Characteristics of PM10 Level during Haze Events in Malaysia Based on Quantile Regression Method
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Areas
2.2. Air Pollutant Dataset
2.3. Trajectory Analysis
2.4. Measure of Association using Pearson Correlation
- r = correlation coefficient
- xi = values of the x-variable in a sample
- = mean of values of the x-variable
- yi = values of the y-variable in a sample
- = mean of values of the y-variable
2.5. Prediction Models
2.5.1. Multiple Linear Regression (MLR)
2.5.2. Quantile Regression (QR)
2.5.3. Performance Indicator
- where
- n = total number of hourly measurements of particular site;
- = predicted values of one set of hourly monitoring record;
- = observed values of one set of hourly monitoring record;
- = mean of the predicted values of one set of hourly monitoring record;
- = mean of the observed values of one set of hourly monitoring record;
- = standard deviation of the predicted values;
- = standard deviation of the observed values of one set.
3. Results and Discussion
3.1. Variation of PM10 Level during Haze Event
3.2. Association of PM10 Level with Other Air Pollutants and Weather Parameter during HPE
3.3. Predictive Models and Their Performances
3.4. Comparing the Effectiveness of the Quantile Regression (QR) with Other Predictive Models
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Location | Station | Coordinates | Background of Study Areas |
---|---|---|---|
Petaling Jaya | Bandar Utama Primary School | 3.1311° N 101.6076° E | Heavy traffic particulars during the morning hour Industrial area and housing |
Melaka | Bukit Rambai Secondary School | 2.2587° N 102.1729° E | Agriculture Residential area and housing |
Pasir Gudang | Pasir Gudang 2 Secondary School | 1.4703° N 103.8956° E | Heavy industrial areas Commercial land Transportation and logistics |
Air Quality and Weather Parameters | Symbol | Unit |
---|---|---|
Particulate matter | PM10 | µg/m3 |
Ground-level ozone | O3 | ppm |
Nitrogen oxides | NOx | ppm |
Nitrogen dioxides | NO2 | ppm |
Sulfur dioxides | SO2 | ppm |
Carbon monoxide | CO | ppm |
Temperature | T | °C |
Relative humidity | RH | % |
Wind Speed | WS | km/h |
Value of r | Description |
---|---|
0.0–0.3 | Weak |
0.3–0.6 | Moderate |
0.6–1.0 | Strong |
Performance Indicators | Equation | Description |
---|---|---|
Mean absolute error (MAE) | When the value of MAE is closer to zero, it indicates better method. | |
Root mean square deviation (RMSE) | When the value of RMSE is closer to zero, it indicates better method. | |
Coefficient of determination (R2) | When the value of R2 is closer to one, it indicates better method. | |
Index of agreement (IA) | When the value of IA is closer to one, it indicates better method. |
Place/ Year | Pasir Gudang | Melaka | Petaling Jaya | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1997 | 2005 | 2013 | 2015 | 1997 | 2005 | 2013 | 2015 | 1997 | 2005 | 2013 | 2015 | ||
Total value, N | Valid | 8631 | 8715 | 8745 | 8710 | 8337 | 8669 | 8669 | 8759 | 8222 | 8727 | 8659 | 8591 |
Missing | 129 | 45 | 15 | 50 | 423 | 91 | 91 | 1 | 538 | 33 | 101 | 169 | |
Mean | 47.7 | 46.59 | 51 | 64.8 | 71.7 | 83.3 | 79.2 | 69.7 | 69.4 | 64.3 | 48.4 | 60.5 | |
Median | 33.0 | 44.0 | 45.0 | 54.0 | 46.0 | 78.0 | 72.0 | 58.0 | 49.0 | 56.0 | 43.0 | 49.0 | |
Standard deviation | 39.9 | 13.7 | 38.4 | 36.1 | 61.6 | 27.4 | 42.8 | 41.5 | 55.1 | 40.7 | 29.3 | 50.1 | |
Minimum | 11 | 19 | 10 | 27 | 13.0 | 29 | 32 | 24 | 20 | 20 | 17 | 5 | |
Maximum | 268 | 116 | 462 | 351 | 415.0 | 268 | 577 | 338 | 393 | 494 | 372 | 472 |
Area | Selected Parameter |
---|---|
Petaling Jaya | CO Temperature |
Melaka | CO RH SO2 Temperature |
Pasir Gudang | CO RH Temperature SO2 |
Area | Method | Quantile | Prediction Day | PM10 | WS | T | RH | NOx | SO2 | NO2 | O3 | CO |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Pasir Gudang | MLR | Mean | PM10+24 | 0.791 | −0.097 | 0.228 | −0.036 | 0.015 | 0.041 | 0.107 | 0.006 | 1.701 |
PM10+48 | 0.610 | −0.181 | 0.788 | −0.006 | −0.069 | 0.213 | −0.139 | −0.071 | 0.800 | |||
PM10+72 | 0.482 | −0.352 | 1.428 | 0.095 | −0.104 | 0.213 | −0.037 | −0.100 | −3.572 | |||
QR | 0.25 | PM10+24 | 0.471 | −0.115 | −0.111 | −0.118 | 0.021 | 0.206 | 0.072 | −0.078 | −0.409 | |
PM10+48 | 0.272 | 0.057 | 0.282 | −0.033 | 0.170 | 0.54 | 0.002 | −0.089 | −1.271 | |||
PM10+72 | 0.169 | 0.009 | 0.574 | 0.030 | 0.025 | 0.428 | −0.100 | −0.139 | −0.810 | |||
0.50 | PM10+24 | 0.679 | −0.112 | 0.154 | −0.035 | −0.058 | 0.212 | −0.034 | −0.067 | −0.537 | ||
PM10+48 | 0.529 | −0.193 | 0.424 | −0.029 | −0.100 | 0.355 | 0.084 | −0.045 | −2.021 | |||
PM10+72 | 0.429 | −0.163 | 0.673 | 0.025 | −0.083 | 0.391 | −0.025 | −0.027 | −3.761 | |||
0.75 | PM10+24 | 0.772 | −0.173 | 0.732 | 0.082 | −0.015 | 0.270 | −0.018 | 0.067 | 0.683 | ||
PM10+48 | 0.704 | −0.243 | 0.687 | 0.037 | −0.203 | 0.216 | 0.093 | 0.036 | −1.092 | |||
PM10+72 | 0.580 | −0.183 | 0.860 | 0.089 | −0.139 | 0.284 | 0.031 | 0.094 | −3.843 | |||
Pearson–QR | 0.25 | PM10+24 | 0.585 | −0.108 | −0.086 | 0.125 | −0.682 | |||||
PM10+48 | 0.385 | 0.263 | −0.065 | 0.499 | −1.373 | |||||||
PM10+72 | 0.310 | 0.586 | 0.021 | 0.320 | −1.958 | |||||||
0.50 | PM10+24 | 0.678 | 0.177 | −0.010 | 0.229 | −0.487 | ||||||
PM10+48 | 0.533 | 0.415 | 0.012 | 0.370 | −1.981 | |||||||
PM10+72 | 0.429 | 0.682 | 0.061 | 0.404 | −3.580 | |||||||
0.75 | PM10+24 | 0.771 | 0.700 | 0.110 | 0.319 | 1.011 | ||||||
PM10+48 | 0.702 | 0.639 | 0.076 | 0.260 | −0.601 | |||||||
PM10+72 | 0.587 | 0.855 | 0.129 | 0.314 | −3.896 | |||||||
Melaka | MLR | Mean | PM10+24 | 0.771 | –0.275 | –0.004 | –0.195 | 100.596 | 29.012 | –53.149 | 17.090 | 0.483 |
PM10+48 | 0.663 | –0.221 | –0.121 | –0.207 | 63.996 | 204.937 | –91.668 | 18.432 | 1.021 | |||
PM10+72 | 0.594 | –0.205 | –0.009 | –0.198 | 63.783 | 208.651 | 144.208 | 41.880 | 0.737 | |||
QR | 0.25 | PM10+24 | 0.549 | 0.037 | –0.695 | –0.193 | 21.083 | −52.16 | 151.800 | 61.620 | 0.531 | |
PM10+48 | 0.430 | 0.084 | –1.023 | –0.245 | –5.578 | –143.956 | 159.496 | 50.740 | –0.477 | |||
PM10+72 | 0.325 | 0.170 | –0.897 | –0.218 | –23.562 | –60.339 | 246.029 | 57.959 | –0.376 | |||
0.50 | PM10+24 | 0.766 | –0.132 | –0.201 | –0.108 | 4.391 | –7.639 | 105.473 | 23.218 | 1.313 | ||
PM10+48 | 0.578 | –0.105 | –0.342 | –0.118 | 23.58 | –48.032 | 159.496 | 50.74 | 0.477 | |||
PM10+72 | 0.581 | –0.250 | –0.391 | –0.117 | 13.265 | –79.94 | 132.925 | 24.141 | –0.655 | |||
0.75 | PM10+24 | 0.860 | 0.218 | 0.227 | 0.068 | 48.006 | 173.937 | 42.777 | 22.264 | 8.331 | ||
PM10+48 | 0.778 | –0.166 | 0.134 | –0.088 | 33.346 | 86.984 | 15.279 | –17.932 | 6.667 | |||
PM10+72 | 0.732 | –0.05 | –0.135 | –0.113 | 14.284 | 162.531 | 45.815 | –18.58 | 6.259 | |||
Pearson–QR | 0.25 | PM10+24 | 0.567 | –0.685 | –0.201 | –29.625 | 0.823 | |||||
PM10+48 | 0.447 | –0.932 | –0.249 | –112.707 | –0.340 | |||||||
PM10+72 | 0.857 | 0.196 | –0.068 | –172.322 | 9.725 | |||||||
0.50 | PM10+24 | 0.776 | –0.135 | –0.099 | 36.943 | 1.824 | ||||||
PM10+48 | 0.583 | –0.296 | –0.105 | –14.280 | 1.820 | |||||||
PM10+72 | 0.774 | 0.004 | –0.087 | 108.901 | 7.559 | |||||||
0.75 | PM10+24 | 0.857 | 0.196 | –0.068 | –172.322 | 9.725 | ||||||
PM10+48 | 0.774 | 0.004 | –0.087 | 108.901 | 7.559 | |||||||
PM10+72 | 0.731 | –0.254 | –0.110 | 164.423 | 6.914 | |||||||
Petaling Jaya | MLR | Mean | PM10+24 | 0.599 | –0.675 | –1.106 | –0.434 | –0.065 | –0.163 | 0.552 | 0.147 | 3.867 |
PM10+48 | 0.457 | –0.68 | –1.506 | –0.536 | 0.119 | 0.367 | 0.360 | 0.082 | –0.11 | |||
PM10+72 | 0.353 | –0.281 | –1.846 | –0.563 | 0.129 | 0.811 | 0.725 | 0.01 | –1.647 | |||
QR | 0.25 | PM10+24 | 0.365 | –0.790 | –0.705 | –0.273 | 0.060 | 0.659 | 0.624 | –0.196 | 1.516 | |
PM10+48 | 0.240 | –0.654 | –0.796 | –0.292 | –0.048 | 1.071 | 0.433 | –0.200 | –0.520 | |||
PM10+72 | 0.141 | –0.467 | –0.925 | –0.279 | 0.004 | 1.250 | 0.563 | –0.076 | –1.194 | |||
0.50 | PM10+24 | 0.526 | –0.749 | –0.746 | –0.299 | –0.090 | 0.173 | 0.724 | –0.009 | 1.477 | ||
PM10+48 | 0.358 | –0.436 | –1.277 | –0.415 | –0.031 | 0.475 | 0.276 | –0.068 | 0.178 | |||
PM10+72 | 0.288 | –0.355 | –1.356 | –0.397 | –0.001 | 0.737 | 0.313 | 0.084 | –1.410 | |||
0.75 | PM10+24 | 0.802 | –0.524 | –1.254 | –0.419 | –0.117 | –0.590 | 0.460 | 0.233 | –0.033 | ||
PM10+48 | 0.631 | –0.181 | –2.025 | –0.609 | 0.050 | –0.484 | 1.159 | 0.111 | –0.903 | |||
PM10+72 | 0.497 | –0.085 | –2.053 | –0.621 | 0.01 | –0.011 | 0.293 | 0.041 | –1.515 | |||
Pearson–QR | 0.25 | PM10+24 | 0.381 | 0.143 | 2.856 | |||||||
PM10+48 | 0.261 | 0.172 | 1.331 | |||||||||
PM10+72 | 0.173 | 0.151 | 0.698 | |||||||||
0.50 | PM10+24 | 0.554 | 0.176 | 1.863 | ||||||||
PM10+48 | 0.386 | 0.166 | 0.329 | |||||||||
PM10+72 | 0.322 | 0.095 | 0.995 | |||||||||
0.75 | PM10+24 | 0.810 | 0.193 | 0.596 | ||||||||
PM10+48 | 0.643 | 0.321 | 2.342 | |||||||||
PM10+72 | 0.514 | 0.202 | 2.444 |
Area | Method | Time | MAE | RMSE | R2 | IA | |
---|---|---|---|---|---|---|---|
Pasir Gudang | MLR | PM10+24 | 5.11 | 8.90 | 0.96 | 0.98 | |
PM10+48 | 7.83 | 13.61 | 0.89 | 0.94 | |||
PM10+72 | 9.86 | 17.03 | 0.82 | 0.90 | |||
QR | 0.25 | PM10+24 | 10.43 | 16.90 | 0.95 | 0.90 | |
0.50 | 5.25 | 9.89 | 0.96 | 0.97 | |||
0.75 | 8.58 | 10.33 | 0.96 | 0.98 | |||
0.25 | PM10+48 | 12.98 | 22.01 | 0.88 | 0.82 | ||
0.50 | 7.73 | 14.37 | 0.89 | 0.93 | |||
0.75 | 10.17 | 13.43 | 0.90 | 0.96 | |||
0.25 | PM10+72 | 14.12 | 24.52 | 0.80 | 0.76 | ||
0.50 | 9.53 | 17.63 | 0.81 | 0.89 | |||
0.75 | 12.00 | 16.42 | 0.82 | 0.93 | |||
Pearson–QR | 0.25 | PM10+24 | 10.92 | 17.64 | 0.94 | 0.90 | |
0.50 | 7.34 | 13.29 | 0.96 | 0.95 | |||
0.75 | 8.86 | 12.75 | 0.91 | 0.96 | |||
0.25 | PM10+48 | 15.06 | 25.05 | 0.84 | 0.73 | ||
0.50 | 10.96 | 20.12 | 0.87 | 0.86 | |||
0.75 | 10.78 | 16.00 | 0.86 | 0.93 | |||
0.25 | PM10+72 | 29.56 | 39.25 | 0.84 | 0.55 | ||
0.50 | 13.71 | 25.65 | 0.69 | 0.73 | |||
0.75 | 13.37 | 21.64 | 0.70 | 0.84 | |||
Melaka | MLR | PM10+24 | 8.93 | 14.43 | 0.93 | 0.9656 | |
PM10+48 | 13.05 | 20.85 | 0.85 | 0.9162 | |||
PM10+72 | 16.48 | 25.55 | 0.76 | 0.8576 | |||
QR | 0.25 | PM10+24 | 16.56 | 25.77 | 0.93 | 0.87 | |
0.50 | 9.50 | 14.47 | 0.94 | 0.96 | |||
0.75 | 13.05 | 16.38 | 0.93 | 0.96 | |||
0.25 | PM10+48 | 45.39 | 52.93 | 0.81 | 0.60 | ||
0.50 | 12.77 | 22.27 | 0.84 | 0.90 | |||
0.75 | 16.67 | 21.65 | 0.85 | 0.93 | |||
0.25 | PM10+72 | 22.71 | 37.02 | 0.74 | 0.67 | ||
0.50 | 15.24 | 26.36 | 0.76 | 0.84 | |||
0.75 | 19.25 | 25.56 | 0.77 | 0.89 | |||
Pearson–QR | 0.25 | PM10+24 | 13.48 | 22.28 | 0.90 | 0.91 | |
0.50 | 7.12 | 12.43 | 0.85 | 0.98 | |||
0.75 | 9.73 | 12.26 | 0.96 | 0.98 | |||
0.25 | PM10+48 | 17.13 | 29.03 | 0.77 | 0.82 | ||
0.50 | 11.92 | 21.43 | 0.89 | 0.91 | |||
0.75 | 12.90 | 17.34 | 0.90 | 0.96 | |||
0.25 | PM10+72 | 19.39 | 34.08 | 0.68 | 0.71 | ||
0.50 | 13.14 | 23.62 | 0.82 | 0.89 | |||
0.75 | 15.45 | 21.53 | 0.83 | 0.93 | |||
Petaling Jaya | MLR | PM10+24 | 10.72 | 19.45 | 0.85 | 0.93 | |
PM10+48 | 14.68 | 25.88 | 0.74 | 0.84 | |||
PM10+72 | 24.41 | 38.00 | 0.34 | 0.70 | |||
QR | 0.25 | PM10+24 | 17.94 | 32.48 | 0.83 | 0.73 | |
0.50 | 11.08 | 21.47 | 0.85 | 0.90 | |||
0.75 | 14.44 | 19.93 | 0.85 | 0.94 | |||
0.25 | PM10+48 | 21.35 | 38.83 | 0.73 | 0.56 | ||
0.50 | 15.20 | 29.12 | 0.74 | 0.77 | |||
0.75 | 17.42 | 24.87 | 0.74 | 0.89 | |||
0.25 | PM10+72 | 23.23 | 42.74 | 0.26 | 0.45 | ||
0.50 | 16.82 | 32.34 | 0.64 | 0.69 | |||
0.75 | 19.29 | 28.51 | 0.64 | 0.82 | |||
Pearson–QR | 0.25 | PM10+24 | 19.27 | 34.20 | 0.86 | 0.73 | |
0.50 | 12.55 | 24.11 | 0.87 | 0.88 | |||
0.75 | 13.92 | 19.30 | 0.87 | 0.94 | |||
0.25 | PM10+48 | 21.66 | 40.12 | 0.75 | 0.58 | ||
0.50 | 16.20 | 31.96 | 0.76 | 0.73 | |||
0.75 | 17.69 | 26.17 | 0.76 | 0.87 | |||
0.25 | PM10+72 | 23.29 | 44.00 | 0.67 | 0.45 | ||
0.50 | 17.86 | 35.22 | 0.67 | 0.64 | |||
0.75 | 20.13 | 30.70 | 0.67 | 0.79 |
Area | Prediction Day | Best Method |
---|---|---|
Petaling Jaya | PM10+24 | Pearson–QR (p = 0.75) |
PM10+48 | QR (p = 0.75) | |
PM10+72 | QR (p = 0.75) | |
Melaka | PM10+24 | Pearson–QR (p = 0.75) |
PM10+48 | Pearson–QR (p = 0.75) | |
PM10+72 | Pearson–QR (p = 0.75) | |
Pasir Gudang | PM10+24 | MLR |
PM10+48 | MLR | |
PM10+72 | QR (p = 0.75) |
Area | Method | Dependent Variable | Prediction Time | Description |
---|---|---|---|---|
Urban area in Malaysia [17] |
| PM10 |
|
|
Petaling Jaya [25] |
| PM10 |
|
|
Peninsular Malaysia [47] |
| PM10 |
|
|
Sichuan, China [48] |
| PM10PM2.5 |
|
|
China [49] |
| PM2.5 |
|
|
Malaysia [50] |
| PM10 |
|
|
West coast of peninsular Malaysia [This study] |
| PM10 |
|
|
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© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Redzuan, S.N.; Noor, N.M.; Rahim, N.A.A.A.; Jafri, I.A.M.; Baidrulhisham, S.E.; Ul-Saufie, A.Z.; Sandu, A.V.; Vizureanu, P.; Zainol, M.R.R.M.A.; Deák, G. Characteristics of PM10 Level during Haze Events in Malaysia Based on Quantile Regression Method. Atmosphere 2023, 14, 407. https://doi.org/10.3390/atmos14020407
Redzuan SN, Noor NM, Rahim NAAA, Jafri IAM, Baidrulhisham SE, Ul-Saufie AZ, Sandu AV, Vizureanu P, Zainol MRRMA, Deák G. Characteristics of PM10 Level during Haze Events in Malaysia Based on Quantile Regression Method. Atmosphere. 2023; 14(2):407. https://doi.org/10.3390/atmos14020407
Chicago/Turabian StyleRedzuan, Siti Nadhirah, Norazian Mohamed Noor, Nur Alis Addiena A. Rahim, Izzati Amani Mohd Jafri, Syaza Ezzati Baidrulhisham, Ahmad Zia Ul-Saufie, Andrei Victor Sandu, Petrica Vizureanu, Mohd Remy Rozainy Mohd Arif Zainol, and György Deák. 2023. "Characteristics of PM10 Level during Haze Events in Malaysia Based on Quantile Regression Method" Atmosphere 14, no. 2: 407. https://doi.org/10.3390/atmos14020407