Nitrate-nitrogen losses through subsurface drainage under various agricultural land covers

Nitrate-nitrogen (NO?-N) loading to surface water bodies from subsurface drainage is an environmental concern in the midwestern United States. The objective of this study was to investigate the effect of various land covers on NO?-N loss through subsurface drainage. Land-cover treatments included (i) conventional corn ( L.) (C) and soybean [ (L.) Merr.] (S); (ii) winter rye ( L.) cover crop before corn (rC) and before soybean (rS); (iii) kura clover ( M. Bieb.) as a living mulch for corn (kC); and (iv) perennial forage of orchardgrass ( L.) mixed with clovers (PF). In spring, total N uptake by aboveground biomass of rye in rC, rye in rS, kura clover in kC, and grasses in PF were 14.2, 31.8, 87.0, and 46.3 kg N ha, respectively. Effect of land covers on subsurface drainage was not significant. The NO?-N loss was significantly lower for kC and PF than C and S treatments (p < 0.05); rye cover crop did not reduce NO?-N loss, but NO?-N concentration was significantly reduced in rC during March to June and in rS during July to November (p < 0.05). Moreover, the increase of soil NO?-N from early to late spring in rS was significantly lower than the S treatment (p < 0.05). This study suggests that kC and PF are effective in reducing NO?-N loss, but these systems could lead to concerns relative to grain yield loss and change in farming practices. Management strategies for kC need further study to achieve reasonable corn yield. The effectiveness of rye cover crop on NO-N loss reduction needs further investigation under conditions of different N rates, wider weather patterns, and fall tillage.     

Economic-based projections of future land use in the conterminous United States under alternative policy scenarios

Land-use change significantly contributes to biodiversity loss, invasive species spread, changes in biogeochemical cycles, and the loss of ecosystem services. Planning for a sustainable future requires a thorough understanding of expected land use at the fine spatial scales relevant for modeling many ecological processes and at dimensions appropriate for regional or national-level policy making. Our goal was to construct and parameterize an econometric model of land-use change to project future land use to the year 2051 at a fine spatial scale across the conterminous United States under several alternative land-use policy scenarios. We parameterized the econometric model of land-use change with the National Resource Inventory (NRI) 1992 and 1997 land-use data for 844 000 sample points. Land-use transitions were estimated for five land-use classes (cropland, pasture, range, forest, and urban). We predicted land-use change under four scenarios: business-as-usual, afforestation, removal of agricultural subsidies, and increased urban rents. Our results for the business-as-usual scenario showed widespread changes in land use, affecting 36% of the land area of the conterminous United States, with large increases in urban land (79%) and forest (7%), and declines in cropland (-16%) and pasture (-13%). Areas with particularly high rates of land-use change included the larger Chicago area, parts of the Pacific Northwest, and the Central Valley of California. However, while land-use change was substantial, differences in results among the four scenarios were relatively minor. The only scenario that was markedly different was the afforestation scenario, which resulted in an increase of forest area that was twice as high as the business-as-usual scenario. Land-use policies can affect trends, but only so much. The basic economic and demographic factors shaping land-use changes in the United States are powerful, and even fairly dramatic policy changes, showed only moderate deviations from the business-as-usual scenario. Given the magnitude of predicted land-use change, any attempts to identify a sustainable future or to predict the effects of climate change will have to take likely land-use changes into account. Econometric models that can simulate land-use change for broad areas with fine resolution are necessary to predict trends in ecosystem service provision and biodiversity persistence.     

Rezensionen

Ohne Zusammenfassung     

Die Kosten des Dieselbooms

Background

In many European states the number of cars equipped with diesel engines has dramatically increased since around ten years. This situation is quantified for Germany. Driven by the political motivation to reduce CO₂-emissions, increase of diesel cars has been stimulated by governmental measures of European as well as state bodies in co-operation with the industry.

Results

Reduction of CO₂-emissions with the help of diesel cars remained relatively small. On contrast, diesel cars are emitting much more of nitric oxides and fine particles compared with gasoline driven cars. Excess emissions by the ‘diesel boom’ are quantified. Health costs and impact on agricultural crops as well as on forestry are estimated with respect to the order of magnitude. Health costs caused by the inhalation of diesel combustion particles emitted by only the excess diesel cars in Germany are in the order of 200 Mio Euro per year. Knowledge gaps of the impact of ultra fine particles as well as of the action of particle traps are demonstrated.

Conclusion and Recommendation

In the public, particle numbers need to be discussed instead of particle emission loads (g km^?1) which have an insufficient correlation to health effects. Much more data are needed as to the toxicologically relevant particle size of <20 nm. Effectiveness and sustainability of a CO₂-reduction strategy by diesel cars are generally questioned.     

Bewertung der Umwelteffizienz moderner Autoantriebe – auf dem Weg vom Diesel-Pkw-Boom zu Elektroautos

Motorized traffic is among the biggest CO₂-emitting sources and is additionally dominating NO_x emission. Engine technology shifts are approaching, while automobiles developed in Germany and Europe are exported worldwide together with the European emission thresholds for cars. The Diesel car boom induced by EU commission, national EU governments and car industry is accordingly analyzed for sustainability and its effects on environment. German CO₂ emission reduction numbers by motorized traffic, as claimed by the government, are questioned. Radiative forcing by soot (black carbon) Diesel car emissions is added on the CO₂ emissions by fuel combustion. Diesel cars without particle filters are found to cause an atmospheric warming. Modelled and measured NO_x emission data are assessed to mismatch considerably. In spite of an ambitious national NO_x reduction plan there is excess NO_x emission by the German and European Diesel car boom. In this context environmental sustainability of battery electric vehicles (BEV) is investigated. Direct (by car) und indirect (by power plant) emissions (CO₂, NO_x, PM₁₀, SO₂) of cars with internal combustion engines (ICE) and BEVs, respectively, are calculated and compared. CO₂-ecoanalysis revealed advantages for BEVs even operated with current German electricity mix based on around 15?% renewable sources.     

Simulating nitrate-nitrogen concentration from a subsurface drainage system in response to nitrogen application rates using RZWQM2

Computer models have been widely used to evaluate the impact of agronomic management on nitrogen (N) dynamics in subsurface drained fields. However, they have not been evaluated as to their ability to capture the variability of nitrate-nitrogen (NO(3)-N) concentration in subsurface drainage at a wide range of N application rates due to possible errors in the simulation of other system components. The objective of this study was to evaluate the performance of Root Zone Water Quality Model2 (RZWQM2) in simulating the response of NO(3)-N concentration in subsurface drainage to N application rate. A 16-yr field study conducted in Iowa at nine N rates (0-252 kg N ha(-1)) from 1989 to 2004 was used to evaluate the model, based on a previous calibration with data from 2005 to 2009 at this site. The results showed that the RZWQM2 model performed "satisfactorily" in simulating the response of NO(3)-N concentration in subsurface drainage to N fertilizer rate with 0.76, 0.49, and -3% for the Nash-Sutcliffe efficiency, the ratio of the root mean square error to the standard deviation, and percent bias, respectively. The simulation also identified that the N application rate required to achieve the maximum contaminant level for the annual average NO(3)-N concentration was similar to field-observed data. This study supports the use of RZWQM2 to predict NO(3)-N concentration in subsurface drainage at various N application rates once it is calibrated for the local condition.