Enhancing groundwater quality assessment in coastal area: A hybrid modeling approach.

Monitoring of groundwater (GW) resources in coastal areas is vital for human needs, agriculture, ecosystems, securing water supply, biodiversity, and environmental sustainability. Although the utilization of water quality index (WQI) models has proven effective in monitoring GW resources, it has faced substantial criticism due to its inconsistent outcomes, prompting the need for more reliable assessment methods. Therefore, this study addressed this concern by employing the data-driven root mean squared (RMS) models to evaluate groundwater quality (GWQ) in the coastal Bhola district near the Bay of Bengal, Bangladesh. To enhance the reliability of the RMS-WQI model, the research incorporated the extreme gradient boosting (XGBoost) machine learning (ML) algorithm. For the assessment of GWQ, the study utilized eleven crucial indicators, including turbidity (TURB), electric conductivity (EC), pH, total dissolved solids (TDS), nitrate (NO3 -), ammonium (NH4 +), sodium (Na), potassium (K), magnesium (Mg), calcium (Ca), and iron (Fe). In terms of the GW indicators, concentration of K, Ca and Mg exceeded the guideline limit in the collected GW samples. The computed RMS-WQI scores ranged from 54.3 to 72.1, with an average of 65.2, categorizing all sampling sites' GWQ as "fair." In terms of model reliability, XGBoost demonstrated exceptional sensitivity (R2 = 0.97) in predicting GWQ accurately. Furthermore, the RMS-WQI model exhibited minimal uncertainty (<1 %) in predicting WQI scores. These findings implied the efficacy of the RMS-WQI model in accurately assessing GWQ in coastal areas, that would ultimately assist regional environmental managers and strategic planners for effective monitoring and sustainable management of coastal GW resources.

Mineral fertiliser equivalent value of dairy processing sludge and derived biochar using ryegrass (Lolium perenne L.) and spring wheat (Triticumaestivum).

As supply chains of chemical fertilisers become more precarious, raw or derived bio-based fertilisers (herein referred to as bio-fertilisers) from the dairy processing industry could be good alternatives. However, their agronomic performance is relatively unknown, and where documented, the method to estimate this value is rarely presented. This pot study investigated aluminium-precipitated and calcium-precipitated dairy processing sludges (Al and Ca-DPS) and DPS-derived biochar as potential bio-fertilisers to grow ryegrass (Lolium perenne L.) and spring wheat (Triticum aestivum). The study aims were to examine how (1) application rate (optimal versus high) and (2) calculation methods (with and without chemical fertiliser response curves) can affect estimates of nitrogen and phosphorus mineral fertiliser equivalence value (N- and P-MFE) and associated agronomic advice. The results from both crops showed that for nitrogen application rates (125 or 160 kg ha-1 for ryegrass and 160 or 240 kg ha-1 for spring wheat) estimates of N-MFE increased for both Al-DPS and Ca-DPS as application rate increased. Dry matter yield response curves produced the highest % N-MFE results (e.g., ryegrass ∼50% and 70% for Al-DPS and Ca-DPS) with other calculation methods producing all similar results (e.g., ryegrass ∼20% for Al-DPS and Ca-DPS). For phosphorus application rates (40 or 80 kg ha-1 for ryegrass and 50 or 80 kg ha-1 for spring wheat), estimates of P-MFE did not increase with application rate. Negative P-MFE values obtained for Ca-DPS and DPS-biochar when growing ryegrass and spring wheat grain, respectively, indicated low plant available phosphorus. Overall, Al-DPS had better performance as a bio-fertiliser when compared to the other products tested. There was no significant difference between the two calculation methods of MFE, which suggests that the determination of MFE could be simplified by using one application as opposed to numerous application rates of fertilisers. Future work should focus on elucidating the N- and P-MFE of a wider range of DPS and STRUBIAS bio-fertilisers, and alternative methods should be investigated that enable a comparison across all bio-fertiliser types.

An examination of maximum legal application rates of dairy processing and associated STRUBIAS fertilising products in agriculture.

The dairy industry produces vast quantities of dairy processing sludge (DPS), which can be processed further to develop second generation products such as struvite, biochars and ashes (collectively known as STRUBIAS). These bio-based fertilizers have heterogeneous nutrient and metal contents, resulting in a range of possible application rates. To avoid nutrient losses to water or bioaccumulation of metals in soil or crops, it is important that rates applied to land are safe and adhere to the maximum legal application rates similar to inorganic fertilizers. This study collected and analysed nutrient and metal content of all major DPS (n = 84) and DPS-derived STRUBIAS products (n = 10), and created an application calculator in MS Excel™ to provide guidance on maximum legal application rates for ryegrass and spring wheat across plant available phosphorus (P) deficient soil to P-excess soil. The sample analysis showed that raw DPS and DPS-derived STRUBIAS have high P contents ranging from 10.1 to 122 g kg-1. Nitrogen (N) in DPS was high, whereas N concentrations decreased in thermo-chemical STRUBIAS products (chars and ash) due to the high temperatures used in their formation. The heavy metal content of DPS and DPS-derived STRUBIAS was significantly lower than the EU imposed limits. Using the calculator, application rates of DPS and DPS-derived STRUBIAS materials (dry weight) ranged from 0 to 4.0 tonnes ha-1 y-1 for ryegrass and 0-4.5 tonnes ha-1 y-1 for spring wheat. The estimated heavy metal ingestion to soil annually by the application of the DPS and DPS-derived STRUBIAS products was lower than the EU guideline on soil metal accumulation. The calculator is adaptable for any bio-based fertilizer, soil and crop type, and future work should continue to characterise and incorporate new DPS and DPS-derived STRUBIAS products into the database presented in this paper. In addition, safe application rates pertaining to other regulated pollutants or emerging contaminants that may be identified in these products should be included. The fertilizer replacement value of these products, taken from long-term field studies, should be factored into application rates.

Landspreading with co-digested cattle slurry, with or without pasteurisation, as a mitigation strategy against pathogen, nutrient and metal contamination associated with untreated slurry.

North Atlantic European grassland systems have a low nutrient use efficiency and high rainfall. This grassland is typically amended with unprocessed slurry, which counteracts soil organic matter depletion and provides essential plant micronutrients but can be mobilised during rainfall events thereby contributing to pathogen, nutrient and metal incidental losses. Co-digesting slurry with waste from food processing mitigates agriculture-associated environmental impacts but may alter microbial, nutrient and metal profiles and their transmission to watercourses, and/or soil persistence, grass yield and uptake. The impact of EU and alternative pasteurisation regimes on transmission potential of these various pollutants is not clearly understood, particularly in pasture-based agricultural systems. This study utilized simulated rainfall (Amsterdam drip-type) at a high intensity indicative of a worst-case scenario of ~11 mm hr-1 applied to plots 1, 2, 15 and 30 days after grassland application of slurry, unpasteurised digestate, pasteurised digestate (two conditions) and untreated controls. Runoff and soil samples were collected and analysed for a suite of potential pollutants including bacteria, nutrients and metals following rainfall simulation. Grass samples were collected for three months following application to assess yield as well as nutrient and metal uptake. For each environmental parameter tested: microbial, nutrient and metal runoff losses; accumulation in soil and uptake in grass, digestate from anaerobic co-digestion of slurry with food processing waste resulted in lower pollution potential than traditional landspreading of slurry without treatment. Reduced microbial runoff from digestate was the most prominent advantage of digestate application. Pasteurisation of the digestate further augmented those environmental benefits, without impacting grass output. Anaerobic co-digestion of slurry is therefore a multi-beneficial circular approach to reducing impacts of livestock production on the environment.

Arsenic contaminated groundwater and its treatment options in Bangladesh.

Arsenic (As) causes health concerns due to its significant toxicity and worldwide presence in drinking water and groundwater. The major sources of As pollution may be natural process such as dissolution of As-containing minerals and anthropogenic activities such as percolation of water from mines, etc. The maximum contaminant level for total As in potable water has been established as 10 µg/L. Among the countries facing As contamination problems, Bangladesh is the most affected. Up to 77 million people in Bangladesh have been exposed to toxic levels of arsenic from drinking water. Therefore, it has become an urgent need to provide As-free drinking water in rural households throughout Bangladesh. This paper provides a comprehensive overview on the recent data on arsenic contamination status, its sources and reasons of mobilization and the exposure pathways in Bangladesh. Very little literature has focused on the removal of As from groundwaters in developing countries and thus this paper aims to review the As removal technologies and be a useful resource for researchers or policy makers to help identify and investigate useful treatment options. While a number of technological developments in arsenic removal have taken place, we must consider variations in sources and quality characteristics of As polluted water and differences in the socio-economic and literacy conditions of people, and then aim at improving effectiveness in arsenic removal, reducing the cost of the system, making the technology user friendly, overcoming maintenance problems and resolving sludge management issues.

Optimizing feed composition for improved methane yield during anaerobic digestion of cow manure based waste mixtures.

This study investigated methane yield via anaerobic digestion of multi-component substrates based on mixtures of biodegradable single-component substrates with cow dung as main component. Bench and full-scale digestion experiments were carried out for both single and multi-component substrates to identify the relationship between methane yield and substrate composition. Results from both bench- and full-scale experiments corresponded well and showed that using multi-component substrates increases the methane yield much more than what would be expected from digestion of single substrates. Process stability as indicated by gas production, pH and NH(4)(+) concentration variations were also improved by using multi-component substrates compared to digestion of single-component substrates. The results, thus, suggest that assessment of methane yield for multi-component substrates cannot reliably be based on methane yields for corresponding single-component substrates but should instead be measured directly.