Dataset Information

The Effects of Fireworks Discharge on Atmospheric PM_2.5 Concentration in the Chinese Lunar New Year.

ABSTRACT: Discharging fireworks during the Chinese Lunar New Year celebrations is a deep-rooted custom in China. In this paper, we analyze the effect of this cultural activity on PM_2.5 concentration using both ground observations and satellite data. By combining remote sensing data, the problem of uneven spatial distribution of ground monitoring has been compensated, and the research time span has been expanded. The results show that the extensive firework displays on New Year's Eve lead to a remarkable increase in nationwide PM_2.5 concentration, which were 159~223% of the average level, indicating the instantaneous effect far exceeds that of any other factor over the whole year. However, the averaged PM_2.5 concentrations of the celebration period were 0.99~16.32 ?g/m³ lower compared to the average values of the corresponding pre-celebration period and post-celebration period, indicating the sustained effect is not very significant. The implementation of firework prohibition policies can greatly reduce the instantaneous PM_2.5 increase, but no obvious air quality improvement is observed over the entire celebration period. Combining these findings and the cultural significance of this activity, we recommend that this custom is actively maintained, using new technologies and scientific governance programs to minimize the negative effects.

SUBMITTER: Zhang X

PROVIDER: S-EPMC7764231 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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The Effects of Fireworks Discharge on Atmospheric PM<sub>2.5</sub> Concentration in the Chinese Lunar New Year.

Zhang Xuechen X Shen Huanfeng H Li Tongwen T Zhang Liangpei L

International journal of environmental research and public health 20201213 24

Discharging fireworks during the Chinese Lunar New Year celebrations is a deep-rooted custom in China. In this paper, we analyze the effect of this cultural activity on PM<sub>2.5</sub> concentration using both ground observations and satellite data. By combining remote sensing data, the problem of uneven spatial distribution of ground monitoring has been compensated, and the research time span has been expanded. The results show that the extensive firework displays on New Year's Eve lead to a r ...[more]

PMID: 33322228

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Project description:The availability of low-cost monitors marketed for use in homes has increased rapidly over the past few years due to the advancement of sensing technologies, increased awareness of urban pollution, and the rise of citizen science. The user-friendly packages can make them appealing for use in research grade indoor exposure assessments, but a rigorous scientific evaluation has not been conducted for many monitors on the open market, which leads to uncertainty about the validity of the data. Furthermore, many previous sensor studies were conducted for a relatively short period of time, which may not capture the changes this type of instrument may exhibit over time (known as sensor aging). We evaluated three monitors (AirVisual Pro, Speck, and AirThinx) in an occupied, non-smoking residence over a 12-month period in order to assess the sensors, the built-in calibrations, and the need for additional data to achieve high accuracy for long deployments. Two units of each type of monitor were evaluated in order to assess the precision between units, and a personal DataRAM (pDR-1200) with a filter was placed in the home for about 20% of the sampling period (e.g., about a week each month) to evaluate the accuracy over time. The average PM2.5 mass concentration from the periods of colocation with the pDR were 5.31 μg/m3 for the gravimetric-corrected pDR (hereafter pDR-corrected), 5.11 and 5.03 μg/m3 for the AirVisual Pro units, 13.58 and 22.68 μg/m3 for the Speck units, and 7.56 and 7.57 μg/m3 for the AirThinx units. The AirVisual Pros exhibited the best accuracy compared to the filter at about 86%, which was slightly better than the nephelometric component of the pDR compared to the filter weight (84%). The accuracies of the Speck (-174 and -405%) and AirThinx (42 and 40%) monitors were much lower. When the 1-minute averaged PM2.5 mass concentrations were categorized by air quality index (AQI), the pDR-corrected matched the AirVisual Pro, Speck, and AirThinx bins about 97, 40, and 87% of the time, respectively. The Pearson correlation coefficients (R2) between the unit pairs and the pDR were 0.90/0.90, 0.50/0.27, and 0.92/0.93 for the AirVisual Pro, Speck, and AirThinx units, respectively. The R2 between units of the same type were 0.99, 0.17, and 1.00 for the AirVisual Pro, Speck, and AirThinx, respectively. All of the monitors could achieve better accuracy by adding filter corrections and post-processing to correct for known biases in addition to the manufacturer's correction routine. Monthly calibrations yielded the highest accuracies, but nearly as high of accuracies could be achieved with only one or two calibrations for the Air Visual Pro and the AirThinx for many applications. In general, this type of new low-cost monitor shows exciting potential for use in scientific research. However, only one of the three monitors exhibited high accuracy (within 20% of the true mass concentration) without any post processing or additional measurements, so an evaluation of each monitor is essential before the data can be used to confidently evaluate residential exposures.

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Dataset Information

The Effects of Fireworks Discharge on Atmospheric PM_2.5 Concentration in the Chinese Lunar New Year.

Publications

The Effects of Fireworks Discharge on Atmospheric PM<sub>2.5</sub> Concentration in the Chinese Lunar New Year.

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The Effects of Fireworks Discharge on Atmospheric PM2.5 Concentration in the Chinese Lunar New Year.

Publications

The Effects of Fireworks Discharge on Atmospheric PM<sub>2.5</sub> Concentration in the Chinese Lunar New Year.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

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The Effects of Fireworks Discharge on Atmospheric PM_2.5 Concentration in the Chinese Lunar New Year.