Ecosystems and Climate Change: Understanding Impacts to Shape the Future

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25 pages, 1672 KB

Open AccessArticle

Effects of Prior Thermal Exposure of a Soil–Compost System on Potentially Bioavailable Mercury and Its Accumulation in Rice Grown on Mining-Impacted Soils

by Marisol Laza-Durante, Iván David Urango-Cárdenas, Germán Enamorado-Montes, Elvia Valeria Durante-Yánez, Roberth Paternina-Uribe and José Luis Marrugo-Negrete

Toxics 2026, 14(8), 692; https://doi.org/10.3390/toxics14080692 - 5 Aug 2026

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Abstract

Mercury (Hg) mobility in contaminated soils may be altered by solarization-induced thermal disturbance and organic amendments. This study evaluated whether a cover-induced prior solarization pretreatment of a mining-impacted soil–compost system modifies the operationally defined labile Hg fraction (F1 + F2, considered potentially bioavailable), rice productivity, grain Hg accumulation, and screening-level health risk. Mining soils from San Jorge River basin were amended with compost at a 1:9 ratio and solarized for one month before crop establishment, generating temperatures of 32, 40, 44, and 50 °C under different cover conditions. After pretreatment, covers were removed and rice was cultivated for four months under uniform flooded conditions. Total Hg in soils and grains was determined by EPA Method 7473, and the potentially bioavailable fraction by modified Bloom extraction. Prior thermal exposure increased this fraction, especially at 50 °C, whereas compost reduced total Hg and partially buffered this increase. Productivity depended on the compost × temperature interaction: compost improved yield at 40 and 44 °C, while no grain production occurred in substrates previously exposed to 50 °C. Compost-amended treatments showed lower grain Hg than unamended soils, although all values exceeded the 20 μg kg⁻¹ reference limit. Hazard quotients remained below 1, with the highest value in unamended soil previously exposed to 44 °C. Full article

(This article belongs to the Topic Ecosystems and Climate Change: Understanding Impacts to Shape the Future)

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26 pages, 2945 KB

Open AccessArticle

Preliminary Assessment of Measurement Frequency and Replication Effects on Season-Long Greenhouse Gas Emissions and Global Warming Potential Estimation Consistency Among Various Ecosystems

by Kristofor R. Brye, Diego Della Lunga, Jonathan B. Brye, Cassie Seuferling, Tyler Buchanan, Will Dockery and Lauren Gwaltney

Gases 2026, 6(3), 32; https://doi.org/10.3390/gases6030032 - 6 Jul 2026

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Abstract

For soil processes that are known to be temporally dynamic, such as soil respiration, methanogenesis, and nitrification–denitrification, it is challenging to capture temporal variations with field-portable greenhouse gas (GHG) analyzers to provide the most accurate estimates of season-long GHG emissions and global warming potentials (GWPs). The objective of this field study was to evaluate the effects of measurement frequency (i.e., weekly, every other week, and every third week), replication (i.e., three, four, or five), and their interaction on the consistency of season-long carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O) emissions and GWP estimates across multiple ecosystems. Results are based on direct, in-field measurements with a field-portable gas analyzer. Field research was conducted throughout the 2024 growing season in a minimally grazed pasture, tallgrass prairie, soybean under conventional and conservation management practices, and cotton under conservation management in Arkansas, USA. Season-long CO₂ emissions and GWP from the tallgrass prairie were 1.1 times (12%) greater from the weekly and every-other-week (16.9 and 17.0 Mg ha⁻¹, respectively), which did not differ, than the every-third-week (14.2 and 14.2 Mg ha⁻¹, respectively) measurement frequencies. Season-long CH₄ emissions from the minimally grazed pasture and conservation-tilled soybean system were ≥7.5 times greater with four and five replications, which did not differ, than with three replications. Global warming potential in the conservation-tilled soybean (13.9 Mg ha⁻¹) and conservation-tilled cotton (21.1 Mg ha⁻¹) systems were ≥1.1 times (13%) greater with the every-third-week than with the weekly data set. Though this study was somewhat limited due the data sub-setting approach used, even using current, state-of-the-art, field-portable GHG analyzers, an appropriate in-field measurement frequency and number of spatial replications should be considered to reliably quantify whole-field, season-long GHG emissions and GWP estimates. Full article

(This article belongs to the Topic Ecosystems and Climate Change: Understanding Impacts to Shape the Future)

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15 pages, 5666 KB

Open AccessArticle

Introducing CdZnTe Detectors into Measuring ²²²Rn Concentrations in Water

by Ioannis Kaissas, Konstantinos Karafasoulis, Aris Kyriakis and Panagiotis Papaprokopiou

Gases 2026, 6(2), 29; https://doi.org/10.3390/gases6020029 - 3 Jun 2026

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Abstract

Radon (²²²Rn) is a noble, radioactive gas and tends to be accumulated in poorly ventilated enclosed spaces. Mainly due to its radioactive daughters and the α-particles emitted, ²²²Rn poses a risk of cancer and therefore its concentration in air and water should be kept under certain reference levels. Several methods have been developed to accurately measure ²²²Rn concentration in water, using α, β or γ counting. A well-established, but not the only, method involves γ-spectroscopy using a High-Purity Germanium (HPGe) detector to identify the ²²²Rn decay isotopes ²¹⁴Pb and ²¹⁴Bi, assuming they are in secular equilibrium with ²²²Rn. This technique requires costly, bulky equipment due to the HPGe’s operation at −196 °C and the need for substantial shielding. The present study introduces a more affordable and compact device, utilizing CdZnTe (CZT) crystals, which provide exceptional energy resolution in the 300 to 600 keV range, with nearly eight times the Full Width at Half Maximum (FWHM) of HPGe. Four stacked CZT detectors, each containing a 0.5 cm³ crystal, were compared with measurements from an HPGe detector. Water samples were collected from boreholes and taps in a region where radon concentration in water ranged from 10 to 900 Bq/L. The results are promising for samples around 100 Bq/L, considering the potential advancements of the device with larger CZT detectors. Additionally, the method has the potential for in situ use due to its handheld capability. Full article

(This article belongs to the Topic Ecosystems and Climate Change: Understanding Impacts to Shape the Future)

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25 pages, 3492 KB

Open AccessArticle

AI-Driven Analysis of Meteorological and Emission Characteristics Influencing Urban Smog: A Foundational Insight into Air Quality

by Sadaf Zeeshan and Muhammad Ali Ijaz Malik

Gases 2026, 6(1), 10; https://doi.org/10.3390/gases6010010 - 5 Feb 2026

Cited by 3 | Viewed by 2424

Abstract

In South Asia, smog has become a critical environmental concern that endangers public health, ecosystems, and the regional climate. To determine the primary causes of smog formation in Lahore during peak polluted months (October and November), the current study develops a dual analytical framework that combines cutting-edge machine learning with sector- and pollutant-specific emission analysis. To assess their relationship with Air Quality Index (AQI) and create a high-accuracy predictive model, meteorological factors and emission data from key sectors are used to build Random Forest and extreme gradient boosting (XGBoost) models. The current study evaluates the joint effects of weather and emission loads on AQI variability by integrating atmospheric dynamics with comprehensive emission profiles. The XGBoost model forecasts important pollutants from the transportation, industrial, and agricultural sectors, including carbon dioxide (CO₂), oxides of nitrogen (NO_x), Volatile Organic Compounds (VOCs), and particulate matter, in the second analytical tier. Particulate matter (PM), NO_x, and transport-related pollutants are consistently identified by the models as the primary predictors of AQI, with high prediction performance. Furthermore, a 3-fold split is used for cross-validation, making sure that each fold maintained the data’s chronological order to avoid leakage. The model has modest root mean square error (RMSE) levels (4.32 and 8.14) and high coefficient of determination (R²) values (0.93–0.99). Approximately 90% of Lahore’s annual emissions resulted from the transportation sector. These results offer aid to policymakers to anticipate air quality, identify important emission sources, and execute targeted initiatives to minimize smog and promote a healthier urban environment. The current study also helps in analyzing the causes of atmospheric and sectoral pollution. While the study captures smog dynamics during peak pollution months, its temporal scope is limited, and finer spatial measurements could further improve the generalizability of the results. Full article

(This article belongs to the Topic Ecosystems and Climate Change: Understanding Impacts to Shape the Future)

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23 pages, 4680 KB

Open AccessArticle

Economic and Technical Viability of Solar-Assisted Methane Pyrolysis for Sustainable Hydrogen Production from Stranded Gas in Nigeria

by Campbell Oribelemam Omuboye and Chigozie Nweke-Eze

Gases 2026, 6(1), 8; https://doi.org/10.3390/gases6010008 - 2 Feb 2026

Cited by 1 | Viewed by 1859

Abstract

This study presents a techno-economic assessment of a modular, solar-assisted methane pyrolysis pilot plant designed for sustainable hydrogen production in Nigeria using concentrated solar power (CSP). Driven by the need to convert flare gas into value and reduce emissions, the work evaluates a hypothetical 100 kg/day hydrogen system by integrating a methane pyrolysis reactor with a solar heliostat–receiver field. Process modelling was carried out in DWSIM, while solar concentration behavior was represented using Tonatiuh. The mass–energy balance results show a hydrogen output of 3.95 kg/h accompanied by 12.30 kg/h of carbon black, with the reactor demanding roughly 44 kW of high-temperature heat at 900 °C. The total capital cost of the ≈50 kW pilot plant is approximately USD 1.5 million, with heliostat and receiver technologies forming the bulk of the investment. Annual operating costs are estimated at USD 69,580, alongside feedstock expenses of USD 43,566. Using annualized cost and discounted cash flow approaches, the resulting levelized cost of hydrogen (LCOH) is USD 5.87/kg, which is competitive with off-grid electrolysis in the region, though still above blue and gray hydrogen benchmarks. The results indicate that hydrogen cost is primarily driven by solar field capital expenditure and carbon by-product valorization. Financial indicators reveal a positive NPV, a 13% IRR, and a 13-year discounted payback period, highlighting the promise of solar-assisted methane pyrolysis as a transitional hydrogen pathway for Nigeria. Full article

(This article belongs to the Topic Ecosystems and Climate Change: Understanding Impacts to Shape the Future)

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14 pages, 4593 KB

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Evolution of Tropospheric Ozone and Surface Temperature in Mexico City from 2000 to 2021

by Telma Castro, Oscar Peralta, Armando Sánchez-Vargas and Alejandro Salcido

Atmosphere 2025, 16(12), 1379; https://doi.org/10.3390/atmos16121379 - 5 Dec 2025

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Abstract

We analyze the relation between maximum tropospheric ozone concentration and surface temperature in Mexico City between 2000 and 2021. Changes in ozone levels over the decades appear to respond to public strategies aimed at reducing its precursors. The exponential fit between temperature and maximum ozone concentration is [O3] = 9.33 × exp (0.0957 × T), with a coefficient of determination of 0.73, for the period 2000–2021. Reordering the data by five-year period improves the fit slightly; the intercepts increase from 8.431 (2000–2004) to 10.428 (2015–2019), and the slopes decrease from 0.1051 (2000–2004) to 0.0839 (2015–2019), providing a quantitative insight into how public strategies and policies modify air pollution and make Mexico City’s atmosphere less reactive. Full article

(This article belongs to the Topic Ecosystems and Climate Change: Understanding Impacts to Shape the Future)

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21 pages, 7051 KB

Open AccessArticle

Inter-Monthly Variations in CO₂ and CH₄ Fluxes in a Temperate Forest: Coupling Dynamics and Environmental Drivers

by Chuying Guo, Fuxi Ke, Leiming Zhang and Shenggong Li

Atmosphere 2025, 16(12), 1326; https://doi.org/10.3390/atmos16121326 - 24 Nov 2025

Cited by 2 | Viewed by 868

Abstract

Climate change, driven largely by anthropogenic greenhouse gas emissions, is a major global issue. Long-term high-frequency measurements of gas fluxes remain limited, especially outside the growing season. This study addresses two key gaps: the absence of continuous annual data capturing diurnal and seasonal variations, and the biases from suboptimal sampling timing. Using automated chambers, we monitored soil CO₂ and CH₄ fluxes throughout 2016 in a temperate forest on Changbai Mountain, China. Our results showed a strong negative correlation between annual CO₂ and CH₄ fluxes, with a slope of −0.21 and R² of 0.70. This relationship persisted from March to November but was absent during the winter and April. Both gases exhibited the largest diurnal variations in summer. Statistical analysis identified 16:00 as the optimal single sampling time for estimating daily mean fluxes in most months. CO₂ fluxes were primarily governed by temperature but modulated by VWC (soil volumetric water content). They were suppressed during summer drought and enhanced during winter freeze–thaw cycles. CH₄ uptake rates were strongly dependent on VWC throughout the growing season, while their temperature response underwent a reversal from positive in summer to negative in winter. Decision tree analysis revealed nonlinear threshold responses. CO₂ fluxes exhibited three temperature thresholds between 5.30 and 15.64 °C and two VWC thresholds between 0.30 and 0.42 m³ m⁻³. CH₄ fluxes showed five temperature thresholds ranging from 2.34 to 15.71 °C and seven VWC thresholds from 0.11 to 0.44 m³ m⁻³. The strongest anticorrelation between CH₄ flux and temperature occurred at intermediate VWC levels. This study provides detailed characteristics of greenhouse gas fluxes based on complete annual high-frequency data. It emphasizes the importance of year-round monitoring and offers improved sampling strategies and mechanistic insights for better flux monitoring and climate prediction. Full article

(This article belongs to the Topic Ecosystems and Climate Change: Understanding Impacts to Shape the Future)

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28 pages, 5708 KB

Open AccessArticle

Exploring the Spatiotemporal Impact of Landscape Patterns on Carbon Emissions Based on the Geographically and Temporally Weighted Regression Model: A Case Study of the Yellow River Basin in China

by Junhui Hu, Yang Du, Yueshan Ma, Danfeng Liu, Jingwei Yu and Zefu Miao

Sustainability 2025, 17(20), 9140; https://doi.org/10.3390/su17209140 - 15 Oct 2025

Viewed by 1033

Abstract

In promoting the “dual-carbon goals” and sustainable development strategy, analyzing the spatio-temporal response mechanism of landscape patterns to carbon emissions is a critical foundation for achieving carbon emission reductions. However, existing research primarily targets urbanized zones or individual ecosystem types, often overlooking how landscape pattern affects carbon emissions across entire watersheds. This research examines spatial–temporal characteristics of carbon emissions and landscape patterns in China’s Yellow River Basin, utilizing Kernel Density Estimation, Moran’s I, and landscape indices. The Geographically and Temporally Weighted Regression model is used to analyze the impact of landscape patterns and their spatial–temporal changes, and recommendations for sustainable low-carbon development planning are made accordingly. The findings indicate the following: (1) The overall carbon emissions show a spatial pattern of “low upstream, high midstream and medium downstream”, with obvious spatial clustering characteristics. (2) The degree of fragmentation in the upstream area decreases, and the aggregation and heterogeneity increase; the landscape fragmentation in the midstream area increases, the aggregation decreases, and the diversity increases; the landscape pattern in the downstream area is generally stable, and the diversity increases. (3) The number of patches, staggered adjacency index, separation index, connectivity index and modified Simpson’s evenness index are positively correlated with carbon emissions; landscape area, patch density, maximum number of patches, and average shape index are negatively correlated with carbon emissions; the distribution of areas positively or negatively correlated with average patch area is more balanced, while the spread index shows a nonlinear relationship. (4) The effects of landscape pattern indices on carbon emissions exhibit substantial spatial heterogeneity. For example, the negative impact of landscape area expands upstream, patch density maintains a strengthened negative effect downstream, and the diversity index shifts from negative to positive in the upper reaches but remains stable downstream. This study offers scientific foundation and data support for optimizing landscape patterns and promoting low-carbon sustainable development in the basin, aiding in the establishment of carbon reduction strategies. Full article

(This article belongs to the Topic Ecosystems and Climate Change: Understanding Impacts to Shape the Future)

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Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Atmosphere atmosphere	2.6	5.4	2010	20.4 Days	CHF 2400	Submit
Gases gases	-	6.5	2021	19.6 Days	CHF 1200	Submit
International Journal of Environmental Research and Public Health ijerph	-	9.8	2004	24 Days	CHF 2500	Submit
Sustainability sustainability	4.1	8.9	2009	16.9 Days	CHF 2400	Submit
Toxics toxics	4.9	7.8	2013	17 Days	CHF 2600	Submit

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