Refined source apportionment of residential and industrial fuel combustion in the Beijing based on real-world source profiles

Pollution characteristics and quantitative source apportionment of heavy metals within a zinc smelting site by GIS-based PMF and APCS-MLR models

The abandoned smelters present a substantial pollution threat to the nearby soil and groundwater. In this study, 63 surface soil samples were collected from a zinc smelter to quantitatively describe the pollution characteristics, ecological risks, and source apportionment of heavy metal(loid)s (HMs). The results revealed that the average contents of Zn, Cd, Pb, As, and Hg were 0.4, 12.2, 3.3, 5.3, and 12.7 times higher than the risk screening values of the construction sites, respectively. Notably, the smelter was accumulated heavily with Cd and Hg, and the contribution of Cd (0.38) and Hg (0.53) to ecological risk was 91.58%. ZZ3 and ZZ7 were the most polluted workshops, accounting for 25.7% and 35.0% of the pollution load and ecological risk, respectively. The influence of soil parent materials on pollution was minor compared to various workshops within the smelter. Combined with PMF, APCS-MLR and GIS analysis, four sources of HMs were identified: P1(25.5%) and A3(18.4%) were atmospheric deposition from the electric defogging workshop and surface runoff from the smelter; P2(32.7%) and A2(20.9%) were surface runoff of As-Pb foul acid; P3(14.5%) and A4(49.8%) were atmospheric deposition from the leach slag drying workshop; P4(27.3%) and A1(10.8%) were the smelting process of zinc products. This paper described the distribution characteristics and specific sources of HMs in different process workshops, providing a new perspective for the precise remediation of the smelter by determining the priority control factors.

Characterizing carbonaceous aerosols in residential coal combustion: Insights from thermal/spectral carbon analyzer coupled with photoionization mass spectrometry analysis

This study aims to identify unique signatures from residential coal combustion in China across various combustion conditions and coal types. Using a Thermal/Spectral Carbon Analyzer with a Photoionization Time-of-Flight Mass Spectrometer (TSCA-PI-TOF-MS), we focus on the optical properties and organic mass spectra of the emissions. Bituminous coal emerged as the primary emitter of total carbon, releasing 729 μg C/mg PM2.5 under smoldering and 894 μg C/mg PM2.5 under flaming. Carbon fractions mainly comprised OC1 and OC2, except for anthracite's dominance of EC1 under smoldering. Pyrolysis carbon absorption shifted from 405, 445 and 532 nm during smoldering to near-infrared bands (635-980 nm) during flaming for both bituminous and anthracite coal. Conversely, clean coal exhibited an inverse trend, attributed to additives enhancing oxygen-containing organic compounds and long-chain hydrocarbons released in charring process. Sample of bituminous coal began charring at OC3 step, while anthracite began earlier at OC2 step, particularly pronounced under flaming. Clean coal displayed unconventional charring at OC1 step under smoldering condition, producing signature compounds like butenal, methylfuran, furanylalcohol, and naphthol. The mass spectra of bituminous coal featured characteristic peaks, including m/z 192 (methylphenanthrene), 206, 220 (alkylated phenanthrenes), and 234 (retene). Anthracite coal showed a potential tracer at m/z 223, shifting from OC1 in smoldering to OC2 in flaming. Clean coal under flaming condition exhibited elevated levels of aromatic compounds, indicating potential toxicity, with peaks at m/z 178 (phenanthrene), 228 (chrysene/benz[a]anthracene), 234 (retene), 242 (methylchrysene), and 252 (benzo[a]pyrene, benzo[k]fluoranthene). Results also showed that the broader mass spectra range in the OC3 and OC4 steps across all coal types suggests that high-temperature pyrolysis promotes diversity. These findings contribute to refined source apportionment of carbon emissions from residential coal combustion and provide the scientific basis for the formulation of air pollution prevention strategies, crucial for coal-dependent regions.

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.

Reactive oxygen species-dependent transient induction of genotoxicity by retene in human liver HepG2 cells

Retene is a polycyclic aromatic hydrocarbon (PAH) emitted mainly by biomass combustion, and despite its ubiquity in atmospheric particulate matter (PM), studies concerning its potential hazard to human health are still incipient. In this study, the cytotoxicity and genotoxicity of retene were investigated in human HepG2 liver cells. Our data showed that retene had minimal effect on cell viability, but induced DNA strand breaks, micronuclei formation, and reactive oxygen species (ROS) formation in a dose- and time-dependent manner. Stronger effects were observed at earlier time points than at longer, indicating transient genotoxicity. Retene activated phosphorylation of Checkpoint kinase 1 (Chk1), an indicator of replication stress and chromosomal instability, which was in accordance with increased formation of micronuclei. A protective effect of the antioxidant N-acetylcysteine (NAC) towards ROS generation and DNA damage signaling was observed, suggesting oxidative stress as a key mechanism of the observed genotoxic effects of retene in HepG2 cells. Altogether our results suggest that retene may contribute to the harmful effects caused by biomass burning PM and represent a potential hazard to human health.

Application of a hybrid GEM-CMB model for source apportionment of PAHs in soil of complex industrial zone

Accurate source apportionment is essential for preventing the contamination of pervasive industrial zones. However, a limitation of traditional receptor models is their negligence of transmission loss, which consequently reduces their accuracy. Herein, chemical mass balance (CMB) and generic environmental model (GEM) was fused into a new method, which was employed to determine the traceability of polycyclic aromatic hydrocarbons (PAHs) in a complex zone containing three coking plants, two steel plants, and one energy plant. Five categories of fingerprints comprising various compounds were established for the six plant sources where seven PAHs with low-high rings were screened as the best. Considering volatilization, dry deposition, and advective and dispersive transport, the GEM model generated 232 "compartments" in multimedia to capture subtle variations of PAHs during transmission. More than 90 % of the transmission of the seven PAHs varied between 0.4 % and 6.0 %. Over pure CMB model, acceptable results and best-fit results improved by 1.6-44.4 % and 0.3-80.8 % in the GEM-CMB model. Additionally, the coking, steel, and energy industries accounted for 36.4-56.1 %, 25.6-41.7 %, and 18.3-23.6 % of PAHs sources at four receptor points, respectively. Furthermore, quantifying contaminant loss rendered the traceability results more realistic, judged by distances and discharge capacities. Accordingly, these outcomes can help in precisely determining soil contamination.