Developing Seasonal Ammonia Emission Estimates with an Inverse Modeling Technique

Significant uncertainty exists in magnitude and variability of ammonia (NH3) emissions, which are needed for air quality modeling of aerosols and deposition of nitrogen compounds. Approximately 85% of NH3emissions are estimated to come from agricultural nonpoint sources. We suspect a strong seasonal pattern in NH3emissions; however, current NH3emission inventories lack intra-annual variability. Annually averaged NH3emissions could significantly affect model-predicted concentrations and wet and dry deposition of nitrogen-containing compounds. We apply a Kalman filter inverse modeling technique to deduce monthly NH3 emissions for the eastern U.S. Final products of this research will include monthly emissions estimates from each season. Results for January and June 1990 are currently available and are presented here. The U.S. Environmental Protection Agency (USEPA) Community Multiscale Air Quality (CMAQ) model and ammonium (NH4+) wet concentration data from the National Atmospheric Deposition Program (NADP) network are used. The inverse modeling technique estimates the emission adjustments that provide optimal modeled results with respect to wet NH4+concentrations, observational data error, and emission uncertainty. Our results suggest that annual average NH3emissions estimates should be decreased by 64% for January 1990 and increased by 25% for June 1990. These results illustrate the strong differences that are anticipated for NH3emissions.

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Human health risk assessment due to ambient PM10 and SO2 by an air quality modeling technique

Process Safety and Environmental Protection ◽

10.1016/j.psep.2017.07.018 ◽

2017 ◽

Vol 111 ◽

pp. 346-354 ◽

Cited By ~ 30

Author(s):

Yusef Omidi Khaniabadi ◽

Riccardo Polosa ◽

Rozalina Zlateva Chuturkova ◽

Mohammad Daryanoosh ◽

Gholamreza Goudarzi ◽

...

Keyword(s):

Risk Assessment ◽

Air Quality ◽

Health Risk ◽

Human Health ◽

Health Risk Assessment ◽

Human Health Risk ◽

Air Quality Modeling ◽

Human Health Risk Assessment ◽

Modeling Technique ◽

Quality Modeling

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Evolution of Gaseous and Particulate Pollutants in the Air: What Changed after Five Lockdown Weeks at a Southwest Atlantic European Region (Northwest of Spain) Due to the SARS-CoV-2 Pandemic?

Atmosphere ◽

10.3390/atmos12050562 ◽

2021 ◽

Vol 12 (5) ◽

pp. 562

Author(s):

Jorge Moreda-Piñeiro ◽

Joel Sánchez-Piñero ◽

María Fernández-Amado ◽

Paula Costa-Tomé ◽

Nuria Gallego-Fernández ◽

...

Keyword(s):

Air Quality ◽

Road Traffic ◽

Statistical Significance ◽

Temporal Trends ◽

Air Pollutant ◽

Concentration Data ◽

Southwest Atlantic ◽

Pollutant Concentrations ◽

Air Quality Monitoring Stations ◽

Almost All

Due to the exponential growth of the SARS-CoV-2 pandemic in Spain (2020), the Spanish Government adopted lockdown measures as mitigating strategies to reduce the spread of the pandemic from 14 March. In this paper, we report the results of the change in air quality at two Atlantic Coastal European cities (Northwest Spain) during five lockdown weeks. The temporal evolution of gaseous (nitrogen oxides, comprising NOx, NO, and NO2; sulfur dioxide, SO2; carbon monoxide, CO; and ozone, O3) and particulate matter (PM10; PM2.5; and equivalent black carbon, eBC) pollutants were recorded before (7 February to 13 March 2020) and during the first five lockdown weeks (14 March to 20 April 2020) at seven air quality monitoring stations (urban background, traffic, and industrial) in the cities of A Coruña and Vigo. The influences of the backward trajectories and meteorological parameters on air pollutant concentrations were considered during the studied period. The temporal trends indicate that the concentrations of almost all species steadily decreased during the lockdown period with statistical significance, with respect to the pre-lockdown period. In this context, great reductions were observed for pollutants related mainly to fossil fuel combustion, road traffic, and shipping emissions (−38 to −78% for NO, −22 to −69% for NO2, −26 to −75% for NOx, −3 to −77% for SO2, −21% for CO, −25 to −49% for PM10, −10 to −38% for PM2.5, and −29 to −51% for eBC). Conversely, O3 concentrations increased from +5 to +16%. Finally, pollutant concentration data for 14 March to 20 April of 2020 were compared with those of the previous two years. The results show that the overall air pollutants levels were higher during 2018–2019 than during the lockdown period.

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Association of temporary Environmental Protection Agency regulation suspension with industrial economic viability and local air quality in California, United States

Environmental Sciences Europe ◽

10.1186/s12302-021-00489-9 ◽

2021 ◽

Vol 33 (1) ◽

Author(s):

Emily Chang ◽

Kenneth Zhang ◽

Margaret Paczkowski ◽

Sara Kohler ◽

Marco Ribeiro

Keyword(s):

United States ◽

Air Quality ◽

Environmental Protection ◽

Environmental Protection Agency ◽

Manufacturing Industry ◽

Economic Viability ◽

Treatment Control ◽

Oil Refineries ◽

Pollution Levels ◽

The Impact

Abstract Background This study seeks to answer two questions about the impacts of the 2020 Environmental Protection Agency’s enforcement regulation rollbacks: is this suspension bolstering the economic viability of industries as oil and manufacturing executives claim they will and are these regulations upholding the agency’s mission of protecting the environment? Results To answer the former question, we utilized 6 months of state employment level data from California, United States, as a method of gauging the economic health of agency-regulated industries. We implemented a machine learning model to predict weekly employment data and a t-test to indicate any significant changes in employment. We found that, following California's state-issued stay-at-home order and the agency’s regulation suspension, oil and certain manufacturing industries had statistically significant lower employment values. To answer the latter question, we used 10 years of PM2.5 levels in California, United States, as a metric for local air quality and treatment–control county pairs to isolate the impact of regulation rollbacks from the impacts of the state lockdown. Using the agency’s data, we performed a t-test to determine whether treatment–control county pairs experienced a significant change in PM2.5 levels. Even with the statewide lockdown—a measure we hypothesized would correlate with decreased mobility and pollution levels—in place, counties with oil refineries experienced the same air pollution levels when compared to historical data averaged from the years 2009 to 2019. Conclusions In contrast to the expectation that the suspension would improve the financial health of the oil and manufacturing industry, we can conclude that these industries are not witnessing economic growth with the suspension and state shutdown in place. Additionally, counties with oil refineries could be taking advantage of these rollbacks to continue emitting the same amount of PM2.5, in spite of state lockdowns. For these reasons, we ask international policymakers to reconsider the suspension of enforcement regulations as these actions do not fulfill their initial expectations. We recommend the creation and maintenance of pollution control and prevention programs that develop emission baselines, mandate the construction of pollution databases, and update records of pollution emissions.

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Emission Inventories and Particulate Matter Air Quality Modeling over the Pearl River Delta Region

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18084155 ◽

2021 ◽

Vol 18 (8) ◽

pp. 4155

Author(s):

Diogo Lopes ◽

Joana Ferreira ◽

Ka In Hoi ◽

Ka-Veng Yuen ◽

Kai Meng Mok ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Pearl River Delta ◽

Air Quality Modeling ◽

Pearl River ◽

Emission Inventories ◽

Atmospheric Emission ◽

The Pearl River Delta ◽

Quality Modeling ◽

The Pearl River

The Pearl River Delta (PRD) region is located on the southeast coast of mainland China and it is an important economic hub. The high levels of particulate matter (PM) in the atmosphere, however, and poor visibility have become a complex environmental problem for the region. Air quality modeling systems are useful to understand the temporal and spatial distribution of air pollution, making use of atmospheric emission data as inputs. Over the years, several atmospheric emission inventories have been developed for the Asia region. The main purpose of this work is to evaluate the performance of the air quality modeling system for simulating PM concentrations over the PRD using three atmospheric emission inventories (i.e., EDGAR, REAS and MIX) during a winter and a summer period. In general, there is a tendency to underestimate PM levels, but results based on the EDGAR emission inventory show slightly better accuracy. However, improvements in the spatial and temporal disaggregation of emissions are still needed to properly represent PRD air quality. This study’s comparison of the three emission inventories’ data, as well as their PM simulating outcomes, generates recommendations for future improvements to atmospheric emission inventories and our understanding of air pollution problems in the PRD region.

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