Nitrogen dioxide (NO₂) is an important air pollutant and highly related to air quality, short- and long-term health effects, and even climate. A national model was developed using the extreme gradient boosting algorithm with high-resolution tropospheric vertical column NO₂ densities from the Sentinel-5 Precursor/Tropospheric Monitoring Instrument and general meteorological variables as input to generate daily mean surface NO₂ concentrations across mainland China. Model-derived daily NO₂ estimates were high accuracy with sample-based cross-validation coefficient of determination of 0.83, a root-mean-square error of 7.58 μg/m³, a mean prediction error of 5.56 μg/m³, and a mean relative prediction error of 18.08%. It has good performance in NO₂ estimations at both regional and individual site scale. The model also performed well in terms of estimating monthly, seasonal, and annual mean NO₂ concentrations across China. The model performance appears to better than or comparable to most previous related studies. The seasonal and annual spatial distributions of surface NO₂ across China and several regional NO₂ hotspots in 2019 were derived from the model and analyzed. Also evaluated were the population exposure levels of NO₂ for cities in and provinces of China. At the national scale, about 12% of the population experienced annual mean NO₂ concentrations exceeding the Chinese national air quality standard. The nationwide model with conventional predictors developed here can derive high-resolution surface NO₂ concentrations across China routinely, benefitting air epidemiological and environmental related studies.

Nitrogen dioxide (NO₂) is an important air pollutant that causes direct harms to the environment and human health. Ground NO₂ mapping with high spatiotemporal resolution is critical for fine-scale air pollution and environmental health research. We thus developed a spatiotemporal regression kriging model to map daily high-resolution (3-km) ground NO₂ concentrations in China using the Tropospheric Monitoring Instrument (TROPOMI) satellite retrievals and geographical covariates. This model combined geographically and temporally weighted regression with spatiotemporal kriging and achieved robust prediction performance with sample-based and site-based cross-validation R² values of 0.84 and 0.79. The annual mean and standard deviation of ground NO₂ concentrations from June 1, 2018 to May 31, 2019 were predicted to be 15.05 ± 7.82 μg/m³, with that in 0.6% of China’s area (10% of the population) exceeding the annual air quality standard (40 μg/m³). The ground NO₂ concentrations during the coronavirus disease (COVID-19) period (January and February in 2020) was 14% lower than that during the same period in 2019 and the mean population exposure to ground NO₂ was reduced by 25%. This study was the first to use TROPOMI retrievals to map fine-scale daily ground NO₂ concentrations across all of China. This was also an early application to use the satellite-estimated ground NO₂ data to quantify the impact of the COVID-19 pandemic on the air pollution and population exposures. These newly satellite-derived ground NO₂ data with high spatiotemporal resolution have value in advancing environmental and health research in China.

Poor air quality is an emerging problem in Australia primarily due to ozone pollution events and lengthening and more severe wildfire seasons. A significant deterioration in air quality was experienced in Australia’s most populous cities, Melbourne and Sydney, as a result of fires during the so-called Black Summer which ran from November 2019 through to February 2020. Following this period, social, mobility and economic restrictions to curb the spread of the COVID-19 pandemic were implemented in Australia. We quantify the air quality impact of these contrasting periods in the south-eastern states of Victoria and New South Wales (NSW) using a meteorological normalisation approach. A Random Forest (RF) machine learning algorithm was used to compute baseline time series’ of nitrogen dioxide (NO₂), ozone (O₃), carbon monoxide CO and particulate matter with diameter < 2.5 μm (PM₂.₅), based on a 19 year, detrended training dataset. Across Victorian sites, large increases in CO (188%), PM₂.₅ (322%) and ozone (22%) were observed over the RF prediction in January 2020. In NSW, smaller pollutant increases above the RF prediction were seen (CO 58%, PM₂.₅ 80%, ozone 19%). This can be partly explained by the RF predictions being high compared to the mean of previous months, due to high temperatures and strong wind speeds, highlighting the importance of meteorological normalisation in attributing pollution changes to specific events. From the daily observation-RF prediction differences we estimated 249.8 (95% CI: 156.6–343.) excess deaths and 3490.0 (95% CI 1325.9–5653.5) additional hospitalisations were likely as a result of PM₂.₅ and O₃ exposure in Victoria and NSW. During April 2019, when COVID-19 restrictions were in place, on average NO₂ decreased by 21.5 and 8% in Victoria and NSW respectively. O₃ and PM₂.₅ remained effectively unchanged in Victoria on average but increased by 20 and 24% in NSW respectively, supporting the suggestion that community mobility reduced more in Victoria than NSW. Overall the air quality change during the COVID-19 lockdown had a negligible impact on the calculated health outcomes.

Pollen allergens, widely present in the atmosphere, are the main cause of seasonal respiratory diseases that affect millions of people worldwide. Although previous studies have reported that nitrogen dioxide (NO₂) and ozone (O₃) promote pollen allergy, the specific biological processes and underlying mechanisms remain less understood. In this study, Platanus pollen grains were exposed to gaseous pollutants (NO₂ and O₃). We employed environmental electron microscopy, flow cytometry, western blot assay, enzyme-linked immunoassay, ultraviolet absorption spectrometry, circular dichroism, and protein mass spectrometry to characterise the subpollen particles (SPPs) released from pollen grains. Furthermore, we determined the immunogenicity and pathogenicity induced by Platanus pollen allergen a 3 (Pla a 3). Our results demonstrated that NO₂ and O₃ could damage the pollen cell membranes in SPPs and increase the amount of Pla a 3 allergen released into the atmosphere. Additionally, NO₂ and O₃ altered the structure of Pla a3 protein through nitrification and oxidation, which not only enhanced the immunogenicity of allergens but also increased the stability of the protein. In vivo analysis using an animal model indicated that NO₂ and O₃ greatly aggravated pollen-induced pneumonia. Thus, our study provides guidance for the prevention of pollen allergic diseases.

Children’s respiratory health are particularly vulnerable to outdoor air pollution, but evidence is lacking on the very acute effects of air pollution on the risk of acute upper respiratory infections (AURI) and acute lower respiratory infections (ALRI) in children. This study aimed to evaluate the risk of cause-specific AURI and ALRI, in children within 24 h of exposure to air pollution. We obtained data on emergency cases, including 11,091 AURI cases (acute pharyngitis, acute tonsillitis, acute obstructive laryngitis and epiglottitis, and unspecified acute upper respiratory infections) and 11,401 ALRI cases (pneumonia, acute bronchitis, acute bronchiolitis, unspecified acute lower respiratory infection) in Brisbane, Australia, 2013–2015. A time-stratified case-crossover analysis was used to examine the hourly association of AURI and ALRI with high concentration (95th percentile) of four air pollutants (particulate matters with aerodynamic diameter <10 μm (PM₁₀) and <2.5 μm (PM₂.₅), ozone (O₃), nitrogen dioxide (NO₂)). We observed increased risk of acute tonsillitis associated with PM₂.₅ within 13–24 h (odds ratio (OR), 1.45; 95% confidence interval [CI], 1.02–2.06) and increased risk of unspecified acute upper respiratory infections related to O₃ within 2–6 h (OR, 1.38, 95%CI, 1.12–1.70), NO₂ within 1 h (OR, 1.19; 95%CI, 1.01–1.40), and PM₂.₅ within 7–12 h (OR, 1.21; 95%CI, 1.02–1.43). Cold season and nigh-time air pollution has greater effects on AURI, whereas greater risk of ALRI was seen in warm season and daytime. Our findings suggest exposures to particulate and gaseous air pollution may transiently increase risk of AURI and ALRI in children within 24 h. Prevention measures aimed at protecting children’s respiratory health should consider the very acute effects of air pollution.

Both air pollution and dyslipidemias contributed to large number of deaths and disability-adjusted life lost years. Long-term air pollution exposure was related to changed blood lipids and risk of dyslipidemias. This study was designed to evaluate relationships between air pollutants, blood lipids and prevalence of dyslipidemias in a Chinese rural population exposed to high-level air pollution based on baseline data of The Henan Rural Cohort study. An amount of 39,057 participants from rural areas in China were included. The 3-year average exposure of air pollutants (PM2.5, PM10, NO2) was estimated by a spatiotemporal model. Logistic and linear regression models were employed to explore relationships between air pollutants, blood lipids (TC, TG, HDL-C and LDL-C) and prevalence of dyslipidemias. The three-year concentration of PM2.5, PM10 and NO2 was 72.8 ± 2.3 μg/m3, 131.5 ± 5.7 μg/m3and 39.1 ± 3.1 μg/m3, respectively. Overall, increased air pollution exposure was related to increased TC and LDL-C, while decreased TG and HDL-C. Each 1-μg/m3 increment of PM2.5 was related to 0.10% (0.07%–0.19%) increase in TC, 0.63% (0.50%–0.77%) increase in LDL-C, 2.93% (2.70%–3.16%) decrease in TG, 0.49% (0.38%–0.60%) decrease in HDL-C; and 5.7% (95%CI: 3.7%–7.6%), 4.0% (95%CI: 2.1%–6.0%) and 3.8% (95%CI: 2.5%–5.1%) increase in odds for hypercholesterolemia, hyperbetalipoproteinemia and hypoalphalipoproteinemia, respectively. Stronger associations were found in male and older participants. Findings suggest that air pollutants were associated with changed blood lipid levels and higher risk of dyslipidemias among rural population. Male and elder people should pay more attention to personal safety protection.

Exposure to air pollutants has been associated with respiratory and cardiovascular mortality, but the underlying molecular mechanisms remain inadequately understood. We aimed to examine molecular-level inflammatory and oxidative stress responses to personal air pollutant exposure. Fifty-three healthy adults aged 22–52 were measured three times for their blood inflammatory cytokines and urinary malondialdehyde (MDA, an oxidative stress biomarker) within 2 consecutive months. Pollutant concentrations monitored indoors and outdoors were combined with the time-activity data to calculate personal O₃, PM₂.₅, NO₂, and SO₂ exposures averaged over 12 h, 24 h, 1 week, and 2 weeks, respectively, prior to biospecimen collection. Inflammatory cytokines and MDA were associated with pollutant exposures using linear mixed-effects models controlling for various covariates. After adjusting for a co-pollutant, we found that concentrations of proinflammatory cytokines were significantly and negatively associated with 12-h O₃ exposures and significantly but positively associated with 2-week O₃ exposures. We also found significant and positive associations of proinflammatory cytokines with 12-h and 24-h NO₂ exposures, respectively. However, we did not find clear associations of PM₂.₅ and SO₂ exposure with proinflammatory cytokines and with MDA. The removal of an O₃-generating electrostatic precipitator in the mechanical ventilation systems of the offices and residences of the subjects was associated with significant decreases in IL-1β, IL-2, IL-6, IL-8, IL-17A, and TNF-α. These findings suggest that exposure to O₃ for different time durations may affect systemic inflammatory responses in different ways.

NO₂ oxidation of soot exhausted from engines is more efficient than O₂ under low-temperature conditions, and is crucial for diesel particulate filter to control soot pollution. To explore the principle behind accelerating soot oxidation by NO₂, this paper uses density functional theory to reveal soot oxidation process by NO₂. This study contributes to understanding rules of soot oxidation by NO₂ and perfecting soot oxidation models to develop soot emission control technologies. Results show that NO₂ oxidation of pyrene radical involves three steps. Firstly, NO₂ attacks the C∗ atom to form –C (NO₂) with reaction energy of 306.3 kJ/mol, which decomposes to produce a –C (O) compound. Secondly, another NO₂ molecule climbs over an energy barrier of 8.8 kJ/mol, and changes into a –C (ONO₂) intermediate on –C (O). Finally, the N or O atom of NO₂ attacks –C (O) for a second time to help open aromatic ring for releasing CO or CO₂. Further decomposition of –C (NO₂) and –C (ONO₂) requires activation energies of 81.6 kJ/mol, 75.7 kJ/mol, and 53.5 kJ/mol, respectively, on preferential pathways. Calculations prove that attacks of O atom from NO₂ on C∗ help open the aromatic ring more efficiently than N atom.

Via the thermal sintering, a nanocrystalline IrO₂ coating was formed on the Ti substrate to successfully prepare a Ti/IrO₂ electrode. Based on the electrochemical analysis, the prepared Ti/IrO₂ electrode was found to have powerful oxidation effect on the organics in the TNT red water, where the nitro compound was oxidized through an irreversible electrochemical process at 0.6 V vs. SCE. According to the analysis of the nitro compound content, the UV–vis spectra, and the FTIR spectra of 2,4,6-trinitrotoluene (TNT) red water with electrolytic periods, the degradation mechanism of the dinitrotoluene sulfonate (DNTS) was developed. And the intermediates were characterized by UPLC-HRMS. The DNTS mainly occurred one electron transfer reaction on the Ti/IrO₂ electrode. At the early stage of the electrolysis, the polymerization of DNTS was mainly dominated. The generated polymer did not form a polymer film on the electrode surface, but instead it promoted a further reduction. After electrolyzing for 30 h, all NO₂ function group in the TNT red water was degraded completely.

Emissions of major reactive nitrogen compounds, including nitric oxide (NO), nitrogen dioxide (NO₂) and ammonia (NH₃), from heavy-duty diesel vehicles (HDDVs) place substantial pressure on air quality for many large cities in China. To control nitrogen oxide (NOX) emissions from HDDVs, selective catalytic reduction (SCR) systems have been widely used since the China IV standards. To investigate the impacts of aftertreatment technologies and driving conditions on real-world emissions of reactive nitrogen compounds, a portable emissions measurement system was employed to test eighteen heavy-duty diesel trucks in China. The results showed that the China IV and China V HDDVs with appropriate SCR functionality could reduce NOX emissions by 36% and 53%, respectively, compared to the China III results, although their real-world emissions were still higher than the corresponding emission limits for regulatory engine tests. For these HDDVs, five samples were tested with NH₃ emissions, ranging from 1.67 ppm to 51.49 ppm. The NH₃ emission rates tended to significantly increase under high-speed driving conditions. The results indicate that the current SCR technology may have certain risks in exceeding the future China VI NH₃ limit. However, five China IV/V HDDVs were found to have SCR temperature sensors that were intentionally tampered with, resulting in comparable or even higher NOX emissions and zero NH₃ emissions. Increased NO₂ emissions due to the adoption of diesel oxidation catalysts and diesel particulate filters were also found from our experiments. This study highlights the importance of enhancing in-use compliance requirements and eliminating aftertreatment tampering for China IV and China V HDDVs.