Average NO2 Concentrations Research Articles

Long-Term exposure to NO2 and Stroke Mortality in Portugal: an ecological study from 2001 to 2021

Abstract Background Air pollution is an important contributing factor for many pathologies, including stroke. Nitrogen dioxide (NO2), an air pollutant, has been associated in multiple studies with strokes’ mortality. Aim This study aims, for the first time, to estimate the number of deaths by stroke due to long-term, ambient exposure to nitrogen dioxide in Portugal for the years 2001-2021. Methods An ecological study was considered, including data for NO2 outdoor concentration from Portugal. Mortality data by stroke was obtained divided in 5-year groups. It was also obtained life expectancy for each year to calculate the years of life lost (YLL). The hazard ratio (HR) was obtained from literature (1.009, CI 1.003-1.016). The population attributable fraction (PAF) of YLL by stroke due to ambient NO2 long-term exposure was calculated. Results The annual average NO2 concentration in Portugal decreased from its peak in 2001 of 29.4 to 12.2 µg/m3 in 2021. The YLL by stroke decreased from an estimated 57452 to 31204 from 2001 to 2021. The PAF of YLL by stroke due to ambient NO2 long-term exposure reached its peak in 2001, when an estimated 5.2% of all the YLL by stroke, corresponding to 3029 YLL, were due to NO2 exposure and a bottom in 2021, when 2.2%, corresponding to 682 YLL, where due NO2 exposure. Conclusions The policies and legislation implemented to curb down NO2 seem to have had an effect in Portugal. A reduction in NO2 emissions was achieved, having a significant impact on YLL by stroke in Portugal, suggesting that curbing the NO2 emissions down had a positive effect on mortality by stroke in Portugal. To further enhance our knowledge on the real impacts of NO2, further studies must be conducted to estimate the morbidity associated with NO2 on stroke as well as in other diseases. Key messages • Pollution by nitrogen dioxide decreased significantly from 2001 to 2021. • Around 20000 years of life were lost just in Portugal due to nitrogen dioxide between 2001 and 2021.

A Study on Ambient Air Quality and Management inCommercial Areas of Gorakhpur City

The current study evaluates the city of Gorakhpur's ambient air quality using an air quality index. For the period January 2018 to November 2022, the 24-hour average concentration of the three primary pollutants SO2, NO2, andPM10 in a commercial area close to Jalkal Bhawan in Gorakhpur city was measured. Pollutant measurements were made between January 2018 and November 2022. The IND-AQI technique was implemented to calculate the Air Quality Index. In July, the highest monthly average concentrations of PM10, SO2, and NO2 were recorded at 401.13, 36.41, and 54.02, respectively. The yearly average SO2 concentration was found to be within the CPCB- recommended limit, while NO2 was found to be slightly above the maximum allowable level. However, PM10 wasconsistently found to be above the CPCB-recommended limit. The average monthly concentration of NO2 is higherthan SO2, and the overall AQI rating was determined to be moderate. The global experiences clearly demonstratedthat international action had been city specific rather than country oriented, and as a result, statistics show a reductionin PM2.5 of 35%–40% in five years for cities like Beijing and Seoul, whereas cities like Santiago and Mexico Cityhave shown reductions in PM2.5 and PM10 concentration of 73% and 61% in 20 to 25 years, respectively. Recent research published in the Lancet found that over the past five years, CO and Sulphur dioxide levels decreased by 28.2% and 54.1%, respectively, while NO2 and O3 concertation showed no considerable improvement. The August2018 TERI and ARAI report examined several interventions and predicted their possible effects. PM2.5 and PM10 levelsin Delhi and the NCR are above average. A different scenario has been developed in light of the intervention that can improve air quality the most. The NCAP produces an estimated national level target of 20%-30% decreasesin PM2.5 and PM10 concentration by 2024 after taking into consideration the existing international and national studies. This keeps 2018 as the baseline year for concentration comparisons. Gorakhpur City has recently experienced an increase in development activity, which has led to particulate matter.

Impact of net zero policy scenarios on air pollution inequalities in England and Wales

BackgroundThe UK is committed to achieve net zero greenhouse gas emissions by 2050. The suite of policies needed to reach net zero will lead to improvements in air quality and, consequently, could lessen air pollution inequalities. We assessed air pollution inequalities across different sociodemographic groups in England and Wales and explored how these might be differentially impacted by future air pollution projections in 2030 and 2040 under net zero policies. MethodsWe employed a geodemographic classification approach to categorise neighbourhoods into five distinct clusters based on 2021 UK Census sociodemographic variables. We modelled fine particulate matter (PM2.5) and nitrogen dioxide (NO2) concentrations for the year 2019, and predicted concentrations in 2030 and 2040. We compared a business-as-usual (BAU) scenario and two policy pathways to achieve net zero currently considered by the UK government. We aggregated air pollution concentrations to the neighbourhood level and assessed differential neighbourhood-level concentrations across the geodemographic groups using descriptive statistics and box plots. ResultsThe Urban Central Professionals group experienced 14 µg/m3 higher average NO2 concentrations compared with the Rural Elderly group in 2019. Despite substantial improvements to air quality in 2030 and 2040 of up to 6.3 µg/m3 for NO2 based on BAU, and further reductions of up to 2.4 µg/m3 NO2 under net zero policies, the overall pattern of inequality persists, but is predicted to be less pronounced. ConclusionsOur findings demonstrate the effectiveness of targeted policies and innovations in reducing both air quality and greenhouse gas emissions and in bridging the environmental inequality gap. Our findings are essential to develop targeted communication campaigns to secure acceptance and willingness across the sociodemographic spectrum to support the significant behavioural changes needed to achieve net zero, by highlighting the wider co-benefits to the environment and health of such policies.

ENVIRONMENTAL POLLUTION IN THE CITY OF BUCHAREST

The work covers air quality monitoring tools in Bucharest, major industrial facilities impacting pollution and the city's eight air quality monitoring stations. Data on pollutant emissions from Bucharest's thermal power plants (SO2, NOx and dust) are presented. Finally, the paper graphically presents the annual average concentrations of NO2, SO2, PM10 and O3 at the monitoring stations and examines pollution peaks and daily limit exceedances from 2017 to 2022.

Evaluating background and local contributions and identifying traffic-related pollutant hotspots: insights from Google Air View mobile monitoring in Dublin, Ireland

Mobile monitoring provides high-resolution observation on temporal and spatial scales compared to traditional fixed-site measurement. This study demonstrates the use of high spatio-temporal resolution of air pollution data collected by Google Air View vehicles to identify hotspots and assess compliance with WHO Air Quality Guidelines (AQGs) in Dublin City. The mobile monitoring was conducted during weekdays, typically from 7:00 to 19:00, between 6 May 2021 and 6 May 2022. One-second data were aggregated to 377,113 8 s road segments, and 8 s rolling medians were aggregated to hourly and daily levels for further analysis. We assessed the temporal variability of fine particulate matter (PM2.5), nitrogen monoxide (NO), nitrogen dioxide (NO2), ozone (O3), carbon monoxide (CO), and carbon dioxide (CO2) concentrations at hyperlocal levels. The average daytime median concentrations of NO2 (28.4 ± 15.7 µg/m3) and PM2.5 (7.6 ± 4.7 µg/m3) exceeded the WHO twenty-four hours (24 h) Air Quality Guidelines in 49.4% and 9% of the 1-year sampling time, respectively. For the diurnal variation of measured pollutants, the morning (8:00) and early evening (18:00) showed higher concentrations for NO2 and PM2.5, mostly happening in the winter season, while the afternoon is the least polluted time except for O3. The low-percentile approach along with 1-h and daytime minima method allowed for decomposing pollutant time series into the background and local contributions. Background contributions for NO2 and PM2.5 changed along with the seasonal variation. Local contributions for PM2.5 changed slightly; however, NO2 showed significant diurnal and seasonal variability related to traffic emissions. Short-lived event enhancement (1 min to 1 h) accounts for 36.0–40.6% and 20.8–42.2% of the total concentration for NO2 and PM2.5. The highly polluted days account for 56.3% of total NO2, highlighting local traffic is the dominant contributor to short-term NO2 concentrations. The longer-lived events (> 8 h) enhancement accounts for 25% of the monitored concentrations. Additionally, conducting optimal hotspot analysis enables mapping the spatial distribution of “hot” spots for PM2.5 and NO2 on highly polluted days. Overall, this investigation suggests both background and local emissions contribute to PM2.5 and NO2 pollution in urban areas and emphasize the urgent need for mitigating NO2 from traffic pollution in Dublin.

Associations of ambient air pollution and lifestyle with the risk of NAFLD: a population-based cohort study

BackgroundBoth ambient air pollution and lifestyle factors contribute to the incidence of non-alcoholic fatty liver disease (NAFLD), but previous studies usually focused on single-factor associations. We aimed to assess the joint associations of ambient air pollution and lifestyle with the NAFLD risk and investigate whether lifestyle modifies the association of air pollution with NAFLD risk.MethodsA total of 417,025 participants from the UK Biobank were included in this study. Annual average concentrations of NO2, NOx, PM2.5, PM10, and PM2.5−10 were estimated. A composite lifestyle score was determined based on physical activity, alcohol intake, smoking status, dietary patterns, sedentary time, and sleep duration. Cox proportional hazards regression models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs), as well as the population attributable fraction (PAF). Potential additive interactions of air pollution with lifestyle were also examined by the relative excess risk due to the interaction (RERI) and the attributable proportion due to the interaction (AP).Results4752 (1.14%) incident NAFLD events were recorded. Long-term exposure to air pollutants and an unhealthy lifestyle were significantly associated with the increased risk of incident NAFLD. Lifestyle was the primary factor of incident NAFLD, with a PAF of 37.18% (95% CI: 29.67%, 44.69%). In addition, a significant additive interaction between air pollution and lifestyle for NAFLD risk was observed (RERI: 0.36, 95% CI: 0.09–0.63).ConclusionsLong-term exposure to ambient air pollutants and poor lifestyle were jointly associated with a higher risk of NAFLD.

Simulating air pollution at the province level: A case of Ba Ria – Vung Tau province, Vietnam

Abstract This study aimed to simulate air pollution in Ba Ria - Vung Tau province (BR-VT), a significant transportation hub in Vietnam and Southeast Asia. The FVM-TAPOM model system was employed to create a spatial distribution map of air pollution concentration including PM2.5, PM10, NO2, SO2, and CO. The model had sufficient capability for simulating air pollutant distribution (R2>0.6). For PM2.5, the average simulated 1-hour PM2.5 concentration is highest during the dry and rainy seasons, reaching 68 μg/m3 and 46 μg/m3, respectively. For PM10, the average 1-hour simulated PM10 dust concentration is highest during the dry and rainy seasons, reaching 90 μg/m3 and 62 μg/m3, respectively. For NO2, the average 1-hour simulated NO2 concentration is highest during the dry and rainy seasons, reaching 56 (μg/m3) and 46 μg/m3, respectively, which is lower than the permissible threshold of QCVN 05:2023/BTNMT (1-hour average 200 μg/m3). For SO2, the average 1-hour simulated SO2 concentration is highest during the dry and rainy seasons, reaching 140 μg/m3 and 88 μg/m3, respectively, which is lower than the permissible threshold of QCVN 05:2023/BTNMT (1-hour average 350 μg/m3). For CO, the average 1-hour simulated CO concentration is highest during the dry and rainy seasons, reaching 2.950 μg/m3 and 2.280 μg/m3, respectively, which is lower than the permissible threshold of QCVN 05:2023/BTNMT (1-hour average 30.000 μg/m3).

The impact of shipping on the air quality in European port cities with a detailed analysis for Rotterdam

Air quality in cities with large maritime ports is considerably impacted by emissions from shipping activity which is of a growing relevance due to an increasing relative contribution. To explore the extent of shipping emissions to ambient air quality, simulations with the chemical transport model LOTOS-EUROS (LOng Term Ozone Simulation – EURopean Operational Smog model) were performed for the year 2018 at an approximate 1 × 1 km resolution for six European cities with large ports, i.e., Rotterdam, Antwerp, Hamburg, Amsterdam, Le Havre, and London. It was found that depending on the investigated city, 6.5%–62% of the nitrogen dioxide (NO2) concentration in the city centres is attributable to shipping activities. This corresponds to contributions of 1.8–11.5 μg/m3 to the ambient air NO2 concentrations. The average NO2 contribution of shipping in these six cities was 28% (7.1 μg/m3). The largest relative contribution was found for Le Havre where 62% (10.8 μg/m3) of the annual average NO2 concentration was caused by shipping emissions. The largest absolute contribution is found for the city centre of Hamburg with 11.5 μg/m3 (41%). The lowest absolute and relative contribution (respectively 1.8 μg/m3 and 6.5%) are found for London, also having the smallest port in terms of tonnage throughput, which is one of the influential factors that determine emission totals, investigated in this study. For the other investigated pollutants, i.e., PM2.5, PM10 and SO2, contributions from shipping were less pronounced with average contribution for all cities of 10% (1.2 μg/m3) 7% (1.5 μg/m3) and 4% (0.16 μg/m3) respectively. To assess the effect of model choices on these results, this study also looked into the choice of simulation resolution and relations between meteorological parameters and NO2 concentrations. Following simulations with varying chemical transport model resolutions (1 × 1 km to 24 × 24 km), it is found that a decrease in ambient air pollutant concentrations away from localized emission sources is more pronounced at higher (1 × 1 km) model resolutions and source contributions are influenced more significantly than total concentrations. Considering meteorology, generally low wind speeds (1–2 m/s) lead to high NO2 concentration in city centres. For the cities where the port is much closer to the city centre (e.g., London, Le Havre, Hamburg and Antwerp) the absolute NO2 concentrations as well as the contributions from shipping emissions become highest for windless conditions. The high concentrations (>60 μg/m3 NO2) only occur when wind speeds fall below 6 m/s.

Excess deaths and loss of life expectancy attributed to long-term NO2 exposure in the Chinese elderly

BackgroundEvidence linking nitrogen dioxide (NO2) air pollution to life span of high-vulnerability older adults is extensively scarce in low- and middle-income countries. This study seeks to quantify mortality risk, excess deaths, and loss of life expectancy (LLE) associated with long-term exposure to NO2 among elderly individuals in China. MethodsA nationwide dynamic cohort of 20352 respondents ≥65 years old were enrolled from the China Longitudinal Health and Longevity Survey during 2005–2018. Residential exposures to NO2 and co-pollutants were assessed by well-validated spatiotemporal prediction models. A Cox regression model with time-dependent covariates was utilized to quantify the association of all-cause mortality with NO2 exposure, controlling for confounders such as demographics, lifestyle, health status, and ambient temperature. NO2-attributable deaths and LLE were evaluated for the years 2010 and 2020 based on the pooled NO2-mortality relation derived from multi-national cohort investigations. Decomposition analyses were conducted to dissociate net shift in NO2-related deaths between 2010 and 2020 into four primary contributing factors. ResultsA total of 14313 deaths were recorded during follow-up of approximately 100 hundred person-years (median 3.6 years). We observed an approximately linear relationship (nonlinear P = 0.882) of NO2 exposure with all-cause death across a broad range from 6.6 to 95.7 μg/m3. Every 10-μg/m3 rise in yearly average NO2 concentration was linked to a hazard ratio (HR) of 1.045 (95% confidence interval [CI]: 1.031–1.059). In the updated meta-analysis of this study and 9 existing cohorts, we estimated a pooled HR of 1.043 (95% CI: 1.023–1.063) for each 10-μg/m3 growth in NO2. Reaching a 10-μg/m3 counterfactual target of NO2 concentration in China could avoid 0.33 (95% empirical CI: 0.19–0.49) million premature deaths and an LLE of 0.40 (95% empirical CI: 0.23–0.59) years in 2010, which greatly dropped to 0.24 (95% empirical CI: 0.14–0.36) million deaths and 0.21 (95% empirical CI: 0.12–0.31) years of LLE in 2020. The net fall in NO2-attributable deaths (–26.8%) between 2010 and 2020 was primarily driven by the declines in both NO2 concentration (–41.6%) and mortality rate (–27.1%) under population growth (+41.0%) and age structure transition (+0.9%). ConclusionsOur findings provide national evidence for increased risk of premature death and loss of life expectancy attributed to later-life NO2 exposure among the elderly in China. In an accelerated aging society, strengthened clean air actions should be formulated to minimize the health burden and regional inequality in NO2-attributable mortality.

Particulate and gaseous air pollutants exceed WHO guideline values and have the potential to damage human health in Faisalabad, Metropolitan, Pakistan

First-ever measurements of particulate matter (PM2.5, PM10, and TSP) along with gaseous pollutants (CO, NO2, and SO2) were performed from June 2019 to April 2020 in Faisalabad, Metropolitan, Pakistan, to assess their seasonal variations; Summer 2019, Autumn 2019, Winter 2019–2020, and Spring 2020. Pollutant measurements were carried out at 30 locations with a 3-km grid distance from the Sitara Chemical Industry in District Faisalabad to Bhianwala, Sargodha Road, Tehsil Lalian, District Chiniot. ArcGIS 10.8 was used to interpolate pollutant concentrations using the inverse distance weightage method. PM2.5, PM10, and TSP concentrations were highest in summer, and lowest in autumn or winter. CO, NO2, and SO2 concentrations were highest in summer or spring and lowest in winter. Seasonal average NO2 and SO2 concentrations exceeded WHO annual air quality guide values. For all 4 seasons, some sites had better air quality than others. Even in these cleaner sites air quality index (AQI) was unhealthy for sensitive groups and the less good sites showed Very critical AQI (> 500). Dust-bound carbon and sulfur contents were higher in spring (64 mg g−1) and summer (1.17 mg g−1) and lower in autumn (55 mg g−1) and winter (1.08 mg g−1). Venous blood analysis of 20 individuals showed cadmium and lead concentrations higher than WHO permissible limits. Those individuals exposed to direct roadside pollution for longer periods because of their occupation tended to show higher Pb and Cd blood concentrations. It is concluded that air quality along the roadside is extremely poor and potentially damaging to the health of exposed workers.Graphical abstract

Short-term effects of nitrogen dioxide on inpatient acute myocardial infarction in Lanzhou, China

ABSTRACT Nitrogen dioxide (NO2) represents a deleterious effect on acute myocardial infarction (AMI), but few relevant studies have been conducted in China. We aim to evaluate the acute effects of NO2 exposure on hospitalization for AMI in Lanzhou, China. In this study, we applied a distributional lag nonlinear model (DLNM) to assess the association between NO2 exposure and AMI hospitalization. We explored the sensitivity of various groups through stratified analysis by gender, age, and season. The daily average concentration of NO2 is 47.50 ± 17.38 µg/m3. We observed a significant exposure-response relationship between NO2 concentration and AMI hospitalization. The single pollutant model analysis shows that NO2 is positively correlated with AMI hospitalization at lag1, lag01, lag02, and lag03. The greatest lag effect estimate occurs at lag01, where a 10 µg/m3 increase in NO2 concentrations is significantly associated with a relative risk (RR) of hospitalization due to AMI of 1.027 [95% confidence interval (CI): 1.013, 1.042]. The results of the stratified analysis by gender, age, and season indicate that males, those aged ≥65 years, and the cold season are more sensitive to the deleterious effects caused by NO2 exposure. Short-term exposure to NO2 can enhance the risk of AMI hospitalization in urban Lanzhou. Implications: Exposure to particulate matter can lead to an increased incidence of AMI. Our study once again shows that NO2 exposure increases the risk of AMI hospital admission. AMI is a common and expensive fatal condition. Reducing NO2 exposure will benefit cardiovascular health and save on healthcare costs.

Hourly near-ground NO2 concentration retrieval from geostationary satellite observations

Abstract. Nitrogen dioxide (NO2) is an important contributor to the formation of acid rain, photochemical smog and aerosol particles, which seriously endangers public health. At present, remote sensing of polar-orbiting satellites is a conventional means to obtain large-scale NO2 distribution, but it cannot capture the rapid change because of long revisit periods. The Advanced Himawari Imager (AHI) on the Himawari-8 geostationary satellite has the advantage of high time resolution, which makes it possible to realize near-real-time atmospheric monitoring. Here, based on the absorption characteristics of NO2 in infrared radiation, hourly near-surface NO2 concentrations are retrieved based on the brightness temperature from AHI and auxiliary information such as meteorology and aerosol. The results of 10-fold cross-validation show that NO2 estimations from satellite are in good agreement with in-situ measurements, and their determination coefficient (R2) can reach 0.79. Due to different emission and atmospheric diffusion conditions at different time, the model performance presents a diurnal variation of high accuracy in the noon and afternoon but low accuracy in the morning. Based on the retrieval dataset, it is found that high NO2 concentrations are mainly concentrated in the densely populated and industrial areas such as the North China area. In addition, NO2 pollution mainly occurs in autumn and winter, and the average NO2 concentration in winter is about 1.63 times that in summer in 2021. This study provides a new insight for satellite retrieval of NO2, which is of great significance for real-time pollution monitoring and public health protection.

Evaluating Phoenix Metropolitan Area Ozone Behavior Using Ground-Based Sampling, Modeling, and Satellite Retrievals

An oxidizing and harmful pollutant gas, tropospheric ozone is a product of a complex set of photochemical reactions that can make it difficult to enact effective control measures. A better understanding of its precursors including volatile organic compounds (VOCs) and nitrogen oxides (NOx) and their spatial distribution can enable policymakers to focus their control efforts. In this study we used low-cost sensors (LCSs) to increase the spatial resolution of an existing NO2 monitoring network in addition to VOC sampling to better understand summer ozone formation in Maricopa County, Arizona, and observed that afternoon O3 values at the downwind sites were significantly correlated, ~0.27, to the morning NO2 × rate values at the urban sites. Additionally, we looked at the impact of wildfire smoke on ozone exceedances and compared non-smoke days to smoke days. The average O3 on smoke days was approximately 20% higher than on non-smoke days, however, the average NO2 concentration multiplied by estimated photolysis rate (NO2 × rate) values were only 2% higher on smoke days. Finally, we evaluated the ozone sensitivity of the region by calculating HCHO/NO2 ratios using three different datasets: ground, satellite, and model. Although the satellite dataset produced higher HCHO/NO2 ratios than the other datasets, when the proper regime thresholds are applied the three datasets consistently show transition and VOC-limited O3 production regimes over the Phoenix metro area. This suggests a need to implement more VOC emission controls in order to reach O3 attainment in the county.

Outdoor air pollution as a risk factor for testing positive for SARS-CoV-2: A nationwide test-negative case-control study in the Netherlands

Air pollution is a known risk factor for several diseases, but the extent to which it influences COVID-19 compared to other respiratory diseases remains unclear. We performed a test-negative case-control study among people with COVID-19-compatible symptoms who were tested for SARS-CoV-2 infection, to assess whether their long- and short-term exposure to ambient air pollution (AAP) was associated with testing positive (vs. negative) for SARS-CoV-2. We used individual-level data for all adult residents in the Netherlands who were tested for SARS-CoV-2 between June and November 2020, when only symptomatic people were tested, and modeled ambient concentrations of PM10, PM2.5, NO2 and O3 at geocoded residential addresses. In long-term exposure analysis, we selected individuals who did not change residential address in 2017–2019 (1.7 million tests) and considered the average concentrations of PM10, PM2.5 and NO2 in that period, and different sources of PM (industry, livestock, other agricultural activities, road traffic, other Dutch sources, foreign sources). In short-term exposure analysis, individuals not changing residential address in the two weeks before testing day (2.7 million tests) were included in the analyses, thus considering 1- and 2-week average concentrations of PM10, PM2.5, NO2 and O3 before testing day as exposure. Mixed-effects logistic regression analysis with adjustment for several confounders, including municipality and testing week to account for spatiotemporal variation in viral circulation, was used. Overall, there was no statistically significant effect of long-term exposure to the studied pollutants on the odds of testing positive vs. negative for SARS-CoV-2. However, significant positive associations of long-term exposure to PM10 and PM2.5 from specifically foreign and livestock sources, and to PM10 from other agricultural sources, were observed. Short-term exposure to PM10 (adjusting for NO2) and PM2.5 were also positively associated with increased odds of testing positive for SARS-CoV-2. While these exposures seemed to increase COVID-19 risk relative to other respiratory diseases, the underlying biological mechanisms remain unclear. This study reinforces the need to continue to strive for better air quality to support public health.

Risk analysis of air pollutants and types of anemia: a UK Biobank prospective cohort study.

Previous studies have suggested that exposure to air pollutants may be associated with specific blood indicators or anemia in certain populations. However, there is insufficient epidemiological data and prospective evidence to evaluate the relationship between environmental air pollution and specific types of anemia. We conducted a large-scale prospective cohort study based on the UK Biobank. Annual average concentrations of NO2, PM2.5, PM2.5-10, and PM10 were obtained from the ESCAPE study using the Land Use Regression (LUR) model. The association between atmospheric pollutants and different types of anemia was investigated using the Cox proportional hazards model. Furthermore, restricted cubic splines were used to explore exposure-response relationships for positive associations, followed by stratification and effect modification analyses by gender and age. After adjusting for demographic characteristics, 3-4 of the four types of air pollution were significantly associated with an increased risk of iron deficiency, vitamin B12 deficiency and folate deficiency anemia, while there was no significant association with other defined types of anemia. After full adjustment, we estimated that the hazard ratios (HRs) of iron deficiency anemia associated with each 10 μg/m3 increase in NO2, PM2.5, and PM10 were 1.04 (95%CI: 1.02, 1.07), 2.00 (95%CI: 1.71, 2.33), and 1.10 (95%CI: 1.02, 1.20) respectively. The HRs of folate deficiency anemia with each 10 μg/m3 increase in NO2, PM2.5, PM2.5-10, and PM10 were 1.25 (95%CI: 1.12, 1.40), 4.61 (95%CI: 2.03, 10.47), 2.81 (95%CI: 1.11, 7.08), and 1.99 (95%CI: 1.25, 3.15) respectively. For vitamin B12 deficiency anemia, no significant association with atmospheric pollution was found. Additionally, we estimated almost linear exposure-response curves between air pollution and anemia, and interaction analyses suggested that gender and age did not modify the association between air pollution and anemia. Our research provided reliable evidence for the association between long-term exposure to PM10, PM2.5, PM2.5-10, NO2, and several types of anemia. NO2, PM2.5, and PM10 significantly increased the risk of iron deficiency anemia and folate deficiency anemia. Additionally, we found that the smaller the PM diameter, the higher the risk, and folate deficiency anemia was more susceptible to air pollution than iron deficiency anemia. No association was observed between the four types of air pollution and hemolytic anemia, aplastic anemia, and other types of anemia. Although the mechanisms are not well understood, we emphasize the need to limit the levels of PM and NO2 in the environment to reduce the potential impact of air pollution on folate and iron deficiency anemia.

Insights into civil aviation emissions in China: Analysis of an emission inventory of air pollutants and the ChinaHighAirPollutants (CHAP) dataset

The emissions from the civil aviation sector are a significant source of CO2 and air pollutants, which represent a serious threat to ambient air quality and public health. To gain a deeper understanding of civil aviation airport emissions, it is imperative to develop a precise and comprehensive emission inventory of China's civil aviation airports. However, there are limited studies dedicated to analyzing and verifying the accuracy and completeness of China's civil aviation emission inventory. Here, this study explored pollution characteristics from temporal trends and spatial distribution perspectives based on a previously developed 2019–2020 high-resolution air pollution and CO2 emission inventory of the landing and take-off (LTO) cycle of civil aviation airports in China and the ChinaHighAirPollutants (CHAP) dataset. Besides, this study established an empirical model to evaluate the relationship between the air pollutant emissions of China's civil aviation sector in 2019–2020 and the pollutant concentration from the CHAP dataset. Compared to those in 2019, the total NOx, CO, PM, and SO2 emissions during the LTO phase in China's civil aviation sector in 2020 decreased by 14.29%–24.32%, and the average concentrations of NO2, CO, PM10, and SO2 in 2020 decreased by 6.33%–9.45%. The eastern, central, and southern regions of China are characterized by high emissions of pollutants, a phenomenon closely related to the economic prosperity and tourism development in these areas. They tend to boast higher route densities, increasing air transport activity and consequently resulting in elevated emissions. In addition, NOx had the highest correlation coefficient in the empirical model, with a correlation coefficient of 0.603 in 2019. Our findings provide new insights into civil aviation emissions in China from the analysis of the emission inventory of air pollutants and the CHAP dataset and provide a new method for verifying the accuracy and completeness of China's civil aviation emission inventory.

Environmental Injustice in Peel Region: A Cross-Sectional Analysis of Air Pollution and Social Vulnerability

Background: Nitrogen dioxide (NO2), a traffic-related air pollutant, is co-emitted with greenhouse gasses that contribute to climate change and negatively affect health. This research examines the relationship between air pollution exposure and social vulnerability to determine whether communities at a social disadvantage experience environmental injustice. Methods: The 2016 census measures for Peel Region were assessed. Peel Region has 1,381,739 people across Mississauga, Brampton, and Caledon; the spatial unit of analysis was the dissemination area (DA) with an average size of 837 people in Peel. Average ambient NO2 concentrations for 2016 came from the Canadian Urban Environmental Health Research Consortium and resampled to DAs. Social disadvantage was defined by the Ontario Marginalization Index (ON-Marg). Measures within index components came from the Canadian census. Environmental injustice was identified through correlation analysis between ON-Marg and NO2 exposure and an analysis of index components with exposure. Results: The 2016 annual NO2 concentrations were positively correlated with the overall ON-Marg quintiles (Spearman: 0.34, p < .001, 95% CI 0.29 to 0.37). The components and their correlations with NO2 were residential instability (Spearman: 0.37, p < .001, 95% CI 0.33 to 0.42), material deprivation (Spearman: 0.15, p < .001, 95% CI 0.10 to 0.19), dependency (Spearman: 0.31, p < .001, 95% CI 0.26 to 0.35), and ethnic concentration (Spearman: −0.06, p = .02, 95% CI −0.11 to −0.01). Conclusions: In Peel Region, a correlation exists between social vulnerability and air pollution, indicating inequitable exposure to NO2. Marginalized communities may not be able to choose their living environment. Environmental justice research in the context of NO2 will support policy aiming to reduce inequitable exposure.

Effects of long-term exposure to outdoor air pollution on COVID-19 incidence: A population-based cohort study accounting for SARS-CoV-2 exposure levels in the Netherlands

Several studies have linked air pollution to COVID-19 morbidity and severity. However, these studies do not account for exposure levels to SARS-CoV-2, nor for different sources of air pollution. We analyzed individual-level data for 8.3 million adults in the Netherlands to assess associations between long-term exposure to ambient air pollution and SARS-CoV-2 infection (i.e., positive test) and COVID-19 hospitalisation risks, accounting for spatiotemporal variation in SARS-CoV-2 exposure levels during the first two major epidemic waves (February 2020–February 2021). We estimated average annual concentrations of PM10, PM2.5 and NO2 at residential addresses, overall and by PM source (road traffic, industry, livestock, other agricultural sources, foreign sources, other Dutch sources), at 1 × 1 km resolution, and weekly SARS-CoV-2 exposure at municipal level. Using generalized additive models, we performed interval-censored survival analyses to assess associations between individuals’ average exposure to PM10, PM2.5 and NO2 in the three years before the pandemic (2017–2019) and COVID-19-outcomes, adjusting for SARS-CoV-2 exposure, individual and area-specific confounders. In single-pollutant models, per interquartile (IQR) increase in exposure, PM10 was associated with 7% increased infection risk and 16% increased hospitalisation risk, PM2.5 with 8% increased infection risk and 18% increased hospitalisation risk, and NO2 with 3% increased infection risk and 11% increased hospitalisation risk. Bi-pollutant models suggested that effects were mainly driven by PM. Associations for PM were confirmed when stratifying by urbanization degree, epidemic wave and testing policy. All emission sources of PM, except industry, showed adverse effects on both outcomes. Livestock showed the most detrimental effects per unit exposure, whereas road traffic affected severity (hospitalisation) more than infection risk. This study shows that long-term exposure to air pollution increases both SARS-CoV-2 infection and COVID-19 hospitalisation risks, even after controlling for SARS-CoV-2 exposure levels, and that PM may have differential effects on these COVID-19 outcomes depending on the emission source.

Indoor Air Quality and Bioaerosols in Spanish University Classrooms.

A comprehensive study assessed indoor air quality parameters, focusing on relevant air pollutants such as particulate matter (PM10 and PM2.5), gaseous compounds (CO, CO2, formaldehyde, NO2) and volatile/semi-volatile organic chemicals, as well as respiratory viruses (including SARS-CoV-2), fungi and bacteria in Spanish university classrooms. Non-target screening strategies evaluated the presence of organic pollutants inside and outside the classrooms. Saliva samples from teachers and students were collected to explore correlations between respiratory viruses in the air and biological samples. Indoor results revealed the punctual exceedance of recommended guidelines for CO2, formaldehyde (HCHO), volatile organic compounds (TVOCs) and PM in the least naturally ventilated classrooms. Significant differences occurred between the classes, with the least ventilated one showing higher average concentrations of CO2, HCHO, NO2, PM10 and PM2.5. A respiratory virus (rhinovirus/enterovirus) was detected in the medium naturally ventilated classroom, although saliva samples tested negative. Suspect screening tentatively identified 65 substances indoors and over 200 outdoors, with approximately half reporting a high toxicological risk based on the Cramer rules. The study provides a comprehensive overview of indoor air quality, respiratory viruses and organic pollutants in university classrooms, highlighting the variations and potential health risks associated with ventilation differences.

Seasonal nitrate variations, risks, and sources in groundwater under different land use types in a thousand-year-cultivated region, northwestern China

The global public health concern of nitrate (NO3−) contamination in groundwater is particularly pronounced in irrigated agricultural regions. This paper aims to analyze the spatial distribution of groundwater NO3−, assess potential health risks for local residents, and quantitatively identify nitrate sources during different seasons and land use types in the Jinghuiqu Irrigation District, a region in northwestern China with a longstanding agricultural history. The investigation utilizes hydrochemical parameters, dual isotopic data, and the Bayesian stable isotope mixing model (MixSIAR). The findings underscore significant seasonal variations in the average concentrations of NO3−, with values of 87.72 mg/L and 101.87 mg/L during the wet and dry seasons, respectively. Furthermore, distinct fluctuations in nitrate concentration were observed across different land use types, whereby vegetable lands manifested the maximum concentration. Prolonged exposure to elevated nitrate concentrations may pose potential health risks to residents, especially in the dry season when the non-carcinogenic groundwater nitrate risk surges past its wet season counterpart. The MixSIAR analysis revealed that chemical fertilizers accounted for the majority of nitrate pollution in vegetable lands, both during the dry season (49.6%) and wet season (41.2%). In contrast, manure and sewage contributed significantly to NO3−concentrations in residential land during the wet (74.9%) and dry seasons (67.6%). For croplands, soil nitrogen emerged as a dominant source during the wet season (42.2%), while chemical fertilizers prevailed in the dry season (38.7%). In addition to source variations, the nitrate concentration of groundwater is further affected by hydrogeological conditions, with more permeable aquifers tending to display higher nitrate concentrations. Thus, targeted measures were proposed to modify or impede the nitrogen migration pathway, taking into consideration hydrogeological conditions and incorporating domestic sewage, organic fertilizer, and agricultural management practices.