Going Small When the City Grows Big
Abstract Actual development of water and wastewater systems in towns is an outcome of several interrelated factors such as physical, economic, and social environments. Demography is also an important factor to consider in the formulation of development strategies. Too often in policy papers, population increase only serves as an argument for urgent action, but rarely as a factor in its own right that affects chances of improving a grave situation. A model is developed to generate water management options in urban areas related to population growth. A hypothesis is that management should go small in periods when the city expands rapidly. A study is presented of the development of water and sanitation in the town of Kisumu in Kenya on the shore of Lake Victoria during last century. The aim is to describe and analyze actual development in the water sector and to foresee what prospective developments could be identified in light of continued rapid population growth. The slow growth of the town in the colonial period allowed towns to adequately meet the needs of all residents for water. The extremely rapid population growth after Independence in 1963 interacted with other factors to cause a successive deterioration of residents access to water and sewage disposal.
Future Projections of Urban Waste Flows aand their Impacts in African Metropolises Cities
This paper presents future trends of urban wastes and their impacts on the environment of African cities using plausible mitigation scenarios. To accomplish this, an integrated dynamic model for urban waste flows was developed, tested, calibrated and validated. Its parameter sensitivity was analyzed. Using population projection up to 2052 with different levels of technological implementation, policy enforcement and awareness raising, four runs were executed. The “business as usual” run showed that with no additional mitigation measures, the environmental quality in Kampala and Dar es salaam Cities deteriorates. The “more enforcement” and “more collection” scenarios showed good reduction in environmental loads but they perform less well in resource recovery. The “proper management” scenario that combines enhanced technological implementation, awareness raising and policy enforcement, produced the smallest environmental loads, and recovered the largest amount of resources. Thus, the city authorities, general public, community based organisations and Non-governmental organizations would have to increase their efforts in finances and commitment to improve the urban environmental quality and increase resource recovery.
Complexity, Network-Decisions And Alternative Risk Premia: Some New Theories Of Structural Change And Portfolio Decisions.
Structural Change is the basis for many decisions such as government fiscal and monetary policies, government interventions, corporate-expenditure decisions, corporate strategic decisions, portfolio management decisions in finance; household allocation decisions, etc.. Structural change in industries and national economies is increasingly more difficult to detect partly because of the growth and dominance of Complex Systems and “Networks” in modern industries and economies – such Networks and Complex Systems include GVCs (global value chains), retail store networks; franchising networks; internet networks; services networks; credit-chains in industries; online social networks; etc.. The relationship between Complexity and Structural Change is well established in the physics, applied math and economic dynamics literatures. Traditional definitions and modeling of structural change have erroneously focused on changes in labor, technological progress, market share, and or capital – which are grossly inadequate in the new economy and post- global financial crisis (as confirmed by changes in the global retailing and housing industries and other industries). Also the modeling of structural change seems to be constrained by the availability of data, and often omits the relationship between structural change on one hand, and globalization, financial stability and international financial contagion. This article: i) introduces the Operations Strategy Model of structural change, explains how it differs from the Lewis Model of Structural Change; and explains the often omitted relationship between operations strategy (of companies and government agencies) and structural change; ii) introduces other new Complexity-based models/theories of Structural Change in industries; iii) reviews the relationships among Operations Research, Complexity and Structural Change; iv) explains the symbiotic relationship between structural change on one hand, and economic growth, financial stability, financial contagion and globalization; v) discusses the significant gap between academic research and practice and explains some issues and factors that should be considered in the development and testing of structural change models; vi) explains how alternative risk premia can be generated from new models of Structural Change.