Search Results (1,205)

The chemistry of atmospheric precipitation serves as an important proxy for discriminating the source(s) of air contaminants in urban environments as well as to discuss the dynamic of atmospheric chemistry exchanges. This approach can be undertaken at time scales varying from single events to seasonal and yearly time frames. Here, we characterized the chemical composition of two single rain episodes (18 July 2018 and 21 February 2019) collected in Wrocław (SW Poland). Our results demonstrated inner variations and seasonality (within the rain event as well as between summer and winter), both in ion concentrations as well as in their potential relations with local air contaminants and scavenging processes. Coupling statistical analysis of chemical parameters with meteorological/synoptic conditions and HYSPLIT back trajectories allowed us to identify three main factors (i.e., principal components; PC) controlling the chemical composition of precipitation, and that these fluctuated during each event: (i) PC1 (40%) was interpreted as reflecting the long-range transport and/or anthropogenic influences of emission sources that included biomass burning, fossil fuel combustion, industrial processes, and inputs of crustal origin; (ii) PC2 (20%) represents the dissolution of atmospheric CO₂ and HF into ionic forms; and (iii) PC3 (20%) originates from agricultural activities and/or biomass burning. Time variations during the rain events showed that each factor was more important at the start of the event. The study of both SO₄²⁻ and Ca²⁺ concentrations showed that while sea spray inputs fluctuated during both rain events, their overall impact was relatively low. Finally, below-cloud particle scavenging processes were only observed for PM₁₀ at the start of the winter rain episode, which was probably explained by the corresponding low rain intensity and an overlap from local aerosol emissions. Our study demonstrates the importance of multi-time scale approaches to explain the chemical variability in rainwater and both its relation to emission sources and the atmosphere operating processes. Full article

Climate change has been significantly affecting human activities due to the accumulation of greenhouse gases, such as carbon dioxide. Biofixation of carbon dioxide (CO₂) has been investigated to reduce the atmospheric CO₂ level and slow the rapid increase in the global temperature. Carbon capture and utilization (CCU) can be performed by either physio-chemical or biological methods. The latter takes place in ambient temperature and mild conditions, such that there is no need for high pressure and high energy consumption nor hazardous chemicals. Biofixation by microalgae has been utilized to capture CO₂ and the microalgae biomass collected after the process can be further utilized in renewable biofuel generation. On the other hand, microbial enzymes, such as carbonic anhydrase (CA), have been investigated to speed up the whole biofixation process by increasing the conversion rate of CO₂ into bicarbonate (HCO₃⁻) in a culture medium and the latter can be readily used by microalgae to increase CO₂ removal. In this study, in the presence of 20% CO₂ (v/v) gas in air and 5 mL CA enzyme extract (0.5 mg mL⁻¹ protein), we can significantly increase the biofixation rate using marine green microalgae, Tetraselmis sp. Results showed that the biofixation rate can be increased from 0.64 g L⁻¹ day⁻¹ (no CA and at 0.04% CO₂) to 4.26 g L⁻¹ day⁻¹. The effects of different experimental conditions such as pH, nutrient levels and working CO₂ concentration levels on Tetraselmis sp. growth and CO₂ biofixation (CO₂ removal) rate have been investigated. This study demonstrates a new alternative approach for effective carbon capture and utilization (CCU) using microalgae which can be applied to achieve the goal of carbon neutrality. Full article

Greening dryland ecosystems greatly benefits from significant CO₂ fertilization. This greening trend across global drylands, however, has also been severely constrained by enhancing atmospheric and soil water (SW) deficits. Thus far, the relative offsets in the contributions between the atmospheric vapor pressure deficit (VPD), SW at varying depths, and CO₂ fertilization to vegetation dynamics, as well as the differences in the impacts of decreasing SW at different soil depths on dryland ecosystems over long periods, remain poorly recorded. Here, this study comprehensively explored the relative offsets in the contributions to vegetation dynamics between high VPD, low SW, and rising CO₂ concentration across global drylands during 1982–2018 using process-based models and satellite-observed Leaf Area Index (LAI), Gross Primary Productivity (GPP), and solar-induced chlorophyll fluorescence (SIF). Results revealed that decreasing-SW-induced reductions of LAI in dryland ecosystems were larger than those caused by rising VPD. Furthermore, dryland vegetation was more severely constrained by decreasing SW on the subsurface (7–28 cm) among various soil layers. Notable offsets were found in the contributions between enhanced water constraints and CO₂ fertilization, with the former offsetting approximately 38.49% of the beneficial effects of the latter on vegetation changes in global drylands. Process-based models supported the satellite-observed finding that increasing water constraints failed to overwhelmingly offset significant CO₂ fertilization on dryland ecosystems. This work emphasizes the differences in the impact of SW at different soil depths on vegetation dynamics across global drylands as well as highlights the far-reaching importance of significant CO₂ fertilization to greening dryland ecosystems despite increasing atmospheric and SW constraints. Full article

Increased air pollution is driven by anthropogenic pollution emissions and climate change, which pose great challenges to environmental governance. Strengthening the monitoring of regional air quality levels and analyzing the causes of regional pollution is conducive to the management and sustainable development of the regional atmosphere. Functional data obtained on a wavelet basis were used in the fitting of air quality data of Fujian Province, and wavelet decomposition was performed to obtain low-frequency and high-frequency information. While the Fourier basis cannot adaptively adjust the time–frequency window, resulting in the loss of location information of special frequencies, the wavelet basis solves this problem. Functional analysis of variance was utilized for analyzing spatial differences in air pollution characteristics. Furthermore, the study established a multivariate functional linear regression model to explore the impact of meteorological factors and ozone precursor factors. The results indicated that the overall air quality was gradually improving in Fujian Province, but the concentration of ozone was progressively increasing. Air pollution in coastal areas was higher than that in inland areas. The p-values of the functional analysis of variance for energy values and crest values were less than 0.05. Moreover, the energy entropy and kurtosis values were greater than 0.05. There were significant differences of AQI in the fluctuation amplitude and variation characteristics of different cities. The total squared multiple correlation of regression model was above 50% on average. Ozone is currently the most serious pollution factor, mainly affected by wind speed, temperature, NO₂, and CO. In summer, it was principally influenced by VOCs. The findings of this study could act as a reference in exploring the time–frequency characteristics of air quality data and support of air pollution control. Full article

Chemical nanosensors based on nanoparticles of tin dioxide and graphene-decorated tin dioxide were developed and characterized to detect low NO₂ concentrations. Sensitive layers were prepared by the drop casting method. SEM/EDX analyses have been used to investigate the surface morphology and the elemental composition of the sensors. Photoactivation of the sensors allowed for detecting ultra-low NO₂ concentrations (100 ppb) at room temperature. The sensors showed very good sensitivity and selectivity to NO₂ with low cross-responses to the other pollutant gases tested (CO and CH₄). The effect of humidity and the presence of graphene on sensor response were studied. Comparative studies revealed that graphene incorporation improved sensor performance. Detections in complex atmosphere (CO + NO₂ or CH₄ + NO₂, in humid air) confirmed the high selectivity of the graphene sensor in near-real conditions. Thus, the responses were of 600%, 657% and 540% to NO₂ (0.5 ppm), NO₂ (0.5 ppm) + CO (5 ppm) and NO₂ (0.5 ppm) + CH₄ (10 ppm), respectively. In addition, the detection mechanisms were discussed and the possible redox equations that can change the sensor conductance were also considered. Full article

Compared with other organs in the body, the human brain is extremely sensitive to changes in O₂ and CO₂ levels. This study applied functional near-infrared spectroscopy (fNIRS) to analyze the changes in cerebral oxygen saturation (COS) and hemoglobin (Hb) concentrations in response to various atmospheric gas concentrations and investigate their effects on brain function. Twenty-nine adults were exposed to four gas conditions, namely atmospheric concentration (C1), high O₂ concentration (C2), high CO₂ concentration (C3), and high O₂ and CO₂ concentrations (C4). Changes in COS and Hb concentrations were measured using fNIRS, whereas heart rate (HR) and percutaneous oxygen saturation (SpO₂) were measured using a patient monitor. COS, oxy-Hb (HbO), and total-Hb (HbT) increased progressively from C1 to C4, whereas deoxy-Hb (HbR) exhibited a decreasing trend. Moreover, the COS and Hb concentrations were more strongly influenced by high CO₂ levels than by high O₂ levels. High O₂ concentrations increased the blood O₂ saturation, whereas high CO₂ concentrations increased blood flow as a physiological response, enhancing O₂ delivery to the brain. Additionally, HR and SpO₂ increased at high CO₂ concentrations. However, at high O₂ concentrations providing a sufficient O₂ supply, SpO₂ increased while HR decreased. Therefore, adjusting the concentrations of CO₂ and O₂ may improve cerebral blood flow and change brain function, supporting cerebrovascular health and preventing related diseases. Full article

Respiration of soil heterotrophs—mainly of bacteria and fungi—is a substantial part of carbon balance in terrestrial ecosystems, which tie up organic matter decomposition with the rise of atmospheric CO₂ concentration. Deep understanding and prediction of seasonal and interannual variation of heterotrophic and autotrophic components of CO₂ efflux from soil is limited by the lack of long-term, full-year measurements. To better understand the impact of current climate changes on CO₂ emissions from soils in the mixed forest and mowed grassland, we measured CO₂ efflux every week for 2 years. Heterotrophic (SOM-derived + leaf litter) and root-associated (root with rhizosphere microorganisms) components were partitioned by the root exclusion method. The total CO₂ efflux from soil was averaged 500 g C m⁻² yr⁻¹ in the forest and 650 g C m⁻² yr⁻¹ in the grassland, with shares of the no-growing cold season (Nov–Mar) of 22% and 14%, respectively. The heterotrophic component of CO₂ efflux from the soil averaged 62% in the forest and 28% in the grassland, and it was generally stable across seasons. The redistribution of the annual precipitation amounts as well as their deficit (droughts) reduced soil respiration by 33–81% and heterotrophic respiration by 24–57% during dry periods. This effect was more pronounced in the grassland (with an average decline of 56% compared to 39% in the forest), which is related to lower soil moisture content in the grassland topsoil during dry periods. Full article

Carbon dioxide (CO₂) is the most abundant greenhouse gas (GHG) in the atmosphere and the substrate for the photosynthetic fixation of carbohydrates in plants. Increasing GHGs from anthropogenic emissions is warming the Earth’s atmospheric system at an alarming rate and changing its climate, which can affect photosynthesis and other biochemical reactions in crop plants favorably or unfavorably, depending on plant species. For the substrate role in plant carbon reduction reactions, CO₂ concentration ([CO₂]) in air potentially enhances photosynthesis. However, N uptake and availability for protein synthesis can be a potential limiting factor in enhanced biomass synthesis under enriched [CO₂] conditions across species. Legumes are C₃ plants and symbiotic N fixers and are expected to benefit from enhanced [CO₂] in the air. However, the concurrent increase in air temperatures with enhanced [CO₂] demands more detailed investigations on the effects of [CO₂] enhancement on grain legume growth and yield. In this article, we critically reviewed and presented the online literature on growth, phenology, photosynthetic rate, stomatal conductance, productivity, soil health, and insect behavior under elevated [CO₂] and temperature conditions. The review revealed that specific leaf weight, pod weight, and nodule number and weight increased significantly under elevated [CO₂] of up to 750 ppm. Under elevated [CO₂], two mechanisms that were affected were the photosynthesis rate (increased) and stomatal conductivity (decreased), which helped enhance water use efficiency in the C₃ legume plants to achieve higher yields. Exposure of legumes to elevated levels of [CO₂] when water stressed resulted in an increase of 58% in [CO₂] uptake, 73% in transpiration efficiency, and 41% in rubisco carboxylation and decreased stomatal conductance by 15–30%. The elevated [CO₂] enhanced the yields of soybean by 10–101%, peanut by 28–39%, mung bean by 20–28%, chickpea by 26–31%, and pigeon pea by 31–38% over ambient [CO₂]. However, seed nutritional qualities like protein, Zn, and Ca were significantly decreased. Increased soil temperatures stimulate microbial activity, spiking organic matter decomposition rates and nutrient release into the soil system. Elevated temperatures impact insect behavior through higher plant feeding rates, posing an enhanced risk of invasive pest attacks in legumes. However, further investigations on the potential interaction effects of elevated [CO₂] and temperatures and extreme climate events on growth, seed yields and nutritional qualities, soil health, and insect behavior are required to develop climate-resilient management practices through the development of novel genotypes, irrigation technologies, and fertilizer management for sustainable legume production systems. Full article

Atmospheric particulate matter (PM) samples were collected in Riyadh, Saudi Arabia, to assess air quality, quantify, heavy metal concentrations, and evaluate related ecological and health risks. This study’s uniqueness stems from its focused and detailed analysis of PM pollution in Riyadh, including an extensive assessment of heavy metal concentrations across different PM sizes by applying diverse pollution and health indices. This brings to light critical health and ecological issues and provides foundation for targeted pollution control efforts in the region. The study focused on two PM size fractions, PM_2.5 and PM₁₀ and analyzed the presence of heavy metals, including iron (Fe), nickel (Ni), chromium (Cr), zinc (Zn), cobalt (Co), copper (Cu), silver (Ag), arsenic (As), cadmium (Cd), and lead (Pb), using inductively coupled plasma emission spectrometry. Results showed significantly higher levels of PM₁₀ (223.12 ± 66.12 µg/m³) compared to PM_2.5 (35.49 ± 9.63 µg/m³), suggesting that local dust is likely a primary source. Air quality varied from moderate to unhealthy, with PM₁₀ posing substantial risks. Heavy metal concentrations in PM_2.5 followed the order Fe (13.14 ± 11.66 ng/m³) > As (2.87 ± 2.08 ng/m³) > Cu (0.71 ± 0.51 ng/m³) > Zn (0.66 ± 0.46 ng/m³) > Cr 0.50 ± 0.23 ng/m³) > Pb (0.14 ± 0.10 ng/m³) > Ni (0.03 ± 0.04 ng/m³) > Cd (0.004 ± 0.002 ng/m³) > Ag (0.003 ± 0.003 ng/m³) > Co (0.002 ± 0.004 ng/m³). In PM10, they followed the order Fe (743.18 ± 593.91 ng/m³) > As (20.12 ± 13.03 ng/m³) > Cu (10.97 ± 4.66 ng/m³) > Zn (9.06 ± 5.50 ng/m³) > Cr (37.5 ± 2.70 ng/m³) > Ni (1.72 ± 01.54 ng/m³) > Pb (1.11 ± 0.64 ng/m³) > Co (0.25 ± 0.28 ng/m³) > Ag (0.10 ± 0.26 ng/m³) > Cd (0.04 ± 0.02 ng/m³). Enrichment factor analysis revealed elevated levels for the metals Cu, Zn, As, Ag, Cd, and Pb. Pollution indices indicated various contamination levels, with Ag and As showing particularly high contamination and ecological risks. The study highlighted significant health concerns, especially from As, which poses a substantial long-term carcinogenic threat. The findings emphasize the urgent need to reduce hazardous metal levels in Riyadh’s air, especially with high child exposure. Full article

Opposite to atmospheric CO₂ concentrations, which reach a minimum during the vegetation season (e.g., June–August in the Northern Hemisphere), soil CO₂ reaches a maximum in the same period due to the root respiration. In karst areas, characterized by high rock porosity, this excess CO₂ seeps inside caves, locally increasing pCO₂ values above 1%. To better understand the role of karst areas in the carbon cycle, it is essential to understand the mechanisms of CO₂ dynamics in such regions. In this study, we present and discuss the spatial and temporal variability of air temperature and CO₂ concentrations in Samograd Cave, Croatia, based on three years of monthly spot measurements. The cave consists of a single descending passage, resulting in a characteristic bimodal climate, with stable conditions during summer (i.e., stagnant air inside the cave) and a strong convective cell bringing in cold air during winter. This bimodality is reflected in both CO₂ concentrations and air temperatures. In summer, the exchange of air through the cave’s main entrance is negligible, allowing the temperature and CO₂ concentration to equilibrate with the surrounding rocks, resulting in high in-cave CO₂ concentrations, sourced from enhanced root respiration. During cold periods, CO₂ concentrations are low due to frequent intrusions of fresh external air, which effectively flush out CO₂ from the cave. Both parameters show distinct spatial variability, highlighting the role of cave morphology in their dynamics. The CO₂ concentrations and temperatures have increased over the observation period, in line with external changes. Our results highlight the role of caves in transferring large amounts of CO₂ from soil to the atmosphere via caves, a process that could have a large impact on the global atmospheric CO₂ budget, and thus, call for a more in-depth study of these mechanisms. Full article

Corrosion is the deterioration of metals due to environmental exposure. Commercial inhibitors used to control corrosion often contain heavy metal salts, which are highly toxic to both the environment and human health. A biosurfactant produced by the bacterium Pseudomonas cepacia CCT 6659 was tested as a corrosion inhibitor on carbon steel and galvanized iron surfaces. Matrices based on plant ingredients with different compositions were tested in a laboratory-constructed accelerated corrosion chamber (ACC) simulating a critical maritime atmosphere in conditions of 40 °C, 5% NaCl, and 100% humidity. The most stable matrix was selected for biosurfactant incorporation in different concentrations, expressed as critical micellar concentration (CMC), and was applied to metal surfaces to evaluate its ability to inhibit corrosion. Additionally, to evaluate the potential of the biosurfactant as a low-toxicity corrosion inhibitor additive in paint systems, iron and carbon steel samples were coated with three biosurfactant-containing commercial paints and subjected to critical atmospheric conditions for testing coating effectiveness. The formulation containing vegetable resin as a plasticizer, oleic acid, ethanol, and CaCO₃ was chosen to incorporate the biosurfactant. The addition of the biosurfactant at twice its CMC led to a reduction in carbon steel sample mass loss from 123.6 to 82.2 g/m², while in the galvanized iron plates, the mass loss decreased from 285.9 to 226.7 g/m² at the same biosurfactant concentration. When supplemented with the biosurfactant, the alkyd resin-based paint (A) ensured less mass loss in samples (46.0 g/m²) compared to the control without biosurfactant (58.0 g/m²). Using the paint formulated with oil-based resin (B), the mass loss decreased from 53.0 to 24.1 g/m², while with that based on petroleum derivatives (C), it decreased from 82.2 to 27.6 g/m². These results confirm the feasibility of using biosurfactants in biodegradable coatings, reducing the need for commercial corrosion inhibitors. Full article

One of the keys towards sustainable policies and advanced air quality monitoring is the detailed assessment of all factors that affect the surface concentrations of greenhouse gases (GHGs) and aerosols. While the development of new atmospheric tracers can pinpoint emission sources, the atmosphere itself plays a relevant role even at local scales: Its dynamics can increase, or reduce, surface concentrations of pollutants harmful to human health and the environment. PBL (planetary boundary layer), or peplospheric, variability is known to affect such concentrations. In this study, an unprecedented characterization of PBL cycles and patterns is performed at the WMO/GAW regional coastal site of Lamezia Terme (code: LMT) in Calabria, Southern Italy, in conjunction with the analysis of key GHGs and aerosols. The analysis, accounting for five months of 2024 data, indicates that peplospheric variability and wind regimes influence the concentrations of key GHGs and aerosols. In particular, PBLH (PBL height) patterns have been tested to further influence the surface concentrations of carbon monoxide (CO), black carbon (BC), and particulate matter (PM). This research introduces four distinct wind regimes at LMT: breeze, not complete breeze, eastern synoptic, and western synoptic, each with its peculiar influences on the local transport of gases and aerosols. This research demonstrates that peplosphere monitoring needs to be considered when ensuring optimal air quality in urban and rural areas. Full article

The Meteorological Optical Range (MOR) is a measurement of atmospheric visibility. Visibility impairment has been linked to increased aerosol levels in the air. This study conducted statistical analyses using meteorological, air pollutant concentration, and MOR data collected in Mexico City from August 2014 to December 2015 to determine the factors contributing to haze occurrence (periods when MOR < 10,000 m), defined using a light scatter sensor (PWS100). The outcomes revealed seasonal patterns in PM_2.5 and relative humidity (RH) for haze occurrence along the year. PM_2.5 levels during hazy periods in the dry season were higher compared to the wet season, aligning with periods of poor air quality (PM_2.5 > 45 μg/m³). Pollutant-to-CO ratios suggested that secondary aerosols’ production, led by SO₂ conversion to sulfate particles, mainly impacts haze occurrence during the dry season. Meanwhile, during the rainy season, the PWS100 registered haze events even with PM_2.5 values close to 15 μg/m³ (considered good air quality). The broadened distribution of extinction efficiency during the wet period and its correlation with RH suggest that aerosol water vapor uptake significantly impacts visibility during this season. Therefore, attributing poor visibility strictly to poor air quality may not be appropriate for all times and locations. Full article

As talk grows about billions or even trillions of dollars being directed toward potential “Net Zero” activities, it is imperative that the chemistry inherent in or driving those actions make scientific sense. The challenge is to close the mass and energy balances to the carbon and oxygen cycles in the Earth’s atmosphere and oceans. Several areas of climate science have been identified that chemists can investigate through methods that do not require a supercomputer or a climate model for investigation, most notably the following: (1) The carbon cycle, which still needs to be balanced, as many known streams, such as carbon to landfills, carbon in human-enhanced sewage and land runoff streams, and carbon stored in homes and other material, do not seem to have been accounted for in carbon balances used by the IPCC. (2) Ocean chemistry and balances are required to explain the causes of regional and local-scale salinity, pH, and anoxic conditions vs. global changes. For example, local anoxic conditions are known to be impacted by changes in nutrient discharges to oceans, while large-scale human diversions of fresh water streams for irrigation, power, and industrial cooling must have regional impacts on oceanic salinity and pH. (3) Carbon Capture and Storage (CCS) schemes, if adopted on the large scales being proposed (100s to 1000s of Gt net injection by 2100), should impact the composition of the atmosphere by reducing free oxygen, adding more water from combustion, and displacing saline water from subsurface aquifers. Data indicate that atmospheric oxygen is currently dropping at about twice the rate of CO₂ concentrations increasing, which is consistent with combustion chemistry with 1.5 to 2 molecules of oxygen being converted through combustion to 1 molecule of CO₂ and 1 to 2 molecules of H₂O, with reverse reactions occurring as a result of oxygenic photosynthesis by increased plant growth. The CCS schemes will sabotage these reverse reactions of oxygenic photosynthesis by permanently sequestering the oxygen atoms in each CO₂ molecule. Full article

Accurately predicting the wheat potential yield (PY) is crucial for enhancing agricultural management and improving resilience to climate change. However, most existing crop models for wheat PY rely on type-specific parameters that describe wheat traits, which often require calibration and, in turn, reduce prediction confidence when applied across different spatial or temporal scales. In this study, we integrated eco-evolutionary optimality (EEO) principles with a universal productivity model, the Pmodel, to propose a comprehensive full-chain method for predicting wheat PY. Using this approach, we forecasted wheat PY across China under typical shared socioeconomic pathways (SSPs). Our findings highlight the following: (1) Incorporating EEO theory improves PY prediction performance compared to current parameter-based crop models. (2) In the absence of phenological responses, rising atmospheric CO₂ concentrations universally benefit wheat growth and PY, while increasing temperatures have predominantly negative effects across most regions. (3) Warmer temperatures expand the window for selecting sowing dates, leading to a national trend toward earlier sowing. (4) By simultaneously considering climate impacts on wheat growth and sowing dates, we predict that PY in China’s main producing regions will significantly increase from 2020 to 2060 and remain stable under SSP126. However, under SSP370, while there is no significant trend in PY during 2020–2060, increases are expected thereafter. These results provide valuable insights for policymakers navigating the complexities of climate change and optimizing wheat production to ensure food security. Full article