The short-term effects of air pollutants on pneumonia hospital admissions in Lanzhou, China, 2014–2019: evidence of ecological time-series study

Jin, Limei; Zhou, Tian; Fang, Shuya; Zhou, Xiaowen; Han, Bisen; Bai, Yana

doi:10.1007/s11869-022-01244-6

Cited by 10 publications

(3 citation statements)

References 35 publications

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“…When the concentrations of PM10, PM2.5, SO2, NO2, and CO increased by 10 μg/m 3 (0.1 mg/m 3 for CO), the maximum increase in the number of hospitalizations within 7 days was 0.72%, 0.79%, 3.57%, 3.16%, and 1.52%, respectively. A study in Lanzhou showed that when the concentrations of PM10, PM2.5, SO2, NO2, and CO increased by 10 μg/m 3 (0.1 mg/m 3 for CO), the risk of pneumonia hospitalizations increased by 1.01%, 1.04%, 1.09%, 1.07%, and 1.16%, respectively (27). Previous studies have verified the relationship between air pollutants and pneumonia.…”

Section: Discussionmentioning

confidence: 97%

Pneumonia hospitalization risk attributable to ambient air pollution and temperature in a mid-temperate, industrial city: a time-series analysis

Jia

et al. 2023

Preprint

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Background Pneumonia has become a public health problem of global concern, in which air pollution and meteorological conditions were important influencing factors. Methods A time series analysis was conducted on the number of pneumonia hospitalizations. The generalized additive model and distributed lag nonlinear model were used to investigate the single-day and cumulative lag-day effects of air pollutants and temperature on pneumonia hospitalizations. Results Air pollutants and meteorological factors were significantly associated with pneumonia hospitalizations. Over 7 days cumulative lag time, when the PM2.5, PM10, SO2, CO, and NO2 increased by 10 µg/m3(0.1 mg/m3 for CO), pneumonia hospitalizations increased by 0.56% (95% CI: 0.30, 0.81), 0.82% (95% CI: 0.62, 1.03), 4.74% (95% CI: 3.98, 5.50), 1.99% (95% CI: 1.60, 2.38), and 5.00% (95% CI: 4.24, 5.75) respectively, women and children are at higher risk. Within a cumulative lag time of 7 days, extreme cold (-18°C versus − 1°C) and extreme heat (27°C versus − 1°C) increased the risk of pneumonia hospitalizations by 8.96% (95% CI: 0.20, 18.49) and 40.78% (95% CI: 21.85, 62.65), respectively, with a higher risk in males, children, and elderly individuals. Conclusions From 2015 to 2019, pneumonia in Changchun showed an increasing trend and decreased sharply in 2020. Increased concentrations of air pollutants (PM2.5, PM10, SO2, CO, and NO2) led to an increased risk of pneumonia hospitalizations, with a significant lag effect, among them, SO2 and NO2 are the strongest effect. Extreme heat and cold can lead to an increased risk of pneumonia hospitalizations.

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Section: Discussionmentioning

confidence: 97%

Pneumonia hospitalization risk attributable to ambient air pollution and temperature in a mid-temperate, industrial city: a time-series analysis

Jia

et al. 2023

Preprint

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“…Moreover, it was previously ranked as the most polluted city among the provincial capitals in China, and the main urban areas include the four districts (Chengguan, Qilihe, Xigu, and Anning) shown in Figure A1. Mountains to the south and north surround the Lanzhou city core, a typical valley city, extending mainly from east to west and approximately 40 km long; the narrowest width from north to south is approximately 3 km [68]. Overall, the city's shape is similar to that of a saddle city.…”

Section: Appendix Amentioning

confidence: 95%

Land Use Regression Models for Particle Number Concentration and Black Carbon in Lanzhou, Northwest of China

Fang,

Zhou,

Jin

et al. 2023

Sustainability

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It is necessary to predict the spatial variation in particle number concentration (PNC) and black carbon (BC) because they are considered air pollutants associated with traffic and many diseases. In this study, land use regression (LUR) models for PNC and BC were developed based on a mobile monitoring campaign in January 2020 in Lanzhou, and the performance of models was evaluated with hold-out validation (HV) and leave-one-out cross-validation (LOOCV). The results show that the adjusted R2 of the LUR models for PNC and BC are 0.51 and 0.53, respectively. The R2 of HV and LOOCV are 0.43 and 0.44, respectively, for the PNC model and 0.42 and 0.50, respectively, for the BC model. The performances of the LUR models are of a moderate level. The spatial distribution of the predicted PNC is related to the distance from water bodies. The high PNC is related to industrial pollution. The BC concentration decreases from south to north. High BC concentrations are associated with freight distribution centres and coal-fired power plants. The range of PNC particle sizes in this study is larger than in most studies. As one of few studies in Lanzhou to develop LUR models of air pollutants, it is important to accurately estimate pollutant concentrations to improve air quality and provide health benefits for residents.

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“…Dust aerosols can also accelerate snow melting by altering the surface albedo of the snow and ice sheets [6][7][8]. From a public health perspective, mineral dust can transport pathogens and anthropogenic pollutants that trigger a variety of respiratory and cardiovascular diseases, as well as additional systemic pathologies [9,10]. Mineral dust's vertical characteristics are essential to accurately evaluate its climate forcing and transboundary transportation to downstream areas [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Investigation of the Vertical Distribution Characteristics and Microphysical Properties of Summer Mineral Dust Masses over the Taklimakan Desert Using an Unmanned Aerial Vehicle

Zhou

Fang

et al. 2023

Remote Sensing

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Investigating the vertical distribution of mineral dust masses and their microphysical properties is crucial for accurately assessing the climate effects of dust. However, there are limited studies related to relevant in situ observations over dust source areas. In this study, the near-surface vertical characteristics (within 500 m a.g.l) of dust mass concentrations in five size fractions (PMs: TSP, PM10, PM4, PM2.5, and PM1) were investigated using an unmanned aerial vehicle (UAV) in Tazhong (TZ) in the Taklimakan Desert (TD) in July 2021. To the best of our knowledge, the vertical profiles of particle number concentration (PNC), effective radius (Reff), and volume concentration (Cv) were obtained for the first time by UAV over the TD. Four scenarios of clear sky, floating dust, blowing sand, and dust storm were selected based on the classification criteria for PMs. The PMs, PNC, Reff, and Cv decreased with height for all scenarios. From clear-sky to dust-storm scenarios PMs, PNC, Reff, and Cv in the column gradually increased. Reff (Cv) increased from 1.15 μm (0.08 μm3/μm2) to 4.53 μm (0.74 μm3/μm2). The diurnal variations of PMs, PNC, and Reff (Cv) revealed a unimodal pattern, with the peak occurring between 13:00 and 16:00, due to the evolution of wind speed and the atmospheric boundary layer in TZ. Unexpectedly, among the three postprecipitation scenarios (P1, P2, and P3), the PNC of P2 was smaller than those of P1 and P3. The Reff (Cv) for P2 was similar to or greater than that for dust storms, which may be associated with moist dust particles on the ground surface being carried into the air by wind. These investigations add to our understanding of the mineral dust vertical characteristics over the source area, and provide a meaningful reference for colocated lidar inversion and dust simulations.

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The short-term effects of air pollutants on pneumonia hospital admissions in Lanzhou, China, 2014–2019: evidence of ecological time-series study

Cited by 10 publications

References 35 publications

Pneumonia hospitalization risk attributable to ambient air pollution and temperature in a mid-temperate, industrial city: a time-series analysis

Pneumonia hospitalization risk attributable to ambient air pollution and temperature in a mid-temperate, industrial city: a time-series analysis

Land Use Regression Models for Particle Number Concentration and Black Carbon in Lanzhou, Northwest of China

Investigation of the Vertical Distribution Characteristics and Microphysical Properties of Summer Mineral Dust Masses over the Taklimakan Desert Using an Unmanned Aerial Vehicle

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