Ecological risk assessment of heavy metals in desulfurized seawater discharged from a coal-fired power plant in Qingdao.

Despite the prevalence of discharge of large volumes of heavy-metal-bearing seawater from coal-fired power plants into adjacent seas, studies on the associated ecological risks remain limited. This study continuously monitored concentrations of seven heavy metals (i.e. As, Cd, Cr, Cu, Hg, Pb, and Zn) in surface seawater near the outfall of a coal-fired power plant in Qingdao, China over three years. The results showed average concentrations of As, Cd, Cr, Cu, Hg, Pb, and Zn of 2.63, 0.33, 2.97, 4.63, 0.008, 0.85, and 25.00 µg/L, respectively. Given the lack of data on metal toxicity to local species, this study investigated species composition and biomass near discharge outfalls and constructed species sensitivity distribution (SSD) curves with biological flora characteristics. Hazardous concentrations for 5% of species (HC5) for As, Cd, Cr, Cu, Hg, Pb, and Zn derived from SSDs constructed from chronic toxicity data for native species were 3.23, 2.22, 0.06, 2.83, 0.66, 4.70, and 11.07 µg/L, respectively. This study further assessed ecological risk of heavy metals by applying the Hazard Quotient (HQ) and Joint Probability Curve (JPC) based on long-term heavy metal exposure data and chronic toxicity data for local species. The results revealed acceptable levels of ecological risk for As, Cd, Hg, and Pb, but unacceptable levels for Cr, Cu, and Zn. The order of studied heavy metals in terms of ecological risk was Cr > Cu ≈ Zn > As > Cd ≈ Pb > Hg. The results of this study can guide the assessment of ecological risk at heavy metal contaminated sites characterized by relatively low heavy metal concentrations and high discharge volumes, such as receiving waters of coal-fired power plant effluents.

What is China's efficient power generation portfolio under carbon neutrality target? An empirical analysis considering flexibility and system cost.

Variable renewable energy (VRE) is the most promising form of primary generation under a carbon neutrality target due to its environmental benefits, incentive policy, and technological progress. However, the increasing proportion of VRE generation, such as solar and wind power, has sharply increased integration cost and reduced power grid stability. This study uses portfolio theory to investigate China's optimal power generation portfolio by 2050 considering flexibility constraint and system cost, including technical and integration costs. The results demonstrate that non-fossil-fuel power generation technologies have cost and emission reduction advantages over fossil-fuel-based technologies. VRE generation technologies must be developed in synergy with other forms of power generation when considering flexibility requirement and integration cost. A complete phase-out of fossil-fuel power generation technologies in China appears unlikely in the study period. Gas-fired and coal-fired power generation are the pillar forms of power generation to meet future flexibility needs.

An electricity market-based approach to finance environmental flow restoration.

As environmental flow demands become better characterized, improved water allocation and reservoir operating solutions can be devised to meet them. However, significant economic trade-offs are still expected, especially in hydropower-dominated basins. This study explores the use of the electricity market as both an institutional arrangement and an alternative financing source to handle the costs of implementing environmental flows in river systems managed for hydropower benefits. A framework is proposed to identify hydropower plants with sustainable operation within the portfolio of power sources, including a cost-sharing mechanism based on the electricity market trading to manage a time-step compensation fund. The objective is to address a common limitation in the implementation of environmental flows by reducing the dependence on government funding and the necessity for new arrangements. Compensation amounts can vary depending on ecosystem restoration goals (level of flow regime restoration), hydrological conditions, and hydropower sites characteristics. The application in the Paraná River Basin, Brazil, shows basin-wide compensation requirements ranging from zero in favorable hydrological years to thousands of dollars per gigawatt-hour generated in others. Each electricity consumer's contribution to the compensation fund is determined by their share of energy consumption, resulting in values ranging from cents for residential users to thousands of dollars for industrial facilities. Finally, the compensation fund signals the economic value of externalities in energy production. For residential users, achieving varying levels of ecosystem restoration led to an electricity bill increase of less than 1 %. For larger companies, the increase ranged from less than 1 %-12 %.

Contribution of the carbon tax, phase-out of thermoelectric power plants, and renewable energy subsidies for the decarbonization of Chile - A CGE model and microsimulations approach.

There are various climate policies to decarbonize the energy matrix of a country. In the case of Chile, a carbon tax of 5 USD/tCO2 was initially implemented, and later, a schedule was established for the phase-out of coal-fired thermoelectric plants, all the above in the absence of subsidies for non-conventional renewable energy (NCRE). This study uses a computable general equilibrium (CGE) model and microsimulations to assess the contribution of current climate policies and other more demanding scenarios that accelerate the decarbonization of the Chilean energy matrix, considering economic, environmental, and distributional impacts. Specifically, carbon taxes are simulated with and without complementary climate policies (phase-out of coal-fired power plants and NCRE subsidies). The results show that the scenarios that combine the three climate policies generate a greater decrease in greenhouse gas emissions (40.4% âˆ¼ 57.5%). Besides, the drop in GDP is more pronounced when coal-fired thermoelectric plants phase out (0.3% additional), and NCRE subsidies contribute to moderately reducing emissions. However, NCRE subsidies reduce the negative effect on households' expenditure and income, especially in the poorest quintile. Finally, microsimulations show marginal changes in income distribution and an increase of up to 0.4 percentage points in the poverty rate.

Solar photovoltaic panel production in Mexico: A novel machine learning approach.

This study examines the potential for widespread solar photovoltaic panel production in Mexico and emphasizes the country's unique qualities that position it as a strong manufacturing candidate in this field. An advanced model based on artificial neural networks has been developed to predict solar photovoltaic panel plant metrics. This model integrates a state-of-the-art non-linear programming framework using Pyomo as well as an innovative optimization and machine learning toolkit library. This approach creates surrogate models for individual photovoltaic plants including production timelines. While this research, conducted through extensive simulations and meticulous computations, unveiled that Latin America has been significantly underrepresented in the production of silicon, wafers, cells, and modules within the global market; it also demonstrates the substantial potential of scaling up photovoltaic panel production in Mexico, leading to significant economic, social, and environmental benefits. By hyperparameter optimization, an outstanding and competitive artificial neural network model has been developed with a coefficient of determination values above 0.99 for all output variables. It has been found that water and energy consumption during PV panel production is remarkable. However, water consumption (33.16 × 10-4 m3/kWh) and the emissions generated (1.12 × 10-6 TonCO2/kWh) during energy production are significantly lower than those of conventional power plants. Notably, the results highlight a positive economic trend, with module production plants generating the highest profits (35.7%) among all production stages, while polycrystalline silicon production plants yield comparatively lower earnings (13.0%). Furthermore, this study underscores a critical factor in the photovoltaic panel production process which is that cell production plants contribute the most to energy consumption (39.7%) due to their intricate multi-stage processes. The blending of Machine Learning and optimization models heralds a new era in resource allocation for a more sustainable renewable energy sector, offering a brighter, greener future.

Evolution of China's NOx emission control strategy during 2005∼2020 over coal-fired power plants: A satellite-based assessment.

Since especially the 12th Five-Year Plan (2011-2015), China has made great efforts to reverse the increasing trend of NOx emissions through end-of-pipe measures. With the Ozone Monitoring Instrument (OMI) level 2 swath product of tropospheric NO2, this study explores the temporal-spatial patterns of NOx concentrations over China's coal-fired power plants from 2005 to 2020 and investigates the evolution of its control strategy. The nationwide deployment of flue-gas denitration facilities was a critical measure to mitigate NOx emissions from coal-fired power plants, while this study externally assesses the implementation gap of their operation. Our results illustrate that, besides the impacts of economic cycles, China's control strategy experienced a dramatic transformation from an ad hoc campaign style for meeting short-term temporary targets to more sustainable, technology- and governance-centered institutional arrangements for ensuring long-term fundamental solutions. Furthermore, the satellite-based assessment may provide not only ex post evaluation, but also in-time and independent data for more effective and efficient environmental compliance monitoring.

Prediction and balanced allocation of thermal power carbon emissions from a provincial perspective of China.

Carbon control in the thermal power generation industry is crucial for achieving the overall carbon peak target. How to predict, evaluate, and balance the allocation of inter provincial carbon emissions has a significant impact on the decision-making of reasonable allocation of inter provincial carbon emissions in the target year. Therefore, this paper uses Monte Carlo-ARIMA-BP neural network and ZSG-DEA model to conduct temporal trend prediction and carbon emission quota allocation research. We propose the "intra provincial and inter provincial" framework for carbon emissions trading in thermal power plants, which aims to break through the barriers in carbon emission rights exchange among provinces. The conclusions are as follows: (1) the growth trend of carbon emissions from thermal power is gradually slowing down and is expected to peak before 2030. (2) Inner Mongolia, Jiangsu, and Shandong have high input-output efficiency, and are all the main output provinces for carbon emission quota allocation. After being adjusted using the ZSG-DEA model, they can still be at the forefront of efficiency. (3) The "intra provincial and inter provincial" framework for carbon emissions trading can effectively predict and allocate the carbon emission demand of each province from time and space dimensions, balance the carbon emission rights and interests of each province, and provide forward-looking planning suggestions for inter provincial carbon emission rights exchange.

Optimization of low-grade coal and refuse-derived fuel blends for improved co-combustion behavior in coal-fired power plants.

This study is aimed at utilizing three waste materials, i.e., solid refuse fuel (SRF), tire derived fuel (TDF), and sludge derived fuel (SDF), as eco-friendly alternatives to coal-only combustion in co-firing power plants. The contribution of waste materials is limited to ≤5% in the composition of the mixed fuel (coal + waste materials). Statistical experimental design and response surface methodology are employed to investigate the effect of mixed fuel composition (SRF, TDF, and SDF) on gross calorific value (GCV) and ash fusion temperature (AFT). A quadratic model is developed and statistically verified to apprehend mixed fuel constituents' individual and combined effects on GCV and AFT. Constrained optimization of fuel blend, i.e., GCV >1,250 kcal/kg and AFT >1,200 °C, using the polynomial models projected the fuel-blend containing 95% coal with 3.84% SRF, 0.35% TDF, and 0.81% SDF. The observed GCV of 5,307 kcal/kg and AFT of 1225 °C for the optimized blend were within 1% of the model predicted values, thereby establishing the robustness of the models. The findings from this study can foster sustainable economic development and zero CO2 emission objectives by optimizing the utilization of waste materials without compromising the GCV and AFT of the mixed fuels in coal-fired power plants.

Exploration on the scientific rationality of low-carbon investment projects from the perspective of supply chain: a case study of CS thermal power plant.

Climate warming has gradually become a major problem threatening human survival, and countries have begun to pay attention to carbon emissions. Energy conservation and emission reduction has become a central task in China's economic development since the 14th Five-Year Plan. As the main force of carbon emissions in China, thermal power industry is bound to become the focus of attention in China's low-carbon development strategy and energy conservation and emission reduction. Moreover, with the marketization of the power industry, the state has joined the market competition at the power generation sectors and the power sale sectors, and implemented the "opening the middle of the two pipes." Therefore, the coverage of influence of carbon emissions and carbon investment behavior of power generation companies is not limited to itself, but will also be extended to the supply chain level. Based on the above background, this paper evaluates the scientific rationality of low-carbon investment projects of thermal power enterprises from the perspective of low-carbon supply chain, which not only can help enterprises achieve a win-win situation of economic and environmental benefits, but also contribute to the carbon emission reduction of the entire supply chain, thereby promoting China's entire social and economic energy conservation and emission reduction work.

Pond ash as a potential material for sustainable geotechnical applications - a review.

Energy-harnessing sources significantly influence a country's infrastructure and economic development. Though nuclear and hydel power sources are used for energy harnessing, thermal sources are still the primary power source in India and contribute to 75% of the demand. Thermal power plants exploit large volumes of coal reserves. The combustion of coal leads to 30%-40% of waste ash residues such as Fly ash and Bottom ash. Though Fly ash finds greater applicability, pond ash poses a severe environmental hazard due to its large occupancy of terrain in ash dykes and lagoons. Many research efforts are underway to utilize pond ash in various structural and geotechnical infrastructure projects; however, there are still limitations and apprehensions about its properties and determination. The present study provides a detailed review of the morphological and chemical properties. Further, the geotechnical attributes of pond ash, including strength characteristics, consolidation parameters, and durability aspects, are critically reviewed for the probable application as fill material for backfill and many other applications. Based on the earlier research on pond ash, it could be comprehended that pond ash has wide property variability and finds compatibility with many other pozzolanic admixtures and, in this way, finds broader applicability in geotechnical projects. The way forwards could be a significant step towards cleaner and greener technology.

Parametric Life Cycle Assessment of Nuclear Power for Simplified Models.

Electrifying the global economy is accepted as a main decarbonization lever to reach the Paris Agreement targets. The IEA's 2050 Net Zero transition pathways all involve some degree of nuclear power, highlighting its potential as a low-carbon electricity source. Greenhouse gas emissions of nuclear power reported in the life cycle assessment literature vary widely, from a few grams of CO2 equivalents to more than 100 g/kWh, globally. The reasons for such a variation are often misunderstood when reported and used by policymakers. To fill this gap, one can make LCA models explicit, exploring the role of the most significant parameters, and develop simplified models for the scientific community, policymakers, and the public. We developed a parametric cradle-to-grave life cycle model with 20 potentially significant variables: ore grade, extraction technique, enrichment technique, and power plant construction requirements, among others. Average GHG emissions of global nuclear power in 2020 are found to be 6.1 g CO2 equiv/kWh, whereas pessimistic and optimistic scenarios provide extreme values of 5.4-122 g CO2 equiv/kWh. We also provide simplified models, one per environmental impact indicator, which can be used to estimate environmental impacts of electricity generated by a pressurized water reactor without running the full-scale model.

Technical-economic and environmental protection performance evaluation of a novel hybrid solar-nuclear thermally coupled power and desalination plant.

Clean energy complementary system can reduce environmental pollution effectively and is considered as a future energy development direction. In this paper, an innovative solar-nuclear thermally coupled power and desalination plant for electricity and freshwater productions is proposed. As solar power and nuclear power are combined, this multi-energy system is a clean energy system and basically has no emissions of soot, sulfur oxides, carbon dioxide, and nitrogen oxides. The operating behavior assessment results of the multi-energy system show that the power generation and freshwater production systems can operate synergistically. The electric power and corresponding efficiency of the multi-energy system are 290.7 MW and 38.2%, in which the solar proportion is about 38.1%. The daily freshwater production of the multi-energy system is 3761.3 t. The economic assessment results reveal that the levelized costs of electricity and freshwater of the multi-energy system are 0.361 yuan/(kWh) and 1.645 yuan/t. The environmental protection analysis results show that in contrast with a coal-fired system, the annual emission reductions of soot, sulfur oxides, carbon dioxide, and nitrogen oxides of the multi-energy system are 7350.94 t, 12,634.42 t, 513,034.14 t, and 11,945.28 t, revealing a significant environmental protection performance.

Cost-benefits analysis of ultra-low emissions standard on air quality and health impact in thermal power plants in China.

As China's largest energy infrastructure, thermal power plant consumed approximately half of China's coal over the past decade and threatened air quality, human health and socioeconomic development. Thus, a series of control policies have been implemented to alleviate those impacts in China. Particularly, China has witnessed unprecedented declines in air pollutant emissions from thermal power plants since the ultra-low emissions (ULE) standards were implemented. In contrast, the effect of the ULE policy on air quality, health and cost benefits remains poorly understood. Therefore, this study estimates the improved air quality and associated health and economic benefits under the ULE standards in the thermal power sector by using a measure-specific approach, combining a bottom-up emission inventory, an atmospheric model, a health assessment model and a cost analysis model. The results show that all the control measures lead to reduced air pollution, and renovating pre-existing units (RPU) is the most effective. Compared to without implementing the ULE policy, the population-weighted average PM2.5 and O3 concentrations decreased by 1.50 µg/m3 and 0.87 ppm, and 67,831 premature deaths could be avoided nationally. Furthermore, the results also show the net economic benefits of combining health benefits and costs due to control measures are 109.92 billion Yuan (in 2015 value) in China. The comprehensive results reveal that the health benefits outweigh the direct policy. Based on these empirical findings and the specific circumstances of China, we suggest that RPU should be further promoted to the entire of China, and if necessary, establish a long-term compensation mechanism for inter-provincial interests and institute and enforce comprehensive policies that carefully consider the health impacts of policies. This study provides strong arguments for China's policy-making and considering tightening emission standards for thermal power plants worldwide.

Environmental Burden of Disease due to Emissions of Hard Coal- and Lignite-Fired Power Plants in Germany.

Objectives: The study estimated the environmental burden of disease (EBD) attributable to a long-term exposure of the population to nitrogen dioxide (NO2) and fine particulate matter (PM2.5) emissions from hard coal- and lignite-fired power plants in Germany for the year 2015. Methods: The contribution of coal-fired power plants to the total air pollutant concentration was modelled using a chemical transport model and then combined with population data to assess the corresponding population exposure. We calculated years of life lost (YLL), years of life with disability, or disability-adjusted life years for different health outcomes with a strong evidence for an association with the exposure. Results: The burden of disease from PM2.5 emissions from lignite is 1.2 times higher than that from hard coal emissions (7,866 YLL compared to 6,412 YLL). NO2 emissions from lignite, cause a burden of disease 2.3 times higher than hard coal NO2-emission (13,537 YLL compared to 5,906 YLL). The EBD for both pollutants is dominated by diseases of the cardiovascular system. Conclusion: Abandoning energy generation by coal-fired power plants would lower the burden of disease in Germany.

Analytical hierarchy process and economic analysis for optimal renewable sites in Bangladesh.

Bangladesh has a huge potential for utilizing renewable energy with the availability of sources for solar, wind, hydro, and biogas. This paper provides a comprehensive analysis of the potential for renewable energy sources and predicts optimal sites for renewable plant implementation in Bangladesh. A country-wise mapping approach is followed by validation of prediction using multi-criteria decision analysis (MCDA) known as the analytical hierarchy process (AHP) which will aid in the planning and execution of Bangladesh's upcoming expansion of renewable farms and will also be a useful tool for policymakers. Moreover, an economic analysis for 50 MW solar and wind power plant has been presented to estimate the levelized cost of electricity (LCoE) of the system and society. This work predicts the enormous potential for the expansion of renewable energy by assessing the appropriate future sites, economic viability, and provides several suggestions on the basis of the analysis from Bangladesh's perspective.

A life cycle assessment of coal-fired thermal power plants with post-combustion control techniques: an India scenario.

In recent years, there has been a focus on clean power generation, and it is critical to assess the environmental impact of novel technologies used in pollution control in power generation. The study uses life cycle assessment (LCA) to assess the environmental impacts of coal-fired thermal power plants with different emission control techniques in an Indian scenario. As there are no such studies available in the Indian context, this work might provide a holistic view of the impacts of energy generation. A supercritical coal-fired plant with a capacity of 660 MW is considered in this study. The system boundary included coal extraction, transportation, power plant operation, and transmission losses of electricity with a functional unit of 1 kWh. It was observed that there was an energy penalty due to the power consumed in emission control devices, but the maximum energy penalty was due to the power used in the carbon capture system. The LCA is done from "cradle to gate", with impact indicators at the mid-point evaluated using the RECIPE (H) 2016 LCIA method. LCA results showed that power plant operation is the most significant contributor to environmental impact. Initially, in cases 1 and 2, climate change (CC) potential was a major impact category, but CC potential was reduced with carbon capture and storage, 0.27 kg CO2 eq. in case 3 with ESP, FGD, SCR, and carbon capture and storage (CCS) and 0.263 kg CO2 eq. in case 4 with ESP and CCS. But there was a considerable increase in the majority of the impact categories in case 4. Freshwater consumption potential increased from 3.98 E-03 m3 in base case 1 to 4.98 E-03 m3 in case 3 due to the amount of water used in chemical production during CCS, as CC potential is a major concern in power generation, However, compared to case 1, the potential for climate change increased in case 2, whilst in case 4, the potential for climate change is lower but has resulted in an increase in the majority of impact categories. Case 3 shows an optimal approach to reducing CO2 emissions compared to other cases. The combination of ESP, FGD, SCR, and CCS is favourable for cleaner energy generation.

Thermal power plants pollution assessment based on deep neural networks, remote sensing, and GIS: A real case study in Iran.

To investigate the impact of the Bandar Abbas thermal power plant on the waters of the Persian Gulf coast, a combination of satellite images and ground data was utilized to determine the Sea Surface Temperature (SST) as a thermal index, Total Organic Carbon (TOC) and Chemical Oxygen Demand (COD) as biological indices. Additionally, measurements of SO2, O3, NO2, CO2, CO, and CH4 values in the atmosphere were taken to determine the plant's impact on air pollution. Temperature values of the water for different months were predicted using Long Short-Term Memory (LSTM), Support Vector Regression (SVR), and Cascade neural networks. The results indicate that the waters near thermal power plants exhibit the highest temperatures in July and September, with temperatures reaching approximately 50 °C. Furthermore, the SST values were found to be strongly correlated with ecological indices. The Multiple Linear Regression (MLR) analysis revealed a strong correlation between the temperature and TOC, COD, and O2 in water (RTOC2=0.98), [Formula: see text] , RCOD2=0.87 and O3, NO3, CO2, and CO in the air ( [Formula: see text] ). Finally, the results demonstrate that the LSTM method exhibited high accuracy in predicting the water temperature (R2 = 0.98).

The impact of electricity-carbon market coupling on system marginal clearing price and power supply cost.

In this study, we assessed the impacts of the benchmark designs of emissions allowance allocation in China's national carbon emissions trading system with plant-level data and further estimated the marginal clearing price and power supply cost in Guangdong power market under electricity-carbon market coupling with unit commitment and economic dispatch model. We find that the existing allowances benchmark would result in a considerable surplus of allowances at about 222 Mt. But the benchmarking and exemplary levels on the heat rate of power supply would motivate thermal power units to reduce CO2 emissions. Under a tight balance of supply and demand in Guangdong, peaking thermal power plants will become the marginal clearing units and higher clearing prices will add to the revenue of lower cost inframarginal renewable energy power units. However, the combined impact of electricity-carbon market coupling would cause the marginal clearing price fluctuates obviously from 0 to 1159 CNY/MWh. Compared to the baseline scenario with free CO2 allowances allocation, the efficiency of thermal power utilization would decrease by 23%-59% and the net revenue per MWh power supply of coal-fired power units would decrease by 275%-325% under the stress scenario. Our study suggests that setting a more stringent allowances allocation benchmark for carbon price discovery is necessary. As electricity-carbon market coupling changes the role of coal-fired power plants to provide flexibility service and decrease their revenues, it calls for further market designs on proper reimbursement of flexible resources, under which the electricity market can effectively achieve the synergy among accommodating new energy, ensuring resource adequacy, and delivering cost efficiency. In addition, the synergy can be enhanced by formulating a tax program, which can promote renewable energy investment.

Health risk assessment of heavy metals in soil, plant, and water samples near "Gacko" power plant, in Bosnia and Herzegovina.

This study assesses heavy metal content in soil, water, and plant material from sites located around the lignite mine and the power plant "Gacko", Bosnia and Herzegovina. The samples were collected, prepared, and analyzed for heavy metals content using the flame atomic absorption spectrophotometer. Samples were analyzed for cadmium, lead, copper, zinc, manganese, and iron. To identify the relationship among the metals in samples and their possible sources, Pearson's correlation and principal component analysis were performed. Health risk assessment was applied to establish potential health risks posed to humans caused by contaminants in different environmental compartments. The results of our analyses show that most soil samples contain copper, and one of those samples had a copper concentration of more than 70 µg/g, which is a critical upper value for agricultural use. In the soil samples that were analyzed, cadmium was also detected, and its concentration was greater than 2 µg/g. Lead, on the other hand, had a concentration that was higher than the maximum permissible for unpolluted soils in 40% of the soil samples that were analyzed. Lead and cadmium concentrations in surface waters mostly contribute to a non-carcinogenic risk in the scenario of recreational swimming exposure. The presence of Cd, a highly toxic element in water, may be explained by the leaching of artificial fertilizers used in the study area, whereas Pb's origin may be geological. The results of this study recommend routine heavy metal monitoring in samples of soil, water, and plants from the examined area so that, if metal concentrations continue increasing, remedial action should be advised to prevent accumulation in the food chain.

Inequitable Exposures to U.S. Coal Power Plant-Related PM2.5: 22 Years and Counting.

BACKGROUND: Emissions from coal power plants have decreased over recent decades due to regulations and economics affecting costs of providing electricity generated by coal vis-à-vis its alternatives. These changes have improved regional air quality, but questions remain about whether benefits have accrued equitably across population groups. OBJECTIVES: We aimed to quantify nationwide long-term changes in exposure to particulate matter (PM) with an aerodynamic diameter ≤2.5µm (PM2.5) associated with coal power plant SO2 emissions. We linked exposure reductions with three specific actions taken at individual power plants: scrubber installations, reduced operations, and retirements. We assessed how emissions changes in different locations have influenced exposure inequities, extending previous source-specific environmental justice analyses by accounting for location-specific differences in racial/ethnic population distributions. METHODS: We developed a data set of annual PM2.5 source impacts ("coal PM2.5") associated with SO2 emissions at each of 1,237 U.S. coal-fired power plants across 1999-2020. We linked population-weighted exposure with information about each coal unit's operational and emissions-control status. We calculate changes in both relative and absolute exposure differences across demographic groups. RESULTS: Nationwide population-weighted coal PM2.5 declined from 1.96µg/m3 in 1999 to 0.06 µg/m3 in 2020. Between 2007 and 2010, most of the exposure reduction is attributable to SO2 scrubber installations, and after 2010 most of the decrease is attributable to retirements. Black populations in the South and North Central United States and Native American populations in the western United States were inequitably exposed early in the study period. Although inequities decreased with falling emissions, facilities in states across the North Central United States continue to inequitably expose Black populations, and Native populations are inequitably exposed to emissions from facilities in the West. DISCUSSION: We show that air quality controls, operational adjustments, and retirements since 1999 led to reduced exposure to coal power plant related PM2.5. Reduced exposure improved equity overall, but some populations continue to be inequitably exposed to PM2.5 associated with facilities in the North Central and western United States. https://doi.org/10.1289/EHP11605.