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Table 4 Comparison of multiple linear regression in two different monitoring sites

From: Particulate matter (PM10) prediction based on multiple linear regression: a case study in Chiang Rai Province, Thailand

Chiang Rai (Station 65)

Chiang Rai (Station 73)

Ya = 46.9 + 56.6x1 + 1.3x2 + 0.3x3 + 0.7x4

Ya = 22.1 + 45.2x1 + 1.1x2 + 0.4x4

Ys = 1486.0 + 116.8x1 + 0.7x2 + 0.6x3 − 0.9x4 − 1.5x5

Ys =  − 87.3 + 54.4x1 + 1.5x2 + 2.6x3

Yr = 67.0 + 9.3x1 + 0.4x2 + 0.03x3 − 0.3x4 − 0.03x5

Yr =  − 124.0 − 6.11x1 + 4.4x3 + 0.5x4

Yw = 11.4 + 10.7x1 + 1.5x2 + 0.7x3 − 0.2x4 + 0.03x5

Yw =  − 33.9 + 58.4x1 + 1.9x2

  1. Here, Y = The concentration of PM10 (a =annual, s = summer, r = rainy, and w = winter), x1 = CO, x2 = O3, x3 = Temperature, x4 = Relative humidity and x5 = Air Pressure
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