Is the Recent Decrease in Belgian Air Pollution Concentration Levels Due to Meteorology or to Emission Reductions?

Abstract

Recent years have shown significant decrease in concentrations levels of particulate matter (PM₁₀) and nitrogen dioxide (NO₂) in Belgium. For ozone (O₃), no such trend is found. Recent years, however, did not feature many periods with unfavourable meteorological dispersion conditions, casting some ambiguity on the underlying reasons for the decrease. This study tries to separate the impact of weather effects from emission reductions in the long-term trend. We build a statistical model explaining the daily averaged concentrations based on 32 meteorological parameters, the day of the week, the month of the year and the year itself, for the period 2004–2014. The 32 meteorological parameters are those considered to train the neural network prediction model OVL. Many of these meteo variables have only a small predictability and are intercorrelated with each other. Therefore, only those meteo parameters are used that have a significant impact on concentration levels. This procedure is applied for the complete time series and for each air quality monitoring location separately. In order to avoid overfitting, the same analysis is done, restricted to the data of even-numbered years, and the regression is then applied to the odd-numbered years. It is shown that the statistical parameters remain reasonably constant, which proves that the amount of overfitting is not significant. The results show, on average over all measurement locations, a range of yearly meteorological effects of 1.9 µg/m³ for NO₂, 3.1 µg/m³ for PM₁₀ and 2.7 µg/m³ for O₃. Meteorology combined with the residuals of the statistical fit show a range of 1.2 µg/m³ for NO₂, 2.9 µg/m³ for PM₁₀ and 4.4 µg/m³ for O₃. Finally, the long-term trend shows a range of 5.3 µg/m³ for NO₂, 11.1 µg/m³ for PM₁₀ and 2.3 µg/m³ for O₃, with clearly decreasing trends for NO₂ and PM₁₀, and an oscillating trend for O₃. Differences between rural, urban background, urban and industrial stations exist but are rather small. We can conclude that the major trend in air pollution (Belgium) is a long-term trend, linked to emission changes, and it can be expected that the concentration decreases of the last years will not suddenly disappear in the near future given unchanged policy. Furthermore, it can be concluded that emission reductions at the local, regional, European and worldwide scale are the dominant factors explaining the improvement of air quality.

Questions and Answers

Questioner: Paul Makar

Question: I was wondering whether clouds, cloud rainfall were included in the set of meteo variables, since they would influence O₃ via photolysis rates?

Answer: The meteovariables (day of the week and month of the year are added later) that were taken into account are shown in the table below:

P1	2-m temperature
P2	30-m temperature
P3	10-m wind velocity
P4	10-m wind direction
P5	30-m wind velocity
P6	30-m wind direction
P7	Boundary layer height (corresponding to critical bulk Richardson = 0.5)
P8	Height of the layer where the transport length < 100 m
P9	Transport length at the first level (about 25-m height)
P10	Mean transport length in the layer 0–50 m (from the surface)
P11	Mean transport length in the layer 0–100 m
P12	Total cloud cover (range0 to 1)
P13	Low cloud cover (range0 to 1)
P14	Medium cloud cover (range0 to 1)
P15	High cloud cover (range0 to 1)
P16	Horizontal transport in the boundary layer
P17	Height of the layer where the transport length < 200 m
P18	Height of the layer where the transport length < 300 m
P19	Height of the layer where the transport length < 500 m
P20	Height of the layer where the transport length < 1000 m
P21	“S parameter” of Bultynck-Malet classification (multiplied by a factor 1000)
P22	“λ parameter” of Bultynck-Malet classificationLambda = LOG10(106 * ABS(S))
P23	Relative humidity (%) at 300-m height
P24	Relative humidity in the layer 0–50 m
P25	Relative humidity at 100-m height (not layer 0–100 m!)
P26	Wind velocity at 50-m height
P27	Wind velocity at 100-m height
P28	Wind velocity at 200-m height
P29	Wind velocity at 300-m height
P30	Wind velocity at 500-m height
P31	Wind velocity at 750-m height
P32	Wind velocity at 1000-m height

Cloud cover is thus taken directly into account, precipitation only with related variables (such as relative humidity).

Questioner: Tony Dore

Question: For analysis of trends, consistency in monitoring techniques is important. Your air concentrations showed more annual variability at the start of the time series. Has there been any change in quality control during the monitoring period?

Answer: There have been changes between monitoring techniques, and thus probably to associated quality control. However, at least for NO₂ and PM₁₀, these changes cannot account for the large trends that have been found in the results.