Health Assessment and Air Pollution Ilias G. Kavouras, Ph.D. Department of Environmental and Occupational Health University of Arkansas for Medical Sciences College of Public Health

Study tasks evaluate the relative contribution of local and regional sources on PM 10, PM 2.5 and O 3 concentrations the concentration trends and spatiotemporal variations of O 3 in relation to wildfires produce a regional health profile for air quality related chronic and infectious diseases obtain baseline information on the state of health and risks factors of the region through acquisition and analysis of available indicators: Mortality and hospital admissions for COPD, asthma, heart failure, stroke and infectious diseases (Flu, pneumonia, pertussis and Coccidioidomycosis) estimate the relative risks for respiratory and cardiovascular diseases in Dona Ana county Obtain and analyze emergency rooms visits and hospital admissions and air pollution (PM 10, PM 2.5 and O 3 )

Air mass residence time Shipping emissions (SO 4, NO 3 ) O 3 and precursors Local sources Shipping emissions (SO 4, NO 3 ) O 3 and precursors

Tracer Mass Balance model CiCi = measured concentration of the i species at the receptor site Q ij = emission rate of the i species from the j source region T ij = transformation and deposition factor of the i species from the j source region to account for deposition, diffusion, and chemical conversion NjNj = number of back trajectory endpoints in the j source region E ij = entrainment factor of the i species from the j source region to account for disassociation between the back trajectories and the transport of pollutants Assumption: measured concentrations at a receptor are linearly related to the frequency of airmass transport from a source region to the receptor site Development of the model: Pitchford and Pitchford, 1985; Gebhart et al Application of the model: Gebhart et al. 2001; 2006; Xu et al. 2006; Huang et al. 2010; Kavouras et al. 2013; Chalbot et al = dust concentration (μg/m 3 ) at the receptor site on j day = contribution of region i on j day = residence time for all air parcels arriving at the receptor site over source region i on j day = regression coefficient of source region i = intercept ε ij = residual of region i on j day

Source regions contributions 19 regions, four adjacent to Las Cruces (500 km) The four adjacent sectors are important contributors to PM 10, PM 2.5 and O 3 Southern California, Arizona, Baja California and southeast Texas are also important determinants Northwest US contributes up to 8 ppbv of O 3

O 3 monitoring locations

Approach The relative (%ΔC/Ref) differences and the coefficient of divergence (COD)of 8-hr maximum monthly concentrations between two sites (Chiricahua National Monument was the reference site). COD values vary from 0 to 1, with COD values close to unity being suggestive of strong spatial variation. Total counts of fire detections/month Frequency: >25%, 25-50%, 50-75%, >75% Distance from the site: 0-160, , , , , km Ordinary least squares regression of deseasonalized monthly 8-hr maximum O 3 concentrations (“Census I” method)

Site codeAnnual trend (ppbv/yr) hr max%ΔC/Ref; Median (σ)COD ch 0.12 b 74 nm (13)0.10 nm a 65-2 (16)0.10 nm (11)0.06 nm a 70 1 (13)0.06 nm a (8)0.07 nm a (11)0.13 nm a (7)0.06 nm a (10)0.11 ep (25)0.21 ep a (16)0.08 ep (21)0.14 ep (21)0.11 ep (17)0.10 ep b (16)0.07 cj a 79 7 (32)0.21 cj a (25)0.16 cj a (24)0.11 a significant at p < 0.001; b significant at p<0.01 Annual and spatial trends

Fires, distance and O 3 Increasing trend is due to the decomposition of peroxyacetylnitrates (PAN) Decrease of O 3 for fires within 400 km may be due to NO titration of O 3 Increase in extreme fire events within 400 km may be due to changes of NO 2 and O 3 photolysis rates in the smoke plume

Fires, distance and O 3 a Significant estimates (at p-value < 0.15) Site code Buffer contribution (ppbv) a >160 km km km km km km ch nm nm nm nm nm nm nm nm nm nm ep ep ep ep ep ep ep ep cj

Fires, distance and O 3

Fires and asthma/COPD hospitalizations β is related to an increase of 4.25% (asthma,all ages), 1.85% (asthma, children), 2.46 (asthma years) and 3.29% (COPD, all ages) for an increase of 10 ppbv of 8-hr maximum O 3 concentration (Ji et al., 2011), p is the county population and b is the county baseline hospitalizations rates Mean contribution ΔO 3 =5.2 ppbv Maximum contribution ΔO 3 =8 ppbv Asthma (All Ages) Asthma (Children) Asthma (15-64 ages) COPD (All ages)

Regional Health Profile State of New Mexico's, Department of Health, Indicator Based Information System for Public Health (NEW MEXICO-IBIS) Mortality Data State of New Mexico's, Department of Health, Indicator Based Information System for Public Health (NEW MEXICO-IBIS) Hospital Impatient Discharge Data (HIDD). State of New Mexico's, Department of Health, Indicator Based Information System for Public Health (NEW MEXICO-IBIS) Behavioral Risk Factor Surveillance System (BRFSS) State of New Mexico's, Department of Health, Indicator Based Information System for Public Health (NEW MEXICO-IBIS) Youth Risk and Resiliency Survey New Mexico EnviroNew Mexicoent Department, Air Quality Bureau US Census Bureau US Department of Health and Human Services, Health Resources and Services Administration US Department of Labor, Bureau of Labor Statistics US Environmental Protection Agency Air Quality System

Total mortality number of people who died in 2010 in relation to the population size (per 100,000) New Mexico: 742 USA: 798

MaleFemale White Hispanic Af.Amer Native Amer Asian/PIs a Total mortality per race and age Males higher than females Race patterns

Leading causes of death

Heart failure mortality MaleFemale White Hispanic Af.Amer a 7.5 a Native Amer. 4.4 a 6.7 a Asian/PIs 30.4 a

Heart failure hospital admissions primary diagnosis is the condition to be responsible for the admission of the patient to the hospital. secondary diagnosis includes the condition that coexist at the time of inpatient admission which affect the treatment received and/or length of stay Data from federal facilities (military and veteran’s affairs hospitals) and Indian health service facilities are not included

COPD mortality MaleFemale White Hispanic Af.Amer a 20.8 a Native Amer a 6.7 a Asian/PIs 9a9a

COPD hospital admissions

Asthma mortality MaleFemale White Hispanic a

Asthma hospital admissions Middle- and high- school students

Stroke mortality MaleFemale White Hispanic Af.Amer a 32 a Native Amer. 4.4 a 13.4 a Asian/PIs 30.4 a

Stroke hospital admissions

Flu and pneumonia

Pertussis and Coccidioidomycosis Mortality Pertussis: six deaths are reported in New Mexico; one death in Hidalgo County Coccidioidomycosis: ten deaths were reported in New Mexico, none of them within the border Counties in period Hospitalizations Pertussis: 254 are reported in New Mexico; 16 in in study area (15 in Dona Ana, eight in Otero County, four in Grant County, two in Luna County and one in Sierra County) 26 children, 24 of them > 1 years old (17 boys and 7 girls) Coccidioidomycosis: 131 are reported in New Mexico; 13 in in study area (33 in Dona Ana, four in Otero County, four in Grant County, seven in Luna County and three in Sierra County) years ols (56% males and 44% females) in period

O3O3 PM 2.5 PM 10 4 th highest 8-hr moving average <75 ppbv Annual average < 15 μg/m 3 2 nd highest 24-hr concentration < 150 μg/m 3 Las Cruces 6.3 Solano 65 Holman Road Did Not Meet; (Exceeded in 2005) West Mesa Did Not Meet; (Exceeded in 2004, 2008) Paso del Norte Anthony Did Not Meet; (Exceeded in 2003, 2006) Chaparral 69 (below since 1991) Did Not Meet; (Exceeded in 2005) Desert View76 (above since 1996) Did Not Meet; (Exceeded in 2008) La Union70 (below since 2004) Santa Teresa72 (below since 2004) Sunland Park 69 (below since 2004)10.5Met Design Value; (Exceeded in 2003) Southwestern New Mexico Deming Airp. 58 Did not meet; (Exceeded in 2003, 2008) Hurley 64 Silver City 5.4 Air pollution indicators

Health Status Behavioral Risk Factor Surveillance System (BRFSS) Youth Risk and Resiliency Survey

Blood pressure and cholesterol

Smoking Middle- and high- school students

Health facilities and access Dona Ana County Memorial Medical Center in Las Cruces with 293 beds MountainView Regional Medical Center in Las Cruces with 142 beds Advanced Care Hospital of Southern New Mexico in Las Cruces with 20 beds Rehabilitation Hospital of Southern New Mexico in Las Cruces with 40 beds Mesilla Valley, a psychiatric facility, in Las Cruces with 120 beds. Otero County General Champion Memorial Hospital In Alamogordo with 90 beds Mescalero Indian Hospital in Mescalero with 13 beds Sierra County Sierra Vista Hospital in Truth or Consequences with 23 beds Grant County Gila Regional Medical Center in Silver City, with 68 beds Luna County Mimbres Memorial Hospital in Deming with 115 beds

Epidemiological analysis Daily emergency room (ER) visits and hospital admissions from the Memorial Medical Center (MMC), 2007 to 2011 for the adult population (≥ 18 years of age) were retrieved. 67.5% of hospital beds (293) and 65% (35,939) of emergency room visits in Dona Ana County PM 10, PM 2.5 and O­ 3 measurements from the U.S. Environmental Protection Agency (EPA) Air Quality System (AQS) based on the completeness of the datasets. 24-hr PM 10 and PM 2.5 mass concentrations and the daily 8-hr maximum O 3 concentration were used as metrics of ambient exposures E[Y t ] is the expected value Y t indicating the daily visits or admissions count on day t with Var(Y t )=φE[Y t ] with φ being the over-dispersion parameter, temp t is the value of mean temperature on day t, lag16(temp t ) is its lagged effect over the previous six days and (Pollutant) t is the pollutant’s level on day t. on the previous day (lag1), on the average of the same and previous days (lags01) S are the natural splines smoothing functions to capture the non-linear relationship between the time-varying covariates and calendar time and daily admissions, with three df for temperature on the day of the admission and with two df for the previous days controlled for season and long-term trend with a natural cubic regression spline with 1.5 degrees of freedom (df) for each season and year (corresponding to six df per year). two- pollutant models using the previous day pollutants concentrations

Mean (min-max)Median (25 th -75 th percentile)Total Emergency room visits Respiratory visits All ages3.24 (0-13)3 (2-4) years2.83 (0-12)3 (1-4) years0.41 (0-4)0 (0-1)599 COPD all ages0.32 (0-3)0 (0-1)471 Cardiovascular visits All ages1.39 (0-7)1 (0-2) years0.75 (0-5)1 (0-1) years0.64 (0-4)0 (0-1)941 Stroke all ages0.04 (0-2)0 (0-0)63 Hospital admission Respiratory admissions All ages1.63 (0-9)1 (1-2) years0.68 (0-4)0 (0-1) years0.95 (0-7)1 (0-2)1382 COPD all ages0.44 (0-4)0 (0-1)640 Cardiovascular admissions All ages3.53 (0-12)3 (2-5) years1.40 (0-8)1 (0-2) years2.13 (0-9)2 (1-3)3115 Stroke all ages0.32 (0-4)0 (0-1)468 ER and hospital admissions

Percent increase in ER visits 10 μg/m 3 of PM 10, PM 2.5 and 10 ppbv of O­ 3

Percent increase in hospital admissions 10 μg/m 3 of PM 10, PM 2.5 and 10 ppbv of O­ 3

Seasonal effect MorbidityOutceomPollutant Percent Increase (95% CI) Lag1 Annual Effects: Percent Increase ColdHot Emergencies CVD PM (-6.37, 11.90)12.42 (-3.46, 30.92) 4.53 (-4.25, 14.11) PM (-2.65, 3.35) 3.10 (-0.51, 6.85) (·) 2.35 (-1.97, 6.87) PM (-2.03, 3.32) 2.80 (-0.24, 5.92) (·) 3.61 (-0.37, 7.75) (·) O3O (-9.03, 15.73)6.03 (-3.74, 16.80) Respiratory † PM (-4.30, 7.59)0.59 (-10.43, 12.97) 5.23 (-0.52, 11.32) (·) PM (-2.77, 1.40)-0.21 (-3.51, 3.21) 2.21 (-0.62, 5.12) PM (-2.28, 1.54)-0.03 (-2.78, 2.80) 3.24 (0.53, 6.02) (*) O3O (-12.75, 2.62)3.28 (-3.85, 10.94) Admissions CVD PM (-7.05, 4.81)-1.28 (-10.23, 8.57) (-8.17, 2.81) PM (-1.61, 2.62)-0.24 (-2.77, 2.34) (-3.40, 2.09) PM (-1.25, 2.65)-0.56 (-2.66, 1.58) (-2.62, 2.47) O3O (-8.38, 7.41)0.72 (-4.89, 6.65) Respiratory † PM (-3.01, 11.78)-5.93 (-19.67, 10.14) 0.79 (-6.39, 8.52) PM (-1.04, 3.21)-0.99 (-5.15, 3.36) 1.42 (-2.19, 5.16) PM (-0.58, 3.28)-0.93 (-4.30, 2.57) 0.85 (-2.59, 4.40) O3O (-3.72, 17.87)0.92 (-8.56, 11.38) † Without influenza control, (*) Significant at 5%, (·) Significant at 10%

Conclusions Sources within 500 km, southern California, Baja California, southern Arizona, southeast Texas and north Mexico are responsible for most of PM 10, PM 2.5 and O 3 Wildfires within km and more than 1600 km may contribute up to 11 ppbv of O 3 and trigger an increase of up to 3.3% in asthma hospitalizations More than 70% of residents in the border Counties reported at least one behavioral risk factor (smoking, high blood pressure or cholesterol) for chronic diseases. The levels of particulate matter are among the highest in the Nation, and exceed the threshold concentrations set by US EPA for the protection of human health; For ozone, threshold concentrations were exceeded in the past; current levels are slightly below the threshold value Cancer and heart diseases are the primary causes of death for adults; chronic respiratory diseases are among the top six causes of death in the border Counties. Mortality and hospitalization due to COPD and asthma are above the State’s average and they are increasing Childhood asthma is a concern, with about 50% of high school students being active smokers. One-third of hospitalized cases of coccidioidomycosis in New Mexico since 1999 were observed in border Counties; however, none of them died Positive but not significant associations were observed for asthma, COPD and heart disease An increase of 3-5% (statistically significant) was computed for emergency cardiovascular and respiratory symptoms for a 10 μg/m 3 increase in PM mass in the summer.

Acknowledgements Paul Dulin, NM DOH Dave DuBois, Erin Ward and all study partners Bruce D. San Filippo and MMC staff Marie-Cecile Chalbot, Sophia Rodopoulou and Evi Samoli