Quantifying the scale of erosion along major coastal aquifers of Pakistan using geospatial and machine learning approaches.

Insufficient freshwater recharge and climate change resulted in seawater intrusion in most of the coastal aquifers in Pakistan. Coastal aquifers represent diverse landcover types with varying spectral properties, making it challenging to extract information about their state hence, such investigation requires a combination of geospatial tools. This study aims to monitor erosion along the major coastal aquifers of Pakistan and propose an approach that combines data fusion into the machine and deep learning image segmentation architectures for the erosion and accretion assessment in seascapes. The analysis demonstrated the image segmentation U-Net with EfficientNet backbone achieved the highest F1 score of 0.93, while ResNet101 achieved the lowest F1 score of 0.77. Resultant erosion maps indicated that Sandspit experiencing erosion at 3.14 km2 area. Indus delta is showing erosion, approximately 143 km2 of land over the past 30 years. Sonmiani has undergone substantial erosion with 52.2 km2 land. Miani Hor has experienced erosion up to 298 km2, Bhuri creek has eroded over 4.11 km2, east Phitii creek over 3.30 km2, and Waddi creek over 3.082 km2 land. Tummi creek demonstrates erosion, at 7.12 km2 of land, and East Khalri creek near Keti Bandar has undergone a measured loss of 5.2 km2 land linked with quantified reduction in the vertical sediment flow from 50 (billion cubic meters) to 10 BCM. Our analysis suggests that intense erosions are primarily a result of reduced sediment flow and climate change. Addressing this issue needs to be prioritized coastal management and climate change mitigation framework in Pakistan to safeguard communities. Leveraging emerging solutions, such as loss and damage financing and the integration of nature-based solutions (NbS), should be prioritized for the revival of the coastal aquifers.

Potential to reduce pesticides in intensive apple production through management practices could be challenged by climatic extremes.

Apples are the third most produced fruit in the world, but their production is often pesticide-intensive. Our objective was to identify options for pesticide reduction using farmer records from 2549 commercial apple fields in Austria during five years between 2010 and 2016. Using generalized additive mixed modeling, we examined how pesticide use was related to farm management, apple varieties, and meteorological parameters, and how it affected yields and toxicity to honeybees. Apple fields received 29.5 ± 8.6 (mean ± SD) pesticide applications per season at a rate of 56.7 ± 22.7 kg ha-1, which included a total of 228 pesticide products with 80 active ingredients. Over the years, fungicides accounted for 71 % of the pesticide amounts applied, insecticides for 15 %, and herbicides for 8 %. The most frequently used fungicides were sulfur (52 %), followed by captan (16 %) and dithianon (11 %). Of insecticides, paraffin oil (75 %) and chlorpyrifos/chlorpyrifos-methyl (6 % combined) were most frequently used. Among herbicides, glyphosate (54 %), CPA (20 %) and pendimethalin (12 %) were most often used. Pesticide use increased with increasing frequency of tillage and fertilization, increasing field size, increasing spring temperatures, and drier summer conditions. Pesticide use decreased with increasing number of summer days with maximum temperatures >30 °C and number of warm, humid days. Apple yields were significantly positively related to the number of heat days, warm humid nights, and pesticide treatment frequency, but were not affected by frequency of fertilization and tillage. Honeybee toxicity was not related to insecticide use. Pesticide use and yield were significantly related to apple varieties. Our analysis shows that pesticide use in the apple farms studied can be reduced by less fertilization and tillage, partly because yields were >50 % higher than the European average. However, weather extremes related to climate change, such as drier summers, could challenge plans to reduce pesticide use.

Unexpected air pollutants with potential human health hazards: Nitrification inhibitors, biocides, and persistent organic substances.

To better understand the influence of land use and meteorological parameters on air pollutants, we deployed passive air samplers in 15 regions with different land use in eastern Austria. The samplers consisted of polyurethane PUF and polyester PEF filter matrices, which were analyzed for 566 substances by gas-chromatography/mass-spectrometry. In a previous article, we highlighted a widespread contamination of ambient air with pesticides that depends on the surrounding land use and meteorological parameters. Here we report that, in addition to agricultural pesticides, eight other substances were frequently detected in ambient air: Nitrapyrin, a nitrification inhibitor used to increase nitrogen use efficiency of fertilizers and banned in Austria since 1993; biocides against insects (DEET and transfluthrin) used mainly outside agriculture; piperonyl butoxide (PBO), a synergist mixed into pesticide formulations; and four industrially used polychlorinated biphenyls (PCBs), long banned worldwide. Concentrations of the detected substances were positively related to air temperature, but only slightly related to agricultural land use in the sampler's vicinity. The city center showed the highest concentrations of biocides, PCBs and PBO, but also medium concentrations of nitrapyrin. Four sites had no air contamination with these substances; including two national parks dominated by grassland or forest, but also two sites with mixed land use. The potential human toxicity of the detected substances based on globally harmonized hazard classifications was high: seven substances had specific organ toxicity, six were cancerogenic, and two were acutely toxic; however, several substances had incomplete information of hazard profiles. Moreover, all substances were acutely and chronically toxic to aquatic life. We recommend that substances of different origins be included in the air pollution monitoring portfolio to comprehensively assess the potential hazards to humans and the environment.

SECURES-Met: A European meteorological data set suitable for electricity modelling applications.

The modelling of electricity production and demand requires highly specific and comprehensive meteorological data. One challenge is the high temporal frequency as electricity production and demand modelling typically is done with hourly data. On the other side the European electricity market is highly connected, so that a pure country-based modelling is not expedient and at least the whole European Union (EU) area has to be considered. Additionally, the spatial resolution of the data set must be able to represent the thermal conditions, which requires high spatial resolution at least in mountainous regions. All these requirements lead to huge data amounts for historic observations and even more for climate change projections for the whole 21st century. Thus, we have developed the aggregated European wide climate data set SECURES-Met that has a temporal resolution of one hour, covers the whole EU area and other selected European countries, has a reasonable size but considers the high spatial variability.

Pesticides in ambient air, influenced by surrounding land use and weather, pose a potential threat to biodiversity and humans.

Little is known about (i) how numbers and concentrations of airborne pesticide residues are influenced by land use, interactions with meteorological parameters, or by substance-specific chemo-physical properties, and (ii) what potential toxicological hazards this could pose to non-target organisms including humans. We installed passive air samplers (polyurethane PUF and polyester PEF filter matrices) in 15 regions with different land uses in eastern Austria for up to 8 months. Samples were analyzed for 566 substances by gas-chromatography/mass-spectrometry. We analyzed relationships between frequency and concentrations of pesticides, land use, meteorological parameters, substance properties, and season. We found totally 67 pesticide active ingredients (24 herbicides, 30 fungicides, 13 insecticides) with 10-53 pesticides per site. Herbicides metolachlor, pendimethalin, prosulfocarb, terbuthylazine, and the fungicide HCB were found in all PUF samplers, and glyphosate in all PEF samplers; chlorpyrifos-ethyl was the most abundant insecticide found in 93% of the samplers. Highest concentrations showed the herbicide prosulfocarb (725 ± 1218 ng sample-1), the fungicide folpet (412 ± 465 ng sample-1), and the insecticide chlorpyrifos-ethyl (110 ± 98 ng sample-1). Pesticide numbers and concentrations increased with increasing proportions of arable land in the surroundings. However, pesticides were also found in two National Parks (10 and 33 pesticides) or a city center (17 pesticides). Pesticide numbers and concentrations changed between seasons and correlated with land use, temperature, radiation, and wind, but were unaffected by substance volatility. Potential ecotoxicological exposure of mammals, birds, earthworms, fish, and honeybees increased with increasing pesticide numbers and concentrations. Human toxicity potential of detected pesticides was high, with averaged 54% being acutely toxic, 39% reproduction toxic, 24% cancerogenic, and 10% endocrine disrupting. This widespread pesticide air pollution indicates that current environmental risk assessments, field application techniques, protective measures, and regulations are inadequate to protect the environment and humans from potentially harmful exposure.

Storylines of combined future land use and climate scenarios and their hydrological impacts in an Alpine catchment (Brixental/Austria).

In this paper, the hydrological impacts of future socio-economic and climatic development are assessed for a regional-scale Alpine catchment (Brixental, Tyrol, Austria). Therefore, coupled storylines of future land use and climate scenarios were developed in a transdisciplinary stakeholder process by means of questionnaire analyses and interviews with local experts from various relevant societal sectors. Resulting future land use maps for each decade were used as spatial input in the hydrological model WaSiM, to which a new module for the consideration of snow-canopy interaction processes has been added. Simulation results for three developed storylines, each combined with a moderate (A1B) and an extreme (RCP8.5) climate future, show that in a warmer and dryer climate the amount of annual simulated streamflow at the gauge of the catchment undergoes a significant reduction. The (mainly natural) reforestation of the catchment - caused by abandonment of previously cultivated areas - leads to additional losses of water by enhanced interception and evapotranspiration processes. Further cultivation of the current mountain pasture areas has a certain potential to attenuate undesirable long-term impacts of climate change on the catchment water balance.

Inequalities between degree- and distance-based graph invariants.

Inequalities provide a way to study topological indices relatively. There are two major classes of topological indices: degree-based and distance-based indices. In this paper we provide a relative study of these classes and derive inequalities between degree-based indices such as Randic connectivity, GA, ABC, and harmonic indices and distance-based indices such as eccentric connectivity, connective eccentric, augmented eccentric connectivity, Wiener, and third ABC indices.

On Eccentric Connectivity Index of TiO2 Nanotubes.

The eccentric connectivity index (ECI) is a distance based molecular structure descriptor that was recently used for mathematical modeling of biological activities of diverse nature. The ECI has been shown to give a high degree of predictability compare to Wiener index with regard to diuretic activity and anti-inflammatory activity. The prediction accuracy rate of ECI is better than the Zagreb indices in case of anticonvulsant activity. Titania nanotubular materials are of high interest metal oxide substances due to their widespread technological applications. The numerous studies on the use of this material also require theoretical studies on the other properties of such materials. Recently, the Zagreb indices were studied of an infinite class of titania (TiO2) nanotubes [32]. In this paper, we study the eccentric connectivity index of these nanotubes.