Response of PM2.5-bound elemental species to emission variations and associated health risk assessment during the COVID-19 pandemic in a coastal megacity

Influence of sources and atmospheric processes on metal solubility in PM2.5 in urban Guangzhou, South China

Water-soluble metals exert a significant influence on human and ecosystem health. In this study, a comprehensive investigation was undertaken to elucidate the solubilities of metals in PM2.5 and potential influencing factors during the dry season of 2019-2020 in urban Guangzhou, South China. The observed average solubility was <20 % for Al, Fe, Sn, and Ti; 20-40 % for V, Cr, Sb, Pb, and Ni; 40-60 % for Ba and Cu; and 60-80 % for Zn, As, Se, Cd, and Mn. Metals (Al, Ti, and Fe) originated from crustal sources (e.g., soil dust) have much lower solubilities than those (Mn, Zn, As, Se, Cd, and Ba) from fossil fuel combustion sources (e.g., traffic emission, coal combustion), suggesting the dominant role the metal sources played on solubility. Enhanced solubilities of Cu, As, Se, Cd, Sn, Sb, and Pb were associated with aerosol acidity, while those of V, Cr, Mn, Ni, Zn, and Ba were linked to organic acid complexation. For the three crustal metals, the solubilities of Al and Ti primarily depended on aerosol acidity, whereas the solubility of Fe depended on both aerosol acidity under pH < 2 conditions and organic acid complexation under pH > 2 conditions. These findings underscore the primary influence of inherent properties of the metals on their solubility and reveal the varying impacts of atmospheric physicochemical processes, with changes in their solubilities being <10 % for Cd, Sn, Sb, and Pb, 10-20 % for Cu, Cr, Mn, Ni, and Ba, and 20-30 % for As, Se, and Zn.

Intelligent technologies powering clean incineration of municipal solid waste: A system review

Cleanliness has been paramount for municipal solid waste incineration (MSWI) systems. In recent years, the rapid advancement of intelligent technologies has fostered unprecedented opportunities for enhancing the cleanliness of MSWI systems. This paper offers a review and analysis of cutting-edge intelligent technologies in MSWI, which include process monitoring, intelligent algorithms, combustion control, flue gas treatment, and particulate control. The objective is to summarize current applications of these techniques and to forecast future directions. Regarding process monitoring, intelligent image analysis has facilitated real-time tracking of combustion conditions. For intelligent algorithms, machine learning models have shown advantages in accurately forecasting key process parameters and pollutant concentrations. In terms of combustion control, intelligent systems have achieved consistent prediction and regulation of temperature, oxygen content, and other parameters. Intelligent monitoring and forecasting of carbon monoxide and dioxins for flue gas treatment have exhibited satisfactory performance. Concerning particulate control, multi-objective optimization facilitates the sustainable utilization of fly ash. Despite remarkable progress, challenges remain in improving process stability and monitoring instrumentation of intelligent MSWI technologies. By systematically summarizing current applications, this timely review offers valuable insights into the future upgrade of intelligent MSWI systems.

Insight study of rare earth elements in PM2.5 during five years in a Chinese inland city: Composition variations, sources, and exposure assessment

The booming development of rare earth industry and the extensive utilization of its products accompanied by urban development have led to the accelerated accumulation of rare earth elements (REEs) as emerging pollutants in atmospheric environment. In this study, the variation of REEs in PM2.5 with urban (a non-mining city) transformation was investigated through five consecutive years of sample collection. The compositional variability and provenance contribution of REEs in PM2.5 were characterized, and the REEs exposure risks of children and adults via inhalation, ingestion and dermal absorption were also evaluated. The results showed an increase in the total REEs concentration from 46.46 ± 35.16 mg/kg (2017) to 81.22 ± 38.98 mg/kg (2021) over the five-year period, with Ce and La making the largest contribution. The actual increment of industrial and traffic emission source among the three pollution sources was 1.34 ng/m3. Coal combustion source displayed a downward trend. Ingestion was the main exposure pathway for REEs in PM2.5 for both children and adults. Ce contributed the most to the total intake of REEs in PM2.5 among the population, followed by La and Nd. The exposure risks of REEs in PM2.5 in the region were relatively low, but the trend of change was of great concern. It was strongly recommended to strengthen the concern about traffic-related non-exhaust emissions of particulate matter.

Elemental composition of atmospheric PM10 during COVID-19 lockdown and recovery periods in Moscow (April-July 2020)

Changes in the concentrations of PM10-bound potentially toxic elements (PTEs) during the COVID-19 lockdown period and after the revocation of restrictions were analyzed using the data received at the Aerosol Complex of Moscow State University in April-July 2020. During the lockdown, the input of biomass combustion products enriched in PTEs from the Moscow region hindered the decrease in pollutant concentrations. After the introduction of the self-isolation regime, lower concentrations of most PTEs occurred due to the decrease in anthropogenic activity and the rainy meteorological conditions. After the revocation of restrictive measures, the PTE concentrations began to increase. Multivariate statistical analysis (APCA-MLR) identified the main sources of atmospheric pollutants as urban dust, non-exhaust traffic emissions, and combustion and exhaust traffic emissions. PM10 particles were significantly enriched with Sb, Cd, Sn, Bi, S, Pb, Cu, Mo, and Zn. The total non-carcinogenic and carcinogenic risks, calculated according to the U.S. EPA model, decreased by 24% and 23% during the lockdown; after the removal of restrictions, they increased by 61% and 72%, respectively. The study provides insight into the PTE concentrations and their main sources at different levels of anthropogenic impact.

High time-resolution source apportionment and health risk assessment for PM2.5-bound elements at an industrial city in northwest China

To better respond to heavy air pollution, the local government of Baoji City, a traditionally industry dominated city in northwest China, released several warning levels between December 2019 and January 2020. The system aims to provide a more efficient control of pollution sources. In this study, a high-time resolution measurement of PM_2.5-bound elements was applied to capture the diurnal-scale dynamic processes associated with major pollution activities in northwest China. A series of elements were quantified and used for source apportionment using the positive matrix factorization (PMF) model. Combined with the local characteristics, nine sources were resolved with contributions in descending order: fugitive dust (36.6 %), biomass burning (20.1 %), traffic-related (10.4 %), coal combustion (10.0 %), titanium alloy smelting (7.2 %), As-related industry (6.9 %), Zn-related industry (5.6 %), molybdenum alloy smelting (2.5 %), and Cr-related industry (0.7 %). The health risk assessment indicated non-carcinogenic risks for Mn and carcinogenic risks for As and Cr in both adults and children. The cumulative non-carcinogenic risk for the elements was 3.2 times the safety threshold, while the carcinogenic risk (CR) was 6.8 and 27 times the acceptable levels for children and adults, respectively. For source-resolved risks, As- and Cr-related industry emissions showed the highest carcinogenic risk. Five of the nine resolved sources for adults have CR values 1.4 and 9.7 times the acceptable level. This study provides valuable information for developing targeted strategies to control air pollutants and protect public health.