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Peatlands store up to 2320 Mt of carbon (C) on only ~20% of the land area in Ireland; however, approximately 90% of this area has been drained and is emitting up to 10 Mt C per year. Gross primary productivity (GPP) is a one of the key components of the peatland carbon cycle, and detailed knowledge of the spatial and temporal extent of GPP under changing management practices is imperative to improve our predictions of peatland ecology and biogeochemistry. This research assesses the relationship between remote sensing and ground-based estimates of GPP for a near-natural peatland in Ireland using eddy covariance (EC) techniques and high-resolution Sen-tinel 2A satellite imagery. Hybrid models were developed using multiple linear regression along with six widely used conventional indices and a light use efficiency model. Estimates of GPP using NDVI, EVI, and NDWI2 hybrid models performed well using literature-based light use efficiency parameters and showed a significant correlation from 89 to 96% with EC-derived GPP. This study also reports additional site-specific light use efficiency parameters for dry and hydrologically normal years on the basis of light response curve methods (LRC). Overall, this research has demonstrated the potential of combining EC techniques with satellite-derived models to better understand and monitor key drivers and patterns of GPP for raised bog ecosystems under different climate scenarios and has also provided light use efficiency parameters values for dry and wetter conditions that can be used for the estimation of GPP using LUE models across various site and scales. [ABSTRACT FROM AUTHOR]

A 28‐year hydrological record on four intermittent wetlands (turloughs) in a hydraulically linked karst area in the west of Ireland was used to assess ecohydrological metrics for different vegetation communities. A methodology using a combination of continuous water level monitoring and high resolution topographic surveying was used to develop a detailed hydrological model of the karst network, from which water levels at any point within the turloughs can be defined at any time during the 28‐year period (1989 to 2017). The flood conditions experienced across the spatial distributions for different vegetation communities (as mapped by a field survey) have then been collated and presented as statistical distributions for flood duration, flood depth, flood frequency and mean temperature/global radiation at the time of year in spring when the flood waters start to recede. Analysis of these four turloughs has revealed distinct differences between vegetation communities, from Eleocharis acicularis communities at the turlough base typically experiencing 6 to 7 months of inundation per year compared to the limestone pavement community at the top fringes of the turloughs only flooded from 1 to 2 months per year. An approach that used Sentinel‐2 satellite data to provide an assessment of whether there have been changes in the spatial distribution of the communities is also presented. Such metrics can be evaluated alongside other variables such as water quality (particularly nutrients), soil type and land‐use, in order to understand the habitat requirements for such plant communities and their associated ecological systems. [ABSTRACT FROM AUTHOR]

Assessing real-world emissions from buses and taxis is vital to comprehend their impact on urban air quality. Such vehicles differ significantly from the majority of the fleet owing to their higher mileage rates. However, few studies have focused on specifically assessing the emissions from this segment of the vehicle fleet. In this context, this study evaluated the real-world emissions of nitrogen oxides (NO x) from in-use buses and taxis in Dublin, Ireland, using crossroad remote sensing technology. The remote sensing system was deployed at strategic locations throughout the city to capture on-road emissions from passing vehicles. The collected data included vehicle related information such as emission standard, make, and mileage, and pollutants including NO x. Based on this data, analysis was aimed to understand the impact of Euro emission standard, ambient temperature, mileage, and make of the vehicle on NO x emissions. The results reveal that the average emissions from taxis reduce by 37% from Euro 5 to Euro 6b, and average emissions from Euro 6 buses are 87% lower compared to Euro 5. The trends in emission factors (EFs) of buses and taxis were similar during summer and winter sampling. Moreover, on comparing the emissions from the top five taxi manufacturers, different trends in the emission factors were observed. Finally, the study found that the effect of vehicle mileage on emissions was unclear for both buses and taxis. In any case, these findings provide valuable insights into the real-world emission performance of the existing fleet of buses and taxis in Dublin and highlight the need for targeted measures to reduce emissions from these vehicles. The results can assist policymakers and urban planners in formulating evidence-based strategies to improve air quality in Dublin and other cities facing similar challenges. • Evaluated real-world emissions from in-use buses and taxis in Dublin, Ireland. • On-road remote sensing technology was used to obtain NO x emission measurements. • Average emissions from taxis reduce by 37% from Euro 5 to Euro 6b. • Average emissions from Euro 6 buses are significantly lower (− 87 %) compared to Euro 5. [ABSTRACT FROM AUTHOR]

Due to the inaccessibility of many wetlands, there is a growing recognition that remote sensing techniques can be a viable and cost-effective alternative to field-based ecosystem monitoring. Wetlands encompass a diverse array of habitats, for example, fens, bogs, marshes, and swamps. In this study, we have concentrated on natural raised bogs, found in the Irish midlands. The objective of the study was to investigate the use of multispectral satellite imagery for delineating the extent of raised bogs and then monitoring their ecological composition in order to help with Ireland's obligations under the EU Habitats Directive. This was carried out using open-source Sentinel-2 data. An initial study to delineate the boundary of the bogs using the combination of edge detection techniques was performed. Once the bog boundary was defined, the spectra from the delineated area were studied. Various vegetation indices along with soil moisture information and DEM were used as features to train the classification algorithm. An ensemble classifier Bagged Tree (BT) as a supervised pixel-based learner has been used for mapping the ecotopes. In order to acknowledge the spatial distribution of the ecotopes, we partitioned the bog into ecotope-objects via graph cut segmentation also known as MAP (maximum a posteriori) estimation. The results have been verified for 5 different bog-sites using field-derived ecotope maps which has shown that the addition of spatial knowledge enhances the overall accuracy. The study further extends to investigate the scope whether it is possible to transfer the knowledge contained in the classification algorithm from one bog-wetland to other wetlands. If this is possible it would mean that other bogs could be automatically and remotely mapped. Various bog-indices highlighting special areas in the bogs under consideration were created. For bogs located in close proximity, the knowledge transfer is carried out successfully for the active regions (i.e. the major peat forming areas) using a binary-linear discriminant. The study limits to closely located bogs due to unavoidable changes in environmental conditions which in turn changes the intensity values of ecotopes in far-away locations. Such a methodology that is just being developed may be able to significantly reduce the amount of field work required by ecologists on each wetland using freely available satellite data. [ABSTRACT FROM AUTHOR]

Emissions from real-world driving are often higher than estimated emission levels based on Euro emissions standards and type-approval tests. Consequently, the air quality in cities has not improved as originally anticipated from fleet renewal and stringent emission regulations for newer vehicles. This paper presents the real-world emission factors (EFs) for in-use cars, taxis, vans, and buses obtained using on-road remote sensing in Dublin city, Ireland. EFs from both petrol and diesel Euro 6 vehicles were significantly improved compared to the EFs of older emission standard vehicles. The analyses indicated that the presence of a few high emitting older vehicles skewed the overall distribution of EFs. Detailed description of variations in EFs for individual pollutants based on changes in emission standards, location, and other driving characteristics were studied and reported, which provide justification for implementing policies targeting fleet renewal. • First study to report real-world emission factors for in-use vehicles in Ireland. • This study considers cars, taxis, vans, and buses of varying makes and models. • Decreasing trends of NO EFs for all diesel vehicles with higher Euro standards. • Strong temperature dependence of NO x emissions for Euro 4 and Euro 5 diesel cars. • Remote sensing measurements can be used to inform vehicle emission control policies. [ABSTRACT FROM AUTHOR]