Studies have linked gaseous air pollutants to multiple health effects via inflammatory pathways. Several major inflammatory biomarkers, including C-reactive protein (CRP), fibrinogen, interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) have also been considered as predictors of cardiovascular disease. However, there has been no meta-analysis to evaluate the associations between gaseous air pollutants and these typical biomarkers of inflammation to date. To evaluate the overall associations between short-term and long-term exposures to ambient ozone (O₃), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), carbon dioxide (CO) and major inflammatory biomarkers including CRP, fibrinogen, IL-6 and TNF-α. A meta-analysis was conducted for publications from PubMed, Web of Science, Scopus and EMBASE databases up to Feb 1st, 2021. The meta-analysis included 38 studies conducted among 210,438 participants. Generally, we only observed significant positive associations between short-term exposures to gaseous air pollutants and inflammatory biomarkers. For a 10 μg/m³ increase in short-term exposure to O₃, NO₂, and SO₂, there were significant increases of 1.05% (95%CI: 0.09%, 2.02%), 1.60% (95%CI: 0.49%, 2.72%), and 10.44% (95%CI: 4.20%, 17.05%) in CRP, respectively. Meanwhile, a 10 μg/m³ increase in NO₂ was also associated with a 4.85% (95%CI: 1.10%, 8.73%) increase in TNF-α. Long-term exposures to gaseous air pollutants were not statistically associated with these biomarkers, but the study numbers were relatively small. Subgroup analyses found more apparent associations in studies with better study design, higher quality, and smaller sample size. Meanwhile, the associations also varied across studies conducted in different geographical regions. Short-term exposure to gaseous air pollutants is associated with increased levels of circulating inflammatory biomarkers, suggesting that a systemic inflammatory state is activated upon exposure. More studies on long-term exposure to gaseous air pollutants and inflammatory biomarkers are warranted to verify the associations.

We provide a comprehensive and updated systematic review and meta-analysis of the association between air pollution exposure and depression, searching PubMed, Embase, and Web of Sciences for relevant articles published up to May 2021, and eventually including 39 studies. Meta-analyses were performed separately according to pollutant type [particulate matter with diameter ≤10 μm (PM₁₀) and ≤2.5 μm (PM₂.₅), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃), and carbon monoxide (CO)] and exposure duration [short- (<30 days) and long-term (≥30 days)]. Test for homogeneity based on Cochran's Q and I² statistics were calculated and the restricted maximum likelihood (REML) random effect model was applied. We assessed overall quality of pooled estimates, influence of single studies on the meta-analytic estimates, sources of between-study heterogeneity, and publication bias. We observed an increased risk of depression associated with long-term exposure to PM₂.₅ (relative risk: 1.074, 95% confidence interval: 1.021–1.129) and NO₂ (1.037, 1.011–1.064), and with short-term exposure to PM₁₀ (1.009, 1.006–1.012), PM₂.₅ (1.009, 1.007–1.011), NO₂ (1.022, 1.012–1.033), SO₂ (1.024, 1.010–1.037), O₃ (1.011, 0.997–1.026), and CO (1.062, 1.020–1.105). The publication bias affecting half of the investigated associations and the high heterogeneity characterizing most of the meta-analytic estimates partly prevent to draw very firm conclusions. On the other hand, the coherence of all the estimates after excluding single studies in the sensitivity analysis supports the soundness of our results. This especially applies to the association between PM₂.₅ and depression, strengthened by the absence of heterogeneity and of relevant publication bias in both long- and short-term exposure studies. Should further investigations be designed, they should involve large sample sizes, well-defined diagnostic criteria for depression, and thorough control of potential confounding factors. Finally, studies dedicated to the comprehension of the mechanisms underlying the association between air pollution and depression remain necessary.

Air pollution could be a risk factor for the development of pterygium. This study aimed to investigate the potential associations between outpatient visits for pterygium and air pollutants. Using a time-stratified case-crossover design, the data of 3017 outpatients with pterygium visiting an eye center in Hangzhou, China, and the air pollution data of the Environmental Protection Department of Zhejiang Province between July 1, 2014, and November 30, 2019, were examined. The relationships between the air pollutants nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone, and fine particulate matter (PM) with median aerometric diameter <2.5 μm (PM₂.₅) and <10 μm (PM₁₀) and outpatient visits for primary pterygium were assessed using single- and multiple-pollutant models. Significant associations between outpatient visits for pterygium and air pollutants (PM₂.₅, PM₁₀, SO₂, and NO₂) were observed. Younger patients were found to be more sensitive to air pollution. Interestingly, the younger female patients with pterygium were more vulnerable to PM₂.₅ exposure during the warm season, while the younger male patients with pterygium were more sensitive to NO₂ during the cold season. Significant effects were also observed between the pterygium outpatients and PM₂.₅ (odds ratio [OR] = 1.06, P = 0.02), PM₁₀ (OR = 1.04, P = 0.01), and SO₂ (OR = 1.26, P = 0.01) during the warm season, as well as NO₂ (OR = 1.06, P = 0.01) during the cold season. Our study provides evidence that outpatient visits for pterygium are positively associated with increases in the air pollutants PM₂.₅, PM₁₀, SO₂, and NO₂, revealing the important role of air pollution in the occurrence and development of pterygium.

Recent studies suggests that air pollution, from among others road traffic, can influence growth and development of the human foetus during pregnancy. The effects of air pollution from heavy industry on birth outcomes have been investigated scarcely.Our aim was to investigate the associations of air pollution from heavy industry on birth outcomes.A cross-sectional study was conducted among 4488 singleton live births (2012–2017) in the vicinity of a large industrial area in the Netherlands. Information from the birth registration was linked with a dispersion model to characterize annual individual-level exposure of pregnant mothers to air pollutants from industry in the area. Associations between particulate matter (PM₁₀), nitrogen oxides (NOX), sulphur dioxide (SO₂), and volatile organic compounds (VOC) with low birth weight (LBW), preterm birth (PTB), and small for gestational age (SGA) were investigated by logistic regression analysis and with gestational age, birth weight, birth length, and head circumference by linear regression analysis.Exposures to NOX, SO₂, and VOC (per interquartile range of 1.16, 0.42, and 0.97 μg/m³ respectively) during pregnancy were associated with LBW (OR 1.20, 95%CI 1.06–1.35, OR 1.20, 95%CI 1.00–1.43, and OR 1.21, 95%CI 1.08–1.35 respectively). NOX and VOC were also associated with PTB (OR 1.14, 95%CI 1.01–1.29 and OR 1.17, 95%CI 1.04–1.31 respectively). Associations between exposure to air pollution and birth weight, birth length, and head circumference were statistically significant. Higher exposure to PM₁₀, NOX, SO₂ and VOC (per interquartile range of 0.41, 1.16, 0.42, and 0.97 μg/m³ respectively) was associated with reduced birth weight of 21 g to 30 g.The 90th percentile industry-related PM₁₀ exposure corresponded with an average birth weight decrease of 74 g.

Shandong is the most populous and highly industrialized province in eastern China, and the resultant poor air quality is a cause for widespread concern. This study combines bottom–up and top–down approaches to develop a high-resolution anthropogenic emission inventory of air pollutants for 2017. The inventory was developed based on updated emission factors and detailed activity data. The emissions of sulfur dioxide (SO₂), nitrogen oxides (NOₓ), particulate matter with aerodynamic diameters smaller than 2.5 and 10 μm (PM₂.₅ and PM₁₀, respectively), carbon monoxide (CO), volatile organic compounds (VOCs), and ammonia (NH₃) were estimated to be 1387.8, 2488.6, 5281.7, 3193.0, 9250.7, 2254.7, and 1210.6 kt, respectively. Power plants were the largest contributors of SO₂ and NOₓ emissions accounting for 43.7% and 41.9% of the total emissions, respectively. CO emissions mainly originated from industrial processes (40.1%), mobile sources (24.8%), and fossil fuel burning (21.2%). The major sources of PM₁₀ and PM₂.₅ emissions were industrial processes and fugitive dust, contributing 83.0% and 86.9% of their total emissions, respectively. Industrial processes (60.0%) contributed the largest VOC emissions, followed by mobile sources (16.8%) and solvent use (14.5%). Livestock and N-fertilizers were major emitters of NH₃, accounting for 69.9% and 21.2% of the total emissions, respectively. Emissions were spatially allocated to grid cells with a resolution of 0.05 ° × 0.05 ° based on spatial surrogates, using Geographic Information System (GIS). Heavy pollutant emissions were mainly concentrated in the central and eastern areas of Shandong, while high NH₃–emissions occurred in the western region. Most pollutant emissions from industrial sectors occurred in June and July, while low emissions were recorded between January and February. Range uncertainties in emission inventory were quantified using Monte Carlo simulations. Our inventory provides effective information to understand local pollutant emission characteristics, perform air quality simulations, and formulate pollution control measures.

Stillbirth has a great impact on contemporary and future generations. Increasing evidence show that ambient air pollution exposure is associated with stillbirth. However, previous studies showed inconsistent findings. To clarify the effect of maternal air pollution exposure on stillbirth, we searched for studies examining the associations between air pollutants, including particulate matter (diameter ≤ 2.5 μm [PM₂.₅] and ≤10 μm [PM₁₀]) and gaseous pollutants (sulfur dioxide [SO₂], nitrogen dioxide [NO₂], carbon monoxide [CO] and ozone [O₃]), and stillbirth published in PubMed, Web of Science, Embase and Cochrane Library until December 11, 2020. The pooled effect estimates and 95% confidence intervals (CI) were calculated, and the heterogeneity was evaluated using Cochran’s Q test and I² statistic. Publication bias was assessed using funnel plots and Egger’s tests. Of 7546 records, 15 eligible studies were included in this review. Results of long-term exposure showed that maternal third trimester PM₂.₅ and CO exposure (per 10 μg/m³ increment) increased the odds of stillbirth, with estimated odds ratios (ORs) of 1.094 (95% CI: 1.008–1.180) and 1.0009 (95% CI: 1.0001–1.0017), respectively. Entire pregnancy exposure to PM₂.₅ was also associated with stillbirth (OR: 1.103, 95% CI: 1.074–1.131). A 10 μg/m³ increment in O₃ in the first trimester was associated with stillbirth, and the estimated OR was 1.028 (95% CI: 1.001–1.055). Short-term exposure (on lag day 4) to O₃ was also associated with stillbirth (OR: 1.002, 95% CI: 1.001–1.004). PM₁₀, SO₂ and NO₂ exposure had no significant effects on the incidence of stillbirth. Additional well-designed cohort studies and investigations regarding potential biological mechanisms are warranted to elaborate the suggestive association that may help improve intergenerational inequality.

Several epidemiological studies have evaluated the fractional exhaled nitric oxide (FeNO) of ambient air pollution but the results were controversial. We therefore conducted a systematic review and meta-analysis to investigate the associations between short-term exposure to air pollutants and FeNO level. We searched PubMed and Web of Science and included a total of 27 articles which focused on associations between ambient air pollutants (PM₁₀, PM₂.₅, black carbon (BC), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃)) exposure and the change of FeNO. Random effect model was used to calculate the percent change of FeNO in association with a 10 or 1 μg/m³ increase in air pollutants exposure concentrations. A 10 μg/m³ increase in short-term PM₁₀, PM₂.₅, NO₂, and SO₂ exposure was associated with a 3.20% (95% confidence interval (95%CI): 1.11%, 5.29%), 2.25% (95%CI: 1.51%, 2.99%),4.90% (95%CI: 1.98%, 7.81%), and 8.28% (95%CI: 3.61%, 12.59%) change in FeNO, respectively. A 1 μg/m³ increase in short-term exposure to BC was associated with 3.42% (95%CI: 1.34%, 5.50%) change in FeNO. The association between short-term exposure to O₃ and FeNO level was insignificant (P＞0.05). Future studies are warranted to investigate the effect of multiple pollutants, different sources and composition of air pollutants on airway inflammation.

To investigate chemical characteristics, abatement mechanisms and regional transport of atmospheric pollutants during the COVID-19 outbreak control period in the Yangtze River Delta (YRD) region, China, the measurements of air pollutants including fine particulate matter (PM₂.₅) and volatile organic compounds (VOCs) on non-control period (NCP, 24 December 2019–23 January 2020) and control period (CP, 24 January–23 February 2020) were analyzed at the urban Pudong Supersite (PD) and the regional Dianshan Lake Supersite (DSL). Due to the stricter outbreak control, the levels of PM₂.₅ and VOCs, and the occurrence frequencies of haze-fog episodes decreased substantially from NCP to CP, with average reduction rates of 31.6%, 38.9% and 35.1% at PD, and 34.5%, 50.7% and 37.9% at DSL, respectively. The major source for PM₂.₅ was secondary sulfate & nitrate in both periods, and the emission control of primary sources such as coal burning and vehicle exhaust decreased the levels of precursors gas sulfur dioxide and nitrogen oxide, which highly contributed to the abatement of PM₂.₅ from NCP to CP. The higher levels of ozone at both PD and DSL on CP might be due to the weak nitrogen monoxide titration, low relative humidity and high visibility compared with NCP. Vehicle exhaust and fugitive emission from petrochemical industry were the major contributors of ambient VOCs and their decreasing activities mainly accounted for VOCs abatement. Moreover, the high frequency of haze-fog events was closely impacted by medium-scale regional transport within Anhui and Jiangsu provinces. Therefore, the decreasing regional transported air pollutants coincided with the emission control of local sources to cause the abatement of haze-fog events in YRD region on CP. This study could improve the understanding of the change of atmospheric pollutants during the outbreak control period, and provide scientific base for haze-fog pollution control in YRD region, China.

Pollutant gases and particulate matters (PM) from livestock facilities can affect the health of animals and farm workers and lead to great social environmental risks. This paper presents a comprehensive study on the characteristics of ammonia (NH₃), nitrogen oxides (NOₓ), sulfur dioxide (SO₂) and PM (including PM₂.₅ and PM₁₀) in a 100,000-bird manure-belt layer house in suburb Beijing for three typical seasons of summer, autumn and winter. Indoor air was sampled at an exhaust fan of the mechanically ventilated commercial house. The monitored indoor concentrations of NH₃, NOₓ, SO₂, PM₂.₅ and PM₁₀ were 3.7–5.0 mg m⁻³, 17–58 μg m⁻³, 0–11 μg m⁻³, 100–149 μg m⁻³ and 354–828 μg m⁻³, respectively. The indoor NH₃ concentrations were largely influenced by the manure removal frequency. The NOₓ and SO₂ were mainly sourced from the ambient air, and the NOₓ was also partly sourced from manure decomposition in summer. The indoor PM₂.₅ and PM₁₀ were largely sourced from the ambient air and the indoor manure, respectively. The abundant indoor NH₃ caused significantly higher NH₄⁺ concentration in the indoor PM₁₀ (7.98 ± 9.04 μg m⁻³) than that in the ambient PM₁₀ (3.48 ± 3.52 μg m⁻³). Secondary inorganic ions (SO₄²⁻, NO₃⁻ and NH₄⁺) totally contributed 5.7% and 14.6% to the indoor and ambient PM₂.₅, respectively; they contributed 2.8% and 8.9% to the indoor and ambient PM₁₀, respectively. Organic carbon was the main component of the PM and accounted for 26.6% and 41.5% of the indoor PM₂.₅ and PM₁₀, respectively. Heavy metal elements (Zn, Cu and Cr) were likely transported from feed to manure and finally accumulated in the PM. Given the high emission potential, the air pollutants from animal production suggested potential risks for human health.