Environments, Volume 10, Issue 10 (October 2023) – 22 articles

With the increase in population, large amounts of food waste are produced worldwide every day. These leftovers can be used as a source of lignocellulosic waste, oils, and polysaccharides for renewable fuels. In a fixed bed reactor, low-temperature catalytic pyrolysis was investigated using biomass gathered from domestic garbage. Thermogravimetry, under N₂ flow, was used to assess the pyrolysis behavior of tea and coffee grounds, white potato, sweet potato, banana peels, walnut, almonds, and hazelnut shells. A mixture of biomass was also evaluated by thermogravimetry. Waste inorganic materials (marble, limestone, dolomite, bauxite, and spent Fluid Catalytic Cracking (FCC) catalyst) were used as catalysts (16.7% wt.) in the pyrolysis studies at 400 °C in a fixed bed reactor. Yields of bio-oil in the 22–36% wt. range were attained. All of the catalysts promoted gasification and a decrease in the bio-oil carboxylic acids content. The marble dust catalyst increased the bio-oil volatility. The results show that it is possible to valorize lignocellulosic household waste by pyrolysis using inorganic waste materials as catalysts. Full article

For arsenic decontamination from groundwater, arsenic crystallization is becoming adopted due to its sustainability and economic benefits. However, arsenic crystallization technology is a two-step process, which makes it complex and generates hazardous waste. Successful efforts toward making it a single-step process are presented here. The addition of nanorods and ball-milled zinc sulfide nanoparticles to arsenic-contaminated water result in highly monodispersed and high-arsenic-containing mineralized nanowaste with a crystalline structure similar to the mineral Tooeleite ((Fe³⁺₆(As³⁺O₃)₄SO₄(OH)₄·4H₂O)). This study reports the results of a short-term stability test based on a toxicity characteristic leaching procedure and a long-term stability test of the mineralized synthetic nanowaste produced from water treatment. The Tooeleite-like mineralized nanowaste passed short-term stability tests. Arsenic in the leachate were found to be 1.1 ± 0.2 mg L⁻¹ and 4.8 ± 0.3 mg L⁻¹ from waste generated by the nanorod and ball-milled nanoparticles, respectively. The crystallinity was well preserved, as observed from the post-stability-test diffraction patterns, consequently proving that the waste product can be non-hazardous and therefore would not require any secondary treatment before final disposal. Full article

Aerobic denitrifier Alcaligenes faecalis No. 4 removes ammonium-nitrogen to nitrogen gas via denitrification in a single aerobic condition. In our previous studies, factors such as ammonium removal rate, denitrification ratio, and cell growth were tested in various conditions. The removal pathway from ammonium to nitrogen gas still needs to be determined in detail. To clarify this pathway of Alcaligenes faecalis No. 4, we in this study investigated the effects of several factors on ammonium removal, such as foam-recycle, initial pH, initial ammonium concentration, and airflow rate. Denitrification ratio was improved by up to 23% through foam-recycle. The improvement of the denitrification ratio was resulted by the higher enzyme activity of hydroxylamine oxidoreductase (HAO) in the produced foam, which was about 28 times higher than that in the culture broth (i.e., without foam-recycle). The stripped ammonia was significantly high (above pH 9). The initial ammonium concentration and airflow rate also influenced the denitrification ratio. Full article

In the European Union List of Wastes, the category of “mirror entry” waste refers to either hazardous or non-hazardous waste, depending on their composition and specificity. Classifying waste as hazardous or non-hazardous is essential because it influences the feasibility and economic viability of subsequent management methods. Thus, waste classification represents a challenge both for the scientific community and for the producers/holders of waste. The methodology presented in this paper describes the stages that are the basis for evaluating the dangerousness of “mirror entry” waste and the potential factors that influence the evaluation process. Three case studies that represented three types of industrial waste were selected: waste from the non-metallic minerals industry (W1), waste from glass manufacturing (W2), and waste from the iron and steel industry (W3). The case studies were characterized and evaluated according to hazardous properties and the assignment of a waste code. The W1 and W2 waste samples did not present the hazardous properties HP1–HP15 and were included in the non-hazardous waste list. The W3 waste sample exhibited five dangerous properties and was classified as hazardous waste. The assessed wastes maintain the classifications as long as there are no changes in the technological process generation and in their composition. Full article

Small airborne particulate contaminants such as mould spores can harm human health by causing or exacerbating respiratory illnesses. Such particulates tend to be microscopic; however, in the case of moulds, contamination can be associated with visible colonial growth on surfaces and musty odours detectable by occupants of the room. Shared spaces, such as offices and classrooms, represent areas of higher risk due to the larger numbers of people being exposed to airborne particulates. To better appreciate the health risks associated with airborne particulates, it is therefore advantageous to assess the levels of breathable particulates in a room and compare them with the proportion of particulates represented by mould spores. An air image sensor machine was used to collect PM_2.5 particulate levels for three urban-campus classrooms and three semi-urban-campus classrooms during different wintertime (August) days in New Zealand. For each room, a settle-plate method was also used to compare background mould levels at breathing height for seated occupants. Three of the classrooms had been recently built or renovated with an adequate ventilation system installed, while the remaining three classrooms were not upgraded and had no evidence of a ventilation system. The results indicated that the classrooms in the new building, located at the semi-urban campus, tended to have lower levels of particulate matter PM_2.5 compared with the urban classrooms, which had not been upgraded. However, the semi-urban classrooms tended to have higher mould counts than the urban spaces. Moreover, the building envelope for both new and old classrooms tended to be porous, with indoor PM_2.5 readings increasing in step with outdoor PM_2.5 readings. This study will assist in identifying new approaches to reduce the risk of particulate-related respiratory issues associated with urban teaching spaces, particularly those buildings requiring more sustainable technologies to purify the air and improve the indoor air quality (IAQ). Full article

Stormwater outfalls are frequently listed as sources of microplastic (MP) contamination into aquatic systems. To date, few studies have been undertaken to determine if stormwater outfalls are MP hotspots in estuaries. This study compared the surface waters adjacent to and at least one kilometer away from stormwater outfalls of a subtropical estuarine system: the Indian River Lagoon (IRL) on the east coast of Florida, USA. Citizen scientists collected water samples monthly for 12 months from stormwater outfalls (n = 24) and control sites (n = 6). Overall, 958 MPs were identified from 1800 L of water, with the most found in the fall months during hurricane season. Stormwater outfalls (mean: 0.53 MP/L) were found to discharge smaller MPs (GLM: p = 0.0008) in significantly higher amounts compared to control sites (GLM: p = 0.02), documenting stormwater as a point-source pollutant in this system. Two types of stormwater outfalls drained into the IRL—closed culverts and open drainage channels—with no difference in MP abundances between the two (GLM: p = 0.60). Microfibers dominated collections (89%). Using ATR-FTIR for polymer identification, 80% of the materials found were plastic; polypropylene (29%), polyethylene (18%), and polyethylene terephthalate (18%) were the most abundant polymers found. Full article

Blue holes are submarine karst cavities with chemical and physical characteristics of the water column completely different from those in the surrounding environment. In this study a multi-parameter probe was used, for the first time, to characterise the water column of the Blue Hole of Faanu Madugau (Ari Atoll, Maldives, 3°55.799′ E 72°56.469′ N), the only blue hole described in the Indian Ocean up to date. Measurements of the temperature, salinity, dissolved oxygen, turbidity, chlorophyll-α, photosynthetically active radiation, potential density, pH, and H₂S were obtained with a high detail. Three distinct physical–chemical layers were identified from the surface up to 70 m depth. An intermediate and turbid layer, located between 40 m and 46 m depth, sharply separates the upper layer displaying water characteristics equal to those of the outside environment from the deep and more characteristic layer of the blue hole, where a unique environment can be observed. Waters are oxygenated, warm, and rich in chlorophyll-α in the upper layer, whilst waters are anoxic, colder, denser, and completely dark, with low pH values and high H₂S content in the deep layer. The Blue Hole of the Maldives represents an extreme environment from a geological, oceanographic, biological, and ecological point of view. Further investigations will be thus required to understand the origin of the Blue Hole waters, the mechanisms that keep it isolated from the external environment, the influence of weather and marine forcing on it, and how climate change may impact it. Full article

Agricultural plastic mulching is an important horticultural process for increasing crop yields because it preserves soil moisture, soil temperature, and nutrients, and avoids the need for weed herbicides. However, there are risks to using plastic mulch, since residual macroplastic (MaP), microplastic (MP), and nanoplastic (NP) in fields have a significant negative impact on the environment, causing damage to soil properties, harming microorganisms in the soil, and entering the human body via the food chain. Plastic mulch is often disposed of in landfills or used in techniques like the thermal process to gain energy or recycling to generate plastic granules for the plastic industry. Pretreatments are occasionally required before recycling, such as cleaning the mulch from the soil to fit the recycling process. This review provides an overview of the quantities and negative impacts of plastic, especially plastic mulch films after use, as well as their decomposition products, on the environment, soil, and human health, and presents alternatives. The possibilities and problems of collecting and recycling films are discussed in addition to the alternatives, for example, the use of biodegradable films. Overall, agricultural advancements to reduce plastic waste in the environment by using thicker films, collection after use, and recycling in developed countries are on a good path. However, NP poses a risk, as it is still completely unclear how it affects human health. Alternatives to plastic mulch have found little acceptance so far due to the significantly higher material costs. Full article

Red claw crayfish Cherax quadricarinatus has emerged as a highly significant and suitable species to be raised in integrated rice–aquatic animal farming systems. To optimize an integrated aquaculture and agriculture (IAA) system and ensure sustainable utilization and development of land resources, an IAA system combining rice cultivation with red claw crayfish culture was implemented to assess the impacts of rice–red claw crayfish co-culturing on the dynamics and assembly of bacterial communities in paddy soils. We established two experimental groups, each with eight replicates. We utilized 16S rRNA Illumina high-throughput sequencing to access the bacterial community composition and assembly in paddy soils. Red claw crayfish C. quadricarinatus cultivation did not significantly affect the alpha diversity of the bacterial community in the paddy field, but it obviously increased the relative abundances of the phyla Acidobacteriota and Pseudomonadota involved in organic matter degradation and nitrogen, phosphorus, and carbon cycling. Red claw crayfish cultivation could lead to more complex bacterial communities, increased bacterial resistance to disturbances, the promotion of niche differentiation, and increased competition intensity between bacterial communities during the mid-cultivation period. Nitrogen emerged as a critical factor influencing the bacterial community composition in paddy soil during the culture period, and the red claw crayfish cultivation affected the bacterial community by altering the ammonia concentration in the paddy soil. As the culture progressed, the assembly of the bacterial community in the paddy soil was predominantly driven by stochastic processes, and red claw crayfish cultivation accelerated the evolution of the bacterial community assembly towards a stochastic process. Our study offers valuable insights into the dynamic changes occurring in the composition and assembly of bacterial communities in paddy soils in response to red claw crayfish cultivation. Full article

Transformer load losses cause various adverse effects, such as derating, a decreased lifetime, and greenhouse gas emissions. In this paper, the load losses caused by non-linear loads on distribution transformers are analyzed. For this study, the load loss expressions provided by the IEEE Standard C57.110 and ANSI/UL 1561-1562 were adapted to the usual case where the transformer currents differ in each phase. The novel load loss expressions adapted from the IEEE Standard C57.110 were applied using the software known as the “Transformer Loss Calculator” (TLC), implemented with LabVIEW. For the application of new load loss expressions, carbon dioxide (CO₂) emissions were determined by multiplying the load losses by the emission factors of each country. The experimental results are based on the recordings made by a FLUKE 435 Series II analyzer on the second of two 1000 kVA transformers, feeding real residential distribution networks with very differently distorted loads. An analysis of these transformers shows that the annual energy losses and CO₂ emissions obtained from the adapted load loss expressions could be more than 5% of those determined by the original IEEE and ANSI Standard expressions. Due to these percentage loss and emission differences, it is advisable to use the TLC software in transformer monitoring instruments. Full article

Nitrogen (N) is the essential plant nutrient needed by turfgrass in the greatest quantity. Urea and urea-based liquids are arguably the safest, least expensive, and subsequently most popular soluble N fertilizers. Unfortunately, urea fertilizer application to turfgrass is often subject to NH₃ volatilization: a deleterious phenomenon from both environmental and agronomic perspectives. The objective of this research was to quantify the efficacy of creeping bentgrass (Agrostis stolonifera L.) golf course fairway foliar fertilization by urea-based N fertilizers as influenced by a petroleum-derived spray oil (PDSO) containing Cu II phthalocyanine colorant (Civitas Turf Defense^TM Pre-M1xed, Intelligro LLC, Mississauga, ON, Canada). In 2019 and 2020, a maintained creeping bentgrass fairway received semimonthly 9.76 kg ha^–1 soluble N treatment either alone or in combination with Civitas at a rate of 27 L ha^–1. In the 48 h following foliar application, fertilizer N loss as NH₃ ranged from 1.3 to 5.5% and corresponded directly to fertilizer urea content but not Civitas inclusion. In the 1 to 14 d following semimonthly treatment, Civitas had either a beneficial (methylol urea and UAN) or negligible (urea) effect on canopy mean dark green color index. Once cumulative N inputs exceeded 47 kg ha^–1, creeping bentgrass fairway shoot growth and N nutrition were consistently increased by Civitas complementation of commercial liquid N fertilizer. Over the 2-yr study, absolute mean percent fertilizer N recovery from plots treated by Civitas-complemented foliar liquid N treatment exceeded their ’N only’ counterparts by 8.7%. Full article

The impact of chain length on the sorption of anionic PFAS by soils and sediments was investigated by aggregating and synthesizing data sets from the literature. Quantitative structure/property relationship (QSPR) analysis was applied to characterize the influence of molecular size and soil properties on sorption. The log of the organic carbon-normalized equilibrium sorption coefficient (K_oc) exhibited a biphasic relationship with molar volume, wherein the log K_oc values for the short-chain PFAS were generally greater than would be predicted using the QSPR correlation determined for the long-chain PFAS. This enhanced differential sorption is observed to different degrees for all studies, which are compiled and synthesized for the first time. The results reveal remarkable congruency across a wide array of soils comprising a large range of properties and indicate that the observed enhanced differential sorption of short-chain PFAS is a prevalent phenomenon. Aggregating the long-chain PFAS data for all soils and sediments with organic carbon contents > 1% produced a strong correlation, indicating that the resultant QSPR model can produce representative log K_oc values irrespective of the other properties of the medium. Silt+clay content was shown to be an important soil component for the short-chain PFAS for most soils, as well as the long-chain PFAS for soils with organic carbon contents < 1%. The results indicate that while the simple K_oc-f_oc approach may produce reasonable estimates of K_d values for long-chain anionic PFAS, particularly for soils and sediments with larger organic carbon contents, it is unlikely to do so for short-chain anionic PFAS. Full article

The strain of red microalgae Galdieria sulphuraria CCMEE 5587.1 was evaluated in a controlled laboratory environment for its ability to tolerate and remove two heavy metal (HM) ions: cadmium [Cd(II)] and lead [Pb(II)] in aqueous solutions as a single metal species. Various concentrations (0 mg L⁻¹ to 5 mg L⁻¹) of Cd and Pb ions were added to the Cyanidium medium in which the chosen microalgae strain G. sulphuraria CCMEE 5587.1 was grown at an acidic pH of 2.5. The effectiveness of G. sulphuraria CCMEE 5587.1 in tolerating and removing these two metal ions was measured by analyzing its growth profile, growth rate, nutrient removal, and metal ion removal efficiency. The growth of G. sulphuraria CCMEE 5587.1 was inhibited during the initial days of incubation, and the growth rate decreased when the HM concentration in the media was increased. Nutrient removal in the HM-containing media is comparable to that in the control media at low metal concentrations but decreases as the metal concentration rises. G. sulphuraria CCMEE 5587.1 has the highest removal efficiency for Cd and Pb in a medium containing 2.5 mg L⁻¹ of metal ions, which is 49.80% and 25.10%, and the corresponding sorption capacity is 1.45 mg g⁻¹ and 0.53 mg g⁻¹ of dry biomass, respectively. These findings suggest that G. sulphuraria CCMEE 5587.1 holds potential as a viable bioremediation solution for extracting Cd and Pb from wastewater, alongside its capacity to remove nutrients concurrently. The study underscores the dual advantage of G. sulphuraria CCMEE 5587.1, making it a promising candidate for addressing heavy metal pollution in wastewater treatment processes. Full article

This study investigated whether surface soil organic carbon (SOC) content could be estimated using hyperspectral data provided by the Italian Space Agency PRISMA satellite. We collected 100 representative topsoil samples in an area of 30 × 30 Km² in the province of Ferrara (Northern Italy), estimated their SOC content and other soil properties through thermo-gravimetric analysis, and matched these to the spectra of the sampled areas that were measured by PRISMA on 7 April 2020. A tentative model was created for SOC estimation using ordinary least-squares (OLS) regression and an artificial neural network (ANN). Repeated k-fold cross-validation of the OLS and ANN models yielded R² values of 0.64 and 0.49, respectively. The performance of the models was inferior to that obtained from the literature using similar modeling techniques in relatively small areas (up to 3 × 3 Km²) and characterized by restricted SOC variability (0.2–2.1 wt%). However, our data were collected over a wider area with high SOC content variability (0.7–9.3 wt%); consequently, significant variations were observed over a spatial scale of just a few meters. Therefore, this work shows the importance of testing remote sensing techniques for SOC measurements in more complex areas than those reported in the existing literature. Furthermore, our study sheds light on the geolocation errors and missing data of PRISMA. Full article

The present work was aimed at investigating the possibility to produce bricks using volcanic ash from the Etna volcano and with photoluminescent properties. The volcanic ash was analyzed using X-ray diffractometry, scanning electron and energy dispersive X-ray microscopy. Mixtures with 0%, 10% and 30% of volcanic ash were prepared and fired at 950 °C for 14 h. Their mechanical properties, dynamic modulus of elasticity, drying linear retraction, capillary water absorption and water absorption were measured. The obtained results show that increasing the percentage of volcanic ash in the initial mixture results in a decrease in the measured dynamic modulus of elasticity, in a greater dimensional stability and in a lower weight loss upon firing. Mechanical properties are negatively affected by volcanic ash, with a compressive strength of 11 MPa obtained with mixtures with 30% of it. A decrease in the absorption of water was also observed upon increasing the amount of volcanic ash in the mixes. Brick surfaces with intense photoluminescent activity were obtained. The produced bricks meet the criteria required by the for bricks that can be used in normal weathering and absorption criteria for second-class brick. Full article

In this study, activated carbon was suitably modified with Mg/Si/La and its effectiveness in removing As(III) was investigated. The structure of Magnesium/Silica/Lanthamum@Activated Carbon (Mg-Si-La@AC) was fully characterized and several parameters, such the dosage, pH, contact time, and initial As(III) concentration, were studied. Thus, the BET surface area, total pore volume, and micropore volume of Mg-Si-La@AC were measured to be 271.46 m²/g, 0.006 cm³/g and 0.52 cm³/g, respectively. The results showed that the optimal condition for the reduction in As(III) from the initial concentration of 100 μg/L to below 10 μg/L was the addition of 1.5 g/L of adsorbent at pH 7.0. Furthermore, 4 h of contact time showed >90% removal. The Langmuir isotherm model was best fitted to the experimental results, exhibiting a maximum adsorption capacity of 322 μg/g, and the PSO kinetic model was found to be the most applicable according to kinetics. Consecutive regeneration studies were carried out and the results showed that the adsorbent was effectively used up to four cycles. Full article

This review paper adopts bibliometric and meta-analysis approaches to explore the application of supervised machine learning regression models in satellite-based water quality monitoring. The consistent pattern observed across peer-reviewed research papers shows an increasing interest in the use of satellites as an innovative approach for monitoring water quality, a critical step towards addressing the challenges posed by rising anthropogenic water pollution. Traditional methods of monitoring water quality have limitations, but satellite sensors provide a potential solution to that by lowering costs and expanding temporal and spatial coverage. However, conventional statistical methods are limited when faced with the formidable challenge of conducting pattern recognition analysis for satellite geospatial big data because they are characterized by high volume and complexity. As a compelling alternative, the application of machine and deep learning techniques has emerged as an indispensable tool, with the remarkable capability to discern intricate patterns in the data that might otherwise remain elusive to traditional statistics. The study employed a targeted search strategy, utilizing specific criteria and the titles of 332 peer-reviewed journal articles indexed in Scopus, resulting in the inclusion of 165 articles for the meta-analysis. Our comprehensive bibliometric analysis provides insights into the trends, research productivity, and impact of satellite-based water quality monitoring. It highlights key journals and publishers in this domain while examining the relationship between the first author’s presentation, publication year, citation count, and journal impact factor. The major review findings highlight the widespread use of satellite sensors in water quality monitoring including the MultiSpectral Instrument (MSI), Ocean and Land Color Instrument (OLCI), Operational Land Imager (OLI), Moderate Resolution Imaging Spectroradiometer (MODIS), Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), and the practice of multi-sensor data fusion. Deep neural networks are identified as popular and high-performing algorithms, with significant competition from extreme gradient boosting (XGBoost), even though XGBoost is relatively newer in the field of machine learning. Chlorophyll-a and water clarity indicators receive special attention, and geo-location had a relationship with optical water classes. This paper contributes significantly by providing extensive examples and in-depth discussions of papers with code, as well as highlighting the critical cyber infrastructure used in this research. Advances in high-performance computing, large-scale data processing capabilities, and the availability of open-source software are facilitating the growing prominence of machine and deep learning applications in geospatial artificial intelligence for water quality monitoring, and this is positively contributing towards monitoring water pollution. Full article

The pressure of nutrient pollution derived from wastewater treatment works and agricultural runoff is a reason for the decline in the ecological health of aquatic habitats. Projected residential development in catchments creates further nutrient loading that can be offset by nutrient management solutions that maintain ‘nutrient neutrality’ either onsite or elsewhere within the same catchment. This study developed an export coefficient model in conjunction with detailed farm business data to explore a nature-based solution to nutrient neutrality involving seven scenarios of crop conversion to mixed woodland or grazing grass in an area of intensive arable cultivation in the groundwater-fed Blackwater sub-catchment of the River Wensum, UK. When compared with the monitored riverine export of nutrients, the calculated nitrogen (N) and phosphorus (P) inputs under current land use showed that subsurface denitrification is removing 48–78% of the leached N and that P is accumulating in the field soils. The addition of 235 residential homes planned for 2018–2038 in the Blackwater will generate an additional nutrient load of 190 kg N a⁻¹ and 4.9 kg P a⁻¹. In six of the seven scenarios, the modelled fractions of crop conversion (0.02–0.21) resulted in the required reduction in P loading and more than sufficient reduction in N loading (196–1874 kg a⁻¹ for mixed woodland and 287–2103 kg a⁻¹ for grazing grass), with the additional reduction in N load above the requirement for nutrient neutrality potentially contributing to further improvement in water quality. The cost of land conversion is modelled in terms of crop gross margins and nutrient credits generated in the form of 0.1 kg units of N or P. For the range of scenarios considered, the annual cost per credit ranged from GBP 0.78–11.50 for N for mixed woodland (GBP 0.74–7.85 for N for grazing grass) and from GBP 160–782 for P for both scenarios. It is concluded that crop conversion is a viable option to achieve nutrient neutrality in arable catchments in eastern England when considered together with other nutrient management solutions. Full article

Taiwan is located at the junction of plates in which the stratum is relatively unstable, resulting in frequent earthquakes. Driftwood has always been regarded as a precious asset that enables ecoscientists to track earthquakes. In the event of a typhoon or heavy rain, the surface water flows to flush the woods from the hills to the coast. More specifically, a large rainfall or earthquake may cause floods and collapses, and the trees in the forest will be washed down. Therefore, this study used high-resolution images to build an image database of the new north coast of Taiwan, and a deep learning approach is incorporated to classify the driftwoods. To improve the interpretation of driftwood in the remote images, we initially import eight pieces of textured information which are employed to the raw bands (B, G, R, and IR). The usage of spatial information image extraction technology is incorporated into a deep learning analysis using two parallel approaches. The generative adversarial network (GAN) is used to analyze the color images alongside an ancillary image with texture information. Most of the salt–pepper effects are produced by applying a high-resolution thematic map, and an error matrix is generated to compare the differences between them. The raw data (original R + G + B + IR) images, when analyzed using GAN, have about 70% overall classification outcomes. Not all of the driftwood can be detected. By applying the texture information to the parallel approach, the overall accuracy is enhanced to 78%, and about 80% of the driftwood can be recognized. Full article

Recent EU circular economy, bioeconomy policies and the New Green Deal promote the recycling of organic wastes into soil improvers and fertilisers, thereby reducing the use of mineral fertilisers. This has renewed interest in the use of compost and digestate as fertilisers. At the same time, the Russian invasion of Ukraine has strengthened the demand for sustainable domestic fertilisers to guarantee the security of supply. It is now more important than ever that quality standards in Ireland are fit for the purpose of aiding the sustainable local production of fertilisers. Quality standards for compost and digestate ensure and protect the environment. This study collated the results of the analysis of Irish compost and digestate samples and made comparisons of the Irish data to databases, reports and standards from other countries, including the EU Fertiliser Products Regulation 2019/1009. This paper, therefore, provides comprehensive information on heavy metal, stability and phytotoxicity standards from a number of European and other countries. In addition, it includes actual data on these parameters from Ireland and a few European countries. From this collation and comparison process, we propose to update the heavy metals and stability limits in the Irish compost standard (IS 441) and heavy metals and stability limits in a new digestate standard (whole, liquid and fibre). Our methodology and collated data can be used as templates for countries, especially in Europe, which have not developed their own standards. Having an updated compost quality standard supports the development of a circular economy while still respecting the precautionary principle of avoiding pollution when compost and digestate are used on the soil. Full article

Climate dictates the critical aspects of human environmental conditions. The frequency and intensity of extreme weather conditions due to human-induced climate change have alarmingly increased. Consequently, climate change directly affects environmental sustainability and human mortality in the short term and creates prolonged and complicated long-term indirect grave risks. This paper examines three-level environmental impact risks associated with climate change on human mortality. It proposes a conceptual framework for developing an empirical event-based human mortality database related to climate change and communication strategies to enhance global environmental adaptation, resilience, and sustainability. Full article