Environmental and Sustainability Indicators最新文献

Understanding the dynamics of Fractional Vegetation Cover (FVC) is crucial for effective environmental monitoring and management, especially in regions like Pakistan that are sensitive to climate change. This study employs an innovative approach using MODIS NDVI data and the Pixel Dichotomy Model (PDM) to analyze the spatiotemporal dynamics of FVC across Pakistan from 2003 to 2020. Our findings reveal an overall increasing trend in FVC, with the highest value recorded in 2017 (0.37) and the lowest in 2004 (0.26). The Hurst exponent analysis (R/S ratio = 0.718) indicates a degree of long-term memory in the FVC time series. Rainfall was found to positively correlate with FVC (r = 0.6), while Land Surface Temperature (LST) and the Compounded Night Light Index (CNLI) exhibited negative correlations (r = −0.59 and r = −0.43, respectively). The Random Forest regression model highlighted CNLI as the most influential predictor (importance = 62.4%), emphasizing the need to consider human-induced factors in environmental management. These results provide critical insights for sustainable land management and contribute to understanding vegetation-climate interactions in arid and semi-arid environments."

This study aims to assess the level of sustainability in vegetable-based agrifood production systems in Benin and to propose actions to enhance sustainability, food safety, and year-round production in the vegetable production systems. Semi-structured interviews were conducted with 200 vegetable farmers in contrasting agroecological areas (with areas of extensive production of staples and intensive production of vegetables), using the “Indicateur de Durabilité des Exploitations Agricoles” (IDEA) framework (an on-farm sustainability index). Most of the surveyed vegetable farmers produced a wide range of crops, including leafy vegetables (amaranth, African eggplant, and African basil) and peppers, grown by more than 50% of the farmers. The average scores achieved by the vegetable farms regarding three dimensions of sustainability—ecological, social, and economic—were 35, 41, and 63, respectively, out of a maximum score of 100. All three sustainability dimensions of the vegetable farms were, on average, at a low level and improvements were needed for them to reach an acceptable standard. The vegetable farms located in the south of Benin had, on average, a higher sustainability score than those in the north: around 50% of vegetable farms in the south had a medium score, while the sustainability level of almost 75% of vegetable farms in the north was low. Interventions seeking to improve the sustainability of vegetable farms in Benin should focus on the promotion and adoption of eco-responsible practices that improve on-farm biodiversity, water conservation, and the effective allocation and management of land and labor, to mitigate the environmental impacts of vegetable production.

Steel production is a critical economic activity and amongst the largest industrial consumers of energy. The industry faces a complex and costly task to decarbonise in line with global climate targets. This paper evaluates the performance of environmental and emissions scores within leading Environmental, Social and Governance (ESG) ratings products in capturing carbon emissions outcomes and investment in low-carbon production amongst major steel producers. We assess data for 75 steel producers, representing 65% of global production. We find no strong evidence that environmental or emissions scores reflect either levels of, or changes in, firms’ total greenhouse gas emissions or emissions intensity in the period 2013–2022. Overall, ‘good’ scores are not explained by available emissions or investment data. These findings for a critical industry emphasise the need for methodological transparency from all ratings providers, more research into ratings’ performance in reflecting outcomes and investments, and further policies to enhance disclosures from firms and rating agencies.

Designing sustainable agricultural models is imperative to enhance farm productivity, and soil health with minimum ecological footprints. Therefore, three cropping systems viz., maize-mustard (M-Mus), maize + cowpea-mustard (M + C-Mus), pigeon pea-wheat (PP-W) were tested under four production scenarios viz., integrated organic management (IOM), integrated crop management (ICM), conventional system (CS), and conservation agriculture (CA) for three consecutive years (2018–2021) to find out the productive, soil supportive, and eco-efficient production model. The ICM recorded significantly higher system productivity i.e. 12107, 12889, and 12866 kg ha⁻¹ during 2018–19, 2019–20, and 20–21 over other production system, respectively. Among the cropping systems, the PP-W system registered the maximum system productivity of 12007.0 kg ha⁻¹ during 2018–19, 11899 kg ha⁻¹ in 2019–20, and 12247 kg ha⁻¹ during 20–21. This led to ∼15% higher average system productivity over the maize-mustard system. Nutrient (N, P, and K) acquisition was the highest by the M + C-Mus system followed by the PP-W system. All soil biological indicators considerably improved under IOM followed by ICM across the soil profile after three years. Cultivation of the PP-W system under IOM registered the highest energy use efficiency (73.24). Concerning the eco-efficiency index (EEI), cultivation of PP-W under the IOM production scenario registered ∼ 2.85 times higher EEI (0.20 US$ MJ⁻¹) over the M-Mus cropping under CS. Thus, findings inferred that legume-embedded systems under either IOM or ICM production scenarios are sustainable production models for fetching higher profitability with minimum environmental impact under semi-arid regions.