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Photovoltaic capacity additions: the optimal rate of deployment with sensitivity to time-based GHG emissions

Description
Current policies subsidizing or accelerating deployment of photovoltaics (PV) are typically motivated by claims of environmental benefit, such as the reduction of CO2 emissions generated by the fossil-fuel fired power plants that PV is intended to displace. Existing practice is to assess these environmental benefits on a net life-cycle basis,…

Current policies subsidizing or accelerating deployment of photovoltaics (PV) are typically motivated by claims of environmental benefit, such as the reduction of CO2 emissions generated by the fossil-fuel fired power plants that PV is intended to displace. Existing practice is to assess these environmental benefits on a net life-cycle basis, where CO2 benefits occurring during use of the PV panels is found to exceed emissions generated during the PV manufacturing phase including materials extraction and manufacture of the PV panels prior to installation. However, this approach neglects to recognize that the environmental costs of CO2 release during manufacture are incurred early, while environmental benefits accrue later. Thus, where specific policy targets suggest meeting CO2 reduction targets established by a certain date, rapid PV deployment may have counter-intuitive, albeit temporary, undesired consequences. Thus, on a cumulative radiative forcing (CRF) basis, the environmental improvements attributable to PV might be realized much later than is currently understood. This phenomenon is particularly acute when PV manufacture occurs in areas using CO2 intensive energy sources (e.g., coal), but deployment occurs in areas with less CO2 intensive electricity sources (e.g., hydro). This thesis builds a dynamic Cumulative Radiative Forcing (CRF) model to examine the inter-temporal warming impacts of PV deployments in three locations: California, Wyoming and Arizona. The model includes the following factors that impact CRF: PV deployment rate, choice of PV technology, pace of PV technology improvements, and CO2 intensity in the electricity mix at manufacturing and deployment locations. Wyoming and California show the highest and lowest CRF benefits as they have the most and least CO2 intensive grids, respectively. CRF payback times are longer than CO2 payback times in all cases. Thin film, CdTe PV technologies have the lowest manufacturing CO2 emissions and therefore the shortest CRF payback times. This model can inform policies intended to fulfill time-sensitive CO2 mitigation goals while minimizing short term radiative forcing.
ContributorsTriplican Ravikumar, Dwarakanath (Author) / Seager, Thomas P (Thesis advisor) / Fraser, Matthew P (Thesis advisor) / Chester, Mikhail V (Committee member) / Sinha, Parikhit (Committee member) / Arizona State University (Publisher)
Created2013
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Community Air Quality Measurement, Management, and Control Methods

Description
As air quality standards become more stringent to combat poor air quality, there is a greater need for more effective pollutant control measures and increased air monitoring network coverage. Polluted air, in the form of aerosols and gases, can impact respiratory and cardiovascular health, visibility, the climate, and material weathering.…

As air quality standards become more stringent to combat poor air quality, there is a greater need for more effective pollutant control measures and increased air monitoring network coverage. Polluted air, in the form of aerosols and gases, can impact respiratory and cardiovascular health, visibility, the climate, and material weathering. This work demonstrates how traditional networks can be used to study generational events, how these networks can be supplemented with low-cost sensors, and the effectiveness of several control measures. First, an existing network was used to study the effect of COVID-19 travel restrictions on air quality in Maricopa County, Arizona, which would not have been possible without the historical record that a traditional network provides. Although this study determined that decreases in CO and NO2 were not unique to the travel restrictions, it was limited to only three locations due to network sparseness. The second part of this work expanded the traditional NO2 monitoring network using low-cost sensors, that were first collocated with a reference monitor to evaluate their performance and establish a robust calibration. The sensors were then deployed to the field to varying results; their calibration was further improved by cycling the sensors between deployment and reference locations throughout the summer. This calibrated NO2 data, along with volatile organic compound data, were combined to enhance the understanding of ozone formation in Maricopa County, especially during wildfire season. In addition to being in non-attainment for ozone standards, Maricopa County fails to meet particulate matter under 10 μm (PM10) standards. A large portion of PM10 emissions is attributed to fugitive dust that is either windblown or kicked up by vehicles. The third part of this work demonstrated that Enzyme Induced Carbonate Precipitation (EICP) treatments aggregate soil particles and prevent fugitive dust emissions. The final part of the work examined tire wear PM10 emissions, as vehicles are another significant contributor to PM10. Observations showed a decrease in tire wear PM10 during winter with little change when varying the highway surface type.
ContributorsMiech, Jason Andrew (Author) / Herckes, Pierre (Thesis advisor) / Fraser, Matthew P (Committee member) / Shock, Everett (Committee member) / Arizona State University (Publisher)
Created2023