Abstract
Concerns over regional climate change include its impact on air quality. A major contributor to unhealthy air quality is surface-based temperature inversions. Poor air quality is a serious public health concern that is often addressed by public health agencies. To assist with understanding the climatology and trend of temperature inversions for a large public health department, innovative pragmatic criteria were developed and used to determine morning and evening surface-based temperature inversions from datasets derived from Pittsburgh National Weather Service (NWS) radiosonde measurements made from 1 January 1991 through 31 December 2020. During this 30-year period, the strength of the morning (7 a.m. EST; 12 UTC) inversions was 3.9 °C on average. The depth of the inversion layer measured an average height of 246 m above the ground. The inversions tended to dissipate by 10 a.m. EST. The frequency of occurrence of morning inversions averaged 47%. The mean strength of the evening (7 p.m. EST; 00 UTC) inversions was 1.1 °C with a mean depth of 101 m above the ground. The frequency of evening inversion occurrence averaged 20% during this period. The 30-year climatology revealed generally declining frequency of inversions in the Pittsburgh area. Morning surface-based inversion strengths usually declined while morning depths and break times were steady. Evening inversion strengths and depths increased overall during the 30-year period. Monthly means showed a morning-evening overlap of some months that record the most frequent substantial inversions during the fall time of the year, coinciding with the time when the worst air pollution events occur.
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Data availability
Data used to produce tables and figures herein were obtained from spreadsheets contained in supplemental material. Data populating the spreadsheets were evaluated from University of Wyoming [http://weather.uwyo.edu/upperair/sounding.html] and Plymouth State University [https://vortex.plymouth.edu/mapwall/upperair/raob_conus.html] on-line upper-air records.
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Acknowledgements
This work was performed while the author was employed by the Allegheny County Health Department, Air Quality Program (ACHD AQP) in Pittsburgh, Pennsylvania. Special recognition goes to Caitlin K. Grosse, former Air Quality Analyst for the ACHD AQP. Ms. Grosse conducted a major portion of the data evaluation, tabulation, and analysis. Many others have contributed to this research over recent years especially William Maguire, Air Quality Analyst and Aja Ellis, Air Pollution Administrator for the ACHD AQP and Megan Fedkoe, summer student contractor for ACHD AQP. In addition, I am grateful for suggestions regarding data interpretation by Matthew Kramar of the Pittsburgh National Weather Service Forecast Office, Dr. Richard Clark of Millersville University, and Dr. Larry Oolman of the University of Wyoming.
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The author declares that no extra funds, grants, or other financial support were received during the preparation of this manuscript under normal employment conditions while the author was employed by the Allegheny County Health Department, Air Quality Program, Pittsburgh, Pennsylvania.
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Author prepared the study conception and design and wrote all drafts of the manuscript. Material preparation, data collection, and analysis were performed by Allegheny County Health Department staff and contractors identified in the “Acknowledgements” section.
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Appendices
Appendix
Appendix A. “Rules” to calculate substantial surface inversions
For this research, a surface-based inversion was defined as a minimum temperature increase of 1 °C over a depth of at least 15 m from the surface, with the base of the inverted layer beginning less than 130 m AGL. The application of this definition to determine inversion statistics from PIT data was achieved through the following instructions used to train ACHD AQP staff to calculate surface-based temperature inversions from UWYO or Plymouth datasets.
12Z (7a.m. EST) observation
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1.
Surface inversion is at least 1.0 °C for at least 15 m AGL.
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2.
Surface inversion begins below 130 m AGL.
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3.
Acceptable conditions: isothermal layer(s) or decrease of temperature(s) for less than 1.0 °C below or within surface inversion, as long as the isothermal or decrease layer(s) are no deeper than 129 m and no inversion of at least 5 °C begins above isothermal/decrease layer(s). For inversions of at least 5 °C, a case-by-case evaluation is necessary. *Isothermal conditions above the final ground inversion height are not included in the depth calculation.
00Z (7p.m. EST) observation
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1.
Surface inversion is at least 0.4 °C for at least 15 m AGL.
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Surface inversion begins below 130 m AGL.
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3.
Acceptable conditions: isothermal layer(s) or decrease of temperature(s) for less than 1.0 °C below or within surface inversion, as long as the isothermal or decrease layer(s) are no deeper than 129 m and no inversion of at least 5 °C begins above isothermal/decrease layer(s). For inversions of at least 5 °C, a case-by-case evaluation is necessary. *Isothermal conditions above the final ground inversion height are not included in the depth calculation.
*Note that the special case-by-case condition was applied only once in the 30-year data. The application was made for December 6, 2015, at 12Z when the temperature decreased for 1.6 °C for 64 m from the surface before there was an inversion of 11.7 °C for 482 m, as measured from the surface.
Appendix B. “Rules” to calculate estimated break times
For this research, the following instructions were used to train ACHD AQP staff to calculate surface-based temperature inversion break times.
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First, an estimated break temperature needs to be determined. To calculate and record “Est. Break Temp. (°C)” as indicated on the daily record form (see Figure 6):
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Use 1 °C/100 m for an approximate dry adiabatic lapse rate. Multiply 1 °C/100 m by the height (or “Top”) of the inversion.
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Add the product calculated in step (a) to the temperature at the top of the surface inversion layer (“Temp. at Top (°C)”) as indicated by the 12Z sounding to obtain the “Est. Break Temp.” in °C.
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Go to: https://www.ncdc.noaa.gov/cdo-web/datatools/lcd. Select “Pennsylvania,” then select “PITTSBURGH ASOS, PA US.”
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Select Year and Month, then pick hourly (“Hourly (10A)”) data for days being evaluated.
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Go to page 2 of the Pittsburgh ASOS data record. From column 8, which is labeled “Dry Bulb Temp (°C),” find the temperature that matches the estimated break temperature given in the column labeled “Est. Break Temp. (°C)” on the daily record form. Interpolation may be necessary. Record the time to the nearest half hour under “Est. Break Time (h).” NOTE: If a frontal passage or gustiness occurs—determined from a synoptic map (see https://www.wpc.ncep.noaa.gov/dailywxmap/) or an observation of wind gusts (column 16, “Wind Gusts”) or a significant amount of precipitation (at least 0.02″) (as indicated in columns 6, “Weather Type,” and 22, “Precip Total”), for example, use the time of the frontal passage/gusts/substantial precipitation as the “Est. Break Time.”
Fig. 6
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Sadar, A.J. Climatology and trends of morning and evening surface-based temperature inversions in southwestern Pennsylvania with air quality implications. Environ Sci Pollut Res 29, 49411–49421 (2022). https://doi.org/10.1007/s11356-022-20504-7
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DOI: https://doi.org/10.1007/s11356-022-20504-7