Rapid urbanization and the aggregation of human activities in cities have resulted in large amounts of anthropogenic heat (AH) emission, which affects urban climate. Quantifying and assessing the AH emission values accurately and analyzing their spatial distribution characteristics is important to understand the energy exchange processes of urban areas. In this study, the high spatial resolution anthropogenic heat flux (AHF) quantification and spatial distribution analysis were conducted using multi-source data in the Beijing-Tianjin-Hebei region (BTH region) of China. First, the AH emission in district and city level were estimated using inventory method based on energy consumption and socio-economic statistical data; Then, AHF spatial quantification models were constructed based on high spatial resolution nighttime light (NTL) data and Point of interests (POI) data, and 130 m × 130 m gridded AHF quantification result in BTH region was realized; Finally, the potential numerical and spatial distribution patterns of AHF were analyzed using various indicators including contribution rate and aggregation index. The results show that: (1) The parameterized index constructed based on NTL and POI data shows a strong correlation with AHF, with R² ranging from 0.79 to 0.94 and a mean absolute error (MAE) value of 0.72 w·m⁻², which can be applied to the quantification of gridded AHF values with high resolution. The highest total AHF in the study area is 214 w·m⁻², and the average value is 2.24 w·m⁻². (2) Considering the sources of AHF, industrial emission sources in BTH region contribute the most to the total AHF, but commercial building emission sources in Beijing have a higher contribution, which can reach 33.8%. (3) Different types of AHF have different spatial aggregation levels. Commercial building emission and human metabolic emission have the highest aggregation level, and transportation emission has the lowest aggregation level.

Most amyotrophic lateral sclerosis (ALS) cases are sporadic (∼90%) and environmental exposures are implicated in their etiology. Large industrial facilities are permitted the airborne release of certain chemicals with hazardous properties and report the amounts to the US Environmental Protection Agency (EPA) as part of its Toxics Release Inventory (TRI) monitoring program. The objective of this project was to identify industrial chemicals released into the air that may be associated with ALS etiology. We geospatially estimated residential exposure to contaminants using a de-identified medical claims database, the SYMPHONY Integrated Dataverse®, with ∼26,000 nationally distributed ALS patients, and non-ALS controls matched for age and gender. We mapped TRI data on industrial releases of 523 airborne contaminants to estimate local residential exposure and used a dynamic categorization algorithm to solve the problem of zero-inflation in the dataset. In an independent validation study, we used residential histories to estimate exposure in each year prior to diagnosis. Air releases with positive associations in both the SYMPHONY analysis and the spatio-temporal validation study included styrene (false discovery rate (FDR) 5.4e-5), chromium (FDR 2.4e-4), nickel (FDR 1.6e-3), and dichloromethane (FDR 4.8e-4). Using a large de-identified healthcare claims dataset, we identified geospatial environmental contaminants associated with ALS. The analytic pipeline used may be applied to other diseases and identify novel targets for exposure mitigation. Our results support the future evaluation of these environmental chemicals as potential etiologic contributors to sporadic ALS risk.

Sixteen paired surface sediment samples (0–5 cm, n = 32) covering upstream to downstream of water-level-fluctuation zone of Three Gorges Reservoir, China were collected in March 2018 (following six months of submergence) and September 2018 (after six months of exposure). Seventeen per- and poly-fluoroalkyl substances (PFASs) were quantified to evaluate contamination characteristics, apportion source categories and estimate mass inventory and loadings. The concentration of ΣPFASs ranged from 0.26 to 0.82 ng·g⁻¹ at high water-level (HWL) and 0.46–1.53 ng·g⁻¹ at low water-level (LWL). Perfluorooctanoic acid (PFOA, mean: 0.32 ng·g⁻¹) and perfluorooctane sulfonate (PFOS, mean: 0.12 ng·g⁻¹) dominated, accounting 44.9% and 16.3% of the total PFASs, respectively. The distribution of PFASs was more influenced by anthropogenic activities than physicochemical parameters of the sediments. Positive matrix factorization (PMF) identified PFOA-based products was the major sources (40.1% and 38.6%, respectively). Besides, the direct sources of PFOA-, PFOS-, PFNA-and PFBA-based products played the predominant role, while the indirect degradation of precursors contributed relatively little. The sediment (0–5 cm) mass inventory of PFASs at LWL (57.5 kg) was higher than HWL (39.3 kg). The annual mass loadings of the total PFASs, PFOA, PFOS, perfluoroundecanoic acid (PFUdA) and perfluorononanoic acid (PFNA) from the upstream to the middle-lower reaches of Yangtze River were 27.4 kg, 11.1 kg, 4.63 kg, 2.89 kg and 2.57 kg, respectively. This study could provide the basic datasets of PFASs in surface sediments of the TGR, and also indicate an important transport of PFASs from upstream to the lower reaches, which should be further studied as well.

Copper-containing antifouling paints (AFP) are widely used for leisure boat maintenance. Cu emitted from AFP into German surface water bodies has been suggested to be a significant source of heavy metal pollution, threatening water quality. We developed two scenarios to model Cu emissions from AFP applied on leisure boats on national scale, which allow identifying regional hotspots. The top-down approach (scenario A) was based on a previous study on national AFP consumption, while in the bottom-up approach (scenario B), median and interquartile range of Cu release rates depending on salinity conditions were considered for emission estimation. Both scenarios clearly highlighted the locally high emission pressure on inland waters in popular watersport regions, identifying these as requiring intense protection. Scenario B generally predicted lower Cu emissions (sea: 11.05–25.53 t a⁻¹, inland: 14.15–34.59 t a⁻¹) than scenario A (sea: 22.53 t a⁻¹, inland: 47.97 t a⁻¹). To evaluate their relevance, scenario results were compared to emissions modelled with MoRE (Modelling of Regionalized Emissions), which is used as reporting tool on substance emissions by Germany. According to scenarios A and B, the emission from AFP accounted for 13 % and 4–9 % of the total Cu emissions into inland waters in 2016, respectively. Scenario results were similar or higher than other emission pathways such as industrial direct dischargers. Thus, we consider Cu emissions from AFP as a significant pathway to be included in the MoRE emission inventory. We recommend scenario B for implementation as it allows a more flexible adaptation for future modelling.

China has been famous for its porcelains for millennia, and the combustion processes of porcelain production emit substantial amounts of air pollutants, which have not been well understood. This study provided firsthand data of air pollutant emissions from biomass porcelain kilns. The emission factor of PM₂.₅ was 0.95 ± 1.23 g/kg during the entire combustion cycle, lower than that of biomass burning in residential stoves and coal burning in brick kilns, attributed to the removal effects of the long-distance transport in dragon kilns. The temporal trend of particle pollutants, including particulate matters (PMs) and particulate polycyclic aromatic hydrocarbons (PAHs) (low at ignition phase and high at the end) again indicated the removal effects of the special structure, while gaseous pollutants, such as gaseous PAHs, exhibited the opposite result. The GWC₁₀₀ was estimated as 1.4 × 10⁶ and 0.5 × 10⁶ kg CO₂e/yr for the scenarios in which 50% and 100% of the wood was renewable, respectively. The GWC₁₀₀ of dragon kilns is nearly equal to that of 745 households using wood-fueled stoves. These results indicate the necessity of pollution controls for biomass porcelain kilns to estimate the emission inventory and climate change.

From 2015 to 2017, China took strong air pollution control measures (APCMs) for coal-fired industrial boilers (CFIBs), including eliminating CFIBs, promoting clean fuels, and updating air pollution control devices (APCDs). Based on the industrial boiler’s emission inventory of air pollutants, measure-specific emission reductions from 2015 to 2017 was estimated in this study. Besides, the measure-specific environmental benefits of unit emission reduction on concentration and deposition flux were systematically evaluated by WRF-CMAQ model. The total emission reductions for CFIBs of PM₁₀, PM₂.₅, SO₂, NOx, Hg, As, Cd, Cr and Pb from 2015 to 2017 were 1.2 Tg, 0.53 Tg, 2.06 Tg, 0.65 Tg, 37.6 tons, 179.5 tons, 17.9 tons, 1029.3 tons and 676.0 tons, respectively. Based on meteorological fields in 2017, their corresponding national population-weighted mitigated concentration was 1.8 μg m⁻³, 1.3 μg m⁻³, 3.6 μg m⁻³, 0.6 μg m⁻³ (NO₂), 0.076 ng m⁻³, 0.37 ng m⁻³, 0.04 ng m⁻³, 1.83 ng m⁻³ and 2.3 ng m⁻³, respectively. Updating APCDs was identified as the major measure to reduce air pollutants (except NOₓ), accounting for more than 35% of emission reductions and mitigated concentration. Moreover, elimination was the major NOx reduction method, contributing to 55% of NOx emission reductions. The promoting of fuels, including replacement of CFIBs with gas-fired and biomass-fired industrial boilers, had higher environmental benefits for unit emission reductions. Furthermore, there were still more than 43,000 CFIBs with the capacity <10 t h⁻¹, accounting for 14%, 21%, and 11% of total PM₂.₅, SO₂, and NOX emissions for CFIBs in 2017; meanwhile, 20% and 59% of CFIBs did not install flue gas desulfurization and denitrification devices, respectively. Therefore, it is recommended to give priority to phase out CFIBs with capacity <10 t h⁻¹ and APCDs updating for larger capacity CFIBs in the future.

The infrastructures of coal-fired power plants in China have changed significantly since 2010, but the magnitude and characteristics of polycyclic aromatic hydrocarbon (PAH) emissions remain to be updated. In the present study, a unit-based PAH emission inventory for coal-fired power plants between 2010 and 2017 was constructed for Anhui Province, China. Atmospheric PAH emissions from pulverized coal (PC) and circulating fluidized bed (CFB) units in 2017 were 8600 kg and 7800 kg, respectively. The emission rates and intensities for CFB units (7.2 kg ton⁻¹ and 2.1 kg MW⁻¹) were significantly higher than those for PC units (1.1 kg ton⁻¹ and 0.19 kg MW⁻¹), primarily because CFB boilers were operated at lower combustion temperatures and poor combustion conditions compared to PC boilers. The distribution patterns of PAH emissions across different age groups largely reflected the time periods for constructing coal-fired units in Anhui and for the transition of small units to large ones. The accomplishment of ultralow emission technologies and phase-out of outdated coal-fired units were responsible for the decreasing trend of PAH emissions between 2012 and 2017. The warmer summer in 2013 and 2017 and colder winter in 2011 compared to other years probably caused increased use of air conditioners, resulting in increased electricity consumption and PAH emissions. Future PAH emissions would decrease by 45–57% during 2017–2030, benefitting from power plant fleet optimization, i.e., phasing out outdated coal-fired units and replacing them with large ones. With the best available optimized power plant fleets and end-of-pipe control measures accomplished in Anhui’s CFPPs, PAH emissions in 2030 would potentially be reduced by 56–65%.

Black carbon (BC) is the most potent light-absorbing component of particulate matter and can have a significant warming impact. On-road vehicles are a major source of BC and a significant contributor to global warming. This paper establishes an updated inventory to quantify the mitigation potential of efforts to control BC emissions from on-road transportation in China. The total emissions of BC from on-road vehicles in China were 152.1 thousand tons in 2017. Heavy-duty diesel fleets accounted for a large percentage of emissions, whereas light-duty gasoline fleets presented a gradually increasing trend of emissions. Historically, comprehensive control policies for on-road vehicle emissions have achieved substantial BC reductions, with a 45% decrease in 2017 compared to 2000. With the implementation of stringent control policies and the development of advanced control technologies, BC emissions from the on-road sector may have a greater reduction potential in the future. By 2035, three various future scenarios representing different stringency levels of emission controls will reduce BC emissions by 58%, 90%, and 93% relative to 2017. The major benefits in reducing BC emissions result from more stringent emission standards and the accelerated retirement of older heavy-duty diesel vehicles. The shorter lifetime of BC than that of CO₂ implies that the mitigation of BC emissions would offer an important opportunity to contribute to alleviating global warming in the short term. Our assessment reveals that in 2035, the most stringent scenario, Scenario PC3, could deliver a CO₂-equivalent emission reduction on a 20-year scale of 234.2 (GWP₂₀₋yᵣ) million tons compared with the NAP Scenario, which is equivalent to reducing the oil consumption in China’s transportation sector by nearly 20% from a climate impact perspective.

Riverine nitrogen loading to the continental shelf sea is important for terrestrial–marine linkage and global nitrogen cycling and leads to serious marine environmental problems. The budget and cycle of riverine nitrogen over the continental shelf in the East China Sea (ECS) are unknown. Using the tracking technique within a physical–biological coupled model, we quantified the nitrogen budgets of riverine dissolved inorganic nitrogen (DIN) and particulate organic nitrogen (PON) over seasonal to annual scales in the ECS, especially from the Changjiang River, which plays a dominant role in riverine nitrogen input. The horizontal distributions of the Changjiang DIN and PON generally followed the Changjiang diluted water and coastal currents and were affected by stratification in the vertical direction. Their inventory variations were dominated by biological fluxes and modulated by physical ones, and changed most dramatically in the inner shelf among three subregions. Less than half of DIN were converted to PON with most of the rest leaving the ECS through lateral transport pathways, among which the flux through the Tsushima Strait was dominant. With the increasing loading of the Changjiang DIN flux from the 1980s–2010s, lateral transports rather than PON production increased due to limited primary production. Approximately 60 % of the produced PON exported to the sediment and 34 % went to the Tsushima Strait. According to the export production, the DIN from the Changjiang River contributed 12–42 % to the ECS carbon sequestration.

Biomass burning, a recurring global phenomenon is also considered an environmental menace, making headlines every year in India with onset of autumn months. Agriculture is demographically the broadest economic sector and plays a significant role in the overall socio-economic fabric of India. Hence, disposal of crop residue is done mainly by burning leading to deterioration of air quality. Residue burning in parts of India is blamed for changing air quality in nearby cities. The spatial distribution of these emissions has always been a challenge due to various data constraints. We hereby present a comprehensive spatially resolved seasonal high resolution gridded (∼10 km × ∼10 km) emission inventory of major pollutants from crop residue burning source in India for the latest year 2018. The winter months contributes almost around ∼50% of total emission followed by summer (∼48%), which is the prime cause of changing air quality in nearby cities. Among all the crops; rice, wheat, maize and sugarcane accounts ∼90% of total PM₁₀ load in the country. The estimated emission for PM₂.₅, PM₁₀, BC and OC, CO, NOx, SO₂, VOC, CH₄ and CO₂ are found to 990.68 Gg/yr, 1231.26 Gg/yr, 123.33 Gg/yr, 410.99 Gg/yr, 11208.18 Gg/yr, 484.55 Gg/yr, 144.66 Gg/yr, 1282.95 Gg/yr, 785.56 Gg/yr and 262051.06 Gg/yr respectively. The cropping pattern and its role in different geographic regions are analysed to identify all potential emission hotspots regions scattered across the country. The developed gridded emissions inventory is envisaged to serve as an important input to regional atmospheric chemistry transport model to better quantify its contribution in deteriorating air quality in various regions of India, paving the way to policy makers to better plan the mitigation and control strategies. The developed fundamental tool is likely to be useful for air quality management.