Effects of Road Traffic on the Accuracy and Bias of Low-Cost Particulate Matter Sensor Measurements in Houston, Texas.

Although PM2.5 measurements of low-cost particulate matter sensors (LCPMS) generally show moderate and strong correlations with those from research-grade air monitors, the data quality of LCPMS has not been fully assessed in urban environments with different road traffic conditions. We examined the linear relationships between PM2.5 measurements taken by an LCPMS (Dylos DC1700) and two research grade monitors, a personal environmental monitor (PEM) and the GRIMM 11R, in three different urban environments, and compared the accuracy (slope) and bias of these environments. PM2.5 measurements were carried out at three locations in Houston, Texas (Clinton Drive largely with diesel trucks, US-59 mostly with gasoline vehicles, and a residential home with no major sources of traffic emissions nearby). The slopes of the regressions of the PEM on Dylos and Grimm measurements varied by location (e.g., PEM/Dylos slope at Clinton Drive = 0.98 (R2 = 0.77), at US-59 = 0.63 (R2 = 0.42), and at the residence = 0.29 (R2 = 0.31)). Although the regression slopes and coefficients differed across the three urban environments, the mean percent bias was not significantly different. Using the correct slope for LCPMS measurements is key for accurately estimating ambient PM2.5 mass in urban environments.

Effects of aerosol particle size on the measurement of airborne PM2.5 with a low-cost particulate matter sensor (LCPMS) in a laboratory chamber.

Previous validation studies found a good linear correlation between the low-cost particulate matter sensors (LCPMS) and other research grade particulate matter (PM) monitors. This study aimed to determine if different particle size bins of PM would affect the linear relationship and agreement between the Dylos DC1700 (LCPMS) particle count measurements (converted to PM2.5 mass concentrations) and the Grimm 11R (research grade instrument) mass concentration measurements. Three size groups of PM2.5 (mass median aerodynamic diameters (MMAD): < 1 µm, 1-2 µm, and > 2 µm) were generated inside a laboratory chamber, controlled for temperature and relative humidity, by dispersing sodium chloride crystals through a nebulizer. A linear regression comparing 1-min average PM2.5 particle counts from the Dylos DC1700 (Dylos) to the Grimm 11R (Grimm) mass concentrations was estimated by particle size group. The slope for the linear regression was found to increase as MMAD increased (< 1 µm, 0.75 (R2 = 0.95); 1-2 µm, 0.90 (R2 = 0.93); and > 2 µm, 1.03 (R2 = 0.94). The linear slopes were used to convert Dylos counts to mass concentration, and the agreement between converted Dylos mass and Grimm mass was estimated. The absolute relative error between converted Dylos mass and the Grimm mass was smaller in the < 1 µm group (16%) and 1-2 µm group (16%) compared to the > 2 µm group (32%). Therefore, the bias between converted Dylos mass and Grimm mass varied by size group. Future studies examining particle size bins over a wider range of coarse particles (> 2.5 µm) would provide useful information for accurately converting LCPMS counts to mass concentration.

Heavy metal pollution of soils and risk assessment in Houston, Texas following Hurricane Harvey.

In August 2017, after Hurricane Harvey made landfall, almost 52 inches of rain fell during a three-day period along the Gulf Coast Region of Texas, including Harris County, where Houston is located. Harris County was heavily impacted with over 177,000 homes and buildings (approximately 12 percent of all buildings in the county) experiencing flooding. The objective of this study was to measure 13 heavy metals in soil in residential areas and to assess cancer and non-cancer risk for children and adults after floodwaters receded. Between September and November 2017, we collected 174 surface soil samples in 10 communities, which were classified as "High Environmental Impact" or "Low Environmental Impact" communities, based on a composite metric of six environmental parameters. A second campaign was conducted between May 2019 and July 2019 when additional 204 soil samples were collected. Concentrations of metals at both sampling campaigns were higher in High Environmental Impact communities than in Low Environmental Impact communities and there was little change in metal levels between the two sampling periods. The Pollution Indices of lead (Pb), zinc, copper, nickel, and manganese in High Environmental Impact communities were significantly higher than those in Low Environmental Impact communities. Further, cancer risk estimates in three communities for arsenic through soil ingestion were greater than 1 in 1,000,000. Although average soil Pb was lower than the benchmark of the United States Environmental Protection Agency, the hazard indices for non-cancer outcomes in three communities, mostly attributed to Pb, were greater than 1. Health risk estimates for children living in these communities were greater than those for adults.

RETRACTED: A study of shower aerosols and deposition of lead dust from distribution system and premise plumbing in Baltimore homes.

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