Reductions in Respiratory Hospital Visits after a Coal Coking Plant Closure: A Natural Experiment 10.1164/rccm.202410-2005OC Abstract Rationale Abrupt air quality improvements have followed the closure or dramatic emission control of large air pollution sources. These “natural experiments” provide ideal opportunities to assess the real-world health benefits of air quality improvements. The shutdown of the Shenango coking plant, a significant fossil-fuel pollution source located on an island in the Ohio River near Pittsburgh, Pennsylvania, presented such an opportunity to test for changes in respiratory health in the local community after the closure. Objectives We sought to identify and quantify the immediate and/or longer term changes in respiratory hospitalizations and emergency department (ED) visits among the population residing near the Shenango coke plant at the time of its closure. Methods We acquired data for respiratory hospitalizations and ED visit counts from residents living in zip codes surrounding the plant, as well as at comparison control sites, 3 years before and after the shutdown date. The immediate and longer term changes of respiratory health outcomes were tested with an interrupted time series model and compared with findings from external control sites and internal control outcomes. Measurements and Main Results We found that the closure of the Shenango plant was associated with an immediate 20.5% (95% confidence interval = 12.8–27.6) decrease for weekly respiratory ED visits and an immediate 41.2% (95% confidence interval = 14.4–59.9) decrease in ED visits for pediatric asthma, followed by an additional 4% per-month longer term downward trend. Longer term reductions, as compared with preclosure trends, were also observed for hospitalizations for chronic obstructive pulmonary disease. Conclusions Our study provides strong confirmation that reductions in fossil-fuel–related air pollution produce both short-term and longer term respiratory health benefits. Keywords: air pollution, interrupted time series analysis, asthma, COPD At a Glance Commentary Scientific Knowledge on the Subject Despite numerous public health studies finding statistical associations between ambient air pollution and adverse health, direct accountability tests of emissions control and subsequent human health benefits are limited. This study leverages the closure of a coal coking plant to provide a direct quantification of the resulting short- and/or longer term health changes in nearby residents’ respiratory disease hospitalizations and emergency department visits. In the past, the potential health benefits of such air pollution reductions have been estimated on the basis of concentration–response functions from epidemiologic studies of ambient pollution exposures and their health impacts. However, the composition and toxicity of particles emitted by specific sources can vary widely. What This Study Adds to the Field This work indicates that the physical and chemical characteristics of particles emitted in the coal coking process make them especially potent in eliciting inflammatory responses, compared with other types of ambient particles. Our findings add to the growing body of evidence that reducing fossil-fuel–related air pollution emissions produces especially large public health benefits, both in the short term and longer term. To mitigate and prevent the documented health risk from air pollution exposures, a broad range of air quality standards and emission regulations have been implemented over the past decades ( 1 – 3 ). The potential health benefits of these regulatory programs were estimated on the basis of concentration-response functions from preexisting epidemiologic studies of prevailing pollution exposures and their health impacts ( 4 ). To validate the actual real-world health benefits of such air quality improvements versus expected, accountability case studies such as the one considered here have emerged as useful evaluation tools ( 4 , 5 ). In this case, we evaluate the health benefits of a coal coking plant near Pittsburgh, Pennsylvania. The manufacturing of coke from coal pyrolysis is known to generate high emissions of complex air pollution mixtures into the ambient air ( 6 – 10 ). Despite past statistical associations between pollution from such industrial point source and adverse health effects ( 11 – 14 ), and the well-established general knowledge that the fossil fuel combustion–related emission sources contribute to a large health burden ( 15 , 16 ), direct tests of a cause-and-effect relationship between fossil fuel–related emissions control and health benefits are limited. Therefore, the January 2016 shutdown of the Shenango, Inc., coking plant, a significant industrial emission source on an island in the Ohio River in Pittsburgh provides an ideal “natural experiment” opportunity to perform an accountability analysis. Our prior study of this event found significant short-term immediate and longer term decreases in cardiovascular emergency department (ED) visits in neighborhoods surrounding the coke plant after its shutdown and not at control sites or in control health outcomes ( 17 ). Previous epidemiological studies have reported that occupational exposures to coke oven emissions are significantly associated with chronic obstructive pulmonary disease (COPD) ( 18 ) and lung function decline ( 19 ). Studies have also linked events of coke oven control failure to an elevated risk of asthma in nearby residents ( 20 , 21 ). Therefore, we hypothesized that the closure of the Shenango coke plant would have also been accompanied by respiratory health benefits in the community residing near the facility but not in unaffected control (reference) communities at the same time. Using a quasi-experimental design and an interrupted time series (ITS) model, this study aims to identify and quantify the immediate and/or longer term declines in respiratory disease hospitalizations and ED visits in the population living near the Shenango coke plant coinciding with its closure. Some of the results of this study have been previously reported in the form of scientific abstracts ( 22 , 23 ). Methods Study Sites and Population The overall design of the study is summarized in Figure 1 . The study period for this evaluation of health effects encompassed the 3 years before and 3 years after the plant’s shutdown date (final operation on January 6, 2016), from 2013 through 2018. Three study sites were defined for comparison ( Figure 2 ): 1 ) the exposure site (i.e., Avalon; adjacent to the Shenango, Inc., coke plant address, located to the west and northwest of Pittsburgh); 2 ) the exposed positive control site (i.e., Clairton; adjacent to the still-operating Clairton Coke Works address, upwind from and south of Pittsburgh, and unlikely to be impacted by Shenango plant pollution changes); and 3 ) the unexposed negative control site (i.e., Johnstown; an urban community also in Pennsylvania, but without any coking operations nearby, and also having a nearby federal air monitoring network station). Figure 1. Flow diagram of overall study design. Dashed boxes indicate the causal inference criteria addressed by the before versus after and/or exposure versus control comparisons. COPD = chronic obstructive pulmonary disease; ED = emergency department; PADOH = Pennsylvania Department of Health; PHC4 = Pennsylvania Health Care Cost Containment Council. Figure 2. Zip codes of the study populations. ( A ) Exposure site (near-Shenango coke plant; Avalon): 15202, 15225, 15233, 15212, and 15136. ( B ) Exposed positive control site (Near still-operating Clairton coke plant; Clairton): 15025, 15037, 15088, 15133, 15122, and 15045. ( C ) Unexposed negative control site (Urban area, no coke plant nearby; Johnstown): 15902, 15901, and 15905. Green dots indicate the Allegheny County Health Department air quality monitoring sites; blue dots indicate the U.S. Environmental Protection Agency Chemical Speciation Network air quality monitor sites. Adapted by permission from Reference 17 . For each study area, counts of visits and admissions from contiguous zip codes were selected to be consolidated and analyzed as a group for health outcome counts over time. The zip codes where the emission source coke plants and/or federal air quality monitors were located were first identified as the center zip codes for each site. Zip codes in their immediate vicinity were included in the respective study site to assess the direct health impacts of fugitive emissions and unintended air pollution release from the operations ( 24 ). Population demographic characteristics information in 2013 and 2018 were acquired from the 5-year estimates from the American Community Survey by Zip Code Tabulation Areas ( 25 ). The annual mean population at each study site was derived using linear interpolation ( 26 ). Data Acquisition The count aggregation time interval for individual hospital outcomes varied to satisfy minimum count limits (i.e., longer times for less frequent events) because of imposed agency limits on minimum counts per data cell (to protect patient privacy). Quarterly hospital inpatient visit count data were acquired from the Pennsylvania Health Care Cost Containment Council. Respiratory hospitalization cases were identified on the basis of admitting diagnosis codes (defined by diagnosis at admission; International Classification of Diseases, Ninth Edition [ICD-9] or Tenth Edition [ICD-10] codes) and principal diagnosis codes (defined by diagnosis at discharge; ICD-9 or ICD-10 codes). Data entries of inpatient hospitalizations due to respiratory symptoms and/or diagnoses of respiratory diseases (i.e., COPD and asthma, and for comparison, acute respiratory infections and lung cancer; see Table E1 in the online supplement) were retrieved for analysis consistent with previous literature and the General Equivalence Mapping Tool developed by the Centers for Medicare and Medicaid Services ( 27 – 31 ). Hospitalizations were aggregated by time interval and residential zip code to generate counts at each reported quarter of the year. ED visit count data were procured from the EpiCenter syndromic surveillance database maintained by the Pennsylvania Department of Health ( 32 ). We acquired daily ED visit counts for both respiratory and traumatic injury (for comparison), on the basis of chief complaints and discharge diagnoses for populations residing near the plant exposure site zip codes and weekly counts at less populous control site residential zip codes ( 33 ). Pennsylvania Department of Health data privacy release restrictions require that small count values (1 ⩽  N  < 5) need to be redacted, so monthly visit counts for pediatric asthma (in patients from birth to 17 yr old) were aggregated at study site areas to minimize missing data. We filled missing (i.e., 1 <  N  < 5) data cells with N  = 2.5 in the main analysis but also performed sensitivity analyses using only complete cases or using an imputed stochastic replacement process for missing values for comparison ( 34 ). For compatibility, only those healthcare facilities that were enrolled in the EpiCenter reporting system beginning before 2013 were included in the main analysis, but the data including all reporting facilities were also evaluated in sensitivity analysis. Statistical Approach We assessed the health data for potential changes in trends before versus after the closure of the coking plant using a segmented regression analysis of ITS at each site ( 35 ). In the equation, Y t = β 0 + β 1 T + β 2 X t + β 3 P X t + f t , Y t is the health outcome (i.e., the crude number of cases or case rate) at time t , T is the time elapsed since beginning of the study period, P is the time elapsed since the shutdown date, and X t denotes the operation vs. closure of the Shenango coke plant. A quasi-Poisson generalized linear model with a log-link function was applied to account for data skewness and overdispersion ( 35 , 36 ). Term f t , controlling for seasonality, used quarters for hospitalizations (only four quarters per year) and cubic b-splines (7 degrees of freedom [DF] per calendar year) for ED visits ( 37 ). Residual autocorrelations were evaluated with the Breusch-Godfrey test and addressed using the Newey–West SE estimator ( 38 , 39 ). The modeled immediate effect (i.e., β 2 , intercept at the time of event, the day or week after January 6th, 2016, for daily or weekly ED visits, respectively, or January or Quarter 1 of 2016 for monthly or quarterly visits, respectively) and the before-versus-after trend changes at the exposure site were compared with those at the control sites. The respiratory ED visit rate changes at the exposure site were further explored by stratified analysis in the population subgroup over 65 years of age and were compared with the ED visit rate of traumatic injury in the same population (i.e., traumatic injuries served as an internal control outcome, not expected to be affected by air pollution) ( 33 , 40 ). Models were further tested in sensitivity analyses by adjusting for weekends and federal holidays for daily visits, using natural and cyclic cubic splines with different degrees of freedom per year to adjust for seasonality, using complete case analysis and multiple imputation for missing data and using the ED visit data from all facilities enrolled in the EpiCenter reporting system. Additionally, because visual inspection found that the injury ED visit rates in the same age group met the preintervention parallel trend assumption, they were included in the model as an offset to perform a controlled ITS of pediatric ED visits at the exposure site ( 38 ). The incidence rate ratios (IRRs) were computed on the basis of model results, and the relative changes were calculated as (IRR − 1) · 100% ( 41 ). Statistical analyses were performed using R Statistical Software, Version 4.2.2 ( 42 ). Results Study Population Characteristics The sociodemographic characteristics of the exposed and control study populations of Allegheny County (where the Shenango coke plant was located) and of Pennsylvania State remained relatively stable over the study period (2013–2018) ( see Table E2). There was a 3.9% decrease in population below the poverty level residing in the area surrounding the Shenango coke plant in 2018, compared with that in 2013. At the Johnstown (unexposed control) site, there was an overall 8.8% decline in population residing in the neighborhood. All three sites saw a small (1–3%) decrease in population under 18 years of age and a small (1–3%) increase in population over 65 years of age. Models were adjusted to statistically account for these population shifts. Table 1 shows the frequency of inpatient hospitalizations and ED visits, percentages of imputed monthly pediatric asthma ED data, and daily mean levels of particulate matter with an aerodynamic diameter ⩽2.5 μm (PM 2.5 ) and sulfur dioxide (SO 2 ) by study site and period. Because a missingness suggested a lower count number redacted from the data release (i.e., 1 <  N  < 5), significantly different percentages of redacted data before versus after the closure were interpreted as indicating a change in monthly incidence (e.g., above 5 vs. 1–5, or vice versa). Pediatric asthma counts were fully available before the shutdown, but redacted counts (i.e., one to five visits per month) rose to 48.6% of the months after the shutdown at the exposure site, itself indicating an obvious reduction of pediatric asthma incidence in the years after the Shenango plant closed. No respiratory ED data were redacted. The daily SO 2 level significantly and abruptly dropped at the exposure site after the plant shutdown, whereas the change in total PM 2.5 mass concentration was relatively small ( see Figures E1 and E2). Table 1. Frequency of Inpatient Hospitalizations, ED Visits, and Air Pollution Levels at the Study Sites Variable Exposure Exposed Control Unexposed Control   2013–2015 2016–2018 2013–2015 2016–2018 2013–2015 2016–2018 Quarterly inpatient hospitalizations by study site and period  Admitting diagnosis at admission, mean ± SE   Respiratory symptoms 422.7 ± 13.7 341.3 ± 17.7 338.7 ± 14.6 324.5 ± 14.3 235.6 ± 8.8 209.6 ± 7.2  Principal diagnosis at discharge, mean ± SE   Total respiratory diseases 273.3 ± 12.8 242.2 ± 15.5 228.3 ± 12.7 218.3 ± 12.4 136.8 ± 6.7 114.3 ± 7.3   COPD and allied conditions 62.6 ± 3.5 59.0 ± 4.7 61.8 ± 3.9 73.2 ± 5.2 38.0 ± 2.0 36.5 ± 2.7   Asthma 31.5 ± 2.1 13.7 ± 1.3 31.9 ± 2.7 12.8 ± 1.3 10.9 ± 1.4 5.3 ± 0.7   Acute respiratory infections 14.0 ± 1.9 11.8 ± 1.7 12.4 ± 2.0 14.6 ± 1.8 7.8 ± 1.7 5.3 ± 1.1   Lung cancer 14.8 ± 0.8 14.1 ± 1.4 14.3 ± 1.0 10.1 ± 0.9 5.3 ± 0.7 6.1 ± 0.8   Total inpatient hospitalizations 3,064.1 ± 22.6 2,805.3 ± 37.7 2,315.8 ± 26.3 2,209.0 ± 22.0 1,624.1 ± 23.1 1,464.3 ± 15.5   Exposure Exposed Control Unexposed Control   Before January 6, 2016 After January 6, 2016 Before January 6, 2016 After January 6, 2016 Before January 6, 2016 After January 6, 2016 ED visits by study site and period  Respiratory, mean ± SE   Daily visits 21.4 ± 0.2 22.2 ± 0.2 — — — —   Weekly visits — — 58.5 ± 1.4 102.6 ± 2.8 71.1 ± 0.3 10.2 ± 0.3  Pediatric asthma, mean ± SE   Monthly visits 13.1 ± 0.9 5.3 ± 0.5 3.2 ± 0.3 3.7 ± 0.4 3.9 ± 0.4 5.9 ± 0.5    % Imputed 0 48.6 62.2 65.7 64.9 34.3   Exposure Exposed Control Unexposed Control   2015 2016 2015 2016 2015 2016 Daily PM 2.5 and SO 2 levels by study site and period, mean ± SE * PM 2.5 , μg/m 3 11.35 ± 0.32 10.13 ± 0.25 13.02 ± 0.47 11.38 ± 0.38 11.77 ± 0.30 9.22 ± 0.28 SO 2 , ppb 1.51 ± 0.10 0.35 ± 0.04 4.59 ± 0.30 3.80 ± 0.24 1.80 ± 0.11 0.88 ± 0.08 Definition of abbreviations : COPD = chronic obstructive pulmonary disease; ED = emergency department; PM 2.5  = particulate matter with an aerodynamic diameter ⩽2.5 μm; SO 2  = sulfur dioxide. * Air quality measurements at the Exposure and Exposed Control sites obtained from the Allegheny County Health Department Air Monitoring Network; measurements at the Unexposed Control site obtained from the EPA Chemical Speciation Network. Hospitalizations for Total Respiratory Symptoms Although the overall total respiratory hospitalization rate did not significantly change at the time of, or after, the closure of the Shenango coke plant at any study site, hospitalizations with respiratory symptom–related admission codes did decrease by 16% among the near-Shenango exposure populations during the first quarter of 2016, as compared with the preclosure trend (IRR = 0.84; 95% confidence interval [CI] = 0.76–0.94) ( Figure 3 and Table 2 ), indicating significant immediate respiratory health improvements. The immediate decrease was only observed at the near-Shenango exposure site, not at the control sites. Figure 3. Trends of annual hospitalizations at study sites, 2013–2018, for ( A ) COPD and allied conditions, ( B ) asthma, and ( C ) respiratory symptoms, at the exposure (Avalon/Shenango) site, the exposed control (Clairton) site, and the unexposed control (Johnstown) site. The models were adjusted for seasonality. Blue solid line indicates the quarterly hospitalization rate before Shenango shutdown. Purple dashed line indicates the predicted trend of hospitalization rate without Shenango shutdown. Red solid line indicates the actual visit rate after intervention. The vertical line represents the day of the coke plant closure. COPD = chronic obstructive pulmonary disease. Table 2. Main Results from ITS Analysis, Respiratory Hospitalizations Variable Exposure: Coke Plant Shutdown Positive Control: Coke Plant Operating Negative Control: No Coke Plant Nearby IRR 95% CI P Value IRR 95% CI P Value IRR 95% CI P Value Hospitalizations for COPD and allied conditions  Preintervention trend, per year 1.03 0.92, 1.15 0.65 0.90 0.81, 1.01 0.09 0.96 0.84, 1.10 0.59  Immediate effect, Quarter 1, 2016 1.15 0.88, 1.50 0.33 1.51 1.15, 1.99 0.01 * 1.07 0.77, 1.50 0.68  Postintervention trend change, per year 0.81 0.70, 0.95 0.02 * 1.06 0.92, 1.23 0.43 1.04 0.87, 1.25 0.65 Asthma hospitalizations  Preintervention trend, per year 0.90 0.78, 1.05 0.19 0.86 0.75, 0.99 0.06 0.80 0.61, 1.05 0.13  Immediate effect, Quarter 1, 2016 0.44 0.27, 0.69 <0.01 * 0.57 0.37, 0.89 0.02 * 0.98 0.44, 2.14 0.95  Postintervention trend change, per year 1.24 0.97, 1.61 0.11 1.09 0.84, 1.40 0.53 1.00 0.63, 1.57 1.00 Hospitalizations from respiratory symptoms  Preintervention trend, per year 1.00 0.96, 1.04 0.99 0.95 0.90, 1.00 0.05 0.98 0.92, 1.03 0.41  Immediate effect, Quarter 1, 2016 0.84 0.76, 0.94 0.01 * 1.11 0.98, 1.25 0.13 0.98 0.86, 1.13 0.81  Postintervention trend change, per year 0.97 0.91, 1.03 0.33 1.02 0.95, 1.09 0.56 1.02 0.95, 1.10 0.61 Definition of abbreviations : CI = confidence interval; COPD = chronic obstructive pulmonary disease; IRR = incidence rate ratio; ITS = interrupted time series. All models were adjusted for seasonality. * Statistical significance ( P  < 0.05). Hospitalizations for COPD and Allied Conditions A statistically significant 19% reduction in long-term hospitalization risk due to COPD and allied diseases (i.e., chronic bronchitis, emphysema, and other COPD) was found in the population at (and only at) the near-Shenango exposure site after the shutdown (annual hospitalization: IRR = 0.81; 95% CI = 0.69–0.94). In contrast, the acute respiratory infections and lung cancer hospitalization rates, which were less likely to be directly and immediately impacted by this intervention, remained consistent across the three sites over the span of the study as expected ( see Table E3), supporting the specificity of the health benefits to biologically plausible outcomes. We found a similar effect size using a difference-in-difference model, further confirming the validity of our primary analysis. Hospitalizations for Asthma A significant 56% decline in all-age, asthma-related hospitalization rate was observed in the exposure site population immediately after the shutdown (IRR = 0.44; 95% CI = 0.27–0.69). A 43% decrease (IRR = 0.57; 95% CI = 0.37–0.89) was also seen at the study site population living where the Clairton coke plant was still operating, but such a decrease was not observed at the no-coke-plant unexposed negative control site. Total Respiratory ED Visits Before its shutdown, there was a long-term upward trend of overall respiratory ED visits in the Shenango exposure area ( Figure 4 and Table 3 ), which did not significantly change after the closure. However, there was a statistically significant short-term 21% reduction in respiratory ED visit rate observed in the near-Shenango site population immediately after the closure (daily visit IRR = 0.79; 95% CI = 0.72–0.87), as opposed to increases seen at the control sites (16% and 11% increases in weekly ED visit rate at the exposed control and unexposed control sites, respectively). The immediate near-Shenango site decrease remained robust in sensitivity analyses and similar in effect size in the subpopulation over 65 years of age but was not observed for traumatic injury ED control visits of the same age subgroup ( see Figures E3, E4 and Table E5). Figure 4. Segmented regression results for weekly respiratory ED visit rates at the exposure (Avalon) site, the exposed positive control (Clairton) site, and the unexposed negative control (Johnstown) site, 2013–2018. Blue solid line indicates the visit rate before Shenango shutdown. Purple dashed line indicates the predicted trend of visit rate without Shenango shutdown. Red solid line indicates the actual visit rate after intervention. The vertical line represents the day of the coke plant closure. ED = emergency department. Table 3. Main Results from ITS Analysis, Weekly Respiratory ED Visit Rates Variable Exposure: Coke Plant Shutdown Positive Control: Coke Plant Operating Negative Control: No Coking Operation Nearby IRR 95% CI P Value IRR 95% CI P Value IRR 95% CI P Value Preintervention, per week 1.002 1.001, 1.003 <0.001 * 1.000 0.998, 1.001 0.616 1.001 1.000, 1.002 <0.001 * Immediate effect, week after closure 0.795 0.724, 0.872 <0.001 * 1.164 0.993, 1.366 0.062 1.114 1.008, 1.230 0.034 * Postintervention change, per week 1.000 0.999, 1.001 0.753 1.006 1.004, 1.008 <0.001 0.999 0.998, 1.000 0.065 Definition of abbreviations : CI = confidence interval; ED = emergency department; IRR = incidence rate ratio; ITS = interrupted time series. All models are adjusted for seasonality. * Statistical significance ( P  < 0.05). Pediatric Asthma ED Visits Monthly pediatric asthma ED visits in the population residing at the near-Shenango exposure area were after a long-term upward trend before the shutdown (monthly IRR = 1.01; 95% CI = 1.00–1.02) but demonstrated an immediate and statistically significant 41% drop (IRR = 0.59; 95% CI = 0.40–0.86) after the shutdown, followed by a further 4% per-month decrease from the preclosure trend in the following 3 years ( Figure 5 and Table 4 ). In contrast, pediatric traumatic injury ED control visits for the near-plant exposure population did not exhibit a drop during the years after the closure, whereas pediatric asthma ED visits increased over time at the control sites after closure. The contrast between preclosure increasing trend versus postclosure changes in pediatric asthma visits (i.e., immediate and/or longer term declines) remained robust in sensitivity analyses ( see Figure E5, Tables E6–E8). Figure 5. Segmented regression results for monthly pediatric asthma ED visit rates at the exposure (Avalon) site, the exposed control (Clairton) site, and the unexposed negative control (Johnstown) site, 2013–2018. Blue solid line indicates the visit rate before Shenango shutdown. Purple dashed line indicates the predicted trend of visit rate without Shenango shutdown. Red solid line indicates the actual visit rate after intervention. The vertical dashed line indicates the day of the Shenango coke plant closure. ED = emergency department. Table 4. Main Results from ITS Analysis, Monthly Pediatric Asthma ED Visit Rates Variable Exposure: Coke Plant Shutdown Positive Control: Coke Plant Operating Negative Control: No Coking Operation Nearby IRR 95% CI P Value IRR 95% CI P Value IRR 95% CI P Value Preintervention 1.012 1.001, 1.024 0.037 * 0.984 0.966, 1.003 0.106 1.005 0.986, 1.024 0.638 Immediate effect, January, 2016 0.588 0.401, 0.856 0.008 * 1.007 0.564, 1.802 0.982 1.938 1.189, 3.202 0.011 * Postintervention change 0.958 0.940, 0.977 <0.001 * 1.041 1.016, 1.067 0.002 * 0.985 0.963, 1.009 0.218 For definition of abbreviations, see Table 3 . All models are adjusted for seasonality. * Statistical significance ( P  < 0.05). Discussion Taking advantage of the “natural experiment” scenario of the Shenango, Inc., coal coking plant closure and utilizing ITS analysis methods, we confirmed multiple short and longer term respiratory health benefits in the neighboring resident community after the plant shutdown, as compared with before its closure and compared with control sites and control outcomes (as summarized in Figure 6 ). Notably, the pediatric asthma ED visit risk precipitously dropped by 41% the month after closure and continued to decrease in the following years, significantly differing from the preclosure time trend. Overall respiratory ED visits also abruptly dropped by 21% after the shutdown in the near-plant exposure population but then continued to time-trend at a rate not different from that for the preclosure period. Overall hospitalizations for respiratory symptoms, as well as for people primarily diagnosed with asthma, decreased immediately in the quarter of the plant closure (by 56% and 16%, respectively) but followed the preclosure trend afterward, whereas COPD hospitalizations decreased in the longer term versus the prior trend. These near-plant community reductions in pulmonary medical visits after the closure were not found in the control populations during the same postclosure period, consistent with the interpretation of the near-plant reductions as due to the plant closure. Figure 6. Summary of study findings. White header row and column cells refer to the respiratory health benefits tested at the near-Shenango exposure site. Gray header row and column cells refer to internal and external controls. Green boxes refer to the statistically significant decrease observed. Blue boxes indicate that no significant change was observed. Red boxes indicate that a statistically significant increase was observed. COPD = chronic obstructive pulmonary disease; ED = emergency department. Known air pollution health effect mechanisms are consistent with the health benefits noted after the plant closure. The immediate respiratory health benefits observed are consistent with the significant large reduction of airway irritants, and longer term reductions may represent lung repair after the closure. These lung health benefits from reduced fossil-fuel air pollution appear remarkably consistent with the lung function and airway inflammation benefits experienced by smokers with asthma after they quit smoking ( 43 ). Coke ovens emit SO 2 and hydrogen sulfide (which spontaneously oxidizes to SO 2 ), which can induce airway irritation and bronchoconstriction and thus result in asthma exacerbation ( 20 , 44 ). The immediate drop in ambient SO 2 concentrations at the exposure site is consistent with the significant immediate decreases observed for both asthma hospitalizations and pediatric ED visits. The immediate declines in respiratory ED visits and hospitalizations of patients admitted for respiratory symptoms are also consistent with the instant elimination of environmental SO 2 . Longer term downward trends were observed for COPD hospitalizations and for pediatric asthma ED visits, suggesting a gradual reduction of chronic systemic inflammation from improved air quality over time, consistent with the elimination of chronic oxidative stress inducing coking-related PM particles. Although the closure-associated PM 2.5 mass concentration reduction was just a few micrograms per cubic meter, the physical and chemical characteristics of particles emitted in the coking process can make them especially potent in eliciting inflammatory responses and systemic effects, as compared with other types of PM (e.g., windblown soil particles) that lack those especially toxic characteristics. In particular, coking-related particles are usually higher in number concentration and smaller in size than other more usual ambient PM particles ( 9 ), exhibiting a higher ratio of surface area to volume and, thus, a higher capacity for biochemical reactions and biological interactions, as well as a higher amount of toxic components adhered ( 45 , 46 ). Commonly adhered gaseous compounds include SO 2 , which not only trigger irritation themselves but also increase the solubility and bioavailability of transition metals present in fossil fuel– associated PM ( 20 , 47 ). Such submicron particles can also penetrate deeper into the respiratory tract, enter the bloodstream, and translocate into the systemic circulation ( 48 , 49 ). Once inhaled, metal oxides—widely used as catalysts in coke production—can be generally easily dissolved in lung fluids ( 50 , 51 ). Moreover, high concentrations of heavy metals and transition metals have been found to be enriched in coking-related PM ( 52 , 53 ), which is consistent with an enhanced adverse effect per micrograms per cubic meter than reported for PM 2.5 particles, in both the short and long term. The presence of these fossil fuel– related PM particles can individually or synergistically induce oxidative stress and excess reactive oxygen species production, inflammation, and chronic systemic health effects ( 47 , 54 ). The inflammatory responses in the airway epithelium and pulmonary circulation also involve the secretion of proinflammatory cytokines (e.g., tumor necrosis factor α, IL-1β, IL-6, IL-8, etc.) ( 47 , 55 , 56 ). The elevation of these proinflammatory cytokines are known to be associated with, and involved in, the pathogenesis of COPD; for example, recent scientific evidence suggests that IL-6 can interfere with the cell signaling pathway, induce apoptosis, and play a role in airway remodeling ( 57 , 58 ). The shutdown of the coke plant, therefore, would mitigate prior exposure-induced systemic inflammation and, in the longer term, alleviate the exacerbation of chronic respiratory diseases such as COPD and childhood asthma. The hypothesized biological mechanism of alleviated systemic inflammation and oxidative stress is further supported by our previously reported findings of immediate and longer term cardiovascular health benefits in nearby residents ( 17 ). The findings of this study must be considered in the context of its limitations, despite its strengths in design. First, the spatial-temporal resolution of health data acquired for the analyses was limited by the local agency data release rules. Notably, in contrast to the complete unredacted data before closure, nearly half of the numbers of monthly pediatric ED visits had to be redacted because of low (1 ⩽  N  < 5) counts after the shutdown at the near-Shenango exposure site. Such significantly higher percentages of redacted data after versus before the closure can also be interpreted as further evidence of the reduction in incidences after the closure. Also, the findings remained robust in sensitivity analyses with only complete case data and with alternate imputation methods (Table E4). In addition, the transition from ICD-9 to ICD-10 codes in the last quarter of 2015 in hospitalization data may have contributed to a systematic reporting bias and result in less accurate intervention effect size estimates, but such count reductions were not seen at other sites, and multiple studies have reported no significant changes in coding validity or sensitivity in other similar databases ( 28 , 59 ). Second, our analytical areas were defined using zip codes, as the data were supplied or aggregated by residential zip code by the providing agencies. However, because of the complexity of terrain and wind patterns, and their associated heterogeneous dispersion of air pollutants emitted from point sources such as the Shenango coke plant, these zip code areas’ spatial heterogeneity and geographical complexity may have led to exposure misclassification and thus may have affected the estimated health effect size ( 60 ). In this study, we restricted our study area to zip codes in the immediate vicinity of the Shenango plant to examine the health impacts of the most directly affected population—those who were exposed to the fugitive emissions and unintended air pollution releases in its air quality violations ( 24 ). Higher spatiotemporal resolution air quality and health data, more accurate dispersion models considering plant characteristics and wind pattern, and source-specific air pollution data, if they were available, could potentially enable further analyses to assess the benefits from the intervention more accurately ( 60 , 61 ). Third, despite the extensive efforts to address potential confounding with the inclusion of internal and external control series, the control outcomes may still not exhibit the exact same temporal patterns to completely address the concern for unmeasured/residual confounding. By using the same population as its own control over time, the ITS study design inherently minimized potential confounding effects from individual participant level health condition and lifestyle factors; however, a long-term nonlinear trend and/or the population/area level confounding effects may still exist. Nevertheless, we were not aware of any other events or policy changes at the study sites that could have alternatively led to the robust patterns of decreased health impact trends observed. In terms of the generalizability of our results, there were a few modest demographic differences between the study sites and the county and state population: The exposure population had a slightly higher poverty rate and percentage of non-White people, as well as a smaller population growth rate, limiting the generalization of the results (e.g., effect coefficients) to dissimilar (e.g., healthier and wealthier) populations. Although the type of health benefits found from this plant closure should apply to other areas with such plant closures, caution should be given in the direct quantitative application of effect size findings to another population with very different population characteristics. Moreover, air pollution from different emissions sources can vary drastically in its composition and particle properties. Therefore, interventions targeting different air pollution components can have different health implications; with varying susceptibility of population exposed, the responses would very likely differ. Therefore, future environmental and health benefit assessments of interventions would help generate further scientific evidence to inform policymaking. Another possible complication lies in the potential demographic and socioeconomic changes after implementations of energy transition and industrial transformation policies ( 62 ). In this case, the closure of the Shenango coke plant affected 173 workers in the local neighborhood ( 63 ), representing some 0.2% of the population at the exposure site, which is small compared with the percent change found in respiratory impacts. Despite their potentially higher occupational exposures, it is not plausible that they could account for all the reductions in respiratory hospitalizations and ED visits observed. Also, in terms of the local and spillover socioeconomic impacts, we did not observe significant immediate changes in the demographic and socioeconomic factors at our study sites, and adjusting for poverty rate did not change our effect estimates. However, it should be noted that environmental interventions that target industrial emissions, especially those with larger scale interventions and on a longer term basis, can exert complex systemic implications on the health and well-being of the local communities ( 62 ). Overall, the aforementioned potential limitation considerations are deemed unlikely to be able to explain away our robust findings, and prior epidemiologic studies lend strong support to our findings. Those studies have found that the respiratory health of young children improved after the closure of coal-fired powerplants ( 64 ) and steel mills ( 65 ). Although past literature has suggested that living in the vicinity of coking plants can potentially increase health risks in resident populations ( 13 , 20 , 66 ), a previous investigation on the Shenango coke plant closure, which was based on annual counts but not the immediate and long-term trend changes, was reluctant to conclude a causal relationship between the shutdown and the health benefits observed ( 32 ). Our analysis, considering more immediate time periods before and after the closure, are more definitive as to the cause-and-effect relation, as it revealed the strong time coincidence of the closure and multiple subsequent health benefits, especially in comparison with control health outcomes and other locales at the same time, meeting the temporality, strength, consistency, specificity, and biological plausibility criteria for causal inference ( 67 ). Our findings on respiratory benefits, together with the previously reported cardiovascular benefits, are consistent with the conclusion of a causal inference of significant cardiopulmonary health benefits from the closure of the Shenango coke plant being caused by the noted air pollution reductions ( 17 , 67 , 68 ). Our findings add to the growing body of evidence that regulating and reducing fossil fuel–related air pollution emissions produce significant public health benefits, in both the short term and the longer term ( 69 – 71 ). Supplemental Materials Online Data Supplement 10.1164/rccm.202410-2005OC Acknowledgments Acknowledgment The authors thank the Pennsylvania Health Care Cost Containment Council and the Pennsylvania Department of Health for generating and sharing the health data. The authors thank Dr. Philip R. S. Johnson of the Heinz Endowment for his support and advice. Footnotes Supported by Heinz Endowments grants E8132 and G0320. Author Contributions: W.Y. and G.D.T. contributed to the study concept and design. W.Y. and G.D.T. acquired, analyzed, and interpreted the data. W.Y. wrote the draft manuscript and conducted the statistical analyses. G.D.T. revised the manuscript for important intellectual content. This article has a related editorial . A data supplement for this article is available via the Supplements tab at the top of the online article. Artificial Intelligence Disclaimer: No artificial intelligence tools were used in writing this manuscript. 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