Impact of regional climate change and future emission scenarios on surface O3 and PM2.5 over India

Eleven of the world\u27s 20 most polluted cities are located in India and poor air quality is already a major public health issue. However, anthropogenic emissions are predicted to increase substantially in the short-term (2030) and medium-term (2050) futures in India, especially if no further policy efforts are made. In this study, the EMEP/MSC-W chemical transport model has been used to predict changes in surface ozone (O3) and fine particulate matter (PM 2.5 ) for India in a world of changing emissions and climate. The reference scenario (for present-day) is evaluated against surface-based measurements, mainly at urban stations. The evaluation has also been extended to other data sets which are publicly available on the web but without quality assurance. The evaluation shows high temporal correlation for O 3 (r = 0.9) and high spatial correlation for PM 2.5 (r = 0.5 and r = 0.8 depending on the data set) between the model results and observations. While the overall bias in PM 2.5 is small (lower than 6%), the model overestimates O 3 by 35%. The underestimation in NO x titration is probably the main reason for the O 3 overestimation in the model. However, the level of agreement can be considered satisfactory in this case of a regional model being evaluated against mainly urban measurements, and given the inevitable uncertainties in much of the input data. For the 2050s, the model predicts that climate change will have distinct effects in India in terms of O 3 pollution, with a region in the north characterized by a statistically significant increase by up to 4% (2 ppb) and one in the south by a decrease up to -3% (-1.4 ppb). This variation in O 3 is assumed to be partly related to changes in O 3 deposition velocity caused by changes in soil moisture and, over a few areas, partly also by changes in biogenic non-methane volatile organic compounds. Our calculations suggest that PM 2.5 will increase by up to 6.5% over the Indo-Gangetic Plain by the 2050s. The increase over India is driven by increases in dust, particulate organic matter (OM) and secondary inorganic aerosols (SIAs), which are mainly affected by the change in precipitation, biogenic emissions and wind speed. The large increase in anthropogenic emissions has a larger impact than climate change, causing O 3 and PM 2.5 levels to increase by 13 and 67% on average in the 2050s over the main part of India, respectively. By the 2030s, secondary inorganic aerosol is predicted to become the second largest contributor to PM 2.5 in India, and the largest in the 2050s, exceeding OM and dust

Geosimulation and Multicriteria Modelling of Residential Land Development in the City of Tehran: A Comparative Analysis of Global and Local Models

Conventional models for simulating land-use patterns are insufficient in addressing complex dynamics of urban systems. A new generation of urban models, inspired by research on cellular automata and multi-agent systems, has been proposed to address the drawbacks of conventional modelling. This new generation of urban models is called geosimulation. Geosimulation attempts to model macro-scale patterns using micro-scale urban entities such as vehicles, homeowners, and households. The urban entities are represented by agents in the geosimulation modelling. Each type of agents has different preferences and priorities and shows different behaviours. In the land-use modelling context, the behaviour of agents is their ability to evaluate the suitability of parcels of land using a number of factors (criteria and constraints), and choose the best land(s) for a specific purpose. Multicriteria analysis provides a set of methods and procedures that can be used in the geosimulation modelling to describe the behaviours of agents. There are three main objectives of this research. First, a framework for integrating multicriteria models into geosimulation procedures is developed to simulate residential development in the City of Tehran. Specifically, the local form of multicriteria models is used as a method for modelling agents’ behaviours. Second, the framework is tested in the context of residential land development in Tehran between 1996 and 2006. The empirical research is focused on identifying the spatial patterns of land suitability for residential development taking into account the preferences of three groups of actors (agents): households, developers, and local authorities. Third, a comparative analysis of the results of the geosimulation-multicriteria models is performed. A number of global and local geosimulation-multicriteria models (scenarios) of residential development in Tehran are defined and then the results obtained by the scenarios are evaluated and examined. The output of each geosimulation-multicriteria model is compared to the results of other models and to the actual pattern of land-use in Tehran. The analysis is focused on comparing the results of the local and global geosimulation-multicriteria models. Accuracy measures and spatial metrics are used in the comparative analysis. The results suggest that, in general, the local geosimulation-multicriteria models perform better than the global methods

Spatiotemporal modeling of interactions between urbanization and flood risk: a multi-level approach

The main goal of this PhD research is to investigate the expected flood damage for future urban patterns at different scales. Four main steps are followed to accomplish this goal. In the first step, a retrospective analysis is performed for the evolution of the urban development in Wallonia (Belgium) as a case study. Afterward, two land use change models, cellular automata-based, and agent-based are proposed and compared. Based on this comparison, the agent-based model is employed to simulate future urbanization scenarios. An important feature of this research is evident in the consideration of the multiple densities of built-up areas, which enables to study both expansion and densification processes. As the model simulates urbanization up to 2100, forecasting land use change over such time frames entails very significant uncertainties. In this regard, uncertainty in land use change models has been considered. In the third step, 24 urbanization scenarios that differed in terms of spatial policies and urbanization rate are generated. The simulated scenarios have then been integrated with a hydrological model. The results suggest that urban development will continue within flood-prone zones in a number of scenarios. Therefore, in the fourth and last step, a procedural urban generation system is developed to analyze the respective influence of various urban layout characteristics on inundation flow, which assists in designing flood-resistant urban layouts within the flood-prone zones.This thesis was funded through the ARC grant for Concerted Research Actions for project number 13/17-01 entitled "Land-use change and future flood risk: influence of micro-scale spatial patterns (FloodLand)" financed by the French Community of Belgium (Wallonia-Brussels Federation)