A novel, reusable ozone filter design for the monitoring of biogenic volatile organic compounds using sorbent tubes and multi-tube samplers was evaluated. The ozone filters proved high efficiency in retaining high recovery rates across different environmentally relevant levels of relative humidity and ozone concentrations while safeguarding the sorbent material in both laboratory and field experiments. The filter design has the advantage of not requiring additional equipment or regular checks.

A method is introduced to expand the observational capability of a diode-laser-based lidar system. This method allows the lidar transmitter to change the laser pulse characteristics from one shot to the next. We use this capability to lower the minimum altitude of observation and to observe clouds with higher range resolution.

We introduce a new cloud retrieval algorithm using the O₂–O₂ absorption band at 477 nm to generate harmonized cloud datasets from OMI and TROPOMI. The algorithm improves upon the OMI O₂–O₂ operational cloud algorithm in several aspects. The new approach improves consistency in cloud parameters and NO₂​ retrievals between two sensors.

This paper examines the seasonal variation of column formaldehyde (HCHO), NO₂, and O₃ as retrieved from satellite Ozone Monitoring Instrument (OMI) and ground-based Pandora spectrometer observations. Both OMI and Pandora show that HCHO has a strong seasonal dependence. The daily amount of NO₂ pollution is underestimated by the OMI satellite observations. Pandora O₃ measurements have been successfully compared with hourly satellite measurements from the Earth Polychromatic Imaging Camera (EPIC).

Current infrared satellite sounders offer high spectral but low spatial resolution, limiting their ability to quantify atmospheric ammonia (NH₃) at small scales. Through simulations and analysis of real data, we show that NH₃ can be measured effectively from spectra with reduced resolution, either in a contiguous spectral range or in select well-chosen bands. This approach opens possibilities for the development of smaller dedicated instruments for observing NH₃ at high spatial resolution.

This work demonstrates a simple approach for using mass flow meters connected to rigid chambers for measuring gas emissions rates in situations the meter cannot be attached directly, such as orphan oil and gas wells. This paper shows the results of performance testing, demonstrates common sources of uncertainty, and provides suggestions for how to use the approach to generate the best quality data. The findings can be used by researchers, the petroleum industry, regulators, and carbon markets.

Chemical ionization mass spectrometers used for trace gas analysis can be operated under various conditions, complicating quantitative comparisons. We evaluate sensitivity dependence on a relatively few key instrument parameters and show that when these are held constant, consistent performance is achieved. We show that the maximum sensitivity of a given flow tube reactor across various reagent ion chemistries is a constant, which aids in the quantification of compounds lacking analytical standards.

Our research improves satellite-based precipitation monitoring by using deep learning to reconstruct radar observations from passive microwave radiances. Active radar is costly, so we focus on a more accessible approach. Using data from the Fengyun-3G satellite, we successfully tracked severe weather like Typhoon Khanun and heavy rainfall in Beijing in 2023. This method enhances global precipitation data and helps better understand extreme weather.

Fuel-operated auxiliary heaters are used in vehicles to provide extra heating to improve passenger comfort and vehicle functionality in cold climates. Currently heater emissions are not regulated as part of vehicle emissions, so this research was done to assess harmful gaseous and airborne particle emissions from them. Heaters were found to be major source of particles, especially when particles formed after combustion were accounted for, and large carbon monoxide emissions were also observed.

Uncertainty estimation for Global Navigation Satellite System (GNSS) radio occultation (RO) soundings in the planetary boundary layer (PBL) depends on the algorithms used to process the RO data. We compare the refractivity retrievals from three RO processing centers – each with their own retrieval algorithm – in the PBL, finding a strong underestimation of refractivity in regions with the strongest refractivity gradients, especially in Jet Propulsion Laboratory (JPL) processing, as well as areas of weak overestimation of refractivity near the poles.

The Qinghai–Tibetan Plateau is a key system that impacts the global carbon balance. This study presents the greenhouse gas (GHG) mole fraction measurement campaign in May 2022 at Mt. Qomolangma station, including ground-based remote sensing and in situ measurements. The GHG measurements are carried out in this region for the first time and used for satellite validation.

We conducted this study to assess the accuracy of airborne measurements of wind, temperature, and humidity, essential for understanding atmospheric processes. Using data from NASA's ACTIVATE campaign, we compared measurements from the Turbulent Air Motion Measurement System (TAMMS) and diode laser hygrometer (DLH) aboard a Falcon aircraft with dropsondes from a King Air, matching data points based on location and time using statistical methods. The study showed strong agreement, confirming the reliability of these methods for advancing climate models.

Air pollution affects climate and health, but accurately measuring how pollutants mix in the atmosphere remains challenging. In Chiang Mai, Thailand, we developed a new light detection and ranging (lidar)-based method to better distinguish key atmospheric layers by incorporating temperature-based adjustments. This improves accuracy, especially at night, compared to traditional techniques. Our findings help refine air quality models and provide better data for tackling pollution in Southeast Asia.

The World Health Organization (WHO) warns of ground-level ozone problems in urban areas and recommends increased monitoring. This paper shows that low-cost sensors coupled with artificial intelligence are an excellent alternative.

This study presents our advanced methods to qualitatively detect ship-related nitrogen dioxide (NO₂) signals in TROPOMI satellite data. By applying filtering techniques, we identify numerous global shipping routes, including previously undetected ones, as well as emissions from offshore platforms. Additionally, we compare the filtered satellite data with high-pass-filtered CAMS global model data to estimate the differences between observed and modeled NO₂ emissions.

For the balloon-borne detection of particles (diameter 0.4 < D_p < 40 µm), the Universal Cloud and Aerosol Sounding System (UCASS) was used, whose sample flow is determined by GPS-measured ascent rates. In flights, actual UCASS sample flows rarely match the ascent rates. Errors are minimised by real-time detection of the UCASS flows, e.g. by implementing a thermal flow sensor (TFS) within the UCASS. The TFSs were tested in flight and calibrated at up to 10 m s⁻¹ and at variable angles of attack.

To ensure robust use of measurement-based approaches to estimate methane emissions from individual sites, it is important to validate the accuracy of the methods used in the field. By using co-emitted carbon dioxide, we evaluate the performance of one such quantification method at liquefied natural gas terminals. We further demonstrate the potential for a more efficient quantification approach via tracer correlation by considering the ratio of methane to carbon dioxide concentrations.

Humidity observations are crucial for an accurate weather forecast. We propose a new way to measure humidity by measuring how radio signals from commercial aircraft are refracted by the atmosphere. Humidity affects the refractive index of air, allowing its presence to be detected. With thousands of flights in the airspace over the United Kingdom every day, there is the potential for a large increase in the number of humidity measurements for use in weather forecasting models.

In this study, the primary instrument carried by the satellite MATS is compared to the OSIRIS instrument on board the Odin satellite. A total of 36 close approaches between December 2022 and February 2023 were identified and analysed. The comparison reveals that the two instruments have good structural agreement and that MATS detects a signal that is ~20 % stronger than what is measured by OSIRIS.

A novel disaggregation algorithm for commercial microwave links (CMLs), named CLEAR (CML Segments with Equal Amounts of Rain), is proposed. CLEAR utilizes a multiplicative random cascade generator to control the splitting of link segments. The evaluation performed both on virtual and real CML data shows that CLEAR outperforms a commonly used benchmark algorithm. Moreover, the stochastic nature of CLEAR allows it to represent uncertainty as an ensemble of rain rate distributions along CML paths.

This study explores the potential of a hypothetical spaceborne radar to observe water vapor within clouds.

We measured carbon dioxide (CO₂) and methane (CH₄) over South India using a ground-based spectrometer and compared the results with satellite data from GOSAT (Greenhouse gases Observing SATellite; Japan) and OCO-2 (Orbiting Carbon Observatory-2; NASA, USA). The satellite data have good accuracy and precision for estimating emissions. A computer model showed that changes in methane levels are influenced more by background levels than by local sources.

This study, part of my 2024 postdoctoral research, explores an all-fiber coupled laser heterodyne radiometer (LHR) for CO₂ measurements using a tunable diode laser. The LHR employs balanced detection to measure tropospheric CO₂ column concentrations. Simulations are validated against previously validated instruments. This work enhances greenhouse gas monitoring and supports campaigns for emissions studies and satellite validation.