Global nitrogen (N) enrichment has resulted in increased nitrous oxide (N(2)O) emission that greatly contributes to climate change and stratospheric ozone destruction, but little is known about the N(2)O emissions from urban river networks receiving anthropogenic N inputs. We examined N(2)O saturation and emission in the Shanghai city river network, covering 6300 km(2), over 27 months. The overall mean saturation and emission from 87 locations was 770% and 1.91 mg N(2)O-N m(-2) d(-1), respectively. Nitrous oxide (N(2)O) saturation did not exhibit a clear seasonality, but the temporal pattern was co-regulated by both water temperature and N loadings. Rivers draining through urban and suburban areas receiving more sewage N inputs had higher N(2)O saturation and emission than those in rural areas. Regression analysis indicated that water ammonium (NH(4)(+)) and dissolved oxygen (DO) level had great control on N(2)O production and were better predictors of N(2)O emission in urban watershed. About 0.29 Gg N(2)O-N yr(-1) N(2)O was emitted from the Shanghai river network annually, which was about 131% of IPCC's prediction using default emission values. Given the rapid progress of global urbanization, more study efforts, particularly on nitrification and its N(2)O yielding, are needed to better quantify the role of urban rivers in global riverine N(2)O emission.

China's urban environments are particularly vulnerable to flooding due to climate change and rapid urbanization. Study of the urban flood risk analysis has significantly increased over the past decade, and this paper therefore reviews the main results (i.e. theoretical basis, methods, techniques, case studies) obtained in the literature from China. We focus on the following topics: (1) urban flood hazard analysis, (2) exposure and vulnerability analysis, and (3) urban flood risk assessment. Recent advances made in the research area are presented with suggestions for further research to improve the availability and reliability of urban flood risk analysis.

Evasion of carbon dioxide (CO2) and methane (CH4) in streams and rivers play a critical role in global carbon (C) cycle, offsetting the C uptake by terrestrial ecosystems. However, little is known about CO2 and CH4 dynamics in lowland coastal rivers profoundly modified by anthropogenic perturbations. Here we report results from a long‐term, large‐scale study of CO2 and CH4 partial pressures (pCO2 and pCH4) and evasion rates in the Shanghai river network. The spatiotemporal variabilities of pCO2 and pCH4 were examined along a land use gradient, and the annual CO2 and CH4 evasion were estimated to assess its role in regional C budget. During the study period (August 2009 to October 2011), the overall mean pCO2 and median pCH4 from 87 surveyed rivers were 5846 ± 2773 μatm and 241 μatm, respectively. Internal metabolic CO2 production and dissolved inorganic carbon input via upstream runoff were the major sources sustaining the widespread CO2 supersaturation, coupling pCO2 to biogeochemical and hydrological controls, respectively. While CH4 was oversaturated throughout the river network, CH4 hot spots were concentrated in the small urban rivers and highly discharge‐dependent. The Shanghai river network played a disproportionately important role in regional C budget, offsetting up to 40% of the regional terrestrial net ecosystem production and 10% of net C uptake in the river‐dominated East China Sea fueled by anthropogenic nutrient input. Given the rapid urbanization in global coastal areas, more research is needed to quantify the role of lowland coastal rivers as a major landscape C source in global C budget.

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Abstract. Emergency medical service (EMS) response is extremely critical for pre-hospital lifesaving when disaster events occur. However, disasters increase the difficulty of rescue and may significantly increase the total travel time between dispatch and arrival, thereby increasing the pressure on emergency facilities. Hence, facility location decisions play a crucial role in improving the efficiency of rescue and service capacity. In order to avoid the failure of EMS facilities during disasters and meet the multiple requirements of demand points, we propose a multi-coverage optimal location model for EMS facilities based on the results of disaster impact simulation and prediction. To verify this model, we explicitly simulated the impacts of fluvial flooding events using the 1-D–2-D coupled flood inundation model FloodMap. The simulation results suggested that even low-magnitude fluvial flood events resulted in a decrease in the EMS response area. The integration of the model results with a geographical-information-system (GIS) analysis indicated that the optimization of the EMS locations reduced the delay in emergency responses caused by disasters and significantly increased the number of rescued people and the coverage of demand points.