[Characteristics and Source Apportionment of PM2.5 in the Core Area of Ili River Valley in Spring].

To explore the characteristics and sources of PM2.5 in the core area of Ili River Valley in spring, a total of 140 PM2.5 samples were collected at six sampling sites during April 20-29, 2021, and 51 chemical components including inorganic elements, water-soluble ions, and carbon components were analyzed. The results showed that ρ(PM2.5) was at a low level during sampling, ranging from 9 µg·m-3 to 35 µg·m-3. Si, Ca, Al, Na, Mg, Fe, and K were the most abundant elements, accounting for 12% of PM2.5, indicating that PM2.5 was affected by the dust sources in spring. The spatial distribution characteristics of elements depended on the surrounding environments of the sampling sites. The new government area was affected by coal-fired sources, so the value of As concentration was high. Yining Municipal Bureau and the Second Water Plant were greatly affected by motor vehicle sources, so the values of Sb and Sn concentration were higher. The enrichment factor results showed that Zn, Ni, Cr, Pb, Cu, and As were mainly emitted from fossil fuel combustion and motor vehicles. The concentration of water-soluble ions accounted for 33.2% of PM2.5. Among them, ρ(SO42-), ρ(NO3-), ρ(Ca2+), and ρ(NH4+) were (2.48±0.57), (1.22±0.75), (1.18±0.49), and (0.98±0.45) µg·m-3, respectively. The higher Ca2+ concentration also reflected the contribution of dust sources. The ratio of n(NO3-)/n(SO42-) was between 0.63 and 0.85, which indicated that the influence of stationary sources was more important than that of mobile sources. Both Yining Municipal Bureau and the Second Water Plant were affected by motor vehicle exhaust; therefore, their n(NO3-)/n(SO42-) ratios were high. Yining County was in a residential area, and therefore its n(NO3-)/n(SO42-) ratio was lower. The average ρ(OC) and ρ(EC) in PM2.5 were 5.12 µg·m-3(4.67-6.25 µg·m-3) and 0.75 µg·m-3(0.51-0.97 µg·m-3), respectively. Yining Municipal Bureau was significantly affected by motor vehicle exhaust from both sides, so the values of OC and EC concentration were slightly higher than those in other sampling sites. The SOC concentration was calculated by the minimum ratio method, and the results showed that the values of SOC concentration in the New Government Area, the Second Water Plant, and Yining Ecological Environment Bureau were higher than those in other sampling sites. The results of the CMB model showed that PM2.5 in this area mainly came from the contribution of secondary particulate matter and dust sources, which accounted for 33.3% and 17.5%, respectively. Secondary organic carbon (16.2%) was the main contribution source of secondary particulate matter.

[Size Distribution and Source Appointment of Road Particles During Winter in Tianjin].

The significant role of traffic emissions mixed from various sources in urban air pollution has been widely recognized. However, the corresponding contributions to the roadside particle distribution are poorly understood due to the mixed impacts of various sources. Particle number concentrations of different sizes at the roadside in Nankai District of Tianjin were continuously monitored using a portable aerosol particle spectrometer during the morning rush hour (07:30-09:20) from Nov. 9, 2018 to Jan. 6, 2019. Characteristic and influencing factors of particle size distributions were discussed combined with temperature and relative humidity data, while potential sources of particles at the roadside were identified based on size distribution analysis. The results showed that the average total particle number concentrations were 502 cm-3, and the concentrations of the accumulation mode and coarse mode were 500 cm-3 and 2 cm-3, respectively. The distribution of number concentrations at the roadside was unimodal and primarily concentrated at 0.25-0.50 µm, with peak sizes at 0.28-0.30 µm. The same distribution trend of particle number concentration and difference in the concentration in the same segment size were observed at different periods. Vehicle activity level was the main influencing factor of road particulate matter concentration on different weekdays; the probability of the high value of road particulate matter concentration was reduced by a reasonable combination of the vehicle tail numbers. Temperature and relative humidity were both found to be positively correlated with the number concentration of particles. With the increase in temperature and relative humidity, the total and peak particle number concentration showed an overall upward trend. In addition, the peak particle size increased from 0.28-0.30 µm to 0.35-0.40 µm when relative humidity was higher than 80%. Three sources, including road dust, brake and tire wear, and the aging particles from vehicle exhaust, were identified using positive matrix factorization in this study. Road dust contributed 8.6% of the total number concentration, which mainly consisted of particles with sizes above 5.00 µm. Brake and tire wear contributed 2.8% of the total number concentration of particles with a size range of 0.80-4.00 µm. The aging particles from vehicle exhaust contributed the most (88.5%), with a peak at 0.25-0.65 µm. The sources of roadside particles were mainly related to vehicle activity, whereas temperature and relative humidity also affected the particle number size distribution.

Characteristics of PM2.5 in an Industrial City of Northern China: Mass Concentrations, Chemical Composition, Source Apportionment, and Health Risk Assessment.

Urban and suburban PM2.5 samples were collected simultaneously during selected periods representing each season in 2019 in Zibo, China. Samples were analysed for water-soluble inorganic ions, carbon components, and elements. A chemical mass balance model and health risk assessment model were used to investigate the source contributions to PM2.5 and the human health risks posed by various pollution sources via the inhalation pathway. Almost 50% of the PM2.5 samples exceeded the secondary standard of China's air quality concentration limit (75 µg/m3, 24 h). Water-soluble inorganic ions were the main component of PM2.5 in Zibo, accounting for 50 ± 8% and 56 ± 11% of PM2.5 at the urban and suburban sites, respectively. OC and OC/EC decreased significantly in the past few years due to enhanced energy restructuring. Pearson correlation analysis showed that traffic emissions were the main source of heavy metals. The Cr(VI) concentrations were 1.53 and 1.92 ng/m3 for urban and suburban sites, respectively, exceeding the national ambient air quality standards limit of 0.025 ng/m3. Secondary inorganic aerosols, traffic emissions, and secondary organic aerosols were the dominant contributors to PM2.5 in Zibo, with the total contributions from these three sources accounting for approximately 80% of PM2.5 and the remaining 20% attributed to traffic emissions. The non-carcinogenic risks from crustal dust for children were 2.23 and 1.15 in urban and suburban areas, respectively, exceeding the safe limit of 1.0 in both locations, as was the case for adults in urban areas. Meanwhile, the carcinogenic risks were all below the safe limit, with the non-carcinogenic and carcinogenic risks from traffic emissions being just below the limits. Strict control of precursor emissions, such as SO2, NOx, and VOCs, is a good way to reduce PM2.5 pollution resulting from secondary aerosols. Traffic control, limiting or preventing outdoor activities, and wearing masks during haze episodes may be also helpful in reducing PM2.5 pollution and its non-carcinogenic and carcinogenic health impacts in Zibo.

[Source and Health Risk Assessment of PM2.5-Bound Metallic Elements in Road Dust in Zibo City].

To study the pollution characteristics, sources, and ecological and health risk of PM2.5-bound metallic elements in road dust in Zibo City, a total of 97 dust samples were collected in eight districts between October 2016 and May 2017, and particles smaller than 2.5 µm were suspended filtered using a resuspension system. Inductively coupled plasma mass spectrometry (ICP-MS) and optical emission spectrometry (ICP-OES) were used to investigate 18 metal elements within the dust samples. The results showed that the mass fraction of Ca[ω(Ca)] was highest with an average of 120307.7 mg·kg-1, which was 7.2 times higher than the soil background values for Shandong Province. The mean values of ω(Zn), ω(Cu), ω(Sb), and ω(Cd) were 13.9, 11.7, 13.3, and 29.6 times higher than the background values, respectively. The geo-accumulation index (Igeo) indicated high levels of Cd, Zn, Cu, and Sb pollution, especially in winter. Enrichment factors (EFs) also indicated high concentrations of Cd, Zn, Sb, and Cu in the road dust, which were notably affected by human activities. Principal component analysis (PCA) showed that biomass combustion, coal burning, vehicle emissions, iron and steel smelting, and soil dust are the five main sources of metal elements in road dust in Zibo City. The potential ecological risk of Cd and the total potential risk were extremely high during three seasons and was highest in winter. Health risk assessment showed that As and Pb had a non-carcinogenic risk for children, while Cr presents a carcinogenic risk. In conclusion, pollution from PM2.5-bound metallic elements in road dust in Zibo City is derived from anthropogenic sources and is most severe during winter. Importantly, the levels of pollution detected represent potential ecological risk as well as some non-carcinogenic and carcinogenic risks for children. Therefore, the source control of road dust requires particular attention.