Browsing by Author "Dr. Wajih Ur Rehman"

Now showing 1 - 3 of 3

Source Apportionment of PM2.5 in Lahore: Chemical Mass Balance Modeling and Inter-Study variability Assessment
(Library Information Services, CUI Lahore, 2025) Muhammad Nabeel Khan; FA23-RNE-04/; Dr. Wajih Ur Rehman
Elevated concentrations of fine particulate matter (PM₂.₅) pose a serious public health risk in Lahore due to their ability to penetrate deep into the respiratory system. This thesis applies the U.S. Environmental Protection Agency Chemical Mass Balance receptor model (CMB v8.2) to apportion PM₂.₅ sources using three independent, chemically speciated datasets from Lahore: a winter campaign (February 2019), a year-long monthly study (2019), and paired summer–winter measurements (2022). U.S. EPA source profiles for gasoline and diesel vehicles, biomass burning, coal combustion, road/soil dust, industrial emissions, and secondary Sulfate and Nitrate were employed. Model performance was evaluated using standard diagnostics (R², χ², percent mass explained, t-statistics, and residuals). The winter 2019 analysis showed good model performance (R² = 0.72, χ² = 3.8), with dominant contributions from petrol vehicles (101 µg·m⁻³) and biomass burning (81 µg·m⁻³), along with substantial secondary Nitrate and Sulfate. Monthly CMB runs for 2019 yielded R² values between 0.73 and 0.87, indicating stable performance across seasons. Diesel vehicle emissions peaked during late autumn and winter, while petrol vehicle contributions increased in warmer months. Coal and industrial combustion, together with secondary inorganic aerosols, contributed persistently throughout the year. Seasonal analysis of 2022 data showed PM₂.₅ increasing from approximately 130 µg·m⁻³ in summer to 303 µg·m⁻³ in winter, with acceptable mass closure and statistically significant source contributions. Across all datasets, combustion-related sources—vehicular emissions, biomass burning, and coal combustion—along with seasonally enhanced secondary inorganic aerosols were the dominant contributors to PM₂.₅ in Lahore, while dust sources were more influential during pre-monsoon periods. These results provide higher source resolution than previous PMF/PCA studies and support targeted mitigation strategies focused on vehicle emissions, combustion sources, and precursor gas control.
Source Apportionment of PM2.5 in Lahore: Chemical Mass Balance Modeling and Inter-Study variability Assessment
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2025) Muhammad Nabeel Khan; CIIT/FA23-RNE-04/LHR; Dr. Wajih Ur Rehman; LHR TP 10051
Elevated concentrations of fine particulate matter (PM₂.₅) pose a serious public health risk in Lahore due to their ability to penetrate deep into the respiratory system. This thesis applies the U.S. Environmental Protection Agency Chemical Mass Balance receptor model (CMB v8.2) to apportion PM₂.₅ sources using three independent, chemically speciated datasets from Lahore: a winter campaign (February 2019), a year-long monthly study (2019), and paired summer–winter measurements (2022). U.S. EPA source profiles for gasoline and diesel vehicles, biomass burning, coal combustion, road/soil dust, industrial emissions, and secondary Sulfate and Nitrate were employed. Model performance was evaluated using standard diagnostics (R², χ², percent mass explained, t-statistics, and residuals). The winter 2019 analysis showed good model performance (R² = 0.72, χ² = 3.8), with dominant contributions from petrol vehicles (101 µg·m⁻³) and biomass burning (81 µg·m⁻³), along with substantial secondary Nitrate and Sulfate. Monthly CMB runs for 2019 yielded R² values between 0.73 and 0.87, indicating stable performance across seasons. Diesel vehicle emissions peaked during late autumn and winter, while petrol vehicle contributions increased in warmer months. Coal and industrial combustion, together with secondary inorganic aerosols, contributed persistently throughout the year. Seasonal analysis of 2022 data showed PM₂.₅ increasing from approximately 130 µg·m⁻³ in summer to 303 µg·m⁻³ in winter, with acceptable mass closure and statistically significant source contributions. Across all datasets, combustion-related sources—vehicular emissions, biomass burning, and coal combustion—along with seasonally enhanced secondary inorganic aerosols were the dominant contributors to PM₂.₅ in Lahore, while dust sources were more influential during pre-monsoon periods. These results provide higher source resolution than previous PMF/PCA studies and support targeted mitigation strategies focused on vehicle emissions, combustion sources, and precursor gas control.
Source Apportionment of PM2.5 in Lahore: Chemical Mass Balance Modeling and Inter-Study variability Assessment
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2025) Muhammad Nabeel Khan; CIIT/FA23-RNE-04/LHR; Dr. Wajih Ur Rehman; LHR TP 10010
Elevated concentrations of fine particulate matter (PM₂.₅) pose a serious public health risk in Lahore due to their ability to penetrate deep into the respiratory system. This thesis applies the U.S. Environmental Protection Agency Chemical Mass Balance receptor model (CMB v8.2) to apportion PM₂.₅ sources using three independent, chemically speciated datasets from Lahore: a winter campaign (February 2019), a year-long monthly study (2019), and paired summer–winter measurements (2022). U.S. EPA source profiles for gasoline and diesel vehicles, biomass burning, coal combustion, road/soil dust, industrial emissions, and secondary Sulfate and Nitrate were employed. Model performance was evaluated using standard diagnostics (R², χ², percent mass explained, t-statistics, and residuals). The winter 2019 analysis showed good model performance (R² = 0.72, χ² = 3.8), with dominant contributions from petrol vehicles (101 µg·m⁻³) and biomass burning (81 µg·m⁻³), along with substantial secondary Nitrate and Sulfate. Monthly CMB runs for 2019 yielded R² values between 0.73 and 0.87, indicating stable performance across seasons. Diesel vehicle emissions peaked during late autumn and winter, while petrol vehicle contributions increased in warmer months. Coal and industrial combustion, together with secondary inorganic aerosols, contributed persistently throughout the year. Seasonal analysis of 2022 data showed PM₂.₅ increasing from approximately 130 µg·m⁻³ in summer to 303 µg·m⁻³ in winter, with acceptable mass closure and statistically significant source contributions. Across all datasets, combustion-related sources—vehicular emissions, biomass burning, and coal combustion—along with seasonally enhanced secondary inorganic aerosols were the dominant contributors to PM₂.₅ in Lahore, while dust sources were more influential during pre-monsoon periods. These results provide higher source resolution than previous PMF/PCA studies and support targeted mitigation strategies focused on vehicle emissions, combustion sources, and precursor gas control