Research & Projects

Research 1: Greenhouse Gas Emissions and Climate Change

Research 2: Urban Air Pollution and Atmospheric Chemistry

Research 3: Air Pollution: A Global Threat to Health

Research 4: New Techniques in Air Monitoring

Research 1: Greenhouse Gas Emissions and Climate Change

Using CYGNSS-based Inundation Maps to Address Major Gaps in Representing Tropical Wetland CH4 Emissions

Wetlands are the largest and most uncertain natural source of atmospheric methane (CH4). Accurate representation of wetland CH4 emissions remains challenging, particularly in tropics, where wet/dry season dynamics lead to large seasonal and interannually variations. However, the current state of the science fails to capture any significant seasonality in inundation extent, likely due to the inability of observe inundation through clouds and forest canopy.

Objectives

Develop new high-resolution inundation maps based on the Cyclone Global Navigation Satellite System (CYGNSS) observations.
Evaluate whether the CYGNSS driven inundation maps improve wetland CH4 emissions.
Determine the relative role tropical wetlands play in recent atmospheric CH4 surge.

Results

CYGNSS inundation maps predict significantly larger water fractions than classical products, leading to higher estimates of tropical wetland CH4 emissions.
Despite a downward interannual trend of global wetland emissions between 2019 and 2022 (-9.6% to -11.9%), the Sudd wetland surged CH4 emissions by 46-62%.

Fig. Comparison of monthly CH4 emissions among WetCHARTs 36 ensembles in Sudd wetland.

Fig. Monthly anomaly in inundation extent in Sudd wetland during 2019-2022.

Fig. Averaged fractional water in tropical regions derived from CYGNSS observations.

Research 2: Urban Air Pollution and Atmospheric Chemistry

sources, transpot pathway, and formation meachanism of air pollution

Air pollution arises from various sources, including industrial emissions, vehicle exhaust, agricultural activities, and natural events. These sources release pollutants like fine particle (PM2.5), nitrogen oxides (NOx), and volatile organic compounds (VOCs) into the atmosphere. Once emitted, these pollutants follow diverse transport pathways, dispersing through the air via wind. Formation mechanisms vary; for instance, photochemical reactions between sunlight and emissions generate secondary pollutants like ozone (O3). Understanding these sources, transport pathways, and formation mechanisms is crucial for mitigating and managing the impacts of air pollution on human health and the environment.

We integrated diverse field study observations of air pollutants with a range of modeling tools, such as receptor models, 0-dimensional box models, 3-dimensional chemical transport models, and machine learning techniques. This amalgamation aimed to elucidate the origins of urban air pollution and understand the mechanisms driving its formation on both regional and global scales.

Objectives

Identify the sources of air pollutants like PM2.5, VOCs, NOx, etc.
Determine the transport pathways of air pollution and reveal areas with high emissions.
Understand the complex mechanisms involved in air pollution formation, particularly the impact of meteorological parameters, emission sources, and chemical reactions in this process.

Results

The sources of urban air pollution differ across regions and nations due to socioeconomic factors, landscapes, weather patterns, and human activities.
Prioritizing the regulation of secondary air pollution, such as O3 pollution, should focus significantly on controlling its precursors.
Validating modeling outcomes across various methods holds crucial importance in the decision-making process.

Fig. Global annual mean surface PM2.5 (upper two panels) and O3 (lower two panels) concentrations for diesel and gasoline emission sectors for the years of 2000, 2005, 2010, and 2015. (Xiong et al., 2022b)

Fig. The O3 isopleths in Southeast Michigan (SEMI) on high O3 days in response to changes in (a) NOx and VOC concentrations and (b) HCHO and NO2 concentrations. (Xiong et al., 2023)

Fig. The weighted PSCF maps for the PMF-derived VOCs sources in Port Moody in Western Canada. (Xiong et al., 2020a)

Fig. 72 h air mass backward trajectories analysis (at 500 m height) for different seasons in Wuhan using hierarchical clustering method. (Xiong et al., 2017)

Research 3: Air Pollution: A Global Threat to Health

global gasoline and diesel emissions and Associated health burdens for 2000–2015

Global economic development and urbanization during the past two decades have driven the increases in demand of personal and commercial vehicle fleets, especially in developing countries, which has likely resulted in changes in year-to-year vehicle tailpipe emissions associated with aerosols and trace gases. However, long-term trends of impacts of global gasoline and diesel emissions on air quality and human health are not clear.

Objectives

Estimate which country/region had the largest gasoline & diesel-related emissions.
Evaluate the long-term impact of these emissions on surface PM2.5 and O3 concentrations.
Quantify global health burden (i.e., premature deaths) associated with exposure to gasoline and diesel-emitted PM2.5 and O3.

Results

PM2.5 pollution dominated (86.7-88.5%) global Annual Premature Deaths (APDs), compared with O3 pollution.
China, India, and rest of Asia had the highest health burdens associated with gasoline and diesel emissions (70% and 84% of global PM2.5- and O3-induced premature deaths).
Diesel and gasoline emissions created health-effect disparities between the developed and developing countries, which are likely to aggravate afterwards. (Xiong et al., 2022b)

Fig. PM2.5- and O3-induced Annual Premature Death (APD) attributable to the diesel (a), (c) and gasoline (b), (d) emission sectors in each region for the years of 2000, 2005, 2010, and 2015, respectively. Percentages in the bar plots are the absolute change rates of APDs. (Xiong et al., 2022b)

Fig. Global annual premature deaths associated with PM2.5 and O3 exposure attributable to the diesel and gasoline emission sectors for the years of (a) 2000, (b) 2005, (c) 2010, and (d) 2015, respectively. (Xiong et al., 2022b)

Health Risk of Volatile organic compounds in western Canada

A number of epidemiological evidence have directly linked adverse health outcomes with exposure to hazardous volatile organic compounds (VOCs). For example, exposure to benzene can lead to acute leukemia and probably other hematological cancers.

Traditionally, environmental authorities make regulatory policies for controlling VOC pollution based on the mitigation of dominant VOC sources. However, the emission from each VOC source has a unique combination of VOC species of different toxicities. Without quantitatively assessing the health risk associated with each source, the effectiveness of the mitigation policy could be undermined.

Objectives

Develop a new health risk-oriented source apportionment method that can provide quantitative health risk assessment and source-specific mitigation strategies for hazardous VOCs.
Apply this new method to assess exposure risk of VOC sources in eight Canadian cities.

Results

Anthropogenic sources were responsible for 56.3–73.8% of cancer risks across eight Canadian cities .
Substantial environmental and health benefits could be achieved via reducing the ambient levels of benzene and 1,3-butadiene by 39.3–75.7 and 14–69.3%, respectively .
Mitigating emissions from fuel combustion (by 31.3–54.1%), traffic source (3.0–36.8%), and other anthropogenic sources (5.3–20.1%) in Western Canada are necessary to protect public health. (Xiong et al., 2022a)

Fig. Relative contribution of VOC sources to the integrated inhalation cancer risk (ICR) at nine sites in Western Canada. (Xiong et al., 2022a)

Fig. Carcinogenic risks associated with inhalation exposure to (a) hazardous VOCs in Western Canada and (b) each site during 2013-2018. (Xiong et al., 2022a)

Research 4: New Techniques in Air Monitoring

Evaluation and Calibartion of a low-cost particle sensor using machine-learning methods

Particle sensing technology has shown great potential for monitoring particulate matter (PM) with very few temporal and spatial restrictions because of its low cost, compact size, and easy operation. However, the performance of low-cost sensors for PM monitoring in ambient conditions has not been thoroughly evaluated. Monitoring results by low-cost sensors are often questionable.

Objectives

Assemble low-cost PM sensors, co-located them with a reference instrument in ambient conditions, and evaluate the performance of sensors.
Calibrate sensors' readings using different machine learning (ML) methods.

Results

Large overestimations by the low-cost sensor before calibration were observed particularly when ambient PM2.5 levels were higher than 10 µg m−3 .
The calibration by the feed neural network (NN) forward had the smallest RMSE of 3.91 in the test dataset compared to the calibrations by SLR (4.91), MLR (4.65), and XGBoost (4.19).
A feedforward NN is a promising method to address the poor performance of low-cost sensors for PM2.5 monitoring. (Si and Xiong et al., 2020)

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