Climatic condition, geology, and geochemical processes in an area play a major role on groundwater quality. Impact of these on the fluoride content of groundwater was studied in three regions-part of Nalgonda district in Telangana, Pambar River basin, and Vaniyar River basin in Tamil Nadu, southern India, which experience semi-arid climate and are predominantly made of Precambrian rocks. High concentration of fluoride in groundwater above 4 mg/l was recorded. Human exposure dose for fluoride through groundwater was higher in Nalgonda than the other areas. With evaporation and rainfall being one of the major contributors for high fluoride apart from the weathering of fluoride rich minerals from rocks, the effect of increase in groundwater level on fluoride concentration was studied. This study reveals that groundwater in shallow environment of all three regions shows dilution effect due to rainfall recharge. Suitable managed aquifer recharge (MAR) methods can be adopted to dilute the fluoride rich groundwater in such regions which is explained with two case studies. However, in deep groundwater, increase in fluoride concentration with increase in groundwater level due to leaching of fluoride rich salts from the unsaturated zone was observed. Occurrence of fluoride above 1.5 mg/l was more in areas with deeper groundwater environment. Hence, practicing MAR in these regions will increase the fluoride content in groundwater and so physica or chemical treatment has to be adopted. This study brought out the fact that MAR cannot be practiced in all regions for dilution of ions in groundwater and that it is essential to analyze the fluctuation in groundwater level and the fluoride content before suggesting it as a suitable solution. Also, this study emphasizes that long-term monitoring of these factors is an important criterion for choosing the recharge areas.

Nitrogen loss via overland flow from agricultural land use is a global threat to waterways. On-farm denitrifying woodchip bioreactors can mitigate NO₃⁻ exports by increasing denitrification capacity. However, denitrification in sub-optimal conditions releases the greenhouse gas nitrous oxide (N₂O), swapping the pollution from aquatic to atmospheric reservoirs. Here, we assess NO₃⁻-N removal and N₂O emissions from a new edge-of-field surface-flow bioreactor during ten rain events on intensive farming land. Nitrate removal rates (NRR) varied between 5.4 and 76.2 g NO₃⁻-N m⁻³ wetted woodchip d⁻¹ with a mean of 30.3 ± 7.3 g NO₃⁻-N m⁻³. The nitrate removal efficiency (NRE) was ∼73% in ideal hydrological conditions and ∼18% in non-ideal conditions. The fraction of NO₃⁻-N converted to N₂O (rN₂O) in the bioreactor was ∼3.3 fold lower than the expected 0.75% IPCC emission factor. We update the global bioreactor estimated Q₁₀ (NRR increase every 10 °C) from a recent meta-analysis with previously unavailable data to >20 °C, yielding a new global Q₁₀ factor of 3.1. Mean N₂O CO₂-eq emissions (431.9 ± 125.4 g CO₂-eq emissions day⁻¹) indicate that the bioreactor was not significantly swapping aquatic NO₃⁻ for N₂O pollution. Our estimated NO₃⁻-N removal from the bioreactor (9.9 kg NO₃⁻-N ha⁻¹ yr⁻¹) costs US$13.14 per kg NO₃⁻-N removed and represents ∼30% NO₃⁻-N removal when incorporating all flow and overflow events. Overall, edge-of-field surface-flow bioreactors seem to be a cost-effective solution to reduce NO₃⁻-N runoff with minor pollution swapping to N₂O.

Spatiotemporal variability complicates source apportionment of metals in urban lakes, especially when rainfall drives urban non-point source pollution. As, Cd, Cr, Pb, Hg, Ag, Co, Cu, Fe, Mn, Ni, Sb, Sr and Zn concentrations in 648 water samples collected before and after rain in 6 urban lakes of Beijing, China were determined during 2013–2015. The response of metals concentrations after rain to the interaction between rainfall and antecedent dry days was significant. Metals concentrations were normalized pursuant to the interaction effect as the input of positive matrix factorization (PMF) to develop the interaction normalized-PMF (IN-PMF). Four primary pollution sources were diagnosed. Sediment release was considered to be the main source of Fe, Co and Ni independent of rainfall. Hg, As and some Cr associated with pesticides and fertilizers were likely to come from soil erosion and runoff from green space. It is probable that road runoff was the dominant source for heavy metals related to traffic emissions, including Pb, Cd, Cu, Sb, Mn and Zn. Cr, Sr and some Cu and Zn as key elements of rooftops can be regarded as from roof runoff. The IN-PMF lowered roof and road runoff contributions and raised the contribution of soil erosion from green space, with Pb, Sb, Cu, Zn, Cd and Mn increasing by 15.9%, 10.7%, 13.1%, 12.2%, 13.3% and 16.8%. The results shed more light on the stormwater runoff pollution mitigation on impervious surfaces and metals enrichment problems in infiltration soil on green space in the low impact development (LID) setting. The Bayesian network revealed the spatial variability of transport and fate of metal elements from land surfaces to urban lakes, supplementing the secondary pollution sources from different land use. This study will provide new insights for source apportionment of non-point source pollution under the background of sponge city construction.

Glyphosate (N-phosphonomethylglycine; GLP) and its main metabolite AMPA (aminomethylphosphonic acid), are frequently detected in relatively high concentrations in European agricultural topsoils. Glyphosate has a high sorption affinity, yet it can be detected occasionally in groundwater. We hypothesized that shrinkage cracks occurring after dry periods could facilitate GLP transport to greater depths where subsoil conditions slow further microbial degradation. To test this hypothesis, we simulated a heavy rainfall event (HRE) on a clay-rich arable soil. We applied 2.1 kg ha⁻¹ of 100% ¹³C₃, ¹⁵N-labeled GLP one day before the simulated rainfall event. Microbial degradation of translocated GLP over a 21-day period was assessed by quantifying ¹³C incorporation into phospholipid fatty acids. Microbial degradation potential and activity were determined by quantifying the abundance and expression of functional genes involved in the two known degradation pathways of GLP; to AMPA (goxA) or sarcosine (sarc). We confirmed that goxA transcripts were elevated in the range of 4.23 x 10⁵ copy numbers g⁻¹ soil only one day after application. The increase in AMPA associated with a rise in goxA transcripts and goxA-harboring microorganisms indicated that the degradation pathway to AMPA dominated. Based on ¹³C-enrichment 3 h after the HRE, fungi appeared to initiate glyphosate degradation. At later time points, Gram⁺-bacteria proved to be the main degraders due to their higher ¹³C-incorporation. Once GLP reached the subsoil, degradation continued but more slowly. By comparing GLP distribution and its microbial degradation in macropores and in the bulk soil, we demonstrated different time- and depth-dependent GLP degradation dynamics in macropores. This indicates the need for field studies in which soil properties relevant to GLP degradation are related to limiting environmental conditions, providing a realistic assessment of GLP fate in soils.

Hot moments of nitrous oxide (N₂O) emissions induced by interactions between weather and management make a major contribution to annual N₂O budgets in agricultural soils. The causes of N₂O production during hot moments are not well understood under field conditions, but emerging evidence suggests that short-term fluctuations in soil oxygen (O₂) concentration can be critically important. We conducted high time-resolution field observations of O₂ and N₂O concentrations during hot moments in a dryland agricultural soil in Northern China. Three typical management and weather events, including irrigation (Irr.), fertilization coupled with irrigation (Fer.+Irr.) or with extreme precipitation (Fer.+Pre.), were observed. Soil O₂ and N₂O concentrations were measured hourly for 24 h immediately following events and measured daily for at least one week before and after the events. Soil moisture, temperature, and mineral N were simultaneously measured. Soil O₂ concentrations decreased rapidly within 4 h following irrigation in both the Irr. and Fer.+Irr. events. In the Fer.+Pre. event, soil O₂ depletion did not occur immediately following fertilization but began following subsequent continuous rainfall. The soil O₂ concentration dropped to as low as 0.2% (with the highest soil N₂O concentration of up to 180 ppmv) following the Fer.+Pre. event, but only fell to 11.7% and 13.6% after the Fer.+Irr. and Irr. events, which were associated with soil N₂O concentrations of 27 ppmv and 3 ppmv, respectively. During the hot moments of all three events, soil N₂O concentrations were negatively correlated with soil O₂ concentrations (r = −0.5, P < 0.01), showing a quadratic increase as soil O₂ concentrations declined. Our results provide new understanding of the rapid short response of N₂O production to O₂ dynamics driven by changes in soil environmental factors during hot moments. Such understanding helps improve soil management to avoid transitory O₂ depletion and reduce the risk of N₂O production.

Phytoextraction using hyperaccumulator, Pteris vittata, to extract arsenic (As) from soil has been applied to large areas to achieve an As removal rate of 18% per year. However, remarkable difference among different studies and field practices has led to difficulties in the standardization of phytoextraction technology. In this study, data on As concentration in P. vittata and related environmental conditions were collected through literature search. A conceptual framework was proposed to guide the improvement of phytoextraction efficiency in the field. The following influencing factors of As concentration in this hyperaccumulator were identified: total As concentration in soil, soil available As, organic matter in soil, total potassium (K) concentration in soil, and annual rainfall. The geodetection results show that the main factors that affect As concentration in P. vittata include soil organic matter (q = 0.75), soil available As (q = 0.67), total K (q = 0.54), and rainfall (q = 0.42). The predictive models of As concentration in P. vittata were established separately for greenhouse and field conditions through multivariate linear stepwise regression method. Under greenhouse condition, soil available As was the most important influencing factor and could explain 41.4% of As concentration in P. vittata. Two dominant factors were detected in the field: soil available As concentration and average annual rainfall. The combination of these two factors gave better prediction results with R² = 0.762. The establishment of the model might help predict phytoextraction efficiency and contribute to technological standardization. The strategies that were used to promote As removal from soil by P. vittata were summarized and analyzed. Intercropping with suitable plants or a combination of different measures (e.g., phosphate fertilizer and water retention) was recommended in practice to increase As concentration in P. vittata.