Residential cooking-related PM2.5: Spatial-temporal variations under various intervention scenarios

Xiang, Jianbang; Hao, Jiayuan; Austin, Elena; Shirai, Jeffry H.; Seto, Edmund

doi:10.1016/j.buildenv.2021.108002

Cited by 20 publications

(3 citation statements)

References 38 publications

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“…Exposure to high levels of PM could lead to respiratory health problems and increase the susceptibility of exposed populations to respiratory diseases like COVID-19, such as asthma, chronic obstructive pulmonary disease, pneumonia, and lung cancer (Shi et al 2021;Chen et al 2021;Wang et al 2021b;Bera et al 2021;Yu et al 2021). Due to more activities in the home during a lockdown, small particles generated in the kitchen can be a potential source of pollution (Wimalasena et al 2021;Zhang et al 2021a, b;Xiang et al 2021;Du et al 2021;Huang et al 2021).…”

Section: Indoor Air Qualitymentioning

confidence: 99%

COVID-19, a double-edged sword for the environment: a review on the impacts of COVID-19 on the environment

Atoufi

Lampert

2021

Environ Sci Pollut Res

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This review paper discusses the most relevant impacts of the COVID-19 pandemic on the environment. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) originated in Wuhan, China, in December 2019. The disease has infected 70 million people and caused the death of 1.58 million people since the US Food and Drug Administration issued an Emergency Use Authorization to develop a vaccine to prevent COVID-19 on December 11, 2020. COVID-19 is a global crisis that has impacted everything directly connected with human beings, including the environment. This review discusses the impacts of COVID-19 on the environment during the pandemic and post-COVID-19 era. During the first months of the COVID pandemic, global coal, oil, gas, and electricity demands declined by 8%, 5%, 2%, and 20%, respectively, relative to 2019. Stay-at-home orders in countries increased the concentrations of particles in indoor environments while decreasing the concentrations of PM 2.5 and NO X in outdoor environments. Remotely working in response to the COVID-19 pandemic increased the carbon, water, and land footprints of Internet usage. Microplastics are released into our environment from the mishandling and mismanagement of personal protective equipment that endanger our water, soils, and sediments. Since the COVID-19 vaccine cannot be stored for a long time and spoils rapidly, more awareness of the massive waste of unused doses is needed. So COVID-19 is a doubleedged sword for the environment.

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Section: Indoor Air Qualitymentioning

confidence: 99%

COVID-19, a double-edged sword for the environment: a review on the impacts of COVID-19 on the environment

Atoufi

Lampert

2021

Environ Sci Pollut Res

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“…Previous studies have indicated that cooking activities have a considerable impact on IAQ [12][13][14][15][16][17][18][19]. Common indoor activities, such as cooking, release PM (e.g., PM 2.5 and PM 10 ) [20,21], along with various types of indoor air pollutants, including volatile organic compounds (VOCs) and semi-VOCs. The increase in indoor air pollutants can have adverse effects on occupants' cardiorespiratory systems [22,23], lung function [24][25][26][27], cardiovascular health [28,29], human brain activity [30], and cognitive performance [31].…”

Section: Introductionmentioning

confidence: 99%

Examining Recognition of Occupants’ Cooking Activity Based on Sound Data Using Deep Learning Models

Kim,

Choi,

Park

et al. 2024

Buildings

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In today’s society, where people spend over 90% of their time indoors, indoor air quality (IAQ) is crucial for sustaining human life. However, as various indoor activities such as cooking generate diverse types of pollutants in indoor spaces, IAQ has emerged as a serious issue. Previous studies have employed methods such as CO2 sensors, smart floor systems, and video-based pattern recognition to distinguish occupants’ activities; however, each method has its limitations. This study delves into the classification of occupants’ cooking activities using sound recognition technology. Four deep learning-based sound recognition models capable of recognizing and classifying sounds generated during cooking were presented and analyzed. Experiments were carried out using sound data collected from real kitchen environments and online data-sharing websites. Additionally, changes in performance according to the amount of collected data were observed. Among the developed models, the most efficient is found to be the convolutional neural network, which is relatively unaffected by fluctuations in the amount of sound data and consistently delivers excellent performance. In contrast, other models exhibited a tendency for reduced performance as the amount of sound data decreased. Consequently, the results of this study offer insights into the classification of cooking activities based on sound data and underscore the research potential for sound-based occupant behavior recognition classification models.

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“…During high PM2.5 episodes, air ventilation also effectively reduces indoor PM2.5 levels by diluting with fresh outdoor air. 20,21 Further, baseline indoor PM2.5 levels are highly influenced by the penetration of ambient PM2.5 into the indoor environment. Although indoor air quality can be improved with proper air exchange and filtration systems, numerous studies have shown a strong relationship between indoor and ambient PM2.5 levels.…”

Section: Introductionmentioning

confidence: 99%

Indoor and Ambient Influences on PM2.5 Exposure and Well-being for a Rail Impacted Community and Implications for Personal Protections

Torres,

Do,

Delgado

et al. 2023

Preprint

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Background. Higher air pollution emissions can be observed near rail networks, local and highway automobile corridors, and shipyards. Communities near such sources are often disproportionately exposed to emissions from these stationary and mobile sources. One such community is West San Bernardino in California, where households are feet away from the Burlington Northern Santa Fe intermodal facility and are impacted by activities that are estimated to continuously emit air pollutants due to 24/7 operation.Objective. This study aimed to (1) quantify the impact of personal mobility and housing characteristics on daily PM2.5 exposures and well-being for West San Bernardino community members, and (2) develop individualized resilience plans for community collaborators to support future PM2.5 exposure reduction. Methods.Personal PM2.5 exposures were measured for each community collaborator for seven consecutive days during three deployment periods: October 2021, January 2022, and March 2022. Indoor and ambient PM2.5 levels were also continuously measured for five households over six months using PurpleAir Classic monitors. Demographic and well-being data were collected upon recruitment and after each week of engagement, respectively. Results.Personal exposures in home microenvironments were highest near the railyard and decreased with distance from the railyard. Home exposures were 40% higher on average compared to non-home microenvironments. Household PM2.5 levels had a higher-than-expected average infiltration factor of 0.70, and indoor 98th percentiles across the households far exceeded a healthy level at an average of 61 μg/m3. Increasing median personal exposures were linearly correlated with worsening health conditions.Significance.Results suggest that surrounding land use, household building characteristics, and indoor activity all compound to worsen air pollution exposures beyond what is expected for exposures in non-industrialized areas. Findings prompt a call for stronger regulation, not only for emissions, but also for indoor air quality and zoning standards that specifically protect disproportionately impacted communities.

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Residential cooking-related PM2.5: Spatial-temporal variations under various intervention scenarios

Cited by 20 publications

References 38 publications

COVID-19, a double-edged sword for the environment: a review on the impacts of COVID-19 on the environment

COVID-19, a double-edged sword for the environment: a review on the impacts of COVID-19 on the environment

Examining Recognition of Occupants’ Cooking Activity Based on Sound Data Using Deep Learning Models

Indoor and Ambient Influences on PM2.5 Exposure and Well-being for a Rail Impacted Community and Implications for Personal Protections

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