Following formative work in the 1970s, disappearance in the 1980s, and reemergence in the 1990s, a chronological review shows that the past decade has witnessed increasing interest in the study of urban metabolism. The review finds that there are two related, non-conflicting, schools of urban metabolism: one following Odum describes metabolism in terms of energy equivalents; while the second more broadly expresses a city’s flows of water, materials and nutrients in terms of mass fluxes. Four example applications of urban metabolism studies are discussed: urban sustainability indicators; inputs to urban greenhouse gas emissions calculation; mathematical models of urban metabolism for policy analysis; and as a basis for sustainable urban design. Future directions include fuller integration of social, health and economic indicators into the urban metabolism framework, while tackling the great sustainability challenge of reconstructing cities.

Agricultural residue burning is one of the major causes of greenhouse gas emissions and aerosols in the Indo-Ganges region. In this study, we characterize the fire intensity, seasonality, variability, fire radiative energy (FRE) and aerosol optical depth (AOD) variations during the agricultural residue burning season using MODIS data. Fire counts exhibited significant bi-modal activity, with peak occurrences during April–May and October–November corresponding to wheat and rice residue burning episodes. The FRE variations coincided with the amount of residues burnt. The mean AOD (2003–2008) was 0.60 with 0.87 (+1σ) and 0.32 (−1σ). The increased AOD during the winter coincided well with the fire counts during rice residue burning season. In contrast, the AOD-fire signal was weak during the summer wheat residue burning and attributed to dust and fossil fuel combustion. Our results highlight the need for ‘full accounting of GHG’s and aerosols’, for addressing the air quality in the study area.

Greenhouse gas (GHG) emissions from agriculture are a significant contributor to total Danish emissions. Consequently, much effort is currently given to the exploration of potential strategies to reduce agricultural emissions. This paper presents results from a study estimating agricultural GHG emissions in the form of methane, nitrous oxide and carbon dioxide (including carbon sources and sinks, and the impact of energy consumption/bioenergy production) from Danish agriculture in the years 1990–2010. An analysis of possible measures to reduce the GHG emissions indicated that a 50–70% reduction of agricultural emissions by 2050 relative to 1990 is achievable, including mitigation measures in relation to the handling of manure and fertilisers, optimization of animal feeding, cropping practices, and land use changes with more organic farming, afforestation and energy crops. In addition, the bioenergy production may be increased significantly without reducing the food production, whereby Danish agriculture could achieve a positive energy balance.

Modelling complex systems such as farms often requires quantification of a large number of input factors. Sensitivity analyses are useful to reduce the number of input factors that are required to be measured or estimated accurately. Three methods of sensitivity analysis (the Morris method, the rank regression and correlation method and the Extended Fourier Amplitude Sensitivity Test method) were compared in the case of the CERES-EGC model applied to crops of a dairy farm. The qualitative Morris method provided a screening of the input factors. The two other quantitative methods were used to investigate more thoroughly the effects of input factors on output variables. Despite differences in terms of concepts and assumptions, the three methods provided similar results. Among the 44 factors under study, N₂O emissions were mainly sensitive to the fraction of N₂O emitted during denitrification, the maximum rate of nitrification, the soil bulk density and the cropland area.

The aim of this study is to illustrate the importance of farm scale heterogeneity on nitrogen (N) losses in agricultural landscapes. Results are exemplified with a chain of N models calculating farm-N balances and distributing the N-surplus to N-losses (volatilisation, denitrification, leaching) and soil-N accumulation/release in a Danish landscape. Possible non-linearities in upscaling are assessed by comparing average model results based on (i) individual farm level calculations and (ii) averaged inputs at landscape level. Effects of the non-linearities that appear when scaling up from farm to landscape are demonstrated. Especially in relation to ammonia losses the non-linearity between livestock density and N-loss is significant (p > 0.999), with around 20–30% difference compared to a scaling procedure not taking this non-linearity into account. A significant effect of farm type on soil N accumulation (p > 0.95) was also identified and needs to be included when modelling landscape level N-fluxes and greenhouse gas emissions.

INTRODUCTION: It is predicted that demand for electricity in Islamic Republic of Iran will continue to increase dramatically in the future due to the rapid pace of economic development leading to construction of new power plants. At the present time, most of electricity is generated by burning fossil fuels which result in emission of great deal of pollutants and greenhouse gases (GHG) such as SO₂, NOₓ, and CO₂. The power industry is the largest contributor to these emissions. Due to minimal emission of GHG by renewable and nuclear power plants, they are most suitable replacements for the fossil-fueled power plants. However, the nuclear power plants are more suitable than renewable power plants in providing baseload electricity. The Bushehr Nuclear Power Plant, the only nuclear power plant of Iran, is expected to start operation in 2010. This paper attempts to interpret the role of Bushehr nuclear power plant (BNPP) in CO₂ emission trend of power plant sector in Iran. MATERIALS AND METHODS: In order to calculate CO₂ emissions from power plants, National CO₂ coefficients have been used. The National CO₂ emission coefficients are according to different fuels (natural gas, fuels gas, fuel oil). RESULTS AND DISCUSSION: By operating Bushehr Nuclear Power Plant in 2010, nominal capacity of electricity generation in Iran will increase by about 1,000 MW, which increases the electricity generation by almost 7,000 MWh/year (it is calculated according to availability factor and nominal capacity of BNPP). CONCLUSIONS: Bushehr Nuclear Power Plant will decrease the CO₂ emission in Iran power sector, by about 3% in 2010.