Judith C. Chow

Lithium-ion batteries (LIBs) release significant amounts of toxic, corrosive, and flammable gases when they enter thermal runaway (TR). These emissions can be hazardous to human health, damage nearby equipment, pose fire and explosion risks, and degrade air quality. This study measured concentrations for a range of hazardous gases released from TR-driven combustion of cylindrical lithium iron phosphate (LFP) and pouch-style lithium cobalt oxide (LCO) LIB cells. Gas emissions were measured by dedicated analyzers and Fourier transform infrared spectroscopic (FTIR) analysis, and emission factors were calculated. Dangerous concentrations of hydrogen fluoride (HF) were observed, reaching up to 50 ppm from the combustion of single LIB cells. Large amounts of combustible electrolyte solvents and light hydrocarbons were released in some cases, depending on cell combustion behavior. Electrolyte solvents, hydrogen chloride (HCl), and particles were released earlier than other species and should be targeted for early TR detection. Gas emissions were correlated with cell state of charge (SOC) and combustion behavior. Cells at high SOCs had higher peak concentrations of HF, HCl, CO, and flammable hydrocarbons, and these peaks happened sooner after cell failure than for low-SOC tests.

Low-cost particulate matter sensors have seen increased use for monitoring at personal and local levels due to their affordability, ease of operation, and high time resolution. However, the quality of data reported by these sensors can be questionable, and a thorough evaluation of their performance is necessary. This study evaluated the particle sizing accuracy of several commonly used optical sensors, including the Alphasense optical particle counter (OPC), TSI DustTrak DRX aerosol monitor, Plantower PMS5003 sensor, and Sensirion SPS30 sensor, using laboratory-generated monodisperse particles. The OPC and DRX agreed partially with reference instruments and showed promise in detecting coarse-size particles. However, the PMS5003 and SPS30 did not correctly size fine and coarse particles. Furthermore, their reported mass distributions do not directly correspond to their number distribution. Despite these limitations, field measurements involving a dust storm period showed that the SPS30 correlated reasonably well with reference instruments for both PM_2.5 and PM₁₀, though the regression slopes differed significantly. These findings underscore the need for caution when interpreting data from low-cost optical sensors, particularly for coarse particles. Recommendations for improving the performance of these sensors are also provided.

Lithium-ion batteries (LIB) pose a safety risk due to their high specific energy density and toxic ingredients. Fire caused by LIB thermal runaway (TR) can be catastrophic within enclosed spaces where emission ventilation or occupant evacuation is challenging or impossible. The fine smoke particles (PM_2.5) produced during a fire can deposit in deep parts of the lung and trigger various adverse health effects. This study characterizes the chemical composition of PM_2.5 released from TR-driven combustion of cylindrical lithium iron phosphate (LFP) and pouch-style lithium cobalt oxide (LCO) LIB cells. Emissions from cell venting and flaming combustion were measured in real time and captured by filter assemblies for subsequent analyses of organic and elemental carbon (OC and EC), elements, and water-soluble ions. The most abundant PM_2.5 constituents were OC, EC, phosphate (PO₄³⁻), and fluoride (F⁻), contributing 7–91%, 0.2–40%, 1–44%, and 0.7–3% to the PM_2.5 mass, respectively. While OC was more abundant during cell venting, EC and PO₄³⁻ were more abundant when flaming combustion occurred. These freshly emitted particles were acidic. Overall, particles from LFP tests had higher OM but lower EC compared to LCO tests, consistent with the higher thermal stability of LFP cells.

Real-world emission factors for different vehicle types and their contributions to roadside air pollution are needed for air-quality management. Tunnel measurements have been used to estimate emission factors for several vehicle types using linear regression or receptor-based source apportionment. However, the accuracy and uncertainties of these methods have not been sufficiently discussed. This study applies four methods to derive emission factors for different vehicle types from tunnel measurements in Hong Kong, China: (1) simple linear regressions (SLR); (2) multiple linear regressions (MLR); (3) positive matrix factorization (PMF); and (4) EMission FACtors for Hong Kong (EMFAC-HK). Separable vehicle types include those fueled by liquefied petroleum gas (LPG), gasoline, and diesel. PMF was the most useful, as it simultaneously seeks source profiles and source contributions. Diesel-, gasoline-, and LPG-fueled vehicle emissions accounted for 52%, 10%, and 5% of PM_2.5 mass, respectively, while ammonium sulfate (~20%), ammonium nitrate (6%), and road dust (7%) were also large contributors. MLR exhibited the highest relative uncertainties, typically over twice those determined by SLR. EMFAC-HK has the lowest relative uncertainties due to its assumption of a single average emission factor for each pollutant and each vehicle category under specific conditions. The relative uncertainties of SLR and PMF are comparable.

Respirable coal mine dust (RCMD) exposure is associated with black lung and silicosis diseases in underground miners. Although only RCMD mass and silica concentrations are regulated, it is possible that particle size, surface area, and other chemical constituents also contribute to its adverse health effects. This review summarizes measurement technologies for RCMD mass concentrations, morphology, size distributions, and chemical compositions, with examples from published efforts where these methods have been applied. Some state-of-the-art technologies presented in this paper have not been certified as intrinsically safe, and caution should be exerted for their use in explosive environments. RCMD mass concentrations are most often obtained by filter sampling followed by gravimetric analysis, but recent requirements for real-time monitoring by continuous personal dust monitors (CPDM) enable quicker exposure risk assessments. Emerging low-cost photometers provide an opportunity for a wider deployment of real-time exposure assessment. Particle size distributions can be determined by microscopy, cascade impactors, aerodynamic spectrometers, optical particle counters, and electrical mobility analyzers, each with unique advantages and limitations. Different filter media are required to collect integrated samples over working shifts for comprehensive chemical analysis. Teflon membrane filters are used for mass by gravimetry, elements by energy dispersive X-ray fluorescence, rare-earth elements by inductively coupled plasma-mass spectrometry and mineralogy by X-ray diffraction. Quartz fiber filters are analyzed for organic, elemental, and brown carbon by thermal/optical methods and non-polar organics by thermal desorption-gas chromatography-mass spectrometry. Polycarbonate-membrane filters are analyzed for morphology and elements by scanning electron microscopy (SEM) with energy dispersive X-ray, and quartz content by Fourier-transform infrared spectroscopy and Raman spectroscopy.

The international journal of Aerosol and Air Quality Research (AAQR) covers all aspects of aerosol science and technology, atmospheric science and air quality related issues.

Recent improvements in integrated and continuous PM2.5 mass and chemical measurements from the Supersite program and related studies in the past decade are summarized. Analytical capabilit...