Seasonal Airmass Transport to the US Prepared by: Rudolf B. Husar and Bret Schichtel CAPITACAPITA,Washington University, Saint Louis, Missouri Submitted to: Angela Bandemehr April 30, 2000, Draft Big Bend, TX July Big Bend, TX January

Contents Introduction Transport Climatology of North America Back-Trajectory Calculations to the U.S. –Methodology –Seasonal back-trajectories to 15 receptors Transcontinental Transport Events: Dust and Smoke Summary

Introduction Anthropogenic and natural pollutants generated in one country are regularly transported to other countries adding to their air quality burden. On the average, transboundary pollutants transport to the US is small but under favorable emission and transport conditions it may cause elevated pollutant levels. Goal of Work: Illustrate the transboundary airmass transport to the United States The approach is to use backward airmass histories to 15 receptor points in the US, located mostly at the boundaries. The transport analysis was conducted over the entire calendar year 1999, aggregated monthly to illustrate the seasonal pattern of transport to each location This work is a spatial and temporal extension of the previous airmass history analysis for Spring 1998.previous airmass history analysis

Transport Climatology of North America To be completed

Features of Air Flow over North America

Seasonal Air Flow over North America NAVAIR, 1966 January OctoberJuly April

Back-Trajectory Calculations to the U.S.

Methodology – Airmass Histories An airmass history is an estimate of the 3-D transport pathway (trajectory) of an airmass prior to arriving at a specific receptor location and arrival time. Meteorological state variables, e.g. temperature and humidity, are saved along the airmass trajectory. Multiple particles are used to simulate each airmass. Horizontal and vertical mixing is included; particles arriving at the same time to follow different trajectories. Back trajectories incorporate the transport direction, speed over source regions and dilution The history of an airmass arriving at Big Bend on 8/23/99

FNL Meteorological Data Archive The FNL data is a product of the Global Data Assimilation System (GDAS), which uses the Global spectral Medium Range Forecast model (MRF) to assimilate multiple sources of measured data and forecast meteorology. 129 x 129 Polar Stereographic Grid with ~ 190 km resolution. 12 vertical layers on constant pressure surfaces from 1000 to 50 mbar 6 hour time increment Upper Air Data: 3-D winds, Temp, RH Surface Data includes: pressure, 10 meter winds, 2 meter Temp & RH, Momentum and heat flux Data is available from 1/97 to present.

Methodology: Airmass History Analysis For details see: Springtime Airmass Transport Pathways to the USSpringtime Airmass Transport Pathways to the US Backtrajectories are aggregated by counting the hours each ‘particle’ resided in a grid cell. Airmass history (Backtrajectory) Analysis

Methodology –Residence Time Probability Field The probable airmass pathway to the Seattle receptor The grid level residence times hours are divided by the total time the airmasses reside over the entire domain and the area of the grid cell. The resulting probability density function identifies the probability of an airmass traversing a given area prior to impacting the receptor. The residence time probability fields are displayed as isopleth plots where the boundary of each shaded region is along a line of constant probability. The red shaded areas have the highest probability of airmass traversal and the light blue areas have the smallest probability. The most probable pathways of airmass transport to the receptor are along the “ridges” of the isopleth plot.

Residence Time Analysis: A 2 Dimensional Approach Seattle, WA Particle Height Distribution The residence time analysis does not account for the height of the airmass, nor does it account for removal processes. Airmass above the mixing height cannot accumulate surface level emissions Back trajectories tend to increase in height with increasing age

Airmass History Database 15 receptor sites were placed primarily along the United States border Ten day airmass histories were calculated every two hours during all of particles were used to simulated each airmass trajectory Temperature, Relative Humidity, and Precipitation rate, were also saved out along each trajectory. Airmass histories were calculated using the CAPITA Monte Carlo Model driven by the FNL global meteorological data.CAPITA Monte Carlo Model FNL global meteorological data This system was previously validated for hemispheric transport by simulating the April 1998 Chinese Dust Event. April 1998 Chinese Dust Event

1. Aleutian Islands, AK July April October January Description to be completed

2. Point Barrow, AK July April October January Description to be completed

Receptor 3: S. Oregon, OR

Receptor 4: Newport, OR The air masses arriving to Oregon originate from the East throughout the year In July, the prevailing transport direction narrow, from the northeast During the other seasons, the transport direction is variable between NW and SW View monthly animation for Newport, ORNewport, OR

5. Seattle, WA July April October January Description to be completed

Receptor 6: N. California, CA

Receptor 7: San Francisco, CA

Receptor 8: Santa Barbara, CA

9. San Diego, CA July April October January Description to be completed

10. Big Bend, TX July April October January Description to be completed

11. N. Minnesota, MN July April October January Description to be completed

12. St. Louis, MO July April October January Description to be completed

13: Everglades, FL July April October January Description to be completed

14: Rochester, NY July April October January Description to be completed

15: Burlington, VT July April October January Description to be completed

Transcontinental Transport Events: Dust

The Asian Dust Event of April 1998 On April 19, 1998 a major dust storm occurred over the Gobi Desert The dust cloud was seen through SeaWiFS, TOMS, GMS, AVHRR satellites The dust transport was followed on-line by an an ad-hoc international group China Mongolia Korea

Trans-Pacific Dust Transport The dust cloud traversed the Pacific in 6 days at about 4 km altitude As the dust approached N. America, it subsided to the ground

Asian Dust Cloud over N. America On April 27, the dust cloud rolled into North America. The regional average PM10 increased to 65  g/m 3 In Washington State, PM10 exceeded 100  g/m 3 Reg. Avg. PM  g/m 3 Hourly PM10

Smoke from Central American Fires May 14, 98

SeaWiFS, TOMS, Bext May 15, 1998 May 15, 98 DMSP – Night Light Smoke from Central American Fires

Smoke Aerosol and Ozone – Inverse Relationship Surface ozone is generally depressed under the smoke cloud Extinction Coefficient (visibility) Surface Ozone

Summary of Global Air Pollution and Transport The global sulfur emissions have shifted from N. America and Europe to East Asia. The industrial ‘belt’, deg N, is dominated by anthropogenic SO x, NO x and O 3. This conforms to the conventional wisdom since the 1970s. Recent satellite data show that NO x, HC and aerosols are dominated by biomass burning in the subtropics and the southern hemisphere. ?? The radiatively active global aerosol is dominated by smoke and dust, rather then by industrial sulfates as we have presumed. Episodic trans-continental transport of dust and smoke (ozone?) can now be detected and modeled routinely. Such extra-jurisdictional ‘pollution’ events cause significant episodic impact on the air quality of N. America.

Source Impact of Pollution and Dust/Smoke Events Example Concentration/Dosage Calculation The impact of the emission from source i, E i, on the concentration at receptor j, C j, is determined by the transmission probability, T ij : C j = T ij E i The dosage is the integral of the concentration over the time length, L i, D j = L i C j Pollution Emission Rate:E i = 1 Transmission:T ij = 1 Emission Length:L i = 1 C j = 1 x 1 = 1 D j = 1 x 1 x 1 = 1 Dust or Smoke Event: Emission Rate:E i = 100 Transmission:T ij = 1 Emission Length:L i = 0.01 C j = 100 x 1 = 100 D j = 100 x 1 x 0.01 = 1 Two key measures of source impacts are on the concentration and dosage at the receptor Both depend on the source strength as well as the atmospheric transmission probability Pollution emission rates are relative low (say E=1) compared to dust/smoke events (E = 100) but they are continuous (L= 1) while the dust/smoke events are intermittent (L=0.01) Dust/smoke events produce high short-term concentration peaks at the receptor that are easily to detectable. Long-range pollution impacts are difficult to detect because the receptor concentrations are low. However, the long-term dosage form the two types of sources may be similar.

Summary (tentative) At boundaries of the US the air is transported from different directions However, each receptor location has a climatologically well defined seasonal pattern Transport to the West Coast occurs primarily from the Pacific throughout the year Transport to the Southeastern US is form the north in the cold season and from the southeast during the warm season The Northeast is receives air from the Arctic, Pacific and the Tropics The above transport pattern are consistent with the know climatological regimes of N America (…..)

Hemispheric option – full context? Half-hemispheric option-better proportions? What do you think? Note: there is a bit of a gap at the dateline- problem with the splicing. Also, the fine features of the transport pattern an not too meaningful - applicable only to vertically integrated, not surface transport

Polar Stereographic Projection Joe, this projection always confuses me… It is a nice projection for meteorologists but for policy types? R