Dataset Information

Competing PM_2.5 and NO₂ holiday effects in the Beijing area vary locally due to differences in residential coal burning and traffic patterns.

ABSTRACT: The holiday effect is a useful tool to estimate the impact on air pollution due to changes in human activities. In this study, we assessed the variations in concentrations of fine particulate matter (PM_2.5) and nitrogen dioxide (NO₂) during the holidays in the heating season from 2014 to 2018 based on daily surface air quality monitoring measurements in Beijing. A Generalized Additive Model (GAM) is used to analyze pollutant concentrations for 34 sites by comprehensively accounting for annual, monthly, and weekly cycles as well as the nonlinear impacts of meteorological factors. A Saturday effect was found in the downtown area, with about 4% decrease in PM_2.5 and 3% decrease in NO₂ relative to weekdays. On Sundays, the PM_2.5 concentrations increased by about 5% whereas there were no clear changes for NO₂. In contrast to the small effect of the weekend, there was a strong holiday effect throughout the region with average increases of about 22% in PM_2.5 and average reductions of about 11% in NO₂ concentrations. There was a clear geographical pattern in the strength of the holiday effect. In rural areas the increase in PM_2.5 is related to the proportion of coal and biomass consumption for household heating. In the suburban areas between the Fifth Ring Road and Sixth Ring Road there were larger reductions in NO₂ than downtown which might be due to decreased traffic as many people return to their hometown for the holidays. This study provides insights into the pattern of changes in air pollution due to human activities. By quantifying the changes, it also provides insights for improvements in air quality due to control policies implemented in Beijing during the heating season.

SUBMITTER: Hua J

PROVIDER: S-EPMC7417943 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Competing PM2.5 and NO2 holiday effects in the Beijing area vary locally due to differences in residential coal burning and traffic patterns.

Hua Jinxi J Zhang Yuanxun Y de Foy Benjamin B Mei Xiaodong X Shang Jing J Feng Chuan C

The Science of the total environment 20200811

The holiday effect is a useful tool to estimate the impact on air pollution due to changes in human activities. In this study, we assessed the variations in concentrations of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) during the holidays in the heating season from 2014 to 2018 based on daily surface air quality monitoring measurements in Beijing. A Generalized Additive Model (GAM) is used to analyze pollutant concentrations for 34 sites by comprehensively ac ...[more]

PMID: 32871368

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Project description:RationalePM2.5-induced adverse effects on respiratory health may be driven by epigenetic modifications in airway cells. The potential impact of exposure duration on epigenetic alterations in the airways is not yet known.ObjectivesWe aimed to study associations of fine particulate matter PM2.5 exposure with DNA methylation in nasal cells.MethodsWe conducted nasal epigenome-wide association analyses within 503 children from Project Viva (mean age 12.9 y), and examined various exposure durations (1-day, 1-week, 1-month, 3-months and 1-year) prior to nasal sampling. We used residential addresses to estimate average daily PM2.5 at 1 km resolution. We collected nasal swabs from the anterior nares and measured DNA methylation (DNAm) using the Illumina MethylationEPIC BeadChip. We tested 719,075 high quality autosomal CpGs using CpG-by-CpG and regional DNAm analyses controlling for multiple comparisons, and adjusted for maternal education, household smokers, child sex, race/ethnicity, BMI z-score, age, season at sample collection and cell-type heterogeneity. We further corrected for bias and genomic inflation. We tested for replication in a cohort from the Netherlands (PIAMA).ResultsIn adjusted analyses, we found 362 CpGs associated with 1-year PM2.5 (FDR < 0.05), 20 CpGs passing Bonferroni correction (P < 7.0x10-8) and 10 Differentially Methylated Regions (DMRs). In 445 PIAMA participants (mean age 16.3 years) 11 of 203 available CpGs replicated at P < 0.05. We observed differential DNAm at/near genes implicated in cell cycle, immune and inflammatory responses. There were no CpGs or regions associated with PM2.5 levels at 1-day, 1-week, or 1-month prior to sample collection, although 2 CpGs were associated with past 3-month PM2.5.ConclusionWe observed wide-spread DNAm variability associated with average past year PM2.5 exposure but we did not detect associations with shorter-term exposure. Our results suggest that nasal DNAm marks reflect chronic air pollution exposure.

Project description:Epidemiological studies have consistently linked exposure to PM2.5 with adverse health effects. The oxidative potential (OP) of aerosol particles has been widely suggested as a measure of their potential toxicity. Several acellular chemical assays are now readily employed to measure OP; however, uncertainty remains regarding the atmospheric conditions and specific chemical components of PM2.5 that drive OP. A limited number of studies have simultaneously utilised multiple OP assays with a wide range of concurrent measurements and investigated the seasonality of PM2.5 OP. In this work, filter samples were collected in winter 2016 and summer 2017 during the atmospheric pollution and human health in a Chinese megacity campaign (APHH-Beijing), and PM2.5 OP was analysed using four acellular methods: ascorbic acid (AA), dithiothreitol (DTT), 2,7-dichlorofluorescin/hydrogen peroxidase (DCFH) and electron paramagnetic resonance spectroscopy (EPR). Each assay reflects different oxidising properties of PM2.5, including particle-bound reactive oxygen species (DCFH), superoxide radical production (EPR) and catalytic redox chemistry (DTT/AA), and a combination of these four assays provided a detailed overall picture of the oxidising properties of PM2.5 at a central site in Beijing. Positive correlations of OP (normalised per volume of air) of all four assays with overall PM2.5 mass were observed, with stronger correlations in winter compared to summer. In contrast, when OP assay values were normalised for particle mass, days with higher PM2.5 mass concentrations (μgm-3) were found to have lower mass-normalised OP values as measured by AA and DTT. This finding supports that total PM2.5 mass concentrations alone may not always be the best indicator for particle toxicity. Univariate analysis of OP values and an extensive range of additional measurements, 107 in total, including PM2.5 composition, gas-phase composition and meteorological data, provided detailed insight into the chemical components and atmospheric processes that determine PM2.5 OP variability. Multivariate statistical analyses highlighted associations of OP assay responses with varying chemical components in PM2.5 for both mass- and volume-normalised data. AA and DTT assays were well predicted by a small set of measurements in multiple linear regression (MLR) models and indicated fossil fuel combustion, vehicle emissions and biogenic secondary organic aerosol (SOA) as influential particle sources in the assay response. Mass MLR models of OP associated with compositional source profiles predicted OP almost as well as volume MLR models, illustrating the influence of mass composition on both particle-level OP and total volume OP. Univariate and multivariate analysis showed that different assays cover different chemical spaces, and through comparison of mass- and volume-normalised data we demonstrate that mass-normalised OP provides a more nuanced picture of compositional drivers and sources of OP compared to volume-normalised analysis. This study constitutes one of the most extensive and comprehensive composition datasets currently available and provides a unique opportunity to explore chemical variations in PM2.5 and how they affect both PM2.5 OP and the concentrations of particle-bound reactive oxygen species.

Project description:IntroductionDespite the London Underground (LU) handling on average 2.8 million passenger journeys per day, the characteristics and potential health effects of the elevated concentrations of metal-rich PM2.5 found in this subway system are not well understood.MethodsSpatial monitoring campaigns were carried out to characterise the health-relevant chemical and physical properties of PM2.5 across the LU network, including diurnal and day-to-day variability and spatial distribution (above ground, depth below ground and subway line). Population-weighted station PM2.5 rankings were produced to understand the relative importance of concentrations at different stations and on different lines.ResultsThe PM2.5 mass in the LU (mean 88??g?m-3, median 28??g?m-3) was greater than at ambient background locations (mean 19??g?m-3, median 14??g?m-3) and roadside environments in central London (mean 22??g?m-3, median 14??g?m-3). Concentrations varied between lines and locations, with the deepest and shallowest submerged lines being the District (median 4??g?m-3) and Victoria (median 361??g?m-3 but up to 885??g?m-3). Broadly in agreement with other subway systems around the world, sampled LU PM2.5 comprised 47% iron oxide, 7% elemental carbon, 11% organic carbon, and 14% metallic and mineral oxides. Although a relationship between line depth and air quality inside the tube trains was evident, there were clear influences relating to the distance from cleaner outside air and the exchange with cabin air when the doors open. The passenger population-weighted exposure analysis demonstrated a method to identify stations that should be prioritised for remediation to improve air quality.ConclusionPM2.5 concentrations in the LU are many times higher than in other London transport Environments. Failure to include this environment in epidemiological studies of the relationship between PM2.5 and health in London is therefore likely to lead to a large exposure misclassification error. Given the significant contribution of underground PM2.5 to daily exposure, and the differences in composition compared to urban PM2.5, there is a clear need for well-designed studies to better understand the health effects of underground exposure.

Project description:A direct and quantitative linkage of air pollution-related health effects to emissions from different sources is critically important for decision-making. While a number of studies have attributed the PM2.5-related health impacts to emission sources, they have seldom examined the complicated nonlinear relationships between them. Here we investigate the nonlinear relationships between PM2.5-related premature mortality in the Beijing-Tianjin-Hebei (BTH) region, one of the most polluted regions in the world, and emissions of different pollutants from multiple sectors and regions, through a combination of chemical transport model (CTM), extended response surface model (ERSM), and concentration-response functions (CRFs). The mortalities due to both long-term and short-term exposures to PM2.5 are most sensitive to the emission reductions of primary PM2.5, followed by NH3, nonmethane volatile organic compounds and intermediate volatility organic compounds (NMVOC+IVOC). The sensitivities of long-term mortality to emissions of primary organic aerosol (POA), NMVOC+IVOC and SO2 do not change much with reduction ratio, whereas the sensitivities to primary inorganic PM2.5 (defined as all chemical components of primary PM2.5 other than POA), NH3 and NOx increase significantly with the increase of reduction ratio. The emissions of primary PM2.5, especially those from the residential and commercial sectors, contribute a larger fraction of mortality in winter (57-70%) than in other seasons (28-42%). When emissions of multiple pollutants or those from both local and regional emissions are controlled simultaneously, the overall sensitivity of long-term mortality is much larger than the arithmetic sum of the sensitivities to emissions of individual pollutants or from individual regions. This implies that a multi-pollutant, multi-sector and regional joint control strategy should be implemented to maximize the marginal health benefits. For NOx emissions, we suggest a nationwide control strategy which significantly enhances the effectiveness for reducing mortality by avoiding possible side effects when only the emissions within the BTH region are reduced.

Dataset Information

Competing PM_2.5 and NO₂ holiday effects in the Beijing area vary locally due to differences in residential coal burning and traffic patterns.

Publications

Competing PM<sub>2.5</sub> and NO<sub>2</sub> holiday effects in the Beijing area vary locally due to differences in residential coal burning and traffic patterns.

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