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During summer, melt ponds have a significant influence on Arctic sea-ice albedo. The melt pond fraction (MPF) also has the ability to forecast the Arctic sea-ice in a certain period. It is important to retrieve accurate melt pond fraction (MPF) from satellite data for Arctic research. This paper proposes a satellite MPF retrieval model based on the multi-layer neural network, named MPF-NN. Our model uses multi-spectral satellite data as model input and MPF information from multi-site and multi-period visible imagery as prior knowledge for modeling. It can effectively model melt ponds evolution of different regions and periods over the Arctic. Evaluation results show that the MPF retrieved from MODIS data using the proposed model has an RMSE of 3.91% and a correlation coefficient of 0.73. The seasonal distribution of MPF is also consistent with previous results.

This article considers the potential of including farmers in the governance, organization and execution of biodiversity monitoring. More specifically, we consider the opportunities for farmer involvement in biodiversity data collection through an explorative empirical analysis of the governance of biodiversity monitoring activities in agricultural landscapes within the Netherlands. We identify practical obstacles to farmer participation, assess the role of environmental NGOs in this process, and consider the extent to which this data leads to increasingly adaptive land management decisions to promote biodiversity. The governance of agri-environmental subsidy contracts with farmer collectives in the Netherlands, we conclude, could be used as an important vehicle to incentivize both biodiversity data collection and science-based land management decisions.

Abstract Milk and beef derived from pasture-based systems have been characterized by higher nutritional values and a lower environmental footprint than their equivalents obtained via indoor systems. However, intensification of pasture-based production can have adverse impacts on biodiversity and the environment. To date, studies on pro-environmental diversification options leading to improvement of environmental performance of pasture-based dairy and beef production have rarely been synthesized. The present study sought to review current on-farm pro-environmental measures with the potential for enhancing biodiversity status and/or reducing the environmental impacts of pasture-based agriculture. Literature on farmer attitudes toward these measures was also reviewed to identify potential obstacles and opportunities for transitioning to pro-environmental agriculture. A systematic search of published research from high-income island countries characterized by oceanic temperate climate with a high dependence on pasture-based agriculture—the Republic of Ireland, the United Kingdom and New Zealand, was conducted. Thirty studies that assessed the impact of pro-environmental measures, eight ‘attitudinal’ studies of dairy and beef farmers and one study covering both aspects were identified. Inductive thematical analysis was subsequently undertaken. Environmentally sensitive management practices such as hedgerows and field margins management, mixed grazing (where two or more herbivorous animals graze the same land), rare livestock breeds, multispecies swards, organic farming and agroforestry were identified as primary themes studied under the auspices of pro-environmental diversification, while forestry, bioenergy crops and organic farming were the main themes identified within attitudinal research studies. Findings suggest that environmentally sensitive practices have varied effects on biodiversity. Mixed grazing was found to improve livestock production, while studies of organic farming reported multiple positive impacts on biodiversity and animal welfare. Effect of multispecies swards on methane emissions and urinary nitrogen extraction were found to be inconsistent. Attitudinal research suggests that the main barrier to implementing afforestation is its lack of attractiveness compared to ‘traditional’ farming and that organic farmer decisions regarding agricultural management practices might be less profit-oriented and influenced by ecological beliefs to a greater extent than decisions of conventional farmers. The results of this study confirm that pro-environmental diversification inherently encompasses multiple scientific disciplines; however, previous study designs and outcomes were found to be fragmented and narrowly focused. Considering the urgency and importance of climate and biodiversity crises, pro-environmental diversification of pasture-based dairy and beef production has rarely been holistically approached and remains understudied. The development of practical, sustainable solutions for farming based on circular economy and respect to nature and additional strategies to increase farmer and consumer environmental awareness should be prioritized by policymakers, advisory and scientific bodies.

Livestock producers are under rising pressure to nourish a growing population while simultaneously reducing the impact of meat/milk production on the planets’ climate. Decision Support Tools (DST) provide a valuable evidence-based decision-making framework in agriculture to improve productivity and environmental outputs. Decision Support Tools are often developed and designed by local stakeholders and tend to represent their national system. While current DSTs may be used to examine the impact of management choices on farm emissions, there are relatively few tools available for Irish farms that take into account both the environmental and financial aspects of decision-making. This research will improve existing farm scale descision support systems designed to cost effectively mitigate Green House Gas emissions from livestock production systems.

Atmospheric ammonia (NH3) released from agriculture is contributing significantly to acidification and atmospheric NH3 may have on human health is much less readily available. The potential direct impact of NH3 on the health of the general public is under-represented in scientific literature, though there have been several studies which indicate that NH3 has a direct effect on the respiratory health of those who handle livestock. These health impacts can include a reduced lung function, irritation to the throat and eyes, and increased coughing and phlegm expulsion. More recent studies have indicated that agricultural NH3 may directly influence the early on-set of asthma in young children. In addition to the potential direct impact of ammonia, it is also a substantial contributor to the fine particulate matter (PM2.5) fraction (namely the US and Europe); where it accounts for the formation of 30% and 50% of all PM2.5 respectively. PM2.5 has the ability to penetrate deep into the lungs and cause long term illnesses such as Chronic Obstructive Pulmonary Disease (COPD) and lung cancer. Hence, PM2.5 causes economic losses which equate to billions of dollars (US) to the global economy annually. Both premature deaths associated with the health impacts from PM2.5 and economic losses could be mitigated with a reduction in NH3 emissions resulting from agriculture. As agriculture contributes to more than 81% of all global NH3 emissions, it is imperative that food production does not come at a cost to the world's ability to breathe; where reductions in NH3 emissions can be easier to achieve than other associated pollutants. Department of Agriculture, Food and the Marine

Aquaponics, one of the vertical farming methods, is a combination of aquaculture and hydroponics. To enhance the production capabilities of the aquaponics system and maximize crop yield on a commercial level, integration of Industry 4.0 technologies is needed. Industry 4.0 is a strategic initiative characterized by the fusion of emerging technologies such as big data and analytics, internet of things, robotics, cloud computing, and artificial intelligence. The realization of aquaponics 4.0, however, requires an efficient flow and integration of data due to the presence of complex biological processes. A key challenge in this essence is to deal with the semantic heterogeneity of multiple data resources. An ontology that is regarded as one of the normative tools solves the semantic interoperation problem by describing, extracting, and sharing the domains’ knowledge. In the field of agriculture, several ontologies are developed for the soil-based farming methods, but so far, no attempt has been made to represent the knowledge of the aquaponics 4.0 system in the form of an ontology model. Therefore, this study proposes a unified ontology model, AquaONT, to represent and store the essential knowledge of an aquaponics 4.0 system. This ontology provides a mechanism for sharing and reusing the aquaponics 4.0 system’s knowledge to solve the semantic interoperation problem. AquaONT is built from indoor vertical farming terminologies and is validated and implemented by considering experimental test cases related to environmental parameters, design configuration, and product quality. The proposed ontology model will help vertical farm practitioners with more transparent decision-making regarding crop production, product quality, and facility layout of the aquaponics farm. For future work, a decision support system will be developed using this ontology model and artificial intelligence techniques for autonomous data-driven decisions.

The unprecedented development, growth, and widespread pervasiveness of digital Information Communication Technologies (ICTs) have coincided with ever-increasing levels of consumption and the climate emergency. Digital ICTs, once lauded for their potential to dematerialize society, are now imposing additional burdens on the planet. The widespread consumption of personal electronics continues to grow at an enormous rate, while recycling of the scarce rare-earth minerals that are crucial to their development is negligible. As digital technologies become ubiquitous, the need for additional energy to power our ever-increasing number of digital devices and services must also keep pace. Moreover, despite their public veneer as progressives, digital tech companies are collaborating with fossil fuel companies to render oil and gas extraction more profitable and with greater speed, fuelling climate breakdown. Online social platforms are also being misused as podiums for dis/misinformation and falsehoods counter to the scientific consensus of anthropogenic climate change, allowing the digital tech sector to abdicate any social responsibility and denying the dire consequences of inaction. This review article explores the growing consumption demands and the ecological threat from digitalization and the digital tech sector: demands that will only intensify with our insatiable appetite for digital tech services and products. Such a review aims to draw closer attention to some ways such technology can be used to assist ecological research and conservation, but also to expand upon our understanding of the negative environmental aspects of a relentless push toward a Digital Society. In uncritically accepting Big Tech's virtuous credentials, we are choosing to ignore the immense power and influence they have over our lives, and the ways they may be propelling our environment toward collapse.

Turkey is a laggard in terms of the achievement of its Sustainable Development Goals (SDGs), and one of the primary issues it faces is environmental deterioration. Therefore, a policy-level reorientation may be needed to address this relevant issue. From this standpoint, this research assesses the impact of renewable energy (RE) use and financial development on the emissions of CO2 as well as the role of urbanization and agriculture, utilizing a dataset stretching between 1985 and 2019. By applying the innovative quantile-on-quantile regression (QQR) and non-parametric Granger causality in quantiles techniques, the study assesses the ways in which the quantiles of the independent variables affect the quantiles of CO2 emissions. The outcomes from the QQR show that in all quantiles, financial development, economic growth, urbanization, and agriculture impact CO2 emissions positively, while in the middle quantiles, the influence of renewable energy use on CO2 is negative. Furthermore, the outcomes from the non-parametric Granger causality test disclosed that in mean and variance, all the variables could predict CO2 emissions at different quantiles. A complete SDG-oriented policy framework has been proposed based on the research’s findings so that Turkey may move toward reaching its SDG 13 and SDG 7 targets.