Review of 'How did "state of emergency" declaration in Japan due to the COVID-19 pandemic affect the acoustic environment in a rather quiet residential area?'

The study investigates the impact of the “state of emergency” declaration due to the COVID-19 pandemic on the acoustic environment of a residential area in Japan. The acoustic community has been mobilized to measure and characterize the impact of the COVID outbreak and consequent confinement situation on noise exposure and on people´s perception (i.e. the soundscape) in several cities around the world [1,2]. Interestingly, this manuscript contributes to this global measurement campaign with some elements of peculiarity. Indeed, i) it focuses on a quiet residential urban area and not on a busy city center and ii) it aims at measuring the effect of Japan´s “state of emergency declaration” that was someway different compared to the “lockdown” policies implemented in many different countries, as explained by the Author. The main suggestions and comments on the manuscript are reported in the following:

• Given the limitations in measurement capabilities due to the “state of emergency” situation, the paper provides a comparison of exposure levels before, during and after the emergency period relying on short measurements of equivalent continuous A-weighted sound pressure levels LAeq (T=30 s) gathered through the NoiseCapture app for Android [3]. The Author reports that a “detailed check of accuracy was not performed” but that the app had been calibrated using a Class 1 SLM before emergency period. If absolute levels might not be accurate, relative levels (before vs. during vs. after the state of emergency period) are useful for the sake of comparison. The data collection methods and the very short duration of recordings (30s) limit the data quality and representativeness and do not allow to align with the recent proposal of harmonization for data reporting by Asensio et al. [2]. This latter aspect would have been important to allow for a comparison and integration of data provided by this study with other gathered from similar initiatives, in future meta-analysis;
• Comparison of noise levels (LAeq (T=30 s)) at the six measurement points (Table 1) or at fixed recording positions (Fig. 2-4) do not show consistent trends. When referring to the exposure values averaged across the six measurement points, a slight increase in noise levels can be observed during and immediately after the emergency phase compared to the period before the pandemic outbreak. This is someway in contrast with what can be expected and, according to the Author, might be related to the increased traffic volume observed and to the construction works that were present in that area. This effect should be better described in the Concluding remarks section, where the Author describes a “1–2 dBA” effect, without clearly specifying the direction of the change. Moreover, the measurement methodology (recording device and length of recordings) limit the general validity of results;
• Besides noise levels, interestingly the Author reports the composition of perceived sound sources. Even if no statistical inference was sought. descriptive statistics suggest no difference during and after the “state of emergency” situation.

Taken together, the study contributes to current research efforts on the characterization of the impact of the COVID-19 scenario on urban soundscape and on the use of smartphones for recording purposes. Clear trends in the noise dose and sound type composition could not be observed by comparing the different time periods (i.e. before, during and after the state of emergency declaration). This might be due to the different impact of “the state of emergency” compared to a “lockdown” situation and/or to differences of the impacts in a residential area compared to city centers. Anyway, due to data collection limitations, no sound conclusion or generalization can be done at this stage, as also stressed by the Author.

References

1. Aletta, F.; Osborn, D. The COVID-19 global challenge and its implications for the environment – what we are learning. UCL Open Environ. 2020, 8–10.

2. Asensio, C.; Aumond, P.; Can, A.; Gasc, L.; Lercher, P.; Wunderli, J.; Lavandier, C.; Arcas, G. De; Ribeiro, C.; Muñoz, P.; et al. A Taxonomy Proposal for the Assessment of the Changes in Soundscape Resulting from the COVID-19 Lockdown. 2020, 1–9.

3. Picaut, J.; Fortin, N.; Bocher, E.; Petit, G.; Aumond, P.; Guillaume, G. An open-science crowdsourcing approach for producing community noise maps using smartphones. Build. Environ. 2019, 148, 20–33.