Publications by authors named "Wulahati Adalibieke"

Food consumption contributes to the degradation of air quality in regions where food is produced, creating a contrast between the health burden caused by a specific population through its food consumption and that faced by this same population as a consequence of food production activities. Here we explore this inequality within China's food system by linking air-pollution-related health burden from production to consumption, at high levels of spatial and sectorial granularity. We find that low-income groups bear a 70% higher air-pollution-related health burden from food production than from food consumption, while high-income groups benefit from a 29% lower health burden relative to their food consumption.

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Denitrification plays a critical role in soil nitrogen (N) cycling, affecting N availability in agroecosystems. However, the challenges in direct measurement of denitrification products (NO, N O, and N ) hinder our understanding of denitrification N losses patterns across the spatial scale. To address this gap, we constructed a data-model fusion method to map the county-scale denitrification N losses from China's rice fields over the past decade.

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Nitrogen (N) is an important nutrient for crop growth. However, the overuse of N fertilizers has led to a series of devastating global environmental issues. Recent studies show that multiple datasets have been created for agricultural N fertilizer application with varied temporal or spatial resolutions, nevertheless, how to synchronize and use these datasets becomes problematic due to the inconsistent temporal coverages, spatial resolutions, and crop-specific allocations.

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The impacts of low soil moisture (SM) and high vapour pressure deficit (VPD) on tree's photosynthesis and productivity are ultimately realized by changing water content in the canopy leaves. In this study, variations in canopy water content (CWC) that can be detected from microwave remotely sensed vegetation optical depth (VOD) have been proposed as a promising measure of vegetation water status, and we first reported that the regulation of CWC on productivity stability is universally applicable for global forests. Results of structural equation model (SEM) also confirmed the significant negative effect of CWC on coefficient of variation (CV) of productivity, indicating that the decrease in CWC could inevitably induce the instability of forest productivity under climate change.

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Changes in land use intensity and types can affect the structure and function of ecosystems, and thus ecosystem services (ESs) as well as their interactions. However, the impacts of changes in land use intensity on ESs remain poorly understood. Through four different land use scenarios, we distinguished the independent contribution of changes in agricultural land use intensity and types to grain production (GP), water purification (WP), and their trade-offs in the Dongting Lake Basin.

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Agricultural soils are the largest anthropogenic emission source of nitrous oxide (NO). National agricultural policies have been implemented to increase crop yield and reduce nitrogen (N) losses to the environment. However, it is difficult to effectively quantify crop-specific and regional NO mitigation priorities driven by policies, due to lack of long-term, high-resolution crop-specific activity data, and oversimplified models.

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Mitigating soil nitrous oxide (NO) emissions is essential for staying below a 2 °C warming threshold. However, accurate assessments of mitigation potential are limited by uncertainty and variability in direct emission factors (EFs). To assess where and why EFs differ, we created high-resolution maps of crop-specific EFs based on 1,507 georeferenced field observations.

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Cropland ammonia (NH ) emission is a critical driver triggering haze pollution. Many agricultural policies were enforced in past four decades to improve nitrogen (N) use efficiency while maintaining crop yield. Inadvertent reductions of NH emissions, which may be induced by such policies, are not well evaluated.

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Reducing ammonia (NH) volatilization from croplands while satisfying the food demand is strategically required to mitigate haze pollution. However, the global pattern of NH volatilization remains uncertain, primarily because of the episodic nature of NH volatilization rates and the high variation of fertilization practices. Here, we improve a global estimate of crop-specific NH emissions at a high spatial resolution using an updated data-driven model with a survey-based dataset of the fertilization scheme.

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