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Strong hydroclimatic controls on vulnerability to subsurface nitrate contamination across Europe
(2020)
Subsurface contamination due to excessive nutrient surpluses is a persistent and widespread problem in agricultural areas across Europe. The vulnerability of a particular location to pollution from reactive solutes, such as nitrate, is determined by the interplay between hydrologic transport and biogeochemical transformations. Current studies on the controls of subsurface vulnerability do not consider the transient behaviour of transport dynamics in the root zone. Here, using state-of-the-art hydrologic simulations driven by observed hydroclimatic forcing, we demonstrate the strong spatiotemporal heterogeneity of hydrologic transport dynamics and reveal that these dynamics are primarily controlled by the hydroclimatic gradient of the aridity index across Europe. Contrasting the space-time dynamics of transport times with reactive timescales of denitrification in soil indicate that similar to 75% of the cultivated areas across Europe are potentially vulnerable to nitrate leaching for at least onethird of the year. We find that neglecting the transient nature of transport and reaction timescale results in a great underestimation of the extent of vulnerable regions by almost 50%. Therefore, future vulnerability and risk assessment studies must account for the transient behaviour of transport and biogeochemical transformation processes.
We study optimal and equilibrium sizes of cities in a city system model with pollution. Pollution is a function of population size. If pollution is local or per-capita pollution increases with population, equilibrium cities are too large under symmetry; with asymmetric cities, the largest cities are too large and the smallest too small. When pollution is global and per-capita pollution declines with city size, cities may be too small under symmetry; with asymmetric cities, the largest cities are too small and the smallest too large if the marginal damage of pollution is large enough. We calibrate the model to US cities and find that the largest cities may be undersized by 3-4%.