Chemical characterization and source apportionment of PM₁₀ and PM_2.5 were carried out for two different elevations (lower elevation (LE) ~ 5–10 m and higher elevation (HE) ~ 30–45 m) at four different locations representing urban background, city center, upwind, and downwind of the Delhi city during January 2017–March 2017. The 24-h average PM₁₀ and PM_2.5 concentrations were varied between 135.2–258.7 and 79.3–120.9 µg/m³, respectively. The average PM₁₀ and PM_2.5 concentrations were found significantly higher at LE than HE. The PM samples were analyzed for ions, elements and carbonaceous matter (EC/OC), and their concentrations (except S, V, As, Ni, Sb, Sr, Ga, elements associated with industrial combustion activities, and NO₃⁻, attributed to high nitrate formation potential at HE) were observed higher in LE than HE at all the study locations. The chemical mass balance model was applied to quantify the source contributions to PM₁₀ and PM_2.5 mass at two different elevations. Model identified vehicular emission (diesel, PM₁₀ ~ 8.8–21.7% and PM_2.5 ~ 10.5–24.4% and gasoline, PM₁₀ ~ 4.8–15.6% and PM_2.5 ~ 6.7–14.8%), industrial residual oil combustion (PM₁₀ ~ 8.8–23.5% and PM_2.5 ~ 3.2–10.4%), road dust (PM₁₀ ~ 13.6–22.3% and PM_2.5 ~ 8.8–17.8%), soil dust (PM₁₀ ~ 33.8–41.1% and PM_2.5 ~ 5.8–8.3%), secondary nitrate (PM₁₀ ~ 6.1–16.2% and PM_2.5 ~ 13.4–20.2%), secondary sulfate (PM₁₀ ~ 7.1–12.3% and PM_2.5 ~ 10.6–16.7%), and biomass burning (PM₁₀ ~ 6.8–21.8% and PM_2.5 ~ 4.9–38.7%) as the main sources of PM₁₀ and PM_2.5 mass at both the elevations at all the study sites. The contribution of industrial residual oil combustion, vehicular emission, and secondary nitrate to PM₁₀ and PM_2.5 mass was found relatively higher in HE than LE. Results also revealed that biomass burning contributed significantly to PM pollution in the outskirts of Delhi than inside the city. Further, potential source contribution function analysis revealed that there may not be a long-range transport of PM emitted from biomass burning in the upwind region of Delhi during the study period. Shifting to Indian BS VI vehicles and fuel, switching to cleaner fuel in slum households, strict compliance on industries, and regular vacuum cleaning of roads will reduce the severe air quality problem in Delhi.

PM ₁₀和 PM _{2.5 的}化学特征和来源解析是在代表城市背景、城市背景的四个不同位置的两个不同海拔（低海拔 (LE) ~ 5-10 m 和高海拔 (HE) ~ 30-45 m）进行的。 2017 年 1 月至 2017 年 3 月期间德里市的中心、上风和下风。24 小时平均 PM ₁₀和 PM _2.5浓度分别在 135.2-258.7 和 79.3-120.9 µg/m ³之间变化。平均 PM ₁₀和 PM _2.5发现 LE 的浓度显着高于 HE。分析了 PM 样品的离子、元素和含碳物质 (EC/OC) 及其浓度（S、V、As、Ni、Sb、Sr、Ga、与工业燃烧活动相关的元素和 NO ₃ ^-除外，归因于在 HE 处观察到高硝酸盐形成潜力）在 LE 中高于 HE 在所有研究位置。应用化学质量平衡模型来量化源对两个不同高度的PM ₁₀和 PM _2.5质量的贡献。模型识别车辆排放（柴油，PM ₁₀  ~ 8.8–21.7% 和 PM _2.5  ~ 10.5–24.4% 和汽油，PM ₁₀  ~ 4.8–15.6% 和 PM _2.5 ~ 6.7–14.8%）、工业残油燃烧（PM ₁₀  ~ 8.8–23.5% 和 PM _2.5  ~ 3.2–10.4%）、道路扬尘（PM ₁₀  ~ 13.6–22.3% 和 PM _2.5  ~ 8.8–17.8%）、土壤粉尘（PM ₁₀  ~ 33.8–41.1% 和 PM _2.5  ~ 5.8–8.3%）、二次硝酸盐（PM ₁₀  ~ 6.1–16.2% 和 PM _2.5  ~ 13.4–20.2%）、二次硫酸盐（PM ₁₀  ~ 7.1–12.3% 和PM _2.5  ~ 10.6–16.7%）和生物质燃烧（PM ₁₀  ~ 6.8–21.8% 和 PM _2.5  ~ 4.9–38.7%）是 PM ₁₀和 PM _2.5的主要来源所有研究地点的两个海拔处的质量。发现工业残油燃烧、车辆排放和二次硝酸盐对 PM ₁₀和 PM _2.5质量的贡献在 HE 中高于 LE。结果还显示，与城市内部相比，德里郊区的生物质燃烧对 PM 污染的贡献显着。此外，潜在源贡献函数分析表明，在研究期间，德里上风区的生物质燃烧排放的 PM 可能没有长距离传输。转向印度 BS VI 车辆和燃料、贫民窟家庭改用更清洁的燃料、严格遵守工业法规以及定期对道路进行真空清洁，将减少德里严重的空气质量问题。