Nutrient cycling and nutrient use efficiency in urban and peri-urban agriculture of Kabul, Afghanistan

Like elsewhere also in Kabul, Afghanistan urban and peri-urban agriculture (UPA) has often been accused of being resource inefficient and unsustainable causing negatives externalities to community health and to the surroundings. These arise from the inappropriate management and use of agricultural inputs, including often pesticides and inter-city wastes containing heavy metal residues and pathogens. To address these concerns, parallel studies with the aims of quantification of carbon (C), nitrogen (N), phosphorus (P) and potassium (K) horizontal and vertical fluxes; the assessment of heavy metal and pathogen contaminations of UPA produce, and an economic analysis of cereal, vegetable and grape production systems conducted for two years in UPA of Kabul from April 2008 to October 2009. The results of the studies from these three UPA diverse production systems can be abridged as follows: Biennial net balances in vegetable production systems were positive for N (80 kg ha-1 ), P (75 kg ha-1) and C (3,927 kg ha-1), negative for K (-205 kg ha-1), whereas in cereal production systems biennial horizontal balances were positive for P (20 kg ha-1 ) and C (4,900 kg ha-1) negative for N (-155 kg ha-1) and K (-355 kg ha-1) and in vineyards corresponding values were highly positive for N (295 kg ha-1), P (235 kg ha-1), C (3,362 kg ha-1) and slightly positive for K (5 kg ha-1). Regardless of N and C gaseous emissions, yearly leaching losses of N and P in selected vegetable gardens varied from 70 - 205 kg N ha-1 and 5 - 10 kg P ha-1. Manure and irrigation water contributed on average 12 - 79% to total Inputs of N, P, K and C, 10 - 53% to total inputs of C in the gardens and fields. The elevated levels of heavy metal and pathogen loads on fresh UPA vegetables reflected contamination from increasing traffic in the city, deposits of the past decades of war, lacking collection and treatment of raw inter-city wastes which call for solutions to protect consumer and producer health and increase reliability of UPA productions. A cost-revenue analysis of all inputs and outputs of cereal, vegetable and grapes production systems over two years showed substantial differences in net UPA household income. To confirm these results, more detailed studies are needed, but tailoring and managing the optimal application of inputs to crop needs will significantly enhance farmer’s better revenues as will as environmental and produce quality.

On Solution Sets of Information Inequalities

We investigate solution sets of a special kind of linear inequality systems. In particular, we derive characterizations of these sets in terms of minimal solution sets. The studied inequalities emerge as information inequalities in the context of Bayesian networks. This allows to deduce important properties of Bayesian networks, which is important within causal inference.

Development of an ArcGIS extension to model urban climate factors

The possibility to develop automatically running models which can capture some of the most important factors driving the urban climate would be very useful for many planning aspects. With the help of these modulated climate data, the creation of the typically used “Urban Climate Maps” (UCM) will be accelerated and facilitated. This work describes the development of a special ArcGIS software extension, along with two support databases to achieve this functionality. At the present time, lacking comparability between different UCMs and imprecise planning advices going along with the significant technical problems of manually creating conventional maps are central issues. Also inflexibility and static behaviour are reducing the maps’ practicality. From experi-ence, planning processes are formed more productively, namely to implant new planning parameters directly via the existing work surface to map the impact of the data change immediately, if pos-sible. In addition to the direct climate figures, information of other planning areas (like regional characteristics / developments etc.) have to be taken into account to create the UCM as well. Taking all these requirements into consideration, an automated calculation process of urban climate impact parameters will serve to increase the creation of homogenous UCMs efficiently.