Search

Previous research established that chlorine can be photochemically activated in the pres- ence of acidic iron(III) chloride. In this thesis, the photolysis mechanism of iron(III) chloride is investigated computationally and experimentally. Three Visual MinteQ mod- els were built to model the behavior of iron(III) chlorides under different conditions such as pH, iron concentration, temperature, and the effect of other compounds found in seawater. FeCl2+, FeCl+2 , FeCl3, and FeCl−4 were investigated computationally at the CAM-B3LYP/6-311++G(d,p) level of theory. Transition state analysis was used to de- termine the energy dissociation thresholds, and UV-Vis spectra were calculated with time-dependent density functional theory using the polarizable continuum model for sol- vent effects. The absorbance rates were calculated in vacuum, seawater, and water. The methane depleting photolysis mechanism of FeCl3·6H2O was investigated experimentally for the first time under narrow wavelength ranges. The experiments were performed un- der low humidity and carbon dioxide conditions in a nitrogen carrier gas. Nine optical windows with medians of 408, 436, 457, 477, 500, 523, 547, 581, and 601 nm were used. The Visual MinteQ models show that temperature, sulfates, and pH play an important role for the aqueous speciation of iron(III) chlorides. Iron(III) chlorides and iron sulfates dominate from pH 1 to 4, and iron(III) hydroxides dominate above pH 5, which is in good agreement with the literature. FeCl+2 was the most dominant iron(III) chloride species, with a maximum of 51% to 65%, depending on the composition of the aqueous phase. A competition between sulphate and iron chloride species was established, which affects the speciation of FeCl+2 by up to 40%. According to the calculations, all four iron(III) chloride species absorb in the visible spectrum, where the results for seawater and water

Low-cost Particulate Matter (PM) sensors offer an excellent opportunity to improve our knowledge about this type of pollution. Their size and cost, which support multi-node network deployment, along with their temporal resolution, enable them to report fine spatio-temporal resolution for a given area. These sensors have known issues across performance metrics. Generally, the literature focuses on the PM mass concentration reported by these sensors, but some models of sensors also report Particle Number Concentrations (PNCs) segregated into different PM size ranges. In this study, eight units each of Alphasense OPC-R1, Plantower PMS5003 and Sensirion SPS30 have been exposed, under controlled conditions, to short-lived peaks of PM generated using two different combustion sources of PM, exposing the sensors’ to different particle size distributions to quantify and better understand the low-cost sensors performance across a range of relevant environmental ranges. The PNCs reported by the sensors were analysed to characterise sensor-reported particle size distribution, to determine whether sensor-reported PNCs can follow the transient variations of PM observed by the reference instruments and to determine the relative impact of different variables on the performances of the sensors. This study shows that the Alphasense OPC-R1 reported at least five size ranges independently from each other, that the Sensirion SPS30 reported two size ranges independently from each other and that all the size ranges reported by the Plantower PMS5003 were not independent of each other. It demonstrates that all sensors tested here could track the fine temporal variation of PNCs, that the Alphasense OPC-R1 could closely follow the variations of size distribution between the two sources of PM, and it shows that particle size distribution and composition are more impactful on sensor measurements than relative humidity.

Carbon dioxide is a waste product of human metabolism that is unwanted in the indoor atmosphere. Here we test advanced materials that could be used to pump away carbon dioxide and thereby improve indoor air quality. Metal-organic framework (MOF) structures have a variety of properties that make them attractive for direct air capture (DAC) of CO2 . In this study, Mg 2 (dobpdc4- = 4,4-dioxidobiphenyl-3,3-dicarboxylate) and m-2-mMg2 (dobpdc) were evaluated for their ability to adsorb and desorb CO 2 at ambient atmospheric conditions via a thermal swing. The Mg2 (dobpdc) sample did not show appreciable interaction with CO 2 in contrast to the diamine-appended version. The molar occupancy of CO 2 on the active sites of m-2-m-Mg 2 (dobpdc) (m-2-m = N,Ndimethylethylenediamine) during adsorption and desorption was in the range of 5.6–11.8%. These experiments showed the rapid ad- and de-sorption of CO 2 by the MOF. Relative humidity was seen to be an important variable and the performance of the tested structures decreased slightly after several cycles of use., Carbon dioxide is a waste product of human metabolism that is unwanted in the indoor atmosphere. Here we test advanced materials that could be used to pump away carbon dioxide and thereby improve indoor air quality. Metal-organic framework (MOF) structures have a variety of properties that make them attractive for direct air capture (DAC) of CO 2 . In this study, Mg 2 (dobpdc4- = 4,4-dioxidobiphenyl-3,3-dicarboxylate) and m-2-m- Mg 2 (dobpdc) were evaluated for their ability to adsorb and desorb CO 2 at ambient atmospheric conditions via a thermal swing. The Mg 2 (dobpdc) sample did not show appreciable interaction with CO 2 in contrast to the diamine-appended version. The molar occupancy of CO 2 on the active sites of m-2-m-Mg 2 (dobpdc) (m-2-m = N,N- dimethylethylenediamine) during adsorption and desorption was in the range of 5.6–11.8%. These experiments showed the rapid ad- and de-sorption of CO 2 by the MOF. Relative humidity was seen to be an important variable and the performance of the tested structures decreased slightly after several cycles of use.

Air pollution exhibits hyper-local variation, especially near emissions sources. In addition to people's time-activity patterns, this variation is the most critical element determining exposure. Pollution exposure is time-activity- and path-dependent, with specific behaviours such as mode of commuting and time spent near a roadway or in a park playing a decisive role. Compared to conventional air pollution monitoring stations, nodes containing low-cost air pollution sensors can be deployed with very high density. In this study, a network of 18 nodes using low-cost air pollution sensors was deployed in Newcastle-under-Lyme, Staffordshire, UK, in June 2020. Each node measured a range of species including nitrogen dioxide (NO2), ozone (O-3), and particulate matter (PM2.5 and PM10); this study focuses on NO2 and PM2.5 over a 1-year period from 1 August 2020 to 1 October 2021. A simple and effective temperature, scale, and offset correction was able to overcome data quality issues associated with temperature bias in the NO2 readings. In its recent update, the World Health Organization (WHO) dramatically reduced annual exposure limit values from 40 to 10 mu g m(-3) for NO2 and from 10 to 5 mu g m(-3) for PM2.5. We found that the average annual mean NO2 concentration for the network was 17.5 mu g m(-3) and 8.1 mu g m(-3) for PM2.5. While in exceedance of the WHO guideline levels, these average concentrations do not exceed legally binding UK/EU standards. The network average NO2 concentration was 12.5 mu g m(-3) higher than values reported by a nearby regional air quality monitoring station, showing the critical importance of monitoring close to sources before pollution is diluted. We demonstrate how data from a low-cost air pollution sensor network can reveal insights into patterns of air pollution and help determine whether sources are local or non-local. With spectral analysis, we investigate the variation of the pollution levels and identify typical periodicities. Bo

In this thesis, the isotope effect on the photolysis of formaldehyde is investigated experimentally and computationally. Using a multi-pass cell, the pressure dependence of the relative rates have been determined for the first time for H213CO and H2C18O, as well as for DCHO and D2CO. The mechanism for the photolysis of formaldehyde was investigated computationally, with the use of unimolecular and master equations methods and the coupling between the excited state manifolds. Reaction rate coefficients were calculated for the decomposition of the S0, S1 and T1 states using Rice-Ramsperger-Kassel-Marcus (RRKM) theory. The rates of intersystem crossing (ISC) and internal conversion (IC) were calculated using RRKM theory and the spin-orbit coupling constants of crossing points found in the literature. The determined rates were used to build two Kintecus models, one for determining the relative rates of the isotopologoues at various altitudes and one for investigating the isotope effect on the quantum yields at sea-level. The experimentally determined relative rates were in good agreement with the literature at low pressures and they were found to be reproducible. The relative rate of H213CO was found to be approximately twice as large as H2C18O and the same was observed for D2CO compared to DCHO. The computationally determined total rates clearly indicated a pressure dependency on the isotope effect, with the largest kinetic isotope effects (KIEs) at high pressures, as for the experimental findings. The KIEs of the RRKM rates remained mostly the same at varying temperatures. The largest KIE was found for the rate of IC, which was calculated to be 53.74 for D2CO at 285 nm, while the KIE for the total rate was 15.71. This was followed by the rate of ISC, which had a maximum KIE of 24.39 for D2CO at 285 nm and 7.86 for the total rate. The theoretical relative rates were slightly larger than the experimentally determined values in this project, but slightly smaller

Accurate calibration of low-cost gas sensors is, at present, a time consuming and difficult process. Laboratory calibration and field calibration methods are currently used, but laboratory calibration is generally discounted due to poor transferability, and field methods requiring several weeks are standard. The Enhanced Ambient Sensing Environment (EASE) method described in this article, is a hybrid of the two, combining the advantages of a laboratory calibration with the increased accuracy of a field calibration. It involves calibrating sensors inside a duct, drawing in ambient air with similar properties to the site where the sensors will operate, but with the added feature of being able to artificially increases or decrease pollutant levels, thus condensing the calibration period required. Calibration of both metal-oxide (MOx) and electrochemical (EC) gas sensors for the measurement of NO2 and O-3 (0-120 ppb) were conducted in EASE, laboratory and field environments, and validated in field environments. The EC sensors performed marginally better than MOx sensors for NO2 measurement and sensor performance was similar for O-3 measurement, but the EC sensor nodes had less node inter-node variability and were more robust. For both gasses and sensor types the EASE calibration outperformed the laboratory calibration, and performed similarly to or better than the field calibration, whilst requiring a fraction of the time.

Airborne particulate matter (PM) exposure has been identified as a key environmental risk factor, associated especially with diseases of the respiratory and cardiovascular system and with almost 9 million premature deaths per year. Low-cost optical sensors for PM measurement are desirable for monitoring exposure closer to the personal level and particularly suited for developing spatiotemporally dense city sensor networks. However, questions remain over the accuracy and reliability of the data they produce, particularly regarding the influence of environmental parameters such as humidity and temperature, and with varying PM sources and concentration profiles. In this study, eight units each of five different models of commercially available low-cost optical PM sensors (40 individual sensors in total) were tested under controlled laboratory conditions, against higher-grade instruments for: lower limit of detection, response time, responses to sharp pollution spikes lasting <1 min , and the impact of differing humidity and PM source. All sensors detected the spikes generated with a varied range of performances depending on the model and presenting different sensitivity mainly to sources of pollution and to size distributions with a lesser impact of humidity. The sensitivity to particle size distribution indicates that the sensors may provide additional information to PM mass concentrations. It is concluded that improved performance in field monitoring campaigns, including tracking sources of pollution, could be achieved by using a combination of some of the different models to take advantage of the additional information made available by their differential response.

This volume of the Encyclopedia of Sustainability Science and Technology, Second Edition, provides a broad and comprehensive view of air pollution, extending from ground-level, localized air quality and regional and global air quality and effects, to sensors and measurement and air pollution control. Despite substantial improvements in many parts of the world, globally, air pollution remains the most hazardous environmental threat. The increasing quality of exposure assessments, access to new and better statistical methods, and more complete and precise health data have led to stronger associations between air pollution exposure and health effects. Air pollution exposure-effect relationships have now been established for a wide variety of health outcomes, and well documented through parallel studies in many countries around the world using a variety of approaches and methodologies. Assessments of the health effects in the population are now performed on a routine basis in many countries and by many agencies, and often these also include calculation of externalities associated with the negative health effects. Such knowledge is essential for pushing development towards a more sustainable society. This volume covers topics including, but not limited to, basic knowledge to understand foundational concepts and drivers of regional and global air pollution in relation to air quality and ways to sense, measure and control pollutants, while placing this knowledge into the perspectives of health and technological systems.

Air pollution threatens our health, environment, and climate. The sources of air pollution are numerous anthropogenic and natural emissions; some are pollution in their own right, and some trigger the formation of secondary pollution. Detailed knowledge of the sources of pollution and the transformations of pollution in the atmosphere is the best possible basis for effective and cost-effective management strategies. While this knowledge is the basis of environmental management as regards emissions standards and best-practice pollution control systems, it is also critically important to society as it seeks to adopt policies and behaviors to reduce air pollution and its associated impacts and direct resources toward research and technological development to achieve sustainability. In fact, reducing air pollution emissions and thereby improving air quality will help us to meet a series of United Nations Sustainable Development Goals. Environmental pollution contributes to poverty, low crop yields, and disease, and the fight for resources leads to political instability. Thus, reducing air pollution helps us achieve sustainability by reducing poverty and inequality, providing jobs in the clean technology sector, and reducing and overcoming climate change. During the 2020 Corona crises, air pollution levels have decreased substantially in urban areas around the world because of reduced travel and industrial activity. These improvements in air quality have made real some of the improvements that can be obtained from, e.g., moving towards a society less dependent on fossil fuels. Improved cleaning technologies are the result of both pull and push strategies. This can be seen in the vehicle industry where strict emission standards have forced manufacturers to develop new technologies. These developments have been important for improving air quality in many parts of the world over the past two to three decades.

BACKGROUND: The inhalation anesthetics are potent greenhouse gases. To reduce the global environmental impact of the health care sector, technologies are sought to limit the release of waste anesthetic gas into the atmosphere. METHODS: Using a photochemical exhaust gas destruction system, removal efficiencies for nitrous oxide, desflurane, and sevoflurane were measured at various inlet concentrations (25% and 50%; 1.5%, 3.0%, and 6.0%; and 0.5%, 1.0%, and 2.0%, respectively) with flow rates ranging from 0.25 to 2.0 L/min. To evaluate the economic competitiveness of the anesthetic waste gas destruction system, its price per ton of carbon dioxide equivalent was calculated and compared to other greenhouse gas abatement technologies and current market prices. RESULTS: All inhaled anesthetics evaluated demonstrate enhanced removal efficiencies with decreasing flow rates (P < .0001). Depending on the anesthetic and its concentration, the photochemical exhaust gas destruction system exhibits a constant first-order removal rate, k. However, there was not a simple relation between the removal rate k and the species concentration. The costs for removing a ton of carbon dioxide equivalents are <$0.005 for desflurane, <$0.114 for sevoflurane, and <$49 for nitrous oxide. CONCLUSIONS: Based on this prototype study, destroying sevoflurane and desflurane with this photochemical anesthetic waste gas destruction system design is efficient and cost-effective. This is likely also true for other halogenated inhalational anesthetics such as isoflurane. Due to differing chemistry of nitrous oxide, modifications of this prototype photochemical reactor system are necessary to improve its removal efficiency for this gas.

Systems and methods for transaction platforms include various systems interacting with each other and transacting in various ways. A method for configuring and launching a marketplace includes: identifying, by a processing system having one or more processors, an opportunity to facilitate configuration of a new marketplace; receiving marketplace opportunity data, wherein the marketplace opportunity data includes information related to a set of assets of one or more types; determining configuration parameters to be implemented in the new marketplace; determining the feasibility of implementing the configuration parameters in the new marketplace; determining data resources to support the new marketplace; determining an architecture of the new marketplace; determining the configuration of the data resources in a data model for the marketplace; configuring a marketplace object; connecting selected data resources to populate the marketplace object; and launching the new marketplace.

The present invention relates to an air delivery system for providing cleaned and cooled air to a specified zone, such as a street canyon or other public space, comprising a) an air cleaning unit having an inlet and an outlet, wherein the inlet is adapted to receive ambient air or cooled air and the outlet is adapted to provide the cleaned and cooled air or the cleaned air, and b) an air cooling unit having an inlet and an outlet, wherein the inlet is adapted to receive ambient air or cleaned air and the outlet is adapted to provide the cleaned and cooled air or the cooled air; wherein the inlet of the cooling unit is connected to the outlet of the air cleaning unit, or wherein the outlet of the cooling unit is connected to the inlet of the air cleaning unit; or c) a unit for cleaning and cooling air simultaneously, having an inlet and an outlet, wherein the inlet is adapted to receive ambient air and the outlet is adapted to provide the cleaned and cooled air.