System Enhancement of Title V Permit Reviews and Point Source Inventories

Emission inventories are a critical component for air quality management. An accurate and up-to-date inventory data is an essential element of air quality modeling that is crucial in determining compliance with ambient standards and in making policy decisions. To insure that accurate inventory data are obtained in a State or local agency, a combined Title V permitting process and point source inventory reporting infrastructure are being implemented using Microsoft’s Access database program. The purpose of this thesis is to develop a consolidated system for the State of Tennessee point source inventory, the Consolidated Emission Reporting Rule (CERR) request information system and Tennessee Title V permitting system, thus allowing the management of these tasks within the same system. The system provides a method for companies to complete their Title V permit applications electronically and, at the same time, generate their point source inventory required by CERR. For validation purposes, the inventory data obtained from the electronic Title V permit application via the system are checked against the National Emission Inventory Input Format (NIF 3.0) quality assurance algorithm. With this method of collecting and verifying data, regulatory agencies can update emission inventories with data to meet the requirements of the Consolidated Emissions Reporting Rule with minimal effort

Effects of 2000-2050 Global Climate Change on Ozone and Particulate Matter Air Quality in the United States Using Models-3/CMAQ System

The Models-3/Community Multi-scale Air Quality modeling system (CMAQ), coupled with Goddard Institute for Space Studies (GISS) atmospheric General Circulation Model (GCM), fifth Generation Mesoscale Model system (MM5), and Goddard Earth Observing System-CHEMistry (GEOS-Chem), was used to simulate atmospheric concentration of ozone and particulate matter over the continental United States 12-km and 36-km (CONUS) domains at year 2000 and year 2050. In the study, GISS GCM model outputs interfaced with MM5 were utilized to supply the current and future meteorological conditions for CMAQ. The conventional CMAQ profile initial and boundary conditions were replaced by time-varied and layer-varied GEOS-Chem outputs. The future emission concentrations were estimated using year 2000 based emissions with emission projections suggested by the IPCC A1B scenario. Multi-scenario statistical analyses were performed to investigate the effects of climate change and change of anthropogenic emissions toward 2050. The composite effects of these changes were broken down into individual effects and analyzed on three distinct regions (i.e., Midwest, Northeast and Southeast). The results of CMAQ hourly and 8-hour average concentrations indicate the maximum ozone concentration in the Midwest is increased slightly from year 2000 to year 2050, as a result of increasing average and maximum temperatures by 2 to 3 degrees Kelvin. In converse, there is an observed reduction of surface ozone concentration in the Southeast caused by the decrease in solar radiation. For the emission reduction scenario, the decline of anthropogenic emissions causes reductions of both ozone and PM2.5 for all regions. The emission reduction has compensated the effect of increasing temperature. The overall change on the maximum daily 8-hr ozone and average PM2.5 concentrations in year 2050 were estimated to be 10% and 40% less than the values in year 2000, respectively. The modeling results indicates the effect of emissions reduction has greater impact than the effect of climate change

Impact Assessment of Biomass Burning on Air Quality in Southeast and East Asia During BASE-ASIA

A synergy of numerical simulation, ground-based measurement and satellite observation was applied to evaluate the impact of biomass burning originating from Southeast Asia (SE Asia) within the framework of NASA's 2006 Biomass burning Aerosols in Southeast Asia: Smoke Impact Assessment (BASE-ASIA). Biomass burning emissions in the spring of 2006 peaked in MarcheApril when most intense biomass burning occurred in Myanmar, northern Thailand, Laos, and parts of Vietnam and Cambodia. Model performances were reasonably validated by comparing to both satellite and ground-based observations despite overestimation or underestimation occurring in specific regions due to high uncertainties of biomass burning emission. Chemical tracers of particulate K(+), OC concentrations, and OC/EC ratios showed distinct regional characteristics, suggesting biomass burning and local emission dominated the aerosol chemistry. CMAQ modeled aerosol chemical components were underestimated at most circumstances and the converted AOD values from CMAQ were biased low at about a factor of 2, probably due to the underestimation of biomass emissions. Scenario simulation indicated that the impact of biomass burning to the downwind regions spread over a large area via the Asian spring monsoon, which included Southern China, South China Sea, and Taiwan Strait. Comparison of AERONET aerosol optical properties with simulation at multi-sites clearly demonstrated the biomass burning impact via longrange transport. In the source region, the contribution from biomass burning to AOD was estimated to be over 56%. While in the downwind regions, the contribution was still significant within the range of 26%-62%

Analysis of spatial and temporal patterns of on-road NO2 concentrations in Hong Kong

In this paper we present an investigation of the spatial and temporal variability of street-level concentrations of NO2 in Hong Kong as an example of a densely populated megacity with heavy traffic. For the study we use a combination of open-path remote sensing and in situ measurement techniques that allows us to separate temporal changes and spatial patterns and analyse them separately. Two measurement campaigns have been conducted, one in December 2010 and one in March 2017. Each campaign lasted for a week which allowed us to examine diurnal cycles, weekly patterns as well as spatially resolved long-term changes. We combined a long-path differential optical absorption spectroscopy (DOAS) instrument with a cavity-enhanced DOAS and applied several normalizations to the data sets in order to make the different measurement routes comparable. For the analysis of long-term changes we used the entire unfiltered data set and for the comparison of spatial patterns we filtered out the accumulation of NO2 when stopping at traffic lights for focusing on the changes of NO2 spatial distribution instead of comparing traffic flow patterns. For the generation of composite maps the diurnal cycle has been normalized by scaling the mobile data with coinciding citywide path-averaged measurement results. An overall descending trend from 2010 to 2017 could be observed, consistent with the observations of the Ozone Monitoring Instrument (OMI) and the Environment Protection Department (EPD) air quality monitoring network data. However, long-term difference maps show pronounced spatial structures with some areas, e.g. around subway stations, revealing an increasing trend. We could also show that the weekend effect, which for the most part of Hong Kong shows reduced NO2 concentrations on Sundays and to a lesser degree on Saturdays, is reversed around shopping malls. Our study shows that spatial differences have to be considered when discussing citywide trends and can be used to put local point measurements into perspective. The resulting data set provides a better insight into on-road NO2 characteristics in Hong Kong, which helps to identify heavily polluted areas and represents a useful database for urban planning and the design of pollution control measures

Mechanical Engineering

Black carbon (BC) emissions play an important role in regional climate change in the Arctic. It is necessary to pay attention to the impact of long-range transport from regions outside the Arctic as BC emissions from local sources in the Arctic were relatively small. The task force Hemispheric Transport of Air Pollution Phase 2 (HTAP2) set up a series of simulation scenarios to investigate the response of BC in a given region to different source regions. This study investigated the responses of Arctic BC concentrations and surface temperature to 20&thinsp;% anthropogenic emission reductions from six regions in 2010 within the framework of HTAP2 based on ensemble modeling results. Emission reductions from East Asia (EAS) had the most (monthly contributions: 0.2&ndash;1.5&thinsp;ng&thinsp;m&minus;3) significant impact on the Arctic near-surface BC concentrations, while the monthly contributions from Europe (EUR), Middle East (MDE), North America (NAM), Russia&ndash;Belarus&ndash;Ukraine (RBU), and South Asia (SAS) were 0.2&ndash;1.0, 0.001&ndash;0.01, 0.1&ndash;0.3, 0.1&ndash;0.7, and 0.0&ndash;0.2&thinsp;ng&thinsp;m&minus;3, respectively. The responses of the vertical profiles of the Arctic BC to the six regions were found to be different due to multiple transport pathways. Emission reductions from NAM, RBU, EUR, and EAS mainly influenced the BC concentrations in the low troposphere of the Arctic, while most of the BC in the upper troposphere of the Arctic derived from SAS. The response of the Arctic BC to emission reductions in six source regions became less significant with the increase in the latitude. The benefit of BC emission reductions in terms of slowing down surface warming in the Arctic was evaluated by using absolute regional temperature change potential (ARTP). Compared to the response of global temperature to BC emission reductions, the response of Arctic temperature was substantially more sensitive, highlighting the need for curbing global BC emissions. &nbsp;</p

Screening Approach for Short-Term PM2.5 Health Co-Benefits: A Case Study from 15 Metropolitan Cities around the World during the COVID-19 Pandemic

Fifteen cities across the world have been selected to investigate the public health co-benefits of PM2.5 reduction, during a period when various non-pharmaceutical interventions (NPIs) were adopted in the COVID-19 pandemic. Through applying a public health model, AirQ+, substantial spatial variations of global public health co-benefits were identified. Differences in seasonal air quality and population baselines were key underlying factors. For cities in North America, NPIs were introduced during the low pollution season, generating no co-benefits. On the other hand, tremendous health co-benefits were observed for cities in India and China, due to the high PM2.5 background with a large population. Among all, New Delhi has received the largest co-benefits, which saved over 14,700 premature deaths. As the pollution level (i.e., 45 &mu;g m&minus;3) with NPIs still exceeded the air quality standard, more rigorous emission controls are urgently needed to protect the public&prime;s health in India. At last, a novel and practical tool for co-benefit screening was developed using data from one of the global measurement networks (i.e., IQAir)

Investigation of Policy Relevant Background (PRB) Ozone in East Asia

The concept of Policy Relevant Background (PRB) ozone has emerged in recent years to address the air quality baseline on the theoretical limits of air pollution controls. In this study, the influence of Long-range Transport (LRT) of air pollutants from North America and the effect of Stratosphere-Troposphere Transport (STT) on PRB ozone was investigated using GEOS-Chem coupled WRF-CMAQ modelling system. Four distinct seasons in 2006 were simulated to understand better the seasonal and geographical impacts of these externalities on PRB ozone over East Asia (EA). Overall, the LRT impact from North America has been found to be ~0.54 ppbv, while the maximum impacts were found at the mountain stations with values of 2.3 ppbv, 3.3 ppbv, 2.3 ppbv, and 3.0 ppbv for January, April, July, and October, respectively. In terms of PRB ozone, the effect of STT has enhanced the surface background ozone by ~3.0 ppbv, with a maximum impact of 7.8 ppbv found in the northeastern part of East Asia (near Korea and Japan). Springtime (i.e., April) has the most vital STT signals caused by relatively cold weather and unstable atmospheric condition resulting from the transition of the monsoon season. The simulated PRB ozone based on the mean values of the maximum daily 8-h average (MDA8) is 53 ppbv for spring (April) and 22 ppbv for summer (July). Up to ~1.0 ppbv and ~2.2 ppbv of MDA8 ozone were attributed to LRT and STT, respectively. Among the selected cities, Beijing and Guangzhou have received the most substantial anthropogenic enhancement in MDA8 ozone in summer, ranging from 40.0 ppbv to 56.0 ppbv

Screening approach for short-term PM2.5 health co-benefits: A case study from 15 metropolitan cities around the world during the COVID-19 pandemic

Fifteen cities across the world have been selected to investigate the public health co-benefits of PM2.5 reduction, during a period when various non-pharmaceutical interventions (NPIs) were adopted in the COVID-19 pandemic. Through applying a public health model, AirQ+, substantial spatial variations of global public health co-benefits were identified. Differences in seasonal air quality and population baselines were key underlying factors. For cities in North America, NPIs were introduced during the low pollution season, generating no co-benefits. On the other hand, tremendous health co-benefits were observed for cities in India and China, due to the high PM2.5 background with a large population. Among all, New Delhi has received the largest co-benefits, which saved over 14,700 premature deaths. As the pollution level (i.e., 45 μg m−3) with NPIs still exceeded the air quality standard, more rigorous emission controls are urgently needed to protect the public′s health in India. At last, a novel and practical tool for co-benefit screening was developed using data from one of the global measurement networks (i.e., IQAir).ISSN:2073-443

Screening Approach for Short-Term PM_2.5 Health Co-Benefits: A Case Study from 15 Metropolitan Cities around the World during the COVID-19 Pandemic

Fifteen cities across the world have been selected to investigate the public health co-benefits of PM2.5 reduction, during a period when various non-pharmaceutical interventions (NPIs) were adopted in the COVID-19 pandemic. Through applying a public health model, AirQ+, substantial spatial variations of global public health co-benefits were identified. Differences in seasonal air quality and population baselines were key underlying factors. For cities in North America, NPIs were introduced during the low pollution season, generating no co-benefits. On the other hand, tremendous health co-benefits were observed for cities in India and China, due to the high PM2.5 background with a large population. Among all, New Delhi has received the largest co-benefits, which saved over 14,700 premature deaths. As the pollution level (i.e., 45 μg m−3) with NPIs still exceeded the air quality standard, more rigorous emission controls are urgently needed to protect the public′s health in India. At last, a novel and practical tool for co-benefit screening was developed using data from one of the global measurement networks (i.e., IQAir)