The Air Quality Monitoring System is the main source of particulate matter data in the Mexico City (MC) and Metropolitan Area (MA). The monitoring system's gradual development has produced variable coverage data throughout space and time, making difficult to use it for epidemiological studies. The WHO suggests to use the PM2.5-PM10 ratio (PMR) for PM2.5 estimation when only PM10 data is available. The aim was to estimate PM2.5 concentrations in the MC and MA using the PMR for 2003 to 2016, in order to increase space-time coverage data for epidemiological studies. The monitoring stations (MS) that measured simultaneously PM2.5 and PM10 were identified year by year. For each, the hourly PMR were estimated. Then, monthly and annual hourly PMR average were obtained. The hourly PM2.5 missing values in this MS were imputed by dividing the PM10 hourly data available between the annual hourly PMR average. In the MS that measured only PM10, PM2.5 monthly data was imputed using the monthly PMR average considering the location of the MS. The PM2.5 annual averages for each MS, for MC and MA were estimated. Pearson's correlation analysis and statistical significance tests were carried out between imputed and measured data. Procedures were done using R 3.4.1. and Stata 14. Higher annual hourly PMR average was observed in MC than in MA (54 vs 50%, p <0.000), and similar to the PMR suggested by the WHO (50%). PM2.5 was estimated for 101 MS which measured PM10 only, and for 5 MS which measured both. High concordance was observed between hourly data measured vs estimated for MS located in MC (R2=0.83) and in MA (R2=0.73). Most PM2.5 annual averages were no statistically different (data imputed included vs only measured data). Our results show that the PMR is an adequate method to robustly estimate space-time PM2.5 when only PM10 data is available. This study establishes a precedent for other urban areas where monitoring systems are growing and information of PM2.5 might not be available.
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