Exposure to household air pollution (HAP) from solid fuel use (SFU) causes millions of premature deaths globally. Direct leakage from stoves into indoor air is believed to be the main cause of severe HAP. However, previous laboratory-based measurements reported leakage of minimal fractions from wood fuel combustion. Using a newly developed measurement method, on-site measurements were conducted to quantitatively evaluate the leakage of gases and particulate matter from different fuel-stove combinations. The fraction of indoor leakage to the total emission (F) of the measured air pollutants varied from 23 ± 11% to 40 ± 16% for different pollutants and fuel-stove combinations, and these were significantly higher than previously lab-based results. Fuel differences overwhelmed stove differences in influencing F values, with higher values from biomass burning than from coal combustion. The particles had higher F values than gases. Fugitive emission rates (ERs) were log-normally distributed, and biomass burning had higher ERs than coal burning. Indoor PM₂.₅ (fine particulate matter) and CO (carbon monoxide) concentrations measured during the burning period increased by nearly 1–2 orders of magnitude compared to concentrations before or after burning, confirming substantially high indoor leakage from fuel combustion in cookstoves. High fugitive emissions in indoor cookstoves quantified from the present on-site measurements effectively explain the high HAP levels observed in rural SFU households, and call for interventions to improve indoor air quality.

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.

Ambient carbon monoxide (CO) and particulate matters (PMs) are two important air pollutants in urban areas with known impacts on fetuses. Hence, this study measured some biochemistry factors of 200 neonates with birth dates from January 19 to October 12, 2020, including the birth weight and height and the serum levels of ALT, AST, ALP, GGT, and TSH. The Support Vector Machine-fitted land-use regression approach was used to predict the spatio-temporal variability of intra-urban PM 2.5 and CO concentrations by month during the pregnancy period of the cases employing 5 variables of Digital Elevation Model (DEM), slope, and distance from Compressed Natural Gas (CNG) stations, Bus Rapid Transit (BRT) stations, and mines and industries. Spearman correlation analysis (p < 0.05) was performed between the neonate indices and mean monthly PM 2.5 and CO concentrations at the exact residential address of maternal cases and their nearby areas in 250, 500, 1000, 1500, and 2000 m-radius buffer rings. All modeling efforts succeeded in predicting CO and PM 2.5 levels with acceptable adjusted r² values. Northern Isfahan had relatively higher CO and PM 2.5 concentrations due to its adjacency to low-vegetated open lands and its high traffic load as compared to southern areas. The correlation results between the neonate biochemistry indices and mean PM 2.5 and CO concentrations were mostly positive in most buffer rings, especially in the >500 m-radius buffer rings for PM 2.5 and in the 2000 m-radius rings for CO. Although the correlation results of PM 2.5 followed a detectable trend in the buffer rings, the associations between CO and the neonate biochemistry indices differed significantly between the buffer rings. Results showed that increasing mean monthly concentration of CO and PM 2.5 may stimulate further production of liver enzymes while decreasing the birth weight and height.

Commuters are exposed to a variety of physicochemical and microbiological pollutants that can lead to adverse health effects. This study aims to evaluate the indoor air quality (IAQ) in cars, buses and trains in Lisbon, to estimate inhaled doses while commuting and to evaluate the impacts of cleaning and ventilation on the IAQ. Particulate matter with diameter lower than 1, 2.5 and 10 μm (PM₁, PM₂.₅ and PM₁₀), black carbon (BC), carbon monoxide (CO), carbon dioxide (CO₂) volatile organic compounds (VOCs), formaldehyde (CH₂O) and total airborne bacteria and fungi were measured and bacterial isolates were identified. Results showed that the type of ventilation is the main factor affecting the IAQ in vehicle cabins. Under the fan off condition, the concentration of BC was lower, but the concentration of gases such as CO₂, CO and VOC tended to accumulate rapidly. When the ventilation was used, the coarse particles were filtered originating the decrease of indoor concentrations. Commuters travelling in trains received the lowest dose for all chemical pollutants, except VOC, mainly because railways are further away from the direct vehicular emissions. Commuters travelling in cars without ventilation received the highest inhaled dose for almost all pollutants despite having the lowest travel duration. Airborne microbiota was highly affected by the occupancy of the vehicles and therefore, the fungi and bacterial loads were higher in trains and buses. Most of the isolated species were human associated bacteria and some of the most abundant species have been linked to respiratory tract infections.

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.

This paper presents the results of experimental research into the component composition of gases and ash residue from the combustion of a set of high-potential coal-water slurries containing petrochemicals. We have established that the use of slurry fuels provides a decrease in the CO₂, CH₄, SO₂, and NOₓ concentrations as compared to those from coal combustion. The content of carbon monoxide and hydrogen in the gas environment from the combustion of slurries is higher due to the intense water evaporation. It is shown that adding biomass allows a further 5–33% reduction in the emissions of nitrogen and sulfur oxides as compared to the coal-water slurry and the composition with added waste turbine oil and a 23–68% decrease as compared to coal (per unit mass of the fuel burnt). The mechanisms and stages of CO₂, SO₂, and NOₓ formation are explained with a view to controlling gaseous anthropogenic emissions and ash buildup. The values of the relative environmental performance indicator are calculated for slurry fuels. It is shown to exceed the same indicator of bituminous coal by 28–56%.

Vehicular emissions contribute significantly to air pollution, and the number of vehicles in use is continuing to rise. Policymakers thus need to formulate vehicular emission reduction policies to improve urban air-quality. This study used different vehicle control scenarios to predict the associated potential of mitigating carbon monoxide (CO), volatile organic compounds (VOCs), nitrogen oxide (NOₓ), particulate matter with an aerodynamic diameter less than 2.5 μm (PM₂.₅), and particulate matter with an aerodynamic diameter less than 10 μm (PM₁₀) in Xi’an China, in 2020 and 2025. One business-as-usual scenario and six control scenarios were established, and vehicular emission inventory was developed according to each scenario. The results revealed that eliminating high-emission vehicles and optimizing after-treatment devices would effectively reduce vehicular emissions. In addition, increasing the number of alternative fuel vehicles, restraining vehicle use, and restraining the growth of the vehicle population would all have certain effects on CO and VOCs emissions, but the effects would not be significant for NOx, PM₂.₅, and PM₁₀. The results also indicated that if all control measures were stringently applied together, emissions of CO, VOCs, NOₓ, PM₂.₅, and PM₁₀ would be reduced by 51.66%, 51.58%, 30.19%,71.12%, and 71.81% in 2020, and 53.55%, 51.44%, 19.09%, 54.88%, and 55.51%, in 2025, respectively.

This study investigates changes in air quality conditions during the restricted COVID-19 lockdown period in 2020 across 21 metropolitan areas in the Middle East and how these relate to surface urban heat island (SUHI) characteristics. Based on satellite observations of atmospheric gases from Sentinel-5, results indicate significant reductions in the levels of atmospheric pollutants, particularly nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and carbon monoxide (CO). Air quality improved significantly during the middle phases of the lockdown (April and May), especially in small metropolitan cities like Amman, Beirut, and Jeddah, while it was less significant in “mega” cities like Cairo, Tehran, and Istanbul. For example, the concentrations of NO₂ in Amman, Beirut, and Jeddah decreased by −56.6%, −43.4%, and −32.3%, respectively, during April 2020, compared to April 2019. Rather, there was a small decrease in NO₂ levels in megacities like Tehran (−0.9%) and Cairo (−3.1%). Notably, during the lockdown period, there was a decrease in the mean intensity of nighttime SUHI, while the mean intensity of daytime SUHI experienced either an increase or a slight decrease across these locations. Together with the Gulf metropolitans (e.g. Kuwait, Dubai, and Muscat), the megacities (e.g. Tehran, Ankara, and Istanbul) exhibited anomalous increases in the intensity of daytime SUHI, which may exceed 2 °C. Statistical relationships were established to explore the association between changes in the mean intensity and the hotspot area in each metropolitan location during the lockdown. The findings indicate that the mean intensity of SUHI and the spatial extension of hotspot areas within each metropolitan had a statistically significant negative relationship, with Pearson's r values generally exceeding - 0.55, especially for daytime SUHI. This negative dependency was evident for both daytime and nighttime SUHI during all months of the lockdown. Our findings demonstrate that the decrease in primary pollutant levels during the lockdown contributed to the decrease in the intensity of nighttime SUHIs in the Middle East, especially in April and May. Changes in the characteristics of SUHIs during the lockdown period should be interpreted in the context of long-term climate change, rather than just the consequence of restrictive measures. This is simply because short-term air quality improvements were insufficient to generate meaningful changes in the region's urban climate.

Air pollution is an important risk factor for autoimmune diseases, but its association with the recurrence of rheumatoid arthritis (RA) remains unclear so far. This study aimed to investigate the short-term association between traffic-related air pollutants and hospital readmissions for RA in Hefei, China. Data on daily hospital readmissions for RA and traffic-related air pollutants, including particulate matter (PM₂.₅ and PM₁₀), nitrogen dioxide (NO₂), and carbon monoxide (CO), from 2014 to 2018 were retrieved. A time-series approach using generalized linear regression model was employed. The analysis was further stratified by sex, age and season. A total of 1153 readmissions for RA were reported during the study period. A significant association between high-concentration PM₂.₅ (90th percentile) and RA readmissions was observed on lag1 (relative risk (RR) = 1.09, 95% confidence interval (CI): 1.01–1.19) and lasted until lag3 (RR = 1.06, 95%CI: 1.01–1.12). From lag2 to lag5, high-concentration NO₂ (90th percentile) was associated with increased risk of RA readmissions, with the highest RR observed at lag 4 (1.11, 95%CI: 1.05–1.17). Stratified analyses indicated that females and the elderly appeared to be more vulnerable to high-concentration PM₂.₅ and NO₂ exposure. High-concentration PM₂.₅ and NO₂ in cold seasons were consistently significantly associated with increased risk of RA readmissions. Exposure to high-concentration PM₂.₅ and NO₂ was associated with increased risk of RA readmissions. Protective measures against the exposure to high-concentration PM₂.₅ and NO₂ should be taken to reduce the recurrence risk in RA patients, especially in females, the elderly and during cold seasons.