Industrial Emissions Research Articles

Pinus eldarica (L.) bark as urban atmospheric trace element pollution bioindicator: pollution status, spatial variations, and quantitative source apportionment based on positive matrix factorization receptor model.

In this study, a total of 180 Pinus eldarica bark samples were collected from different regions of Hamedan megacity, Iran, in 2023, and contents of Cd, Cr, Cu, Mn, Ni, Pb, and Zn in the samples were determined using ICP-OES. The results illustrated that the average contents of all the analyzed elements were greater than those in the background contents, which presumably demonstrated anthropogenic sources of these potentially toxic elements (PTEs). The greatest concentrations of the analyzed PTEs for different functional areas were observed in specimens collected from commercial or industrial areas, indicating the impact of human entries. The I-geo values were in the range of "unpolluted to moderately polluted" to "moderately to heavily polluted", PI showed "moderate to very high pollution", and PLI reflected high to very high pollution levels for the whole study area. Additionally, the cumulative mean value of ecological risk (RI) was found to be 152, demonstrating moderate ecological risk across the study area. The results of positive matrix factorization (PMF) showed that the PTE contamination in the air of Hamedan could mainly have an anthropogenic origin (82.7%) and that the traffic emissions as the primary pollution source (33.6%) make the highest contribution to the PTE pollution and ecological risks in the study area. In residential areas, demolition and construction activities could be considered the main sources of PTEs, while in commercial and industrial areas traffic emissions and industrial emissions, could be regarded as the main sources of such pollution, respectively. In conclusion, this study provides a useful approach to identifying the sources and contributions of the toxic elements in different functional areas and can inform future endeavors that aim at managing and controlling metal element pollution.

A study on long-term industrial electricity consumption and carbon emission forecasting methods based on TimesNet models

Abstract Aiming at the prediction problem of industrial electricity consumption and carbon emission, a TimesNet model is established to improve the accuracy of industrial electricity consumption and carbon emission prediction. Five significant influencing factors were screened out by grey correlation analysis; based on the energy consumption dataset of an iron and steel enterprise in 2023, the dataset was preprocessed and inputted into the TimesNet model, the prediction results were integrated and summarized, and the prediction results of the DLinear, LightTS, PatchTST, and iTransformer time series prediction models were compared and analyzed. The results show that the predicted values of the TimesNet model fit the actual values, and its mean absolute error (MAE), mean square error (MSE), root mean square error (RMSE), and mean absolute percentage error (MAPE) are 0.31, 0.36, 0.6, and 1.12, respectively, which are better than those of the other models. It proves that the model can predict industrial electricity usage and release of carbon more accurately, providing a practical method for industrial electricity usage and release of carbon prediction.

Distribution assessment and source apportionment of particulate bound-PAHs in indoor air of south Asian precinct using IDW and PMF receptor model: A comprehensivestudy

PAHs have been recognised as a major menace to living-beings as well as environment. Several researchers have extensively claimed regarding death-defying nature of PAHs and its derivatives. However, these studies have only considered the ambient air which is a composition of automobile exhausts, industrial emissions etc. as major source of harmful air pollutants. Indoor air quality (IAQ) is an overlooked area since, although many researchers in recent times have been working on the chemistry and composition of IAQ, yet, source determination and nature of pollutants is still a comprehensive area to be explored. With the above stated objective, the present study emphases on 16 USEPA specified PAHs which are allied with particulate matter. Both PM as well as PAHs are some very common and treacherous chemical contaminant accountable for more than a million death globally. PAHs are organic compound which are either attached to PM of various sizes or can exist in gaseous form. Current work precises the concentration of PAHs associated with fine PM i.e., PM2.5 in indoor environment of south Asian precinct, further, using receptor modelling technique for determination indoor sources responsible for the emanation of specific PAHs. The toxicity equivalent quotient i.e., TEQ evaluated in the study demonstrations that the highest toxicity among all PAHs is exhibited by BaP followed by InP, BKF, BbF. Seasonal variations in the concentration of PAHs and their respective sources were also established using PMF models, which depicted the domination of 3-ring PAHs in winter with 42% contribution in outdoors, whereas, four-ring PAHs dominion in indoors. Similarly, in summer two-ring accounted for 35% in outdoors, and three-ring PAHs contributed highest with 26.8% in indoors. In monsoon PAHs with two-ring contributed highest with 45.2% in outdoors, whereas, 2-ring PAHs contributed 38.3% in indoors. Also, IDW mapping and molecular diagnostic ratio were assessed for an intense study on distribution of PAHs in the locality and the source apportionment purpose respectively. To the best of our knowledge, the study is first of its kind in this part of the world where, majority of the countries are either developing or under-developed and hence at greater risk to the noxious effects which are often overlooked. The study will provide a clear picture regarding the indoor sources of the PAHs and further help the further professionals to build a credible and pragmatic mitigation technique accordingly.

An automated approach for carbon integration in industrial park

Industrial park is a hub for various industrial activities. Industrial emissions are one of the main sources of carbon emissions. The reduction of carbon emissions is crucial to achieve carbon neutrality for industrial parks. This paper presents an automated approach to maximize the utilization of CO2 among different plants in industrial parks through carbon allocation network. The minimum target of external fresh CO2 is determined based on automated composite table algorithm (ACTA), which is then materialized with the detailed design of carbon allocation network. A case study with four scenarios were analyzed to systematically guide the carbon reduction process towards its carbon neutrality target. Direct utilization scenario refers to CO2 utilization between sources and sinks in the parks without any purification scheme. Sink manipulation and source reduction scenarios indicate that process parameter changes, equipment modifications and other measures in the sinks or sources lead to the reduction of CO2 demands or supplies. In the purification scenario, CO2 is purified to different concentrations to maximize its allocations among different plants. A case study based on chemical industrial park in Fuyang, China is presented to illustrate the approach. Four factories (coal-fired power, cement, ammonia, ethanol) were identified as carbon sources, while three others (urea, methanol, dimethyl ether) as carbon sinks. By implementing sink manipulation and source reduction, the fresh CO2 resources and CO2 emissions are effectively reduced to 205.25 t/h and 149.61 t/h, respectively. The result for purification scenario indicates that CO2 emissions can be decreased from 317.33 t/h to 105.72 t/h, with an overall reduction of 66.68 %, while the fresh carbon requirement is reduced from 357.41 t/h to 161.34 t/h. This work provides a useful tool for the utilization of excess CO2 within an industrial park.

A real-time estimation method of carbon emission for cement corporations based on load identification

Abstract Accurate carbon emission estimation is the basis for assessing the carbon emissions of various regions and industries and formulating reasonable and feasible emission reduction programs. This paper presents a generalized real-time corporate carbon footprint measurement method. The total carbon emissions are categorized into direct emissions and indirect emissions. For the former, a load identification method based on CNN-BLSTM is proposed to monitor the state of the devices, and the carbon emissions are directly calculated in combination with the carbon emission intensity of the devices; for the latter, accurate estimation of carbon emissions is achieved through the application of marginal carbon emission factor. By utilizing this analytical model, the estimated carbon emissions are more accurate than those of other methods, which can better grasp the carbon emissions of enterprises and promote energy saving and emission reduction.

Does Scaling Up Pig Farming Promote Carbon Neutrality Among Pig Farmers?

Pig farming is a major source of carbon emissions in China's livestock industry, and the promotion and application of carbon neutral technologies dedicated to carbon reduction and sequestration is a key measure to promote the realization of carbon neutrality in pig farming industry. In the absence of a system for carbon emission reduction in agriculture, it is important to explore whether large-scale pig farming can spontaneously promote the application of carbon neutral technologies by pig farmers. Combined with the technical background of carbon neutrality in pig farming industry and using the field survey data of 468 pig farmers in Shandong Province, this paper empirically analyzed the effect of large-scale pig farming on the carbon neutral behavior of pig farmers. The findings are threefold. Firstly, because of the effect of economies of scale in the application of carbon neutral technologies, large-scale pig farming can promote the carbon neutral behavior of pig farmers. However, the effect of economies of scale in the application of carbon neutral technologies has a boundary, and the annual output of pigs should be maintained at 3000 to 4999. Secondly, among the effects of pig breeding scale on the application and its degree of composting project, state of planting and breeding cycle has no regulating effect. Thirdly, among the effects of pig breeding scale on the application and its degree of biogas engineering, both state of planting and breeding cycle and subsidy for construction of biogas digester have negative regulating effects. In this paper, the pig farming industry is taken as a typical example to reveal the endogenous incentive mechanism of promoting agricultural carbon emission reduction, which provides theoretical reference and experience enlightenment for the formulation of effective policies to promote agricultural carbon neutrality, which are different from industrial industries.

Linking animal and human health burden: challenges and opportunities.

Quantifying the impact of poor animal health outcomes on human health represents a complex challenge. Using the disability-adjusted life year (DALY) metric as an endpoint, this article discusses how animal health outcomes can impact humans through three key processes: directly through zoonotic disease, indirectly via changes in yields and their impacts on nutrition and wealth, and finally, through indirect features associated with the agricultural industry, such as pharmaceuticals and climate change. For each process, the current state of the art and feasibility of global DALY-associated estimates are discussed. Existing frameworks for zoonoses already consider some key pathogens; ensuring completeness in the pathogens considered and consistency in methodological decisions is an important next step. For diet, risk factor frameworks enable a calculation of attributable DALYs; however, significant economic methodological developments are needed to ensure that local production changes are appropriately mapped to both local and global changes in dietary habits. Concerning wealth-related impacts, much work needs to be done on method development. Industry-related impacts require a focus on key research topics, such as attribution studies for animal antimicrobial resistance contributing to human outcomes. For climate change, a critical next step is identifying to what extent associated industry emissions are amenable to change should animal health outcomes improve. Allocation of finite funds to improve animal health must also consider the downstream impact on humans. Leveraging DALYs enables comparisons with other human health-related decisions and would represent a transformative way of approaching animal health decision-making should the obstacles in this article be addressed and new methods be developed.

Study on the establishment of air pollutant and carbon emission inventory and collaborative emission reduction potential of China's coking industry from 2012 to 2022

Coking industry is usually regarded as a high pollution and high energy consumption industry. China is accelerating its efforts to reduce pollution and carbon emissions in the industrial sector, which has received little attention as the world's largest producer of coke. Therefore, in this study, the trend of air pollution and carbon emissions in China's coking industry and the path of coordinated emission reduction were studied. The results indicate that the average annual emissions of PM, SO2, NOx, VOCs, and CO2 in China's coking industry from 2012 to 2022 amount to 205.98, 69.47, 193.45, 599.80 Gg and 191.10 Tg, respectively. The main sources of PM, SO2, NOx, VOCs and CO2 in coking industry were coal preparation (51.5 %), charge and pushing (39.5 %), coke oven gas (99.8 %), byproduct recovery (47.0 %) and fuel combustion (87.5 %). The emissions from coking plants in central and southern Shanxi, eastern and southern Hebei, and central Shandong are the most concentrated. Ultra-low emission transformation and deep treatment of VOCs have greatly reduced pollutant emissions in key areas of air pollutant control, but the actual emission reduction effect of these measures has been weakened by the additional emissions caused by the increase of coke production in other non-key areas. The research on synergetic emission reduction path shows that there is a great synergistic benefit between air pollutants and CO2 emission reduction in coking industry. It is estimated that the APeq (air pollutants and carbon equivalent) of China's coking industry in 2025, 2028 and 2030 will decrease by 38.2 %, 63.5 % and 70.8 % respectively compared with 2022. With the continuous promotion of pollution reduction and carbon reduction measures, the emission reduction potential of China's coking industry will gradually shift from key areas to non-key areas.

Environmental Performance of Ammonia Production in Indonesia using Life Cycle Assessment Approach

Ammonia is a fundamental component in fertilizer and chemical manufacturing processes around the world, but its production is a significant contributor to CO2 emissions in chemical industry. Implementation of carbon capture utilization and storage (CCUS) offers an alternative decarbonisation strategy to mitigate CO2 emissions in ammonia production. This study assesses the environmental performance of ammonia production through life cycle assessment (LCA) methodology. Environmental impacts are calculated using openLCA software with various impact assessment methods, including CML IA Baseline, Impact 2002+, Recipe 2016 Midpoint (H), and AWARE. The study scope encompasses the cradle-to-grave analysis, from the extraction of raw materials and transportation to ammonia production, main processes, distribution, and consumer product consumption, with a declared unit of 1-kg ammonia product. Our findings showed that CO2 removal and Power Plant in core processes in the core process as the most significant contributors to Global Warming Potential. Therefore, sensitivity analysis was conducted by reducing CO2 emission by 10% and 70% through CCUS implementation. The results showed that the CCUS implementation could reduce Global Warming Potential by up to 43%.

The application of green hydrogen in iron ore smelting under the target of carbon neutralization

Currently, green development and sustainable development have become a global consensus. In March 2023, the Intergovernmental Panel on Climate Change (IPCC) released the sixth comprehensive assessment report Climate Change 2023, which pointed out that greenhouse gas emissions are currently at the highest level in human history, and the global temperatures has been about 1.1 higher than that before industrialization. In July, 2023, the government of China also emphasized that the construction of ecological civilization in China has entered a critical period with carbon emission reduction as the focus. According to the survey, the steel industry in China has the highest carbon emission in manufacturing industry, and it is also one of the most important areas for China to deal with climate change. Based on the basic principle of blast furnace iron making, this paper first analyzes the causes of high emissions in the steel industry, and draws the conclusion that hydrogen metallurgy technology must be developed to achieve low-carbon development; Then, depending on different energy endowments, the differences in metallurgical technology between China and other countries are analyzed, and brief conclusions and suggestions are given on the basis of analyzing the challenges faced by low-carbon development of Chinas steel industry. This study provides insights into the importance of hydrogen metallurgy technology and enhance our understanding of how to achieve low-carbon development in Chinas iron and steel industry.

Industrial Intelligence and Carbon Emission Reduction: Evidence from China’s Manufacturing Industry

Industrial Intelligence and Carbon Emission Reduction: Evidence from China’s Manufacturing Industry

PERHITUNGAN EMISI GAS RUMAH KACA DALAM KAWASAN PERTAMBANGAN

Carbon emissions are one of the components of greenhouse gas (GHG) emissions in the form of carbon dioxide (CO2) which mainly comes from the use of fossil fuels and various human activities. Based on fossil fuel and industrial emissions data, in 2022 Indonesia ranked as the 6th largest carbon emitting country in the world after China, the United States, India, Russia and Japan, with 728.88 million tons of CO2e total emissions. The Ministry of Industry reported that total GHG emissions from Indonesia's industrial sector reached 238.1 million tons of CO2e in 2022. In the mining industry, GHG emissions originate from deforestation, energy use, processing, and refining, with non-renewable energy use being the largest emitter. GHG emissions from primary mineral and metal production contribute approximately 10% of global GHG emissions related to energy. Each mining industry may have varying primary sources of GHG emissions depending on the type of mine and the final product. Mining industries, as one of the major emitters, must conduct GHG inventories to understand emission sources and develop effective reduction strategies. GHG inventory activities are conducted based on guidelines provided by the Ministry of Environment and Forestry's National Greenhouse Gas Inventory Management Handbook (2012), Book II Volumes 1-4. Efforts to reduce GHG emissions can be undertaken through planting plants that have high carbon absorption and storage capabilities in mine reclamation activities, as well as using New and Renewable Energy (NRE) as an alternative to replace fossil energy.

Climate change and its impact on women's living

Climate change is one of the biggest global health threats to the world’s population. Global warming can occur largely due to increased levels of greenhouse gases caused by human activities and conditions such as the burning of fossil fuels (carbon dioxide), livestock (methane from manure), industrial emissions, vehicle/factory exhaust and chlorofluorocarbon aerosols that trap extra heat in the Earth’s atmosphere. The resulting extreme weather conditions lead to uncontrollable fires, air pollution, ecological changes and floods. The realization of ecological changes has major impacts on population displacement, family fragmentation, violence, water availability and quality, food security, public health and economic infrastructures. The consequences of ecological changes affect public safety and their ability to maintain health. Climate change also has direct impacts on human health and well-being. Particularly vulnerable populations are affected, including women, pregnant women, children, persons with disabilities and the elderly, who make up the majority of disadvantaged populations globally. In addition, when disasters occur, communities of different ethnic groups, low-income and disadvantaged individuals are more affected by climate change challenges. The climate crisis negatively alters the balance of risk for women’s sexual and reproductive health and rights, as well as for newborn and child health. Obstetric nurses and midwives have a unique opportunity to raise awareness, educate and advocate for mitigation strategies to reverse climate change affecting patients and their families. The objective of this review is to examine the circumstances under which climate change may emerge as a significant public health, social justice, human rights, economic, and women’s health challenge. The FIGO reports that the current climate crisis poses an imminent health risk to pregnant women, developing fetuses, and reproductive health, and calls for community-wide solutions, government policies, and global action.

Role of green and sustainable practices in shaping the future of medical imaging technology: A cross-sectional multi-stakeholder analysis among students, radiographers, and academic experts

IntroductionThe detection and treatment of diseases like COVID, diabetes, cancer, cardiovascular conditions, etc., have made medical imaging technology more necessary, so it is expected that the demands of imaging modalities are also increasing and are major contributors to carbon emissions in the healthcare industry. Hence, the Radiology departments, like the rest of the healthcare industry should adapt the procedures to become more sustainable. MethodsA total of 1016 respondents completed the online survey to assess the perception, current practices, and challenges in adopting green and sustainable practices in medical imaging. The radio technologists, teaching faculties, and students of medical imaging were recruited for the study. The survey tool was distributed to the closed groups through social media and emails. ResultsThe majority of participants (66.6%) highlighted the importance of green and sustainable practices in medical imaging whereas only 21.06% of participants seem to have implemented these practices. Most of the participants give positive responses on the use of zero-lead aprons (77%), refurbished medical systems (85.8%), and eco-friendly packaging (89.5%). The mixed response was received from waste segregation and energy-saving measures. The majority (60.3%) of them have no formal education or training. However, they have a good attitude towards the willingness to adopt green practices. ConclusionsThere is a gap between perception and implementation of green and sustainable practices due to leadership and information barriers. Comprehensive training for stakeholders of medical imaging is crucial to fully integrate sustainability practices, possibly through webinars or educational modules. Implications for practiceThe study's findings shed light on how important medical imaging stakeholders view green and sustainable practices as well as potential obstacles to their implementation at the local level whilst suggesting the need for exclusive training on these practices to promote sustainability.

Exploring the spatio-temporal driving mechanism of multi-dimensional urbanization on urban residential buildings based on GTWR: a case study of China

ABSTRACT Examining how urbanization affects carbon emissions in the construction industry is crucial for China's efforts to achieve environmentally friendly and low-carbon growth. Nevertheless, current research predominantly employs a unidimensional approach to gauge urbanization, overlooking the nuanced characteristics of novel urbanization. This study explored the spatial and temporal characteristics of the impact of urbanization on carbon emissions from urban residential buildings from a multidimensional perspective, starting from five dimensions: population, economy, land, life, and ecology, using a spatial–temporal geographically weighted regression model (GTWR) and panel data from 30 provinces in China for the period 2010–2020. The findings of this study revealed that, on the whole, population urbanization, land urbanization, and lifestyle urbanization exert a significant facilitating influence on carbon emissions from urban residential buildings. Conversely, economic urbanization exhibits a notable inhibitory effect on carbon emissions from urban residential buildings. Furthermore, ecological urbanization transitions from an inhibitory effect to a promoting effect on carbon emissions from urban residential buildings. The impact of urbanization across various dimensions on carbon emissions from urban residential buildings displays spatiotemporal heterogeneity across different regions and periods. In addition, the structure of energy consumption is a contributing factor to the increase in carbon emissions from urban residential buildings, while there is a notable U-shaped relationship between the level of foreign investment, the industrial structure, and carbon emissions originating from urban residential areas. This study offers profound insights into the relationship between urbanization and carbon emissions, providing valuable guidance for policymakers.

The impact of hydrogen fuel cell heavy-duty trucks purchase subsidies on air quality.

The pollutant emissions of diesel-powered heavy-duty trucks (HDTs) seriously damage the air quality. The promotion of hydrogen fuel cell HDTs through purchase subsidy policy to reduce emissions has become an important approach to control air pollution. This study focuses on the impact of hydrogen fuel cell HDT purchase subsidies on air quality in the context of China, covering the panel data of 31 Chinese cities from 2014 to 2021 and applying a two-way fixed effects model to analyze the contribution of purchase subsidies and hydrogen refueling station construction subsidies to air quality. Results show that (1) the increase in purchase subsidies could improve the air quality by around 6.1% and there is a lag effect. (2) Purchase subsidies make a larger contribution to air quality compared with construction subsidies. (3) Purchase subsidies can improve air quality by reducing carbon emissions in transport industry. In sight of these results, policy makers should emphasize the implementation of purchase subsidies and hydrogen refueling station construction subsidies and stimulate manufacturers to improve the performance of hydrogen fuel cell so as to contribute more to the environment.

A novel green learning artificial intelligence model for regional electrical load prediction

Load prediction is crucial to unit commitment and scheduling in electricity systems; however, load prediction models consume considerable electricity. Most conventional prediction methods are based on deep learning (DL) models, such as long short-term memory and gated recurrent units. The nonlinear activation functions and backpropagation mechanisms used in these methods result in high computational complexity and correspondingly high energy consumption. This paper proposes a prediction model based on a green learning (GL) framework aimed at reducing energy consumption. The proposed GL model replaces the activation functions conventionally used for feature extraction with a hybrid scheme combining categorical and numerical features, such as seasonal climate features and multi-autoregression terms. The proposed GL model also eliminates the backpropagation methods used to optimize hyperparameters by employing seasonal centroids and the quantile auto-regression forest algorithm for classification/regression. In a case study, the proposed GL model significantly outperformed conventional DL models in terms of energy consumption without compromising accuracy. The energy savings of the proposed GL model are equivalent to the annual electricity consumption of 211 ∼ 565 households, increasing with model penetration. This paper demonstrates the importance of energy-saving models in mitigating the linkage effect of industrial carbon emissions. It also explores policy implications for the implementation of GL models.

Rebuilding with sand roses: Cold sintering of sand-gypsum mixture for sustainable brick production

In the arid climate of the Sahara Desert, several historical cities dating back to the 16th century were constructed using bricks made from sand roses, a rosette-like rock composed of sand and gypsum. This study proposes the cold sintering of sand – dihydrate gypsum (uncalcined) mixtures as a sustainable approach to develop geomimetic sand roses with satisfactory mechanical performance. The results showed that crucial factors for enhancing the unconfined compressive strength (UCS) of the cold-sintered sand-gypsum mixtures are reducing gypsum size, utilizing cyclic loading, and applying higher pressures. Reducing sand size or introducing lubricant has minimal or negative effects. Cold-sintered sand-gypsum mixtures containing over 30 % micron-sized gypsum, subjected to cyclic pressures of 100 MPa for 15 minutes, can achieve superior UCS values compared to equidimensional concrete bricks. In addition, coating the mixture with calcium carbonate can be a viable approach for protecting against weathering agents. Coating and recycling the sand-gypsum mixture do not compromise the mechanical performance of the bricks. The proposed integration of sustainable materials and manufacturing practices has the potential to reduce costs, energy consumption, and industrial emissions, while promoting a circular economy and resource preservation. The proposed brick is referred to as “sand rose brick.”

Exploring the potential of boron-nitride nanobelts in environmental applications: Greenhouse gases capture

This study examines boron-nitride nanobelts, including Möbius-type, for capturing and detecting nine greenhouse gases (ammonia, carbon dioxide, carbon monoxide, hydrogen sulfide, methane, methanol, nitric dioxide, nitric oxide, and phosgene). Negative adsorption energies indicate favorable adsorption on both nanobelt types. The systems show recovery times ranging between 2 h to few nanoseconds. Only nitric oxide forms covalent bonds; other gases interact non-covalently. Molecular dynamics simulations reveal consistent single-molecule interactions and attractive forces with multiple molecules. Semi-empirical tight-binding methods, as implemented in the xTB software were used for computational efficiency. Results demonstrate the potential of boron-nitride nanobelts for environmental monitoring and remediation of industrial toxic gas emissions, addressing concerns about human health and environmental impact.

Deployment expectations of multi-gigatonne scale carbon removal could have adverse impacts on Asia’s energy-water-land nexus

Existing studies indicate that future global carbon dioxide (CO2) removal (CDR) efforts could largely be concentrated in Asia. However, there is limited understanding of how individual Asian countries and regions will respond to varying and uncertain scales of future CDR concerning their energy-land-water system. We address this gap by modeling various levels of CDR-reliant pathways under climate change ambitions in Asia. We find that high CDR reliance leads to residual fossil fuel and industry emissions of about 8 Gigatonnes CO2yr−1 (GtCO2yr−1) by 2050, compared to less than 1 GtCO2yr−1 under moderate-to-low CDR reliance. Moreover, expectations of multi-gigatonne CDR could delay the achievement of domestic net zero CO2 emissions for several Asian countries and regions, and lead to higher land allocation and fertilizer demand for bioenergy crop cultivation. Here, we show that Asian countries and regions should prioritize emission reduction strategies while capitalizing on the advantages of carbon removal when it is most viable.