A hierarchical Bayesian model for the analysis of space-time air pollutant concentrations and an application to air pollution analysis in Northern China

Abstract. Northern China in the 2015 winter months of November and December has witnessed the most severe air pollution phenomena since the 2013 winter haze events occurred, which triggered the first ever Red Alert in the air pollution control history of Beijing, with an instantaneous PM2.5 concentration over 1 mg m−3. Analysis and modeling results show that the worsening meteorology conditions are the main reason behind this unusual increase of air pollutant concentrations and the emission control measures taken during this period of time have contributed to mitigate the air pollution in the region. This work provides a scientific insight of the emission control measures vs. meteorology impacts for the period.

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Attributions of meteorological and emission factors to the 2015 winter severe haze pollution episodes in Northern China

10.5194/acp-2016-798 ◽

2016 ◽

Cited By ~ 1

Author(s):

Tingting Liu ◽

Sunling Gong ◽

Meng Yu ◽

Qichao Zhao ◽

Huairui Li ◽

...

Keyword(s):

Air Pollution ◽

Emission Control ◽

Northern China ◽

Air Pollutant ◽

Control Measures ◽

Air Pollution Control ◽

Pollutant Concentrations ◽

Haze Pollution ◽

Air Pollutant Concentrations ◽

Emission Control Measures

Abstract. Northern China in the 2015 winter months of November and December has witnessed the most severe air pollution phenomena since the 2013 winter haze events occurred, which triggered the first ever Red Alert in the air pollution control history of Beijing, with an instantaneous PM2.5 concentration over 1 mg m−3. Analysis and modeling results show that the worsening meteorology conditions are the main reason behind this unusual increase of air pollutant concentrations and the emission control measures taken during this period of time have contributed to mitigate the air pollution in the region. This work provides a scientific insight of the emission control measures vs. meteorology impacts for the period.

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Analysis of Temporal Variations of Air Pollutant Concentrations in Ogoni Area, Niger Delta Region, Nigeria

Asian Journal of Environment & Ecology ◽

10.9734/ajee/2021/v16i430260 ◽

2021 ◽

pp. 63-73

Author(s):

B. Yorkor ◽

T. G. Leton ◽

J. N. Ugbebor

Keyword(s):

Air Pollution ◽

Temporal Variability ◽

Niger Delta ◽

Air Pollutants ◽

Temporal Variations ◽

Time Of Day ◽

Air Pollutant ◽

Pollutant Concentrations ◽

Hourly Data ◽

Air Pollutant Concentrations

This study investigated the temporal variations of air pollutant concentrations in Ogoni area, Niger Delta, Nigeria. The study used hourly data measured over 8 hours for 12 months at selected locations within the area. The analyses were based on time series and time variations techniques in Openair packages of R programming software. The variations of air pollutant concentrations by time of day and days of week were simulated. Hours of the day, days of the week and monthly variations were graphically simulated. Variations in the mean concentrations of air pollutants by time were determined at 95 % confidence intervals. Sulphur dioxide (SO2), Nitrogen dioxide (NO2), ground level Ozone (O3) and fine particulate matter (PM2.5) concentrations exceeded permissible standards. Air pollutant concentrations showed increase in January, February, November and December compared to other months. Simulation showed that air pollutants varied significantly by hours-of-the-day and days-of-the-week and months-of-the-year. Analysis of temporal variability revealed that air pollutant concentrations increased during weekdays and decreased during weekends. The temporal variability of air pollutants in Ogoni area showed that anthropogenic activities were the main sources of air pollution in the area, therefore further studies are required to determine air pollutant dispersion pattern and evaluation the potential sources of air pollution in the area.

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Associations of Ambient Air Pollutants and Meteorological Factors With COVID-19 Transmission in 31 Chinese Provinces: A Time Series Study

INQUIRY The Journal of Health Care Organization Provision and Financing ◽

10.1177/00469580211060259 ◽

2021 ◽

Vol 58 ◽

pp. 004695802110602

Author(s):

Han Cao ◽

Bingxiao Li ◽

Tianlun Gu ◽

Xiaohui Liu ◽

Kai Meng ◽

...

Keyword(s):

Air Pollution ◽

Relative Humidity ◽

Wind Velocity ◽

Air Pollutants ◽

Meteorological Factors ◽

Meta Analysis ◽

Ambient Air ◽

Air Pollutant ◽

Pollutant Concentrations ◽

Air Pollutant Concentrations

Evidence regarding the effects of environmental factors on COVID-19 transmission is mixed. We aimed to explore the associations of air pollutants and meteorological factors with COVID-19 confirmed cases during the outbreak period throughout China. The number of COVID-19 confirmed cases, air pollutant concentrations, and meteorological factors in China from January 25 to February 29, 2020, (36 days) were extracted from authoritative electronic databases. The associations were estimated for a single-day lag as well as moving averages lag using generalized additive mixed models. Region-specific analyses and meta-analysis were conducted in 5 selected regions from the north to south of China with diverse air pollution levels and weather conditions and sufficient sample size. Nonlinear concentration–response analyses were performed. An increase of each interquartile range in PM2.5, PM10, SO2, NO2, O3, and CO at lag4 corresponded to 1.40 (1.37–1.43), 1.35 (1.32–1.37), 1.01 (1.00–1.02), 1.08 (1.07–1.10), 1.28 (1.27–1.29), and 1.26 (1.24–1.28) ORs of daily new cases, respectively. For 1°C, 1%, and 1 m/s increase in temperature, relative humidity, and wind velocity, the ORs were 0.97 (0.97–0.98), 0.96 (0.96–0.97), and 0.94 (0.92–0.95), respectively. The estimates of PM2.5, PM10, NO2, and all meteorological factors remained significantly after meta-analysis for the five selected regions. The concentration–response relationships showed that higher concentrations of air pollutants and lower meteorological factors were associated with daily new cases increasing. Higher air pollutant concentrations and lower temperature, relative humidity and wind velocity may favor COVID-19 transmission. Controlling ambient air pollution, especially for PM2.5, PM10, NO2, may be an important component of reducing risk of COVID-19 infection. In addition, as winter months are arriving in China, the meteorological factors may play a negative role in prevention. Therefore, it is significant to implement the public health control measures persistently in case another possible pandemic.

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A hierarchical Bayesian model for space-time variation of disease risk

Statistical Modelling ◽

10.1177/1471082x0100100103 ◽

2001 ◽

Vol 1 (1) ◽

pp. 17-29 ◽

Cited By ~ 2

Author(s):

Corrado Lagazio ◽

Emanuela Dreassi ◽

Annibale Biggeri

Keyword(s):

Time Variation ◽

Bayesian Model ◽

Disease Risk ◽

Space Time ◽

Hierarchical Bayesian ◽

Hierarchical Bayesian Model

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Prolonged Exposure to Air Pollution Increases Periodontal Disease Risk: A Nationwide, Population-Based, Cohort Study

Atmosphere ◽

10.3390/atmos12121668 ◽

2021 ◽

Vol 12 (12) ◽

pp. 1668

Author(s):

Han-Jie Lin ◽

Stella Chin-Shaw Tsai ◽

Frank Cheau-Feng Lin ◽

Yi-Chao Hsu ◽

Shih-Wei Chen ◽

...

Keyword(s):

Air Pollution ◽

Cohort Study ◽

Prolonged Exposure ◽

Disease Risk ◽

Cox Proportional Hazards ◽

Air Pollutant ◽

Daily Average ◽

Pollutant Concentrations ◽

Air Pollutant Concentrations

(1) Background: No association between air pollution and periodontitis has yet been shown. Thus, we merged two nationwide databases to evaluate the risk of periodontitis in Taiwanese residents with long-term exposure to air pollution. (2) Methods: We conducted a nationwide retrospective cohort study using the Longitudinal Generation Tracking Database and the Taiwan Air Quality-Monitoring Database. The daily average air pollutant concentrations were categorized into quartiles (Q1, Q2, Q3, and Q4). We carried out Cox proportional hazards models to compute the hazard ratios of periodontitis, with 95% confidence intervals, in Q2–Q4 of the daily average air pollutant concentrations, compared with Q1. (3) Results: the adjusted HR (95 CI%) for periodontitis in Q2–Q4 increased with increased exposure to SO2, CO, NO, NO2, NOX, PM2.5, and PM10 from 1.72 (1.70, 1.76) to 4.86 (4.78–4.94); from 1.89 (1.85–1.93) to 2.64 (2.59–2.70); from 1.04 (1.02–1.06) to 1.52 (1.49–1.55); from 1.61 (1.58–1.64) to 2.51 (2.47–2.56); from 1.48 (1.45–1.51) to 2.11 (2.07–2.15); from 2.02 (1.98–2.06) to 22.9 (22.4–23.4, and from 2.71 (2.66–2.77) to 17.2 (16.8–17.6), respectively, compared to Q1. (4) Conclusions: Residents in Taiwan with long-term exposure to higher levels of air pollutants had a greater risk of periodontitis.

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The role of meteorological conditions and pollution control strategies in reducing air pollution in Beijing during APEC 2014 and Victory Parade 2015

Atmospheric Chemistry and Physics ◽

10.5194/acp-17-13921-2017 ◽

2017 ◽

Vol 17 (22) ◽

pp. 13921-13940 ◽

Cited By ~ 33

Author(s):

Pengfei Liang ◽

Tong Zhu ◽

Yanhua Fang ◽

Yingruo Li ◽

Yiqun Han ◽

...

Keyword(s):

Air Pollution ◽

Pollution Control ◽

Air Pollutants ◽

Meteorological Parameters ◽

Control Strategies ◽

Meteorological Conditions ◽

Air Pollutant ◽

Pollutant Concentrations ◽

Air Pollutant Concentrations

Abstract. To control severe air pollution in China, comprehensive pollution control strategies have been implemented throughout the country in recent years. To evaluate the effectiveness of these strategies, the influence of meteorological conditions on levels of air pollution needs to be determined. Using the intensive air pollution control strategies implemented during the Asia-Pacific Economic Cooperation Forum in 2014 (APEC 2014) and the 2015 China Victory Day Parade (Victory Parade 2015) as examples, we estimated the role of meteorological conditions and pollution control strategies in reducing air pollution levels in Beijing. Atmospheric particulate matter of aerodynamic diameter  ≤ 2.5 µm (PM2.5) samples were collected and gaseous pollutants (SO2, NO, NOx, and O3) were measured online at a site in Peking University (PKU). To determine the influence of meteorological conditions on the levels of air pollution, we first compared the air pollutant concentrations during days with stable meteorological conditions. However, there were few days with stable meteorological conditions during the Victory Parade. As such, we were unable to estimate the level of emission reduction efforts during this period. Finally, a generalized linear regression model (GLM) based only on meteorological parameters was built to predict air pollutant concentrations, which could explain more than 70 % of the variation in air pollutant concentration levels, after incorporating the nonlinear relationships between certain meteorological parameters and the concentrations of air pollutants. Evaluation of the GLM performance revealed that the GLM, even based only on meteorological parameters, could be satisfactory to estimate the contribution of meteorological conditions in reducing air pollution and, hence, the contribution of control strategies in reducing air pollution. Using the GLM, we found that the meteorological conditions and pollution control strategies contributed 30 and 28 % to the reduction of the PM2.5 concentration during APEC and 38 and 25 % during the Victory Parade, respectively, based on the assumption that the concentrations of air pollutants are only determined by meteorological conditions and emission intensities. We also estimated the contribution of meteorological conditions and control strategies in reducing the concentrations of gaseous pollutants and PM2.5 components with the GLMs, revealing the effective control of anthropogenic emissions.

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The Role of Meteorological Conditions and Pollution Control Strategies in Reducing Air Pollution in Beijing during APEC 2014 and Parade 2015

10.5194/acp-2017-456 ◽

2017 ◽

Author(s):

Pengfei Liang ◽

Tong Zhu ◽

Yanhua Fang ◽

Yingruo Li ◽

Yiqun Han ◽

...

Keyword(s):

Air Pollution ◽

Pollution Control ◽

Meteorological Parameters ◽

Control Strategies ◽

Meteorological Conditions ◽

Air Pollutant ◽

Pollutant Concentrations ◽

Air Pollutant Concentrations ◽

Pm2.5 Concentration

Abstract. To control severe air pollution in China, comprehensive pollution control strategies have been implemented throughout the country in recent years. To evaluate the effectiveness of these strategies, the influence of meteorological conditions on levels of air pollution needs to be determined. We therefore developed a generalized linear regression model (GLM) to establish the relationship between the concentrations of air pollutants and meteorological parameters. Using the intensive air pollution control strategies implemented during the Asia-Pacific Economic Cooperation Forum in 2014 (APEC 2014) and the Victory Parade for the Commemoration of the 70th Anniversary of the Chinese Anti-Japanese War and the World Anti-Fascist War in 2015 (Parade 2015) as examples, we estimated the role of meteorological conditions and pollution control strategies in reducing air pollution levels in Beijing. During the APEC (1 October to 31 December 2014) and Parade (1 August to 31 December 2015) sampling periods, atmospheric particulate matter of aerodynamic diameter ≤ 2.5 μm (PM2.5) samples were collected and gaseous pollutants (SO2, NO, NOx, and O3) were measured online at a site in Peking University (PKU). The concentrations of all pollutants except ozone decreased dramatically (by more than 20 %) during both events, compared with the levels during non-control periods. To determine the influence of meteorological conditions on the levels of air pollution, we first compared the air pollutant concentrations during days with stable meteorological conditions (i.e. when the daily average wind speed (WS) was less than 2.50 m s−1 and planetary boundary layer (PBL) height was lower than 290 m). We found that the average PM2.5 concentration during APEC decreased by 45.7 % compared with the period before APEC and by 44.4 % compared with the period after APEC. This difference was attributed to emission reduction efforts during APEC. However, there were few days with stable meteorological conditions during Parade. As such, we were unable to estimate the level of emission reduction efforts during this period. Finally, GLMs based only on meteorological parameters were built to predict air pollutant concentrations, which could explain more than 70 % of the variation in air pollutant concentration levels, after incorporating the nonlinear relationships between certain meteorological parameters and the concentrations of air pollutants. Evaluation of the GLM performance revealed that the GLM, even based only on meteorological parameters, could be satisfactory to estimate the contribution of meteorological conditions in reducing air pollution, and hence the contribution of control strategies in reducing air pollution. Using the GLM, we found that the meteorological conditions and pollution control strategies contributed 30 % and 28 % to the reduction of the PM2.5 concentration during APEC 2014, and 38 % and 25 % during Parade 2015. We also estimated the contribution of meteorological conditions and control strategies implemented during the two events in reducing the concentrations of gaseous pollutants and PM2.5 components with the GLMs, revealing the effective control of anthropogenic emissions.

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30 Years of Air Quality Trends in Japan

Atmosphere ◽

10.3390/atmos12081072 ◽

2021 ◽

Vol 12 (8) ◽

pp. 1072

Author(s):

Akiyoshi Ito ◽

Shinji Wakamatsu ◽

Tazuko Morikawa ◽

Shinji Kobayashi

Keyword(s):

Air Pollution ◽

Air Quality ◽

Air Pollutant ◽

Control Measures ◽

Related Substances ◽

Pollutant Concentrations ◽

Exhaust Particles ◽

Air Pollutant Concentrations ◽

Atmospheric Concentrations ◽

Pollution Concentrations

The aim of this paper is to obtain information that will contribute to measures and research needed to further improve the air quality in Japan. The trends and characteristics of air pollutant concentrations, especially PM2.5, ozone, and related substances, over the past 30 years, are analyzed, and the relationships between concentrations and emissions are discussed quantitatively. We found that PM2.5 mass concentrations have decreased, with the largest reduction in elemental carbon (EC) as the PM2.5 component. The concentrations of organic carbon (OC) have not changed significantly compared to other components, suggesting that especially VOC emissions as precursors need to be reduced. In addition, the analysis of the differences in PM2.5 concentrations between the ambient and the roadside showed that further research on non-exhaust particles is needed. For NOx and SO2, there is a linear relationship between domestic anthropogenic emissions and atmospheric concentrations, indicating that emission control measures are directly effective in the reduction in concentrations. Also, recent air pollution episodes and the effect of reduced economic activity, as a consequence of COVID-19, on air pollution concentrations are summarized.

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Estimating the Causal Effects of Cruise Traffic on Air Pollution using Randomization-Based Inference

10.31219/osf.io/v7ctk ◽

2021 ◽

Author(s):

Léo Zabrocki ◽

Marion Leroutier ◽

Marie-Abèle Bind

Keyword(s):

Air Pollution ◽

Time Series Data ◽

Air Pollutant ◽

Series Data ◽

Randomized Experiments ◽

Adverse Health Effects ◽

Maritime Traffic ◽

Pollutant Concentrations ◽

Air Pollutant Concentrations ◽

Matched Data

Local environmental organizations and media have recently expressed concerns over air pollution induced by maritime traffic and its potential adverse health effects on the population of Mediterranean port cities. We explore this issue with unique high-frequency data from Marseille, France’s largest port for cruise ships, over the 2008- 2018 period. Using a new pair-matching algorithm designed for time series data, we create hypothetical randomized experiments and estimate the variation in air pollutant concentrations caused by a short-term increase in cruise vessel traffic. We carry out a randomization-based approach to compute 95% Fisherian intervals (FI) for constant treatment effects consistent with the matched data and the hypothetical intervention. At the hourly level, cruise vessels’ arrivals increase concentrations of nitrogen dioxide (NO2) by 4.7 μg/m³ (95% FI: [1.4, 8.0]), of sulfur dioxide (SO2) by 1.2 μg/m³ (95% FI: [-0.1, 2.5]), and of particulate matter (PM10) by 4.6 μg/m³ (95% FI: [0.9, 8.3]). At the daily level, cruise traffic increases concentrations of NO2 by 1.2 μg/m³ (95% FI: [-0.5, 3.0]) and of PM10 by 1.3 μg/m³ (95% FI: [-0.3, 3.0]). Our results suggest that well-designed hypothetical randomized experiments provide a principled approach to better understand the negative externalities of maritime traffic.

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