Leveraging the water-environment-health nexus to characterize sustainable water purification solutions.

Chemicals of emerging concern (CECs) pose critical threats to both public health and the environment, emphasizing the urgent need for effective water treatment measures. Yet, the implementation of such intervention technologies often results in increased energy consumption and adverse environmental consequences. Here, we employ a comprehensive methodology that integrates multiple datasets, assumptions, and calculations to assess the human health and environmental implications of removing various CECs from source water.

A critical review of heat pump adoption in empirical and modeling literature.

Household electrification is an important pillar of decarbonization in the US and requires the rapid adoption of electric heat pumps. Household energy models that project adoption rates do not represent these decisions well. To what extent are they limited by fundamental knowledge gaps, or is there scope to incorporate insights from the social science literature? We review the energy modeling and social science literature on heating equipment adoption to synthesize our understanding of adoption decisions, to identify best practices on representing decision-making behavior among energy models, and to suggest model improvements.

Can spatial self-organization inhibit evolutionary adaptation?

Plants often respond to drier climates by slow evolutionary adaptations from fast-growing to stress-tolerant species. These evolutionary adaptations increase the plants' resilience to droughts but involve productivity losses that bear on agriculture and food security. Plants also respond by spatial self-organization, through fast vegetation patterning involving differential plant mortality and increased water availability to the surviving plants.

Learning, economies of scale, and knowledge gap effects on power generation technology cost improvements.

Cost reductions are essential for accelerating clean technology deployment. Because multiple factors influence costs, traditional one-factor learning models, solely relying on cumulative installed capacity as an explanatory variable, may oversimplify cost dynamics. In this study, we disentangle learning and economies of scale effects at unit and project levels and introduce a knowledge gap concept to quantify rapid technological change's impact on costs.

A principle-based framework to determine countries' fair warming contributions to the Paris Agreement.

Equity is a cornerstone of global climate policy, yet differing perspectives mean that international agreement on how to allocate mitigation efforts remains elusive. A rich literature informs this question, but a gap remains in approaches that appropriately consider non-CO emissions and their warming contributions. In this study, we address this gap and define a global warming budget applicable to all anthropogenic greenhouse gases that is allocated to countries based on principles drawn from international treaties and environmental law.

Can ecosystem services supply match local residents' perception: Linking macro-ESs and micro-individual perceptions in the Yellow River Basin.

Residents' satisfaction perceptions of ecosystem services (ESs) are essential for the ecological protection and high-quality development of the Yellow River Basin (YRB). Existing studies lacks large-scale survey of local residents' satisfaction perception at urban scale within river basins, and has not effectively explored the matching relationship between the ESs supply and the perceptions of local residents. To address this gap, this study develops a database on nine ESs supply and individual perceptions of the YRB, constructs a comprehensive framework to quantify the matching of ESs supply and local residents' satisfaction perceptions, and proposes targeted strategy.

Uncertainties around net-zero climate targets have major impact on greenhouse gas emissions projections.

Globally, more than 100 countries have adopted net-zero targets. Most studies agree on how this increases the chance of keeping end-of-century global warming below 2°C. However, they typically make assumptions about net-zero targets that do not capture uncertainties related to gas coverage, sector coverage, sinks, and removals.

An eco-physiological model of forest photosynthesis and transpiration under combined nitrogen and water limitation.

Although the separate effects of water and nitrogen (N) limitations on forest growth are well known, the question of how to predict their combined effects remains a challenge for modeling of climate change impacts on forests. Here, we address this challenge by developing a new eco-physiological model that accounts for plasticity in stomatal conductance and leaf N concentration. Based on optimality principle, our model determines stomatal conductance and leaf N concentration by balancing carbon uptake maximization, hydraulic risk and cost of maintaining photosynthetic capacity.

A dataset of structural breaks in greenhouse gas emissions for climate policy evaluation.

The quantitative assessment of policies aimed at climate change mitigation requires rigorously identifying abnormal changes in greenhouse gas emissions. We present a new dataset of robust level changes in greenhouse gas emissions that cannot be explained by aggregate socioeconomic fluctuations. Modern methods of structural break identification based on two-way fixed effects models are employed to estimate the size of significant level changes in emissions.

Regional Trends and Spatial Gradients of Total Column Methane over India, China, and USA─Implications for Emissions from Coal Mining and Oil/Gas Exploitation.

Observation-based verification of regional/national methane (CH) emission trends is crucial for transparent monitoring and mitigation strategy planning. Although surface observations track the global and sub-hemispheric emission trends well, their sparse spatial coverage limits our ability to assess regional trends. Dense satellite observations complement surface observations, offering a valuable means to validate emission trends, especially in regions where emissions changes are substantial but debated.

The utility of the Living Planet Index as a policy tool and for measuring nature recovery.

The Living Planet Index (LPI) is a leading global biodiversity indicator based on vertebrate population time series. Since it was first developed over 25 years ago, the LPI has been widely used to indicate trends in biodiversity globally, primarily reported every two years in the Living Planet Report. Based on relative abundance, a sensitive metric of biodiversity change, the LPI has also been applied as a tool for informing policy and used in assessments for several multilateral conventions and agreements, including the Convention on Biological Diversity 2010 Biodiversity Target and Aichi targets.

Contributions of countries without a carbon neutrality target to limit global warming.

Bioenergy with carbon capture and storage (BECCS) is a key negative emission technology for climate mitigation. Some countries have made no commitment to carbon neutrality but are viewed as potential BECCS candidates (hereafter, non-CN countries). Here we analyze contributions of these countries to global climate mitigation with respect to BECCS using an Earth system model with explicit representations of bioenergy crops.

Heterogeneities in landed costs of traded grains and oilseeds contribute to unequal access to food.

Despite the growing accessibility of international grain and oilseed markets, high production costs and trade frictions are still prevalent, contributing to regional heterogeneities in the landed cost of grain imports. Here we quantify the landed cost for six grain commodities across 3,500 administrative regions, capturing regional cost differences to produce grain and transport it across international borders. We find large heterogeneities in the costs of imported grain, which are highest in Oceania, Central America and landlocked Africa.

Modeling Hydrogen Markets: Energy System Model Development Status and Decarbonization Scenario Results.

Hydrogen can be used as an energy carrier and chemical feedstock to reduce greenhouse gas emissions, especially in difficult-to-decarbonize markets such as medium- and heavy-duty vehicles, aviation and maritime, iron and steel, and the production of fuels and chemicals. Significant literature has been accumulated on engineering-based assessments of various hydrogen technologies, and real-world projects are validating technology performance at larger scales and for low-carbon supply chains. While energy system models continue to be updated to track this progress, many are currently limited in their representation of hydrogen, and as a group they tend to generate highly variable results under decarbonization constraints.

Revisiting the role of education in attitudes toward immigration in different contexts in Europe.

Unlabelled: Among the individual determinants of attitudes toward immigration, the liberalising role of education is well known-those with higher levels of education tend to be more in favour of immigration. However, recent socioeconomic changes and idiosyncratic differences between European countries prompt us to reassess the role of education, given these contextual differences. Does it still apply, and is it universal? Moreover, does this relationship apply to both cultural and economic attitudes toward immigration? Using data from the European Social Survey, we analyse the role of education and socioeconomic changes in shaping economic and cultural attitudes toward immigration in 15 European countries over 16 years using a hierarchical model with cross-classified random effects.

Socioeconomic inequalities in depression and the role of job conditions in China.

Background: The rising prevalence of depression in China, coupled with a tightening job market, highlights concern for the workforce's mental health. Although socioeconomic inequalities in depression have been well documented in high-income countries, the association between socioeconomic status (SES) and depression, along with its work-related mediators, has not been sufficiently studied in China.

Methods: The study participants are 6,536 non-agriculturally employed working adults from the 2020 China Family Panel Studies (CFPS).

Social conditions of smallholder dairy farmers influence their environmental decisions.

The objective of this study is to characterize the social conditions for making agricultural decisions. Particular attention is paid to sustainable agricultural practices in dairy farming. The theoretical framework has been developed around two major explicatory perspectives: sustainable development and quality of life.

A dataset of income distribution on provincial, urban, and rural levels for China from 2020 to 2100.

Projections of future income distributions at subnational levels are becoming increasingly important for a variety of analyses and evaluations. However, relevant datasets are currently limited. This study presents a methodological framework that introduces machine learning algorithms to a top-down approach used for generating income distribution datasets.

The association of temperature extremes, ecosystem resilience, with child mortality: Novel evidence from India.

The present study investigates how ecosystem resilience affects children's health and acts as a protective shield against high temperature exposure. Ecosystem resilience is the ability of an ecosystem to absorb anthropogenic or climatic shocks and recover from those shocks. The study used various data sources to estimate the impact of temperature extremes on child mortality in India.

Metapopulation heterogeneities in host mobility, productivity, and immunocompetency always increase virulence and infectiousness.

The epidemiology and evolution of diseases unfold in populations that are rarely homogeneous. Instead, hosts infected by pathogens often form metapopulations, in which local populations connected by the movement of hosts experience different demographic and epidemiological conditions. Here, we develop a general theory of the evolution of pathogens in heterogeneous metapopulations.

Understanding Uncertainty in Market-Mediated Responses to US Oilseed Biodiesel Demand: Sensitivity of ILUC Emission Estimates to GLOBIOM Parametric Uncertainty.

The life cycle greenhouse gas (GHG) emissions of biofuels depend on uncertain estimates of induced land use change (ILUC) and subsequent emissions from carbon stock changes. Demand for oilseed-based biofuels is associated with particularly complex market and supply chain dynamics, which must be considered. Using the global partial equilibrium model GLOBIOM, this study explores the uncertainty in market-mediated impacts and ILUC-related emissions from increasing demand for soybean biodiesel in the United States in the period 2020-2050.

Annual 30-m maps of global grassland class and extent (2000-2022) based on spatiotemporal Machine Learning.

The paper describes the production and evaluation of global grassland extent mapped annually for 2000-2022 at 30 m spatial resolution. The dataset showing the spatiotemporal distribution of cultivated and natural/semi-natural grassland classes was produced by using GLAD Landsat ARD-2 image archive, accompanied by climatic, landform and proximity covariates, spatiotemporal machine learning (per-class Random Forest) and over 2.3 M reference samples (visually interpreted in Very High Resolution imagery).

Drivers of environmental externality reduction in China's electric power industry: A spatial-temporal analysis.

China's electric power industry has made significant efforts to reduce environmental externality in the past two decades. However, the extent of the reduction, the driving factors behind it, and the regional performance are not well clarified. This study constructs a comprehensive framework that integrates the impact pathway approach with index decomposition analysis to explore the driving factors behind the reduction of environmental externality from a spatial-temporal perspective.

Future land carbon removals in China consistent with national inventory.

China's commitment to carbon neutrality by 2060 relies on the Land Use, Land-Use Change, and Forestry (LULUCF) sector, with forestation targets designed to enhance carbon removal. However, the exact sequestration potential of these initiatives remains uncertain due to differing accounting conventions between national inventories and scientific assessments. Here, we reconcile both estimates and reassess LULUCF carbon fluxes up to 2100, using a spatially explicit bookkeeping model, state-of-the-art historical data, and national forestation targets.