# Did Noise Pollution Really Improve during COVID-19? Evidence from Taiwan

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## Abstract

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## 1. Introduction

## 2. Materials and Methods

#### 2.1. Busy Areas of Taiwan and Sources of Noise Pollution

#### 2.2. Bayesian Regression MCMC

#### 2.3. Dataset

## 3. Results

#### 3.1. The Construction Steps of Bayesian MCMC

#### 3.2. Evidence of Noise Pollution Reduction

#### 3.3. Measuring Noise Pollution Using Bayesian MCMC

^{2}84.70%. If we look in more detail at Table 2, the prior setting for EB-local and EB-global has the same value. The objectives of the two priors are to find the global empirical Bayes estimates of g in Zellner’s g-prior and model probabilities [50].

## 4. Conclusions

^{2}84.70%. The Environmental Protection Administration (EPA), Executive Yuan, Taiwan declared on 21 January 2010 the Environmental Sound Level Standard to preserve adequate noise levels. In compliance with Article 20(3) of the Noise Control Act, the EPA has proposed the Environmental Noise Measurement Methods. At the moment, large-scale noise management activities, including local councils, event promoters and local suppliers, are expected to take responsibility for noise reduction and regulation prior to and after activities to maintain a safe atmosphere. Preventive steps include the elimination of noise at the sound source, the modification of the sound propagation route and the preservation of levels of the reception of noise. Any individual in violation of noise reduction requirements will be liable to a fine of NTD 3000–30,000. Several city councils also advised activity planners and local suppliers that they would cooperate with the regulations. City municipalities have already adopted these guidelines into their autonomous rules on the protection of large-scale activities. In a nutshell, as in Taiwan’s pre-COVID-19 pandemic strategy, the Taiwan CDC, in coordination with the Central Epidemic Command Center (CECC), held the responsibility of controlling the pandemic. Taiwanese officials were alerted to the outbreak in China by established action networks, triggering an urgent response, including screening of all airline passengers. We do not know when COVID-19 will end, but between the dynamics that occur, we see a positive impact, especially concerning reducing noise pollution. COVID-19 has had a positive impact on the environment, and this paper has proven that reductions in the amount of noise pollution in Taiwan were related to the number of petition cases. Future research should examine types of emissions and GHG reduction.

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Conflicts of Interest

## Nomenclature

CNS | Chinese National Standard |

COVID-19 | Coronavirus disease |

DNL | day–night level |

EPA | Environmental Protection Administration |

EU | European Union |

Fisher Test | statistical significance test |

IEC | International Electrotechnical Commission |

LOGMARG | values of the log of the marginal likelihood for the models |

MCMC | Markov chain Monte Carlo |

POSTROBS | posterior of Bayesian |

Wilcoxon Test | non-parametric statistical hypothesis test used to compare two related samples |

## Appendix A. Posterior Computation

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**Figure 1.**Chord diagram noise pollution in Taiwan 2005–2019 (before COVID-19) and 2020 (during COVID-19).

Descriptive | Cases of Over-Standard Noise per Time Frame | Petition Cases | Industry Petitions | Motorcycles | Cars | Density of Vehicles | |
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Before COVID-19 | Min. | 2 | 39,636 | 25,445 | 13,195,265 | 6,667,542 | 549 |

1st | 3 | 58,722 | 29,201 | 13,719,027 | 6,769,454 | 587 | |

Median | 4 | 81,368 | 32,034 | 13,968,198 | 7,287,146 | 595 | |

Mean | 6 | 72,394 | 31,628 | 14,110,811 | 7,351,197 | 593 | |

3rd | 9 | 87,076 | 33,998 | 14,425,164 | 7,869,013 | 606 | |

Max. | 14 | 96,739 | 40,174 | 15,173,602 | 8,193,237 | 617 | |

During COVID-19 | Min. | 6 | 85,457 | 31,142 | 13,992,922 | 8,118,885 | 611 |

1st | 6 | 87,926 | 33,400 | 14,020,632 | 8,137,473 | 612 | |

Median | 7 | 90,394 | 35,658 | 14,048,343 | 8,156,061 | 613 | |

Mean | 7 | 90,394 | 35,658 | 14,048,343 | 8,156,061 | 613 | |

3rd | 7 | 92,863 | 37,916 | 14,076,053 | 8,174,649 | 615 | |

Max. | 8 | 95,331 | 40,174 | 14,103,763 | 8,193,237 | 616 | |

Statistical Test | p-value Wilcoxon test (before and during COVID19) | 0.58680 | 0.00002 | 0.66670 | 0.50000 | 0.50000 | 0.66700 |

Fisher’s test (before and during COVID-19) | 0.43750 | 0.02564 | 0.00020 | 0.00050 | 0.00051 | 0.00050 |

Prior | R^{2} | Dim | LOGMARG | POSTROBS |
---|---|---|---|---|

AIC * | 84.70% | 6 | 2.845605 | 0.0644 |

g-prior | 30.7% | 2 | 1.131336 | 0.0785 |

ZS-null | 30.7% | 2 | 0.062679 | 0.0449 |

ZS-full | 48.2% | 4 | 3.190674 | 0.0316 |

Hyper-g | 64.6% | 6 | 0.820071 | 0.0304 |

Hyper-g-n | 30.7% | 2 | 0.613492 | 0.0414 |

Hyper-g-Laplace | 40.86% | 3 | 0.7213114 | 0.0465 |

Hyper-g-n | 30.7% | 2 | 0.6134929 | 0.0307 |

EB-local | 64.70% | 6 | 1.520647 | 0.0267 |

EB-global | 64.70% | 6 | 1.377268 | 0.0200 |

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## Share and Cite

**MDPI and ACS Style**

Caraka, R.E.; Yusra, Y.; Toharudin, T.; Chen, R.-C.; Basyuni, M.; Juned, V.; Gio, P.U.; Pardamean, B.
Did Noise Pollution Really Improve during COVID-19? Evidence from Taiwan. *Sustainability* **2021**, *13*, 5946.
https://doi.org/10.3390/su13115946

**AMA Style**

Caraka RE, Yusra Y, Toharudin T, Chen R-C, Basyuni M, Juned V, Gio PU, Pardamean B.
Did Noise Pollution Really Improve during COVID-19? Evidence from Taiwan. *Sustainability*. 2021; 13(11):5946.
https://doi.org/10.3390/su13115946

**Chicago/Turabian Style**

Caraka, Rezzy Eko, Yusra Yusra, Toni Toharudin, Rung-Ching Chen, Mohammad Basyuni, Vilzati Juned, Prana Ugiana Gio, and Bens Pardamean.
2021. "Did Noise Pollution Really Improve during COVID-19? Evidence from Taiwan" *Sustainability* 13, no. 11: 5946.
https://doi.org/10.3390/su13115946