RESUMO
Oil and gas development is occurring in urban, densely populated neighborhoods; however, the impacts of these operations on neighborhood air quality are not well characterized. In this research, we leveraged ambient air monitoring adjacent to an oil and gas production site in Los Angeles, California during active and idle periods. This study analyzed continuous methane (CH4) and non-methane hydrocarbon (NMHC) measurements, together with triggered grab samples and 24 hour integrated canister samples collected by the South Coast Air Quality Management District. Ambient air pollutant levels and trends were evaluated during active and idle well operations to assess changes in neighborhood air quality after the suspension of oil and gas production. We find that mean concentrations of methane, NMHC, benzene, toluene, ethylbenzene, xylenes, styrene, n-hexane, n-pentane, ethane, and propane decreased following the stop in production activities. Using a source apportionment approach, we observed that the "natural gas" drilling source contributed 23.7% to the total VOCs measured during the active phase, and only 0.6% to the total measured VOCs in the idle phase. Near urban oil and gas production sites, residents may face poorer air quality due to the oil and gas activities which may pose adverse health and environmental risks among proximate communities.
Assuntos
Poluentes Atmosféricos , Poluição do Ar , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Monitoramento Ambiental , Hidrocarbonetos/análise , Los Angeles , Gás NaturalRESUMO
Over the past decade, sensor networks have been proven valuable to assess air quality on highly localized scales. Here we leverage innovative sensors to characterize gaseous pollutants in a complex urban environment and evaluate differences in air quality in three different Los Angeles neighborhoods where oil and gas activity is present. We deployed monitors across urban neighborhoods in South Los Angles adjacent to oil and gas facilities with varying levels of production. Using low-cost sensors built in-house, we measured methane, total non-methane hydrocarbons (TNMHCs), carbon monoxide, and carbon dioxide during three deployment campaigns over four years. The multi-sensor linear regression calibration model developed to quantify methane and TNMHCs offers up to 16% improvement in coefficient of determination and up to a 22% reduction in root mean square error for the most recent dataset as compared to previous models. The deployment results demonstrate that airborne methane concentrations are higher within a 500 m radius of three urban oil and gas facilities, as well as near a natural gas distribution pipeline, likely a result of proximity to sources. While there are numerous additional sources of TNMHCs in complex urban environments, some sites appear to be larger emitters than others. Significant methane emissions were also measured at an idle site, suggesting that fugitive emissions may still occur even if production is ceased. Episodic spikes of both compounds suggested an association with oil and gas activities, demonstrating how sensor networks can be used to elucidate community-scale sources and differences in air quality moving forward.