5 resultados para rural-urban comparison
em DRUM (Digital Repository at the University of Maryland)
Resumo:
Urban forests are often highly fragmented with many exotic species. Altered disturbance regimes and environmental pollutants influence urban forest vegetation. One of the best ways to understand the impacts of land-use on forest composition is through long-term research. In 1998, the Baltimore Ecosystem Study established eight forest plots to investigate the impacts of urbanization on natural ecosystems. Four plots were located in urban forest patches and four were located in rural forests. In 2015, I revisited these plots to measure abundances and quantify change in forest composition, diversity, and structure. Sapling, shrub, and seedling abundance were reduced in the rural plots. Alpha diversity and turnover was lower in the rural plots. Beta diversity was reduced in the rural plots. The structure of the urban plots was mostly unchanged, except for a highly reduced sapling layer. Beta diversity in the urban plots was consistent across surveys due to high species turnover.
Resumo:
Streams in urban areas often utilize channelization and other bank erosion control measures to improve flood conveyance, reduce channel migration, and overbank flooding. This leads to reductions in evapotranspiration and sediment storage on floodplains. The purpose of this study is to quantify the evapotranspiration and sediment transport capacity in the Anacostia Watershed, a large Coastal Plain urban watershed, and to compare these processes to a similar sized non-urban watershed. Times series data of hydrologic and hydraulic changes in the Anacostia, as urbanization progressed between 1939-2014, were also analyzed. The data indicates lower values of warm season runoff in the non-urban stream, suggesting a shift from evapotranspiration to runoff in urban streams. Channelization in the Anacostia also increased flow velocities and decreased high flow width. The high velocities associated with channelization and the removal of floodplain storage sites allows for the continued downstream transport of sediment despite stream bank stabilization.
Resumo:
Carbon and nitrogen loading to streams and rivers contributes to eutrophication as well as greenhouse gas (GHG) production in streams, rivers and estuaries. My dissertation consists of three research chapters, which examine interactions and potential trade-offs between water quality and greenhouse gas production in urban streams of the Chesapeake Bay watershed. My first research project focused on drivers of carbon export and quality in an urbanized river. I found that watershed carbon sources (soils and leaves) contributed more than in-stream production to overall carbon export, but that periods of high in-stream productivity were important over seasonal and daily timescales. My second research chapter examined the influence of urban storm-water and sanitary infrastructure on dissolved and gaseous carbon and nitrogen concentrations in headwater streams. Gases (CO2, CH4, and N2O) were consistently super-saturated throughout the course of a year. N2O concentrations in streams draining septic systems were within the high range of previously published values. Total dissolved nitrogen concentration was positively correlated with CO2 and N2O and negatively correlated with CH4. My third research chapter examined a long-term (15-year) record of GHG emissions from soils in rural forests, urban forest, and urban lawns in Baltimore, MD. CO2, CH4, and N2O emissions showed positive correlations with temperature at each site. Lawns were a net source of CH4 + N2O, whereas forests were net sinks. Gross CO2 fluxes were also highest in lawns, in part due to elevated growing-season temperatures. While land cover influences GHG emissions from soils, the overall role of land cover on this flux is very small (< 0.5%) compared with gases released from anthropogenic sources, according to a recent GHG budget of the Baltimore metropolitan area, where this study took place.
Resumo:
In the course of integrating into the global market, especially since China’s WTO accession, China has achieved remarkable GDP growth and has become the second largest economy in the world. These economic achievements have substantially increased Chinese incomes and have generated more government revenue for social progress. However, China’s economic progress, in itself, is neither sufficient for achieving desirable development outcomes nor a guarantee for expanding peoples’ capabilities. In fact, a narrow emphasis on GDP growth proves to be unsustainable, and may eventually harm the life quality of Chinese citizens. Without the right set of policies, a deepening trade-openness policy in China may enlarge social disparities and some people may further be deprived of basic public services and opportunities. To address these concerns, this dissertation, a set of three essays in Chapters 2-4, examines the impact of China's WTO accession on income distribution, compares China’s income and multidimensional poverty reduction and investigates the factors, including the WTO accession, that predict multidimensional poverty. By exploiting the exogenous variation in exposure to tariff changes across provinces and over time, Chapter 2 (Essay 1) estimates the causal effects of trade shocks and finds that China’s WTO accession has led to an increase in average household income, but its impacts are not evenly distributed. Households in urban areas have benefited more significantly than those in rural areas. Households with members working in the private sector have benefited more significantly than those in the public sector. However, the WTO accession has contributed to reducing income inequality between higher and lower income groups. Chapter 3 (Essay 2) explains and applies the Alkire and Foster Method (AF Method), examines multidimensional poverty in China and compares it with income poverty. It finds that China’s multidimensional poverty has declined dramatically during the period from 1989-2011. Reduction rates and patterns, however, vary by dimensions: multidimensional poverty reduction exhibits unbalanced regional progress as well as varies by province and between rural and urban areas. In comparison with income poverty, multidimensional poverty reduction does not always coincide with economic growth. Moreover, if one applies a single measure ─ either that of income or multidimensional poverty ─ a certain proportion of those who are poor remain unrecognized. By applying a logistic regression model, Chapter 4 (Essay 3) examines factors that predict multidimensional poverty and finds that the major factors predicting multidimensional poverty in China include household size, education level of the household head, health insurance coverage, geographic location, and the openness of the local economy. In order to alleviate multidimensional poverty, efforts should be targeted to (i) expand education opportunities for the household heads with low levels of education, (ii) develop appropriate geographic policies to narrow regional gaps and (iii) make macroeconomic policies work for the poor.
Resumo:
Common building energy modeling approaches do not account for the influence of surrounding neighborhood on the energy consumption patterns. This thesis develops a framework to quantify the neighborhood impact on a building energy consumption based on the local wind flow. The airflow in the neighborhood is predicted using Computational Fluid Dynamics (CFD) in eight principal wind directions. The developed framework in this study benefits from wind multipliers to adjust the wind velocity encountering the target building. The input weather data transfers the adjusted wind velocities to the building energy model. In a case study, the CFD method is validated by comparing with on-site temperature measurements, and the building energy model is calibrated using utilities data. A comparison between using the adjusted and original weather data shows that the building energy consumption and air system heat gain decreased by 5% and 37%, respectively, while the cooling gain increased by 4% annually.