Dataset Information

Characterization Factors to Assess Land Use Impacts on Pollinator Abundance in Life Cycle Assessment.

ABSTRACT: While wild pollinators play a key role in global food production, their assessment is currently missing from the most commonly used environmental impact assessment method, Life Cycle Assessment (LCA). This is mainly due to constraints in data availability and compatibility with LCA inventories. To target this gap, relative pollinator abundance estimates were obtained with the use of a Delphi assessment, during which 25 experts, covering 16 nationalities and 45 countries of expertise, provided scores for low, typical, and high expected abundance associated with 24 land use categories. Based on these estimates, this study presents a set of globally generic characterization factors (CFs) that allows translating land use into relative impacts to wild pollinator abundance. The associated uncertainty of the CFs is presented along with an illustrative case to demonstrate the applicability in LCA studies. The CFs based on estimates that reached consensus during the Delphi assessment are recommended as readily applicable and allow key differences among land use types to be distinguished. The resulting CFs are proposed as the first step for incorporating pollinator impacts in LCA studies, exemplifying the use of expert elicitation methods as a useful tool to fill data gaps that constrain the characterization of key environmental impacts.

SUBMITTER: Alejandre EM

PROVIDER: S-EPMC9979645 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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Characterization Factors to Assess Land Use Impacts on Pollinator Abundance in Life Cycle Assessment.

Alejandre Elizabeth M EM Scherer Laura L Guinée Jeroen B JB Aizen Marcelo A MA Albrecht Matthias M Balzan Mario V MV Bartomeus Ignasi I Bevk Danilo D Burkle Laura A LA Clough Yann Y Cole Lorna J LJ Delphia Casey M CM Dicks Lynn V LV Garratt Michael P D MPD Kleijn David D Kovács-Hostyánszki Anikó A Mandelik Yael Y Paxton Robert J RJ Petanidou Theodora T Potts Simon S Sárospataki Miklós M Schulp Catharina J E CJE Stavrinides Menelaos M Stein Katharina K Stout Jane C JC Szentgyörgyi Hajnalka H Varnava Androulla I AI Woodcock Ben A BA van Bodegom Peter M PM

Environmental science & technology 20230213 8

While wild pollinators play a key role in global food production, their assessment is currently missing from the most commonly used environmental impact assessment method, Life Cycle Assessment (LCA). This is mainly due to constraints in data availability and compatibility with LCA inventories. To target this gap, relative pollinator abundance estimates were obtained with the use of a Delphi assessment, during which 25 experts, covering 16 nationalities and 45 countries of expertise, provided sc ...[more]

PMID: 36780611

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Project description:Rapid urbanization is changing the existing patterns of land use land cover (LULC) globally, which is consequently increasing the land surface temperature (LST) in many regions. The present study is focused on estimating current and simulating future LULC and LST trends in the urban environment of Chaoyang District, Beijing. Past patterns of LULC and LST were identified through the maximum likelihood classification (MLC) method and multispectral Landsat satellite images during the 1990-2018 data period. The cellular automata (CA) and stochastic transition matrix of the Markov model were applied to simulate future (2025) LULC and LST changes, respectively, using their past patterns. The CA model was validated for the simulated and estimated LULC for 1990-2018, with an overall Kappa (K) value of 0.83, using validation modules in IDRISI software. Our results indicated that the cumulative changes in built-up to vegetation area were 74.61 km2 (16.08%) and 113.13 km2 (24.38%) from 1990 to 2018. The correlation coefficient of land use and land cover change (LULCC), including vegetation, water bodies and built-up area, had values of r = - 0.155 (p > 0.005), -0.809 (p = 0.000), and 0.519 (p > 0.005), respectively. The results of future analysis revealed that there will be an estimated 164.92 km2 (-12%) decrease in vegetation area, while an expansion of approximately 283.04 km2 (6% change) will occur in built-up areas from 1990 to 2025. This decrease in vegetation cover and expansion of settlements would likely cause a rise of approximately ∼10.74 °C and ∼12.66 °C in future temperature, which would cause a rise in temperature (2025). The analyses could open an avenue regarding how to manage urban land cover patterns to enhance the resilience of cities to climate warming. This study provides scientific insights for environmental development and sustainability through efficient and effective urban planning and management in Beijing and will also help strengthen other research related to the UHI phenomenon in other parts of the world.

Dataset Information

Characterization Factors to Assess Land Use Impacts on Pollinator Abundance in Life Cycle Assessment.

Publications

Characterization Factors to Assess Land Use Impacts on Pollinator Abundance in Life Cycle Assessment.

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