Dramatic decrease of secondary organic aerosol formation potential in Beijing: Important contribution from reduction of coal combustion emission

Hourly emission amounts and concentration of water-soluble ions in primary particles from residential coal burning in rural northern China

Residential coal burning (RCB) stands as an important contributor to ambient pollutants in China. For the effective execution of air pollution control policies, it is essential to maintain precise emission inventories of RCB. The absence of hourly emission factors (EFs) combined with the inaccuracies in the spatial-temporal distribution of activity data, constrained the quality of residential coal combustion emission inventories, thereby impeding the estimation of air pollutant emissions. This study revised the hourly EFs for PM2.5 and water-soluble ions (WSIs) emitted from RCB in China. The hourly emission inventories for PM2.5 and WSIs derived from RCB illustrate the diurnal fluctuations in emission patterns. This study found that the emissions of PM2.5, NH4+, Cl-, and SO42- showed similar emission features with emission of 106.8 Gg, 1417.6, 356.8, and 5868.5 ton in erupt period. The results provide basic data for evaluating RCB emission reduction policies, simulating particles, and preventing air pollution in both sub-regions and time periods. The spatial emission and simulated concentration distribution of PM2.5 and WSIs indicated that emission hotspot shifted from North China Plain (NCP) to Northeast region in China. The emissions in China were well-controlled in '2 + 26' region (R28) priority region, with hotspots decreasing by 99.6% in BTH region. The RCB became the dominant contributor to ambient PM2.5 with a ratio in the range of 16.2-23.7% in non-priority region.

Anthropogenic-driven changes in concentrations and sources of winter volatile organic compounds in an urban environment in the Yangtze River Delta of China between 2013 and 2021

Volatile organic compounds (VOCs) serve as crucial precursors to surface ozone and secondary organic aerosols (SOA). In response to severe air pollution challenges, China has implemented key air quality control policies from 2013 to 2021. Despite these efforts, a comprehensive understanding of the chemical composition and sources of urban atmospheric VOCs and their responses to emission reduction measures remains limited. Our study focuses on analyzing VOCs composition and concentrations during the winters of 2013 and 2021 through online field observations in urban Nanjing, a typical city in the Yangtze River Delta region of China. Using a machine learning approach, we found a notable reduction in total VOCs concentration from 52.4 ± 30.4 ppb to 33.9 ± 21.6 ppb between the two years, with dominant contributions (approximately 94.3 %) associated with anthropogenic emission control. Furthermore, alkanes emerged as the major contributors (48.6 %) to such anthropogenic-driven decline. The total SOA formation potential decreased by approximately 27.4 %, with aromatics identified as the major contributing species. Positive matrix factorization analysis identified six sources. In 2013, prominent contributors were solid fuel combustion (43.6 %), vehicle emission (16.7 %), and paint and solvent use (12.8 %). By 2021, major sources shifted to solid fuel combustion (31.9 %), liquefied petroleum gas and natural gas (26.8 %), and vehicle emission (25.5 %). Solid fuel combustion emerged as the primary driver for total VOCs reduction. The lifetime carcinogenic risk in 2021 decreased by 72.6 % relative to 2013, emphasizing the need to address liquefied petroleum gas and natural gas source, and vehicle emissions for improved human health. Our findings contribute critical insights for policymakers working on effective air quality management.

Source apportionment of fine particulate matter at a megacity in China, using an improved regularization supervised PMF model

The source apportionment of particulate matter plays an important role in solving the atmospheric particulate pollution. Positive matrix factorization (PMF) is a widely used source apportionment model. At present, high resolution online datasets are increasingly rich, but acquiring accurate and timely source apportionment results is still challenging. Integrating prior knowledge into modelling process is an effective solution and can yield reliable results. This study proposed an improved source apportionment method for the regularization supervised PMF model (RSPMF). This method leveraged actual source profile to guide factor profile for rapidly and automatically identifying source categories and quantifying source contributions. The results showed that the factor profile from RSPMF could be interpreted as seven factors and approach to actual source profile. Average source contributions were also an agreement between RSPMF and EPAPMF, including secondary nitrate (26 %, 27 %), secondary sulfate (23 %, 24 %), coal combustion (18 %, 18 %), vehicle exhaust (15 %, 15 %), biomass burning (10 %, 9 %), dust (5 %, 4 %), industrial emission (3 %, 3 %). The solutions of RSPMF also exhibited good generalizability during different episodes. This study reveals the superiority of supervised model, this model embeds prior knowledge into modelling process to guide model for obtaining more reliable results.

Characteristics of volatile organic compounds and secondary organic aerosol pollution in different functional areas of petrochemical industrial cities in Northwest China

The aim of this study was to better understand the characteristics of volatile organic compounds (VOCs) and secondary organic aerosol (SOA) pollution in different functional areas of petrochemical industrial cities. In Lanzhou, a typical petrochemical industrial city in Northwest China, with the use of an Integrated Atmospheric Mobile Monitoring Vehicle (IAMMV), various real-time online monitoring instruments, including a VOC monitoring instrument (TH-300B) and single-particle aerosol mass spectrometer (SPAMS), were used in combination. These instruments were employed to determine PM_2.5, VOCs and other factors at monitoring sites in Xigu (XG) and Chengguan (CG) districts in September 2020 and 2021, respectively. The results revealed that during the monitoring period, the average VOC concentrations at the XG and CG monitoring sites were 102.3 and 35.8 ppb, respectively. Benzene (45.58 %) and toluene (24.47 %) significantly contributed to the SOA formation potential at the XG site. M/P-xylene (27.88 %) and toluene (23.64 %) more notably contributed to the SOA formation potential at the CG site. The PM_2.5 mass concentration at the XG site (24.1 μg·m^-3) was similar to that at the CG site (21.2 μg·m^-3), but the proportion of particulate matter components greatly differed. The proportion of organic carbon (OC) at the XG site (19.00 %) was higher than that at the CG site (9.97 %). The number of particles containing C₂H₃O⁺ (m/z = 43) accounted for 36.96 % and 15.41 % of the total particles at the XG and CG sites, respectively. The mixing ratios of OC and hybrid carbon (OCEC) with C₂H₃O⁺ (m/z = 43) were 0.81 and 0.53, respectively, at the XG site and reached only 0.48 and 0.25, respectively, at the CG site. The secondary ageing degree of particles in XG district was high. These results could provide a reference for ambient air quality improvement and the formulation of governance measures in different functional areas of petrochemical industrial cities.