Air pollution and inhalation exposure to particulate matter of different sizes in rural households using improved stoves in central China

Comparing human exposure to fine particulate matter in low and high-income countries: A systematic review of studies measuring personal PM2.5 exposure

BACKGROUND

Due to the adverse health effects of air pollution, researchers have advocated for personal exposure measurements whereby individuals carry portable monitors in order to better characterise and understand the sources of people's pollution exposure.

OBJECTIVES

The aim of this systematic review is to assess the differences in the magnitude and sources of personal PM2.5 exposures experienced between countries at contrasting levels of income.

METHODS

This review summarised studies that measured participants personal exposure by carrying a PM2.5 monitor throughout their typical day. Personal PM2.5 exposures were summarised to indicate the distribution of exposures measured within each country income category (based on low (LIC), lower-middle (LMIC), upper-middle (UMIC), and high (HIC) income countries) and between different groups (i.e. gender, age, urban or rural residents).

RESULTS

From the 2259 search results, there were 140 studies that met our criteria. Overall, personal PM2.5 exposures in HICs were lower compared to other countries, with UMICs exposures being slightly lower than exposures measured in LMICs or LICs. 34% of measured groups in HICs reported below the ambient World Health Organisation 24-h PM2.5 guideline of 15 μg/m3, compared to only 1% of UMICs and 0% of LMICs and LICs. There was no difference between rural and urban participant exposures in HICs, but there were noticeably higher exposures recorded in rural areas compared to urban areas in non-HICs, due to significant household sources of PM2.5 in rural locations. In HICs, studies reported that secondhand smoke, ambient pollution infiltrating indoors, and traffic emissions were the dominant contributors to personal exposures. While, in non-HICs, household cooking and heating with biomass and coal were reported as the most important sources.

CONCLUSION

This review revealed a growing literature of personal PM2.5 exposure studies, which highlighted a large variability in exposures recorded and severe inequalities in geographical and social population subgroups.

Socioeconomic and Environmental Aspects of Traditional Firewood for Cooking on the Example of Rural and Peri-Urban Mexican Households

Firewood is a solid biofuel that is widely used for cooking in Mexico’s residential sector. This study seeks to identify relevant factors in firewood consumption patterns, and their implications for climate change, gender, and health, and for energy poverty in Mexico, by climate region and socioeconomic level. For this purpose, a statistical analysis was conducted of recently published official information. We estimate that a total of 31.3 million Mexicans—26% of the total population—use firewood, and we have identified three main types of users: (i) exclusive firewood users (30%); (ii) mixed firewood users using firewood as their primary fuel (18%) and (iii) mixed firewood users using firewood as their secondary fuel source (52%). Total consumption of firewood was estimated at 116.6 PJ, while estimated greenhouse gas emissions were 8.1 million tCO2e. Out of all the households studied, 53% were in the tropical climate region; 59% were categorized as being in the “low” socioeconomic level; and 75% were in population centers comprising fewer than 2500 inhabitants. Some 68% of households do not pay for the acquisition of firewood, and for those households that do pay for the resource, estimated transactions total USD 286.9 million. Expenditures on firewood for energy represent up to 10% of household income. Finally, it was estimated that 15.7 million direct users of firewood are women who use the resource in three-stone fires, in which they expose themselves to health risks in doing so. In conclusion, main universal findings, the study’s limitations, and future research are presented.

Source contributions and drivers of physiological and psychophysical cobenefits from major air pollution control actions in North China

North China is among the most polluted regions in the country, and human exposure to PM_2.5 (particulate matter with an aerodynamic diameter less than 2.5 μm) in this region has led to severe health consequences. The region has also benefited the most from emission reductions in recent years. It is of interest to understand to what extent and through which paths emissions from different sectors cause adverse health impacts. Here, we present the results of a full evaluation of the health benefits of emission control actions implemented in recent years based on segregated emission inventories with an emphasis on residential emissions. Two major causal paths, one from residential emissions to indoor air pollution, exposure, and premature deaths, and the other from nonresidential emissions to ambient air pollution and psychophysical impacts, were identified and quantified. From 2014 to 2019, both ambient (33%) and indoor (39%) PM_2.5 decreased significantly, leading to decreasing trends in exposure (36%), premature deaths (10%), and psychophysical impacts (21%). The Air Pollution Prevention and Control Action Plan, the Clean Heating Campaign, and spontaneous residential shifts to clean energy contributed significantly to these reductions when the effects of other drivers, such as population and economic growth, were excluded.

A critical review of pollutant emission factors from fuel combustion in home stoves

A large population does not have access to modern household energy and relies on solid fuels such as coal and biomass fuels. Burning of these solid fuels in low-efficiency home stoves produces high amounts of multiple air pollutants, causing severe air pollution and adverse health outcomes. In evaluating impacts on human health and climate, it is critical to understand the formation and emission processes of air pollutants from these combustion sources. Air pollutant emission factors (EFs) from indoor solid fuel combustion usually highly vary among different testing protocols, fuel-stove systems, sampling and analysis instruments, and environmental conditions. In this critical review, we focus on the latest developments in pollutant emission factor studies, with emphases on the difference between lab and field studies, fugitive emission quantification, and factors that contribute to variabilities in EFs. Field studies are expected to provide more realistic EFs for emission inventories since lab studies typically do not simulate real-world burning conditions well. However, the latter has considerable advantages in evaluating formation mechanisms and variational influencing factors in observed pollutant EFs. One main challenge in field emission measurement is the suitable emission sampling system. Reasons for the field and lab differences have yet to be fully elucidated, and operator behavior can have a significant impact on such differences. Fuel properties and stove designs affect emissions, and the variations are complexly affected by several factors. Stove classification is a challenge in the comparison of EF results from different studies. Lab- and field-based methods for quantifying fugitive emissions, as an important contributor to indoor air pollution, have been developed, and priority work is to develop a database covering different fuel-stove combinations. Studies on the dynamics of the combustion process and evolution of air pollutant formation and emissions are scarce, and these factors should be an important aspect of future work.

Characterization and exposure assessment of household fine particulate matter pollution in China

Household fine particulate matter (PM_2.5 ) pollution greatly impacts residents' health. To explore the current national situation of household PM_2.5 pollution in China, a study was conducted based on literature published from 1998 to 2018. After extracting data from the literature in conformity with the requirements, the nationwide household-weighted mean concentration of household PM_2.5 (HPL) was calculated. Subgroup analyses of spatial, geographic, and temporal differences were also done. The estimated overall HPL in China was 132.2 ± 117.7 μg/m³ . HPL in the rural area (164.3 ± 104.5 μg/m³ ) was higher than that in the urban area (123.9 ± 122.3 μg/m³ ). For HPLs of indoor sampling sites, the kitchen was the highest, followed by the bedroom and living room. There were significant differences of geographic distributions. The HPLs in the South were higher than the North in four seasons. The inhaled dose of household PM_2.5 among school-age children differed from provinces with the highest dose up to 5.9 μg/(kg·d). Countermeasures should be carried out to reduce indoor pollution and safeguard health urgently.

Quantifying and predicting ecological and human health risks for binary heavy metal pollution accidents at the watershed scale using Bayesian Networks

The accidental leakage of industrial wastewater containing heavy metals from enterprises poses great risks to resident health, social instability, and ecological safety. During 2005-2018, heavy metal mixed pollution accidents comprised approximately 33% of the major environmental ones in China. A Bayesian Networks-based probabilistic approach is developed to quantitatively predict ecological and human health risks for heavy metal mixed pollution accidents at the watershed scale. To estimate the probability distributions of joint ecological exposure once a heavy metal mixed pollution accident occurs, a Copula-based joint exposure calculation method, comprised of a hydro-dynamic model, emergent heavy metal pollution transport model, and the Copula functions, is embedded. This approach was applied to the risk assessment of acute Cr⁶⁺-Hg²⁺ mixed pollution accidents at 76 electroplating enterprises in 24 risk sub-watersheds of the Dongjiang River downstream watershed. The results indicated that nine sub-watersheds created high ecological risks, while only five created high human health risks. In addition, the ecological and human health risk levels were highest in the tributary (the Xizhijiang River), while the ecological risk was more critical in the river network, and the human health risk was more serious in the mainstream of the Dongjiang River. The quantitative risk assessment provides a substantial support to incident prevention and control, risk management, as well as regulatory decision making for electroplating enterprises.

Sensors for indoor air quality monitoring and assessment through Internet of Things: a systematic review

The growing populations around the world are closely associated with rising levels of air pollution. The impact is not restricted to outdoor areas. Moreover, the health of building occupants is also deteriorating due to poor indoor air quality. As per the World Health Organization, indoor air pollution is a leading cause of 1.6 million premature deaths annually. Therefore, numerous companies have started the development of low-cost sensors to monitor indoor air pollution with the Internet of Things-based applications. However, due to the close association of air pollution levels to the mortality and morbidity rates, communities face several limitations while selecting sensors to address this public health challenge. The main contribution of this systematic review is to present a qualitative and quantitative evaluation of low-cost sensors while providing deep insights into the selection criteria for adequate monitoring. The authors in this paper discussed studies published after the year 2015, and it includes an analysis of papers published in the English language only. Moreover, this study highlights crucial research questions, states answers, and provides recommendations for future research studies. The outcomes of this paper will be useful for students, researchers, and industry members concerning the upcoming research and manufacturing activities. The results show that 28 studies (70%) include indoor thermal comfort assessment, 26 (65%) and 12 (30%) studies include CO₂ and CO sensors, respectively. In total, 32 (45.7%) out of 71 sensors (whose prices are available) discussed in this study are available in a price below the US $20 over online marketplaces. Furthermore, the authors conclude that 77.5% of the analyzed literature does not include calibration details, and the accuracy specification is missing for 39.4% sensors.

Determinants of personal exposure to PM2.5 and black carbon in Chinese adults: A repeated-measures study in villages using solid fuel energy

Exposure to air pollution is a leading health risk factor. The variance components and contributions of indoor versus outdoor source determinants of personal exposure to air pollution are poorly understood, especially in settings of household solid fuel use. We conducted a panel study with up to 4 days of repeated measures of integrated gravimetric personal exposure to PM2.5 and black carbon in 787 men and women (ages 40-79) living in peri-urban villages in northern (Beijing and Shanxi) and southern (Guangxi) China. We simultaneously measured outdoor PM2.5 and collected questionnaire data on sociodemographic characteristics and indoor pollution sources including tobacco smoking and solid fuel stove use. We obtained over 2000 days of personal exposure monitoring which showed higher exposures in the heating season (geometric mean (GM): 108 versus 65 μg/m3 in the non-heating season for PM2.5) and among northern participants (GM: 90 versus 59 μg/m3 in southern China in the non-heating season for PM2.5). We used mixed-effects models to estimate within- and between-participant variance components and to assess the determinants of exposures. Within-participant variance in exposure dominated the total variability (68-95%). Outdoor PM2.5 was the dominant variable for explaining within-participant variance in exposure to PM2.5 (16%). Household fuel use (PM2.5: 8%; black carbon: 10%) and smoking status (PM2.5: 27%; black carbon: 5%) explained the most between-participant variance. Indoor sources (solid fuel stoves, tobacco smoking) were associated with 13-30% higher exposures to air pollution and each 10 μg/m3 increase in outdoor PM2.5 was associated with 6-8% higher exposure. Our findings indicate that repeated measurements of daily exposure are likely needed to capture longer-term exposures in settings of household solid fuel use, even within a single season, and that reducing air pollution from both outdoor and indoor sources is likely needed to achieve measurable reductions in exposures to air pollution.

Indoor Air Quality Monitoring Systems Based on Internet of Things: A Systematic Review

Indoor air quality has been a matter of concern for the international scientific community. Public health experts, environmental governances, and industry experts are working to improve the overall health, comfort, and well-being of building occupants. Repeated exposure to pollutants in indoor environments is reported as one of the potential causes of several chronic health problems such as lung cancer, cardiovascular disease, and respiratory infections. Moreover, smart cities projects are promoting the use of real-time monitoring systems to detect unfavorable scenarios for enhanced living environments. The main objective of this work is to present a systematic review of the current state of the art on indoor air quality monitoring systems based on the Internet of Things. The document highlights design aspects for monitoring systems, including sensor types, microcontrollers, architecture, and connectivity along with implementation issues of the studies published in the previous five years (2015-2020). The main contribution of this paper is to present the synthesis of existing research, knowledge gaps, associated challenges, and future recommendations. The results show that 70%, 65%, and 27.5% of studies focused on monitoring thermal comfort parameters, CO₂, and PM levels, respectively. Additionally, there are 37.5% and 35% of systems based on Arduino and Raspberry Pi controllers. Only 22.5% of studies followed the calibration approach before system implementation, and 72.5% of systems claim energy efficiency.

Indoor Air Quality Monitoring Systems Based on Internet of Things: A Systematic Review

Indoor air quality has been a matter of concern for the international scientific community. Public health experts, environmental governances, and industry experts are working to improve the overall health, comfort, and well-being of building occupants. Repeated exposure to pollutants in indoor environments is reported as one of the potential causes of several chronic health problems such as lung cancer, cardiovascular disease, and respiratory infections. Moreover, smart cities projects are promoting the use of real-time monitoring systems to detect unfavorable scenarios for enhanced living environments. The main objective of this work is to present a systematic review of the current state of the art on indoor air quality monitoring systems based on the Internet of Things. The document highlights design aspects for monitoring systems, including sensor types, microcontrollers, architecture, and connectivity along with implementation issues of the studies published in the previous five years (2015-2020). The main contribution of this paper is to present the synthesis of existing research, knowledge gaps, associated challenges, and future recommendations. The results show that 70%, 65%, and 27.5% of studies focused on monitoring thermal comfort parameters, CO2, and PM levels, respectively. Additionally, there are 37.5% and 35% of systems based on Arduino and Raspberry Pi controllers. Only 22.5% of studies followed the calibration approach before system implementation, and 72.5% of systems claim energy efficiency.

Aerosol-photolysis interaction reduces particulate matter during wintertime haze events

Aerosol-radiation interaction (ARI) plays a significant role in the accumulation of fine particulate matter (PM_2.5) by stabilizing the planetary boundary layer and thus deteriorating air quality during haze events. However, modification of photolysis by aerosol scattering or absorbing solar radiation (aerosol-photolysis interaction or API) alters the atmospheric oxidizing capacity, decreases the rate of secondary aerosol formation, and ultimately alleviates the ARI effect on PM_2.5 pollution. Therefore, the synergetic effect of both ARI and API can either aggravate or even mitigate PM_2.5 pollution. To test the effect, a fully coupled Weather Research and Forecasting (WRF)-Chem model has been used to simulate a heavy haze episode in North China Plain. Our results show that ARI contributes to a 7.8% increase in near-surface PM_2.5 However, API suppresses secondary aerosol formation, and the combination of ARI and API results in only 4.8% net increase of PM_2.5 Additionally, API increases the solar radiation reaching the surface and perturbs aerosol nucleation and activation to form cloud condensation nuclei, influencing aerosol-cloud interaction. The results suggest that API reduces PM_2.5 pollution during haze events, but adds uncertainties in climate prediction.

Distribution characteristics of and personal exposure with polycyclic aromatic hydrocarbons and particulate matter in indoor and outdoor air of rural households in Northern China

Gaseous and particulate polycyclic aromatic hydrocarbons (PAHs) and size-segregated particulate matter (PM) in indoor air and outdoor air, along with personal exposure, were monitored in rural households of Northern China. The daily average concentrations of 28 species were 1310 ± 811, 738 ± 321, 465 ± 247, and 655 ± 250 ng/m³ in kitchen air, bedroom air, and outdoor air, and for personal exposure, respectively. PAHs tended to occur in the particulate phase with increasing molecular weight. Absorption by particulate organic carbon was dominant in the gas-particle partitioning process. The daily averaged concentrations of PM_2.5 and PM_1.0 were 104 ± 39.5 and 88.4 ± 39.3 μg/m³ in kitchen air, 79.0 ± 63.2 and 65.7 ± 57.5 μg/m³ in bedroom air, 52.9 ± 16.5 and 41.5 ± 12.5 μg/m³ in outdoor air, and 71.7 ± 30.8 and 61.5 ± 28.4 μg/m³ for personal exposure, respectively. The non-priority components contributed 5.5 ± 2.8% to the total PAHs, while their fraction of carcinogenic risk reached 85.6 ± 6.9%. The mean cancer risk posed to rural residents via inhalation exposure to PAHs exceeded the current acceptable threshold of 1.0 × 10^-6 and the national average estimated in China. The personal exposure levels of PAHs and PM in households using clean energy were lower than those in households using traditional biomass by 30.0%, 29.4%, and 38.5% for PAH₂₈, PM_2.5, and PM_1.0, respectively. However, the cancer risk of personal inhalation exposure to PAH₂₈ from using liquid petroleum gas (LPG) was higher than that from using firewood, implying the adoption of LPG may not effectively reduce the cancer risk despite the decreasing exposure levels of PAH₂₈ and PM with respect to the use of firewood. Cooking individuals suffered higher exposure levels of PAH₂₈ and PM_1.0 compared with non-cooking individuals, and the cancer risk of personal inhalation exposure to PAH₂₈ for cooking individuals was 1.7 times that for non-cooking individuals. Cooking was a critical factor that affected the personal exposure levels of the local male and female residents.

Population-weighted exposure to PM2.5 pollution in China: An integrated approach

Fine particulate matter air pollution (PM_2.5) is a major risk factor for premature death globally. Studies of the PM_2.5 health burden usually treat exposure to ambient air pollution (AAP) and household air pollution from solid fuels (HAP) as separate risk factors. AAP and HAP can, however, be closely interrelated. Taking as the starting point that the total exposure to PM_2.5 is what matters for health, and recognizing the curvilinear form of exposure-response functions for important health effects, we develop a method for estimating the total annual mean population-weighted personal exposure, denoted integrated population-weighted exposure (IPWE). To establish the IPWE in China, we used recent emission inventories, Chemical Transport Models, China Census data on population and residential fuel use, and estimates of the PM_2.5 exposure among solid fuel users. We found an IPWE of 151 [123-179] μg/m³, of which 62-74% was attributable to residential solid fuels through HAP exposure and the residential sector emissions' contribution to AAP. We found large disparities in the PM_2.5 exposure burden, with an estimated IPWE in rural populations nearly twice the level in urban populations. Using the IPWE metric, we estimated that 1.15 [1.09-1.19] million premature deaths were attributable to PM_2.5 exposure annually in the period 2010-2013. Using the same data set, but calculating premature deaths from AAP and HAP in isolation, the estimated number was nearly 50% higher. The IPWE metric enables integration across AAP and HAP in policy analyses and could mitigate the concern of a potential double counting of the health burden that may arise from treating AAP and HAP as separate health risk factors.