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Article

Clean Air Benefits and Climate Penalty: A Health Impact Analysis of Mortality Trends in the Mid-South Region, USA

by
Chunrong Jia
1,*,
Hongmei Zhang
1,
Namuun Batbaatar
1,
Abu Mohd Naser
1,
Ying Li
2 and
Ilias Kavouras
1
1
School of Public Health, University of Memphis, Memphis, TN 38152, USA
2
Department of Environmental and Occupational Health and Safety Sciences, College of Public Health, East Tennessee State University, Johnson City, TN 37614, USA
*
Author to whom correspondence should be addressed.
Climate 2025, 13(3), 45; https://doi.org/10.3390/cli13030045
Submission received: 24 December 2024 / Revised: 17 February 2025 / Accepted: 21 February 2025 / Published: 22 February 2025
(This article belongs to the Special Issue Confronting the Climate Change and Health Nexus: Interactions, Impacts, and Adaptation Strategies)
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Abstract

:
The lowering air pollution in the US has brought significant health benefits; however, climate change may offset the benefits by increasing the temperature and worsening air quality. This study aimed to estimate the mortality changes due to air pollution reductions and evaluate the potential climate penalty in the Mid-South Region of the US. Daily concentrations of PM2.5 and ozone measured at local monitoring stations in 1999–2019 were extracted from the US Environmental Protection Agency’s Air Quality System. Meteorological data for the same period were obtained from the National Oceanic and Atmospheric Administration’s Local Climatological Data. Annual average age-adjusted all-cause mortality rates (MRs) were downloaded from the US Centers for Disease Control and Prevention’s WONDERS Databases. MRs attributable to exposure to PM2.5, ozone, and high temperatures in warm months were estimated using their corresponding health impact functions. Using Year 1999 as the baseline, contributions of environmental changes to MR reductions were calculated. Results showed that annual average concentrations of PM2.5 and ozone decreased by 46% and 23% in 2019, respectively, compared with the base year; meanwhile, the mean daily temperature in the warm season fluctuated and displayed an insignificant increasing trend (Kendall’s tau = 0.16, p = 0.30). MRs displayed a significant decreasing trend and dropped by 215 deaths/100,000 person-year in 2019. Lower PM2.5 and ozone concentrations were estimated to reduce 59 and 30 deaths/100,000 person-year, respectively, contributing to 23% and 17% of MR reductions, respectively. The fluctuating temperatures had negligible impacts on mortality changes over the two-decade study period. This study suggests that improved air quality may have contributed to mortality reductions, while the climate penalty effects appeared to be insignificant in the Mid-South Region.

1. Introduction

Clean air is crucial for promoting better health, given the widely recognized harmful impacts of air pollution [1]. The levels of criteria pollutants have steadily declined by 22–90% between 1970 and 2022, due to the Clean Air Act, its amendments and derivative federal and state rules, and technological advances to reduce emissions from industrial and mobile sources [2]. Consequently, Americans are now exposed to lower air pollution, reducing the risk of death and other diseases. Studies have quantified the positive impacts, e.g., a 10 μg/m3 decrease in average PM2.5 concentrations increased the life expectancy of the US population by 0.61 years during 1980–2000 [3] and 0.35 years during 2000–2007 [4]. A follow-up study emphasized that the reduction in air pollution-related mortality was primarily due to decreases in ambient fine particulate matter (PM2.5) [5]. Improved air quality is particularly beneficial for children’s health, including improvements in lung function, asthma, and low birth weight [6,7,8]. The benefits are not only reported for the US but extend to countries worldwide [9,10].
Climate change, unfortunately, undermines the health benefits of air quality improvements. The direct environmental impacts of climate change are increased frequency, magnitude, and duration of extreme temperature events [11]. The interaction between climate change and air pollution is projected to impose a “climate penalty”, defined as the amplification effect on air pollutants by climate change and the associated excess health risks [12]. Climate penalty mainly occurs to ozone (O3), PM2.5, black carbon, and nitrogen oxides, despite the ongoing efforts to reduce their emissions [13,14]. Ozone is most sensitive to temperature variation. Although the national average ozone concentration decreased from 88 ppb in 1999 to 65 ppb in 2019 [2], studies projected a potential increase of up to 7 ppb in some US regions by 2050 due to rising temperatures [15]. Similarly, temperature changes also affect PM2.5 concentrations, with estimates suggesting a 2–3 µg/m3 increase in the eastern US during the summertime by 2050 [16]. As a result, climate change has both direct and indirect impacts on human health. An increase of 1 °C in summer mean daily temperature is associated with a 2.2% mortality increase and indirectly associated with 1.0% and 3.2% increases in PM2.5- and ozone-related mortality, respectively [17].
The cumulative impacts of air pollution and climate change warrant urgent attention in research and practice. The scientific community is interested in predicting future impacts with hypothetical climate change scenarios on the global and national scales [18]. Limaye et al. [19] estimated that warmer average apparent temperatures could cause over 10,000 additional annual deaths in the eastern US by 2050. Neumann et al. [20] projected that wildfire emissions would cause 1300–1600 PM2.5-related premature deaths per year in the western US by 2050. Wilson et al. [21] estimated that mortality attributed to ozone elevation will increase by 14.2% in the US in 2035. A global study suggested that global greenhouse gas reductions in Representative Concentration Pathway 4.5 (RCP4.5) could avoid 16,000 PM2.5-related all-cause deaths and 8000 O3-related respiratory deaths per year in the US [22]. Limited studies have retrospectively evaluated the cumulative impacts for a specific region in the US. In practice, health impacts are assessed using tools such as the World Health Organization (WHO)’s AirQ+ and the US Environmental Protection Agency (EPA)’s BenMAP to evaluate pollution control policies and programs [23]; however, these assessments often focus only on PM2.5, without simultaneous consideration of climate penalty effects.
This study aimed to evaluate the impacts of air pollution reduction and temperature increase on mortality changes over the past two decades in the Mid-South Region of the US. This region, like many other US metropolitan areas, has had declining mortality rates in the past decades before the COVID-19 pandemic [24]. With the recent 20 years of vital and environmental data, this study was aimed at understanding the contributions to mortality changes from air quality improvements as well as the potential climate penalty in this region. This motive responded to the need for local decision-making in affected communities [25], a gap in predominant global and national analyses on this topic [26].

2. Methods

2.1. Study Area

The Mid-South is an informally defined region of the US anchored by the City of Memphis. Memphis is the largest city in the State of Tennessee and the 20th largest city in the US. As the demographic and environmental data are collected at the county level, this study used data in three neighboring urban counties in the Mid-South: Shelby County, Tennessee (TN), DeSoto County, Mississippi (MS), and Crittenden County, Arkansas (AR), as displayed Figure 1. Table S1 summarizes the key demographic and socioeconomic statistics of Shelby, DeSoto, and Crittenden Counties in Year 2019.

2.2. Vital and Environmental Data

All the vital and environmental data for this study were extracted from publicly available online databases. The start and end years for data extraction were initially set as 1980 and 2019. The US EPA archived air quality data starting in 1980, but PM2.5 data were only available beginning in 1999. The COVID-19 pandemic started in this region in March 2020 and was known to increase the mortality rate dramatically. Considering the data availability, this study covered the period between 1999 and 2019.
County-level demographic data, including mortality rates, were downloaded from the US Centers for Disease Control and Prevention’s (CDC) WONDER online databases [27]. To match the original studies that determined relative risks (RRs), health measures used natural-cause mortality (ICD codes: A00-R99) for PM2.5 [28], all-cause mortality (ICD codes: A00-U99) for ozone [29], and all-cause mortality excluding accidental deaths (V01-Y98) for temperature [30,31]. Although the ICD codes were different for these three mortality rates, the actual rates were the same for any county in any year. The crude mortality rates were converted to age-adjusted mortality rates, if not available in the original datasets, by applying age-specific rates in the study population to Year 2000 standardized US age distribution [32,33]. For convenience, the mortality rate (MR) in this study refers to the annual average age-adjusted mortality rate. MR was expressed as the number of deaths per 100,000 people-years, written as deaths/PY* following a convenient way by EPA [34]. For any year, the MR of the three counties was computed as the weighted average of the three counties’ MRs by weighing their population sizes. As Shelby County had a far larger population (Table S1), the weighted average statistics were driven by and similar to Shelby County data.
For air pollution data, annual average concentrations of PM2.5 and ozone were extracted from EPA’s Air Quality System [35] for 1999–2019. It should be noted that the annual average concentrations of ozone were calculated from daily 8 h maximum concentrations. DeSoto County had only one monitoring station (Hernando Station, AQS Site ID: 28-033-0002), and Crittenden County had only one station (Marion Station, AQS Site ID: 05-035-0005), too. Shelby County had multiple air monitoring stations. The Memphis National CORE Station (AQS Site ID: 47-157-0075) was a comprehensive air monitoring station that started operation in 2011, and the data collected at this site were used for the period 2011–2019. Data measured at the Frayser Station (AQS Site ID: 47-157-0021) were used for the period 1999–2010. Our previous study showed small variability in criteria air pollutant concentrations in this region [36], and thus, it was reasonable to use air pollution data collected at one site in each county and average them to represent the overall air pollution level in the Mid-South Region.
Meteorological data for the same period were obtained from the National Oceanic and Atmospheric Administration’s (NOAA) Local Climatological Data [37]. There were no weather stations that had validated meteorological data in DeSoto County or Crittenden County. Thus, the meteorological data collected at the Memphis International Airport (Network ID: WBAN:13893: Latitude/Longitude: 35.05639°, −89.9864°) were used for this region. Weather station data have been used to study the impacts of temperature on mortality in urban areas in the US [38,39]. The Memphis International Airport is situated at the center of the entire study area (Figure 1) and can broadly represent the climate of this region. The hourly temperature data (in °C) at this airport were downloaded from the NOAA database [37], and the daily average temperatures were computed for the following analyses.

2.3. Trend Analysis

The long-term trends of MRs, air pollution levels, and ambient summertime temperatures during the study period of 1999 through 2019 were examined by plotting these parameters against year. The significance of trends was examined using the Mann–Kendall test, which yielded a Kendall tau correlation between parameter and time. In this study, a positive correlation indicated an increasing trend, and vice versa. A p-value of <0.05 indicated a statistically significant trend.

2.4. Impacts of Environmental Factors on Mortality

The US EPA has been using the health impact function approach to evaluate the health impacts of air pollution on mortality [40]. In any specific year, the MR attributable to exposure to PM2.5 (MRPM2.5) or ozone (MRO3) is calculated as
MRPM2.5 (or O3) = MR × (eβ‧∆x − 1)
where β is the coefficient for the exposure–health association, and Δx is the difference between an exposure and the threshold level. In this study, Δx was calculated as the annual average concentration of PM2.5 or ozone minus 0, assuming air pollution is always detrimental. MRs attributable to other criteria air pollutants were not calculated due to the lack of exposure–mortality relationships. The β value was derived from the relative risk (RR) of the effect determined in previous epidemiological studies conducted in representative US populations. Table 1 summarizes the RRs, β values, and their data sources. Model (1) assumes there was no safe threshold of air pollution exposure for adverse health effects, supported by the recent World Health Organization’s Air Quality Guidelines [41].
High temperatures during the warm season, i.e., between 1 May and 30 September, elevate the daily mortality rate if the daily average temperature is above the optimum temperature of 15.6 °C (60 F°) [42]. The daily mortality rate attributable to the elevated temperature is calculated as [31]
Daily MRTemp = Daily MR × (eβ‧∆x − 1)
where β is the coefficient for the heat–mortality association (Table 1), and Δx is the temperature increase from 15.6 °C. Equation (2) was applied to days between 1 May and 30 September inclusively for any year. The daily mortality rate was unavailable and thus was calculated by dividing the annual MR by 365 (or 366 for a leap year), an approach applied in previous health impact studies [31,43]. Days with an average temperature below 15.6 °C were assumed to have no detrimental effects due to heat. In any year, the elevated daily mortality rates were added to yield the annual MR related to heat, i.e., MRTemp.
As seen in the results, MR displayed a downward trend in this area. Using Year 1999 as the baseline, the change of the MRs in a later year (ΔMRs) was calculated by subtracting the MR in 1999 from the MR in that particular year. Similarly, changes in environment-related MRs, i.e., ∆MRPM2.5, ∆MRO3, and ∆MRTemp, were calculated by subtracting MRPM2.5 (O3, Temp) in 1999 from MRPM2.5 (O3, Temp) in a later year. The contribution of an environmental (PM2.5, ozone, or temperature) change to ∆MR in a year was expressed as a percentage:
ContribPM2.5 (or O3, Temp) = ∆MRPM2.5 (O3, Temp)/∆MR × 100%
For the Mid-South Region, the environment-related MRs and their contributions to ∆MR were computed by weighing their population sizes. As Shelby County had a predominantly large population (Table S1), the Mid-South results were similar to those using only Shelby County data.

3. Results

3.1. Trends in Air Pollution and Temperature

PM2.5 and ozone levels had apparent declining trends in the Mid-South Region during the study period, as displayed in Figure 2. Annual average concentrations of PM2.5 and ozone were 8.3 µg/m3 and 41 ppb in 2019, 46% and 23% down from 1999, respectively. The Mann–Kendall tests showed both PM2.5 and ozone trends were statistically significant (p-values < 0.01). These trends were in accordance with the national trends: the national annual average PM2.5 concentration dropped from 13.5 µg/m3 in 2000 (1999 data were not available) to 7.7 µg/m3 in 2019, and the national average ozone concentration (The national annual average is the average of the annual 98th percentile of daily 8 h maximum across the sites, and our annual average ozone concentration is the average of daily 8 h max concentrations. Thus, the national annual averages and our annual averages differed in their values, but both showed distinctly decreasing trends) from 84 ppb in 1999 to 65 ppb in 2019 [2]. Warm-season temperatures fluctuated over the years and had an insignificant positive association with time (Kendall’s tau = 0.16, p = 0.30). The three bordering counties had similar levels and trends of PM2.5 concentrations (Figure S1). Ozone concentrations were similar in Shelby and DeSoto Counties but were lower in Crittenden County; they all displayed downward trends in these three counties.

3.2. All-Cause and Environment-Related Mortality Rates

The all-cause mortality rate (MR) in the Mid-South Region showed a declining trend over the two decades between 1999 and 2019 (Figure 3A). MR and year had a significant negative association (Kendall’s tau = −0.86, p < 0.0001). The MR was 1003 deaths/PY* in 1999 and decreased to 788 deaths/PY* in 2019, with some small fluctuations in between. By 2019, MR was 215 deaths/PY* less than that in 1999, a 21% decrease. In individual counties, MRs consistently showed an order of Crittenden > Shelby > DeSoto and exhibited generally decreasing trends (Figure S2). The Kendall’s tau coefficients between MR and year were −0.84 (p < 0.0001), −0.50 (p = 0.0014), and −0.71 (p < 0.0001) in Shelby, DeSoto, and Crittenden Counties, respectively, suggesting statistically significant decreasing trends.
MRs attributable to PM2.5 and ozone displayed downward trends, as a result of the decreasing air pollution levels. MRPM2.5 dropped from 126 deaths/PY* in 1999 to 67 deaths/PY* in 2019 (Figure 3B), and the trend was significant (Kendall’s tau = −0.88, p < 0.0001). MRO3 decreased from 117 deaths/PY* in 1999 to 87 deaths/PY* in 2019 (Figure 3C), and the trend was significant (Kendall’s tau = −0.79, p < 0.0001), too. Due to the variation in the original exposure–effect relationships, MRPM2.5 and MRO3 both had large confidence intervals. In individual counties, MRPM2.5 showed a consistent order of Crittenden > Shelby > DeSoto (Figure S3), and MRO3 was similar in Shelby and DeSoto Counties but higher in Crittenden County (Figure S4). Comparing Figure 3B and Figure 3C, PM2.5-related mortality was greater than ozone-related mortality before 2010 but smaller afterward, suggesting more health benefits from PM2.5 reduction over the past two decades.
The impact of high temperatures on mortality was much lower than those of air pollution (Figure 3D). MRTemp ranged between 3.5 and 4.7 deaths/PY* during the study period. MRTemp showed a positive but insignificant association with time (Kendall’s tau = 0.21, p = 0.17). The MRTemp averaged 4.0 deaths/PY* in the Mid-South Region and Shelby County. Considering a population of around 1 million in Shelby County, the total number of deaths due to high temperatures was about 40 deaths per year. Our previous study based on actual daily death numbers in Shelby County also reported 40 deaths/year on heatwave days between 2008 and 2017 [44]. This agreement between the modeled and observed death numbers, to some extent, suggested the validity of the impact assessment model Equation (1).

3.3. Contributions of Environmental Factors to MR Changes

The improved air quality had sizable contributions to the reductions in all-cause MRs. The lowered PM2.5 concentrations reduced MRs by 4–62 deaths/PY* in 2000 through 2019, compared to the baseline MR in 1999. The contributions of ∆MRPM2.5 to ∆MR drastically fluctuated in 2000 through 2002, which then showed a limited range of 8–44% afterwards (Figure 4A). The average contribution of ∆MRPM2.5 to ∆MR was 23% between 2003 and 2019. Contributions of ∆MRPM2.5 to ∆MR displayed similar patterns in individual counties (Figure S5).
Reduced ozone concentrations were estimated to reduce MRs by 6–34 deaths/PY* in 2000 through 2019. Similar to PM2.5, the contributions of ozone-related MR reductions (∆MRO3) to ∆MRs varied drastically between 2000 and 2002, but had a limited range of 9–43% in the later years (Figure 4B). Between 2003 and 2019, ∆MRO3 contributed 17% of ∆MR on average in the Mid-South, and 18%, 12%, and 9% to ∆MRs in Shelby, DeSoto, and Crittenden Counties, respectively (Figure S6).
The contributions of temperature-related MR changes (∆MRTemp) to ∆MR were overall small, ranging from −0.4% to 2.0% (Figure 4C). The average contribution of ∆MRTemp to ∆MR was 0 on average for the period of 2003 through 2019, meaning a negligible contribution of high temperatures on mortality in warm seasons.

4. Discussion

This study documented the declining mortality, improved air quality, and fluctuating but generally unchanged warm-season temperatures in the Mid-South Region two decades before the COVID-19 pandemic. Changes in the death risk factors drive the change in population mortality [45]. Smoking, poor diet, physical inactivity, and alcohol consumption were the leading causes of death in the US in 2000 [46]. The declining mortality rates in the US were attributable to improvements in public health, medical advances, and behavioral changes [47], e.g., reductions in tobacco smoking accounted for 40% of fall in US male cancer mortality [48]. Numerous studies have confirmed air pollution as a risk factor for mortality [28,49]; however, there is no direct analysis showing that the decreases in environmental stressors lead to a decline in mortality.
This retrospective health impact assessment confirmed the health benefits of air pollution reduction reported in previous studies. Most health impact studies only estimate death numbers due to PM2.5 exposure on the international [50], national [51], and local [52] scales, without quantifying contributions to the actual mortality. Only a few studies quantified the contributions of air pollution improvement to mortality reductions in the US, and the estimates varied greatly. An Arkansas-based study reported that 50–100% reduction of non-accidental mortality was attributable to PM2.5 reductions in Crittenden County between 2000 and 2010 [53]. A modeling study showed that 5.0%, 5.2%, and 5.0% of deaths were attributable to 40% reduction of PM2.5 levels in TN, MS, and AR, respectively [54]. A national analysis of PM2.5 trends in the US reported that the average annual PM2.5-related decrease in cardiovascular mortality rate (CMR) contributed 11% of the total CMR reduction between 1990 and 2010 [34]. Globally, the reduction in deaths due to PM improvement contributed 18% of the all-cause death reduction from 2007 to 2017 [55]. The estimated 23% contribution to mortality reduction by PM2.5 reduction in the Mid-South was comparable to the range of the reported contributions.
The tropospheric ozone situation was more complex, as ozone is a secondary air pollutant strongly affected by temperature shifts. Increasing temperatures accelerate atmospheric reactions and, in turn, increase ground ozone levels; however, the climate penalty on ozone has high site-to-site heterogeneity in the US [56]. A few studies predicted ozone-related mortality burden attributable to climate changes by modeling, e.g., Bell et al. [57] predicted 0.11–0.27% increase in daily total mortality due to elevated ozone levels by 2050, and Wilson et al. [21] predicted that mortality would increase by 7.7% and 14.2% attributed to ozone exceeding 40 ppb and 75 ppb, respectively, by 2030. In the Mid-South, the improvement in air pollution outweighed the climate penalty on ozone, evidenced by the significantly decreasing ozone trends. Our results were consistent with a recent study that reported a significant reduction in climate penalty effects on PM2.5 and ozone due to efficient emission control strategies [58].
The changes in heat-related mortality, using average daily temperatures in warm seasons, were negligible over the study period for two reasons. First, the health impact of heat was small in this region based on the exposure–response relationship. Our results showed that heat-related mortality was about 25 times lower than air pollution-related mortality (Figure 3). The Mid-South is not a traditionally vulnerable heat area, and the correlation between anomalously high temperatures and human health is more ambiguous [59]. A national analysis reported decreased deaths attributable to summertime heat in Memphis from 1987 to 2005, due mainly to the higher population resilience to heat over time [55]. The global disease burden analysis found mortality due to environmental heat and cold dropped from 0.9 deaths/PY* in 2005 to 0.7 deaths/PY* in 2015, suggesting a lack of association between mortality and climate change [60]. Second, climate change is a long-term change in the state of the climate that persists for decades or longer. Two decades may not be long enough to show significant temperature increases, evidenced by the generally flat temperatures in warm seasons between 1999 and 2019 (Figure 2).
The analyses in this study had multiple uncertainties in every component of the health impact function. A significant source of uncertainty derived from the coefficients for the exposure–health association (βs in Table 1) taken from national or regional cohort studies. For this study, the best available β values were adopted for PM2.5, ozone, and temperature from the literature for all-cause mortality. The validity of Model (2) and its parameters could be evidenced by the good agreement between modeled and observed heat-related death numbers in Shelby County. The calculations did not factor in changes in the exposure–response relationship over time. Nationally, there was a remarkable decline in the US temperature–mortality relationship, thanks to wide uses of residential air conditioning [61]. Numerous factors are known to impact mortality rates, e.g., healthcare system improvements, medical treatment advancements, and public health interventions, which were not considered in this study. This health impact assessment also had several limitations. The joint effects from co-exposure to multiple environmental stressors are still inconsistent [62], and the exposure–health associations in original studies accounted for other environmental factors. Thus, each stressor’s impact was presented separately. Evaluating health impacts for ethnic and socioeconomic subgroups would be an interesting study addressing health and environmental disparities. National analyses using county-level data indicated that PM2.5 attributable cardiovascular mortality burden was 3.5 times higher for black people than for white people [63], and PM2.5-related cardiovascular mortality reductions were highest in counties with moderate to high deprivation [34]. However, this task was unachievable for this study due to a lack of mortality data for subpopulations. Our study covered the urban counties of the Mid-South but not the rural counties. In the US, trends, causes, and risks of mortality in rural (nonmetropolitan) areas differed substantially from those in urban areas [64,65]. It would be interesting to address sociodemographic disparities and urban–rural gaps in future health impact studies.
This study presented several methodological and practical novelties. First, it put together the health impacts of changes in atmospheric PM2.5, ozone, and temperature. Previous studies either estimated the positive impacts of air quality improvements or the negative impacts of climate change. Our methodology offered a novel perspective to assess the benefits of clean air and the penalties of climate change simultaneously. Second, this study presented the only and first detailed health impact assessment for the Mid-South Region. Most air pollution and climate impact studies have been conducted at national or global levels that include hundreds or thousands of cities. Those studies can offer a broad overview of health impacts but lack the detailed results necessary for local environmental decision-making. The Mid-South Region is particularly unique, characterized by a high percentage of disadvantaged populations, numerous sources of air pollution, and poor health outcomes. No specific environmental health impact assessment has been conducted for this area, so our findings help fill this knowledge gap. More regional and local impact assessments are warranted to complement large-scale national and global studies. Third, from the practical perspective, our study demonstrated a health impact framework using publicly available health and environmental data and multi-pollutant impact models. Local regulatory agencies and interested stakeholders can easily replicate this framework to evaluate the health impacts from changing air pollution and climate in their respective areas. Our results evidenced the effectiveness and benefits of air pollution control in the Mid-South Region. These findings endorsed the contributions to and achievements in environmental protection of local professionals, who otherwise seldom gain professional recognition or credibility.

5. Conclusions

To our knowledge, this is the first study that simultaneously examined clean air benefits and climate penalties in the Mid-South Region of the US. The long-term environmental data showed significant reductions in annual average concentrations of PM2.5 (46%) and ozone (23%) and in mortality rate (21%) in 2019 compared with the baseline year 1999. Average temperatures in warm seasons did not display significant increasing or decreasing trends. Health impact assessment showed that PM2.5 and ozone reductions contributed to 23% and 17% of the mortality reduction, respectively, but warm-season temperature changes had an average null contribution to mortality changes. These results suggested that air quality improvement might have brought health benefits in the Mid-South in the past two decades; meanwhile, the climate penalty seemed negligible during the same period. This study demonstrated a health assessment framework that local governments can adopt to evaluate the health benefits of pollution control and endorse environmental professionals’ contributions.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/cli13030045/s1, Table S1: Demographic, social, and economic characteristics of Shelby County, TN, DeSoto County, MS, and Crittenden County, AR; Figure S1: Annual averages of PM2.5 concentrations (in µg/m3) and 8 h max daily ozone concentrations (in ppb) in the three urban counties in the Mid-South Region between 1999 and 2019; Figure S2: Age-adjusted all-cause annual average mortality rates in the Mid-South Metropolitan Region and three counties between 1999 and 2019; Figure S3: Age-adjusted all-cause annual average mortality rates attributable to PM2.5 exposure in the Mid-South Region and three counties between 1999 and 2019; Figure S4: Age-adjusted all-cause annual average mortality rates attributable to ozone exposure in the Mid-South Metropolitan Region and three counties between 1999 and 2019; Figure S5: Contributions of PM2.5-related ∆MRs to all-cause ∆MRs in three urban counties in the Mid-South Region. Notes: The baseline year was 1999; Figure S6: Contributions of ozone-related ∆MRs to all-cause ∆MRs in three urban counties in the Mid-South Region. Notes: The baseline year was 1999.

Author Contributions

Conceptualization, C.J., H.Z., and I.K.; methodology, C.J., H.Z., I.K., and Y.L.; formal analysis, N.B. and H.Z.; data curation, N.B. and H.Z.; writing—original draft preparation, C.J.; writing—review and editing, Y.L. and A.M.N.; visualization, N.B. and C.J.; supervision, C.J.; project administration, C.J.; funding acquisition, C.J. All authors have read and agreed to the published version of the manuscript.

Funding

This research was partially funded by a sub-award (Number: 2-340-0219134-67597L) from the U.S. Environmental Protection Agency’s Environmental Justice Thriving Communities Technical Assistance Center (EJ TCTAC) Program (Cooperative Agreement 13746193).

Data Availability Statement

The mortality data were downloaded from CDC’s WONDER Database at https://wonder.cdc.gov/ (accessed on 23 May 2023). The air quality data were downloaded from EPA’s Air Quality System at https://aqs.epa.gov/aqsweb/airdata/download_files.html (accessed on 22 May 2023). The temperature data were downloaded from NOAA’s Local Climatological Data (LCD) at https://www.ncdc.noaa.gov/cdo-web/datatools/lcd (accessed on 22 May 2023). Details of the data have been described in the Methods section of this manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Map of the Mid-South Metropolitan region, USA.
Figure 1. Map of the Mid-South Metropolitan region, USA.
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Figure 2. Annual average PM2.5 concentrations (in µg/m3), annual average 8 h max daily ozone concentrations (in ppb), and average ambient temperatures (in °C) during the warm season (May–September) in the Mid-South Region between 1999 and 2019. The error bars indicate standard deviations.
Figure 2. Annual average PM2.5 concentrations (in µg/m3), annual average 8 h max daily ozone concentrations (in ppb), and average ambient temperatures (in °C) during the warm season (May–September) in the Mid-South Region between 1999 and 2019. The error bars indicate standard deviations.
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Figure 3. Total mortality rates (MRs) and MRs attributable to PM2.5 (MRPM2.5), ozone (MRO3), and warm-season temperature (MRTemp) in the Mid-South Metropolitan Region between 1999 and 2019. The errors bars of MRPM2.5, MRO3, and MRTemp were upper and lower 95% confidence intervals (CIs) calculated from the 95% CIs of β values in Table 1.
Figure 3. Total mortality rates (MRs) and MRs attributable to PM2.5 (MRPM2.5), ozone (MRO3), and warm-season temperature (MRTemp) in the Mid-South Metropolitan Region between 1999 and 2019. The errors bars of MRPM2.5, MRO3, and MRTemp were upper and lower 95% confidence intervals (CIs) calculated from the 95% CIs of β values in Table 1.
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Figure 4. Contributions of PM2.5, ozone, and temperature-related ∆MRs to observed ∆MRs in the Mid-South Metropolitan Region. Notes: The baseline year was 1999.
Figure 4. Contributions of PM2.5, ozone, and temperature-related ∆MRs to observed ∆MRs in the Mid-South Metropolitan Region. Notes: The baseline year was 1999.
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Table 1. Exposure–response relationships determined in previous cohort studies.
Table 1. Exposure–response relationships determined in previous cohort studies.
Environmental ParameterMortalityRelative Risk (95% Confidence Interval)β (95% CI)Source
PM2.5 1Natural-cause mortality, excluding accidents, suicides, and homicides1.08 (1.06, 1.09) per 10 µg/m30.0077 (0.0058, 0.0086) per 1 µg/m3[28]
Ozone 2All-cause mortality1.02 (1.01, 1.03) per 10 ppb0.00198 (0.0010, 0.0030) per 1 ppb[29]
Temperature in the warm season 3All-cause mortality, excluding accidental deaths1.0009 (1.0000, 1.0018) per 1 °C 40.0009 (0.0000, 0.0018) per 1 °C[42]
1 Measured as annual average PM2.5 concentrations (µg/m3). 2 Measured as annual average 8 h daily maximum ozone concentrations (ppb). 3 Daily average ambient temperature (°C). 4 The RR for the Southeast Region was used, as this study area belongs to the Southeast Region.
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Jia, C.; Zhang, H.; Batbaatar, N.; Naser, A.M.; Li, Y.; Kavouras, I. Clean Air Benefits and Climate Penalty: A Health Impact Analysis of Mortality Trends in the Mid-South Region, USA. Climate 2025, 13, 45. https://doi.org/10.3390/cli13030045

AMA Style

Jia C, Zhang H, Batbaatar N, Naser AM, Li Y, Kavouras I. Clean Air Benefits and Climate Penalty: A Health Impact Analysis of Mortality Trends in the Mid-South Region, USA. Climate. 2025; 13(3):45. https://doi.org/10.3390/cli13030045

Chicago/Turabian Style

Jia, Chunrong, Hongmei Zhang, Namuun Batbaatar, Abu Mohd Naser, Ying Li, and Ilias Kavouras. 2025. "Clean Air Benefits and Climate Penalty: A Health Impact Analysis of Mortality Trends in the Mid-South Region, USA" Climate 13, no. 3: 45. https://doi.org/10.3390/cli13030045

APA Style

Jia, C., Zhang, H., Batbaatar, N., Naser, A. M., Li, Y., & Kavouras, I. (2025). Clean Air Benefits and Climate Penalty: A Health Impact Analysis of Mortality Trends in the Mid-South Region, USA. Climate, 13(3), 45. https://doi.org/10.3390/cli13030045

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