Extrapolation of human health damage cost from particulate matter 2.5 exposure in Chiang Mai province using grey model

Abstract

The continuous air pollution crisis, especially fine particulate matter (PM2.5), poses a significant challenge annually, with the Chiang Mai province being identified as one of the areas with the highest levels of air pollution worldwide. The health implications of PM2.5 exposure spanning from immediate to long-term effect, causing various diseases including cardiovascular diseases, asthma, chronic bronchitis, chronic obstructive pulmonary disease, ischemic heart disease, stroke, and lung cancer. Moreover, a relationship between rising PM2.5 levels and the worsening of health risks, including increased disease incidence and mortality. Additionally, impact of air pollution related human health also carries economic significance such as the expenditures at diminishing the risk of diseases from pollution exposure, and the costs associated with treating related diseases. Regarding the continuous PM2.5 issue, which inquiring to resolve, and the consistent exposure of the population to pollution levels that exceed air quality standards annually. It is essential to develop strategies for both the prevention and management of immediate impacts. The shortage of action or strategies to tackle the health effects of PM2.5 highlights the critical need for an economic impact assessment. Such an assessment is imperative to realize the effects on public health, facilitate accurate forecasts, and develop effective strategies for prompt and efficient responses to the impact of PM2.5 pollution. This study aims to develop a model that forecasts PM2.5 concentration trends utilizing the gray model, aimed at predicting future PM2.5 levels. The economic assessment of the health impacts occurring from PM2.5 exposure is also included in this study. Additionally, the purpose is to establish an extrapolation model to estimate the cost of damages resulting from heightened PM2.5 levels. This study focuses on Chiang Mai Province, utilizing secondary data sourced from the province. PM2.5 concentration measurements were obtained from the DustBoy monitoring system. Health impact data, including the number of hospital visits and treatment costs for various diseases, were collected from the Chiang Mai Provincial Public Health Office. The research encompassed an investigation into all causes of respiratory and cerebrovascular diseases, conjunctivitis, dermatitis, and lung cancer, categorizing these conditions according to the ICD-10 classification. The findings of this study indicate that PM2.5 exposure incurs substantial health-related economic costs in Chiang Mai province, totaling about 2,989 million baht each year. The breakdown of damage cost due to various health issues reveals all-cause respiratory diseases costing 2,449-million-baht, all-cause cardiovascular diseases at 343-million-baht, conjunctivitis at 95-million-baht, dermatitis also at 85 million baht, and lung cancer at 16 million baht annually. These figures highlight the significant economic burden of medical treatments necessitated by PM2.5 pollution. Additionally, the study finds that each 1 µg/m3 increase in PM2.5 concentration above the Pollution Control Department's recommended standard of 15 µg/m3 results in an additional economic cost of 149 million baht, emphasizing the financial implications of incremental increases in PM2.5 pollution. Moreover, the outcomes of the PM2.5 exposure effects analysis were illustrated through a spatial distribution map, clearly identifying risk areas within each district of Chiang Mai province. This approach enhances the understanding of pollution impact across different areas. This research offers valuable insights and information for public health and policymakers, aiding in the strategic allocation of resources, including healthcare personnel, medical equipment, and medications, to effectively manage health issues. Additionally, it supports the identification and prioritization of high-risk areas, enabling informed decision-making on the allocation of budgets to cover expenses during periods of rapid increases in PM2.5 dust concentration levels.