudi Arabia39 presented that PMs and some elements (such as Fe, Mg, Ca and Al) increased more than doubled during dust storm days. Shen et al. indicated that during dust storms, crustal matter and carbon-containing matter accounted for 69% and 14% of PM2.5, respectively40. However, the concentration of NO3− and NH4+ decreased during the dust storm days. A study in Lanzhou indicated that due to the comprehensive effects of dust adsorption, the drag effect of sedimentation, and the strengthening of atmospheric diffusion capacity caused by increased wind speeds, concentrations of local emissions have decreased significantly, resulting in lower NO3− and NH4+ concentrations34. A study in Seoul, South Korea41 demonstrated that during heavy dust periods, NO3− concentrations decreased, while Ca2+ and Mg2+ concentrations increased significantly.

The Pearson correlations between water-soluble ions on normal and dust storm days in Lanzhou are listed in Table 2. During normal days, NH4+ was positively correlated with Cl−, NO3−, and SO42−, indicating that ammonium salts were mainly present in the form of NH4Cl, NH4NO3, and (NH4)2SO4. Previous studies42,43 also indicated that the compositions of PM2.5 in different regions were consistent with our results during normal days. Gluščić et al. demonstrated that SO42−, NO3−, and NH4+ were the main contributing ions to the total mass of PM2.5, and these ions were present in the atmosphere in the form of NH4NO3, NH4HSO4, and (NH4)2SO4 in Croatia42. A study performed in Heze, China44 showed that ions mainly exist in the form of NH4NO3, NH4HSO4, and (NH4)2SO4 in winter and autumn, and the forms were more complex and diverse in spring and summer. Chen et al. found that in Sichuan, China, the content of NH4+ in most samples during spring was sufficient to neutralize SO42 and NO3− to form (NH4)2SO4 and NH4NO345. A study in southeastern Italy46 indicated there was a strong correlation between SO42- and NH4+, with the ammonium salt in the form of ammonium sulfate.

Table 2 Pearson correlations between water-soluble ions for normal and dust storm days from March 1, 2021, to May 31, 2021 in Lanzhou, China.
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During dust storm days, the correlations between SO42− and K+, Na+, Mg2+, and Ca2+ ions were stronger than those of NH4+, indicating that sulfate was mainly present in the form of K2SO4, Na2SO4, MgSO4, and CaSO4. A strong positive correlation was identified between NO3− and NH4+, indicating that nitrate was mainly present in the form of NH4NO3. Wu et al. indicated that due to the numerous mirabilite ores distributed along dust transmission pathways in desert source areas of northwest China, sulfate mainly originates from primary discharge in the chemical form of Na2SO4 and CaSO4 during dust storm periods47. Wu et al. indicated that the hydrolysis of N2O5 on neutral mineral dust salts (e.g., CaSO4 and Na2SO4) can promote the formation of NH4NO3 during dust storm periods, leading to the accumulation of NH4NO3 on dust surfaces48. In this study, during normal days, a negative correlation was evident between Na+ and Cl−, whereas during the dust storm period, a significant positive correlation was observed between the two ions, indicating that the sandstorm brought sea salt aerosol (or salt water lake aerosol) through long-range transmission to Lanzhou.

The main characteristic species and corresponding contributions of the six emission sources identified using the PMF model are presented in Figs. 3 and 4. Dust was the highest contributor to spring PM2.5 concentrations in Lanzhou, accounting for 32.0%. The main characteristic water-soluble ions with a dust source were Ca2+, Mg 2+, and SO42−. Lanzhou is located on the northeastern edge of the Tibetan Plateau, with the Taklamakan, Kumtag, and Gurbantunggut deserts to the west and the Badain Jaran and Tengger deserts to the north49, leading to frequent dust storms in spring. The second highest emission source contributing to PM2.5 concentrations was industrial entities, accounting for 29.8%. The main characteristic water-soluble ions with industrial entities source were SO42−, NO3−, NH4+, and Na+. The volatilized chemical solvents and produced pollutants from large industrial sources (such as power plants, petrochemical plants, oil refineries, and pharmaceutical plants), located in the upper winds of Lanzhou, were transported to the observation area, resulting in a high concentration of industrial emissions50. The contribution of biomass combustion to PM2.5 concentrations was 13.4%, and the main water-soluble ions with this source were K+ and Cl−. The contribution of metal smelting to PM2.5 concentrations was 11.2%, and the main water-soluble ions with this source were F−, SO42−, NO3− and Ca2+. Lanzhou is a major aluminum production base in China, and the electrolysis of aluminum produces F−, resulting in large amounts of F− from metal smelting sources51. The contribution of secondary aerosol to PM2.5 concentrations was 10.8%, which was mainly characterized by high concentrations of NH4+, SO42− and NO3−. Lanzhou is located in the Yellow River valley basin, surrounded by mountains52. This unique basin topography prevents air pollutants from being easily diffused, and the long-term retention of these pollutants facilitates the formation of secondary aerosols52,53. Sea salt (or salt water lake aerosol) contributed the least to PM2.5 concentrations, only accounting for 2.7%. The main characteristic water-soluble ions with a sea salt source were Na+ and K+. In addition, correlation analysis revealed that sea salt aerosol (or salt water lake aerosol) was brought to Lanzhou through the long-range transport of dust storms. Na+, Cl−, K+ and Mg2+ are the main ions of sea salt aerosol54. Reaction of gaseous or aqueous HNO3 or H2SO4 with NaCl in sea salt or oxidation of gaseous SO2 to sulfuric acid by sea salt droplets leads to chloride depletion in sea salt aerosols25. A study in Shenzhen, China also reported that the aged sea salt was indicated by high loadings of Na+ and Mg2+ and low concentration of Cl−56. A study in Lijiang, China indicated that sea salt aerosol contains 37% of K+56.

Figure 3
figure 3

Factor contribution and mass concentration (μg/m3) to spring 2021 PM2.5 concentrations in Lanzhou, China.

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Figure 4
figure 4

PMF analysis of spring PM2.5 emission source distribution in Lanzhou, China.

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Due to the difference of industrial structure and climate in different regions, the sources contribution of pollutant is also different. PMF results obtained from Gwangju, Korea57 indicated that the contributions of secondary nitrate, secondary sulfate and traffic emissions are the main sources of PM2.5, accounting for 26, 23 and 14%, respectively. A study in Rabigh, Saudi Arabia58 showed that soil, fossil-fuel combustion, industrial dust, vehicular emissions and sea sprays contributed 39.9, 19.9, 14.7, 13.4 and 12.1% to ambient PM2.5, respectively. Studies performed in southern cities in China, such as Nanjing, Chengdu and Chongqing45,59, indicated that secondary aerosols contributed the most to PM2.5, which might be related to local meteorological factors such as humidity and wind speed. A study in Taipei, China60 demonstrated that industrial entities contributed 40.0% to PM2.5, mainly characterized by high concentrations of NH4+ and NO3−, might be derived from large industrial sources at locations upwind. Yu et al. found that spring fugitive dusts, including soil and road dust, were more than twice as high as in other seasons in Beijing61.

The PSCF analysis for dust storm days, normal days, and the entire spring of 2021 is presented in Fig. 5. The main trajectories that contributed most to PM2.5 concentrations in Lanzhou during the dust storm days are presented in Fig. 5a. The air mass of trajectory 1 originated from the desert in southeastern Kazakhstan and the Gurbantunggut Desert in northern Xinjiang and moved southeastward to Lanzhou. Trajectory 2 moved more eastward than trajectory 1, bringing dust from the deserts of western Mongolia. The air mass of trajectory 3 originated from the Gobi region in the south of Mongolia and moved southwestward through the Badain Jaran Desert in western Inner Mongolia to Lanzhou. The air mass of trajectory 4 originated from the Badain Jaran Desert in western Inner Mongolia. During the normal days, the main potential sources of PM2.5 were in the western and northern parts of Lanzhou (Fig. 5b). This may be due to the large amount of pollutants generated in the Xigu District, the largest petrochemical base in western China, which is located upstream of the downtown area50. From the spring-wide perspective, the contribution to PM2.5 from the northern part of Lanzhou and the Hexi Corridor was increased (Fig. 5c). Tang et al. indicated that under conditions of strong zonal jet fronts in the midlatitudes of East Asia, the Hexi Corridor is prone to low-level jets, which lead to strong sandstorms in spring62. Liang et al. demonstrated that the type of land (especially bare land) on the air mass movement path is a key factor that can determine the intensity of a dust storm17. Improving land management in windward areas of Lanzhou, especially in the Hexi Corridor, may reduce the frequency and intensity of dust storms.

Figure 5
figure 5

PSCF analysis for (a) dust storm days, (b) normal days, and (c) the entire spring in 2021 in Lanzhou, China (MeteoInfo 3.1.7 http://www.meteothink.org/downloads/index.html).

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The transport of pollutants would lead to the variations in concentrations of local pollutants. A study in southern Peninsular Malaysia63 indicated that there was a high potential for long-range transport of pollutants from heavily polluted areas, which could have a significant impact on air quality in less polluted areas. Chen et al. found that cities in the south and east of Chengdu, such as Chongqing and Neijiang, were the main sources of pollution in Chengdu64. Transmission of dust storms could lead to a substantial increase in the concentration of local particulate matter. A study in Seoul, Korea41 reported that the concentrations of PM increased during dust storm days. Xiong et al. suggested that regional sandstorms transported to Wuhan via northwest air masses in spring lead to 1.1–1.8 fold increase in the concentration of crustal elements such as Al, Ca, and Mg65. Turap et al. found that the concentration of PM2.5 in Xinjiang, China was seriously affected by dust particles from Dushanzi district and Kazakhstan in spring66.

The average typical synoptic circulation from March 1, 2021, to May 31, 2021, was determined using T-PCA (Fig. 6). Type 1 was the northwest high pressure (NWH). There was a high pressure ridge in the northwestern part of Lanzhou area, and Lanzhou was affected by the Northwest (NW) wind before the ridge of high pressure. Type 2 was strong northern high pressure and southwest low pressure (NHSL). The north of Lanzhou contained a high-pressure area, and the southwest contained a low-pressure center. The atmosphere converged to the low-pressure area, and northeast winds prevailed in Lanzhou. Type 3 was northwest high pressure and southwest high pressure (NSH). The northwest and southwest of Lanzhou had two high-pressure systems. A strong north wind formed at the front of the northwest high-pressure system and a west wind formed from the southwest high-pressure system. Thus, northwest and west winds prevailed in Lanzhou in type 3. Type 4 was southwest strong high pressure (SWH+). Lanzhou is located in front of a high-pressure system and was, therefore, influenced by high-pressure dispersion, with prevailing west and southwest winds. Type 5 was southwest high pressure and southeast high pressure (WEH). Lanzhou is located behind a southeast high-pressure system with prevailing south winds. The frequencies of typical synoptic circulation types 1, 2, 3, 4 and 5 were 18.2, 21.7, 21.2, 19.8 and 19.0%, respectively. The typical synoptic circulation for types NWH, NHSL, and NSH were prone to dust storms. The frequency of dust storms was lower for the SWH+ and WEH types.

Figure 6
figure 6

850 hPa geopotential height fields and wind vector fields of typical synoptic circulation from March 1, 2021, to May 31, 2021 (cross indicates Lanzhou, China) (NCAR Command Language https://www.ncl.ucar.edu/).

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The synoptic circulation of the most severe dust storm of the past 10 years (lasting from March 14, 2021, to March 20, 2021), which affected most parts of northern China, is presented in Fig. 7. The synoptic circulation for this dust storm process was mainly of the NSH and NHSL types. The synoptic circulation at UTC 18:00 on March 14, 2021 was of the NWH type. A cold high-pressure center occurred in the west of Mongolia, adjacent to a cyclonic system on its eastern side. A rapid accumulation of sand and dust in southern and western Mongolia and central and western Inner Mongolia was influenced by the tail end of the cyclone and the frontal part of high pressure. This sand and dust were rapidly driven into the north of China by cold air. The synoptic circulation at UTC 18:00 on March 15, 2021, and UTC 12:00 on March 17, 2021, were of the NHSL type. A low-pressure center occurred in the southwest region of Lanzhou. The convergence of the atmosphere to Lanzhou led to strong sandstorms in Lanzhou from March 15 to 17. At UTC 12:00 on March 20, 2021, a low-pressure center was still present in the southwest of Lanzhou, causing the sandstorm to continue longer in Lanzhou than in other places. The dust storm faded away when the center of the high-pressure system moved southeast.

Figure 7
figure 7

850 hPa geopotential height field and wind vector field of a typical dust storm from March 14, 2021, to March 20, 2021 (NCAR Command Language https://www.ncl.ucar.edu/).

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In addition to the source of emissions, the frequency and severity of pollution events are influenced by meteorological conditions67. Miao et al. indicated that high-pressure systems in the southeast and east of Beijing block the flow of air to the sea, causing the polluted air of the southern industrial area to move toward Beijing68. Xu et al. reported that the L-shaped high synoptic circulation type is the most meteorologically adverse type, and it results in a low-pressure gradient force, weak wind speed, and rapid accumulation of PM2.531. These weather patterns may induce the movement of atmospheric pollutants and adverse meteorological diffusion conditions, which are the key factors affecting the intensity and duration of air pollution events13,33.

Our study has some limitations. First, we measured the composition of only nine water-soluble ions in PM2.5 and did not include organic carbon, elemental carbon, or metal. Second, we only analyzed the chemical composition and source of PM2.5 in the spring dust storm season. In future research, other composition such as organic carbon, elemental carbon, and metal elements should be measured. The influence of weather conditions on the pollution in Lanzhou would be further studied on a multiyear scale. Future studies should employ sensitivity simulation to quantify the influence of different weather conditions on air quality.

Conclusion

In this study, the emission sources and contributions of pollutants and the influence of weather situation on air pollution in the spring of 2021 in Lanzhou were comprehensively analyzed. The sources contributions of PM2.5 analyzed by PMF were dust (32.0%), industrial entities (29.8%), biomass combustion (13.4%), metal smelting (11.2%), secondary aerosol (10.8%), and sea salt (2.7%), respectively. During dust storm days, the concentration of Mg2+, Ca2+ and SO42− increased sharply. The main sources of dust were the Gobi Desert and deserts southwest and northwest of Lanzhou. The classification of weather types through T-PCA revealed that the NWH, NHSL and NSH synoptic circulation types were prone to dust storms.