Low-cost particulate matter (PM) sensors are becoming increasingly common in community monitoring and atmospheric research, but these sensors require proper calibration to provide accurate reporting. Here, we propose a hygroscopic growth calibration scheme that evolves in time to account for seasonal changes in hygroscopic growth. In San Francisco and Los Angeles, CA, applying a seasonal hygroscopic growth calibration can account for sensor biases driven by the seasonal cycles in PM composition.

NO_x is a precursor to hazardous tropospheric ozone and can be emitted from various anthropogenic sources. It is important to quantify NO_x emissions in urban environments to improve the local air quality, which still remains a challenge, as sources are heterogeneous in space and time. In this study, we calculate NO_x emissions over Los Angeles, based on aircraft measurements in June 2021, and compare them to a local emission inventory, which we find mostly overpredicts the measured values.

The San Joaquin Valley is an agricultural area with poor air quality. Organic gases drive the formation of hazardous air pollutants. Agricultural emissions of these gases are not well understood and have rarely been quantified at landscape scale. By combining aircraft-based emission measurements with land cover information, we found mis- or unrepresented emission sources. Our results help in understanding of pollution sources and in improving predictions of air quality in agricultural regions.

Nitrogen oxide (NO_x) is a hazardous air pollutant, and it is the precursor of short-lived climate forcers like tropospheric ozone and aerosol particles. While NO_x emissions from transportation has been strictly regulated, soil NO_x emissions are overlooked. We use the airborne flux measurements to observe NO_x emissions from highways and urban and cultivated soil land cover types. We show non-negligible soil NO_x emissions, which are significantly underestimated in current model simulations.

Models are essential to diagnose the significant effects of nitrogen oxides (NO_x) on air pollution. We use an air quality model to illustrate the variability of NO_x resolution-dependent simulation biases; how these biases depend on specific chemical environments, driving mechanisms, and vertical variabilities; and how these biases affect the interpretation of satellite observations. High-resolution simulations are thus critical to accurately interpret NO_x and its relevance to air quality.

We have rigorously characterized different sources of error in satellite-based HCHO / NO₂ tropospheric columns, a widely used metric for diagnosing near-surface ozone sensitivity. Specifically, the errors were categorized/quantified into (i) an inherent chemistry error, (ii) the decoupled relationship between columns and the near-surface concentration, (iii) the spatial representativeness error of ground satellite pixels, and (iv) the satellite retrieval errors.

NO_x in the free troposphere (above 2 km) affects global tropospheric chemistry and the retrieval and interpretation of satellite NO₂ measurements. We evaluate free tropospheric NO_x in global atmospheric chemistry models and find that recycling NO_x from its reservoirs over the oceans is faster than that simulated in the models, resulting in increases in simulated tropospheric ozone and OH. Over the U.S., free tropospheric NO₂ contributes the majority of the tropospheric NO₂ column in summer.

We develop a novel method for finding heavy-duty vehicle (HDV) emission factors (g PM kg fuel) using regulatory sensor networks and publicly available traffic data. We find that particulate matter emission factors have decreased by a factor of ~ 9 in the past decade in the San Francisco Bay area. Because of the wide availability of similar data sets across the USA and globally, this method could be applied to other settings to understand long-term trends and regional differences in HDV emissions.

Smoke plumes are chemically complex. This work combines airborne observations of smoke plume composition with a photochemical model to probe the production of ozone and the fate of reactive gases in the outflow of a large wildfire. Model–measurement comparisons illustrate how uncertain emissions and chemical processes propagate into simulated chemical evolution. Results provide insight into how this system responds to perturbations, which can help guide future observation and modeling efforts.

On-road emissions are thought to vary widely from existing predictions, as the effects of the age of the vehicle fleet, the performance of emission control systems, and variations in speed are difficult to assess under ambient driving conditions. We present an observational approach to characterize on-road emissions and show that the method is consistent with other approaches to within ~ 3 %.

Particle-phase nitrates are an important component of atmospheric aerosols and chemistry. In this paper, we systematically explore the application of aerosol mass spectrometry (AMS) to quantify the organic and inorganic nitrate fractions of aerosols in the atmosphere. While AMS has been used for a decade to quantify nitrates, methods are not standardized. We make recommendations for a more universal approach based on this analysis of a large range of field and laboratory observations.

This work builds a high-resolution estimate (500 m) of gross primary productivity (GPP) over the US using satellite measurements of solar-induced chlorophyll fluorescence (SIF) from the TROPOspheric Monitoring Instrument (TROPOMI) between 2018 and 2020. We identify ecosystem-specific scaling factors for estimating gross primary productivity (GPP) from TROPOMI SIF. Extreme precipitation events drive four regional GPP anomalies that account for 28 % of year-to-year GPP differences across the US.

We describe direct estimates of NO_x emissions and lifetimes for biomass burning plumes using daily TROPOMI retrievals of NO₂. Satellite-derived NO_x emission factors are consistent with those from in situ measurements. We observe decreasing NO_x lifetime with fire intensity, which is due to the increase in NO_x abundance and radical production. Our findings suggest promise for applying space-based observations to track the emissions and chemical evolution of reactive nitrogen from wildfires.

The use of a dense network of low-cost CO₂ sensors is an attractive option for measuring CO₂ emissions in cities. However, these low-cost sensors are also subject to uncertainties. Here, we describe a novel method of field calibration for correcting temperature-related errors in the CO₂ sensors deployed in the BEACO₂N network. We show that with this temperature correction, we can achieve a sufficiently low network error to allow for the evaluation of CO₂ emissions at a neighborhood scale.

Observations of winds in the planetary boundary layer remain sparse, making it challenging to simulate and predict the atmospheric conditions that are most important for describing and predicting urban air quality. Here we investigate the application of data assimilation of NO₂ columns as will be observed from geostationary orbit to improve predictions and retrospective analysis of wind fields in the boundary layer.