scholarly journals Combining Cluster Analysis of Air Pollution and Meteorological Data with Receptor Model Results for Ambient PM2.5 and PM10

2020 ◽  
Vol 17 (22) ◽  
pp. 8455
Author(s):  
Héctor Jorquera ◽  
Ana María Villalobos
Keyword(s):  
Air Pollution ◽  
Time Series ◽  
Cluster Analysis ◽  
Meteorological Data ◽  
Short Term ◽  
Pollution Regulation ◽  
Potential Applications ◽  
Pm2.5 And Pm10 ◽  
Air Pollution Regulation ◽  
Justice Studies

Air pollution regulation requires knowing major sources on any given zone, setting specific controls, and assessing how health risks evolve in response to those controls. Receptor models (RM) can identify major sources: transport, industry, residential, etc. However, RM results are typically available for short term periods, and there is a paucity of RM results for developing countries. We propose to combine a cluster analysis (CA) of air pollution and meteorological measurements with a short-term RM analysis to estimate a long-term, hourly source apportionment of ambient PM2.5 and PM10. We have developed a proof of the concept for this proposed methodology in three case studies: a large metropolitan zone, a city with dominant residential wood burning (RWB) emissions, and a city in the middle of a desert region. We have found it feasible to identify the major sources in the CA results and obtain hourly time series of their contributions, effectively extending short-term RM results to the whole ambient monitoring period. This methodology adds value to existing ambient data. The hourly time series results would allow researchers to apportion health benefits associated with specific air pollution regulations, estimate source-specific trends, improve emission inventories, and conduct environmental justice studies, among several potential applications.

scholarly journals Short-term Exposure of PM2.5 and PM10 Increases the Number of Outpatients with Eczema in Guangzhou: A Time-Series Study

2020 ◽  
Author(s):  
Ji Zhang ◽  
Yicheng Yang ◽  
Jing Xu ◽  
Dian Jing ◽  
Bo Sun ◽  
...  
Keyword(s):  
Air Pollution ◽  
Meteorological Data ◽  
Additive Model ◽  
Positive Association ◽  
The Elderly ◽  
Short Term ◽  
Outpatient Visits ◽  
Short Term Exposure ◽  
Pm2.5 And Pm10 ◽  
The Relationship

Abstract Background: The worldwide prevalence of eczema has continued to rise over the past decades.This has led to emphasis on the association between air pollution and eczema. This study investigated the relationship between daily exposure to air pollution and the number of eczema outpatient visits in Guangzhou with the overarching goal of providing novel insights on the interventions for eczema aggravation and prevention.Methods: Daily air pollution data, meteorological data, and number of eczema outpatients were obtained from 18th January 2013 to 31st December 2018 in Guangzhou. A generalized additive model with Poisson distribution was used to assess the association between the number of eczema outpatient visits and short-term exposure of PM2.5 and PM10. In addition, the effect of PM2.5 and PM10 by age (<65 years, ≥65 years) and gender was evaluated. Results: A total of 293,343 eczema outpatient visits were recorded. The obtained results indicated that a 10μg/m3 increase of the same day/ lag 1 day/ lag 2 days PM2.5 was associated with increments of 2.33%(RR=1.0233, 95%CI: 1.0206-1.0260, P<0.001), 1.81% (RR=1.0181, 95%CI: 1.0153-1.0209, P<0.001), and 0.95%(RR=1.0095, 95%CI: 1.0068-1.0123, P<0.001) in eczema outpatients risk, respectively. On the other hand, a 10μg/m3 increase of PM10 was associated with eczema outpatients risk increments of 1.97%(RR=1.0197, 95%CI: 1.0177-1.0217, P<0.001), 1.65%(RR=1.0165, 95%CI: 1.0145-1.0186, P<0.001), and 0.98%(RR=1.0098, 95%CI: 1.0078-1.0118, P<0.001), respectively. Furthermore, the effects of PM on the increment of eczema were similar in the male and female groups. Results obtained after age stratification analyses indicated that the strongest positive association between PM2.5 exposure and eczema were observed at lag 0 day with the percent changes being 4.72% (95%CI, 4.18-5.28%, P<0.001), 1.92%(95%CI: 1.65-2.19%, P<0.001) and 3.34% (95%CI, 2.9- 3.78%, P<0.001) in <12 years old, ≥12 and <65years old, and ≥65 years old groups, respectively. Conclusion: Short-term exposure of PM2.5 and PM10 increases the number of eczema outpatients especially among children and the elderly. This study has provided a further understanding of the relationship between air pollutants and eczema, which will benefit disease prevention and lower the health burden.

scholarly journals PREDICTING DAILY PM2.5 USING WEIGHTED LONG SHORT-TERM MEMORY NEURAL NETWORK MODEL

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 1451-1455
Author(s):  
H. Fan ◽  
M. Yang ◽  
F. Xiao ◽  
K. Zhao
Keyword(s):  
Neural Network ◽  
Air Pollution ◽  
Short Term Memory ◽  
Meteorological Data ◽  
Series Data ◽  
Wind Condition ◽  
Short Term ◽  
Term Memory ◽  
Long Short Term Memory ◽  
Pm2.5 Concentration

Abstract. Over the past few decades, air pollution has caused serious damage on public health, thus making accurate predictions of PM2.5 crucial. Due to the transportation of air pollutants among areas, the PM2.5 concentration is strongly spatiotemporal correlated. However, the distribution of air pollution monitoring sites is not even, making the spatiotemporal correlation between the central site and surrounding sites varies with different density of sites, and this was neglected by most existing methods. To tackle this problem, this study proposed a weighted long short-term memory neural network extended model (WLSTME), which addressed the issue that how to consider the effect of the density of sites and wind condition on the spatiotemporal correlation of air pollution concentration. First, several the nearest surrounding sites were chosen as the neighbour sites to the central station, and their distance as well as their air pollution concentration and wind condition were input to multi-layer perception (MLP) to generate weighted historical PM2.5 time series data. Second, historical PM2.5 concentration of the central site and weighted PM2.5 series data of neighbour sites were input into LSTM to address spatiotemporal dependency simultaneously and extract spatiotemporal features. Finally, another MLP was utilized to integrate spatiotemporal features extracted above with the meteorological data of central site to generate the forecasts future PM_2.5 concentration of the central site. Daily PM_2.5 concentration and meteorological data on Beijing–Tianjin–Hebei from 2015 to 2017 were collected to train models and evaluate the performance. Experimental results with 3 other methods showed that the proposed WLSTME model has the lowest RMSE (40.67) and MAE (26.10) and the highest p (0.59). This finding confirms that WLSTME can significantly improve the PM2.5 prediction accuracy.

scholarly journals Short-Term Effects of Ambient Air Pollution On Daily Emergency Room Visits for Abdominal Pain: A Time-Series Study in Wuhan, China

2021 ◽  
Author(s):  
Yaqi Liu ◽  
Yi Jiang ◽  
Manyi Wu ◽  
Sunghar Muheyat ◽  
Dongai Yao ◽  
...  
Keyword(s):  
Air Pollution ◽  
Time Series ◽  
Abdominal Pain ◽  
Air Pollutants ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
Emergency Room Visits ◽  
Short Term ◽  
Time Series Study ◽  
Series Study

Abstract Background There are few studies focused on the correlations between ambient air pollution and abdominal pain, especially in emergency departments in China. Method: Daily data (from January 1, 2016 to December 31, 2018), including air pollution concentration (SO2, NO2, PM2.5, PM10, CO, and O3) and meteorological variables, for daily emergency room visits (ERVs) were collected in Wuhan, China. We conducted a time-series study to investigate the potential correlation between six ambient air pollutants and ERVs for abdominal pain and their effects, in different genders, ages and seasons. Results A total of 16,306 abdominal pain ERVs were identified during the study period. A 10-µg/m3 increase in concentration of SO2, NO2, PM2.5, PM10, CO, and O3 corresponded respectively to incremental increases in abdominal pain of 6.12% (95% confidence interval [CI]: -0.44-13.12), 1.65% (95%CI: -0.25-3.59), 1.12% (95%CI: -0.18-2.44), 0.38% (95%CI: -1.09-1.87), 9.87% (95%CI:3.14–17.05) and 1.11% (95%CI: 0.03–2.21). We observed significant correlations between CO and O3 and daily abdominal pain ERVs increase, and positive but insignificant correlations between the other pollutants and ERVs. The effects were stronger mainly for females (especially SO2 and O3) and younger people (especially CO and O3). The correlations of PM2.5 and PM10 were stronger in cool seasons, while the correlation of CO was stronger in warm seasons. Conclusion Our time-series study suggested that short-term exposure to air pollution (especially CO and O3) was positively correlated with ERVs for abdominal pain in Wuhan, China, and that their effects varied by season, gender and age. These data can add evidence on how air pollutants affect the human body, and may prompt hospitals to take specific precautions on polluted days and maintain order in emergency departments made busier due to the pollution.

scholarly journals Short-Term Effects of Ambient Air Pollution on Hospitalization for Respiratory Disease in Taiyuan, China: A Time-Series Analysis

2018 ◽  
Vol 15 (10) ◽  
pp. 2160 ◽  
Author(s):  
Lisha Luo ◽  
Yunquan Zhang ◽  
Junfeng Jiang ◽  
Hanghang Luan ◽  
Chuanhua Yu ◽  
...  
Keyword(s):  
Air Pollution ◽  
Time Series ◽  
Respiratory Disease ◽  
Air Pollutants ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
High Risk Population ◽  
Short Term ◽  
Ambient Air Pollutants ◽  
Short Term Effects

In this study, we estimated the short-term effects of ambient air pollution on respiratory disease hospitalization in Taiyuan, China. Daily data of respiratory disease hospitalization, daily concentration of ambient air pollutants and meteorological factors from 1 October 2014 to 30 September 2017 in Taiyuan were included in our study. We conducted a time-series study design and applied a generalized additive model to evaluate the association between every 10-μg/m3 increment of air pollutants and percent increase of respiratory disease hospitalization. A total of 127,565 respiratory disease hospitalization cases were included in this study during the present period. In single-pollutant models, the effect values in multi-day lags were greater than those in single-day lags. PM2.5 at lag02 days, SO2 at lag03 days, PM10 and NO2 at lag05 days were observed to be strongly and significantly associated with respiratory disease hospitalization. No significant association was found between O3 and respiratory disease hospitalization. SO2 and NO2 were still significantly associated with hospitalization after adjusting for PM2.5 or PM10 into two-pollutant models. Females and younger population for respiratory disease were more vulnerable to air pollution than males and older groups. Therefore, some effective measures should be taken to strengthen the management of the ambient air pollutants, especially SO2 and NO2, and to enhance the protection of the high-risk population from air pollutants, thereby reducing the burden of respiratory disease caused by ambient air pollution.

scholarly journals Conservation cobenefits from air pollution regulation: Evidence from birds

2020 ◽  
Vol 117 (49) ◽  
pp. 30900-30906 ◽  
Author(s):  
Yuanning Liang ◽  
Ivan Rudik ◽  
Eric Yongchen Zou ◽  
Alison Johnston ◽  
Amanda D. Rodewald ◽  
...  
Keyword(s):  
Air Pollution ◽  
Large Scale ◽  
Population Decline ◽  
The United States ◽  
Bird Conservation ◽  
Bird Abundance ◽  
Bird Populations ◽  
The Past ◽  
Pollution Regulation ◽  
Air Pollution Regulation

Massive wildlife losses over the past 50 y have brought new urgency to identifying both the drivers of population decline and potential solutions. We provide large-scale evidence that air pollution, specifically ozone, is associated with declines in bird abundance in the United States. We show that an air pollution regulation limiting ozone precursors emissions has delivered substantial benefits to bird conservation. Our estimates imply that air quality improvements over the past 4 decades have stemmed the decline in bird populations, averting the loss of 1.5 billion birds, ∼20% of current totals. Our results highlight that in addition to protecting human health, air pollution regulations have previously unrecognized and unquantified conservation cobenefits.

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