Mapping Eight Years of PM2.5 Pollution and Its Deadly Toll in Central China

Fine particulate matter smaller than 2.5 micrometers across — known as PM2.5 — remains one of the most consequential environmental threats to public health in densely populated regions of the world, and Central China sits squarely in the crosshairs of this challenge. A new study published in Environmental Monitoring and Assessment has now delivered one of the most detailed portraits to date of how this pollutant has evolved across the region, combining eight years of concentration data with sophisticated spatial statistics and an established health impact model to translate atmospheric chemistry into human lives and economic losses. The research, led by Minxia Liu of Northwest Normal University together with Yi Yang and Siqian Wang, examined the three provinces that make up Central China — Henan, Hubei, and Hunan — between 2017 and 2024, with a deeper dive into Henan’s health and economic burden from 2017 to 2023.

Central China occupies a peculiar and important position in the country’s air quality landscape. Situated in the transitional zone between China’s heavily industrialized east and its less developed west, the region functions simultaneously as a source of emissions and as a corridor through which pollutants are transported by prevailing winds. This dual role makes it a natural laboratory for understanding how pollution behaves across a gradient of economic development, and why local control measures alone may not be sufficient to protect residents. Despite this importance, the authors note that integrated studies linking the spatiotemporal evolution of PM2.5 to its health and economic consequences in this specific region had remained limited until now.

To build their analysis, the researchers drew on ground-based monitoring observations alongside the Tracking Air Pollution in China dataset, a near real-time product that fuses satellite retrievals, model simulations, and monitoring station data to produce high-resolution PM2.5 estimates across the country. On top of this data foundation, they layered a suite of analytical tools: spatial statistical methods to detect clustering patterns, a centroid migration model to track how the pollution center of gravity shifted from year to year, and the BenMAP health impact assessment model, a tool widely used to convert pollutant concentrations into estimates of premature mortality and monetary damages. This combination allowed the team to move beyond simple averages and capture the geography of risk in fine detail.

The seasonal signal that emerged from the analysis was unambiguous. PM2.5 concentrations across Central China were consistently higher in winter and spring and lower in summer and autumn, a pattern familiar from many studies of Chinese air quality and driven by a combination of increased heating and combustion emissions during the cold months, stagnant meteorological conditions that trap pollutants near the surface, and chemical processes that favor particle formation in cool, humid air. The spatial pattern was equally distinctive: concentrations were lower in the west and higher in the east, and lower in the south and higher in the north. Within this regional gradient, Henan Province stood out with substantially higher pollution levels and a broader extent of high-value areas than its southern neighbors Hubei and Hunan.

One of the study’s most technically rigorous components was its spatial autocorrelation analysis, which quantified whether PM2.5 concentrations at neighboring locations tend to cluster together more than would be expected by chance. The answer was a resounding yes. Annual global Moran’s I values — a standard statistic ranging from negative one to positive one, where positive values indicate clustering of similar values — ranged from 0.5237 to 0.7376 across the study years, with all corresponding p-values falling below 0.001. In practical terms, this means that polluted areas were reliably surrounded by other polluted areas, and clean areas by clean ones, a finding with direct implications for policy because it suggests that pollution control is most effective when coordinated across administrative boundaries rather than pursued province by province.

The clustering analysis also pinpointed where the pollution hotspots were concentrated. High-value clusters were found mainly in Henan Province, as well as around the major metropolitan centers of Wuhan in Hubei and Changsha in Hunan. Meanwhile, the centroid migration model revealed that the overall center of gravity of PM2.5 concentrations remained near central Hubei throughout the study period, with interannual displacements ranging from 2.86 to 24.37 kilometers. Notably, the authors took a careful and conservative stance on interpreting these shifts: most of the annual displacements did not exceed the noise thresholds they established, and the results, they write, do not support a persistent and robust southwestward migration of the pollution centroid. This kind of methodological restraint matters, because claims about shifting pollution patterns can influence where regulators direct their attention and resources.

Having mapped the pollution, the team then turned to the question of what it costs in human terms. Using the BenMAP framework, they estimated premature deaths attributable to PM2.5 exposure in Henan Province across three categories: deaths from all causes, deaths from respiratory diseases, and deaths from cardiovascular diseases. The results showed that these attributable premature deaths generally declined over the 2017 to 2023 assessment window, though the decline was not smooth — fluctuations occurred along the way, and a slight rebound was observed in the later stage of the study period. This rebound is a cautionary signal that progress on air quality, while real, remains fragile and can be reversed by economic activity, meteorological variability, or lapses in enforcement.

The economic analysis added a layer of nuance that is often missing from air quality studies. As PM2.5 concentrations decreased, both the health burden and the associated economic losses were alleviated — a straightforward win for pollution control. However, the researchers found that the growth in economic benefits from pollution control was less pronounced than the improvement in health benefits. The reason lies in the continued increase in the value of a statistical life, the monetary figure used to assign economic weight to avoided premature deaths. As societies grow wealthier, each statistical life saved is valued more highly, which means that the same health improvement translates into a larger economic valuation over time — but also that the monetary arithmetic of pollution control shifts in ways that complicate simple cost-benefit comparisons across years.

The findings arrive at a moment when China’s air quality trajectory has become a subject of intense international interest, with national clean air actions launched since 2013 credited with substantial reductions in particulate concentrations across the country. This study’s contribution is to show how those national trends play out in a specific transitional region, where the east-west and north-south gradients of pollution reflect the interplay of industrial structure, terrain, and pollutant transport. The pronounced clustering of high values in Henan and around major cities underscores that even within a single region, the exposure landscape is highly uneven, and that residents of certain provinces and metropolitan areas bear a disproportionate share of the health burden.

For policymakers, the study offers a template for precision air pollution control. The authors argue that their results support targeted health risk prevention in key provinces and the formulation of differentiated emission reduction policies across Central China — in other words, that Henan’s more severe situation calls for more aggressive intervention than may be warranted in Hubei or Hunan, while the strong spatial autocorrelation of pollution argues for coordinated regional strategies rather than fragmented local efforts. The slight rebound in attributable deaths in the later study period serves as a reminder that sustained progress requires sustained attention. As the value of a statistical life continues to rise alongside economic development, the economic case for cleaner air will only strengthen, even as the hardest-won reductions in PM2.5 become increasingly difficult to achieve. What this research makes clear is that the tools now exist to track pollution, quantify its toll, and direct resources where they can save the most lives — the remaining challenge is political and administrative coordination across a region where the air, quite literally, does not respect provincial borders.

Subject of Research: Spatiotemporal evolution of PM2.5 pollution and its health and economic effects in Central China

Article Title: Assessment of the spatiotemporal evolution of PM2.5 and its health and economic effects in Central China based on spatial statistics and BenMAP

Article References: Liu, M., Yang, Y., & Wang, S. (2026). Assessment of the spatiotemporal evolution of PM2.5 and its health and economic effects in Central China based on spatial statistics and BenMAP. Environmental Monitoring and Assessment, 198(10), Article 1070. https://doi.org/10.1007/s10661-026-15911-z

Image Credits: AI Generated

DOI: 10.1007/s10661-026-15911-z

Keywords: PM2.5, air pollution, Central China, Henan Province, spatial autocorrelation, BenMAP, premature mortality, health impact assessment, economic losses, value of statistical life, TAP dataset, emission control policy