Ecosystems and Climate Change: Understanding Impacts to Shape the Future

Topic Information

Dear Colleagues,

This topic explores the intersection of environmental chemistry, human health, and climate change, focusing on how climate shifts influence the presence, behavior, fate, and distribution of anthropogenic substances across all environmental compartments—air, soil, sediment, water, and biota. It welcomes both experimental studies and literature reviews, with a dual emphasis on mitigation and adaptation strategies. Technological innovations applicable to large-scale environmental challenges and climate disaster response will also be featured.

A distinctive aspect of this issue is its holistic perspective, addressing critical processes such as bioconcentration, bioaccumulation, biomagnification, biotransformation, and the environmental fate of pollutants. It will also delve into contaminant dynamics, environmental processes, ecotoxicology, and toxicological impacts, all viewed through the lens of climate change.

By re-examining established topics with a climate-focused perspective, the Topic seeks to advance understanding of how environmental and chemical stressors affect both ecosystems and human health. It aligns with the journal’s mission to support sustainable development, offering timely insights and scientific contributions to pressing global issues.

Prof. Dr. Pasquale Avino
Dr. Mario Lovrić
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Atmosphere atmosphere	2.3	4.9	2010	16.9 Days	CHF 2400	Submit
Gases gases	-	5.4	2021	27.5 Days	CHF 1000	Submit
Sustainability sustainability	3.3	7.7	2009	19.3 Days	CHF 2400	Submit
Toxics toxics	4.1	6.4	2013	18.1 Days	CHF 2600	Submit
International Journal of Environmental Research and Public Health ijerph	-	8.5	2004	27.8 Days	CHF 2500	Submit

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Published Papers (1 paper)

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All Atmosphere Gases Sustainability Toxics IJERPH

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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 113

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 [...] Read more.

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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