UV Light Induced Transformation of 1-Methylnaphthalene in the Presence of Air and Its Implications for Contaminants Research

Understanding chemical transformations of contaminants and the resulting products is extremely important in devising proper monitoring methods for such contaminants and in assessing potential human exposure to the transformation products in the environment. Ultraviolet (UV) light from the sun can induce various photochemical transformations of contaminants in the environment. Alkylnaphthalenes are light-molecular-weight polycyclic aromatic hydrocarbons (PAHs) which are one of the most widespread organic pollutants present in ambient air as a result of a variety of incomplete combustion sources. In this study, 1-methylnapthalene,a typical example of an alkylnaphthalene, was subjected to UV irradiation to investigate its transformation in the presence and absence of air. Twenty-one products were detected in the reaction mixtures. Some photo-oxidation products were identified, including both ring-opened and ring-retained oxygenated compounds, such as 1-naphthaldehyde, 1-naphthoic acid, 1-naphthalenemethanol and phthalic anhydride. Although dimeric products were observed in the presence of air, more were found in the presence of helium or argon gas, indicating a different photo-oxidation pathway from those commonly observed in other media, such as water. Under just 48 hours of exposure to the UV light in the presence of air, three major products were formed with a production yield of about 10% each. Compared to 1-methylnapthalene, the UV induced transformation products observed in this study are more volatile, acidic, water soluble or toxic. The formation of these products may significantly change our understanding of the risks assessed solely from the parent compound in contaminants research and supports the inclusion of airborne transformations of the parent compound in risk assessment.

Mechanistic modeling of copper corrosions in data center environments

Air-side economizers are increasingly used to take advantage of“free-cooling”in data centers with the intent of reducing the carbon footprint of buildings.However,they can introduce outdoor pollutants to indoor environment of data centers and cause corrosion damage to the information technology equipment.To evaluate the reliability of information technology equipment under various thermal and air-pollution conditions,a mechanistic model based on multi-ion transport and chemical reactions was developed.The model was used to predict Cu corrosion caused by Cl_(2)-containing pollutant mixtures.It also accounted for the effects of temperature(25℃and 28℃),relative humidity(50%,75%,and 95%),and synergism.It also identified higher air temperature as a corrosion barrier and higher relative humidity as a corrosion accelerator,which agreed well with the experimental results.The average root mean square error of the prediction was 13.7Å.The model can be used to evaluate the thermal guideline for data centers design and operation when Cl_(2)is present based on pre-established acceptable risk of corrosion in data centers’environment.

Development of a procedure for estimating the parameters of mechanistic VOC emission source models from chamber testing data

In order to evaluate the impacts of volatile organic compounds(VOCs)emissions from building materials on the indoor air quality beyond the standard chamber test conditions and test period,mechanistic emission source models have been developed in the past.However,very limited data are available for the required model parameters including the initial concentration(C_(m0)),in-material diffusion coefficient(D_(m)),partition coefficient(Kma),and convective mass transfer coefficient(k_(m)).In this study,a procedure was developed for estimating the model parameters by using VOC emission data from standard small chamber tests.In the procedure,initial values of the model parameters were refined by multivariate regression analysis of the measured emission data.To verify the procedure and estimate its uncertainty,simulated chamber test data were generated by adding 10% experimental uncertainties on the theoretical curve from the analytical solution to a mechanistic emission model.Then the procedure was applied to the generated data to estimate the model parameters.Results indicated that estimates converged to the original parameter values used for the data generation and the error of estimated parameters D_(m1)C_(m0) and K_(ma) were within±10%,±23%,and±25%of the true values,respectively.The procedure was further demonstrated by applying it to estimate the model parameters from real chamber test data.Wide application of the procedure would result in a database of mechanistic source model parameters for assessing the impact of VOC emissions on indoor pollution load,which are essential input data for evaluating the effectiveness of various indoor air quality(IAQ)design and control strategies as well as the energy required for meeting given IAQ requirements.

Green Design Studio: A modular-based approach for high-performance building design

A modular-based Green Design Studio(GDS)platform has been developed in this study for fast and accurate performance analysis for early stage green building design.The GDS platform aims to simplify the design and analysis process by embedding performance parameters into design elements in modules and employing near-real-time model for whole building performance simulation as well as by providing an easy-to-use and intuitive user interface to assist users without extensive knowledge on building physics.The platform consists of building modules as fundamental building blocks,performance predicting models,and a user interface for visualization and interactive design.In the platform,a whole building is composed of modules organized in a hierarchical structure,including spaces,enclosures,service systems,sustainable resource systems and sites.Both physics-based and data-driven models can be used to simulate the building performance and optimize building systems.A simplified physics-based model,the Resistance–Capacitance(RC)model,has been proposed as a generic simulation model for the flows of heat,air,moisture and pollutants,which is significantly faster than conventional simulation tools such as EnergyPlus,and hence more practical for use in real-time design interaction and optimization.A pilot case study is conducted to illustrate the modular-based design approach using a section of an office building.Compared to conventional building performance analysis tools,the GDS platform can provide fast and reliable feedback on performance prediction for early design.The modular approach makes it easier to modify the building design and evaluate the potentials and contributions of various green design features and technologies.

A probabilistic-based method to evaluate hygrothermal performance of an internally insulated brick wall

Uncertainty exists in many aspects of building simulation.A deterministic hygrothermal analysis may not sufficiently give a reliable guidance if a number of input variables are subject to uncertainty.In this paper,a probabilistic-based method was developed to evaluate the hygrothermal performance of building components.The approach accounts for the uncertainties from model inputs and propagates them to the outputs through the simulation model,thus it provides a likelihood of performance risk.Latin hypercube sampling technique,incorporated with correlation structure among the inputs,was applied to generate the random samples that follows the intrinsic relations.The performance of an internally insulated masonry wall was evaluated by applying the proposed approach against different criteria.Thermal performance,condensation and mould growth potential of the renovated wall can overall satisfy the requirements stipulated in multifold standards.The most influential inputs were identified by the standardized regression sensitivity analysis and partial correlation technique.Both methods deliver the same key parameters for the single and time-dependent output variables in the case study.The probabilistic method can provide a comprehensive risk analysis and support the decision-maker and engineer in the design and optimization of building components.

Combined Heat, Air, Moisture and Pollutant Simulations (CHAMPS) research for building and urban energy efficiency and environmental quality analysis

The energy and environmental performance of buildings and communities depends on how the heat,air,moisture and pollutant flows are managed and controlled in the system.Combined Heat,Air,Moisture and Pollutant Simulations(CHAMPS)research and development is vital to the optimal design and operation of building and urban energy and environmental systems.