This study presents an approach using multiple linear regression to quantify the impact of meteorological parameters and chemical species on aerosol pH variance in an urban setting in the Pearl River Delta, China. Additionally, it assesses the contributions of interactions among these factors to the variance in pH. The analysis successfully explains over 96% of the pH variance, attributing 85.8% to the original variables and 6.7% to bivariate interactions, with further contributions of 2.3% and 1.0% from trivariate and quadrivariate interactions, respectively. Our results highlight that meteorological factors, particularly temperature and humidity, are more influential than chemical components in affecting aerosol pH variance. Temperature alone accounts for 37.3% of the variance, while humidity contributes approximately 20%. On the chemical front, sulfate and ammonium are the most significant contributors, adding 14.3% and 9.1% to the pH variance, respectively. In the realm of bivariate interactions, the interplay between meteorological parameters and chemical components, especially the ${\mathrm{TNO}}_3–\mathrm{RH}$ pair, is exceptionally impactful, constituting 58.1% of the total contribution from interactions. In summary, this study illuminates the factors affecting aerosol pH variance and their interplay, suggesting the integration of statistical methods with thermodynamic models for enhanced understanding of aerosol acidity dynamics in the future.

The varying concentrations of polycyclic aromatic hydrocarbons (PAHs) at remote islands is an important indicator, demonstrating the contributions from different regional combustion sources. In this study, gaseous and particulate PAHs were measured at Weizhou Island in the Gulf of Tonkin from 15th March to 14th April, 2015. The concentrations of PAHs ranged from 116.22 to 186.74 ng/m³ and from 40.19 to 61.86 ng/m³ in gas and particulate phase, respectively, which were much higher than those of some remote sites in Asia. Phenanthrene, fluoranthene, pyrene, and chrysene, which were mainly found in diesel vehicle emissions, had relatively high concentrations in both gas and particulate phases. According to the comprehensive results of back trajectory cluster analysis and diagnostic ratios, the local vessel emission was probably the main source of PAHs, which was much more important than the coal and biomass combustion sources from remoter regions. The toxicities represented by ∑PAH₇, benzo(a)pyrene-equivalent carcinogenic power, and 2,3,7,8-tetrachlorodibenzo-p-dioxin-based total toxicity potency are much higher in particulate phase than those in gas phase. However, the toxicities of gas phase should not be neglected from the point of view of indirect-acting mutagenicities due to the high contribution of fluoranthene.

Based on ambient air quality data of the four key cities (Nanning, Liuzhou, Guilin, and Beihai) in Guangxi, China, along with an analysis of the main emission sources, topographic features, weather conditions, and backward trajectories, the variation of main air pollutants and pollution episodes in the four cities were studied. Results showed that air pollution was most serious in Liuzhou and Guilin, followed by Nanning and Beihai. PM_2.5 was the dominant pollutant in each city, followed by O₃, PM₁₀, and NO₂. Concentrations of SO₂ and CO did not exceed their National Ambient Air Quality Standard Grade II limit values. In the cities, the concentrations of PM_2.5, PM₁₀, NO₂, and SO₂ were high during fall and winter and low during spring and summer, while the concentrations of O₃ were high during fall and low during the other seasons. Concentrations of CO were low during summer and high during the other seasons in Nanning and Liuzhou, while they were high during spring and winter and low during summer and fall in Guilin and Beihai. In these cities, pollution episodes resulted mainly from stagnant accumulation and showed characteristics of regional pollution. However, pollution levels and durations for each city were different due to differences in main pollution sources, local geography, and weather conditions. The influences of air masses on the four cities were similar. They were mainly influenced by local emission sources in the spring, while during autumn, long-distance transportation from Hunan and Hubei was significant. In winter, air pollution in Nanning and Beihai was mostly affected by local emission sources, and that in Liuzhou and Guilin was mainly affected by long-distance transportation from the south and northeast of Guangxi.

PM_2.5-bound heavy metals are of concern because of their persistence, toxicity, and inhalation-related carcinogenic and noncarcinogenic effects. Concentrations, emission sources, and inhalation health risks of these pollutants were investigated during a winter campaign lasting 42 days in 2025 in Laibin, China. The mean PM_2.5 concentration was 47.6 μg/m³, with nominally higher nighttime levels associated with lower wind speeds and a shallower nocturnal boundary layer. The total concentration of nine measured heavy metals (Zn, Cr, Ni, Pb, V, Cu, Sb, Cd, and Co) averaged 363.0 ng/m³, dominated by Zn, Cr, and Ni. Enrichment factors indicated severe Cd enrichment, significant Ni enrichment, and moderate enrichment of V, Cu, Cr, Pb, and Zn, suggesting anthropogenic influence, especially for Cd and Ni. PMF analysis preliminarily resolved three major sources in the daily run: mixed non-ferrous metal smelting and coal combustion source (43%), traffic (23%), and industrial combustion (34%). In the separate daytime and nighttime runs, industrial combustion was the largest source in both periods, whereas traffic increased at night. Non-carcinogenic hazard index (HI) values were below 1 for all populations (children > adult males > adult females), and carcinogenic risks (CR) slightly exceeded 1 × 10⁻⁴ under winter exposure scenarios, with Cr as the main contributor. These results provide a winter-only baseline; precautionary Cr controls are suggested for winter pollution episodes, and multi-season monitoring is needed for comprehensive air quality strategies.