Atmosphere最新文献

Urban areas and their surroundings feature unique, horizontally inhomogeneous spatial distributions of land use and land cover, leading to urban heat islands (UHIs) for both air and land surface temperature that complicate the estimation of urban sensible heat flux. The urban dispersion option in AERMOD, the American Meteorological Society (AMS)/Environmental Protection Agency (EPA) Regulatory Model, incorporates this effect at night through a "convective like boundary layer" that modifies the single column meteorology based on a population number representative of the urban area. The model produces positive nighttime sensible heat flux values that often significantly overestimate observed values from the literature. This study re-examines the formulation of the AERMOD urban option assumptions, methodology, and original evaluation against a field study of a power plant in Indianapolis. We investigate replacing the population-based parameterizations of urban-surrounding temperature differences ( $\Delta T$ ) with observations of remotely sensed land surface temperature (LST) data from the Advanced Baseline Imager on the GOES-16/R/East geostationary satellite. We generated a monthly averaged, hourly, wind direction-dependent, clear sky land surface urban heat island $\Delta T$ database for 480 continental United States (CONUS) urban areas, as defined by the 2010 US Census. These $\Delta T$ values are used to advise city-specific horizontal advection corrections to sensible heat flux estimates that are neglected from simple energy balance models. The four cities of Cleveland, Amarillo, Atlanta, and Baltimore are highlighted, showing that the AERMOD predicted nighttime $\Delta T$ values are 794%, 416%, 1048%, and 758% higher, respectively, than the GOES-16 observations. These overestimated $\Delta T$ values in AERMOD lead to nighttime sensible heat flux values > 100 W/m² that rival daytime values. However, using the GOES-16 observations as horizontal advection corrections to sensible heat flux results in trends that match the expected neutral to slightly positive nighttime values from observations recorded in the literature. The annual nighttime average in 2021 was -0.8 W/m², 8.6 W/m², 3.0 W/m², and 3.1 W/m² in Cleveland, Amarillo, Atlanta, and Baltimore, respectively, using this approach. Finally, reviewing the initial evaluation with the Indianapolis database against independent studies from the literature suggest that the AERMOD urban option inadvertently implements an urban heat island modeling approach to account for what was a low-level jet during the field study.

Poor air quality can harm human health and the environment. Air quality data are needed to understand and reduce exposure to air pollution. Air sensor data can supplement national air monitoring data, allowing for a better understanding of localized air quality and trends. However, these sensors can have limitations, biases, and inaccuracies that must first be controlled to generate data of adequate quality, and analyzing sensor data often requires extensive data analysis. To address these issues, an R-Shiny application has been developed to assist air quality professionals in (1) understanding air sensor data quality through comparison with nearby ambient air reference monitors, (2) applying basic quality assurance and quality control, and (3) understanding local air quality conditions. This tool provides agencies with the ability to more quickly analyze and utilize air sensor data for a variety of purposes while increasing the reproducibility of analyses. While more in-depth custom analysis may still be needed for some sensor types (e.g., advanced correction methods), this tool provides an easy starting place for analysis. This paper highlights two case studies using the tool to explore PM_2.5 sensor performance under the conditions of wildfire smoke impacts in the Midwestern United States and the performance of O₃ sensors for a year.

The Fernald Feed Materials Production Center (FMPC), located in Fernald, Ohio, USA, released radon (Rn) as a byproduct of the processing of uranium materials during the years from 1951 to 1989. Rn is a colorless, odorless gas that emits charged alpha radiation that interacts with cells in the lung and trachea-bronchial tree, leading to DNA damage, mutations, and tumor initiation. The purpose of this project was to use evidence collected by the Fernald Dosimetry Reconstruction Project and other sources to estimate the outdoor Rn exposure to individuals in the community immediately surrounding the FMPC during the years of plant operation. Using previously tabulated source terms, diffusion and meteorological data, and self-reported detailed residential histories, we estimated radon exposure for approximately 9300 persons who lived at more than 14,000 addresses. The results indicated that a portion of the population cohort experiences mean annual Rn exposure exceeding the U.S. Environmental Protection Agency (EPA) action limit of 4 pCiL^-1. These exposure estimates support the analysis of the incidence of lung cancer in the Fernald Community Cohort (FCC).

Light-duty trucks (LDTs) are often used to tow trailers. Towing increases the load on the engine, and this additional load can affect exhaust emissions. Although heavy-duty towing impacts are widely studied, data on LDT towing impacts is sparse. In this study, portable emissions measurement systems (PEMSs) were used to measure in-use emissions from three common LDTs during towing and non-towing operations. Emission rates were characterized by operating modes defined in the Environmental Protection Agency's (EPA's) MOVES (MOtor Vehicle Emissions Simulator) model. The measured emission rates were compared to the default rates used by MOVES, revealing similar overall trends. However, discrepancies between measured rates and MOVES predictions, especially at high speed and high operating modes, indicate a need for refinement in emissions modeling for LDTs under towing operations. Results highlight a general trend of increased CO2, CO, HC, and NOx when towing a trailer compared to non-towing operations across nearly all operating modes, with distinct CO and HC increases in the higher operating modes. Although emissions were observed to be notably higher in a handful of scenarios, results also indicate that three similar LDTs can have distinctly different emission profiles.