Indoor-Generated PM2.5 During COVID-19 Shutdowns Across California: Application of the PurpleAir Indoor-Outdoor Low-Cost Sensor Network

The Impact of COVID-19 Health Measures on Adults With Multiple Chemical Sensitivity: Cross-Sectional Study

BACKGROUND

Multiple chemical sensitivity (MCS) develops in response to repeated small-level chemical exposures or a major exposure in a subset of people, who then experience symptoms that can range from mild to debilitating when exposed to chemicals. The arrival of the COVID-19 pandemic and the stringent health measures put in place may have increased the burden for those living with MCS, as it became more challenging to avoid chemicals that trigger their condition.

OBJECTIVE

This study aimed to better understand the lived experience of Canadians living with MCS during the first year of the COVID-19 pandemic.

METHODS

An online questionnaire was created to ask participants to compare daily living during the pandemic to before March 11, 2020. Data were collected in January and February 2021. Three areas were investigated: (1) environmental exposures to chemical triggers from ambient air (pollution from industry, farming, and traffic) and indoor air (the smell of cleaning products, cooking odors, and smoke); (2) access to, and satisfaction with, health care visits; and (3) how people experiencing MCS rated contact with their social network.

RESULTS

In all, 119 Canadians who had lived with MCS for more than a year completed the questionnaire. The participant sample was mostly female (86.6%, n=103) and highly educated, with 57.1% (n=68) having a university degree. Slightly more than half (57.1%, n=68) were older than 55 years. McNemar chi-square and Wilcoxon signed rank tests were used to evaluate if there were statistically significant changes before ("prepandemic period") and after ("postpandemic period") March 11, 2020. Perceived exposure to pollution from a highway or a road was significantly decreased from the prepandemic to postpandemic period (z=-3.347; P<.001). Analysis of industry or power plants also suggested a significant decrease in the perceived exposure from the prepandemic to postpandemic period (z=-2.152; P=.04). Participants reported an increase in exposure to odors from disinfectants or sanitizers that entered their living environment (P<.001). There was a significant decrease between prepandemic and postpandemic levels of satisfaction when attending in-person meetings with a physician (z=-2.048; P=.04), yet there were no significant differences between prepandemic and postpandemic levels of satisfaction for online or telephone meetings with a physician. Although people with MCS experienced increased social isolation (P<.001), they also reported an increase in understanding from family (P=.03) and a decrease in stigma for wearing personal protective equipment (P<.001).

CONCLUSIONS

During the first year of the COVID-19 pandemic, people with MCS were impacted by inaccessibility, loss of social support, and barriers to accessing health care. This study highlights unique challenges and possible benefits associated with the COVID-19 pandemic public health measures for individuals living with MCS. These findings can guide decision makers to improve policies on accessibility through appropriate accommodation measures.

Determining the toxicological effects of indoor air pollution on both a healthy and an inflammatory-comprised model of the alveolar epithelial barrier in vitro

Exposure to indoor air pollutants (IAP) has increased recently, with people spending more time indoors (i.e. homes, offices, schools and transportation). Increased exposures of IAP on a healthy population are poorly understood, and those with allergic respiratory conditions even less so. The objective of this study, therefore, was to implement a well-characterised in vitro model of the human alveolar epithelial barrier (A549 + PMA differentiated THP-1 incubated with and without IL-13, IL-5 and IL-4) to determine the effects of a standardised indoor particulate (NIST 2583) on both a healthy lung model and one modelling a type-II (stimulated with IL-13, IL-5 and IL-4) inflammatory response (such as asthma).Using concentrations from the literature, and an environmentally appropriate exposure we investigated 232, 464 and 608ng/cm2 of NIST 2583 respectively. Membrane integrity (blue dextran), viability (trypan blue), genotoxicity (micronucleus (Mn) assay) and (pro-)/(anti-)inflammatory effects (IL-6, IL-8, IL-33, IL-10) were then assessed 24 h post exposure to both models. Models were exposed using a physiologically relevant aerosolisation method (VitroCell Cloud 12 exposure system).No changes in Mn frequency or membrane integrity in either model were noted when exposed to any of the tested concentrations of NIST 2583. A significant decrease (p < 0.05) in cell viability at the highest concentration was observed in the healthy model. Whilst cell viability in the "inflamed" model was decreased at the lower concentrations (significantly (p < 0.05) after 464ng/cm2). A significant reduction (p < 0.05) in IL-10 and a significant increase in IL-33 was seen after 24 h exposure to NIST 2583 (464, 608ng/cm2) in the "inflamed" model.Collectively, the results indicate the potential for IAP to cause the onset of a type II response as well as exacerbating pre-existing allergic conditions. Furthermore, the data imposes the importance of considering unhealthy individuals when investigating the potential health effects of IAP. It also highlights that even in a healthy population these particles have the potential to induce this type II response and initiate an immune response following exposure to IAP.

Assessing residential PM2.5 concentrations and infiltration factors with high spatiotemporal resolution using crowdsourced sensors

Building conditions, outdoor climate, and human behavior influence residential concentrations of fine particulate matter (PM2.5). To study PM2.5 spatiotemporal variability in residences, we acquired paired indoor and outdoor PM2.5 measurements at 3,977 residences across the United States totaling >10,000 monitor-years of time-resolved data (10-min resolution) from the PurpleAir network. Time-series analysis and statistical modeling apportioned residential PM2.5 concentrations to outdoor sources (median residential contribution = 52% of total, coefficient of variation = 69%), episodic indoor emission events such as cooking (28%, CV = 210%) and persistent indoor sources (20%, CV = 112%). Residences in the temperate marine climate zone experienced higher infiltration factors, consistent with expectations for more time with open windows in milder climates. Likewise, for all climate zones, infiltration factors were highest in summer and lowest in winter, decreasing by approximately half in most climate zones. Large outdoor-indoor temperature differences were associated with lower infiltration factors, suggesting particle losses from active filtration occurred during heating and cooling. Absolute contributions from both outdoor and indoor sources increased during wildfire events. Infiltration factors decreased during periods of high outdoor PM2.5, such as during wildfires, reducing potential exposures from outdoor-origin particles but increasing potential exposures to indoor-origin particles. Time-of-day analysis reveals that episodic emission events are most frequent during mealtimes as well as on holidays (Thanksgiving and Christmas), indicating that cooking-related activities are a strong episodic emission source of indoor PM2.5 in monitored residences.

Estimating the mortality attributable to indoor exposure to particulate matter of outdoor origin in mainland China

Previous estimations on the premature deaths attributable to indoor ambient particulate matter (PM) with aerodynamic diameter < 2.5 μm (PM_2.5) of outdoor origin only considered the indoor PM_2.5 concentration, which always neglected the impact from the distribution of particle size and the PM deposition in human airways. To tackle this issue, we first calculated the premature deaths due to PM_2.5 was approximately 1,163,864 persons in mainland China in 2018 by using the global disease burden approach. Then, we specified the infiltration factor of PM with aerodynamic diameter < 1 μm (PM₁) and PM_2.5 to estimate the indoor PM pollution. Results showed that average concentrations of indoor PM₁ and PM_2.5 of outdoor origin were 14.1 ± 3.9 μg/m³ and 17.4 ± 5.4 μg/m³, respectively. The indoor PM₁/PM_2.5 ratio of outdoor origin was estimated to be 0.83 ± 0.18, which was 36 % higher than the ambient PM₁/PM_2.5 ratio (0.61 ± 0.13). Furthermore, we calculated the premature deaths from the indoor exposure of outdoor origin was approximately 734,696, accounting for approximately 63.1 % of total deaths. Our results are 12 % higher than previous estimations neglecting the impact from the distribution disparities of PM between indoor and outdoor. Regarding the cause-specific diseases, indoor PM_2.5 exposure of outdoor origin accounted for 293,379 deaths to ischemic heart disease, followed by 158,238 deaths to chronic obstructive pulmonary disease, 134,390 deaths to stroke, 84,346 cases to lung cancer, 52,628 deaths to lower respiratory tract infection, and 11,715 deaths to type 2 diabetes. In addition, we for the first time estimated the indoor PM₁ of outdoor origin has led to approximately 537,717 premature deaths in mainland China. Our results have well demonstrated the health impact may be approximately 10 % higher when considering the effects from infiltration and respiratory tract uptake and physical activity levels, comparing to the treatment that only used outdoor PM concentration.

Efficacy of Low-Cost Sensor Networks at Detecting Fine-Scale Variations in Particulate Matter in Urban Environments

The negative health impacts of air pollution are well documented. Not as well-documented, however, is how particulate matter varies at the hyper-local scale, and the role that proximal sources play in influencing neighborhood-scale patterns. We examined PM_2.5 variations in one airshed within Indianapolis (Indianapolis, IN, USA) by utilizing data from 25 active PurpleAir (PA) sensors involving citizen scientists who hosted all but one unit (the control), as well as one EPA monitor. PA sensors report live measurements of PM_2.5 on a crowd sourced map. After calibrating the data utilizing relative humidity and testing it against a mobile air-quality unit and an EPA monitor, we analyzed PM_2.5 with meteorological data, tree canopy coverage, land use, and various census variables. Greater proximal tree canopy coverage was related to lower PM_2.5 concentrations, which translates to greater health benefits. A 1% increase in tree canopy at the census tract level, a boundary delineated by the US Census Bureau, results in a ~0.12 µg/m³ decrease in PM_2.5, and a 1% increase in "heavy industry" results in a 0.07 µg/m³ increase in PM_2.5 concentrations. Although the overall results from these 25 sites are within the annual ranges established by the EPA, they reveal substantial variations that reinforce the value of hyper-local sensing technologies as a powerful surveillance tool.

Chemical explosion, COVID-19, and environmental justice: Insights from low-cost air quality sensors

OBJECTIVES

To examine the impact of the Intercontinental Terminals Company (ITC) fire and COVID-19 on airborne particulate matter (PM) concentrations and the PM disproportionally affecting communities in Houston using low-cost sensors.

METHODS

We compared measurements from a network of low-cost sensors with a separate network of monitors from the Environmental Protection Agency (EPA) in the Houston metropolitan area from Mar 18, 2019, to Dec 31, 2020. Further, we examined the associations between neighborhood-level sociodemographic status and air pollution patterns by linking the low-cost sensor data to EPA environmental justice screening and mapping systems.

FINDINGS

We found increased PM levels during ITC fire and pre-COVID-19, and lower PM levels after the COVID-19 lockdown, comparable to observations from the regulatory monitors, with higher variations and a greater number of locations with high PM levels detected. In addition, the environmental justice analysis showed positive associations between higher PM levels and the percentage of minority, low-income population, and demographic index.

IMPLICATION

Our study indicates that low-cost sensors provide pollutant measures with higher spatial variations and a better ability to identify hot spots and high peak concentrations. These advantages provide critical information for disaster response and environmental justice studies.

SYNOPSIS

We used measurements from a low-cost sensor network for air pollution monitoring and environmental justice analysis to examine the impact of anthropogenic and natural disasters.

Compound Risk of Air Pollution and Heat Days and the Influence of Wildfire by SES across California, 2018-2020: Implications for Environmental Justice in the Context of Climate Change

Major wildfires and heatwaves have begun to increase in frequency throughout much of the United States, particularly in western states such as California, causing increased risk to public health. Air pollution is exacerbated by both wildfires and warmer temperatures, thus adding to such risk. With climate change and the continued increase in global average temperatures, the frequency of major wildfires, heat days, and unhealthy air pollution episodes is projected to increase, resulting in the potential for compounding risks. Risks will likely vary by region and may disproportionately impact low-income communities and communities of color. In this study, we processed daily particulate matter (PM) data from over 18,000 low-cost PurpleAir sensors, along with gridMET daily maximum temperature data and government-compiled wildfire perimeter data from 2018-2020 in order to examine the occurrence of compound risk (CR) days (characterized by high temperature and high PM2.5) at the census tract level in California, and to understand how such days have been impacted by the occurrence of wildfires. Using American Community Survey data, we also examined the extent to which CR days were correlated with household income, race/ethnicity, education, and other socioeconomic factors at the census tract level. Results showed census tracts with a higher frequency of CR days to have statistically higher rates of poverty and unemployment, along with high proportions of child residents and households without computers. The frequency of CR days and elevated daily PM2.5 concentrations appeared to be strongly related to the occurrence of nearby wildfires, with over 20% of days with sensor-measured average PM2.5 > 35 μg/m3 showing a wildfire within a 100 km radius and over two-thirds of estimated CR days falling on such days with a nearby wildfire. Findings from this study are important to policymakers and government agencies who preside over the allocation of state resources as well as organizations seeking to empower residents and establish climate resilient communities.

Characterization of the vertical variation in indoor PM2.5 in an urban apartment in China

Indoor air pollution has aroused increasing concerns due to its significant adverse health impacts. Indoor PM_2.5 exposure assessments often rely on PM_2.5 concentration measured at a single height, which overlooks the vertical variation of PM_2.5 concentrations accompanied by various indoor activities. In this study, we characterize the vertical profile of PM_2.5 concentration by monitoring PM_2.5 concentration at eight different heights in the kitchen and the bedroom, respectively, using low-cost sensors with high temporal resolution. The localized enhancement of PM_2.5 concentration in elevated heights in the kitchen during cooking was observed on clean and polluted days, showing dominating contribution from cooking activities. The source contribution from cooking and outdoor penetration was semi-quantified using regression models. Stratified source contribution from cooking activities was evident in the kitchen during the cooking period. The contribution in elevated heights (above 170 cm) almost tripled the contrition in bottom layers (below 140 cm). In contrast, little vertical variation was observed during other times of the day in the kitchen or the bedroom. The exposure level calculated using the multi-height measurement in this study is consistently higher than the exposure level estimated from the single-height (at 110 cm) measurement. A more significant discrepancy existed for the cookers (17.8%) than the non-cookers (13.5%). By profiling the vertical gradient of PM_2.5 concentration, we show the necessity to conduct multi-height measurements or proper breathing-height measurements to obtain unbiased concentration information for source apportionment and exposure assessment. In particular, the multi-height measuring scheme will be crucial to inform household cooking emission regulations.

Field measurements of indoor and community air quality in rural Beijing before, during, and after the COVID-19 lockdown

The coronavirus (COVID-19) lockdown in China is thought to have reduced air pollution emissions due to reduced human mobility and economic activities. Few studies have assessed the impacts of COVID-19 on community and indoor air quality in environments with diverse socioeconomic and household energy use patterns. The main goal of this study was to evaluate whether indoor and community air pollution differed before, during, and after the COVID-19 lockdown in homes with different energy use patterns. Using calibrated real-time PM_2.5 sensors, we measured indoor and community air quality in 147 homes from 30 villages in Beijing over 4 months including periods before, during, and after the COVID-19 lockdown. Community pollution was higher during the lockdown (61 ± 47 μg/m³ ) compared with before (45 ± 35 μg/m³ , p < 0.001) and after (47 ± 37 μg/m³ , p < 0.001) the lockdown. However, we did not observe significantly increased indoor PM_2.5 during the COVID-19 lockdown. Indoor-generated PM_2.5 in homes using clean energy for heating without smokers was the lowest compared with those using solid fuel with/without smokers, implying air pollutant emissions are reduced in homes using clean energy. Indoor air quality may not have been impacted by the COVID-19 lockdown in rural settings in China and appeared to be more impacted by the household energy choice and indoor smoking than the COVID-19 lockdown. As clean energy transitions occurred in rural households in northern China, our work highlights the importance of understanding multiple possible indoor sources to interpret the impacts of interventions, intended or otherwise.

Public face masks wearing during the COVID-19 pandemic: A comprehensive analysis is needed for potential implications

Face mask-wearing as a public health measure has been practiced since the coronavirus 2019 (COVID-19) pandemic outbreak. Extensive research has shown that face masks are an effective non-pharmaceutical measure to contain the spread of respiratory infections. However, recent studies indicate that face masks release microplastics and other contaminants that have adverse health effects on humans. This communication reviews the evidence for face mask as a potential source of contaminants capable of adversely affecting human health. The benefits of face masks in reducing the transmission of SARS-Cov-2 (severe acute respiratory syndrome coronavirus 2) and seasonal communicable diseases were addressed. In addition, the risk of inhaling microplastics and organic contaminants, as well as the associated exposure level, were discussed. Finally, the potential research gaps that need to be addressed were outlined to provide a holistic view of the problem. This communication has illustrated that face mask-wearing as a public health measure to contain the spread of COVID-19 could be a potential risk factor for human health. Very few studies have been done on microplastics, organic pollutants, and trace metal inhalation from surgical masks. However, future work providing a comprehensive understanding of the risk and exposure levels needs to be undertaken.

Measuring secondhand smoke in homes in Malaysia: A feasibility study comparing indoor fine particulate (PM_2.5) concentrations following an educational feedback intervention to create smoke-free homes during the COVID-19 pandemic

INTRODUCTION

Extensive regulations have been introduced to reduce secondhand smoke (SHS) exposure among non-smokers in Malaysia. However, there is still a need to encourage behavior change of smokers in relation to making homes smoke-free. This feasibility study aimed to use low-cost air pollution monitors to quantify SHS concentrations in Malaysian households and to explore the practicality of using personalized feedback in educating families to make their homes smoke-free.

METHODS

A total of 35 smokers in three states in Malaysia were recruited via snowball and convenience sampling methods. Indoor fine particulate (PM_2.5) concentrations in participants’ homes were measured for 7 days before and after educational intervention using a pre-defined template, which included personalized air-quality feedback, and information on SHS impacts were given. The feedback was delivered over two 20-minute phone calls or in-person sessions following the completion of the air-quality measurements. Data were corrected for outdoor PM_2.5 concentrations from the nearest environmental monitor.

RESULTS

Despite the challenges in conducting the project during COVID-19 pandemic, the delivery of the intervention was found to be feasible. Twenty-seven (77%) out of 35 participants completed PM_2.5 measurements and received a complete intervention. The median (IQR: 25th –75th percentile concentrations) SHS-PM_2.5 concentrations at baseline and follow-up were 18.3 µg/m³ (IQR: 13.3–28.3) and 16.2 µg/m³ (IQR: 10.4 – 25.6), respectively. There was a reduction of SHS-PM_2.5 concentrations at follow-up measurement in the houses of 17 participants (63%). The change in corrected indoor PM_2.5 concentrations between baseline and follow-up was not statistically significant (Z= -1.01, p=0.29).

CONCLUSIONS

This educational intervention, combining the use of a low-cost air particle counter with personalized air-quality feedback, was found to be feasible in the Malaysian setting. It has potential to trigger behavior change among smokers, reducing indoor smoking and consequent SHS concentrations, and increasing smoke-free home implementation. A large-scale trial is needed.

The effect of COVID-19 restrictions on particulate matter on different modes of transport in China

Since the COVID-19 pandemic, ventilation on transport has been improved to control the aerosol transmission. We utilized portable monitors to measure real-time concentrations of PM₁₀, PM_2.5, PM_1.0 and black carbon (BC) on six modes of transport and estimate personal exposures under the epidemic prevention. The mean concentrations of PM₁₀, PM_2.5, PM_1.0 and BC measured on transport were 18.8 ± 19.4, 16.6 ± 16.5, 12.2 ± 10.8 and 4.1 ± 6.9 μg/m³, respectively. It reduced PM levels on subway to apply the full fresh air mode rather than partial recirculation mode. Airplane had the lowest concentrations and the highest decay rates, implying the most efficient ventilation and filtration. PM were higher on intra-city transport than inter-city, and significantly increased on arrival at stations. BC and BC/PM ratios were higher on road transport than rail transport, indicating the contribution of exhaust emissions. The ventilation mode to exchange air with the outside and the positive association between concentrations and decay rates on high-speed train suggested filtration efficiency should be improved simultaneously with enhancing ventilation. Wearing facemasks on transport further protects passengers against PM exposure, which reduced personal exposure concentrations on four modes of transport lower than 10 μg/m³, the World Health Organization guideline.

Environmental Factors Influencing COVID-19 Incidence and Severity

Emerging evidence supports a link between environmental factors-including air pollution and chemical exposures, climate, and the built environment-and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission and coronavirus disease 2019 (COVID-19) susceptibility and severity. Climate, air pollution, and the built environment have long been recognized to influence viral respiratory infections, and studies have established similar associations with COVID-19 outcomes. More limited evidence links chemical exposures to COVID-19. Environmental factors were found to influence COVID-19 through four major interlinking mechanisms: increased risk of preexisting conditions associated with disease severity; immune system impairment; viral survival and transport; and behaviors that increase viral exposure. Both data and methodologic issues complicate the investigation of these relationships, including reliance on coarse COVID-19 surveillance data; gaps in mechanistic studies; and the predominance of ecological designs. We evaluate the strength of evidence for environment-COVID-19 relationships and discuss environmental actions that might simultaneously address the COVID-19 pandemic, environmental determinants of health, and health disparities.

Promoting risk reduction among young adults with asthma during wildfire smoke: A feasibility study

OBJECTIVE(S)

This study explored the feasibility, acceptability, preliminary impact, and functionality of two risk reduction mobile application (app) interventions on asthma outcomes as compared to a control arm during wildfire season.

DESIGN

Three-arm, 8-week randomized clinical trial.

SAMPLE

Sixty-seven young adults with asthma were enrolled.

MEASUREMENTS

The Asthma Control Test, forced expiratory volume in one second (FEV₁ ) and the System Usability Scale were measured at baseline, 4, and 8 weeks. The Research Attitude Scale was administered at 8 weeks. Twenty participants from the two intervention arms completed an optional survey and six were interviewed after completing the study.

INTERVENTION

Both intervention arms could access Smoke Sense Urbanova, an app that supports reducing risks from breathing wildfire smoke. The Smoke Sense Urbanova Plus arm also monitored their daily FEV₁ , received air quality notifications, and accessed preventive tips and a message board.

RESULTS

Most participants agreed the app and spirometer were usable and their privacy and confidentiality were maintained. No adverse events were reported.

CONCLUSIONS

Participant-identified recommendations will support intervention refinement and testing. This research supports asthma self-management tools that public health nurses and community health workers can recommend for at-risk populations.

Substantial health benefits of strengthening guidelines on indoor fine particulate matter in China

In 2020, China for the first time developed guidelines for indoor fine particulate matter (PM_2.5) in the draft document of indoor air standards, while the associated health implication remains unclear. Here, we first estimated the PM_2.5 associated premature deaths was 965 thousand in 2019, with the indoor PM_2.5 of outdoor origin accounting for 72.9%. Then, we examined the dynamic mortalities under a scenario matrix of 36 conditions, by incorporating various shared socioeconomic pathways in 2035, the draft guidelines and the contributions of ambient PM_2.5 to indoor exposure. Although it may be improbable, the averages of premature deaths associated with ambient PM_2.5 will be 1018-1361 thousand in 2035 when the worst-case scenario of guidelines mandating a yearly (rather than daily) indoor PM_2.5 concentration of 75 µg/m³, compared to the averages of estimation were 816-1304 thousand for better-case scenario of 35 µg/m³. Under these scenarios, the increase in the number of premature deaths was mainly driven by population aging. In 2035, an ambitious target of yearly indoor PM_2.5 concentrations of 15 µg/m³ is anticipated to reduce the number of deaths associated with ambient PM_2.5 by approximately 25% of the 2019 baseline. Stricter guidelines to restrict the indoor PM_2.5 concentrations are recommended to mitigate the mortality risk in the future.

Contributions of internal emissions to peaks and incremental indoor PM2.5 in rural coal use households

Indoor air quality is critically important to the human as people spend most time indoors. Indoor PM_2.5 is related to the outdoor levels, but more directly influenced by internal sources. Severe household air pollution from solid fuel use has been recognized as one major risk for human health especailly in rural area, however, the issue is significantly overlooked in most national air quality controls and intervention policies. Here, by using low-cost sensors, indoor PM_2.5 in rural homes burning coals was monitored for ~4 months and analyzed for its temporal dynamics, distributions, relationship with outdoor PM_2.5, and quantitative contributions of internal sources. A bimodal distribution of indoor PM_2.5 was identified and the bimodal characteristic was more significant at the finer time resolution. The bimodal distribution maxima were corresponding to the emissions from strong internal sources and the influence of outdoor PM_2.5, respectively. Indoor PM_2.5 was found to be correlated with the outdoor PM_2.5, even though indoor coal combustion for heating was thought to be predominant source of indoor PM_2.5. The indoor-outdoor relationship differed significantly between the heating and non-heating seasons. Impacts of typical indoor sources like cooking, heating associated with coal use, and smoking were quantitatively analyzed based on the highly time-resolved PM_2.5. Estimated contribution of outdoor PM_2.5 to the indoor PM_2.5 was ~48% during the non-heating period, but decreased to about 32% during the heating period. The contribution of indoor heating burning coals comprised up to 47% of the indoor PM_2.5 during the heating period, while the other indoor sources contributed to ~20%. The study, based on a relatively long-term timely resolved PM_2.5 data from a large number of rural households, provided informative results on temporal dynamics of indoor PM_2.5 and quantitative contributions of internal sources, promoting scientific understanding on sources and impacts of household air pollution.

The Interplay between Housing Environmental Attributes and Design Exposures and Psychoneuroimmunology Profile-An Exploratory Review and Analysis Paper in the Cancer Survivors' Mental Health Morbidity Context

Adult cancer survivors have an increased prevalence of mental health comorbidities and other adverse late-effects interdependent with mental illness outcomes compared with the general population. Coronavirus Disease 2019 (COVID-19) heralds an era of renewed call for actions to identify sustainable modalities to facilitate the constructs of cancer survivorship care and health care delivery through physiological supportive domestic spaces. Building on the concept of therapeutic architecture, psychoneuroimmunology (PNI) indicators-with the central role in low-grade systemic inflammation-are associated with major psychiatric disorders and late effects of post-cancer treatment. Immune disturbances might mediate the effects of environmental determinants on behaviour and mental disorders. Whilst attention is paid to the non-objective measurements for examining the home environmental domains and mental health outcomes, little is gathered about the multidimensional effects on physiological responses. This exploratory review presents a first analysis of how addressing the PNI outcomes serves as a catalyst for therapeutic housing research. We argue the crucial component of housing in supporting the sustainable primary care and public health-based cancer survivorship care model, particularly in the psychopathology context. Ultimately, we illustrate a series of interventions aiming at how housing environmental attributes can trigger PNI profile changes and discuss the potential implications in the non-pharmacological treatment of cancer survivors and patients with mental morbidities.

Beyond air pollution at home: Assessment of personal exposure to PM2.5 using activity-based travel demand model and low-cost air sensor network data

Assessing personal exposure to air pollution is challenging due to the limited availability of human movement data and the complexity of modeling air pollution at high spatiotemporal resolution. Most health studies rely on residential estimates of outdoor air pollution instead which introduces exposure measurement error. Personal exposure for 100,784 individuals in Los Angeles County was estimated by integrating human movement data simulated from the Southern California Association of Governments (SCAG) activity-based travel demand model with hourly PM_2.5 predictions from my 500 m gridded model incorporating low-cost sensor monitoring data. Individual exposures were assigned considering PM_2.5 levels at homes, workplaces, and other activity locations. These dynamic exposures were compared to the residence-based exposures, which do not consider human movement, to examine the degree of exposure estimation bias. The results suggest that exposures were underestimated by 13% (range 5-22%) on average when human movement was not considered, and much of the error was eliminated by accounting for work location. Exposure estimation bias increased for people who exhibited higher mobility levels, especially for workers with long commute distances. Overall, the personal exposures of workers were underestimated by 22% (5-61%) relative to their residence-based exposures. For workers who commute >20 miles, their exposure levels can be at most underestimated by 61%. Omitting mobility resulted in underestimating exposures for people who reside in areas with cleaner air but work in more polluted areas. Similarly, exposures were overestimated for people living in areas with poorer air quality and working in cleaner areas. These could lead to differential estimation biases across racial, ethnic and socioeconomic lines that typically correlate with where people live and work and lead to important exposure and health disparities. This study demonstrates that ignoring human movement and spatiotemporal variability of air pollution could lead to differential exposure misclassification potentially biasing health risk assessments. These improved dynamic approaches can help planners and policymakers identify disadvantaged populations for which exposures are typically misrepresented and might lead to targeted policy and planning implications.