Optimizing Watershed Land Use to Achieve the Benefits of Lake Carbon Sinks while Maintaining Water Quality DOI

R.-Q. Wang,

Peng Deng, Xiangang Hu

et al.

Environmental Science & Technology, Journal Year: 2025, Volume and Issue: unknown

Published: May 6, 2025

Greenhouse gas emissions and water quality decline are two major issues currently affecting lakes worldwide. Determining how to control both greenhouse is a long-term challenge. We compiled data on the annual average carbon dioxide (CO2) flux parameters for 422 global lakes, revealing that 82.42% of act as sources 66.56% have experienced deterioration. Carbon eutrophication trends were observed from 1990s 2020s, with further deterioration expected over next 80 years. Unmanaged land use change in lake watersheds could exacerbate CO2 into degradation. In this study, watershed planning (WLUP) framework was established, 24.83% reduction water, 5.07% chlorophyll (Chl-a), 4.70% total phosphorus, 12.92% increase Secchi depth achieved. The WLUP identifies Asia Europe regions experiencing greatest demands transformation, where optimization leads most significant improvements. Metagenomic analysis revealed forests enhance fixation grasslands reduce degradation phosphorus metabolism watersheds, explaining supporting possibility WLUP. This work provides win-win solution improving fluxes mitigate effects climate promote protection.

Language: Английский

Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data DOI Creative Commons
Rana Waqar Aslam, Hong Shu, Iram Naz

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(5), P. 928 - 928

Published: March 6, 2024

Wetlands provide vital ecological and socioeconomic services but face escalating pressures worldwide. This study undertakes an integrated spatiotemporal assessment of the multifaceted vulnerabilities shaping Khinjhir Lake, ecologically significant wetland ecosystem in Pakistan, using advanced geospatial machine learning techniques. Multi-temporal optical remote sensing data from 2000 to 2020 was analyzed through spectral water indices, land cover classification, change detection risk mapping examine moisture variability, modifications, area changes proximity-based threats over two decades. The random forest algorithm attained highest accuracy (89.5%) for classification based on rigorous k-fold cross-validation, with a training 91.2% testing 87.3%. demonstrates model’s effectiveness robustness vulnerability modeling area, showing 11% shrinkage open bodies since 2000. Inventory zoning revealed 30% present-day areas under moderate high vulnerability. cellular automata–Markov (CA–Markov) model predicted continued long-term declines driven by swelling anthropogenic like 29 million population growth surrounding Lake. research integrating satellite analytics, algorithms spatial generate actionable insights into guide conservation planning. findings robust baseline inform policies aimed at ensuring health sustainable management Lake wetlands human climatic that threaten functioning these ecosystems.

Language: Английский

Citations

41
Toward sustainable development goals 7 and 13: A comprehensive policy framework to combat climate change DOI
Kashif Raza Abbasi, Qingyu Zhang, Badr Saad Alotaibi

et al.

Environmental Impact Assessment Review, Journal Year: 2024, Volume and Issue: 105, P. 107415 - 107415

Published: Jan. 18, 2024

Language: Английский

Citations

35
Soil microplastics: Impacts on greenhouse gasses emissions, carbon cycling, microbial diversity, and soil characteristics DOI
Ismail Khan, Muhammad Tariq, Khulood Fahad Alabbosh

et al.

Applied Soil Ecology, Journal Year: 2024, Volume and Issue: 197, P. 105343 - 105343

Published: Feb. 26, 2024

Language: Английский

Citations

27
From resource curse to green growth: Exploring the role of energy utilization and natural resource abundance in economic development DOI
Muhammad Imran, Md Shabbir Alam, Jijian Zhang

et al.

Natural Resources Forum, Journal Year: 2024, Volume and Issue: unknown

Published: April 16, 2024

Abstract This study delves into the profound repercussions of resource curse hypothesis within Brazil, Russia, India, China, and South Africa (BRICS) nations from 1991 to 2022, examining intricate interplay among natural abundance, energy consumption, economic development (ED). Methodologically, it employs cross‐sectionally augmented Dickey–Fuller test assess stationarity utilizes Westerlund cointegration technique analyze cointegration. Subsequently, autoregressive distributive lag model is deployed explore impact availability, renewable non‐renewable utilization, carbon emissions on ED these countries. The findings reveal a stark reality wherein both consumption wield consistently positive influence short‐ long‐term growth across BRICS economies. Particularly striking dominant consumption. However, this comes in contrast adverse effects identified with excessive coal rents, signifying potential setbacks arising rampant exploitation. Furthermore, suboptimal utilization resources hints at detrimental effect ED. These results transcend confines developing nations, underscoring universality hypothesis, affecting developed illuminates grave risks inherent overreliance overexploitation resources, elucidating heightened competition that severely impedes trajectory countries short long terms. Policymakers must prioritize diversification, implement sustainable management, invest innovative technologies mitigate fostering resilience growth. In conclusion, highlights severe stressing imperative for adept management counter linked overdependence bolster

Language: Английский

Citations

16
Urban engineering insights: Spatiotemporal analysis of land surface temperature and land use in urban landscape DOI Creative Commons
Bo Shu, Yang Chen,

Kai-xiang Zhang

et al.

Alexandria Engineering Journal, Journal Year: 2024, Volume and Issue: 92, P. 273 - 282

Published: March 7, 2024

In the field of urban environment engineering, understanding relationship between land surface temperature (LST) and use cover (LULC) is essential in rapidly growing climatically unstable landscapes such as Chengdu. It helps alleviate magnitude intensity Urban Heat Islands (UHIs). Toward this aim, summer winter Landsat images were acquired four years from 1992 to 2021 used extract LULC classes, LST three indices Normalized Difference Vegetation Index (NDVI), Built-up (NDBI), Modified Water (MNDWI) analyze their spatiotemporal associations. Results showed that built-up areas expanded approximately six times (820.82 Km2, 584.96%) 2021. Meanwhile, mean increased both seasons, by 9.94 °C 0.95 winter. The LST-NDBI correlation was significant positive studied (0.437< r <0.874, p=0.00) while a very high variability observed LST-NDVI (-0.835< <0.255, LST-MNDWI (-0.632< <0.628, coefficients. According results, NDBI can be good intra- inter-annual predictor Chengdu, especially context its fast-paced physical expansion increasing UHI.

Language: Английский

Citations

13
Assessment of land use change and carbon emission: A Log Mean Divisa (LMDI) approach DOI Creative Commons
Liang Wang

Heliyon, Journal Year: 2024, Volume and Issue: 10(3), P. e25669 - e25669

Published: Feb. 1, 2024

Changes in land use have a notable influence on carbon emissions since they can affect the levels of stored both soil and vegetation. To effectively analyze factors influencing from change, Log Mean Divisa (LMDI) method is commonly employed. The LMDI decomposition analysis that dissects changes into different factors, including shifts patterns, population growth, economic activity, energy intensity. This approach enables identification specific drivers emission development targeted policy interventions to address them. explore relationship between emissions, method, case study be conducted. involves selecting particular region or country experiencing change examining driving these transformations. Subsequently, applied decompose within selected country, thereby pinpointing major contributors changes. In our study, we observed necessity regulating consumption greenhouse gas urban communities through sustainable practices technologies. research highlighted variations consumption, renewable utilization, public transportation usage among cities China. Moreover, demonstrated patterns their associated alongside findings analysis, which explored based patterns. illuminates importance understanding employing as valuable analytical tool. It underscores significance technologies mitigating areas provides insights role shaping outcomes.

Language: Английский

Citations

12
Assessing the Impacts of Eco-innovations, Economic Growth, Urbanization on Ecological Footprints in G-11: Exploring the Sustainable Development Policy Options DOI
Usman Mehmood

Journal of the Knowledge Economy, Journal Year: 2024, Volume and Issue: unknown

Published: Feb. 6, 2024

Language: Английский

Citations

10
Unraveling the ecological threads: How invasive alien plants influence soil carbon dynamics DOI
Abdulkareem Raheem,

Paul Yohanna,

Guanlin Li

et al.

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 356, P. 120556 - 120556

Published: March 26, 2024

Language: Английский

Citations

10
Daily scale air quality index forecasting using bidirectional recurrent neural networks: Case study of Delhi, India DOI

Chaitanya B. Pande,

Nand Lal Kushwaha, Omer A. Alawi

et al.

Environmental Pollution, Journal Year: 2024, Volume and Issue: 351, P. 124040 - 124040

Published: April 27, 2024

Language: Английский

Citations

10
Spatial distribution, pollution level and human health risk assessment of heavy metals in urban street dust at neighbourhood scale DOI Creative Commons
Öznur Işınkaralar, Kaan Işınkaralar, Tuyet Nam Thi Nguyen

et al.

International Journal of Biometeorology, Journal Year: 2024, Volume and Issue: 68(10), P. 2055 - 2067

Published: July 2, 2024

Abstract Urban street dust (UStD) is a vital issue for human health and crucial urban sustainability. This study aims to enhance the creation of safe, affordable, resilient cities by examining environmental contamination risks in residential areas. Specifically, it investigates concentrations spatial distribution chromium (Cr), cadmium (Cd), nickel (Ni), copper (Cu), lead (Pb), zinc (Zn) UStD Yenimahalle, Ankara. The mean Zn, Cr, Pb, Cd, Ni, Cu were 97.98, 66.88, 55.22, 52.45, 38.37, 3.81 mg/kg, respectively. geoaccumulation pollution index (Igeo) values these elements were: Cd (5.12), Ni (1.61), Cr (1.21), Pb (1.13), (0.78), Zn (0.24). These indices indicate that area moderately polluted with uncontaminated contaminated extremely Cd. hazard (HI) Cu, below non-carcinogenic risk threshold adults, indicating no significant risk. However, children, HI 3.37, 1.80, 1.25, respectively, suggesting higher Carcinogenic (RI) was both children exposure through ingestion, inhalation, dermal contact hazardous. findings highlight need strategic mitigation measures natural anthropogenic activities, providing essential insights residents, policymakers, stakeholders, planners.

Language: Английский

Citations

10