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A comprehensive evaluation of the use of Lagrangian particle dispersion models for inverse modeling of greenhouse gas emissions
Using the example of sulfur hexafluoride (SF6), we investigate the use of Lagrangian particle dispersion models (LPDMs) for inverse modeling of greenhouse gas (GHG) emissions and explore the limitations of this approach. We put the main focus on the impacts of baseline methods and the LPDM backward simulation period on the a posteriori emissions determined by the inversion. We consider baseline methods that are based on a statistical selection of observations at individual measurement sites and a global-distribution-based (GDB) approach, where global mixing ratio fields are coupled to the LPDM back-trajectories at their termination points. We show that purely statistical baseline methods can cause large systematic errors, which lead to inversion results that are sensitive to the LPDM backward simulation period and can generate unrealistic global total a posteriori emissions. The GDB method produces a posteriori emissions that are far less sensitive to the backward simulation period and that show a better agreement with recognized global total emissions. Our results show that longer backward simulation periods, beyond the often used 5 to 10 d, reduce the mean squared error and increase the correlation between a priori modeled and observed mixing ratios. Also, the inversion becomes less sensitive to biases in the a priori emissions and the global mixing ratio fields for longer backward simulation periods. Further, longer periods might help to better constrain emissions in regions poorly covered by the global SF6 monitoring network. We find that the inclusion of existing flask measurements in the inversion helps to further close these gaps and suggest that a few additional and well-placed flask sampling sites would have great value for improving global a posteriori emission fields.
A DPSIR-analysis of water uses and related water quality issues in the Colombian Alto and Medio Dagua Community Council
A portion of Colombia’s water resources is located on the Pacific coast within the territory of the Community Council of Alto and Medio Dagua (CC-AMDA). Though a harmonious balance between the communities’ subsistent activities and nature was maintained for centuries, the appearance of modern modes of resource extraction has negatively affected the environment, especially the water resources. The Driver-Pressure-State- Impact-Response (DPSIR) framework was used to analyze water quality problems within this community council. The DPSIR analysis revealed that agriculture, mining, logging and infrastructure development constitute important sectoral drivers with some contribution from tourism and fisheries. Pressures included inputs of organic matter, sediment, nutrients and chemical contaminants to the Dagua river, and to the Bay of Buenaventura. These produced corresponding State changes in the water bodies. Impacts on human welfare were poor public health, reduced food and water security, economic loss and some displacement. Societal Responses included public protests and campaigns, legal actions and policy changes for improved governance. As a future policy option, the formation of community-based water resources management is recommended. Though DPSIR was able to link cause-effect relations, further empirical research on these water bodies is necessary to fill in existing gaps in the data set, particularly for public health threatening contaminants.
Taylor & Francis