Time lags of nitrate, chloride, and tritium in streams assessed by dynamic groundwater flow tracking in a lowland landscape

Surface waters are under pressure from diffuse pollution from agricultural activities, and groundwater is known to be a connection between the agricultural fields and streams. This paper is one of the first to calculate long-term in-stream concentrations of tritium, chloride, and nitrate using dynamic groundwater travel time distributions (TTDs) derived from a distributed, transient, 3D groundwater flow model using forward particle tracking. We tested our approach in the Springendalse Beek catchment, a lowland stream in the east of the Netherlands, for which we collected a long time series of chloride and nitrate concentrations (1969–2018). The Netherlands experienced a sharp decrease in concentrations of solutes leaching to groundwater in the 1980s due to legislations on the application of nitrogen to agricultural fields. Stream measurements of chloride and nitrate showed that the corresponding trend reversal in the groundwater-fed stream occurred after a time lag of 5–10 years. By combining calculated TTDs with the known history of nitrogen and chloride inputs, we found that the variable contribution of different groundwater flow paths to stream water quality reasonably explained the majority of long-term and seasonal variation in the measured stream nitrate concentrations. However, combining only TTDs and inputs underestimated the time lag between the peak in nitrogen input and the following trend reversal of nitrate in the stream. This feature was further investigated through an exploration of the model behaviour under different scenarios. A time lag of several years, and up to decades, can occur due to (1) a thick unsaturated zone adding a certain travel time, (2) persistent organic matter with a slow release of N in the unsaturated zone, (3) a long mean travel time (MTT) compared to the rate of the reduction in nitrogen application, (4) areas with a high application of nitrogen (agricultural fields) being located further away from the stream or drainage network, or (5) a higher presence of nitrate attenuating processes close to the stream or drainage network compared to the rest of the catchment. By making the connection between dynamic groundwater travel time distributions and in-stream concentration measurements, we provide a method for validating the travel time approach and make the step towards application in water quality modelling and management.

The impact of COVID-19 on development assistance

This article analyzes the impact of the COVID-19 pandemic on foreign aid. Using examples from Canadian foreign aid, it argues that, despite the terrible toll it is exacting, the crisis has accelerated some significant positive pre-existing trends, both by destabilizing the perception of aid as flowing essentially from the Global North to Global South and by reinforcing awareness of the importance of joint efforts for global public goods and humanitarian assistance, as well as debt relief. However, it has also reinforced potentially harmful self-interested justifications for aid, which could align assistance more with donors’ priorities than the needs of the poor. An important trend reversal is the renewed emphasis on well-being. Two other crucial trends remain unclear—the COVID-19 pandemic’s impact on multilateral approaches and on aid flows. How donors respond to the COVID-19 pandemic and its aftermath over the next few years will depend on their political will, and will profoundly shape the future of development co-operation.

Groundwater quality trend and trend reversal assessment in the European Water Framework Directive context: an example with nitrates in Italy

Groundwater resources are of utmost importance in sustaining water related ecosystems, including humans. The long-lasting impacts from anthropogenic activities require early actions, owing to the natural time lag in groundwater formation and renewal. The European Union (EU) policy, within the implementation of the Water Framework Directive (WFD), requires Member States to identify and reverse any significant and sustained upward trend in the concentration of pollutants, defining specific protection measures to be included in the River Basin Management Plans (RBMP). In Italy, official guidelines for trend and trend reversal assessment have been published recently. Statistical methods, such as the Mann-Kendall test for trend analysis and the Sen’s method for estimating concentration scenarios, should be applied at the fixed terms stated by the WFD implementation cycles to identify upward trends, while the Pettitt test is proposed for the identification of trend reversal. In this paper, we present an application of a slightly modified version of the Italian Guidelines to a groundwater body in Northern Italy featuring nitrate pollution and discuss its advantages and limitations. In addition to Pettitt test, for the trend reversal analysis, we apply the Mann-Kendall test in two sections and compare the results. We conclude that this method seems more reliable than Pettitt test to identify a reversal point in quality time series. The overall procedure can be easily applied to any groundwater body defined at risk across Europe, for the assessment of the upward trends of pollutants and their reversal, even with little chemical monitoring data. Although focused on the EU legislative framework, this procedure may be relevant for a wider context, allowing to individuate upward trend as early warning for contamination processes in an integrated water resources management context.

Roles of climate variability on the rapid increases of early winter haze pollution in North China after 2010

North China experiences severe haze pollution in early winter, resulting in many premature deaths and considerable economic losses. The number of haze days in early winter (December and January) in North China (HDNC) increased rapidly after 2010 but declined slowly before 2010, reflecting a trend reversal. Global warming and emissions were two fundamental drivers of the long-term increasing trend of haze, but no studies have focused on this trend reversal. The autumn sea surface temperature (SST) in the Pacific and Atlantic, Eurasian snow cover and central Siberian soil moisture, which exhibited completely opposite trends before and after 2010, might have close relationships with identical trends of meteorological conditions related to haze pollution in North China. Numerical experiments with a fixed emission level confirmed the physical relationships between the climate drivers and HDNC during both decreasing and increasing periods. These external drivers induced a larger decreasing trend of HDNC than the observations, and combined with the persistently increasing trend of anthropogenic emissions, resulted in a realistic, slowly decreasing trend. However, after 2010, the increasing trends driven by these climate divers and human emissions jointly led to a rapid increase in HDNC.

Carbon Emissions from Fuel Combustion in the Economy of the State of Minas Gerais, Brazil (2005-2016)

The article assesses carbon emissions from fuel combustion in the economy of the Brazilian State of Minas Gerais between 2005 and 2016. An open Leontief model with hybrid units and incorporation of an energy sector was built using available input-output matrices and energy flows by economic sector. Overall, “Transport, storage, and mailing”, “Petroleum derivatives and ethanol”, and “Metallurgy” remained as the most relevant sectors in terms of emissions. Total and distributive impacts decreased between 2005 and 2013, with a trend reversal between 2013 and 2016. In addition to these sectors, “Mining” and “Agriculture, forestry and logging” were significant sources of emissions embedded in exports. A reduction of approximately 20% in sectoral average and aggregate emission requirements was observed, despite the substantial growth of the economy of the State in the period. There were decreasing returns to such gains, which, alongside the trend reversal at the end of the period, point to the role of specific macroeconomic factors in the observed outcomes and the need for new initiatives to curb emissions in the future.