Aqpet — An R package for air quality policy evaluation

Evaluating the effectiveness of clean air policies is important in the cycle of air quality management, ensuring policy accountability and informing future policy-making processes. However, such evaluations are challenging due to complex confounding factors such as varying weather conditions or seasonal or annual changes in air quality unrelated to the policy implementation. To address this challenge, we developed 'aqpet', a R package designed to streamline the quantification of policy effects on air quality using observational data. The package 'aqpet' includes: (1) automated-machine learning to predict air pollutants under average weather conditions – a process term as "weather normalisation"; (2) augmented synthetic control method (ASCM) to quantify the actual policy impact on air pollution. 'aqpet' offers functions for data collection and preparation, building auto-machine learning models, conducting weather normalisation, model performance evaluation and explanation, and causal impact analysis using ASCM. 'aqpet' enables fast, efficient, and interactive policy analysis for air quality management.</p

Quantifying evolution of soot mixing state from transboundary transport of biomass burning emissions

Incomplete combustion of fossil fuels and biomass burning emit large amounts of soot particles into the troposphere. The condensation process is considered to influence the size (Dp) and mixing state of soot particles, which affects their solar absorption efficiency and lifetimes. However, quantifying aging evolution of soot remains hampered in the real world because of complicated sources and observation technologies. In the Himalayas, we isolated soot sourced from transboundary transport of biomass burning and revealed soot aging mechanisms through microscopic observations. Most of coated soot particles stabilized one soot core under Dp &lt; 400 nm, but 34.8% of them contained multi-soot cores (nsoot ≥ 2) and nsoot increased 3–9 times with increasing Dp. We established the soot mixing models to quantify transformation from condensation- to coagulation-dominant regime at Dp ≈ 400 nm. Studies provide essential references for adopting mixing rules and quantifying the optical absorption of soot in atmospheric models.</p

Introduction to Special Issue - In-depth study of air pollution sources and processes within Beijing and its surrounding region (APHH-2 Beijing)

Abstract. The Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-Beijing) programme is an international collaborative project focusing on understanding the sources, processes and health effects of air pollution in the Beijing megacity. APHH-Beijing brings together leading China and UK research groups, state-of-the-art infrastructure and air quality models to work on four research themes: (1) sources and emissions of air pollutants; (2) atmospheric processes affecting urban air pollution; (3) air pollution exposure and health impacts; and (4) interventions and solutions. Themes 1 and 2 are closely integrated and support Theme 3, while Themes 1-3 provide scientific data for Theme 4 to develop cost-effective air pollution mitigation solutions. This paper provides an introduction to (i) the rationale of the APHH-Beijing programme, and (ii) the measurement and modelling activities performed as part of it. In addition, this paper introduces the meteorology and air quality conditions during two joint intensive field campaigns - a core integration activity in APHH-Beijing. The coordinated campaigns provided observations of the atmospheric chemistry and physics at two sites: (i) the Institute of Atmospheric Physics in central Beijing, and (ii) Pinggu in rural Beijing during 10 November – 10 December 2016 (winter) and 21 May- 22 June 2017 (summer). The campaigns were complemented by numerical modelling and automatic air quality and low-cost sensor observations in the Beijing megacity. In summary, the paper provides background information on the APHH-Beijing programme, and sets the scene for more focussed papers addressing specific aspects, processes and effects of air pollution in Beijing

Atmospheric pollution and human health in a Chinese megacity (APHH-Beijing) programme. Final report

In 2016, over 150 UK and Chinese scientists joined forces to understand the causes and impacts - emission sources, atmospheric processes and health effects - of air pollution in Beijing, with the ultimate aim of informing air pollution solutions and thus improving public health. The Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-Beijing) research programme succeeded in delivering its objectives and significant additional science, through a large-scale, coordinated multidisciplinary collaboration. In this report are highlighted some of the research outcomes that have potential implications for policymaking

An interlaboratory comparison of aerosol inorganic ion measurements by ion chromatography : Implications for aerosol pH estimate

Water-soluble inorganic ions such as ammonium, nitrate and sulfate are major components of fine aerosols in the atmosphere and are widely used in the estimation of aerosol acidity. However, different experimental practices and instrumentation may lead to uncertainties in ion concentrations. Here, an intercomparison experiment was conducted in 10 different laboratories (labs) to investigate the consistency of inorganic ion concentrations and resultant aerosol acidity estimates using the same set of aerosol filter samples. The results mostly exhibited good agreement for major ions Cl-, SO2-4, NO-3, NHC4 and KC. However, F-, Mg2C and Ca2C were observed with more variations across the different labs. The Aerosol Chemical Speciation Monitor (ACSM) data of nonrefractory SO2-4, NO-3 and NHC4 generally correlated very well with the filter-analysis-based data in our study, but the absolute concentrations differ by up to 42 %. Cl-from the two methods are correlated, but the concentration differ by more than a factor of 3. The analyses of certified reference materials (CRMs) generally showed a good detection accuracy (DA) of all ions in all the labs, the majority of which ranged between 90 % and 110 %. The DA was also used to correct the ion concentrations to showcase the importance of using CRMs for calibration check and quality control. Better agreements were found for Cl-, SO2-4, NO-3, NHC4 and KC across the labs after their concentrations were corrected with DA; the coefficient of variation (CV) of Cl-, SO2-4, NO-3, NHC4 and KC decreased by 1.7 %, 3.4 %, 3.4 %, 1.2 % and 2.6 %, respectively, after DA correction. We found that the ratio of anion to cation equivalent concentrations (AE/CE) and ion balance (anions-cations) are not good indicators for aerosol acidity estimates, as the results in different labs did not agree well with each other. In situ aerosol pH calculated from the ISORROPIA II thermodynamic equilibrium model with measured ion and ammonia concentrations showed a similar trend and good agreement across the 10 labs. Our results indicate that although there are important uncertainties in aerosol ion concentration measurements, the estimated aerosol pH from the ISORROPIA II model is more consistent

Studies of bimetallic nanocatalysts and synthesis of tricyclic pyrone molecules for Alzheimer’s Disease

Doctor of PhilosophyDepartment of ChemistryDuy H HuaIn the industry, 80% of products were produced by catalysts, and most of the catalysts are tiny particles with sizes less than 25 nm. In the first project (discussed in Chapter 1 and Chapter 2), we selected two types of bimetallic nanocatalysts (Pd/Au and Cu/Au) for our studies. The goals are to use the nanocatalysts (Pd/Au and Cu/Au nanoclusters) to produce products with opposite stereochemistry. A pair of chiral substituted poly-vinyl-N-pyrrolidones (CSPVP) were designed and synthesized for the stabilization of nanocatalyst colloids (in water or dimethylformamide) to synthesize products with opposite stereochemistry using different oxidants such as tertiary-butyl hydrogen peroxide (TBHP) or hydrogen peroxide. We first studied the nanocatalyst colloid using achiral poly-vinyl-N-pyrrolidones (PVP) to explore new catalytic reactions. Phthalan, indene, norbornene and their derivatives were applied to these nanocatalysts using 30% hydrogen peroxide or TBHP as oxidant. Results suggest that Cu/Au tends to activate sp3 carbons, and these carbons are connected to benzene ring or oxygen, while Pd/Au exhibits catalytic potential to oxidize sp2 carbons. Chapter 1 focuses on the syntheses of chiral polymers and the corresponding colloidal nanocatalysts. In the following chapter, a series of substrates were treated with nanocatalyst colloids in different ingredients. Some of these substrates were treated with CSPVP supported colloid, and results remain to be carefully studied. In the second project (discussed in Chapter 3), two tricyclic pyrones were synthesized for the investigation of Alzheimer’s disease in a rat model. We also attempted to synthesize a novel tricyclic pyrone to avoid the formation of two stereoisomers by the insertion of an alkene

Urban Growth Modeling and Future Scenario Projection Using Cellular Automata (CA) Models and the R Package Optimx

Cellular automata (CA) is a spatially explicit modeling tool that has been shown to be effective in simulating urban growth dynamics and in projecting future scenarios across scales. At the core of urban CA models are transition rules that define land transformation from non-urban to urban. Our objective is to compare the urban growth simulation and prediction abilities of different metaheuristics included in the R package optimx. We applied five metaheuristics in optimx to near-optimally parameterize CA transition rules and construct CA models for urban simulation. One advantage of metaheuristics is their ability to optimize complexly constrained computational problems, yielding objective parameterization with strong predictive power. From these five models, we selected conjugate gradient-based CA (CG-CA) and spectral projected gradient-based CA (SPG-CA) to simulate the 2005-2015 urban growth and to project future scenarios to 2035 with four strategies for Su-Xi-Chang Agglomeration in China. The two CA models produced about 86% overall accuracy with standard Kappa coefficient above 69%, indicating their good ability to capture urban growth dynamics. Four alternative scenarios out to the year 2035 were constructed considering the overall effect of all candidate influencing factors and the enhanced effects of county centers, road networks and population density. These scenarios can provide insight into future urban patterns resulting from today's urban planning and infrastructure, and can inform future development strategies for sustainable cities. Our proposed metaheuristic CA models are also applicable in modeling land-use and urban growth in other rapidly developing areas