ABSTRACT
Due to the significance of atmospheric HONO as a reservoir for radicals and the presence of substantial unknown sources of HONO, there is a pressing need for accurate and consistent measurement of its concentration. In this study, we compared the measurements obtained from the monitor for aerosols and gases in ambient air (MARGA) based on wet chemical method with those from the incoherent broadband cavity-enhanced absorption spectroscopy (IBBCEAS) based on optical method to assess the suitability of the MARGA instrument for accurate HONO detection. The diurnal patterns obtained by the two instruments are similar, with peaks at 8 a.m. and lows at 5 p.m. Over the course of the observation period, it was often observed that HONO concentrations recorded by the MARGA instrument consistently exceeded those obtained through the IBBCEAS technique, accounting for approximately 91.33% of the total observation time. Throughout the entire observation period, the R2 value between the two instruments was 0.49, indicating relatively good correlation. However, with a slope of only 0.27, it suggests poor agreement between the two instruments. Furthermore, the R2 and slopes between the two instruments vary with the seasons and day-night. The larger the quartile values of NO2, NH3, and BC, the greater the slopes of both MARGA and IBBCEAS instruments, and the higher the concentrations of NO2, NH3, and BC (indicator of semivolatile oxidizable hydrocarbons), the greater the differences between the two instruments, all indicating that NH3 may promote the reaction of NO2 with semivolatile oxidizable hydrocarbons to produce HONO. The O3 with its strong oxidizing properties may cause underestimation in the MARGA instrument by oxidizing NO2- to NO3- in the absorbing solution. It is challenging to derive a universal correction formula due to the interference of various chemical substances. Hence, MARGA should not be used for HONO research in the future.
Subject(s)
Air Pollutants , Environmental Monitoring , Air Pollutants/analysis , Environmental Monitoring/methods , Environmental Monitoring/instrumentation , Atmosphere/chemistry , Cities , Aerosols/analysis , Seasons , Nitrous Acid/analysisABSTRACT
Fine particulates in city air significantly impact human health, but the hazardous compositional mechanisms are still unclear. Besides the toxicity of environmental PM2.5 to in vitro human lung epithelial cells (A549), the independent cytotoxicity of PM2.5-bound water-soluble (WS-PM2.5) and water-insoluble (WIS-PM2.5) fractions were also compared by cell viability, oxidative stress (reactive oxygen species, ROS), and inflammatory injury (IL-6 and TNF-α). The cytotoxicity of PM2.5 varied significantly by sampling season and place, with degrees greater in winter and spring than in summer and autumn, related to corresponding trend of air PM2.5 level, and also higher in industrial than urban site, although their PM2.5 pollution levels were comparable. The PM2.5 bound metals (Ni, Cr, Fe, and Mn) may contribute to cellular injury. Both WS-PM2.5 and WIS-PM2.5 posed significant cytotoxicity, that WS-PM2.5 was more harmful than WIS-PM2.5 in terms of decreasing cell viability and increasing inflammatory cytokines production. In particular, industrial samples were usually more toxic than urban samples, and those from summer were generally less toxic than other seasons. Hence, in order to mitigate the health risks of PM2.5 pollution, the crucial targets might be components of heavy metals and soluble fractions, and sources in industrial areas, especially during the cold seasons.
Subject(s)
Air Pollutants , Cell Survival , Lung , Particulate Matter , Reactive Oxygen Species , Humans , Particulate Matter/toxicity , Cell Survival/drug effects , Air Pollutants/toxicity , A549 Cells , Lung/drug effects , Lung/cytology , Reactive Oxygen Species/metabolism , Tumor Necrosis Factor-alpha/metabolism , Solubility , Interleukin-6/metabolism , Oxidative Stress/drug effects , Water/chemistry , SeasonsABSTRACT
Exposure to ozone has been associated with metabolic disorders in humans, but the underlying mechanism remains unclear. In this study, the role of the gut-liver axis and the potential mechanism behind the metabolic disorder were investigated by histological examination, microbiome and metabolome approaches in mice during the subacute (4-week) and subchronic (12-week) exposure to 0.5 ppm and 2.5 ppm ozone. Ozone exposure resulted in slowed weight gain and reduced hepatic lipid contents in a dose-dependent manner. After exposure to ozone, the number of intestinal goblet cells decreased, while the number of tuft cells increased. Tight junction protein zonula occludens-1 (ZO-1) was significantly downregulated, and the apoptosis of epithelial cells increased with compensatory proliferation, indicating a compromised chemical and physical layer of the intestinal barrier. The hepatic and cecal metabolic profiles were altered, primarily related to lipid metabolism and oxidative stress. The abundance of Muribaculaceae increased dose-dependently in both colon and cecum, and was associated with the decrease of metabolites such as bile acids, betaine, and L-carnitine, which subsequently disrupted the intestinal barrier and lipid metabolism. Overall, this study found that subacute and subchronic exposure to ozone induced metabolic disorder via disturbing the gut-liver axis, especially the intestinal barrier. These findings provide new mechanistic understanding of the health risks associated with environmental ozone exposure and other oxidative stressors.
Subject(s)
Microbiota , Ozone , Humans , Mice , Animals , Liver/metabolism , Metabolome , Lipids , Ozone/toxicityABSTRACT
Surface ozone pollution under climate warming has become a serious environmental issue. In the summer of 2022, abnormal warming spread over most of the Northern Hemisphere and resulted in the abnormal increase in O3 concentrations. In this study, we focused on the coastal cities in China and investigated the O3 trends in July during 2015 to 2022. Four regions with different locations and emission levels were selected for comparison. A significant increase of O3 concentration in July 2022 were observed in the southern coastal cities (16.7-22.8 µg m-3) while the opposite characteristics were found in the northern coastal cities (decrease of 0.26-2.18 µg m-3). The results indicated various distribution patterns of the O3 concentrations responded to heat wave across China. The weakening of East Asian summer monsoon, extension of the western Pacific subtropical high, significant warming, stronger solar radiation, lower relative humidity, less rainfall and sinking motion of atmosphere in 2022 were beneficial for O3 generation and accumulation in the southern coastal areas. Meteorological changes in July 2022 could lead to an increase of 15.6 % in O3 concentrations in southern coastal cities compared to that in 2015-2021, based on the analysis of machine learning. Air temperature was the main contributor to high O3 concentrations in the coast of Fujian province, while other coastal cities depended on relative humidity. This study indicated the challenge of O3 pollution control in coastal areas under global warming, especially in extreme heat wave events.
ABSTRACT
China faces a dual challenge of improving air quality and reducing greenhouse gas (GHG) emissions. Stringent clean air actions gradually narrow the end-of-pipe (EOP) pollution control potential. Meanwhile, pursuing carbon peaking will reduce air pollution and health risks. However, the impact on air quality and health gains in individual Chinese provinces has not been assessed with a specific focus on local policies. Here, typical shared socio-economic pathways (SSPs) and local policies (i.e., business as usual, BAU; end-of-pipe controls, EOP; co-control mitigation, CCM) are combined to set three scenarios (i.e., BAU-SSP3, EOP-SSP4, CCM-SSP1). Under these three scenarios, we couple the Low Emissions Analysis Platform (LEAP) model, an air quality model and health risk assessment methodology to evaluate the characteristics of carbon peaking in Fujian Province. PM2.5 air quality and impacts on public health are assessed, using the metric of the deaths attributable to PM2.5 pollution (DAPP). The results show that energy-related CO2 emissions will only peak before 2030 in the CCM-SSP1 scenario. In this context, air pollutant emission pathways reveal that mitigation is limited under the EOP-SSP4 scenario, necessitating further mitigation under the CCM-SSP1 scenario. The annual average PM2.5 level is projected to be 16.5 µg·m-3 in 2035 with a corresponding decrease in DAPP of 297 (95 % confidence intervals: 217-308) compared with that of 2020. Despite the significant improvements in PM2.5 air quality and health gains under the CCM-SSP1 scenario, reaching the 5 µg·m-3 target of the World Health Organization (WHO) remains difficult. Furthermore, population aging will require stronger PM2.5 mitigation to enhance health gains. This study provides a valuable reference for other developing regions to co-control air pollution and GHGs.
Subject(s)
Air Pollutants , Air Pollution , Particulate Matter/analysis , Carbon/analysis , Air Pollution/analysis , Air Pollutants/analysis , ChinaABSTRACT
Atmospheric particles have profound implications for the global climate and human health. Among them, ultrafine particles dominate in terms of the number concentration and exhibit enhanced toxic effects as a result of their large total surface area. Therefore, understanding the driving factors behind ultrafine particle behavior is crucial. Machine learning (ML) provides a promising approach for handling complex relationships. In this study, three ML models were constructed on the basis of field observations to simulate the particle number concentration of nucleation mode (PNCN). All three models exhibited robust PNCN reproduction (R2 > 0.80), with the random forest (RF) model excelling on the test data (R2 = 0.89). Multiple methods of feature importance analysis revealed that ultraviolet (UV), H2SO4, low-volatility oxygenated organic molecules (LOOMs), temperature, and O3 were the primary factors influencing PNCN. Bivariate partial dependency plots (PDPs) indicated that during nighttime and overcast conditions, the presence of H2SO4 and LOOMs may play a crucial role in influencing PNCN. Additionally, integrating additional detailed information related to emissions or meteorology would further enhance the model performance. This pilot study shows that ML can be a novel approach for simulating atmospheric pollutants and contributes to a better understanding of the formation and growth mechanisms of nucleation mode particles.
Subject(s)
Air Pollutants , Humans , Air Pollutants/analysis , Particle Size , Pilot Projects , Environmental Monitoring/methods , Particulate Matter/analysisABSTRACT
To gain a comprehensive understanding of sources and health risks of trace elements in an area of China with high population densities and low PM2.5 concentrations, 15 trace elements (Al, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, As, Sn, Ba, Pb) in PM2.5 were monitored from December 2020 to November 2021 in a representative city, Xiamen. The concentrations of trace elements in Xiamen displayed an obvious seasonal variation and were dominated by K, Fe, Al, Ca and Zn. Based on Positive Matrix Factorization analysis, source appointment revealed that the major sources of trace elements in Xiamen were traffic, dust, biomass and firework combustion, industrial manufacture and shipping emission. According to health risk assessment combined with the source appointment results, it indicated that the average noncarcinogenic risk was below the threshold and cancer risk of four hazardous metals (Cr, Ni, As, Pb) exceeded the threshold (10-6). Traffic-related source had almost half amount of contribution to the health risk induced by PM2.5-bound trace elements. During the dust transport period or Spring Festival period, the health risks exceeded an acceptable threshold even an order of magnitude higher, suggesting that the serious health risks still existed in low PM2.5 environment at certain times. Health risk assessment reminded that the health risk reduction in PM2.5 at southeastern China should prioritize traffic-related hazardous trace elements and highlighted the importance of controlling vehicles emissions in the future.
Subject(s)
Air Pollutants , Trace Elements , Particulate Matter/analysis , Air Pollutants/analysis , Trace Elements/analysis , Lead/analysis , Environmental Monitoring , Dust/analysis , ChinaABSTRACT
Airborne microorganisms, including pathogens, would change with surrounding environments and become issues of global concern due to their threats to human health. Microbial communities typically contain a few abundant but many rare species. However, how the airborne abundant and rare microbial communities respond to environmental changes is still unclear, especially at hour scale. Here, we used a sequencing approach based on bacterial 16S rRNA genes and fungal ITS2 regions to investigate the high time-resolved dynamics of airborne bacteria and fungi and to explore the responses of abundant and rare microbes to the atmospheric changes. Our results showed that air pollutants and microbial communities were significantly affected by human activities related to the Chinese New Year (CNY). Before CNY, significant hour-scale changes in both abundant and rare subcommunities were observed, while only abundant bacterial subcommunity changed with hour time series during CNY. Air pollutants and meteorological parameters explained 61.5%-74.2% variations of abundant community but only 13.3%-21.6% variations of rare communities. These results suggested that abundant species were more sensitive to environmental changes than rare taxa. Stochastic processes predominated in the assembly of abundant communities, but deterministic processes determined the assembly of rare communities. Potential bacterial pathogens during CNY were the highest, suggesting an increased health risk of airborne microbes during CNY. Overall, our findings highlighted the "holiday effect" of CNY on airborne microbes and expanded the current understanding of the ecological mechanisms and health risks of microbes in a changing atmosphere.