Identifying and quantifying PM2.5 pollution episodes with a fusion method of moving window technique and constrained Positive Matrix Factorization

Huang, Chun‐Sheng; Liao, Hsin‐Tzu; Lu, Shao-Hao; Chan, Chang-Chuan; Wu, Chang‐Fu

doi:10.1016/j.envpol.2022.120382

Cited by 6 publications

(1 citation statement)

References 61 publications

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“…Therefore, neither NAC nor NAC EW can effectively reveal the spatially varying indicator weights and thus cannot precisely assess the local soil NAC level. The moving window is a local statistical analysis method that can capture indicators' local spatial information well (Song et al, 2021;Huang et al, 2022). If the moving window method can be combined with the entropy weighting method, it is possible to reveal the indicators variation within the local area and further reveal the spatially varying indicator weights in soil NAC assessment.…”

Section: Introductionmentioning

confidence: 99%

Improving assessment quality of soil natural attenuation capacity at the point and regional scales

Guang,

Qu,

Liu

et al. 2023

Environ Monit Assess

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Soil natural attenuation capacity (NAC) is an important ecosystem service that maintains a clean environment for organisms in the soil, which in turn supports other services. However, spatially varying indicator weights were rarely considered in the traditionally-used soil NAC assessment model (e.g., ecosystemservice performance model) at the point scale. Moreover, in the spatial simulation of soil NAC, the traditionally-used geostatistical models were usually susceptible to spatial outliers and ignore valuable auxiliary information (e.g., land-use types). This study rst proposed a novel soil NAC assessment method based on the ecosystem-service performance model and moving window-entropy weight method (MW-EW) (NAC MW−EW ). Next, NAC MW−EW was used to assess soil NAC in the study area in Guixi City, China, and further compared with the traditionally-used NAC and NAC EW . Then, robust sequential Gaussian simulation with land-use types (RSGS-LU) was established for the spatial simulation of NAC MW−EW and compared with the traditionally-used SGS, SGS-LU, and RSGS.Last, soil NAC's spatial uncertainty was evaluated based on the 1000 simulations generated by RSGS-LU. The results showed that: (i) MW-EW effectively revealed the spatially varying indicator weights but EW couldn't; (ii) NAC MW−EW obtained more reasonable results than NAC and NAC EW ; (iii) RSGS-LU (RMSE = 0.118, MAE = 0.089) generated higher spatial simulation accuracy than SGS-LU (RMSE = 0.123, MAE = 0.092), RSGS (RMSE = 0.132, MAE = 0.096), and SGS (RMSE = 0.135, MAE = 0.099); (iv) the relatively high (P[NAC MW−EW (u) > 0.57] ≥ 0.95) and low (P[NAC MW−EW (u) > 0.57] ≤ 0.05) threshold-exceeding probability areas were mainly located in the south and east part of the study area, respectively. It is concluded that the proposed methods were effective tools for soil NAC assessment at the point and regional scales, and the results provided accurate spatial decision support for soil ecosystem service management.

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Section: Introductionmentioning

confidence: 99%