Air Quality Atmosphere and Health最新文献

Regional transmission plays a crucial role in the PM_2.5 and O₃ pollution of Shijiazhuang, a hot inland city in the North China Plain. To analyze the pollution pathways and potential source distribution, airflow backward trajectory cluster analysis, potential source contribution function (PSCF) method, and concentration-weighted trajectory (CWT) analysis were used adopting monitoring data from 2015 to 2021. The results showed that in 2016, the compound pollution days of PM_2.5 and O₃ were the most (24 days), accounting for 36.4% of the total. According to air mass backward trajectory analysis, the highest concentration of O₃ in Shijiazhuang during summer (136.3 μg/m³) was due to the influence of short-distance transmission, specifically Cluster 3 from the southeast direction accounting for the most significant proportion (32.79%). In winter, PM_2.5 pollution primarily originated from long-distance transmission, with Cluster 3 in Mongolia, Inner Mongolia, and Shanxi Province recording PM_2.5 concentrations as high as 179.9 μg/m³. The source area for PM_2.5 pollution in Shijiazhuang significantly expanded during winter, with the increasing high-value area of weighted PSCF (WPSCF) and weighted (WCWT). During summer, the distribution area of O₃ pollution sources and WPSCF value increased significantly. Almost the entire Henan region was covered by a high-value WCWT area (up to 95 μg/m³). O₃ pollution was primarily emitted locally but transported over short distances. These findings underscore the necessity of implementing regional joint prevention and control measures to mitigate PM_2.5 and O₃ pollution.

Graphical Abstract

Short-term effects of exposure to cold spells on blood pressure are still relatively limited, especially large-scale studies. Thus, we explored associations between cold spells and blood pressure using a large sample of Chinese adults. A total of 50,538 participants were included in our study. They are from Zhongda Hospital Health Screening Centre between 2019 and 2021. Data about the weather and air pollution were obtained from the relevant departments in Nanjing, respectively. We defined cold spells as mean apparent temperature (Tappmean) below the third or fifth percentile of the temperature distribution for 2 or more consecutive periods during each cold season. We found blood pressure levels increased significantly 0–6 days after cold spells. The cumulative effects for cold spells (Tappmean < third percentile) at lags 0 to 6 days were significantly associated with increases in systolic blood pressure (SBP) which ranged from 0.95% to 1.69%. In subgroup analyses, stronger effects were observed in females. This longitudinal study revealed that blood pressure was significantly influenced by cold spells. Cold spells pose a greater risk to females. This discovery provides novel perspectives on the impact of cold spells on human health.

Air pollution causes damage and imposes risks on human health, especially in cities, where the pollutant load is a major concern, although the extent of these effects is still largely unknown. Thus, taking the busiest road traffic area in Portugal as a local case study (600 m × 600 m domain, 4 m² spatial resolution), the objective of this work was to investigate two health risk methodologies (linear and nonlinear), which were applied for estimating short-term health impacts related to daily variations of high-resolution ambient nitrogen dioxide (NO₂) concentrations modelled for winter and summer periods. Both approaches are based on the same general equation and health input metrics, differing only in the relative risk calculation. Health outcomes, translated into the total number of cases and subsequent damage costs, were compared, and their associated uncertainties and challenges for health impact modelling were addressed. Overall, for the winter and summer periods, health outcomes considering the whole simulation domain were lower using the nonlinear methodology (less 27% and 28%, respectively). Spatially, these differences are more noticeable in locations with higher NO₂ and population values, where the highest health estimates were obtained. When the daily NO₂ exposure was less than 6 µg.m⁻³, a fact that occurred in 95% of the domain cells and in both periods, relatively small differences between approaches were found. Analysing the seasonality effect, total health impacts derived from the linear and nonlinear applications were greater in summer (around 18% in both approaches). This happens due to the magnitude and spatial variability of NO₂, as the other health input metrics remained constant. This exploratory research in local scale health impact assessment (HIA) demonstrated that the use of refined input data could contribute to more accurate health estimates and that the nonlinear approach is probably the most suitable for characterising air pollution episodes, thus providing important support in HIA.

This study was aimed at classifying the aerosol types and assessing their temporal distribution in the atmosphere of Lahore. For this purpose, we utilized the particle linear depolarization ratio (PLDR) and single scattering albedo (SSA) from Aerosol Robotic Network (AERONET) version 3 inversion products. Datasets from AERONET stationed at Lahore were computed to obtain results. Based on the dust ratio (R_d) (obtained from SSA and PLDR) aerosols were classified into pure dust (PD), pollution aerosols: non-absorbing (NA), weakly absorbing (WA), moderately absorbing (MA), and strongly absorbing (SA) aerosols, and mixtures: pollution-dominated mixture (PDM), and dust dominated-mixture (DDM). The highest aerosol density was in regions with higher angstrom exponent (AE) values. The atmosphere of Lahore is dominated by 65% pollution aerosols (29% PDM and 34% pollution aerosols). DDM (dust-dominated mixtures) prevails mostly in the summer and spring seasons, while PD or DDM is observed in very low quantities in the cold season (only in pre- and post-winter season months). The winter season months are highly polluted with 80% pure pollution aerosol dominance. Mostly low PLDR values are observed in the atmosphere of Lahore indicating dominance by pollution aerosols associated with anthropogenic pollution sources.

A benchmark was performed, comparing the results of three different methodologies proposed by three institutions to calibrate a network of low-cost PM2.5 sensors, on an hourly basis, using synthetically generated real concentrations and sensor measurements. The objective of the network calibrations was to correct the 2000+ sensor measurements in the Netherlands for the sensitivity to (local) environmental conditions. The option to use real measurements was dropped because the number of low-cost sensors sufficiently close to the 40 reference measurement locations was assessed to be spatially insufficient to benchmark the proposed approaches. Instead, synthetic real concentrations were generated to enable validation at all sensor locations. Hourly actual sensor and actual fixed concentrations, as well as interpolated concentration maps, were used as underlying data to generate the synthetic data sets for the period of 1 month. The synthetic sensor measurement errors were constructed by sampling from a collection of differences between actual sensor values and actual measurements. Of the three tested calibration methods, two follow a similar approach, although having differences in, e.g., outlier analyses and method of grouping sensors, leading also to comparable corrections to the raw sensor measurements. A third method uses significantly stricter rules in outlier selection, discarding considerably more sensors because of insufficient quality. Differences between the methods become most apparent when analyzing data at a smaller time scale. It is shown that two network calibration methods are better at correcting the hourly/daily bias.

This paper aims to assess the impact of restrictive measures against the COVID-19 spread on the air quality of the most representative urban centers in Italy during the 66 days of the first lockdown, integrating a broad and detailed set of socioeconomic and health data into machine learning techniques and correlation analysis. Hierarchical Clustering analysis applied to all 104 Italian provinces indicated a group of six provinces to represent the urban environment in Italy. In contrast, correlation analyses suggested two meteorological parameters and four other air quality parameters as the most skilful at expressing changes in air quality during the first lockdown. Filtering the effects of seasonality, NO concentrations were the ones that most acted in improving urban air quality, showing reductions of up to 48% in all analyzed provinces, directly related to reductions in population mobility in this period (other studies reported an incisive role of pollutants as (NO_{2}) and (PM_{10}) or (PM_{2.5}) in the SARS-CoV-3 spread). However, there were increases in (PM_{10}) concentrations related to the use of wood burning for heating, and in (SO_2) concentrations associated with the food industry, a sector slightly affected by the restrictive measures for being framed as essential. Naples was the only province which reported concentration reductions in all pollutants evaluated, including ozone (7%). However, it was the one that registered the most significant increases during the first days after the lockdown, probably due to the less restrictive measures applied to provinces with the lowest contamination numbers.

In this study, the impact of international tourist arrivals on CO₂ emissions caused by transportation is investigated using the quantile regression via method of moments (MMQR) approach with data for the period 1995–2019 from selected Mediterranean countries. Moreover, testing of tourism-induced environmental Kuznets curve (EKC) hypothesis is included in the analysis in terms of transportation sector-based pollution. The U-shaped correlation between economic growth and transportation sector-based emissions in all quintiles is revealed, as well as tourist arrivals are found to increase emissions up to higher quintile levels. At lower quantile levels, an increase in tourist arrivals increases the emission level by approximately 0.06%, while at medium quantile levels this positive effect is approximately 0.07%. This result indicates the necessity of considering emissions from the transportation sector in the tourism-induced EKC for new policy insights. In addition, the findings highlight the environmental impacts caused by tourism through the prism of transportation sector.

Plume rising from wildfire due to the buoyancy generated by the heat released from the fire is a crucial phenomenon to model for a correct description of smoke dispersion within the atmosphere. During the rise, the plume experiences the drag of external air which limits the rising itself. In this work, we investigate the dependence of the hybrid Eulerian-Lagrangian plume rise scheme embedded in the Lagrangian stochastic particle model SPRAY-WEB on the drag coefficient and on the horizontal resolution of the plume rise grid. We test four different drag coefficient models depending on the Reynolds number of the cells as well as a constant drag coefficient. As for the horizontal resolution, we use three different horizontal cell sizes: 200 m, 400 m, and 600 m, namely roughly a quarter, a half, and three-quarters of the source size. We compare the simulation results with the observations taken during a field experiment performed in Idaho organized by the US Environmental Protection Agency, where they collected lidar data and aircraft CO concentration measurements. We found that the drag coefficient influences mainly the plume near the source, where the drag role is more important due to the higher vertical velocities. It has also turned out that the best cell-to-source size ratio for our purpose is one to two.

Residential wood burning has both practical and traditional values among many indigenous communities of the US Mountain West, although household biomass burning also results in emissions that are harmful to health. In a household-level three-arm placebo-controlled randomized trial, we tested the efficacy of portable filtration units and education interventions on improving pulmonary function and blood pressure measures among elder participants that use wood stoves for residential heating. A total of 143 participants were assigned to the Education (n = 49), Filter (n = 47), and Control (n = 47) arms. Blood pressure and spirometry measures were collected multiple times during a pre-intervention winter period and during a follow-up post-intervention winter period. Despite strong PM_2.5 exposure reduction results with the Filter arm (50% lower compared to Control arm), neither this intervention nor the Education intervention translated to improvements in the selected health measures among this population with a mixture of chronic conditions. Intention to treat analysis failed to demonstrate evidence that either of the intervention arms had beneficial effects on the blood pressure or the spirometry measures. Post hoc evaluation of effect modification for blood pressure and spirometry outcomes did not reveal any interaction influence on the outcomes according to sex, residential smoking, chronic disease history, and study area.

ClinicalTrials.gov: NCT02240069.