It is the key point to reveal the effect of irrigation water and fertilization conditions on the agriculture non-point pollution in the paddy field. In this study, the estimation model of agricultural non-point source pollution loads at field scale was established on the basis of agricultural drainage irrigation model and combined with pollutant concentration predication model. Based on the estimation model of agricultural non-point source pollution in the field and experimental data, the load of agricultural non-point source pollution in different irrigate amount and fertilization schedule in paddy field was calculated. The results showed that the variation of field drainage varies greatly under different irrigation conditions, and there is an “inflection point” between the irrigation water amount and field drainage amount. The non-point pollution load increased with the increase of irrigation water and showed a significant power correlation. Under the different irrigation condition, the increase amplitude of non-point pollution load with the increase of irrigation water was different. When the irrigation water is smaller, the non-point pollution load increase relatively less, and when the irrigation water increased to inflection point, the non-point pollution load will increase considerably. In addition, there was a positive correlation between the fertilization and non-point pollution load. The non-point pollution load had obvious difference in different fertilization schedule even with same fertilization level, in which the fertilizer pollution load increased the most in the period of turning green to tillering. The results provide some basis for the field control and management of agricultural non-point source pollution.

The electrochemical conversion of inorganic nitrogen forms (i.e., NO₃⁻-N, NO₂⁻-N, and NH₄⁺-N) to N₂ was studied using Ti as cathode and Ti/PbO₂ as anode in the simulated wastewater. According to linear sweep voltammetry, nitric nitrogen was effectively converted to N₂ on Ti cathode at the working potential more negative than − 1.1 V (vs. SCE). Ti/PbO₂ anode had the working potential of + 0.8 V (vs. SCE) for NH₄⁺-N converted to N₂. The apparent rate constants of NO₃⁻-N to NO₂⁻-N and NO₂⁻-N to N₂ were 2.46 × 10⁻² min⁻¹ and 4.03 × 10⁻² min⁻¹, respectively. The kinetic analyses revealed that the reduction of NO₃⁻-N was a two-step process, and NO₂⁻-N was an unstable intermediate, which could be easily oxidized to NO₃⁻-N or reduced to NH₄⁺-N. The majority of NH₄⁺-N could be effectively converted to N₂ on Ti/PbO₂ anode with the apparent rate constants of 5.12 × 10⁻² min⁻¹. The dual-chamber (DC) reactor with circulation was used in the batch electrolysis of simulated and actual wastewater. The results verified the pathways of NH₄⁺-N oxidation and NO₃⁻-N reduction and achieved high conversion rate of total nitrogen (TN) to N₂.

Phosphorus (P) is a significant limiting nutrient which is essential for all forms of lives. However, phosphate rock reserves are depleting rapidly due to population growth. At the same time, several countries have imposed legislative regulations on P-release into surface waters due to eutrophication. Nutrient recovery from wastewater can facilitate a sustainable, cost-effective and environment-friendly source of phosphorus. Although P-recovery as struvite from wastewater has been widely studied for a long time, there still exists a lot of challenges for widespread full-scale implementation. This paper presents a comprehensive analysis of the current state of the technologies for phosphorus recovery in the form of struvite. Fluidized bed reactors (FBRs) are widely used compared to continuously stirred reactors for P-recovery as struvite because of different solid and liquid retention time. Commercially available technologies were reported to accomplish about 80% P-removal efficiencies with a reasonable P-recovery for the most of the cases. The struvite production rate of various technologies varies from 0.89 to 13.7 kg/kg influent P. Nevertheless, these technologies are associated with several shortcomings such as high operational costs, high energy consumption, and large footprint. Increasing efforts focusing on the development of sustainable and commercially feasible technologies are expected in this sector as P-recovery is considered to be the future of wastewater engineering.

Over the past years, there were dramatic improvements in identifying and assessing various feedstocks for the production of biodiesel fuels. To promote a particular feedstock as a renewable source of energy, it is important to analyze their energy, economic, and engine performance characteristics. The current work attempts to evaluate the net energy and economic indices for both fossil diesel and coconut-blended diesel (B20) considering the diesel consumption by the Indian railways. Further, we present the experimental results of a multi-cylinder diesel engine operated with neat coconut biodiesel (B100) and fossil diesel at various load and speed conditions. The engine experiments reveal that the coconut biodiesel exhibits leaner combustion and shorter ignition delay than fossil diesel. Lower amount of carbon monoxide, hydrocarbon, and smoke emission is observed in the case of coconut biodiesel, with higher levels of nitric oxide (14%) and fuel consumption than diesel. The coefficient of variation in indicated mean effective pressure is within the range of better driveability zone for both the fuels at all test conditions. Overall the engine performance, emission and combustion results with neat coconut biodiesel are favorable with a penalty in NO emission at high load conditions. The techno-economical study highlights higher production cost per liter of B20 than the cost of fossil diesel. However, the net energy ratio (NER) for B20 is 1.021, favoring higher output than diesel and thus lowers the dependency on crude oil.

Leachate is one of the main surface water pollution sources in Selangor State (SS), Malaysia. The prediction of leachate amounts is elementary in sustainable waste management and leachate treatment processes, before discharging to surrounding environment. In developing countries, the accurate evaluation of leachate generation rates has often considered a challenge due to the lack of reliable data and high measurement costs. Leachate generation is related to several factors, including meteorological data, waste generation rates, and landfill design conditions. The high variations in these factors lead to complicating leachate modeling processes. This study aims at identifying the key elements contributing to leachate production and developing various AI-based models to predict leachate generation rates. These models included Artificial Neural Network (ANN)-Multi-linear perceptron (MLP) with single and double hidden layers, and support vector machine (SVM) regression time series algorithms. Various performance measures were applied to evaluate the developed model’s accuracy. In this study, input optimization process showed that three inputs were acceptable for modeling the leachate generation rates, namely dumped waste quantity, rainfall level, and emanated gases. The initial performance analysis showed that ANN-MLP2 model—which applies two hidden layers—achieved the best performance, then followed by ANN-MLP1 model—which applies one hidden layer and three inputs—while SVM model gave the lowest performance. Ranges and frequency of relative error (RE%) also demonstrate that ANN-MLP models outperformed SVM models. Furthermore, low and peak flow criterion (LFC and PFC) assessment of leachate inflow values in ANN-MLP model with two hidden layers made more accurate values than other models. Since minimizing data collection and processing efforts as well as minimizing modeling complexity are critical in the hydrological modeling process, the applied input optimization process and the developed models in this study were able to provide a good performance in the modeling of leachate generation efficiently.

Ecosystem-based management is one of the strategies to protect the coastal areas. One of the key elements is phytoplankton community composition since it represents a good indicator of anthropogenic pressures. This identifies the seasonal patterns of phytoplankton, and its alterations by the stress factors induced by human activities are highly valuable. This research represents the first attempt to study that 476 km of western Mediterranean coastal belongs to the Valencian Community (Spain) based on the phytoplankton composition approach. The water samples during a 5-year period (6757 water samples) were taken to determine its phytoplankton group’s dynamics and its relationship with anthropogenic stressors by means of a series of plots and statistical analyses. Diatoms are the group that most contribute to the whole community composition with two periods of maximum abundance. The Prasinophyceae and Cryptophyceae show unimodal patterns varying its maximum values depending on the season. The picocyanobacteria group exhibited the clearest and best-defined pattern. Other groups have no clear seasonal pattern and become abundant in areas of higher anthropogenic pressure. Graphical abstract Figure A contains poor quality of text in image. Otherwise, please provide replacement figure file.A new graphical abstract, with higher quality is attached.

The study presented the occurrence of antibiotics in 16 different hospital effluents, the removal of antibiotics in urban wastewater treatment plant (WWTP), and the potential ecotoxicological risks of the effluent discharge on the aquatic ecosystem. The total concentration of antibiotics in hospital effluents was ranged from 21.2 ± 0.13 to 4886 ± 3.80 ng/L in summer and from 497 ± 3.66 to 322,735 ± 4.58 ng/L in winter. Azithromycin, clarithromycin, and ciprofloxacin were detected the highest concentrations among the investigated antibiotics. The total antibiotic load to the influent of the WWTP from hospitals was 3.46 g/day in summer and 303.2 g/day in winter. The total antibiotic contribution of hospitals to the influent of the WWTP was determined as 13% in summer and 28% in winter. The remaining 87% in summer and 72% in winter stems from the households. The total antibiotic removal by conventional physical and biological treatment processes was determined as 79% in summer, whereas it decreased to 36% in winter. When the environmental risk assessment was performed, azithromycin and clarithromycin in the effluent from the treatment plant in winter posed a high risk (RQ > 10) for the aquatic organisms (algae and fish) in the receiving environment. According to these results, the removal efficiency of antibiotics at the WWTP is inadequate and plant should be improved to remove antibiotics by advanced treatment processes.

Chlorobenzenes (CBzs) are unintentionally produced organic contaminants from different thermal industrial processes, which have been scarcely surveyed in Asian developing countries including Vietnam. In this study, residue concentrations, profiles, emission factors, and annual emissions of seven chlorobenzene compounds were investigated in fly ash and bottom ash samples of some industrial facilities including brick making plant, steel and zinc production plants, and industrial and municipal waste incinerators in northern Vietnam. Total concentrations of seven CBzs in the ash samples were generally decreased in the order: industrial waste incinerator > municipal waste incinerator > steel-making plant > brick making plant. Emission pattern of CBzs varied considerably among different industrial plants, with 1,2- and 1,3-dichloro-, 1,2,3,4-tetrachloro-, and hexachlorobenzene as predominant compounds in the industrial waste incinerators and steel-making plants. Emission factors of CBzs estimated for the fly ash and bottom ash samples were in the range of 118–2020 and 5.3–22,600 μg ton⁻¹, respectively. Average annual emissions (AEs) of total seven CBzs estimated for fly ash and bottom ash in the investigated plants were in the range of 154–54,300 and 20,160–161,400 mg year⁻¹, respectively. The AEs of CBzs estimated for fly ash in the steel-making plant were higher than those in the waste incinerators. Meanwhile, CBz emissions for bottom ash were the highest in the steel-making plant, followed by the industrial and municipal waste incinerators. This is among the first studies on the emission characteristics of both low and highly chlorinated benzenes from industrial activities in Vietnam.

The higher economic growth of China intensifies the consumption of fossil fuel, such as coal and oil, for electricity generation, transportation etc., which is responsible for environmental degradation through the emissions of carbon, sulfur, and nitrogen etc. The objectives of this study are to investigate the impact of greenhouse gas emission on health issues and provide the effective solution to overcome health-related issues, caused by carbon, sulfur, and nitrogen emission. For this purpose, we propose that higher afforestation activities can help to mitigate the carbon emission and can help to reduce the health diseases. The findings of quantile regressions reported that an increase in carbon emission causes significantly higher health issues. On the contrary, afforestation activities reported a negative coefficient, suggesting that growth of forests can be useful measure in control of health issues. The findings of the current study can be utilized in policy making and to explore the nexus between greenhouse gas emission, afforestation, and health issues.

Fluxes of methane (CH₄) and nitrous oxide (N₂O) from two rice varieties, Huayou 14 and Hanyou 8, were monitored using closed chamber/gas chromatography method. Huayou 14 is a commonly grown variety of rice whereas Hanyou 8 is a water-saving and drought-resistant rice (WDR) variety. Low soil volumetric water content (VWC) existed in the treatments on the slope (W5 < W4 < W3 < W2). On the slope, rice yields of Hanyou 8 decreased by 12–39%, and Huayou 14 by 11–46% as compared to the plots on the flat. The total compatible solutes in Hanyou 8 had a greater variational range than Huayou 14. Compared to W1, CH₄ emissions from W2–W5 decreased by 58–86% in Hanyou 8 and 38–86% in Huayou 14, whereas those of N₂O increased by 26–121% in Hanyou 8 and 49–189% in Huayou 14 across both two seasons, which was mainly because the VWC varied in W2–W5 treatment. Under the treatments in the slope (W2, W3, W4, and W5), the global warming potential (GWP) was dominated by N₂O emissions, which accounted for 69–90% of the GWP. Hanyou 8 had greater tolerance for water stress than Huayou 14 did, as evident from the smaller reductions in rice yield and greater variational range of total compatible solutes content. Water stress could reduce CH₄ emissions but decrease N₂O emissions for both rice varieties. This results suggest that planting WDR varieties under water shortage irrigation (such as W4, W5) will be able to maintain rice yields and reduce the GWP with less water.