Comparison of indoor and outdoor oxidative potential of PM2.5: pollution levels, temporal patterns, and key constituents

Spatiotemporal distribution of oxidative potential in PM2.5 and its key components across six Chinese cities

Increasing evidence has supported that oxidative potential (OP) serves as a crucial indicator of health risk of exposure to PM2.5 over mass concentration. However, there is a lack of comparative studies across multiple cities, particularly on a fine temporal scale. In this study, we aim to investigate daily variation of ambient PM2.5 OP through simultaneous samplings in six Chinese cities for one year. Results showed that more than 60 % of the sampling days exhibited non-zero ranking difference between volume-normalized oxidative potential (OPv) and mass concentration among the six cities. Key components contributing to OPv inculde Mn, NO3-, and K+, followed by Ca2+, Al, SO42-, Cl-, Fe, and NH4+. Based on these chemical components, we developed a stepwise multivariable linear regression model (R2: 0.71) for OPv prediction. The performance of the model is comparable to both species- and sources-based ones in the literature. These findings suggest that a relatively lower daily-averaged mass concentration of PM2.5 does not necessarily indicate a lower oxidative risk. Future studies and policy developments on health benefits should also consider OPv rather than mass concentration alone. Priority could be given to sources/species that contribute significantly to oxidative potential of ambient PM2.5. SYNOPSIS: This study highlights inclusion of oxidative potential as a complementary metric for air pollution assessment and control.

Oxidative potential associated with reactive oxygen species of size-resolved particles: The important role of the specific sources

Oxidative potential (OP) is a predictor of particulate matter (PM) toxicity. Size-resolved PM and its components that influence OP values can be generated from several sources. However, There is little research have attempted to determine the PM toxicity generated from specific sources. This paper studied the OP characterization and reactive oxygen species (ROS) formation of particles from specific sources and their effects on human health. OP associated with ROS of size-resolved particles was analyzed by using dithiothreitol (DTT) method and electron paramagnetic resonance (EPR) spectroscopy technology. And OP and ROS deposition of specific source PM were calculated for health through the Multi-path particle deposition (MPPD) model. The results evidenced that the highest water-soluble OP (OPws) from traffic sources (OPm: 104.50 nmol min-1·ug-1; OPv: 160.15 nmol min-1·m-3) and the lowest from ocean sources (OPm: 22.25 nmol⋅min-1⋅ug-1; OPv: 54.16 nmol min-1·m-3). The OPws allocation in PM from different sources all have a unimodal pattern range from 0.4 to 3.2 μm. ROS (·OH) displayed the uniform trend as PM OPws, indicating that PM< 3.2 is the major contributor to adverse health impacts for size-resolved PM because of its enhanced oxidative activity compared with PM> 3.2. Furthermore, this study predicted the DTT consumption of PM were assigned to different components. Most DTT losses are attributed to the transition metals. For specific sources, transition metals dominates DTT losses, accounting for 38%-80% of DTT losses from different sources, followed by Hulis-C, accounting for 1%-10%. MPPD model calculates that over 66% of pulmonary DTT loss comes by PM< 3.2, and over 71% of pulmonary ROS generation from PM< 3.2. Among these sources of pollution, traffic emissions are the primary contributors to reactive oxygen species (ROS) in environmental particulate matter (PM). Therefore, emphasis should be placed on controlling traffic emissions, especially in coastal areas.

Size-distribution and driving factors of aerosol oxidative potential in rural kitchen microenvironments of northeastern India

This study reports size-resolved dithiothreitol (DTT)-based oxidative potential (OP: total and water-soluble) in rural kitchens using liquefied petroleum gas (LPG), firewood (FW), and mixed biomass (MB) fuels in northeastern (NE) India. In comparison to LPG, volume-normalized total OP (OPtotal(v)DTT) was enhanced by a factor of ∼5 in biomass-using kitchens (74 ± 35 to 78 ± 42 nmol min-1 m-3); however, mass-normalized total OP (OPtotal(m)DTT) was similar between LPG and FW users and higher by a factor of 2 in MB-using kitchens. The water-insoluble OP (OPwi(v, m)DTT) fraction in OPtotal(v, m)DTT was greater than 50% across kitchens. Size distributions across kitchens and OPDTT categories ranged from unimodal to trimodal. OPws(v)DTT was driven by metals as well as organics across size fractions while OPwi(v)DTT was majorly constrained by metals with an increasing importance of organics in fine particles of biomass-using kitchens. Multiple linear regression analysis revealed that Cu and Ba explained 71% of the OPtotal(v)DTT variability in LPG-using kitchens, while water-soluble organic carbon (WSOC) and Ba were responsible for 44% variability in FW-using kitchens. Finally, the high internal dose of OPtotal(v)DTT (28-31 nmol min-1 m-3) in biomass-using kitchens established the severity of oxidative stress on the exposed population.

Chemical and oxidative properties of fine particulate matter from near-road traffic sources

The toxicity associated with the fine particulate matter (PM2.5) has not been well studied, particularly in relation to the emissions from on-road vehicles and other sources in low- and middle-income countries such as India. Thus, a study was conducted to examine the oxidative potential (OP) of PM2.5 at a roadside (RS) site with heavy vehicular traffic and an urban background (BG) site in Mumbai using the dithiothreitol (DTT) assay. Simultaneous gravimetric PM2.5 was measured at both sites and characterized for carbonaceous constituents and water-soluble trace elements and metals. Results depicted higher PM2.5, elemental carbon (EC), and organic carbon (OC) concentrations on the RS than BG (by a factor of 1.7, 4.6, and 1.2, respectively), while BG had higher water-soluble organic carbon (WSOC) levels (by a factor of 1.4) and a higher WSOC to OC ratio (86%), likely due to the dominance of secondary aerosol formation. In contrast, the measured OPDTTv at RS (8.9 ± 5.5 nmol/min/m3) and BG (8.1 ± 6.4 nmol/min/m3) sites were similar. However, OPDTTv at BG was higher during the afternoon, suggesting the influence of photochemical transformation on measured OPDTTv at BG. At RS, OC and redox-active metals (Cu, Zn, Mn, and Fe) were significantly associated with measured OP (p < 0.05), while at BG, WSOC was most strongly associated (p < 0.05). The coefficient of divergence (COD) for PM2.5, its chemical species, and OPDTTv was >0.2, indicating spatial heterogeneity between the sites, and differences in emission sources and toxicity. The estimated hazard index (HI) was not associated with OPDTTv, indicating that current PM2.5 mass regulations may not adequately capture the health effects of PM2.5. The study highlights the need for further studies examining PM2.5 toxicity and developing toxicity-based air quality regulations.

Change of Composition, Source Contribution, and Oxidative Effects of Environmental PM2.5 in the Respiratory Tract

Fine particulate matter is a leading air pollutant, and its composition profile relates to sources and health effects. The human respiratory tract hosts a warmer and more humid microenvironment in contrast with peripheral environments. However, how the human respiratory tract impacts the transformation of the composition of environmental PM2.5 once they are inhaled and consequently changes of source contribution and health effects are unknown. Here, we show that the respiratory tract can make these properties of PM2.5 reaching the lung different from environmental PM2.5. We found via an in vitro model that the warm and humid conditions drive the desorption of nitrate (about 60%) and ammonium (about 31%) out of PM2.5 during the inhalation process and consequently make source contribution profiles for respiratory tract-deposited PM2.5 different from that for environmental PM2.5 as suggested in 11 Chinese cities and 12 US cities. We also observed that oxidative potential, one of the main health risk causes of PM2.5, increases by 41% after PM2.5 travels through the respiratory tract model. Our results reveal that PM2.5 inhaled in the lung differs from environmental PM2.5. This work provides a starting point for more health-oriented source apportionment, physiology-based health evaluation, and cost-effective control of PM2.5 pollution.

Seasonal variation of driving factors of ambient PM2.5 oxidative potential in Shenzhen, China

Reactive oxygen species (ROS) play a central role in health effects of ambient fine particulate matter (PM_2.5). In this work, we screened for efficient and complementary oxidative potential (OP) measurements by comparing the response values of multiple chemical probes (OP^DTT, OP^OH, OP^GSH) to ambient PM_2.5 in Shenzhen, China. Combined with meteorological condition and PM_2.5 chemical composition analysis, we explored the effects of different chemical components and emission sources on the ambient PM_2.5 OP and analyzed their seasonal variations. The results show that OP_m^DTT(mass-normalized) and OP_m^GSH-SLF were highly correlated (r = 0.77). OP^DTT was mainly influenced by organic carbon, while OP^OH was highly dominated by heavy metals. The combination of OP^DTT and OP^OH provides an efficient and comprehensive measurement of OP. Temporally, the OPs were substantially higher in winter than in summer (1.4 and 4 times higher for OP_m^DTT and OP_m^OH, respectively). The long-distance transported biomass burning sources from the north dominated the OP^DTT in winter, while the ship emissions mainly influenced the summer OP. The OP_m^DTT increased sharply with the decrease of PM_2.5 mass concentration, especially when the PM_2.5 concentration was lower than 30 μg/m³. The huge differences in wind fields between the winter and summer cause considerable variations in PM_2.5 concentrations, components, and OP. Our work emphasizes the necessity of long-term, multi-method, multi-component assessment of the OP of PM_2.5.

Spatial and seasonal variations in the carbon and lead isotopes of PM2.5 in air of residential buildings and their applications for source identification

To understand isotope distributions of PM_2.5 in residential buildings and apply them for source identification, carbon (δ¹³C) and lead (Pb) isotope ratios in indoor and outdoor air of residential buildings were analyzed. Moreover, factor analysis (FA) was employed to investigate sources, which were compared through isotopic analyses. The average δ¹³C values of indoor air are -26.94 ± 1.22‰ and -27.04 ± 0.44‰ in warm (August to October) and cold (February to March) seasons, respectively, and the corresponding values for outdoor air are -26.77 ± 0.54‰ and -26.57 ± 0.39‰. The average ²⁰⁶Pb/²⁰⁷Pb (²⁰⁸Pb/²⁰⁷Pb) ratios of indoor air are 1.1584 ± 0.0091 (2.4309 ± 0.0125) and 1.1529 ± 0.0032 (2.4227 ± 0.0081) in warm and cold seasons, respectively, and the corresponding values for outdoor air are 1.1594 ± 0.0069 (2.4374 ± 0.0103) and 1.1538 ± 0.0077 (2.4222 ± 0.0085). Seasonal variation in δ¹³C values or Pb isotope ratios of indoor air was not significant, and similar results were obtained for outdoor air. Significant differences were not observed between δ¹³C values or Pb isotope ratios of indoor and outdoor air. Traffic emission is the major contributor to indoor and outdoor PM_2.5 based on isotopic analyses; this result was consistent with the results of FA. The δ¹³C values of indoor air in buildings with poor ventilation conditions were significantly lighter than those of outdoor air. In summary, the spatial and seasonal variations of isotopes were similar in residential buildings, which can be used to identify sources of indoor PM_2.5, and ventilation condition is an influencing factor.

Chemical characterization, formation mechanisms and source apportionment of PM2.5 in north Zhejiang Province: The importance of secondary formation and vehicle emission

PM_2.5 affects air quality, therefore, chemical evolution, formation mechanism and source identification of PM_2.5 are essential to help figure out mitigation measures. PM_2.5 and its constituents were comprehensively characterized with highly time-resolved measurements from 2019 to 2020 in north Zhejiang Province (Shanxi, SX) for the first time, with an emphasis on the contribution of secondary formation and vehicle emission to PM_2.5. Secondary inorganic ions (sulfate: 3.86 μg/m³, nitrate: 7.82 μg/m³ and ammonium: 4.59 μg/m³, SNA) were found to be the major components (54%) in PM_2.5 (29.70 μg/m³). The highly consistence of nitrate, sulfate and secondary organic compounds (SOC) with Ox (NO₂ + O₃) or RH indicated the importance of photochemical oxidation and heterogeneous reaction in different scenarios. Higher atmospheric oxidative potential facilitated the SOC formation in spring. The PM_2.5 mass was apportioned to eight sources resolved by positive matrix factorization (PMF): secondary nitrate (9.63 μg/m³), secondary sulfate (5.14 μg/m³), vehicle emission (7.26 μg/m³), coal combustion (2.39 μg/m³), biomass burning (1.38 μg/m³), soil dust (0.86 μg/m³), industry emission (0.50 μg/m³), and ship emission (0.32 μg/m³). Secondary nitrate (35%) and sulfate (19%) formation and vehicle emission (26%) were the main factors contributing to the PM_2.5. Furthermore, the contribution of secondary nitrate formation increased with elevating PM_2.5 concentration. Regional transport was synthetically studied by chemical and backward trajectory analysis, reflecting that secondary nitrate contributed severely to the air quality at SX, while vehicle emission contribution enhanced when atmosphere was stagnant. This study first provides long-term comprehensive chemical characterization and source apportionments of PM_2.5 pollution in north Zhejiang, which may provide some guidance for the air pollution control.

Air Pollution and Pediatric Respiratory Hospitalizations: Effect Modification by Particle Constituents and Oxidative Potential

Rationale: Outdoor particulate and gaseous air pollutants impair respiratory health in children, and these associations may be influenced by particle composition. Objectives: To examine whether associations between short-term variations in fine particulate air pollution, oxidant gases, and respiratory hospitalizations in children are modified by particle constituents (metals and sulfur) or oxidative potential. Methods: We conducted a case-crossover study of 10,500 children (0-17 years of age) across Canada. Daily fine particle mass concentrations and oxidant gases (nitrogen dioxide and ozone) were collected from ground monitors. Monthly estimates of fine particle constituents (metals and sulfur) and oxidative potential were also measured. Conditional logistic regression models were used to estimate associations between air pollutants and respiratory hospitalizations, above and below median values for particle constituents and oxidative potential. Measurements and Main Results: Lag-1 fine particulate matter mass concentrations were not associated with respiratory hospitalizations (odds ratio and 95% confidence interval per 10 μg/m³ increase in fine particulate matter: 1.004 [0.955-1.056]) in analyses ignoring particle constituents and oxidative potential. However, when models were examined above or below median metals, sulfur, and oxidative potential, positive associations were observed above the median. For example, the odds ratio and 95% confidence interval per 10 μg/m³ increase in fine particulate matter were 1.084 (1.007-1.167) when copper was above the median and 0.970 (0.929-1.014) when copper was below the median. Similar trends were observed for oxidant gases. Conclusions: Stronger associations were observed between outdoor fine particles, oxidant gases, and respiratory hospitalizations in children when metals, sulfur, and particle oxidative potential were elevated.

Inter-annual variability of source contributions to PM10, PM2.5, and oxidative potential in an urban background site in the central mediterranean

Airborne particulate matter (PM) is studied because of its effects on human health and climate change. PM long-term characterisation allows identifying trends and evaluating the outcomes of environmental protection policies. This work is aimed to study the inter-annual variability of PM_2.5 and PM₁₀ concentrations and chemical composition in an urban background site (Italy). A dataset of daily PM_2.5 and PM₁₀ was collected in the period 2016-2017, including the content of OC, EC, major water-soluble ions, main metals, and compared to a similar dataset collected in the period 2013-2014. Oxidative potential using DTT assay (dithiothreitol) was evaluated and expressed in DTT_V as 0.39 nmol/min·m³ in PM₁₀ and 0.29 in PM_2.5 nmol/min·m³. PM source apportionment was computed using the EPA PMF5.0 model and source contributions compared with those of a previous dataset collected between 2013 and 2014. Multi linear regression analysis identified which source contributed (p < 0.05) to the oxidative potential of each size fraction. Inter-annual trends were more evident on PM_2.5 with reductions of biomass burning contribution and increases in traffic contribution in the 2016-2017 period. Crustal contributions were similar for the two periods, in both size fractions. Carbonates were comparable in PM₁₀ with a slight increase in PM_2.5. Sea spray decreased in PM₁₀. The DTT_V of PM_2.5 peaked during cold periods, while, the DTT_V of the PM_10-2.5 fraction peaked in summer, suggesting that different sources, with different seasonality, influence OP in the PM_2.5 and PM_10-2.5 fractions. Analysis showed that sea spray, crustal, and carbonates sources contribute ∼13.6% to DTT_V in PM_2.5 and ∼62.4% to DTT_V in PM_10-2.5. Combustion sources (biomass burning and traffic) contribute to the majority of DTT_V (50.6%) in PM_2.5 and contribute for ∼26% to DTT_V in PM_10-2.5. Secondary nitrate contributes to DTT_V in both fine and coarse fraction; secondary sulphate contribute to DTT_V in PM_2.5 with negligible contributions to DTT_V in PM_10-2.5.