AirPen: A Wearable Monitor for Characterizing Exposures to Particulate Matter and Volatile Organic Compounds.

Exposure to air pollution is a leading risk factor for disease and premature death, but technologies for assessing personal exposure to particulate and gaseous air pollutants, including the timing and location of such exposures, are limited. We developed a small, quiet, wearable monitor, called the AirPen, to quantify personal exposures to fine particulate matter (PM2.5) and volatile organic compounds (VOCs). The AirPen combines physical sample collection (PM onto a filter and VOCs onto a sorbent tube) with a suite of low-cost sensors (for PM, VOCs, temperature, pressure, humidity, light intensity, location, and motion). We validated the AirPen against conventional personal sampling equipment in the laboratory and then conducted a field study to measure at-work and away-from-work exposures to PM2.5 and VOCs among employees at an agricultural facility in Colorado, USA. The resultant sampling and sensor data indicated that personal exposures to benzene, toluene, ethylbenzene, and xylenes were dominated by a specific workplace location. These results illustrate how the AirPen can be used to advance our understanding of personal exposure to air pollution as a function of time, location, source, and activity, even in the absence of detailed activity diary data.

Cross-sectional study of household solid fuel use and renal function in older adults in China.

BACKGROUND: Emerging evidence links outdoor air pollution and declined renal function but the relationship between household air pollution and renal function is not well understood. METHODS: Using cross-sectional data from the multi-provincial INTERMAP-China Prospective Study, we collected blood samples and questionnaire information on stove use and socio-demographic factors. We calculated estimated glomerular filtration rate (eGFR) from serum creatinine to assess renal function. Participants with eGFR <60 mL/min per 1.73 m2 were defined as having chronic kidney disease (CKD) in this analysis. Generalized estimating equations were used to estimate the association of household fuel with renal function and prevalent CKD in models adjusting for confounders. RESULTS: Among the 646 enrolled adults (40-79y; 56% female), one-third exclusively used clean fuel (gas and electric) cookstoves and 11% of northern China participants (n = 49 of 434) used only clean fuel heaters, whereas the rest used solid fuel. In multivariable models, use of solid fuel cookstoves was associated with 0.17 ml/min/1.73 m2 (95% CI: -0.30, 0.64) higher eGFR and 19% (0.86, 1.64) higher prevalence of CKD than exclusive clean fuel use. Greater intensity of solid fuel use was associated with 0.25 ml/min/1.73 m2 (-0.71, 0.21) lower eGFR per 5 stove-use years, though the confidence intervals included the null, while greater current intensity of indoor solid fuel use was associated with 1.02 (1.00, 1.04) higher prevalent CKD per 100 stove-use days per year. Larger associations between current solid fuel use and intensity of use with lower eGFR and prevalent CKD were observed among participants in southern China, those with hypertension or diabetes (eGFR only), and females (CKD only), through these groups had small sample sizes and some confidence intervals included the null. CONCLUSION: We found inconsistent evidence associating household solid fuel use and renal function in this cross-sectional study of peri-urban Chinese adults.

Socioeconomic and Demographic Associations with Wintertime Air Pollution Exposures at Household, Community, and District Scales in Rural Beijing, China.

The Chinese government implemented a national household energy transition program that replaced residential coal heating stoves with electricity-powered heat pumps for space heating in northern China. As part of a baseline assessment of the program, this study investigated variability in personal air pollution exposures within villages and between villages and evaluated exposure patterns by sociodemographic factors. We randomly recruited 446 participants in 50 villages in four districts in rural Beijing and measured 24 h personal exposures to fine particulate matter (PM2.5) and black carbon (BC). The geometric mean personal exposure to PM2.5 and BC was 72 and 2.5 µg/m3, respectively. The variability in PM2.5 and BC exposures was greater within villages than between villages. Study participants who used traditional stoves as their dominant source of space heating were exposed to the highest levels of PM2.5 and BC. Wealthier households tended to burn more coal for space heating, whereas less wealthy households used more biomass. PM2.5 and BC exposures were almost uniformly distributed by socioeconomic status. Future work that combines these results with PM2.5 chemical composition analysis will shed light on whether air pollution source contributors (e.g., industrial, traffic, and household solid fuel burning) follow similar distributions.

Detailed Investigation of the Contribution of Gas-Phase Air Contaminants to Exposure Risk during Indoor Activities.

Analytical capabilities in atmospheric chemistry provide new opportunities to investigate indoor air. HOMEChem was a chemically comprehensive indoor field campaign designed to investigate how common activities, such as cooking and cleaning, impacted indoor air in a test home. We combined gas-phase chemical data of all compounds, excluding those with concentrations <1 ppt, with established databases of health effect thresholds to evaluate potential risks associated with gas-phase air contaminants and indoor activities. The chemical composition of indoor air is distinct from outdoor air, with gaseous compounds present at higher levels and greater diversity─and thus greater predicted hazard quotients─indoors than outdoors. Common household activities like cooking and cleaning induce rapid changes in indoor air composition, raising levels of multiple compounds with high risk quotients. The HOMEChem data highlight how strongly human activities influence the air we breathe in the built environment, increasing the health risk associated with exposure to air contaminants.

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 PM2.5 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 PM2.5 during the COVID-19 lockdown. Indoor-generated PM2.5 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.

Predicting Within-City Spatial Variations in Outdoor Ultrafine Particle and Black Carbon Concentrations in Bucaramanga, Colombia: A Hybrid Approach Using Open-Source Geographic Data and Digital Images.

Outdoor ultrafine particles (UFP, <0.1 µm) and black carbon (BC) vary greatly within cities and may have adverse impacts on human health. In this study, we used a hybrid approach to develop new models to estimate within-city spatial variations in outdoor UFP and BC concentrations across Bucaramanga, Colombia. We conducted a mobile monitoring campaign over 20 days in 2019. Regression models were trained on land use data and combined with predictions from convolutional neural networks (CNN) trained to predict UFP and BC concentrations using satellite and street-level images. The combined UFP model (R2 = 0.54) outperformed the CNN (R2 = 0.47) and land use regression (LUR) models (R2 = 0.47) on their own. Similarly, the combined BC model also outperformed the CNN and LUR BC models (R2 = 0.51 vs 0.43 and 0.45, respectively). Spatial variations in model performance were more stable for the CNN and combined models compared to the LUR models, suggesting that the combined approach may be less likely to contribute to differential exposure measurement error in epidemiological studies. In general, our findings demonstrated that satellite and street-level images can be combined with a traditional LUR modeling approach to improve predictions of within-city spatial variations in outdoor UFP and BC concentrations.

Chemical Investigation of Household Solid Fuel Use and Outdoor Air Pollution Contributions to Personal PM2.5 Exposures.

In communities with household solid fuel use, transitioning to clean stoves/fuels often results in only moderate reductions in fine particulate matter (PM2.5) exposures; the chemical composition of those exposures may help explain why. We collected personal exposure (men and women) and outdoor PM2.5 samples in villages in three Chinese provinces (Shanxi, Beijing, and Guangxi) and measured chemical components, including water-soluble organic carbon (WSOC), ions, elements, and organic tracers. Source contributions from chemical mass balance modeling (biomass burning, coal combustion, vehicles, dust, and secondary inorganic aerosol) were similar between outdoor and personal PM2.5 samples. Principal component analysis of organic and inorganic components identified analogous sources, including a regional ambient source. Chemical components of PM2.5 exposures did not differ significantly by gender. Participants using coal had higher personal/outdoor (P/O) ratios of coal combustion tracers (picene, sulfate, As, and Pb) than those not using coal, but no such trend was observed for biomass burning tracers (levoglucosan, K+, WSOC). Picene and most levoglucosan P/O ratios exceeded 1 even among participants not using coal and biomass, respectively, indicating substantial indirect exposure to solid fuel emissions from other homes. Contributions of community-level emissions to exposures suggest that meaningful exposure reductions will likely require extensive fuel use changes within communities.

Design and Testing of a Low-Cost Sensor and Sampling Platform for Indoor Air Quality.

Americans spend most of their time indoors at home, but comprehensive characterization of in-home air pollution is limited by the cost and size of reference-quality monitors. We assembled small "Home Health Boxes" (HHBs) to measure indoor PM2.5, PM10, CO2, CO, NO2, and O3 concentrations using filter samplers and low-cost sensors. Nine HHBs were collocated with reference monitors in the kitchen of an occupied home in Fort Collins, Colorado, USA for 168 h while wildfire smoke impacted local air quality. When HHB data were interpreted using gas sensor manufacturers' calibrations, HHBs and reference monitors (a) categorized the level of each gaseous pollutant similarly (as either low, elevated, or high relative to air quality standards) and (b) both indicated that gas cooking burners were the dominant source of CO and NO2 pollution; however, HHB and reference O3 data were not correlated. When HHB gas sensor data were interpreted using linear mixed calibration models derived via collocation with reference monitors, root-mean-square error decreased for CO2 (from 408 to 58 ppm), CO (645 to 572 ppb), NO2 (22 to 14 ppb), and O3 (21 to 7 ppb); additionally, correlation between HHB and reference O3 data improved (Pearson's r increased from 0.02 to 0.75). Mean 168-h PM2.5 and PM10 concentrations derived from nine filter samples were 19.4 µg m-3 (6.1% relative standard deviation [RSD]) and 40.1 µg m-3 (7.6% RSD). The 168-h PM2.5 concentration was overestimated by PMS5003 sensors (median sensor/filter ratio = 1.7) and underestimated slightly by SPS30 sensors (median sensor/filter ratio = 0.91).

Impacts of stove/fuel use and outdoor air pollution on chemical composition of household particulate matter.

Biomass combustion for cooking and heating releases particulate matter (PM2.5 ) that contributes to household air pollution. Fuel and stove types affect the chemical composition of household PM, as does infiltration of outdoor PM. Characterization of these impacts can inform future exposure assessments and epidemiologic studies, but is currently limited. In this study, we measured chemical components of PM2.5 (water-soluble organic matter [WSOM], ions, black carbon, elements, organic tracers) in rural Chinese households using traditional biomass stoves, semi-gasifier stoves with pelletized biomass, and/or non-biomass stoves. We distinguished households using one stove type (traditional, semi-gasifier, or LPG/electric) from those using multiple stoves/fuels. WSOM concentrations were higher in households using only semi-gasifier or traditional stoves (31%-33%) than in those with exclusive LPG/electric stove (13%) or mixed stove use (12%-22%). Inorganic ions comprised 14% of PM in exclusive LPG/electric households, compared to 1%-5% of PM in households using biomass. Total PAH content was much higher in households that used traditional stoves (0.8-2.8 mg/g PM) compared to those that did not (0.1-0.3 mg/g PM). Source apportionment revealed that biomass burning comprised 27%-84% of PM2.5 in households using biomass. In all samples, identified outdoor sources (vehicles, dust, coal combustion, secondary aerosol) contributed 10%-20% of household PM2.5 .

Acute Air Pollution Exposure and the Risk of Violent Behavior in the United States.

BACKGROUND: Violence is a leading cause of death and an important public health threat, particularly among adolescents and young adults. However, the environmental causes of violent behavior are not well understood. Emerging evidence suggests exposure to air pollution may be associated with aggressive or impulsive reactions in people. METHODS: We applied a two-stage hierarchical time-series model to estimate change in risk of violent and nonviolent criminal behavior associated with short-term air pollution in U.S. counties (2000-2013). We used daily monitoring data for ozone and fine particulate matter (PM2.5) from the Environmental Protection Agency and daily crime counts from the Federal Bureau of Investigation. We evaluated the exposure-response relation and assessed differences in risk by community characteristics of poverty, urbanicity, race, and age. RESULTS: Our analysis spans 301 counties in 34 states, representing 86.1 million people and 721,674 days. Each 10 µg/m change in daily PM2.5 was associated with a 1.17% (95% confidence interval [CI] = 0.90, 1.43) and a 10 ppb change in ozone with a 0.59% (95% CI = 0.41, 0.78) relative risk increase (RRI) for violent crime. However, we observed no risk increase for nonviolent property crime due to PM2.5 (RRI: 0.11%; 95% CI = -0.09, 0.31) or ozone (RRI: -0.05%; 95% CI = -0.22, 0.12). Our results were robust across all community types, except rural regions. Exposure-response curves indicated increased violent crime risk at concentrations below regulatory standards. CONCLUSIONS: Our results suggest that short-term changes in ambient air pollution may be associated with a greater risk of violent behavior, regardless of community type.

Effectiveness of a Household Energy Package in Improving Indoor Air Quality and Reducing Personal Exposures in Rural China.

We evaluated whether an energy package comprising a low-polluting semigasifier cookstove with chimney, water heater, and pelletized biomass fuel would improve air pollution in China. We measured the stove use, 48-h air pollution exposures (PM2.5, black carbon), and kitchen concentrations (PM2.5, black carbon, carbon monoxide, nitrogen oxides) for 205 women, along with ambient PM2.5. Over half (n = 125) were offered the energy package after baseline assessment, forming "treated" and "untreated" groups, and we repeated the measurements up to 3 occasions over 18-months. Kitchen carbon monoxide did not change, and nitrogen oxides increased in summer but decreased in winter for both groups. Summer geometric mean exposures and kitchen concentrations of PM2.5 and black carbon decreased by 24-67% in women who received the energy package, but greater reductions (48-70%) were observed in untreated homes, likely due to increased use of gas stoves. After adjusting for differences in outdoor PM2.5, receiving the energy package was associated with decreased winter exposures to PM2.5 (-46%; 95% CI: -70, -2) and black carbon (-55%; -74, -25) and the summer increases were smaller (PM2.5: 8%; -22, 51 and black carbon: 37%; -12, 113). However, PM2.5 exposures remained 1.5-3 times higher than those of health-based international air pollution targets.

The Oxidative Potential of Personal and Household PM2.5 in a Rural Setting in Southwestern China.

The chemical constituents of fine particulate matter (PM2.5) vary by source and capacity to participate in redox reactions in the body, which produce cytotoxic reactive oxygen species (ROS). Knowledge of the sources and components of PM2.5 may provide insight into the adverse health effects associated with the inhalation of PM2.5 mass. We collected 48 h household and personal PM2.5 exposure measurements in the summer months among 50 women/household pairs in a rural area of southwestern China where daily household biomass burning is common. PM2.5 mass was analyzed for ions, trace metals, black carbon, and water-soluble organic matter, as well as ROS-generating capability (oxidative potential) by one cellular and one acellular assay. Crustal enrichment factors and a principal component analysis identified the major sources of PM2.5 as dust, biomass burning, and secondary sulfate. Elements associated with the secondary sulfate source (As, Mo, Zn) had the strongest correlation with increased cellular oxidative potential (Spearman r: 0.74, 0.68, and 0.64). Chemical markers of biomass burning (water-soluble potassium and water-soluble organic matter) had negligible oxidative potential, suggesting that these assays may not be useful as health-relevant exposure metrics in populations that are exposed to high levels of smoke from household biomass burning.

Longitudinal evaluation of a household energy package on blood pressure, central hemodynamics, and arterial stiffness in China.

BACKGROUND: Cardiovascular diseases are the leading contributors to disease burden in China and globally, and household air pollution exposure is associated with risk of cardiovascular disease. OBJECTIVES: We evaluated whether subclinical cardiovascular outcomes in adult Chinese women would improve after distribution of an energy package comprised of a semi-gasifier cookstove, water heater, chimney, and supply of processed biomass fuel. METHODS: We enrolled 204 households (n = 205 women) from 12 villages into a controlled before- and after-intervention study on cardiovascular health and air pollution in Sichuan Province. The intervention was distributed to 124 households during a government-sponsored rural energy demonstration program. The remaining 80 households received the package 18 months later at the end of the study, forming a comparison group. One woman from each household had their blood pressure (BP), central hemodynamics, and arterial stiffness measured along with exposures to air pollution and demographic and household characteristics, on up to five visits. We used a difference-in-differences mixed-effects regression approach with Bayesian inference to assess the impact of the energy package on sub-clinical cardiovascular outcomes. RESULTS: Women who did not receive the energy package had greater mean decreases in brachial systolic (-4.1 mmHg, 95% credible interval (95%CIe) -7.3, -0.9) and diastolic BP (-2.0 mmHg, 95%CIe -3.6, -0.5) compared with women who received the package (systolic: -2.7, 95%CIe -5.0, -0.4; diastolic: -0.3, 95%CIe -1.4, 0.8) resulting in slightly positive but not statistically significant difference-in-differences effect estimates of 1.3 mmHg (95%CIe -2.5, 5.2) and 1.7 mmHg (95%CIe -0.3, 3.6), respectively. Similar trends were found for central BP, central pulse pressure, and arterial stiffness. Air pollution exposures decreased on average for both treatment groups, with a greater range of reductions among women who did not receive the package (with package: -30% to -50%; without package: +2% to -69%), likely as a result of increased use of gas fuel and electric stoves among this group. Outdoor air quality changed very little over time. CONCLUSIONS: Gasifier stoves have been widely promoted as the next generation of 'clean-cooking' technologies, however their effectiveness in improving health in real-world settings should be carefully evaluated and communicated before scaling up their implementation.

The Regional Impacts of Cooking and Heating Emissions on Ambient Air Quality and Disease Burden in China.

Exposure to air pollution is a major risk factor globally and particularly in Asia. A large portion of air pollutants result from residential combustion of solid biomass and coal fuel for cooking and heating. This study presents a regional modeling sensitivity analysis to estimate the impact of residential emissions from cooking and heating activities on the burden of disease at a provincial level in China. Model surface PM2.5 fields are shown to compare well when evaluated against surface air quality measurements. Scenarios run without residential sector and residential heating emissions are used in conjunction with the Global Burden of Disease 2013 framework to calculate the proportion of deaths and disability adjusted life years attributable to PM2.5 exposure from residential emissions. Overall, we estimate that 341 000 (306 000-370 000; 95% confidence interval) premature deaths in China are attributable to residential combustion emissions, approximately a third of the deaths attributable to all ambient PM2.5 pollution, with 159 000 (142 000-172 000) and 182 000 (163 000-197 000) premature deaths from heating and cooking emissions, respectively. Our findings emphasize the need to mitigate emissions from both residential heating and cooking sources to reduce the health impacts of ambient air pollution in China.

Seasonal and Diurnal Air Pollution from Residential Cooking and Space Heating in the Eastern Tibetan Plateau.

Residential combustion of solid fuel is a major source of air pollution. In regions where space heating and cooking occur at the same time and using the same stoves and fuels, evaluating air-pollution patterns for household-energy-use scenarios with and without heating is essential to energy intervention design and estimation of its population health impacts as well as the development of residential emission inventories and air-quality models. We measured continuous and 48 h integrated indoor PM2.5 concentrations over 221 and 203 household-days and outdoor PM2.5 concentrations on a subset of those days (in summer and winter, respectively) in 204 households in the eastern Tibetan Plateau that burned biomass in traditional stoves and open fires. Using continuous indoor PM2.5 concentrations, we estimated mean daily hours of combustion activity, which increased from 5.4 h per day (95% CI: 5.0, 5.8) in summer to 8.9 h per day (95% CI: 8.1, 9.7) in winter, and effective air-exchange rates, which decreased from 18 ± 9 h(-1) in summer to 15 ± 7 h(-1) in winter. Indoor geometric-mean 48 h PM2.5 concentrations were over two times higher in winter (252 µg/m(3); 95% CI: 215, 295) than in summer (101 µg/m(3); 95%: 91, 112), whereas outdoor PM2.5 levels had little seasonal variability.

Pollutant emissions and energy efficiency of Chinese gasifier cooking stoves and implications for future intervention studies.

Household air pollution from solid fuel combustion is the leading environmental health risk factor globally. In China, almost half of all homes use solid fuel to meet their household energy demands. Gasifier cookstoves offer a potentially affordable, efficient, and low-polluting alternative to current solid fuel combustion technology, but pollutant emissions and energy efficiency performance of this class of stoves are poorly characterized. In this study, four Chinese gasifier cookstoves were evaluated for their pollutant emissions and efficiency using the internationally recognized water boiling test (WBT), version 4.1.2. WBT performance indicators included PM2.5, CO, and CO2 emissions and overall thermal efficiency. Laboratory investigation also included evaluation of pollutant emissions (PM2.5 and CO) under stove operating conditions designed to simulate common Chinese cooking practices. High power average overall thermal efficiencies ranged from 22 to 33%. High power average PM2.5 emissions ranged from 120 to 430 mg/MJ of useful energy, and CO emissions ranged from 1 to 30 g/MJ of useful energy. Compared with several widely disseminated "improved" cookstoves selected from the literature, on average, the four Chinese gasifier cookstoves had lower PM2.5 emissions and higher CO emissions. The recent International Organization for Standardization (ISO) International Workshop Agreement on tiered cookstove ranking was developed to help classify stove performance and identify the best-performing stoves. The results from this study highlight potential ways to further improve this approach. Medium power stove operation emitted nearly twice as much PM2.5 as was emitted during high power stove operation, and the lighting phase of a cooking event contributed 45% and 34% of total PM2.5 emissions (combined lighting and cooking). Future approaches to laboratory-based testing of advanced cookstoves could improve to include greater differentiation between different modes of stove operation, beyond those evaluated with the WBT.

Cumulative Exposures to Environmental and Socioeconomic Risk Factors in Milwaukee County, Wisconsin.

The environmental justice literature demonstrates consistently that low-income and minority communities are disproportionately exposed to environmental hazards. In this case study, we examined cumulative multipollutant, multidomain, and multimatrix environmental exposures in Milwaukee County, Wisconsin for the year 2015. We identified spatial hot spots in Milwaukee County both individually (using local Moran's I) and through clusters (using K-means clustering) across a profile of environmental pollutants that span regulatory domains and matrices of exposure, as well as socioeconomic indicators. The cluster with the highest exposures within the urban area was largely characterized by low socioeconomic status and an overrepresentation of the Non-Hispanic Black population relative to the county as a whole. In this cluster, average pollutant concentrations were equivalent to the 78th percentile in county-level blood lead levels, 67th percentile in county-level NO2, 79th percentile in county-level CO, and 78th percentile in county-level air toxics. Simultaneously, this cluster had an average equivalent to the 62nd percentile in county-level unemployment, 70th percentile in county-level population rate lacking a high school diploma, 73rd percentile in county-level poverty rate, and 28th percentile in county-level median household income. The spatial patterns of pollutant exposure and SES indicators suggested that these disparities were not random but were instead structured by socioeconomic and racial factors. Our case study, which combines environmental pollutant exposures, sociodemographic data, and clustering analysis, provides a roadmap to identify and target overburdened communities for interventions that reduce environmental exposures and consequently improve public health.

Indoor air pollution in developing countries: research and implementation needs for improvements in global public health.

Exposure to indoor air pollution (IAP) from the burning of solid fuels for cooking, heating, and lighting accounts for a significant portion of the global burden of death and disease, and disproportionately affects women and children in developing regions. Clean cookstove campaigns recently received more attention and investment, but their successes might hinge on greater integration of the public health community with a variety of other disciplines. To help guide public health research in alleviating this important global environmental health burden, we synthesized previous research on IAP in developing countries, summarized successes and challenges of previous cookstove implementation programs, and provided key research and implementation needs from structured discussions at a recent symposium.

Size-Resolved Field Performance of Low-Cost Sensors for Particulate Matter Air Pollution.

Particulate matter (PM) air pollution is a major health hazard. The health effects of PM are closely linked to particle size, which governs its deposition in (and penetration through) the respiratory tract. In recent years, low-cost sensors that report particle concentrations for multiple-sized fractions (PM1.0, PM2.5, PM10) have proliferated in everyday use and scientific research. However, knowledge of how well these sensors perform across the full range of reported particle size fractions is limited. Unfortunately, erroneous particle size data can lead to spurious conclusions about exposure, misguided interventions, and ineffectual policy decisions. We assessed the linearity, bias, and precision of three low-cost sensor models, as a function of PM size fraction, in an urban setting. Contrary to manufacturers' claims, sensors are only accurate for the smallest size fraction (PM1). The PM1.0-2.5 and PM2.5-10 size fractions had large bias, noise, and uncertainty. These results demonstrate that low-cost aerosol sensors (1) cannot discriminate particle size accurately and (2) only report linear and precise measures of aerosol concentration in the accumulation mode size range (i.e., between 0.1 and 1 µm). We recommend that crowdsourced air quality monitoring networks stop reporting coarse (PM2.5-10) mode and PM10 mass concentrations from these sensors.