Estimating climate change-related impacts on outdoor air pollution infiltration

Exploring relationships between smoke exposure, housing characteristics, and preterm birth in California

Pregnant people are vulnerable to air pollution exposure, including risk of preterm birth, low birth weight, and stillbirth. Understanding the infiltration of outdoor wildfire into a residential space is critical for the accurate assessment of wildfire smoke exposure and associated health effects in pregnant people. Relying on ambient measurements of wildfire smoke alone can result in exposure misclassification. In this study, we examine the role of physical housing characteristics in the relationship between smoke exposure and preterm birth. In particular, we examine the effect of home size, year of construction, cooling type, and renovation status, as effect modifiers in the relationship between smoke exposure during pregnancy and preterm birth from 2007-2015 in California. To do this, we combined data on home characteristics from the California Tax Assessor, birth outcomes from the California birth records database, and the number of smoke days for each pregnancy from NOAA's Administration's Hazard Mapping System (HMS). We estimated the association between smoke day exposures and odds of preterm birth using logistic regression models and stratified by air basin and housing characteristics. Our findings reveal that cooling type and renovation status are key factors modifying the smoke exposure-preterm birth relationship. Notably, we found elevated associations for people living in unrenovated homes, those using evaporative cooling systems, and those using central air conditioning units. While we observed elevated odds of preterm birth associated with increasing smoke day exposure for residents of large and new homes, this effect does not significantly differ across home size and age quartiles. This study highlights the need to further examine the relative roles of housing characteristics as well as factors not measured here including behavioral factors, time spent outdoors, window use, and occupational exposures in driving adverse birth outcomes related to wildfire smoke exposure.

Research progress on the characteristics, sources, and environmental and potential health effects of water-soluble organic compounds in atmospheric particulate matter

Water-soluble organic compounds (WSOCs) have received extensive attention due to their indistinct chemical components, complex sources, negative environmental impact, and potential health effects. To the best of our knowledge, until now, there has been no comprehensive review focused on the research progress of WSOCs. This paper reviewed the studies on chemical constituent and characterization, distribution condition, sources, environmental impact, as well as the potential health effects of WSOCs in the past 13 years. Moreover, the main existing challenges and directions for the future research on WSOCs were discussed from several aspects. Because of the complex composition of WSOCs and many unknown individual components that have not been detected, there is still a need for the identification and quantification of WSOCs. As modern people spend more time in indoor environments, it is meaningful to fill the gaps in the component characteristics and sources of indoor WSOCs. In addition, although in vitro cell experiments have shown that WSOCs could induce cellular oxidative stress and trigger the inflammatory response, the corresponding mechanisms of action need to be further explored. The current population epidemiology research of WSOCs is missing. Prospectively, we propose to conduct a comprehensive and simultaneous analysis strategy for concentration screening, source apportionment, potential health effects, and action mechanisms of WSOCs based on high throughput omics coupled with machine learning simulation and prediction.

Experimental and numerical analysis of indoor air quality affected by outdoor air particulate levels (PM1.0, PM2.5 and PM10), room infiltration rate, and occupants' behaviour

This study conducted an experimental analysis of how indoor air quality (IAQ) is influenced by the outdoor air pollutants levels, infiltration rate, and occupants' behaviours. The impacts of these factors on IAQ were analyzed using on-site measurements and numerical simulations. The results contribute to a better understanding of how to control the Indoor Particulate Level (IPL) for the specific conditions of the studied building. Results showed that occupant behaviour was the primary factor in determining the IPL, significantly changing the number of outdoor particles introduced to the building. Moreover, it was found that the IPL was exponentially correlated to the Outdoor Particulate Level (OPL). Based on numerical simulations, this study concluded that smaller particles do not always have more chance than larger particles of accessing the indoor environment through the building envelope. Meanwhile, a steady-state indoor particle concentration numerical model was established and verified using the 4-fold cross-validation method. Finally, simulation results identified that the room infiltration rate had a positive linear impact on IAQ if the OPL was under 30 μg/m³. This is because the increased air exchange rate can help to dilute indoor air pollutants when the outdoor air is relatively clean.

The impact of climate change on the risk factors for tuberculosis: A systematic review

BACKGROUND

Tuberculosis (TB) continues to pose a major public health risk in many countries. The current incidence of disease exceeds guidelines proposed by the World Health Organisation and United Nations. Whilst the relationship between climate change and TB has surfaced in recent literature, it remains neglected in global agendas. There is a need to acknowledge TB as a climate-sensitive disease to facilitate its eradication.

OBJECTIVE

To review epidemiological and prediction model studies that explore how climate change may affect the risk factors for TB, as outlined in the Global Tuberculosis Report 2021: HIV infection, diabetes mellitus, undernutrition, overcrowding, poverty, and indoor air pollution.

METHODS

We conducted a systematic literature search of PubMed, Embase, and Scopus databases to identify studies examining the association between climate variables and the risk factors for TB. Each study that satisfied the inclusion criteria was assessed for quality and ethics. Studies then underwent vote-counting and were categorised based on whether an association was found.

RESULTS

53 studies met inclusion criteria and were included in our review. Vote-counting revealed that two out of two studies found a positive association between the examined climate change proxy and HIV, nine out of twelve studies for diabetes, eight out of seventeen studies for undernutrition, four out of five studies for overcrowding, twelve out of fifteen studies for poverty and one out of three studies for indoor air pollution.

DISCUSSION

We found evidence supporting a positive association between climate change and each of the discussed risk factors for TB, excluding indoor air pollution. Our findings suggest that climate change is likely to affect the susceptibility of individuals to TB by increasing the prevalence of its underlying risk factors, particularly in developing countries. This is an evolving field of research that requires further attention in the scientific community.

Spatio-Temporal Evolution and Spatial Heterogeneity of Influencing Factors of SO2 Emissions in Chinese Cities: Fresh Evidence from MGWR

In this study, based on the multi-source nature and humanities data of 270 Chinese cities from 2007 to2018, the spatio-temporal evolution characteristics of SO2 emissions are revealed by using Moran’s I, a hot spot analysis, kernel density, and standard deviation ellipse models. The spatial scale heterogeneity of influencing factors is explored by using the multiscale geographically weighted regression model to make the regression results more accurate and reliable. The results show that (1) SO2 emissions showed spatial clustering characteristics during the study period, decreased by 85.12% through pollution governance, and exhibited spatial heterogeneity of differentiation. (2) The spatial distribution direction of SO2 emissions’ standard deviation ellipse in cities was “northeast–southwest”. The gravity center of the SO2 emissions shifted to the northeast, from Zhumadian City to Zhoukou City in Henan Province. The results of hot spots showed a polarization trend of “clustering hot spots in the north and dispersing cold spots in the south”. (3) The MGWR model is more accurate than the OLS and classical GWR regressions. The different spatial bandwidths have a different effect on the identification of influencing factors. There were several main influencing factors on urban SO2 emissions: the regional innovation and entrepreneurship level, government intervention, and urban precipitation; important factors: population intensity, financial development, and foreign direct investment; secondary factors: industrial structure upgrading and road construction. Based on the above conclusions, this paper explores the spatial heterogeneity of urban SO2 emissions and their influencing factors, and provides empirical evidence and reference for the precise management of SO2 emission reduction in “one city, one policy”.

Using Low-Cost Sensors to Assess Fine Particulate Matter Infiltration (PM2.5) during a Wildfire Smoke Episode at a Large Inpatient Healthcare Facility

Wildfire smoke exposure is associated with a range of acute health outcomes, which can be more severe in individuals with underlying health conditions. Currently, there is limited information on the susceptibility of healthcare facilities to smoke infiltration. As part of a larger study to address this gap, a rehabilitation facility in Vancouver, Canada was outfitted with one outdoor and seven indoor low-cost fine particulate matter (PM_2.5) sensors in Air Quality Eggs (EGG) during the summer of 2020. Raw measurements were calibrated using temperature, relative humidity, and dew point derived from the EGG data. The infiltration coefficient was quantified using a distributed lag model. Indoor concentrations during the smoke episode were elevated throughout the building, though non-uniformly. After censoring indoor-only peaks, the average infiltration coefficient (range) during typical days was 0.32 (0.22–0.39), compared with 0.37 (0.31–0.47) during the smoke episode, a 19% increase on average. Indoor PM_2.5 concentrations quickly reflected outdoor conditions during and after the smoke episode. It is unclear whether these results will be generalizable to other years due to COVID-related changes to building operations, but some of the safety protocols may offer valuable lessons for future wildfire seasons. For example, points of building entry and exit were reduced from eight to two during the pandemic, which likely helped to protect the building from wildfire smoke infiltration. Overall, these results demonstrate the utility of indoor low-cost sensors in understanding the impacts of extreme smoke events on facilities where highly susceptible individuals are present. Furthermore, they highlight the need to employ interventions that enhance indoor air quality in such facilities during smoke events.