Highly time-resolved measurements of elements in PM2.5 in Changzhou, China: Temporal variation, source identification and health risks

Characteristics and sources of PM2.5-bound elements in Shanghai during autumn and winter of 2019: Insight into the development of pollution episodes

Elemental composition of PM_2.5 dispersed in the atmosphere has received increasing attention due to its health effect and catalytic activities. In this study, the characteristics and source apportionment of PM_2.5-bound elements were investigated using hourly measurements. K is the most abundant metal element, followed by Fe > Ca > Zn > Mn > Ba > Pb > Cu > Cd. With an average of 8.8 ± 4.1 ng m^-3, Cd was the only element whose pollution level exceeded the limits of Chinese standards and WHO guidelines. The concentrations of As, Se, and Pb doubled in December compared to November, indicating a large increase in coal consumption in winter. The enrichment factors of As, Se, Hg, Zn, Cu, Cd, and Ag were larger than 100, indicating that anthropogenic activities greatly affected them. Ship emissions, coal combustion, soil dust, vehicle emissions, and industrial emissions were identified as major sources of trace elements. In November, the pollution from coal burning and industrial activities was significantly reduced, demonstrating the remarkable achievement of coordinated control measures. For the first time, hourly measurements of PM_2.5-bound elements and secondary sulfate and nitrate were used to investigate the development of dust and PM_2.5 events. During a dust storm event, secondary inorganic salts, potentially toxic elements, and crustal elements sequentially reached peak concentrations, indicating different source origins and formation mechanisms. During the winter PM_2.5 event, the sustained increase of trace elements was attributed to the accumulation of local emissions, while regional transport was responsible for the explosive growth before the end of the event. This study highlights the important role of hourly measurement data in distinguishing local accumulation from regional and long-range transport.

Pollution characteristics and human health risks of PM2.5-bound heavy metals: a 3-year observation in Suzhou, China

This study aimed to analyze the temporal trends, pollution levels, and health risks associated with eleven PM_2.5-bound heavy metals (Sb, Al, As, Hg, Cd, Cr, Mn, Ni, Pb, Se and Tl). A total of 504 PM_2.5 samples were collected in Suzhou from January 2019 to December 2021. The pollution levels were estimated based on enrichment factors (EFs) which can be used to calculate the enrichment of heavy metals in PM_2.5 and determine whether the concentrations of PM_2.5-bound heavy metals are influenced by the crustal or anthropogenic sources, and the health risk of PM_2.5-bound heavy metals via inhalation was assessed following US EPA's Risk Assessment Guidance for Superfund (RAGS). The annual average concentration of PM_2.5 was 46.76 μg m^-3, which was higher than the WHO recommended limit of 5 μg m^-3. The average of the sum of eleven PM_2.5-bound heavy metals was 180.61 ng m^-3, dominated by Al, Mn, and Pb. The concentration of PM_2.5 in 2020 was significantly lower than that in 2019 and 2021. The PM_2.5 and PM_2.5-bound heavy metal concentrations in winter and spring were significantly higher than those in autumn and summer. The EF of As, Cr, Cd, Hg, Ni, Pb, Sb, Mn, Se, and Tl was higher than 10, indicating they were mainly from anthropogenic sources. Exposure to a single non-carcinogenic heavy metal via inhalation was unlikely to cause non-carcinogenic effects (HQ < 1), but the integrated non-carcinogenic risks should be taken seriously (HI > 1). The cumulative carcinogenic risks from the carcinogenic elements were exceeding the lower limit (1 × 10^-6) of the acceptable risk range. The carcinogenic risks of As and Cr(VI) contributed 60.98% and 26.77%, respectively, which were regarded as two key carcinogenic risk factors. Overall, the government policies and countermeasures for the PM_2.5 pollution control should be performed not only based on the PM_2.5 concentration but also based on the PM_2.5-bound heavy metals and their health risks for the local residents.

Heavy metal content and health risk assessment of atmospheric particles in China: A meta-analysis

In recent decades, China has devoted significant attention to the heavy metals pollution in particulate matter. However, the majority of studies have only focused on the field monitoring in relatively remote areas, which may not be representative of air quality across the country. This study reevaluated the characteristics, temporal and spatial changes, and health concerns associated with heavy metal pollution in atmospheric particulates on a national scale by coupling Meta-analysis and Monte Carlo simulation analysis. In terms of spatial distribution, the heavy metals pollution levels in the northern coast and northeastern regions are relatively high, whereas it is low along the middle Yellow River, middle Yangtze River, as well as Southwest. With the exception of Cu, the distribution of all elements in PM2.5 steadily decreased over time Moreover, PM10 and PM2.5 performed similar where Cd and Ni both first increased followed by a decline while, Cr displayed a decrease before it showed an increment. And since the implementation of prevention and control policies about the atmospheric release, the focus of industrial emission has gradually shifted from energy production and processing to living products manufacturing. Moreover, the carcinogenic risk was shown to be Cr > As, Pb > Ni, Cd, while the non-carcinogenic risk was as follows: As, Ni > Cr, Cd. Among all contaminants, Cd, As, and Cr in PM2.5 and PM10 exceeded the WHO standard in the cities with worst air quality. It was observed that As posed the largest non-carcinogenic risk to adults while, Cr caused the most carcinogenic risk to adults and children, where the carcinogenic risk of children remains higher than that of adults. Therefore, the findings of this study may offer data support to the China's heavy metal pollution standards in airborne particles and offer theoretical data support for pollution management.