近年環境的劇烈變遷引起人們對空氣汙染的高度關注，在管制空氣汙染排放量時，也應重視空氣汙染對不同人口特性族群造成的影響。本研究使用2007年至2017年細懸浮微粒濃度和臭氧濃度資料、綜合所得總額資料與各鄉、鎮、市或區的單一年齡人口數資料，採用普通最小平方估計法、固定效果估計法、吉尼係數、絕對負擔與比例負擔來探討空氣汙染物與所得及人口之間的關係，並研究空氣汙染不均等及不同人口特性承受的汙染暴露量。 研究結果顯示普通最小平方法會使係數出現偏誤，因此使用固定效果估計法較佳，而所得項對細懸浮微粒濃度與臭氧濃度皆為顯著負影響，所得平方項皆為顯著正影響。人口結構部分，15歲以下人口對細懸浮微粒濃度與臭氧濃度皆為顯著正影響；65歲以上人口對細懸浮微粒濃度為顯著負影響，對臭氧濃度則為顯著正影響。 根據吉尼係數顯示，細懸浮微粒的汙染不均等現象越趨嚴重，臭氧濃度則越趨均等，且15歲以下人口例較高的地區遭受相對較低的細懸浮微粒濃度暴露；65歲以上人口比例較高的地區遭受相對較高的細懸浮微粒濃度暴露與相對較低的臭氧濃度暴露；低所得族群遭受相對較高的細懸浮微粒濃度與臭氧濃度暴露；高所得族群遭受相對較低的細懸浮微粒濃度暴露與相對較高的臭氧濃度暴露。;Air pollution has drawn great attention since the dramatic environmental changes in recent years. We should pay attention to the impact of air pollution on different population characteristics, while controlling air pollution emissions. This study used PM2.5 and O3 data, the total income data, and data on population by age in each town or township from 2007 to 2017. Applying OLS, fixed effects, Gini coefficient, AB and PB to clarify the relationship between air pollutants, income and population. Also consider air pollution inequality and the amount of pollution exposure sustained by different population characteristics. The results show that fixed effects is better since OLS will cause the coefficient to be biased. The income has a significant negative effect while the income_sq has a significant positive effect on both PM2.5 and O3. In the demographic structure, the population under 15 has a significant positive effect on both PM2.5 and O3; the population over 65 has a significant negative effect on PM2.5 and a significant positive effect on O3. According to Gini coefficient, the pollution inequality of PM2.5 becomes more serious, and O3 becomes more equal. Areas with a high proportion people under 15 expose in relatively lower PM2.5; areas with a high proportion people over 65 expose in relatively higher PM2.5 and relatively lower O3; low income groups expose in relatively higher PM2.5 and O3 whereas high income groups expose in relatively lower PM2.5 and relatively higher O3.
