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Abstract In this study, we investigate the driving forces behind the changes in residential energy consumption (REC) in China’s urban and rural areas over the 2001–2012 period. Based on the logarithmic mean Divisia index method, the REC changes are decomposed into seven driving forces, which are climate change, energy price, energy expenditure mix, energy cost share (in total expenditure), expenditure share (in income), per capita income and population effects. According to the results, climate effect due to increasing days with abnormal temperature, energy cost share effect characterized by more expenditure to be paid for energy use, income effect describing constant income growth in the residential sector definitely increase REC in both urban and rural areas. In contrast, energy prices and energy expenditure mix effects negatively contribute to the REC increase, respectively because of the increase in energy prices and the transition from the low-priced energy to high-priced energy. Expenditure share and population effects play opposite roles in urban and rural areas, and the reasons and implications are analysed in depth.

China has achieved impressive rapid economic growth over the past 30 years but accompanied by significant extreme weather events and environmental changes caused by global change and overfast urbanization. Using the absolute hazards index (AHI), we assessed the spatial distribution patterns and related health effects of 4 major extreme natural disasters, including drought, floods (landslides, mudslides), hails, and typhoons from 2000 to 2011 at the provincial level in China. The results showed that (1) central and south China were the most affected by the 4 natural disasters, and north China suffered less; (2) the provinces with higher AHI suffered most from total death, missing people, collapse, and emergently relocated population; (3) the present health emergency response system to disasters in China mainly lacks a multidisciplinary approach. In the concluding section of this article, suggestions on preparedness and rapid response to extreme health events from environmental changes are proposed.

The growing interest in forest biomass has made chipping increasingly popular all across Europe. Many operators have equipped for the purpose, but the large variety of working conditions found in the European forests makes it difficult to correctly estimate the productivity of each specific operation, leading to uncertainty in crucial decisions, such as: operation scheduling, price setting, machinery selection and acquisition. In 2001, the Italian National Council for Research (CNR) and the University of California (UC) developed a spreadsheet freeware capable of returning reliable estimates of chipping productivity and cost, on the basis of user-defined input data. The model is still available from the CNR website and is the object of frequent downloading and inquiries. Such model contains a set of predictive equations derived from the results of 102 field trials, conducted with 30 different machines, under a range of working conditions. In order to facilitate comparison with other estimates and to achieve methodological transparency, the equations are assembled into a simple Microsoft Excel workbook, and the costs are calculated with standard costing methods currently used in Forest and Agricultural Engineering. Since then CNR has continued to work on the subject, with the goal of updating and refining the model. Such work has included 45 validation tests and a separate study on the delay (idle) time typical for different chipping operation layouts. The study was concluded in 2009 and confirms that the model developed by CNR can provide reliable estimates of chipper productivity under a range of operational conditions. Authors believe that such a model can assist European foresters in keeping ahead with the growing biomass sector, thus helping them to seize an important business opportunity.

Decreasing nutrient losses from excessive synthetic fertilizer inputs is the direct and valid way to address low nutrient use efficiency and the related environmental consequences. Here, we established a comprehensive database of nitrogen (N), phosphorus (P), and carbon (C) losses from rice paddy fields in China, which we used to evaluate fertilization-induced losses and the impact of environmental factors, and to mitigate losses by adopting alternative fertilization options and setting input thresholds. Our results showed that most N-loss pathways had exponential increases with additional N input. In average, 23.8% of the N applied was lost via NH3 (16.1%), N2O (0.3%), leaching (4.8%), and runoff (2.6%). Total P loss was approximately 2.7% of the input, composed of leaching (1.3%) and runoff (1.4%). C lost as CH4 accounted for 4.9% of the organic C input. A relative importance analysis indicated that climate or soil variation rather than fertilizer rate was the dominant factor driving N and P leaching, and CH4 emissions. Based on the sensitivity of multiple N-loss pathways to N fertilization, we propose upper thresholds for N inputs of 142–191 kg N ha−1 across four rice types, which would avoid dramatic increases in N losses. Compared to conventional chemical fertilization, alternative fertilization options had diverse performances: enhanced-efficiency N fertilizer reduced N loss rate by 7.8 percent points and the global warming potential (GWP, considering N2O and CH4 emissions) by 28.8%; combined manure and chemical N fertilizer reduced N loss rate by 9.0 percent points but increased the GWP by 56.9%; straw return had no effect on total N loss but almost doubled the GWP. Using nutrient sources most appropriate to site-specific conditions is demonstrated as a robust way to decrease nutrient losses. Setting nutrient input thresholds would also contribute to the mitigation of environmental pollution, especially in regions with poor fertilization recommendation systems.

The acceptability, energy consumption, and environmental benefits of electric vehicles are highly dependent on travel patterns. With increasing ride-hailing popularity in mega-cities, urban mobility patterns are greatly changing; therefore, an investigation of the extent to which electric vehicles would satisfy the needs of ride-hailing drivers becomes important to support sustainable urban growth. A first step in this direction is reported here. GPS-trajectories of 144,867 drivers over 104 million km in Beijing were used to quantify the potential acceptability, energy consumption, and costs of ride-hailing electric vehicle fleets. Average daily travel distance and travel time for ride-hailing drivers was determined to be 129.4 km and 5.7 h; these values are substantially larger than those for household drivers (40.0 km and 1.5 h). Assuming slow level-1 (1.8 KW) or moderate level-2 (7.2 KW) charging is available at all home parking locations, battery electric vehicles with 200 km all electric range (BEV200) could be used by up to 47% or 78% of ride-hailing drivers and electrify up to 20% or 55% of total distance driven by the ride-hailing fleet. With level-2 charging available at home, work, and public parking, the acceptance ceiling increases to up to 91% of drivers and 80% of distance. Our study suggests that long range BEVs and widespread level-2 charging infrastructure are needed for large-scale electrification of ride-hailing mobility in Beijing. The marginal benefits of increased all electric range, effects on charging infrastructure distribution, and payback times are also presented and discussed. Given the observed heterogeneity of ride-hailing vehicle travel, our study outlines the importance of individual-level analysis to understand the electrification potential and future benefits of electric vehicles in the era of shared smart transportation.

The repercussions of climate change will be felt in various ways throughout both natural and human systems in Sub-Saharan Africa. Climate change projections for this region point to a warming trend, particularly in the inland subtropics; frequent occurrence of extreme heat events; increasing aridity; and changes in rainfall—with a particularly pronounced decline in southern Africa and an increase in East Africa. The region could also experience as much as one meter of sea-level rise by the end of this century under a 4 °C warming scenario. Sub-Saharan Africa’s already high rates of undernutrition and infectious disease can be expected to increase compared to a scenario without climate change. Particularly vulnerable to these climatic changes are the rainfed agricultural systems on which the livelihoods of a large proportion of the region’s population currently depend. As agricultural livelihoods become more precarious, the rate of rural–urban migration may be expected to grow, adding to the already significant urbanization trend in the region. The movement of people into informal settlements may expose them to a variety of risks different but no less serious than those faced in their place of origin, including outbreaks of infectious disease, flash flooding and food price increases. Impacts across sectors are likely to amplify the overall effect but remain little understood.

This paper serves as an introduction to this special issue on new developments in urban transportation planning. The papers in this issue highlight how physical mobility is still an essential priority for urban life, but that there are associated costs in the terms of environmental impacts, quality of life and economic performance of cities. Four features of the emerging urban transportation field are identified. The first defining feature is that it is a discipline in the midst of a paradigmatic transition. Second is its overarching aim of achieving sustainable urban mobility as part of a broader effort towards enhancing quality of life in cities. The third feature is the emphasis on collaboration, integration and exchange with other professions and policy sectors. The last distinctive feature is the recognition that urban transportation planning is a communication-oriented activity.

Feedbacks between land carbon pools and climate provide one of the largest sources of uncertainty in our predictions of global climate. Estimates of the sensitivity of the terrestrial carbon budget to climate anomalies in the tropics and the identification of the mechanisms responsible for feedback effects remain uncertain. The Amazon basin stores a vast amount of carbon, and has experienced increasingly higher temperatures and more frequent floods and droughts over the past two decades. Here we report seasonal and annual carbon balances across the Amazon basin, based on carbon dioxide and carbon monoxide measurements for the anomalously dry and wet years 2010 and 2011, respectively. We find that the Amazon basin lost 0.48 ± 0.18 petagrams of carbon per year (Pg C yr(-1)) during the dry year but was carbon neutral (0.06 ± 0.1 Pg C yr(-1)) during the wet year. Taking into account carbon losses from fire by using carbon monoxide measurements, we derived the basin net biome exchange (that is, the carbon flux between the non-burned forest and the atmosphere) revealing that during the dry year, vegetation was carbon neutral. During the wet year, vegetation was a net carbon sink of 0.25 ± 0.14 Pg C yr(-1), which is roughly consistent with the mean long-term intact-forest biomass sink of 0.39 ± 0.10 Pg C yr(-1) previously estimated from forest censuses. Observations from Amazonian forest plots suggest the suppression of photosynthesis during drought as the primary cause for the 2010 sink neutralization. Overall, our results suggest that moisture has an important role in determining the Amazonian carbon balance. If the recent trend of increasing precipitation extremes persists, the Amazon may become an increasing carbon source as a result of both emissions from fires and the suppression of net biome exchange by drought.