Exploring the characteristics and sources of carbonaceous aerosols in the agro-pastoral transitional zone of Northern China

The ratio of concentration of organic carbon and elemental carbon bound to particulate matter in ambient air: a global systematic review and meta-analysis

Four hundred and sixty-six references with 625 data reports were included in our study. The high frequency of ratio OC/EC for PM0.1 was observed in 3.92-5.93; PM1 in 1.08-3.08; PM2.5, 2.08-4.08; PM10 in 2.70-4.70 and TSP in 2.66-4.66. The rank order of areas based on the pooled concentration of OC bound to PM2.5 was traffic (17.893 µg/m3) > industrial (10.58 µg/m3) > urban (7.696 µg/m3) > rural (4.08 µg/m3). The rank order of areas based on the pooled (mean) concentration of EC in PM2.5 was traffic (17.893 µg/m3) > industrial (2.65 µg/m3) > Urban (1.48 µg/m3) > rural (1.06 µg/m3). The pooled concentrations of OC and EC bound to PM2.5 in traffic areas were higher than in other areas. Therefore, it is recommended that monitoring and effectively reducing concentration plans are carried out, especially in traffic areas.

Characteristics and sources of carbonaceous aerosols in a semi-arid city: Quantifying anthropogenic and meteorological impacts

Carbonaceous aerosols have great adverse impacts on air quality, human health, and climate. However, there is a limited understanding of carbonaceous aerosols in semi-arid areas. The correlation between carbonaceous aerosols and control measures is still unclear owing to the insufficient information regarding meteorological contribution. To reveal the complex relationship between control measures and carbonaceous aerosols, offline and online observations of carbonaceous aerosols were conducted from October 8, 2019 to October 7, 2020 in Hohhot, a semi-arid city. The characteristics and sources of carbonaceous aerosols and impacts of anthropogenic emissions and meteorological conditions were studied. The annual mean concentrations (± standard deviation) of fine particulate matter (PM_2.5), organic carbon (OC), and elemental carbon (EC) were 42.81 (±40.13), 7.57 (±6.43), and 2.25 (±1.39) μg m^-3, respectively. The highest PM_2.5 and carbonaceous aerosol concentrations were observed in winter, whereas the lowest was observed in summer. The result indicated that coal combustion for heating had a critical role in air quality degradation in Hohhot. A boost regression tree model was applied to quantify the impacts of anthropogenic emissions and meteorological conditions on carbonaceous aerosols. The results suggested that the anthropogenic contributions of PM_2.5, OC, and EC during the COVID-19 lockdown period were 53.0, 15.0, and 2.36 μg m^-3, respectively, while the meteorological contributions were 5.38, 2.49, and -0.62 μg m^-3, respectively. Secondary formation caused by unfavorable meteorological conditions offset the emission reduction during the COVID-19 lockdown period. Coal combustion (46.4% for OC and 35.4% for EC) and vehicular emissions (32.0% for OC and 50.4% for EC) were the predominant contributors of carbonaceous aerosols. The result indicated that Hohhot must regulate coal use and vehicle emissions to reduce carbonaceous aerosol pollution. This study provides new insights and a comprehensive understanding of the complex relationships between control strategies, meteorological conditions, and air quality.

Characteristics of fine carbonaceous aerosols in Wuhai, a resource-based city in Northern China:Insights from energy efficiency and population density

As one of the predominant compositions of PM_2.5 (particulate matter with aerodynamic diameter ≤2.5 μm), carbonaceous aerosols not only have adverse effects on air quality, but also can affect climate change. Although there are extensive recent studies on carbonaceous aerosols, comprehensive studies on their socioeconomic influencing factors in a resource-based city are relatively limited. In this study, the spatial-temporal variations of organic carbon (OC), elemental carbon (EC), and secondary organic carbon (SOC) were investigated in January, July, and October in 2015 and April in 2016 in Wuhai and its surrounding areas. The population distribution and industry layout have led to the uneven spatial-temporal distribution of carbonaceous aerosols. The concentrations of carbonaceous aerosols were higher in winter due to the unfavorable meteorology and the increased emissions from heating. The SOC is a significant contributor to OC in the cold season (52.0% for January). Primary carbonaceous aerosols pollution is higher in the industrial sites of resource-based cities, whereas the SOC makes a significant contribution in the residential sites. The results of backward-trajectory and concentration-weighted trajectory analysis suggest that the local emissions and short-range atmospheric transport from nearby areas have a significant impact on PM_2.5 and carbonaceous aerosols. A strong correlation between population density and OC/EC ratio was found, indicating that the megacities with high population density have a higher SOC contribution than the resource-based cities. Resource-based cities are characterized by high level of primary OC emissions, whereas cities with high energy efficiency have a more significant SOC contribution. These results provide a more comprehensive understanding of carbonaceous aerosols in a resource-based city.

Temporal Variation and Source Analysis of Carbonaceous Aerosol in Industrial Cities of Northeast China during the Spring Festival: The Case of Changchun

Carbonaceous aerosol, one of the major components of atmospheric aerosols, significantly affects haze episodes, climate change, and human health. Northeastern China suffers severe air pollution, especially in some periods (e.g., the Spring Festival). However, studies on carbonaceous aerosols in typical northeast industrial cities (i.e., Changchun) are rare, limiting further comprehension of the atmospheric haze formation. In this study, we monitored the concentrations of carbonaceous aerosols (i.e., OC and EC) in Changchun during the Lunar New Year of 2018 (i.e., from Lunar 20 December to Lunar 20 January), and analyzed the temporal variation and source contributions via the HYbrid-Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model with the potential source contribution factor weights (PSCF) method. The daily concentrations of OC and EC were 9.00 ± 2.81 and 1.57 ± 0.46 µg m−3, respectively, and were significantly lower at nighttime than at the day during the Spring Festival. The concentrations during the major period (i.e., OC: 8.13 ± 2.93 µg m−3; EC: 1.47 ± 0.47 µg m−3 in festival days), including the Lunar Little New Year; the Lunar New Year’s Eve; New Year’s Day; Lunar 5 January, and the Spring Lantern Festival, were mainly from the northwestward with the wind speed of 4–6 m/s being lower than that of normal period (OC: 9.87 ± 2.46 µg m−3; EC: 1.67 ± 0.44 µg m−3) from the southeastward with a wind speed of 6–7 m/s. The direction of the airflow trajectory was mainly in local, northwestward, and northward, carrying particulate matter and gaseous pollutants. In major period, the daily concentration of atmospheric pollutants presented a bimodal trend, with peaks appearing regularly from 11:00 a.m. to 12:00 p.m. and 5:00 p.m. 10:00 p.m., which might be related to traffic, cooking, and firecrackers. The OC/EC was greater than 2 during the whole period, indicating the generation of secondary organic aerosols (i.e., SOC). This study was essential to understand the formation mechanisms of severe pollution episodes and develop control measures for the industrial cities of Northeast China during the Spring Festival.

Investigating the impacts of coal-fired power plants on ambient PM2.5 by a combination of a chemical transport model and receptor model

Aimed at evaluating the impacts of coal-fired power plants on urban air quality and human health, a one-month intensive observation campaign was conducted in a typical polluted city located in the 2 + 26 city cluster (Beijing, Tianjin and 26 other cities) of the North China Plain in December 2017. The observation results illustrated that the coal-fired power plant in this city increased the monthly average fine particulate matter (PM_2.5) concentration by ~5% at the city scale. The impacts differed under various diffusion conditions. A three-dimensional nested air quality condition model (the Nested Air Quality Perdition Model System or NAQPMS) with source apportionment was employed to analyze the impacts. The results indicated that power plants had the largest effect on regional air quality during the severe-pollution period, while any influence could be ignored during periods with excellent dissipation under robust winds. PM_2.5 contributed by the power plant mainly occurred below 150 m, diffused 100 km away, and reached a level of approximately 5 μg m^-3 during the light-pollution period. During the accumulation period, the plume reached a height of 500 m, diffused to the downwind area approximately 100 km away within half a day, and contributed at most 40 μg m^-3 to PM_2.5. The affected area expanded to 250 km during the severe-pollution period, and the contribution to PM_2.5 was at least 10 μg m^-3 at different distances. The affected height reached approximately 500 m, with PM_2.5 exceeding 10 μg m^-3, mainly constrained below 150 m. Overall, regional integrated control strategies should be implemented for the power plants in the 2 + 26 city cluster during pollution episodes to further improve air quality.

Quantification of primary and secondary sources to PM2.5 using an improved source regional apportionment method in an industrial city, China

Identifying and quantifying the major sources of atmospheric particulate matter (PM) is essential for the development of pollution mitigation strategies to protect public health. However, urban PM is affected by local primary emissions, transport, and secondary formation; therefore, advanced methods are needed to elucidate the complex sources and transport patterns. Here, an improved source apportionment method was developed by incorporating the receptor model, Lagrangian simulation, and emissions inventories to quantify PM_2.5 sources for an industrial city in China. PM_2.5 data including ions, metals, organic carbon, and elemental carbon were obtained by analyzing 1 year of sampling results at urban and rural sites. This method identified coal combustion (30.64%), fugitive dust (13.25%), and vehicles (12.51%) as major primary sources. Secondary sources, including sulfate, nitrate, and secondary organic aerosols also contributed strongly (25.28%-30.76% in total) over urban and rural areas. Hebei Province was the major regional source contributor (43.05%-57.51%) except for fugitive dust, on which Inner Mongolia had a greater impact (43.51%). The megacities of Beijing and Tianjin exerted strong regional impacts on the secondary nitrate and secondary organic aerosols factors, contributing 11.32% and 15.65%, respectively. Pollution events were driven largely by secondary inorganic aerosols, highlighting the importance of reducing precursor emissions at the regional scale, particularly in the Beijing-Tianjin-Hebei region. Overall, our results demonstrate that this novel method offers good flexibility and efficiency for quantifying PM_2.5 sources and regional contributions, and that it can be extended to other cities.