Particle concentrations, dispersion modelling and evaluation in southern Sweden

High resolution mapping of nitrogen dioxide and particulate matter in Great Britain (2003-2021) with multi-stage data reconstruction and ensemble machine learning methods

In this contribution, we applied a multi-stage machine learning (ML) framework to map daily values of nitrogen dioxide (NO2) and particulate matter (PM10 and PM2.5) at a 1 km2 resolution over Great Britain for the period 2003-2021. The process combined ground monitoring observations, satellite-derived products, climate reanalyses and chemical transport model datasets, and traffic and land-use data. Each feature was harmonized to 1 km resolution and extracted at monitoring sites. Models used single and ensemble-based algorithms featuring random forests (RF), extreme gradient boosting (XGB), light gradient boosting machine (LGBM), as well as lasso and ridge regression. The various stages focused on augmenting PM2.5 using co-occurring PM10 values, gap-filling aerosol optical depth and columnar NO2 data obtained from satellite instruments, and finally the training of an ensemble model and the prediction of daily values across the whole geographical domain (2003-2021). Results show a good ensemble model performance, calculated through a ten-fold monitor-based cross-validation procedure, with an average R2 of 0.690 (range 0.611-0.792) for NO2, 0.704 (0.609-0.786) for PM10, and 0.802 (0.746-0.888) for PM2.5. Reconstructed pollution levels decreased markedly within the study period, with a stronger reduction in the latter eight years. The pollutants exhibited different spatial patterns, while NO2 rose in close proximity to high-traffic areas, PM demonstrated variation at a larger scale. The resulting 1 km2 spatially resolved daily datasets allow for linkage with health data across Great Britain over nearly two decades, thus contributing to extensive, extended, and detailed research on the long-and short-term health effects of air pollution.

Long-term trends of black carbon and particle number concentrations and their vehicle emission factors in Stockholm

Black carbon (BC) and particle number (PN) concentrations are usually high in cities due to traffic emissions. European mitigation policies, including Euro emission standards, have been implemented to curb these emissions. We analyzed BC and PN (particle diameter Dp > 4 nm) concentrations in Stockholm spanning the years 2013-2019 (BC) and 2009-2019 (PN) measured at street canyon and rooftop sites to assess the effectiveness of the implemented policies. Combining these data with inverse dispersion modeling, we estimated BC and PN emission factors (EFBC and EFPN) for the mixed fleet, reflecting real-world driving conditions. The pollutants showed decreasing trends at both sites, but PN concentrations remained high at the canyon site considering the World Health Organization (WHO) recommendations. BC concentrations declined more rapidly than PN concentrations, showing a -9.4% and -4.9% annual decrease at the canyon and -7.2% and -0.5% at the rooftop site in the years 2013-2019. The EFBC and EFPN trends showed that the mitigation strategies for reducing particulate emissions for on-road vehicles were successful over the study period. However, the introduction of biofuels in the vehicle fleet -ethanol and later rapeseed methyl ester (RME)- increased the concentrations of particles with Dp < 10 nm before the adoption of particulate filters in the exhausts. Stricter Euro emission regulations, especially with diesel particulate filters (DPF) in Euro 5, 6, and VI vehicles, led to 66% decrease in EFBC and 55% in EFPN. Real-world EFBC surpassed HBEFA (Handbook Emission Factors for Road Transport) database values by 2.4-4.8 times; however, direct comparisons between real-world and HBEFA EFPN are difficult due to differences in lower cut-off sizes and measurement techniques. Our results underscore the necessity for revising the HBEFA database, updating laboratory testing methods and portable emission measuring systems (PEMS) measurements to account for liquid condensate contributions to PN measurements.

Exposure to long-term source-specific transportation noise and incident breast cancer: A pooled study of eight Nordic cohorts

BACKGROUND

Environmental noise is an important environmental exposure that can affect health. An association between transportation noise and breast cancer incidence has been suggested, although current evidence is limited. We investigated the pooled association between long-term exposure to transportation noise and breast cancer incidence.

METHODS

Pooled data from eight Nordic cohorts provided a study population of 111,492 women. Road, railway, and aircraft noise were modelled at residential addresses. Breast cancer incidence (all, estrogen receptor (ER) positive, and ER negative) was derived from cancer registries. Hazard ratios (HR) were estimated using Cox Proportional Hazards Models, adjusting main models for sociodemographic and lifestyle variables together with long-term exposure to air pollution.

RESULTS

A total of 93,859 women were included in the analyses, of whom 5,875 developed breast cancer. The median (5th-95th percentile) 5-year residential road traffic noise was 54.8 (40.0-67.8) dB Lden, and among those exposed, the median railway noise was 51.0 (41.2-65.8) dB Lden. We observed a pooled HR for breast cancer (95 % confidence interval (CI)) of 1.03 (0.99-1.06) per 10 dB increase in 5-year mean exposure to road traffic noise, and 1.03 (95 % CI: 0.96-1.11) for railway noise, after adjustment for lifestyle and sociodemographic covariates. HRs remained unchanged in analyses with further adjustment for PM2.5 and attenuated when adjusted for NO2 (HRs from 1.02 to 1.01), in analyses using the same sample. For aircraft noise, no association was observed. The associations did not vary by ER status for any noise source. In analyses using <60 dB as a cutoff, we found HRs of 1.08 (0.99-1.18) for road traffic and 1.19 (0.95-1.49) for railway noise.

CONCLUSIONS

We found weak associations between road and railway noise and breast cancer risk. More high-quality prospective studies are needed, particularly among those exposed to railway and aircraft noise before conclusions regarding noise as a risk factor for breast cancer can be made.

Health impact assessment of road traffic noise exposure based on different densification scenarios in Malmö, Sweden

While urbanization provides many opportunities to those arriving in thriving urban areas, a greater number of residents necessitates the expansion of housing and infrastructure. This is often achieved through densification, which can lead to increased noise, particularly through increased road traffic. A key challenge of promoting healthy urban planning is to understand potential health effects, especially on the local level. The aim of the present study is, therefore, to estimate and compare the health impacts of road traffic noise exposure for various urban densification scenarios within a neighborhood (Lorensborg) in Malmö, Sweden. The three scenarios include 1) Present-day, representing the study area as it is presently organized; 2) Planned municipal strategy (the city of Malmö's own densification plans) and 3) Health-centred, which involves major structural alterations and reflects an effort prioritize a health-centred approach. Noise was modelled using the Nordic prediction method for road traffic. Health outcomes included noise annoyance, adverse sleep disturbance, ischemic heart disease (IHD) incidence and mortality. Within all scenarios, a large proportion of the study population was exposed above the WHO's health-based guideline value (L_den 53 dB): >80% for Present-day and Planned municipal strategy scenarios, and almost 50% in the Health-centred scenario. Still, densifying Lorensborg (population ≈9,600) according to the Health-centred scenario could prevent 549 cases of highly annoyed, 193 cases of adverse sleep disturbance, 4.7 new cases of IHD (8.9% of total cases), and 1.5 deaths due to IHD (17.8% of IHD mortality) annually. The results demonstrated that it is possible to considerably lower the health impact with a more health-centred densification strategy. Important co-benefits for public and environmental health include air pollution reduction and green space creation, although their health effects were not quantified in the present study. Urban planning initiatives must be more ambitious in order to create healthy, sustainable cities.

Exposure to local, source-specific ambient air pollution during pregnancy and autism in children: a cohort study from southern Sweden

Evidence of air pollution exposure, namely, ambient particulate matter (PM), during pregnancy and an increased risk of autism in children is growing; however, the unique PM sources that contribute to this association are currently unknown. The aim of the present study was to investigate local, source-specific ambient PM exposure during pregnancy and its associations with childhood autism, specifically, and autism spectrum disorders (ASD) as a group. A cohort of 40,245 singleton births from 2000 to 2009 in Scania, Sweden, was combined with data on locally emitted PM with an aerodynamic diameter < 2.5 µm (PM2.5). A flat, two-dimensional dispersion model was used to assess local PM2.5 concentrations (all-source PM2.5, small-scale residential heating- mainly wood burning, tailpipe exhaust, and vehicle wear-and-tear) at the mother's residential address during pregnancy. Associations were analyzed using binary logistic regression. Exposure to local PM2.5 during pregnancy from each of the investigated sources was associated with childhood autism in the fully adjusted models. For ASD, similar, but less pronounced, associations were found. The results add to existing evidence that exposure to air pollution during pregnancy may be associated with an increased risk of childhood autism. Further, these findings suggest that locally produced emissions from both residential wood burning and road traffic-related sources (tailpipe exhaust and vehicle wear-and-tear) contribute to this association.

Estimated public health benefits of a low-emission zone in Malmö, Sweden

Air pollution is one of the leading causes of morbidity and mortality worldwide. Low-emission zones (LEZ) have been increasingly implemented in cities throughout Europe as a measure to reduce the adverse health effects and premature deaths associated with traffic-related air pollution. In the present study, a health impact analysis was conducted to estimate the effect of a hypothetical LEZ on mortality and morbidity in Malmö, Sweden. Baseline health statistics were gathered from health registers and applied to each resident according to individual-level data on age and/or sex. Concentration-response parameters were derived from current epidemiological literature, specifically meta-analyses. A Gaussian dispersion model (AERMOD) combined with a detailed emission database was used to calculate NO₂ emissions from traffic, which could be applied on an individual-level using data on each person's residential coordinates. The adjusted exposure scenario replaced all vehicles on municipal roads having Euro 5 or lower emission standards with Euro 6 equivalents. This LEZ would, on average, decrease NO₂ concentrations by 13.4%, preventing an estimated 9-26 deaths in Malmö each year. Additionally, 12 respiratory disease hospitalizations, 8 childhood asthma cases, and 9 cases of hypertensive disorders of pregnancy were estimated to be avoided annually. These results suggest that LEZs can effectively improve air quality, reduce greenhouse gas emissions, and safeguard public health.

Prenatal Exposure to Locally Emitted Air Pollutants Is Associated with Birth Weight: An Administrative Cohort Study from Southern Sweden

While prenatal exposure to ambient air pollution has been shown to be associated with reduced birth weight, there is substantial heterogeneity across studies, and few epidemiological studies have utilized source-specific exposure data. The aim of the present study was, therefore, to investigate the associations between local, source-specific exposure to fine particulate matter (PM2.5) during pregnancy and birth weight. An administrative cohort comprising 40,245 singleton births from 2000 to 2009 in Scania, Sweden, was combined with data on relevant covariates. Investigated sources of PM2.5 included all local sources together as well as tailpipe exhaust, vehicle wear-and-tear, and small-scale residential heating separately. The relationships between these exposures, represented as interquartile range (IQR) increases, and birth weight (continuous) and low birth weight (LBW; <2500 g) were analyzed in crude and adjusted models. Each local PM2.5 source investigated was associated with reduced birth weight; average decreases varied by source (12−34 g). Only small-scale residential heating was clearly associated with LBW (adjusted odds ratio: 1.14 (95% confidence interval: 1.04−1.26) per IQR increase). These results add to existing evidence that prenatal exposure to ambient air pollution disrupts fetal growth and suggest that PM2.5 from both vehicles and small-scale residential heating may reduce birth weight.

Association of Prenatal Ambient Air Pollution Exposure With Placental Mitochondrial DNA Copy Number, Telomere Length and Preeclampsia

Background: Studies have shown that ambient air pollution is linked to preeclampsia (PE), possibly via generation of oxidative stress in the placenta. Telomere length and mitochondrial DNA copy number (mtDNAcn) are sensitive to oxidative stress damage. Objective: To study the association between prenatal exposure to ambient nitrogen oxides (NO_x, a marker for traffic-related air pollution), and PE, as well as potential mediation effects by placental telomere length and mtDNAcn. Methods: This is a cross-sectional study of 42 preeclamptic and 95 arbitrarily selected normotensive pregnant women with gestational ambient NO_x exposure assessment in southern Scania, Sweden. Hourly concentrations of NO_x were estimated at the residential addresses by a Gaussian-plume dispersion model with 100 × 100 m spatial resolutions and aggregated into trimester-specific mean concentrations. Placental relative mtDNAcn and telomere length were measured using qPCR. Linear and logistic regression models were used to investigate associations, adjusted for perinatal and seasonal characteristics. Results: Exposure was categorized into low and high exposures by median cut-offs during first [11.9 μg/m³; interquartile range (IQR) 7.9, 17.9], second (11.6 μg/m³; IQR: 7.1, 21.1), third trimesters (11.9 μg/m³; IQR: 7.7, 19.5) and entire pregnancy (12.0 μg/m³; IQR: 7.6, 20.1). Increased risk of PE was found for high prenatal NO_x exposure during the first trimester (OR 4.0; 95% CI: 1.4, 11.1; p = 0.008), and entire pregnancy (OR 3.7; 95% CI: 1.3, 10.4; p = 0.012). High exposed group during the first trimester had lower placental relative mtDNAcn compared with low exposed group (-0.20; 95% CI: -0.36, -0.04; p = 0.01). Changes in relative mtDNAcn did not mediate the association between prenatal NO_x exposure and PE. No statistically significant association was found between placental relative telomere length, prenatal NO_x exposure and PE. Conclusion: In this region with relatively low levels of air pollution, ambient NO_x exposure during the first trimester was associated with reduced placental relative mtDNAcn and an increased risk of PE. However, we did not find any evidence that mtDNAcn or TL mediated the association between air pollution and PE. Future research should further investigate the role of mtDNAcn for pregnancy complications in relation to exposure to ambient air pollution during pregnancy.

Associations between long-term exposure to low-level air pollution and risk of chronic kidney disease-findings from the Malmö Diet and Cancer cohort

BACKGROUND

Associations between air pollution and chronic kidney disease (CKD) have been reported, but studies at low exposure levels and relevant exposure time windows are still warranted. This study investigated clinical CKD at low air pollution levels in the Swedish Malmö Diet and Cancer Cohort in different exposure time windows.

METHODS

This study included 30,396 individuals, aged 45-74 at enrollment 1991-1996. Individual annual average residential outdoor PM_2.5, PM₁₀, nitrogen oxides (NO_x), and black carbon (BC) were assigned using dispersion models from enrollment to 2016. Diagnoses of incident CKD were retrieved from national registries. Cox proportional hazards models were used to obtain hazard ratios (HRs) for CKD in relation to three time-dependent exposure time windows: exposure at concurrent year (lag 0), mean exposure in the 1-5 or 6-10 preceding years (lag 1-5 and lag 6-10), and baseline exposure.

RESULTS

During the study period, the average annual residential exposures were 16 μg/m³ for PM₁₀, 11 μg/m³ for PM_2.5, 26 μg/m³ for NO_x, and 0.97 μg/m³ for BC. For lag 1-5 and lag 6-10 exposure, significantly elevated HRs for incident CKD were found for total PM₁₀:1.13 (95% CI: 1.01-1.26) and 1.22 (1.06-1.41); NO_x: 1.19 (1.07-1.33) and 1.13 (1.02-1.25) and BC: 1.12 (1.03-1.22) and 1.11 (1.02-1.21) per interquartile range increase in exposure. For total PM_2.5 the positive associations of 1.12 (0.97-1.31) and 1.16 (0.98-1.36) were not significant. For baseline or lag 0 exposure there were significant associations only for NO_x and BC, not for PM.

CONCLUSION

Residential exposure to outdoor air pollution was associated with increased risk of incident CKD at relatively low exposure levels. Average long-term exposure was more clearly associated with CKD than current exposure or exposure at recruitment. Our findings imply that the health effects of low-level air pollution on CKD are considerable.

Health Impacts from Ambient Particle Exposure in Southern Sweden

A health impact assessment (HIA) is an important tool for making informed decisions regarding the design and evaluation of environmental interventions. In this study, we performed a quantitative HIA for the population of Scania (1,247,993), the southernmost county in Sweden, in 2016. The impact of annual mean concentrations of particulate matter with an aerodynamic diameter <2.5 µm (PM_2.5), modeled at their home residences for the year 2011, on mortality, asthma, dementia, autism spectrum disorders, preeclampsia and low birth weight (LBW) was explored. Concentration–response (C-R) functions were taken from epidemiological studies reporting meta-analyses when available, and otherwise from single epidemiological studies. The average level of PM_2.5 experienced by the study population was 11.88 µg/m³. The PM_2.5 exposure was estimated to cause 9–11% of cases of LBW and 6% of deaths from natural causes. Locally produced PM_2.5 alone contributed to 2–9% of the cases of diseases and disorders investigated. Reducing concentrations to a maximum of 10 µg/m³ would, according to our estimations, reduce mortality by 3% and reduce cases of LBW by 2%. Further analyses of separate emission sources’ distinct effects were also presented. Reduction of air pollution levels in the study area would, as expected, have a substantial effect on both mortality and adverse health outcomes. Reductions should be aimed for by local authorities and on national and even international levels.