scholarly journals The effects of PM2.5 concentration on residents' health from the perspective of spatial economics

2021 ◽  
Author(s):  
Shiwei Wu
Keyword(s):  
Spatial Economics ◽  
Pm2.5 Concentration

PM2.5 Concentration Prediction for Air Pollution using Machine Learning Algorithms

2019 ◽  
Vol 28 (1) ◽  
pp. 349-354 ◽  
Author(s):  
Ahmed Samy Abd El Aziz Moursi ◽  
Marwa Shouman ◽  
Ezz El-din Hemdan ◽  
Nawal El-Fishawy
Keyword(s):  
Machine Learning ◽  
Air Pollution ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Concentration Prediction ◽  
Pm2.5 Concentration

scholarly journals The Synergistic Effect of PM2.5 and CO2 Concentrations on Occupant Satisfaction and Work Productivity in a Meeting Room

2021 ◽  
Vol 18 (8) ◽  
pp. 4109
Author(s):  
Jindong Wu ◽  
Jiantao Weng ◽  
Bing Xia ◽  
Yujie Zhao ◽  
Qiuji Song
Keyword(s):  
Air Quality ◽  
Synergistic Effect ◽  
Work Productivity ◽  
Co2 Concentration ◽  
Human Beings ◽  
Meeting Room ◽  
Negative Effect ◽  
Carbon Dioxide Co2 ◽  
Occupant Satisfaction ◽  
Pm2.5 Concentration

High indoor air quality is crucial for the health of human beings. The purpose of this work is to analyze the synergistic effect of particulate matter 2.5 (PM2.5) and carbon dioxide (CO2) concentration on occupant satisfaction and work productivity. This study carried out a real-scale experiments in a meeting room with exposures of up to one hour. Indoor environment parameters, including air temperature, relative humidity, illuminance, and noise level, were controlled at a reasonable level. Twenty-nine young participants were participated in the experiments. Four mental tasks were conducted to quantitatively evaluate the work productivity of occupants and a questionnaire was used to access participants’ satisfaction. The Spearman correlation analysis and two-way analysis of variance were applied. It was found that the overall performance declined by 1% for every 10 μg/m3 increase in PM2.5 concentration. Moreover, for every 10% increase in dissatisfaction with air quality, productivity performance decreased by 1.1% or more. It should be noted that a high CO2 concentration (800 ppm) has a stronger negative effect on occupant satisfaction towards air quality than PM2.5 concentration in a non-ventilated room. In order to obtain optimal occupant satisfaction and work productivity, low concentrations of PM2.5 (<50 μg/m3) and CO2 (<700 ppm) are recommended.

scholarly journals Assessment of the Dynamic Exposure to PM2.5 Based on Hourly Cell Phone Location and Land Use Regression Model in Beijing

2021 ◽  
Vol 18 (11) ◽  
pp. 5884
Author(s):  
Junli Liu ◽  
Panli Cai ◽  
Jin Dong ◽  
Junshun Wang ◽  
Runkui Li ◽  
...  
Keyword(s):  
Land Use ◽  
Exposure Assessment ◽  
Activity Pattern ◽  
Cell Phone ◽  
Total Population ◽  
Cell Phones ◽  
Land Use Regression ◽  
Pm2.5 Exposure ◽  
Dynamic Exposure ◽  
Pm2.5 Concentration

The spatiotemporal locations of large populations are difficult to clearly characterize using traditional exposure assessment, mainly due to their complicated daily intraurban activities. This study aimed to extract hourly locations for the total population of Beijing based on cell phone data and assess their dynamic exposure to ambient PM2.5. The locations of residents were located by the cellular base stations that were keeping in contact with their cell phones. The diurnal activity pattern of the total population was investigated through the dynamic spatial distribution of all of the cell phones. The outdoor PM2.5 concentration was predicted in detail using a land use regression (LUR) model. The hourly PM2.5 map was overlapped with the hourly distribution of people for dynamic PM2.5 exposure estimation. For the mobile-derived total population, the mean level of PM2.5 exposure was 89.5 μg/m3 during the period from 2013 to 2015, which was higher than that reported for the census population (87.9 μg/m3). The hourly activity pattern showed that more than 10% of the total population commuted into the center of Beijing (e.g., the 5th ring road) during the daytime. On average, the PM2.5 concentration at workplaces was generally higher than in residential areas. The dynamic PM2.5 exposure pattern also varied with seasons. This study exhibited the strengths of mobile location in deriving the daily spatiotemporal activity patterns of the population in a megacity. This technology would refine future exposure assessment, including either small group cohort studies or city-level large population assessments.

scholarly journals The Combined Effects of Fine Particulate Matter and Temperature on Preterm Birth in Seoul, 2010–2016

2021 ◽  
Vol 18 (4) ◽  
pp. 1463
Author(s):  
Youngrin Kwag ◽  
Min-ho Kim ◽  
Shinhee Ye ◽  
Jongmin Oh ◽  
Gyeyoon Yim ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Preterm Birth ◽  
Pregnant Women ◽  
Low Temperatures ◽  
Fine Particulate Matter ◽  
Temperature Data ◽  
Fine Particulate ◽  
The Mean ◽  
Pm2.5 Exposure ◽  
Pm2.5 Concentration

Background: Preterm birth contributes to the morbidity and mortality of newborns and infants. Recent studies have shown that maternal exposure to particulate matter and extreme temperatures results in immune dysfunction, which can induce preterm birth. This study aimed to evaluate the association between fine particulate matter (PM2.5) exposure, temperature, and preterm birth in Seoul, Republic of Korea. Methods: We used 2010–2016 birth data from Seoul, obtained from the Korea National Statistical Office Microdata. PM2.5 concentration data from Seoul were generated through the Community Multiscale Air Quality (CMAQ) model. Seoul temperature data were collected from the Korea Meteorological Administration (KMA). The exposure period of PM2.5 and temperature were divided into the first (TR1), second (TR2), and third (TR3) trimesters of pregnancy. The mean PM2.5 concentration was used in units of ×10 µg/m3 and the mean temperature was divided into four categories based on quartiles. Logistic regression analyses were performed to evaluate the association between PM2.5 exposure and preterm birth, as well as the combined effects of PM2.5 exposure and temperature on preterm birth. Result: In a model that includes three trimesters of PM2.5 and temperature data as exposures, which assumes an interaction between PM2.5 and temperature in each trimester, the risk of preterm birth was positively associated with TR1 PM2.5 exposure among pregnant women exposed to relatively low mean temperatures (<3.4 °C) during TR1 (OR 1.134, 95% CI 1.061–1.213, p < 0.001). Conclusions: When we assumed the interaction between PM2.5 exposure and temperature exposure, PM2.5 exposure during TR1 increased the risk of preterm birth among pregnant women exposed to low temperatures during TR1. Pregnant women should be aware of the risk associated with combined exposure to particulate matter and low temperatures during TR1 to prevent preterm birth.

scholarly journals Trends in PM2.5 Concentration in Nagoya, Japan, from 2003 to 2018 and Impacts of PM2.5 Countermeasures

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 590
Author(s):  
Makiko Yamagami ◽  
Fumikazu Ikemori ◽  
Hironori Nakashima ◽  
Kunihiro Hisatsune ◽  
Kayo Ueda ◽  
...  
Keyword(s):  
Fine Particulate Matter ◽  
Control Measures ◽  
Source Control ◽  
Atmospheric Concentration ◽  
Construction Machinery ◽  
Emission Regulations ◽  
Volatile Organic ◽  
Stationary Sources ◽  
Pm2.5 Concentration

In Japan, various countermeasures have been undertaken to reduce the atmospheric concentration of fine particulate matter (PM2.5). We evaluated the extent to which these countermeasures were effective in reducing PM2.5 concentrations by analyzing the long-term concentration trends of the major components of PM2.5 and their emissions in Nagoya City. PM2.5 concentrations decreased by 53% over the 16-year period from fiscal years 2003 to 2018 in Nagoya City. Elemental carbon (EC) was the component of PM2.5 with the greatest decrease in concentration over the 16 years, decreasing by 4.3 μg/m3, followed by SO42− (3.0 μg/m3), organic carbon (OC) (2.0 μg/m3), NH4+ (1.6 μg/m3), and NO3− (1.3 μg/m3). The decrease in EC concentration was found to be caused largely by the effect of diesel emission control. OC concentrations decreased because of the effects of volatile organic compound (VOC) emission regulations for stationary sources and reductions in VOCs emitted by vehicles and construction machinery. NO3− concentrations decreased alongside decreased contributions from vehicles, construction machinery, and stationary sources, in descending order of the magnitude of decrease. Although these findings identify some source control measures that have been effective in reducing PM2.5, they also reveal the ineffectiveness of some recent countermeasures for various components, such as those targeting OC concentrations.

scholarly journals Effectiveness of SOx, NOx, and Primary Particulate Matter Control Strategies in the Improvement of Ambient PM Concentration in Taiwan

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 460
Author(s):  
Jiun-Horng Tsai ◽  
Ming-Ye Lee ◽  
Hung-Lung Chiang
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Model Simulation ◽  
Control Strategies ◽  
Ambient Air ◽  
Clean Air Act ◽  
Control Measures ◽  
Control Plan ◽  
Clean Air ◽  
Pm2.5 Concentration

The Community Multiscale Air Quality (CMAQ) measurement was employed for evaluating the effectiveness of fine particulate matter control strategies in Taiwan. There are three scenarios as follows: (I) the 2014 baseline year emission, (II) 2020 emissions reduced via the Clean Air Act (CAA), and (III) other emissions reduced stringently via the Clean Air Act. Based on the Taiwan Emission Data System (TEDs) 8.1, established in 2014, the emission of particulate matter 2.5 (PM2.5) was 73.5 thousand tons y−1, that of SOx was 121.3 thousand tons y−1, and that of NOx was 404.4 thousand tons y−1 in Taiwan. The CMAQ model simulation indicated that the PM2.5 concentration was 21.9 μg m−3. This could be underestimated by 24% in comparison with data from the ambient air quality monitoring stations of the Taiwan Environmental Protection Administration (TEPA). The results of the simulation of the PM2.5 concentration showed high PM2.5 concentrations in central and southwestern Taiwan, especially in Taichung and Kaohsiung. Compared to scenario I, the average annual concentrations of PM2.5 for scenario II and scenario III showed reductions of 20.1% and 28.8%, respectively. From the results derived from the simulation, it can be seen that control of NOx emissions may improve daily airborne PM2.5 concentrations in Taiwan significantly and control of directly emitted PM2.5 emissions may improve airborne PM2.5 concentrations each month. Nevertheless, the results reveal that the preliminary control plan could not achievethe air quality standard. Therefore, the efficacy and effectiveness of the control measures must be considered to better reduce emissions in the future.

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