Environmental science: atmospheres最新文献

Wildfires are a major source of aerosols during summer in the western United States. Aerosols emitted from wildfires could significantly affect air quality, human health, and the global climate. This study conducted a comparison of aerosol characteristics during wildfire smoke-influenced and non-smoke-influenced days. Ambient particle size distribution (PSD) data were collected in Reno, Nevada, between July 2017 and October 2020. During this period, the site was impacted by smoke from over a hundred wildfires burning in a wide range of ecosystems in the western United States located at different distances from the measurement site. The smoke-influenced days were identified using satellite images, a hazard mapping system, and wind back-trajectory. Positive matrix factorization (PMF) was applied to identify the main sources and their characteristics. The wildfire aerosols were observed to have a number mode diameter of 212 nm, which is significantly larger than aerosols on non-smoke-influenced days (61 nm). In addition to the increase in particle size, wildfires made a large contribution to PM_2.5 and CO concentrations. During fire-prone months (July, August, and September) from 2016 to 2021, 56% to 65% of PM_2.5 and 18% to 26% of CO concentrations could be attributed to wildfire emissions in the study area. On an annual basis, wildfire emissions were responsible for 35% to 47% of PM_2.5 concentrations and 5% to 12% of CO concentrations.

Correction for ‘Numerical one-dimensional investigations on a multi-cylinder spark ignition engine using hydrogen/ethanol, hydrogen/methanol and gasoline in dual fuel mode’ by Ufaith Qadiri, Environ. Sci.: Atmos., 2024, 4, 233–242, https://doi.org/10.1039/D3EA00139C.

Atmospheric oxidation largely determines the abundance and lifetime of short-lived climate forcers like methane, ozone and aerosols, as well as the removal of pollutants from the atmosphere. Hydroxyl, nitrate and chlorine radicals (OH, NO₃ and Cl), together with ozone (O₃), are the main atmospheric oxidants. Short-lived halogens (SLH) affect the concentrations of these oxidants, either through direct chemical reactions or indirectly by perturbing their main sources and sinks. However, the effect of SLH on the combined abundance of global oxidants during historical periods remains unquantified and is not accounted for in air quality and climate models. Here, we employ a state-of-the-art chemistry-climate model to comprehensively assess the role of SLH on atmospheric oxidation under both pre-industrial (PI) and present-day (PD) conditions. Our results show a substantial reduction in present-day atmospheric oxidation caused by the SLH-driven combined reduction in the global boundary layer levels of OH (16%), NO₃ (38%) and ozone (26%), which is not compensated by the pronounced increase in Cl (2632%). These global differences in atmospheric oxidants show large spatial heterogeneity due to the variability in SLH emissions and their nonlinear chemical interactions with anthropogenic pollution. Remarkably, we find that the effect of SLH was more pronounced in the pristine PI atmosphere, where a quarter (OH: -25%) and half (NO₃: -49%) of the boundary layer concentration of the main daytime and nighttime atmospheric oxidants, respectively, were controlled by SLH chemistry. The lack of inclusion of the substantial SLH-mediated reduction in global atmospheric oxidation in models may lead to significant errors in calculations of atmospheric oxidation capacity, and the concentrations and trends of short-lived climate forcers and pollutants, both historically and at present.

PM_2.5 (particulate matter with an aerodynamic diameter of less than 2.5 μm) exposure at elevated levels has been associated with adverse health outcomes. However, the high spatiotemporal variability of aerosols poses challenges in monitoring PM_2.5 using ground-based measurement networks. Previously, we developed a new method (referred to as HSRL-CH) to estimate surface PM_2.5 concentration and chemical composition using High Spectral Resolution Lidar (HSRL)-retrieved extinction and derived aerosol types. In this study, we evaluate HSRL-CH performance across the United States using HSRL retrievals from five campaigns: DISCOVER-AQ California, SEAC⁴RS, DISCOVER-AQ Texas, DISCOVER-AQ Colorado, and ACEPOL. We assess the remotely derived PM_2.5 estimates against measurements from the EPA Air Quality System (AQS) and compare HSRL-CH-derived aerosol chemical compositions with AQS-measured compositions. Across all campaigns, HSRL-CH-derived PM_2.5 shows a mean absolute error (MAE) of 10.2 μg m⁻³. The DISCOVER-AQ California campaign had the highest MAE (14.8 μg m⁻³), while other campaigns had MAE ≤ 7.2 μg m⁻³. The lowest MAE occurs when dusty mix type aerosols dominate the retrieved aerosol optical depth, while the highest MAE is associated with smoke type aerosols. Different planetary boundary layer height estimates can lead to a 20% difference in MAE. We anticipate that the HSRL-CH method will provide reliable estimates of PM_2.5 concentration and chemical composition once satellite-based HSRL data acquisition becomes feasible.

Urban street trees can affect air pollutant concentrations by reducing ventilation rates in polluted street canyons (increasing concentrations), or by providing surface area for deposition (decreasing concentrations). This paper examines these effects in Rotterdam, the Netherlands, using mobile measurements of nitrogen dioxide (NO₂), particulate matter (PM), black carbon (BC), and ultrafine particulate matter (UFP). The effect of trees is accounted for in regulatory dispersion models (https://www.cimlk.nl) by the application of an empirically determined tree factor, dependent on the existence and density of the tree canopy, to concentrations due to traffic emissions. Here, we examine the effect of street trees on different pollutants using street-level mobile measurements in a detailed case study (repeated measurements of several neighboring streets) and a larger statistical analysis of measurements across the urban core of Rotterdam. We find that in the summertime, when trees are fully leafed-out, the major short-lived traffic-related pollutants of NO₂ and BC have higher concentrations in streets with higher traffic and greater tree cover, while PM_2.5 has slightly lower concentrations in streets with higher tree factor. UFP shows a less clear, but decreasing trend with tree factor. In low-traffic streets and in wintertime (fewer leaves on trees) measurements confirm the importance of leaves to pollutant trapping by trees, by finding no enhancement of NO₂ and BC with increasing tree cover, rather a slightly decreasing trend in pollutant concentrations with tree factor. Our observations are consistent with the dominant effect of (leafed-out) trees being to trap traffic-emitted pollutants at the surface, but that PM_2.5 in street canyons is more often added by transport from outside the street, which can be attenuated by tree cover. Overall, these measurements emphasize that both traffic-emitted and regional sources are important factors that determine air quality in Rotterdam streets, making the effect of street trees different for different pollutants and different seasons.

Correction for ‘Assessing conditions favoring the survival of African dust-borne microorganisms during long-range transport across the tropical Atlantic’ by Ali Hossein Mardi et al., Environ. Sci.: Atmos., 2025, https://doi.org/10.1039/d4ea00093e.

The proportion of ice crystals in clouds can affect cloud albedo and lifetime, impacting the Earth's radiative budget. Ice nucleating particles (INPs) lower the energy barrier of ice nucleation and thus facilitate primary ice formation in the atmosphere. Atmospheric nanoplastics (NPs) have been detected in remote regions far from emission sources, suggesting that they can become airborne and undergo long-range transport in the atmosphere. During the atmospheric residence of NPs, they could catalyse primary ice crystal formation by acting as INPs. In this study, we present results from laboratory experiments in which model NPs composed of polystyrene and polyacrylonitrile were tested for their ice-nucleating ability using the horizontal ice nucleation chamber (HINC) as a function of ice-nucleation temperature and water saturation ratio. The results showed that NPs can be effective INPs under both cirrus and cold mixed-phase cloud conditions. The surface characteristics and wettability of the NPs were analysed via scanning electron images and dynamic vapour sorption measurements, which revealed the freezing mechanism as a combination of deposition nucleation and pore condensation and freezing. The results highlight the need to enumerate and characterise NPs in the atmosphere, given their potential to get scavenged by clouds via primary ice formation in clouds.

The submicron aerosol number size distribution significantly impacts human health, air quality, weather, and climate. However, its measurement requires sophisticated and expensive instrumentation that demands substantial maintenance efforts, leading to limited data availability. To tackle this challenge, we developed estimation models using advanced deep learning algorithms to estimate the aerosol number size distribution based on trace gas concentrations, meteorological parameters, and total aerosol number concentration. These models were trained and validated with 15 years of ambient data from three distinct environments, and data from a fourth station were exclusively used for testing. Our estimative models successfully replicated the trends in the test data, capturing the temporal variations of particles ranging from approximately 10–500 nm, and accurately deriving total number, surface area, and mass concentrations. The model's accuracy for particles below 75 nm is limited without the inclusion of total particle number concentration as training input, highlighting the importance of this parameter for capturing the dynamics of smaller particles. The reliance on total particle number concentration, a parameter not routinely measured at all in air quality monitoring sites, as a key input for accurate estimation of smaller particles presents a practical challenge for broader application of the models. Our models demonstrated a robust generalization capability, offering valuable data for health assessments, regional pollution studies, and climate modeling. The estimation models developed in this work are representative of ambient conditions in Finland, but the methodology in general can be applied in broader regions.

The interface of the oceans and aqueous aerosols with air drives many important physical and chemical processes in the environment, including the uptake of CO₂ by the oceans. Transport across and reactions at the ocean–air boundary are in large part determined by the chemical composition of the interface, i.e., the first few nanometers into the ocean. The main constituents of the interface, besides water molecules, are dissolved ions and amphiphilic surfactants, which are ubiquitous in nature. We have used a combination of surface tension measurements and liquid-jet X-ray photoelectron spectroscopy to investigate model seawater solutions at realistic ocean-water ion concentrations in the absence and in the presence of model surfactants. Our investigations provide a quantitative picture of the enhancement or reduction of the concentration of ions due to the presence of charged surfactants at the interface. We have also directly determined the concentration of surfactants at the interface, which is related to the ionic strength of the solution (i.e., the “salting out” effect). Our results show that the interaction of ions and surfactants can strongly change the concentration of both classes of species at aqueous solution–air interfaces, with direct consequences for heterogeneous reactions as well as gas uptake and release at ocean–air interfaces.

Carbonaceous aerosol particles are associated with large uncertainties in their climate impacts because of incomplete knowledge of their optical properties and emission magnitudes. Biomass-burning sources significantly contribute to carbonaceous aerosol emissions in India, with crop residue burning being crucial during post-harvest months. Here, for the first time, we study the chemical and optical properties of emission aerosols using in situ real-time and filter-based measurements from significantly contributing crop residue straws, stalks, and stems in India. Emitted particles exhibited optical behaviour characteristic of the brown-black carbon absorption continuum, with large mass absorption cross-sections (MAC₅₂₀: 8.2 ± 9.6 m² g⁻¹) and small absorption Angström exponents (AAE_370/660: 1.97 ± 0.81). They contain significant amounts of lower volatility organic (OC_LV) and elemental carbon fractions. The relative abundances of OC_LV correlate positively with MAC₅₂₀ and negatively with AAE_370/660, implying significant absorption exerted by OC_LV, with likely atmospheric persistence. Additionally, we measured emission factors for a complete list of particulate chemical constituents. Emission factors of elemental carbon are larger than those in earlier studies, indicating a 1.6–3.8 times increase in the climate warming potential of the emitted particles from crop residue burning. The intrinsic property measurements and the emissions estimates made here can aid climate modelling efforts that underestimate aerosol absorption in the region.