A huge amount of agricultural wastes and waste activated-sludge are being generated every year around the world. Anaerobic co-digestion (AcD) has been considered as an alternative for the utilization of organic matters from such organic wastes by producing bioenergy and biochemicals to realize a circular bioeconomy. Despite recent advancement in AcD processes, the effect of feedstock compositions and operating conditions on the biomethane production processe has not been critically explored. In this paper, we have reviewed the effects of feedstock (organic wastes) characteristics, including particle size, carbon-to-nitrogen ratio, and pretreatment options, on the performance of an anaerobic digestion process. In addition, we provided an overview of the effect of key control parameters, including retention time, temperature, pH of digestate, volatile fatty acids content, total solids content, and organic loading rate. Lastly, based on the findings from the literature, we have presented several perspectives and prospects on priority research to promote AcD to a steppingstone for a circular bioeconomy.

Groundwater resources are abundant and widely used in Taiwan’s Lanyang Plain. However, in some places the groundwater arsenic (As) concentrations far exceed the World Health Organization’s standards for drinking water quality. Measurements of the As concentrations in groundwater show considerable spatial variability, which means that the associated risk to human health would also vary from region to region. This study aims to adapt a back-propagation neural network (BPNN) method to carry out more reliable spatial mapping of the As concentrations in the groundwater for comparison with the geostatistical ordinary kriging (OK) method results. Cross validation is performed to evaluate the prediction performance by dividing the As monitoring data into three sets. The cross-validation results show that the average determination coefficients (R²) for the As concentrations obtained with BPNN and OK are 0.55 and 0.49, whereas the average root mean square errors (RMSE) are 0.49 and 0.54, respectively. Given the better prediction performance of the BPNN, it is recommended as a more reliable tool for the spatial mapping of the groundwater As concentration. Subsequently, the As concentrations estimated obtained using the BPNN are applied to develop a spatial map illustrating the risk to human health associated with the ingestion of As-containing groundwater based on the noncarcinogenic hazard quotient (HQ) and carcinogenic target risk (TR) standards established by the U.S. Environmental Protection Agency. Such maps can be used to demarcate the areas where residents are at higher risk due to the ingestion of As-containing groundwater, and prioritize the areas where more intensive monitoring of groundwater quality is required. The spatial mapping of As concentrations from the BPNN was also used to demarcate the regions where the groundwater is suitable for farmland and fishponds based on the water quality standards for As for irrigation and aquaculture.

Although the average municipal water coverage in Taiwan is quite high, at 93.91%, only around half of the residents in the Pingtung Plain use tap water originating from the Taiwan Water Corporation to meet their needs. This means the exploitation of a substantial amount of groundwater as a source of water to meet drinking, agriculture, aquaculture, and industry requirements. Long-term groundwater quality surveys in Taiwan have revealed obvious contamination of the groundwater in several locations in the Pingtung Plain, with measured concentration levels of some groundwater quality parameters in excess of the permissible levels specified by the Taiwan Environmental Protection Administration. Clearly, establishing a sound plan for groundwater quality protection in this area is imperative for maximizing the protection of human health. The inappropriate use of hazardous chemicals and poor management of land use have allowed pollutants to permeate through unsaturated soil and ultimately reach the underlying shallow unconfined groundwater system. Thus, the quality of the water stored in shallow aquifers has been significantly affected by land use. This study is designed to characterize the relationship between groundwater quality and land use in the Pingtung Plain. This goal is achieved by the application of factor analysis to characterize the measured concentrations of 14 groundwater quality parameters sampled from 46 observation wells, the area percentages for nine land use categories in the neighborhood of these 46 observation wells, and the thicknesses of four unsaturated types of soil based on core samples obtained during the establishment of 46 observation wells. The results show that a four-factor model can explain 56% of the total variance. Factor 1 (seawater salinization), which includes the groundwater quality parameters of EC, SO₄²⁻, Cl⁻, Ca²⁺, Mg²⁺, Na⁺, and K⁺, shows a moderate correlation to land used for water conservation. Factor 2 (nitrate pollution), which includes the groundwater quality parameters of NO₃⁻-N and HCO₃⁻, shows a strong correlation to land used for fruit farming and a moderate correlation to the thickness of the gravel comprising unsaturated soil. Factor 3 (arsenic pollution), which is composed of groundwater quality parameters of total organic carbon (TOC) and As, is very weakly affected by land use. Factor 4 (reductive dissolution of Fe³⁺ and Mn²⁺), which involves Mn²⁺ and Fe³⁺, is weakly impacted by land use. Based on a geographic visualization of the scores for the four different factors and the patterns for land use, we can demarcate the areas where the groundwater in shallow unconfined aquifers is more vulnerable to being polluted by specific contaminants. We can then prioritize the areas where more intensive monitoring might be required, evaluate current land use practices, and adopt new measures to better prevent or control groundwater pollution.

The Zhuoshui River alluvial fan is one of the most important groundwater and agricultural areas in Taiwan. Abundant groundwater resources are the main source of domestic water supply and irrigation water. However, groundwater recharge and groundwater quality have been greatly affected under extreme climate and hydrological conditions. Hence, the quality of groundwater has been a topic of concern to the public. In this study, groundwater level and groundwater quality data of the Zhuoshui River alluvial fan from 2008 to 2020 were used to divide the wet and dry season groups according to the sampling dates. An independent samples t-test was used to evaluate the differences in the mean groundwater level and the mean concentration between the wet and dry seasons. The test results show that there was no statistically significant difference in the mean groundwater level between the wet and dry seasons. This may result from the time lag effects of groundwater recharge. Except for groundwater temperature, bicarbonate, and total organic carbon (TOC), there were no significant differences among the mean concentrations of other groundwater quality parameters in Aquifer 1 and Aquifer 2 between the wet and dry seasons. In terms of the alluvial fan location, although the soil texture, land utilization, cropping systems, and hydrogeology of the proximal, mid-, and distal fan may affect groundwater quality variations, it seems that only Aquifer 1 is affected by surface water infiltration, resulting in significant differences in mean groundwater temperature, mean concentrations of major ions, and nitrate between the wet and dry seasons, whereas Aquifer 2 is less affected. At the same time, owing to the geological conditions and intensive cultivation in the Zhuoshui River alluvial fan, nitrate and arsenic could represent a high risk to the public’s health if groundwater is used as a source for domestic water supply or irrigation water in the distal fan area, whether in the wet season or dry season. Meanwhile, due to global climate change and uneven droughts and floods, the hydrological conditions of the so-called “wet season” and “dry season” are obviously different from those in the past. Compared with precipitation, groundwater level may be a better indicator for understanding variations in groundwater quality.