Environmental science: atmospheres最新文献

The planetary boundary layer (PBL) plays a crucial role in determining meteorological fields and the diffusion of atmospheric pollutants. Therefore, accurate PBL simulation is necessary for precise meteorological and air quality simulations, and the choice of PBL scheme significantly influences the accuracy of simulation results. In this study, we investigate the seasonal and diurnal variations of typical meteorological variables over the Yangtze River Delta (YRD) region by using the Weather Research and Forecasting (WRF) model using four different closure schemes. These closure schemes include two non-local closure schemes, i.e., Yonsei University (YSU) and Asymmetric Convective Model version 2 (ACM2), as well as two local closure schemes named Mellor–Yamada–Janjic (MYJ) and Mellor–Yamada Nakanishi and Niino (MYNN). By comparing observations and model inter-comparisons, we discuss the similarities and differences in simulated results among different PBL schemes. The results indicate that local closure schemes, i.e., MYJ and MYNN, generally produce more realistic simulations of meteorological parameters. MYNN performs best in summer with a mean bias (MB) of 0.41 °C for temperature and 0.44 m s⁻¹ for wind speed, while MYJ shows better results under stable conditions during winter with a MB of 0.64 °C for temperature and −5.76% for relative humidity. YSU is found to have less bias in PBL height during summer with the highest R up to 0.81, while MYJ outperforms the three other schemes with the least MB of 38 m (R = 0.65) in winter. Each PBL closure scheme, i.e., the MYJ and MYNN local closure schemes, may not accurately capture all physical processes, leading to performance variations, especially during transitional seasons and under specific diurnal conditions. Thus, it is important to note that each scheme has its strengths and weaknesses, and the selection of the most appropriate scheme should depend on the specific variables and scenarios under consideration.

This study estimates PM_2.5 concentrations in Ouagadougou using satellite-based aerosol optical depth (AOD) and meteorological parameters such as temperature, precipitation, relative humidity, wind speed, and wind direction. First, Simple Linear Regression (SLR), Multiple Linear Regression (MLR), Decision Tree (DT), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) models were developed using the available labeled data (AOD and meteorological parameters with corresponding PM_2.5 values) in the city. The XGBoost model outperformed all other models that were used, with a coefficient of determination (R²) of 0.87 and a root-mean-square error (RMSE) of 15.8 μg m⁻³ after a five-fold cross-validation. The performance of the supervised XGBoost model was upgraded by incorporating a semi-supervised algorithm to use large amounts of unlabeled data in the city and allow for a more accurate and extensive estimation of PM_2.5 for the period 2000–2022. This semi-supervised XGBoost model had an R² of 0.97 and an RMSE of 8.3 μg m⁻³ after a five-fold cross-validation. The results indicate that the estimated 24 hour mean PM_2.5 concentrations in the city are 2 to 4 times higher than the World Health Organization (WHO) 24 hour guidelines of 15 μg m⁻³ in the rainy season and 2 to 22 times higher than the WHO 24 hour guideline in the dry season. The results also reveal that the average annual estimated PM_2.5 concentrations are 11 to 14 times higher than the WHO average annual guideline of 5 μg m⁻³. Finally, we find higher PM_2.5 concentrations in the city's center and industrial areas than in the other areas. The results indicate a need for future air pollution policy and mitigation in Burkina Faso to achieve desired health benefits such as reduced respiratory and cardiovascular problems, which will, in turn, lead to decreased PM_2.5 mortality rates.

The present long-term study has been conducted with dual objectives: firstly, to monitor the spatio-temporal variation of ambient air quality parameters and secondly, to evaluate the impact of air pollutants on the Delhi population. Five years (January 2019 to December 2023) of data of six key pollutants (PM₁₀, PM_2.5, NO₂, O₃, Benzene, and Toluene) were collected by continuous ambient air quality monitoring stations, obtained from the Central Pollution Control Board portal. The impact of air pollutants on human health was assessed using different indices and the AirQ+ model developed by the World Health Organization (WHO). Additionally, the ozone formation potential (OFP) of benzene and toluene was evaluated. The findings of the study revealed that the concentrations of PM₁₀ and PM_2.5 exceeded both national and global guidelines across all the sites throughout the study period. Notably, industrial sites were classified as the severe category according to the National Air Quality Index. At industrial sites, the OFP of volatile organic compounds (VOCs) was observed to be higher in comparison to commercial sites. The AirQ+ model analysis in the health risk assessment indicated a strong association between PM₁₀ exposure and mortality from respiratory (91.36%) and chronic bronchitis (90.85%) diseases. Additionally, long-term PM_2.5 exposure was linked to an increased risk of stroke (65%) and circulatory (63.83%) mortality.

Climate warming is projected to be particularly pronounced in the northern high latitudes coupled with reduced light availability due to increased cloudiness. The changing climate may alter the fluxes of greenhouse gases (GHGs) and atmospherically reactive trace gases, which can drive important climate feedbacks. We investigated the individual and combined effects of warming and increased cloudiness on methane (CH₄), carbon dioxide (CO₂), nitrous oxide (N₂O), nitric oxide (NO), nitrous acid (HONO) and biogenic volatile organic compound (BVOC) fluxes in mesocosms from two tundra and one palsa mire ecosystems kept under strict environmental control in climate chambers. We also examined whether and how prevailing soil physiochemical properties and plant species composition affected the fluxes. In control conditions, all sites were net sinks of CH₄ and CO₂ during both growing seasons except for the palsa site which was a net source of CO₂ in the second growing season. Warming enhanced CH₄ uptake, mostly observed in the palsa site, and turned the palsa site from a sink to a source of CO₂ in the first growing season and increased the CO₂ source strength in the second growing season. Warming increased BVOC emissions while increased cloudiness mostly decreased the emissions. The combined treatment of warming and increased cloudiness decreased CH₄ uptake, mostly observed in the palsa site, and BVOC emissions. Fluxes of CO₂ were linked to availability of soil carbon and organic matter, litter input, soil pH and bulk density, and cover of mosses. Low emissions of N₂O, NO, and HONO could mainly be explained by limited availability of mineral nitrogen. Warming-enhanced CH₄ uptake and BVOC emissions will provide a negative feedback to climate while enhanced CO₂ release from palsa mires will exacerbate global warming. Under combined warming and increased cloudiness, subarctic ecosystems may shift from sinks to sources of CH₄, providing a positive feedback to climate. Prevailing soil physiochemical properties and vegetation composition will play a significant role in controlling the fluxes, hence contributing to the overall climate change effects and feedback.

In the last few decades, atmospheric formation of secondary organic aerosols (SOA) has gained increasing attention due to their impact on air quality and climate. However, methods to predict their abundance are mainly empirical and may fail under real atmospheric conditions. In this work, a close-to-mechanistic approach allowing SOA quantification is presented, with a focus on a chain-like chemical reaction called “autoxidation”. A novel framework is employed to (a) describe the gas-phase chemistry, (b) predict the products' molecular structures and (c) explore the contribution of autoxidation chemistry on SOA formation under various conditions. As a proof of concept, the method is applied to benzene, an important anthropogenic SOA precursor. Our results suggest autoxidation to explain up to 100% of the benzene-SOA formed under low-NO_x laboratory conditions. Under atmospheric-like day-time conditions, the calculated benzene-aerosol mass continuously forms, as expected based on prior work. Additionally, a prompt increase, driven by the NO₃ radical, is predicted by the model at dawn. This increase has not yet been explored experimentally and stresses the potential for atmospheric SOA formation via secondary oxidation of benzene by O₃ and NO₃.

Global air pollution presents substantial risks to both human health and the environment. Particulate Matter (PM) adversely affects ecosystems through pollution, bioaccumulation, and endangerment of aquatic organisms. These contaminants enter water systems via precipitation and industrial runoff, damaging aquatic invertebrates through physical, physiological, and molecular mechanisms, leading to developmental issues and organ toxicity. This study investigates the combined toxicological effect of environmental exposure to polystyrene (PS) nanoparticles and varying PM concentrations from indoor and outdoor dust particles on Artemia salina. Our findings reveal noteworthy elevations in reactive oxygen species (ROS) and malondialdehyde (MDA) levels in air conditioner (AC) dust and PM_2.5 exposures, highlighting potential health risks associated with high particulate contamination. Conversely, superoxide dismutase (SOD) activity decreased, indicating harm to enzyme systems. In contrast, catalase activity (CAT) increased, suggesting a compensatory response to oxidative stress induced by Polystyrene (PS) and suspended particulate pollutants. These results underscore the severe oxidative stress experienced by marine zooplankton when exposed to PM_2.5 combined with NPs, potentially impairing growth. Further research should explore the combined toxicological effects of PM_2.5 and NPs on other marine species and investigate long-term exposure effects and bioaccumulation pathways. Understanding these dynamics is crucial for developing effective strategies to mitigate NP pollution and protect human health and aquatic ecosystems.

We would like to take this opportunity to thank all of Environmental Science: Atmospheres’s reviewers for helping to preserve quality and integrity in chemical science literature. We would also like to highlight the Outstanding Reviewers for Environmental Science: Atmospheres in 2023.

Mercury (Hg) is a threat to the environment and human health. As a consequence, the Minamata Convention on Mercury was adopted in 2013 to reduce Hg pollution by curbing anthropogenic emissions. Analysis of gaseous elemental Hg (Hg⁰) concentration trends in the atmosphere has been identified as a cost-effective means to evaluate progress on reducing Hg pollution. Therefore, spatial coverage of atmospheric Hg⁰ concentration measurements should be expanded. We established an atmospheric Hg⁰ concentration monitoring network with 22 sites across Switzerland, using the Mercury Passive Air Sampler (MerPAS®). The mean annual atmospheric Hg⁰ concentration in Switzerland was 1.34 ± 0.20 ng m⁻³ (August 22, 2022 – September 21, 2023), similar to current observations at European air monitoring stations. Mean atmospheric Hg⁰ concentrations were significantly lower at rural stations (1.25 ± 0.11 ng m⁻³) than at urban (1.37 ± 0.14 ng m⁻³) stations (Mann-Whitney U-test, p < 0.01). This concentration difference can be explained by more local Hg emissions at urban sites (e.g., by fuel combustion) throughout the year as well as by more pronounced stomatal Hg⁰ uptake at rural sites during spring and summer. We recommend continuing the Swiss Atmospheric Mercury Network to support the call from the Minamata Convention to monitor atmospheric Hg⁰ as a control on whether international efforts are successful in reducing Hg in the environment. Longer term records from such monitoring networks will also help improve the understanding of both regional and global Hg cycles.

Our work on aerosol–cloud–radiation interactions became hamstrung by the lack of a suitable aerosol and cloud microphysics equipped aircraft in Australia. To address this infrastructure gap, we have established a new airborne research platform, designed primarily for Marine Cloud Brightening (MCB) field studies but with broader applicability across diverse airborne research domains. This platform, comprising a Cessna 337 aircraft was outfitted with a comprehensive suite of meteorological, aerosol, and cloud microphysical instrumentation normally only found on much larger aircrafts. The aircraft has completed its first field deployment over the Great Barrier Reef (GBR) supporting the Reef Restoration and Adaptation Program. Here we present details of the platform configuration, a flight summary of its first campaign and a case study illustrating the capabilities of the new platform. In the case study presented, data was collected from two well-developed cumulus cloud cells which were similar in macrophysical properties but formed under markedly different aerosol regimes. We observed a strong difference in cloud microphysical properties. Higher aerosol concentrations led to more numerous and smaller cloud drops and suppressed warm rain. Our observations are consistent with the hypothesis that cumulus clouds, dominant over the GBR during summer, are amenable to marine cloud brightening. Our results demonstrate the practical utility of the new research aircraft through a focused case study, laying the groundwork for future scientific investigations of aerosol–cloud interactions.