Risa Patarasuk

Toward quantification and source sector identification of fossil fuel CO2 emissions from an urban area: Results from the INFLUX experiment

The Indianapolis Flux Experiment (INFLUX) aims to develop and assess methods for quantifying urban greenhouse gas emissions. Here we use CO2, 14CO2, and CO measurements from tall towers around Indianapolis, USA, to determine urban total CO2, the fossil fuel derived CO2 component (CO2ff), and CO enhancements relative to background measurements. When a local background directly upwind of the urban area is used, the wintertime total CO2 enhancement over Indianapolis can be entirely explained by urban CO2ff emissions. Conversely, when a continental background is used, CO2ff enhancements are larger and account for only half the total CO2 enhancement, effectively representing the combined CO2ff enhancement from Indianapolis and the wider region. In summer, we find that diurnal variability in both background CO2 mole fraction and covarying vertical mixing makes it difficult to use a simple upwind-downwind difference for a reliable determination of total CO2 urban enhancement. We use characteristic CO2ff source sector CO:CO2ff emission ratios to examine the contribution of the CO2ff source sectors to total CO2ff emissions. This method is strongly sensitive to the mobile sector, which produces most CO. We show that the inventory-based emission product (“bottom up”) and atmospheric observations (“top down”) can be directly compared throughout the diurnal cycle using this ratio method. For Indianapolis, the top-down observations are consistent with the bottom-up Hestia data product emission sector patterns for most of the diurnal cycle but disagree during the nighttime hours. Further examination of both the top-down and bottom-up assumptions is needed to assess the exact cause of the discrepancy.

High‐resolution atmospheric inversion of urban CO2 emissions during the dormant season of the Indianapolis Flux Experiment (INFLUX)

Based on a uniquely dense network of surface towers measuring continuously the atmospheric concentrations of greenhouse gases (GHGs), we developed the first comprehensive monitoring systems of CO2 emissions at high resolution over the city of Indianapolis. The urban inversion evaluated over the 2012-2013 dormant season showed a statistically significant increase of about 20% (from 4.5 to 5.7 MtC ± 0.23 MtC) compared to the Hestia CO2 emission estimate, a state-of-the-art building-level emission product. Spatial structures in prior emission errors, mostly undetermined, appeared to affect the spatial pattern in the inverse solution and the total carbon budget over the entire area by up to 15%, while the inverse solution remains fairly insensitive to the CO2 boundary inflow and to the different prior emissions (i.e., ODIAC). Preceding the surface emission optimization, we improved the atmospheric simulations using a meteorological data assimilation system also informing our Bayesian inversion system through updated observations error variances. Finally, we estimated the uncertainties associated with undetermined parameters using an ensemble of inversions. The total CO2 emissions based on the ensemble mean and quartiles (5.26-5.91 MtC) were statistically different compared to the prior total emissions (4.1 to 4.5 MtC). Considering the relatively small sensitivity to the different parameters, we conclude that atmospheric inversions are potentially able to constrain the carbon budget of the city, assuming sufficient data to measure the inflow of GHG over the city, but additional information on prior emission error structures are required to determine the spatial structures of urban emissions at high resolution.

Urban high-resolution fossil fuel CO2 emissions quantification and exploration of emission drivers for potential policy applications

Fossil fuel carbon dioxide (FFCO2) emissions are the largest driver of anthropogenic climate change. Approximately three-quarters of the world’s fossil fuels carbon dioxide emissions are generated in urban areas. We used the Hestia high resolution approach to quantify FFCO2 for Salt Lake County, Utah, USA and demonstrate the importance of high resolution quantification to urban emissions mitigation policymaking. We focus on the residential and onroad sectors across both urbanized and urbanizing parts of the valley. Stochastic Impact by Regression on Population, Affluence, and Technology (STIRPAT) regression models using sociodemographic data at the census block group level shows that population, per capita income, and building age exhibit positive relationships while household size shows a negative relationship with FFCO2 emissions. Compact development shows little effect on FFCO2 emissions in this domain. FFCO2 emissions in high income block groups is twice as sensitive to income than low income block groups. Emissions are four times as sensitive to household size in low-income versus high-income block groups. These results suggest that policy options targeting personal responsibility or knowledge feedback loops may be the most effective strategies. Examples include utility bill performance comparison or publicly available energy maps identifying high-emitting areas. Within the onroad sector, high emissions density (FFCO2/km) is associated with primary roads, while high emissions intensity (FFCO2/VMT) is associated with secondary roads. Opportunities exist for alignment of public transportation extension with remaining high emission road segments, offering a prioritization of new onroad transportation policy in Salt Lake County.

Emissions and topographic effects on column CO_2 (XCO_2) variations, with a focus on the Southern California Megacity

Within the California South Coast Air Basin (SoCAB), X_(CO)_2 varies significantly due to atmospheric dynamics and the nonuniform distribution of sources. X_(CO)_2 measurements within the basin have seasonal variation compared to the “background” due primarily to dynamics, or the origins of air masses coming into the basin. We observe basin-background differences that are in close agreement for three observing systems: Total Carbon Column Observing Network (TCCON) 2.3 ± 1.2 ppm, Orbiting Carbon Observatory-2 (OCO-2) 2.4 ± 1.5 ppm, and Greenhouse gases Observing Satellite 2.4 ± 1.6 ppm (errors are 1σ). We further observe persistent significant differences (∼0.9 ppm) in X_(CO)_2 between two TCCON sites located only 9 km apart within the SoCAB. We estimate that 20% (±1σ confidence interval (CI): 0%, 58%) of the variance is explained by a difference in elevation using a full physics and emissions model and 36% (±1σ CI: 10%, 101%) using a simple, fixed mixed layer model. This effect arises in the presence of a sharp gradient in any species (here we focus on CO_2) between the mixed layer (ML) and free troposphere. Column differences between nearby locations arise when the change in elevation is greater than the change in ML height. This affects the fraction of atmosphere that is in the ML above each site. We show that such topographic effects produce significant variation in X_(CO)_2 across the SoCAB as well.

Land Cover Pattern and Road Types in Lop Buri Province, Thailand, 1989–2006

Road development leads to several benefits to a region, such as accessibility for people and resources to market areas, farmland, forests, and residential areas. Such a development has an important role in the economic and social development of a nation. Road network development fosters economic growth by providing a means of transportation for people and goods. Although the development of roads brings an overall benefit to society by improving overall connectivity, its impact on land cover is less well understood. This study aims to determine the relationships between road types and land cover in Lop Buri Province, Thailand. The research questions are (1) what is the pattern of land cover associated with different road types? and (2) what is the pattern of change in terms of land cover distribution within a road type? The analysis relies on descriptive statistics and the use of GIS and remote sensing technology. The study concludes that with the improvement of the road network development that aimed to improve social and economic development over the past two decades, the distribution of land cover along these types of roads has changed over time. The loss of forest and increase in upland crops has led to changes in local climate and local hydrology as well as the loss of biodiversity.