Search Results (10)

Long-term (1982–2019) satellite climate data records (CDRs) of aerosols and clouds, reanalysis data of meteorological fields, and machine learning techniques are used to study the aerosol effect on deep convective clouds (DCCs) over the global oceans from a climatological perspective. Our analyses are focused on three latitude belts where DCCs appear more frequently in the climatology: the northern middle latitude (NML), tropical latitude (TRL), and southern middle latitude (SML). It was found that the aerosol effect on marine DCCs may be detected only in NML from long-term averaged satellite aerosol and cloud observations. Specifically, cloud particle size is more susceptible to the aerosol effect compared to other cloud micro-physical variables (e.g., cloud optical depth). The signature of the aerosol effect on DCCs can be easily obscured by meteorological covariances for cloud macro-physical variables, such as cloud cover and cloud top temperature (CTT). From a machine learning analysis, we found that the primary aerosol effect (i.e., the aerosol effect without meteorological feedbacks and covariances) can partially explain the aerosol convective invigoration in CTT and that meteorological feedbacks and covariances need to be included to accurately capture the aerosol convective invigoration. From our singular value decomposition (SVD) analysis, we found the aerosol effects in the three leading principal components (PCs) may explain about one third of the variance of satellite-observed cloud variables and significant positive or negative trends are only observed in the lead PC1 of cloud and aerosol variables. The lead PC1 component is an effective mode for detecting the aerosol effect on DCCs. Our results are valuable for the evaluation and improvement of aerosol-cloud interactions in the long-term climate simulations of global climate models. Full article

Urban forests play a crucial role in both emitting and absorbing atmospheric pollutants. Understanding the ecological processes of biogenic volatile organic compounds (BVOCs) and secondary organic aerosols (SOAs) and their interactions in urban forests can help to assess how they influence air quality. Additionally, exploring the adaptation and feedback mechanisms between urban forests and their surrounding environments can identify new pollutants and potential risks in urban forests. However, the relationship between BVOC emissions and SOA formation is complex due to the influence of meteorological conditions, photochemical reactions, and other factors. This complexity makes it challenging to accurately describe this relationship. In this study, we used time-of-flight mass spectrometry and aerosol particle size spectrometry to monitor concentrations of BVOCs and particulate matter with a diameter less than 1 µm (PM₁; representing SOAs) at a frequency of 10–12 times per min in an urban forest near Shanghai. We then analyzed the temporal changes in concentrations of BVOCs, SOAs, and other chemical pollutants in different periods of the day by using subsequence clustering and causal inference methods. The results showed that after using this method for diurnal segmentation, PM₁ prediction accuracy was improved by 26.77%–47.51%, and the interaction rules of BVOCs and SOAs had sequential interaction characteristics. During the day, BVOCs are an important source of SOAs and have a negative feedback relationship with O₃. From night to early morning, BVOCs have a positive, balanced relationship with O₃, SOAs are affected by wind speed or deposition, BVOCs have no obvious relationship with O₃, and SOAs are affected by temperature or humidity. This study is the first to apply Toeplitz inverse covariance-based clustering and causal inference methods for the high-frequency monitoring of BVOCs and SOAs, revealing the temporal effects and characteristics of BVOCs and SOAs and providing a scientific basis and new methods for understanding the dynamic effects of urban forest communities on the environment. Full article

Emissions of immense amounts of desert dust into the atmosphere, spreading over vast geographical areas, are in direct feedback relation with ongoing global climate changes. An extreme large-scale Saharan dust episode occurred over Mediterranean and Europe in April 2019, driven by a dynamic blocking synoptic pattern (omega block) creating conditions for a powerful northeastward circulation of air masses rich in dust and moisture. Here, we study and characterize the effects of related dust intrusion over Sofia, Bulgaria, using lidar remote sensing combined with in situ measurements, satellite imagery, and modeling data. Optical and microphysical parameters of the desert aerosols were obtained and vertically profiled, namely, backscatter coefficients and backscatter-related Ångström exponents, as well as statistical distributions of the latter as qualitative analogs of the actual particle size distributions. Dynamical and topological features of the dust-dominated aerosol layers were determined. Height profiles of the aerosol/dust mass concentration were obtained by synergistic combining and calibrating lidar and in situ data. The comparison of the retrieved mass concentration profiles with the dust modeling ones shows a satisfactory compliance. The local meteorological conditions and the aerosol composition and structure of the troposphere above Sofia during the dust event were seriously affected by the desert air masses. Full article

In this study, we investigated the impact of wildfires on meteorology and air quality (PM_2.5 and O₃) over the western United States during the September 2017 period. This is done by using Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to simulate scenarios with wildfires (base case) and without wildfires (sensitivity case). Our analysis performed during the first half of September 2017 (when wildfire activity was more intense) reveals a reduction in modelled daytime average shortwave surface downward radiation especially in locations close to wildfires by up to 50 W m⁻², thus resulting in the reduction of the diurnal average surface temperature by up to 0.5 °C and the planetary boundary layer height by up to 50 m. These changes are mainly attributed to aerosol-meteorology feedbacks that affect radiation and clouds. The model results also show mostly enhancements for diurnally averaged cloud optical depth (COD) by up to 10 units in the northern domain due to the wildfire-related air quality. These changes occur mostly in response to aerosol–cloud interactions. Analysis of the impact of wildfires on chemical species shows large changes in daily mean PM_2.5 concentrations (exceeding by 200 μg m⁻³ in locations close to wildfires). The 24 h average surface ozone mixing ratios also increase in response to wildfires by up to 15 ppbv. The results show that the changes in PM_2.5 and ozone occur not just due to wildfire emissions directly but also in response to changes in meteorology, indicating the importance of including aerosol-meteorology feedbacks, especially during poor air quality events. Full article

Aerosols can interact with other meteorological variables in the air via aerosol–radiation or aerosol–cloud interactions (ARIs/ACIs), thus affecting the concentrations of particle pollutants and ozone. The online-coupled model WRF-Chem was applied to simulate the changes in the PM_2.5 (particulate matter less than 2.5 μm in aerodynamic diameter) and ozone concentrations that are caused by these mechanisms in China by conducting three parallel sensitivity tests. In each case, availabilities of aerosol–radiation interactions and aerosol–cloud interactions were set differently in order to distinguish each pathway. Partial correlation coefficients were also analyzed using statistical tools. As suggested by the results, the ARIs reduced ground air temperature, wind speed, and planetary boundary height while increasing relative humidity in most places. Consequently, the ozone concentration in the corresponding region declined by 4%, with a rise in the local annual mean PM_2.5 concentration by approximately 12 μm/m³. The positive feedback of the PM_2.5 concentration via ACIs was also found in some city clusters across China, despite the overall enhancement value via ACIs being merely around a quarter to half that via ARIs. The change in ozone concentration via ACIs exhibited different trends. The ozone concentration level increased via ACIs, which can be attributed to the drier air in the south and the diminished solar radiation that is received in central and northern China. The correlation coefficient suggests that the suppression in the planetary boundary layer is the most significant factor for the increase in PM_2.5 followed by the rise in moisture required for hygroscopic growth. Ozone showed a significant correlation with NO₂, while oxidation rates and radiation variance were also shown to be vitally important. Full article

The direct aerosol-radiative effects in the WRF-Chem model account for scattering/absorption of solar radiation due to aerosols, while aerosol–cloud interactions result in modifying wet scavenging of the ambient concentrations as an indirect aerosol effect. In this study, impact of aerosol on meteorological parameters, PM₁₀ and ozone concentrations are analysed which revealed (i) that a net decrease in shortwave and longwave radiation by direct feedback results in decrease in temperature up to 0.05 K, (ii) that a net increase due to longwave and shortwave radiation when both direct and indirect effects are taken together results in an increase in temperature up to 0.25 K (where the mean of temperature is 33.5 °C and standard deviation 2.13 °C), (iii) a marginal increase in boundary layer height of 50 m with increase in temperature with feedbacks, (iv) overall net increase in radiation by direct and indirect effect together result in an increase in PM₁₀ concentration up to 12 μg m⁻³ (with PM₁₀ mean as 84.5 μg m⁻³ and standard deviation 28 μg m⁻³) and an increase in ozone concentration up to 3 μg m⁻³ (with ozone mean as 29.65 μg m⁻³ and standard deviation 5.2 μg m⁻³) mainly due to net increase in temperature. Furthermore, impact of sensitivity of different aerosol mechanisms on PM₁₀ concentrations was scrutinized for two different mechanisms that revealed underestimation by both of the mechanisms with MOSAIC scheme, showing less fractional bias than MADE/SORGAM. For the dust storm period, MOSAIC scheme simulated higher mass concentrations than MADE/SORGAM scheme and performed well for dust-storm days while closely capturing the peaks of high dust concentrations. This study is one of the first few to demonstrate the impact of both direct and indirect aerosol feedback on local meteorology and air quality using a meteorology–chemistry modelling framework; the WRF-Chem model in a tropical urban airshed in India located in semi-arid climatic zone. It is inferred that semi-arid climatic conditions behave in a vastly different manner than other climatic zones for direct and indirect radiative feedback effects. Full article

In order to investigate the chemical characteristics of aerosol pollution including PM₁ and PM_2.5 in Handan, the offline sampling campaign was conducted and the concentrations of total water-soluble inorganic ions (TWSI), carbonaceous components (OC and EC) were analyzed. The average concentrations were 88.5 μg/m³ for PM₁ and 122 μg/m³ for PM_2.5, and the corresponding ratios of PM₁ versus PM_2.5 on non-pollution, mild-moderate pollution and heavy pollution were 0.67, 0.70 and 0.77, respectively. TWSI and OC accounted for 43.2% and 15.4% in PM₁, 41.8% and 16.0% in PM_2.5. Secondary components in PM_2.5 and PM₁ increased with heavy pollution, SNA (SO₄²⁻, NO₃⁻ and NH₄⁺) was enriched in PM₁ but SOC (Secondary Organic Carbon) was more enriched in PM_1–2.5. Furthermore, for evaluating the effect of aerosol feedback the WRF-Chem model was applied to identify the aerosol-radiation interaction of aerosol feedback influence on the PM_2.5 concentration and various meteorological factors in Handan. The results indicated that the aerosol radiative effects will result in an average 32.62%(36.18 W/m²) decrease in downward short wave flux at ground surface (SWDOWN), an average 17.52% (39.15 m) and 0.16% (0.44 K) decrease in planetary boundary layer height(PBLH) and surface temperature (T2). The wind speed at 10 m (WS) and relative humidity (RH) will be increased by about 4.16%(0.11 m/s) and 1.89% (0.78%), respectively. Full article

In January 2017, historic forest fires occurred in south-central Chile. Although their causes and consequences on health and ecosystems were studied, little is known about their atmospheric effects. Based on chemistry-transport modeling with WRF-CHIMERE, the impact of the 2017 Chilean mega-fires on regional atmospheric composition, and the associated meteorological feedback, are investigated. Fire emissions are found to increase pollutants surface concentration in the capital city, Santiago, by +150% (+30 µg/m${}^3$) for PM${}_{2.5}$ and +50% (+200 ppb) for CO on average during the event. Satellite observations show an intense plume extending over 2000 km, well reproduced by the simulations, with Aerosol Optical Depth at 550 nm as high as 4 on average during the days of fire activity, as well as dense columns of CO and O${}_3$. In addition to affecting atmospheric composition, meteorology is also modified through aerosol direct and indirect effects, with a decrease in surface radiation by up to 100 W/m${}^2$ on average, leading to reductions in surface temperatures by 1 K and mixing layer heights over land by 100 m, and a significant increase in cloud optical depth along the plume. Large deposition fluxes of pollutants over land, the Pacific ocean and the Andes cordillera are found, signaling potential damages to remote ecosystems. Full article

In the atmosphere, aerosols play an important role in climate change, the Earth’s environment and human health. The purpose of this study is to investigate the direct and semi-direct aerosol effects on weather forecasting, focusing on the Iberian Peninsula (IP). To that end, two Weather Research and Forecasting (WRF)-Chem simulations (with and without aerosol feedback) for an entire year (2015) were performed. The model setup includes two nested domains run in two-way mode, allowing the downscaling for the IP domain at a 5 × 5 km² high-horizontal resolution. The results were explored through agreement of pairs of time series and their spatial variability in order to analyse the importance of including the online-coupled aerosol radiative effect on the meteorological variables: shortwave (solar) radiation, air temperature and precipitation. Significant variations of agreement were found when capturing both temporal and spatial patterns of the analysed meteorological variables. While the spatial distribution of temperature and precipitation is similar throughout the IP domain, with agreement values ranging from 0.87 up to 1.00, the solar radiation presents a distinct spatial pattern with lower agreement values (0.68–0.75) over ocean and higher agreement (0.75–0.98) over land regions. With regard to the spatial differences between simulations, the aerosol contributed to a considerable decrease in annual mean and maximum radiation (up to 20 and 40 Wm⁻², respectively), slightly impacting the temperature variation (up to 0.5 °C). These results suggest that the aerosol feedback effects should be accounted when performing weather forecasts, and not only for purposes of air quality assessment. Full article

The Beijing-Tianjin-Hebei (BTH) region experienced heavy air pollution in December 2015, which provided a good opportunity to explore the aerosol-radiation interaction (ARI) effects of different particulate matter (PM) components (sulfate, nitrate, and black carbon (BC)). In this study, five tests were conducted by the Weather Research and Forecasting—Chemistry (WRF-Chem) model. The tests included scenario 1 simulation with ARI turned on, scenario 2 simulation with ARI turned off, scenario3 simulation without NO_x/NO₃⁻ emissions and with ARI turned on, scenario 4 simulation without SO₂/SO₄²⁻ emissions and with ARI turned on, and scenario 5 simulation without BC emissions and with ARI turned on. The ARI decreased the downward shortwave radiation (SWDOWN) and the temperature at 2 m (T2), reduced the planetary boundary layer (PBL) height (PBLH), and increased the relative humidity (RH) at 2 m in the region. These factors also contribute to pollution accumulation. The results revealed that BC aerosols have a stronger effect on the reduction in SWDOWN than sulfate (SO₄²⁻) and nitrate (NO₃⁻). BC aerosols produce both cooling and heating effects, while SO₄²⁻ aerosols produce only cooling effects. The PBL decreased and RH2 increased due to the aerosol feedback effect of sulfate, nitrate, and BC. The ARI effect on meteorological factors during the nonheavy pollution period was much smaller than that during the pollution period. Full article