Journal of Geophysical Research: Atmospheres最新文献

After reading with careful attention the recently published article entitled “Do Microplastics Contribute to the Total Number Concentration of Ice Nucleating Particles?” (Tatsii et al., 2025, https://doi.org/10.1029/2024jd042827), improper assumptions were noticed. Whereas the simulation methodology is not questioned, the input data is simply wrong: emissions of tyre wear and brake wear particles were taken together with polymer contents in road markings (RM) and in polymer-modified bitumen. The polymer contents in organic-inorganic mixtures do not imply their emissions as microplastic. These are two different parameters that cannot be used interchangeably. In this commentary plentiful references from field and laboratory studies are provided that demonstrate significant overestimate of the total emissions and the relative contributions.

This reply addresses the comment by T. Burghardt, ‘Microplastic emissions and polymer contents are not the same: regarding a confusion in Tatsii et al. “Do Microplastics Contribute to the Total Number Concentration of Ice Nucleating Particles?’”, on the paper by Tatsii et al. (2025), https://doi.org/10.1029/2024jd042827. The original study quantified road traffic-related microplastic number concentrations and estimated their contribution to total ice nucleating particle concentrations using an atmospheric transport model. In this reply, we clarify raised concerns related to the estimation of microplastic emissions from road markings and polymer-modified bitumen. We further elaborate on the methodology and objectives of our study to resolve the identified misunderstanding. The main conclusion is that applying the emission constraints for road markings and polymer-modified bitumen proposed by T. Burghardt, values that are one order of magnitude lower than those used in the original study, has a negligible impact on the reported results, as these sources represent a relatively small fraction of the total emissions.

The radioisotope ³⁶Cl was produced prolifically by nuclear weapons testing, principally at Bikini and Enewetak Atolls in the 1950s. Much of this was injected into the stratosphere, from where it was dispersed worldwide. The fallout of this bomb-produced ³⁶Cl has been measured as a function of time in an ice core from a high-accumulation site in Antarctica. These measurements complement an earlier study in an Arctic ice core. A box model has been developed to describe simultaneously the data from both the two sites. Using an up-to-date catalog, the ³⁶Cl production of the individual tests has been estimated and used as input to the box model. Production is dominated by high-yield thermonuclear tests carried out on barges moored in the lagoons of the atolls in the 1950s. Exchange times of 3.7 years for gaseous exchange between stratosphere and troposphere and 4.2 years for gaseous exchange between the stratospheres of the two hemispheres are deduced. The ³⁶Cl bomb pulse constitutes a global tracer with an input function that is well-defined in space and time, and its exchange between stratosphere and troposphere is dominated by one-way transport due to its rapid removal once in the troposphere. This latter behavior greatly simplifies the interpretation of the data in terms of an exchange time relative to the ¹⁴C bomb pulse. The stratosphere-troposphere exchange time derived here from the bomb-produced ³⁶Cl offers an independent constraint on the flux of ozone between stratosphere and troposphere which agrees well with other more direct estimates.

Lakes are a critical component of the terrestrial hydrological cycle, yet their sensitivity to future climate warming—especially in terms of evaporation ($��E�$)—remains insufficiently understood. Here, we use the Lake, Ice, Snow, and Sediment Simulator within the Community Land Model to project the responses of global lake $��E�$ to a warming climate under a high-emissions scenario (RCP8.5) by the end of the 21st century. Simulations reveal a global mean increase of 13% in lake $��E�$, with the largest absolute increases occurring in low- and mid-latitude regions, driven by enhanced energy availability. In contrast, high-latitude lakes exhibit the greatest relative increases due to reduced snow and ice cover, leading to lower albedo and higher solar absorption. By analyzing changes in long-term mean and interannual variability, we identify regional hotspots of $��E�$ sensitivity, which are concentrated in polar regions such as Greenland, Alaska, and Northern Europe. These hotspots do not always align with areas of the greatest absolute $��E�$ increases, underscoring the need for lake-specific assessments of climate vulnerability. Using the Geographical Detector Model, we show that vapor pressure deficit (VPD) is the dominant individual driver of hotspot patterns. Moreover, strong synergistic interactions among VPD, radiation and wind speed reveal that $��E�$ responses are governed by the combined influence of radiative and atmospheric drivers, rather than by individual factors alone. Our findings highlight the importance of accounting for both surface energy balance changes and compound climate drivers when assessing the sensitivity of inland waters to global warming.

Redox-active metals are key toxic components of ambient PM_2.5 that may pose significant health risks through oxidative stress, yet their environmental behavior and bioavailability under varying atmospheric conditions remain insufficiently understood. This study investigated the concentrations, sources, and water solubility of three major redox-active metals (Fe, Cu, Mn) in PM_2.5 collected in urban Xi'an before and during the COVID-19 pandemic restrictions. Results showed that Fe was the most abundant metal but exhibited low solubility (<10%), while Cu and Mn showed higher solubility, with average values exceeding 40% across all periods except the winter during the pandemic restrictions. Source apportionment indicated that dust was the important Fe source, whereas Cu and Mn mainly originated from traffic-related and combustion emissions. During pandemic restrictions, total metal concentrations increased by 20%–35%, yet metal solubility significantly decreased, particularly in winter, coinciding with a significant rise in aerosol pH (from ∼3 to 5.38). Multiple linear regression analysis suggested that pH was the main factor affecting the variations of Cu and Mn solubility, while Fe solubility was more strongly associated with emission sources. Notably, the results suggest that combustion sources exhibited a dual role by directly emitting more soluble metal species and indirectly enhancing solubility via acid precursor emissions that lowered aerosol pH. These findings highlight that, beyond emission reductions, aerosol pH regulation is also critical for mitigating the bioavailability of toxic metals. Therefore, effective air quality management in urban environments should integrate source control with aerosol acidity regulation to reduce the bioavailability of PM_2.5-bound redox-active metals.

Convective downdrafts are a crucial part of convective systems and can cause local damage by generating severe surface gusts. However, fully representing the mechanisms behind strong downdrafts and gusts in models remains difficult. We conducted short-duration regional simulations using a nested downscaling approach with the Weather Research and Forecasting model including a cloud-resolving innermost subregion at various grid spacings down to 200-m. The model generated a strong gust event characterized by a pronounced, coherent downdraft that we used to study the forcing mechanisms. The 1-km simulation underestimated the downdraft and 5-km didn't represent it at all. In addition, the 1-km simulated weaker downdrafts exhibited a vertical momentum budget different to that of the 200-m simulation. The perturbation pressure vertical gradient and thermal buoyancy are the main contributors to the downdraft acceleration in the 200-m simulation, with condensate loading playing a less significant role than other processes at mid and low levels. Coarser resolutions underestimate the role of perturbation pressure, resulting in a smaller contribution to downward acceleration compared to thermal buoyancy and condensate loading. This highlights the potential importance of the spatial distribution of downdraft forcing mechanisms as a key consideration for why coarser grid spacings may fail to adequately capture more realistic downdrafts. The findings presented here are relevant for risk assessment applications and parameterizations of downdrafts, demonstrating benefits of large-eddy simulations (LES) for wind hazard analysis and highlighting the need for care when interpreting results from coarser models.

The detection capability of the global infrasound International Monitoring System (IMS) deployed to monitor compliance with the Comprehensive Nuclear-Test-Ban Treaty is highly variable in space and time. Previous studies estimated the source energy of near-surface explosions from remote observations using empirical yield-scaling relations. However, these relations simplify the complexities of infrasound propagation. In order to reduce the variance in the predicted wave attenuation, massive numerical propagation simulations are carried out by exploring a wide range of realistic atmospheric scenarios. An analytical expression is proposed to model transmission losses at distances up to 4,000 km. This attenuation relation is validated using multi-year near- and far-field records of volcanic eruptions from Mount Etna, Italy, as a benchmark. An idealized explosive source model is combined with transmission loss and measured noise statistics to quantify the 90% probability detection threshold of the IMS network. This approach yields high-resolution detection capability simulation results with limited computational resources. Simulations predict that explosions equivalent to $��\sim �$500 t of TNT equivalent would be detected by at least two stations at any time of the year, with the detection capability being best during the solstice periods. Due to the high spatio-temporal variability of the winds in the ground-to-stratosphere levels, threshold variations can reach one order of magnitude from seasonal down to semi-diurnal scales.

Cold winters in Eurasia considerably affect transportation, agriculture, energy, and public health. This study utilizes 31 global climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and 33 CMIP5 models to evaluate the historical surface air temperature, sea level pressure, 500-hPa geopotential height, 150-hPa meridional and zonal wind, and polar vortex indices during cold winters. Our research quantifies the advancements of CMIP6 over CMIP5. Additionally, future changes in these variables under three different Shared Socioeconomic Pathways (SSPs), that is, SSP 1–2.6, SSP 2–4.5, and SSP 5–8.5, are projected based on 20 out of the 31 CMIP6 models. The results indicate that the multimodel ensemble means from both CMIP5 and CMIP6 effectively capture the main features of the observed Eurasian cold winters and their associated factors with good simulation agreement. The CMIP6 ensemble mean outperforms its CMIP5 counterpart, and both ensemble means (CMIP5 and CMIP6) perform better than individual CMIP6 models. Among CMIP6 models, 500-hPa geopotential height achieves the highest simulation skill, whereas sea level pressure shows the lowest. Compared with same-institute models from CMIP5, CMIP6 models show overall improvements with sea level pressure simulation being notably advanced. Under the three SSPs, the occurrence probability of cold winters is projected to decrease as the area and intensity indices of the polar vortex decline. Moreover, surface temperature anomalies are projected to exhibit a “warm Arctic and cold Eurasia” pattern, and the anticyclonic anomalies at 500 hPa and 150 hPa are projected to be centered at high latitudes.

This study examines the individual and combined impacts of aerosol-radiation interactions (ARI) and aerosol-photolysis interactions (API) on regional air quality over India using the WRF-Chem model for May 2018. Model performance was validated against CERES, MERRA-2, and CPCB observations, demonstrating good agreement in simulating key meteorological variables and air pollutants. Results show that ARI increases mean PM_2.5 concentrations by approximately 3 μg/m³ (12.4%) across India by reducing surface shortwave radiation and enhancing atmospheric stability, which limits pollutant dispersion. In contrast, API reduces PM_2.5 by about 1.8 μg/m³ (7.2%) due to lower photolysis rates, which suppress secondary aerosol formation. When combined, ARI and API lead to a net PM_2.5 increase of around 2 μg/m³ (8.4%). Simultaneously, surface O₃ levels decrease under all scenarios: by 2.6 ppbv (4%) with ARI, 1.7 ppbv (2.6%) with API, and 1.2 ppbv (1.8%) when both effects are included. These results underscore the complex interplay between aerosols, atmospheric stability, and chemical processes. They highlight the need for integrated air quality strategies that account for both direct emissions and feedback effects from aerosol interactions, especially in regions with diverse emission sources like India.