Under the impact of the coronavirus disease 2019 (COVID-19), green, low-carbon, and sustainable development has become a global consensus, and the world will enter a low-carbon and intelligent production mode faster. As the largest contributor to world economic growth and an active participant in global environmental governance, achieving green recovery and the high-quality economic and social development of China is of great significance to promote the global sustainable development strategy. The green transformation of resource-based cities in Western China is the key factor for China to build a high-quality modern economic system and promote long-term sustainable development. This article used the Super Efficiency Slack Based Model (Super-SBM) model and Malmquist index model of the Data Envelope Analysis (DEA) method to measure the static and dynamic green transformation efficiency of resource-based cities in Western China. It investigated the impact of different factors on the static and dynamic efficiency by constructing panel Tobit and dynamic panel models. The research found that the static efficiency of the green transformation of resource-based cities in Western China is low, and the development is uneven. The dynamic efficiency of green transformation showed a fluctuating upward trend first and an accelerating upward trend later. Different factors have different effects on green transformation efficiency. This article holds that the combination of post-epidemic economic recovery and green transformation is expected to promote the green transformation of western resource-based cities while injecting new vitality into China's green sustainable development in the post-COVID-19 era. In 2018, at the National Conference of Ecological and Environmental Protection in China, General Secretary Xi Jinping pointed out that green development is necessary for building a high-quality modern economic system and a fundamental solution for solving pollution problems. Therefore, green development policy should be comprehensively implemented in the future. It can be seen that green transformation is the only way for China's society and economy to move toward high-quality and sustainable development. In recent years, with the advancement of the Green Belt and Road Initiative, sustainable development continues to rise in the western region. As essential strategic support for national energy resources, resource-based cities in Western China have made significant contributions to China's economic and social development. In 2020, the sudden outbreak of the coronavirus disease 2019 (COVID-19) swept the world. To block the spread of the virus, the world had to enter the epidemic prevention and control the situation through blockades and other measures, and the economic and social development was greatly interrupted. The traditional extensive economic growth model with high energy consumption, high pollution, and long-term negative impact of environmental degradation makes the green transformation of western resource-based cities even worse. With the pressure and challenges in choosing “clear waters and green mountains” and “mountains of gold and silver,” the green transformation and development of resource-based cities have become an important and arduous task for the western region. In this context, it is of great practical significance to comprehensively understand and evaluate the pattern of green transformation of resource-based cities in western China, deeply explore the different influencing factors on green transformation and development, accelerate the green transformation of western resource-based cities, and provide decision-making support for high-quality development.Green transformation is a concept of social transformation and development arising from the natural capital constraint in recent years . ResearcThe research and evaluation methods of green transformation in academia are mainly divided into two categories. One is to build a multi-dimensional logical framework and evaluation system of green transformation. For example, Chinese scholar Liu innovatively constructed a three-dimensional structural model of green transformation, including cause dimension, method dimension, and effect dimension, and evaluates the green transformation of resource-based cities from various angles, which has been recognized and used for reference by many scholars in the academic circle . Xiao etAs green transformation is a hot topic of the academic circle in recent years, the relevant research conclusions are very rich. Most scholars choose one or two entry points to investigate the green transformation and development of the region, such as the Porter Hypothesis, financial development and environmental regulation (ER), carbon peak and carbon neutrality, and so on –23. HoweThrough the review and analysis of relevant literature, it can be found that the academic research on green transformation and development has never been interrupted and achieved a lot. On the whole, although the research direction and focus of scholars in various countries are different, the ultimate purpose is to achieve the optimization of resource utilization and promote the sustainable development of society. Existing research results provide great reference and guidance for this article, but we still found the following limitations after analysis: firstly, when investigating the green transformation of resource-based cities in China, the focus is mostly on resource-based cities in a certain province or a specific province as the research object, and there are only a few research on the green transformation and development of resource-based cities in the western region; secondly, there are few evaluations on the efficiency characteristics of the green transformation of resource-based cities, and most of the existing documents only measure one of the annual efficiency or the inter-period efficiency, and the comprehensiveness of the efficiency measurement is insufficient.Therefore, based on the existing literature, this article attempts to enrich the existing research from the following two aspects: first, 38 resource-based cities in western China were selected for green transformation evaluation to enrich the regional research system of resource-based cities' green transformation in China. Second, the efficiency characteristics were used to evaluate the green transformation, and the efficiency was further divided into static efficiency and dynamic efficiency, so as to more comprehensively investigate the green transformation achievements of resource-based cities in western China. By constructing the evaluation index system of green transformation efficiency, two models under the DEA method were used to measure the two efficiencies of green transformation of resource-based cities in western China, and use the panel Tobit model and dynamic panel model to make a regression analysis on the influencing factors on green transformation efficiency. Combined with the empirical results, this article can provide a reference for formulating a more targeted and illuminating green recovery plan and realizing high-quality and sustainable development as soon as possible in the western region and even the whole country in the post-epidemic era.In the National Sustainable Development Plan for Resource-Based Cities (2013–2020) issued by the State Council of China in November 2013, 262 cities were classified as resource-based cities nationwide. There are 102 resource-based cities in the western region, including 48 prefecture-level cities . Based on research practice and data availability, this article finally selected 38 prefecture-level resource-based cities as the research object: Baotou, Wuhai, Chifeng, Ordos, Hulunbuir, Baise, Hezhou, Hechi, Zigong, Panzhihua, Luzhou, Guangyuan, Nanchong, Guang'an, Dazhou, Ya'an, Liupanshui, Anshun, Qujing, Baoshan Zhaotong, Lijiang, Lincang, Tongchuan, Baoji, Xianyang, Weinan, Yan'an, Yulin, Jinchang, Baiyin, Wuwei, Zhangye, Pingliang, Qingyang, Longnan, Shizuishan, and Karamay.The Data Envelopment Analysis (DEA) is a non-parametric technical efficiency analysis method that compares evaluated objects . It usesThe DEA method was first proposed by the famous American operational research scientists Charnes, Cooper, and Rhodes in 1978 . BecauseUj; each DMU has m inputs, denoted as xi; there are r1 kinds of desirable outputs, denoted as ys; there are r2 kinds of undesirable outputs, denoted as yq; x, yd, yu represent the elements in the corresponding input matrix, desirable output matrix, and undesired output matrix; the current DMU to be measured is denoted as DMUk, then the model is obtained:Suppose the number of evaluated DMUs is n, denoted as DMj is the weight vector.In Formula (1), θ represents the comprehensive technical efficiency (TE) under constant return to scale (CRS), which refers to the static efficiency of the green transformation of resource-based cities in Western China. By comparing the productivity in two periods, the Malmquist total factor productivity index analysis method can objectively reflect the changes in productivity and the effects of technical efficiency and technological progress on the changes of productivity. Therefore, MI is considered as a supplement for the DEA method. The global reference Malmquist model is an MI calculation method proposed by Pastor and Lovell in 2005: the sum of all periods of the evaluated DMU can be used as the reference set, which means that each period takes the same global frontier as reference . As a ret to t +1 under CRS is obtained [29]:Combined with Pastor's and Lovell's research results, the global reference MI period MIg represents the MI value, which is the dynamic efficiency value of green transformation of resource-based cities in western China.In Formula (2), According to the concept of the “two mountains theory,” this article believes that the essence of measuring the green transformation efficiency of resource-based cities is to achieve the maximum economic and green output with the least factor input and ecological environment loss, and balance the “clear waters and green mountains” and “mountains of gold and silver” in the process of green transformation and development of western resource-based cities.(1) Input indicators. Input indicators include labor, capital, energy, and land inputs. Combined with the existing research results, labor input is calculated by the total number of people employed in the whole society over the years in each city –32. Capi(2) Output indicators, including desirable output and undesirable output. Desirable output refers to the total economic output and green area of built-up area, and undesirable output refers to three environmental pollution indicators: “waste gas,” “wastewater,” and “smoke (powder) dust” (hereinafter referred to as “three wastes”). According to the existing research results, the total economic output can be measured by the gross domestic product (GDP) of each city –35. ThenIn this article, the green transformation efficiency (including static efficiency and dynamic efficiency) of resource-based cities in Western China is taken as the explained variable. Based on current research results, advanced industrial structure (AIS), regional openness (RO), technological innovation (TI), ER, level of economic development (GDPP), level of urbanization (URB), and human capital (HC) are selected as explanatory variables  36–39).–39.36–39TEit represents the static efficiency value, which is the actually observed explained variable. Xit represents the set of influencing factors. i and t represent region (city) and period (year), respectively. α is the regression coefficient. The random disturbance term εit obeys the normal distribution with mean value 0 and variance σ2. When the latent variable TEit is equal to TEit is equal to 0.In Formula (3), There may be a lag in the dynamic development process of urban green transformation efficiency in the actual social development process. Therefore, this article introduces the first-order lag term of the explained variable MI in the dynamic efficiency model to accurately obtain the dynamic panel model and regression result as Formula (4):MIit refers to the dynamic efficiency value. β is the regression coefficient. γ is the constant term. μi is the individual effect term. εit is the residual term.In Formula (4), China City Statistical Yearbook,” “China Statistical Yearbook for Regional Economy,” provincial statistical yearbooks, and statistical communiques of the city on national economic and social development. A few missing values were supplemented by the interpolation method. In addition, to reduce the impact of data fluctuation and heteroscedasticity on the accuracy of regression results, all variables were logarithmically processed.The explained variables in this article were selected from the panel data of 38 resource-based cities in Western China from 2004 to 2016 to calculate the static value and dynamic value of urban green transformation in 12 years from 2005 to 2016. The panel data from 2005 to 2016 were taken for explanatory variables. All data come from the “MaxDEA@maxdea.com; MaxDEA@qq.com; MaxDEA Software Ltd.) to calculate the annual static efficiency value (TE) of the green transformation of 38 resource-based cities in Western China from the global reference perspective and the perspective of the maximum output of fixed input and CRS hypothesis.Based on the input-output index system and a basic model constructed above, this article used the MAXDEA 7.12.10 software , accounting for 17.76% of the total sample. In other words, 82.24% of the efficiency values show low efficiency. It is worth mentioning that there are 19 effective values in 2016. It indicates that within the research range, the green transformation level of resource-based cities in Western China is obviously higher this year than in other years .To understand the basic situation of the static efficiency of green transformation in each city, the annual average efficiency of 38 resource-based cities from 2005 to 2016 is further calculated. The results show that the mean values of static efficiency are all <1, with the maximum value being 0.983 in Tongchuan and the minimum value being 0.379 in Longnan. This indicates that all cities have a certain degree of resource waste in the process of green transformation, resulting in low transformation efficiency. To sum up, the static efficiency of the green transformation of western resource-based cities is generally at a low level, and it is in the low-efficiency stage for most of the time.Based on the above efficiency evaluation indicators and basic software settings, the MI for 12 years of 38 resource-based cities in western China from 2005 to 2016 is calculated, referring to the dynamic efficiency value of green transformation.Among the 456 dynamic efficiency values, 252 values are ≥1, accounting for 55.26% of all samples. In other words, more than half of the samples increase in MI, indicating that the efficiency of green transformation is improved compared with the previous year, and the effect of green transformation becomes better. If an MI value >1 is evaluated as excellent green transformation, then cities in 2016 have the highest excellence rate and the largest number of cities with positive dynamic efficiency growth (including 35 cities). As shown in The geometric mean is further used to calculate the average MI of each city from 2005 to 2016. According to the calculation results, there is little difference in the mean value of dynamic efficiency among cities from 2005 to 2016, and the difference between the maximum value of 1.062 (Baotou City) and the minimum value of 0.963 (Yulin City) is only 0.099, referring to that there is no obvious difference in the dynamic effect of green transformation among cities in the study area. Among them, there are 28 cities with an average value >1 and 10 cities with an average value <1, accounting for 73.68 and 26.32% of the 38 cities, respectively. It can be explained that in the 12 years from 2005 to 2016, the average dynamic efficiency of 73.68% of the resource-based cities in Western China has increased. The green transformation effect of these cities is generally desirable, and each city has made progress. The green transformation effect of the remaining 26.32% of resource-based cities is backward in a small range (As shown in P = 0.000) is rejected, that is, the model is considered to have individual effects. For this reason, the panel Tobit model with random effects is selected for regression. The results are shown in Regarding the Tobit model regression of panel data and based on the research of scholars, it is difficult to obtain consistent and unbiased estimators by using the fixed effect Tobit model to estimate the panel data . TherefoIt can be seen from the regression results given in the above table: first, TI significantly promotes the static efficiency of green transformation of western resource-based cities at the level of 5%. The higher the government financial investment in science and technology, the higher the static green transformation efficiency. The possible reason is that under the new situation of technological globalization and ecological environmental protection, more resource-based cities in Western China gradually abandoned the extensive resource development and management mode, and choose to adopt more advanced technology and equipment. At the same time, enterprises are strongly encouraged to improve their market competitiveness through TI. The regression results just confirm the correctness of promoting green transformation through TI. Gates Foundation CEO Mark Sussman mentioned in the latest annual open letter of the Gates Foundation in 2022 that COVID-19 has brought heavy losses to society, but also brought technological progress. Particularly in the areas of health and agriculture, we can use the research and development of new drugs to tackle major diseases, such as COVID-19, among the poor, including resource-based cities in Western China, and use agricultural innovation and transformation technologies to help cities solve problems, such as drought, to cope with the threat of climate change. It can be seen that in the post epidemic era, the static efficiency of green transformation of resource-based cities in Western China can still be improved through effective TI.th Five-Year Plan. By increasing the proportion of the local transformation of resources and using industry to drive regional poverty alleviation, it has effectively promoted the rapid economic growth of resource-based cities in Western China, provided more material basis for the green transformation of resource-based cities as well as greatly improved static efficiency. In the early days of COVID-19, China's economy had a short shrinkage. But after the second quarter, with the effective control of COVID-19 in China and the continuous introduction of the “six stability” and “six guarantees” policy measures, China's economy began to steadily recover and return to the pre-epidemic level. Today, most cities in China, including resource-based cities in the western region, have realized continuous regional economic growth, providing strong material support for the improvement of static efficiency of green transformation.Second, the GDPP has a positive influence on the static efficiency of green transformation, indicating that the green transformation of resource-based cities in Western China is closely related to economic development. The GDPP directly affects the economic and social benefits of resource-based cities. Restricted by geographical location, resource dependence, and policy support, the level of economic development of different resource-based cities in Western China is also different, which makes the static efficiency of green transformation different. Since 2010, China has gradually increased the undertaking of industries in Western China, implemented the green Belt and Road Initiative, and further promoted the strategy of western development in the 13Third, HC has negative effects on static efficiency. This may be due to the geographical location of western resource-based cities that is relatively remote and the economic development is relatively backward, resulting in a single level and low level of HC. Although the cities have adopted more talent introduction strategies, they still fail to attract more high-level talents. While resource-based cities lack core talents, homogenized and low-level human resources are relatively crowded. Due to the above reasons, the HC factor in the research range fails to play its endogenous dynamic role but hinders the improvement of static efficiency of green transformation of resource-based cities in Western China. This also points out that western resource-based cities should give more focus on the HC in the process of promoting green economic recovery and realizing green transformation in the post-epidemic era. The problems of education loss and population mobility caused by COVID-19 have further increased the pressure of HC to promote the static efficiency of resource-based cities' green transformation in western China.Fourth, the coefficient of AIS, ER, and URB is positive and the coefficient of RO is negative, but they all fail to pass the significance test.On the basis of testing the influence of different factors on the static efficiency of green transformation in resource-based cities in Western China, and in view that city green transformation is a long-term development process, we further investigate the impact of various factors on the intertemporal efficiency of green transformation from a dynamic perspective, and then the regression analysis of Model 2 is made correspondingly.P > 0.1, it means that the original hypothesis cannot be rejected, that is, the selected tool variables are valid. The Arellano Bond test is used to determine whether the error item has a sequence correlation problem. The P-value of AR (1) should be <0.1, that is, the original hypothesis of “no sequence autocorrelation” is rejected, indicating that the model has first-order autocorrelation. Meanwhile, the P-value of AR (2) should be > 0.1, which is, the original hypothesis of “no sequence autocorrelation” is accepted, indicating that the model has no second-order autocorrelation problem.To obtain more accurate regression results and control the influence of the explained variable with one-period lag, this article adds the first-order lag term of the explained variable MI in the regression model as an instrumental variable, but this will inevitably lead to endogeneity problems. For dynamic panel data, deviations will be made in the estimator if panel data regression models, such as OLS, fixed effects, or random effects, are adopted. The system Gaussian Mixed Model (GMM) can effectively solve the potential endogeneity problem of model variables. Its basic method is to introduce the N-order lag term of the explained variables into the model as instrumental variables to alleviate the influence of endogeneity and ensure the effectiveness and consistency of estimators . TherefoP < 0.1, and the AR (2) P > 0.1, indicating that the model has first-order autocorrelation but no second-order autocorrelation. Therefore, the setting of the dynamic panel data model is reasonable.The test results show that the Sargan test result of model 2 is 1.000, far >0.1, so the original hypothesis is accepted, indicating that the instrumental variables selected in the estimation process are effective. The AR (1) The correlation is positive between TI and the dynamic efficiency of green transformation in resource-based cities, which becomes significant at the statistical level of 5%. It indicates that TI can effectively reduce environmental pollution and improve sustainable development capacity, which is vital for the green transformation and development of resource-based cities in Western China , 43. In Environmental regulation (ER) also has a positive impact on the dynamic efficiency of green transformation of resource-based cities in western China. It shows that the higher the level of ER, the better the development of city green transformation. In other words, long-term and reasonable ER can improve the dynamic efficiency of green transformation of resource-based cities. This may be because since the 11th and 12th Five-Year Plan, governments in Western China have gradually established a number of legal systems and policy guidance and unswervingly promoted green development and improved the environmental governance system. Taking the Environmental Protection Law of the People's Republic of China as the fundamental criterion for ecological and environmental protection in all parts of the west, different ERs and measures have been approved and issued in accordance with local conditions, such as Recent Soil Environmental Protection and Comprehensive Treatment Plan of Yunnan Province, the Environmental Protection Regulations of Inner Mongolia Autonomous Region, etc. Local governments also use their administrative power to strengthen environmental protection, including suspending high-pollution and high energy consumption plants, monitoring and controlling the source of industrial pollution, making marginal cost of pollutant companies close to marginal social cost. At the same time, the governments of resource-based cities in Western China have increased their investment in environmental pollution control. The multi-pronged approach has achieved remarkable results in pollution control and emission reduction, which effectively promotes the region's green transformation and development. Affected by the epidemic, the government has strengthened the environmental supervision of cities and enterprises to prevent the spread of the virus. This measure has accelerated the green transformation of the industry, promoted the green transformation of resource-based cities in western China and regional sustainable development.The regression coefficient of GDPP is positive, indicating that under certain conditions, the higher the economic development level of resource-based cities in Western China is, the greater the positive impact it has on the dynamic efficiency of regional green transformation, and the more conscious and capable the region will be to promote the development of green transformation. In resource-based cities with a high GDPP, the government and the people tend to invest more material and HC. Through the development of high-tech R&D, equipment updating and innovation, and ecology of science and technology, the production efficiency can be improved while the emission reduction effect of science and technology can be brought into play to effectively reduce urban pollution. It also promotes green development which has low energy consumption, low pollution, high quality, and high efficiency. With the deepening of the concept of sustainable development and the One Belt and One Road initiative raised by general secretary Xi Jinping, the economy of the western resources-based city continues to improve. The cities take advantage of resources and energy to speed up the industrial transformation, build a sound environment to attract investment. The accumulation of financial strength for the transformation of green resources has fundamentally promoted the green sustainable development of resource-based cities. China is the first country to recover from COVID-19 in the world. The western resource-based cities, which is the same as the national economic development situation, have achieved economic recovery and sustained growth after a short period of shrinkage. This shows the economic resilience of resource-based cities in Western China and provides a strong endogenous impetus for the realization of green transformation.The regression coefficient of URB on the dynamic efficiency of green transformation is positive, and it is significant at the 5% level. The research shows that the higher the URB, the stronger the promotion effect on the green transformation development of resource-based cities, which is consistent with the research results of Gao . A healtThrough the eastern industrial transfer, trade exchanges, and cooperation with countries and regions along the Belt and Road, it has provided abundant employment opportunities, attracted a large number of rural population to the cities, and developed the urban economy. This has fundamentally promoted the urbanization process of the western resource-based cities. These cities have been rapidly facilitating the urbanization process, effectively gathering abundant capital and labor resources, introducing and developing advanced technology and equipment, and then they begin to be able to deal with various environmental pollution and other problems in a centralized manner. In addition, the human resources reserve in the urbanization construction also plays its due role, which helps to tap and release the green potential of the city, and promotes the green transformation and development of the western resource-based cities as a whole. Besides, the human resource in the urbanization construction also makes a contribution, which helps release the potential of cities, and promotes the green transformation development of resource-based cities in Western China as a whole. The outbreak of COVID-19 has increased the living pressure of residents in western resource-based cities. Especially during the closed management period, it is necessary to guarantee the basic living needs and the normal operation of the city while ensuring the safety of life. But at the same time, the epidemic has also strengthened the development of the urban medical and health industry and digital industry and deepened the city and its residents' awareness of the green industry and green life. Therefore, in the post-epidemic era, the improvement of URB can effectively promote the green transformation of resource-based cities in western China.Both RO and HC have negative effects on dynamic efficiency, but they do not pass the significance test. However, it does not mean that the two have no impact on the green transformation development of resource-based cities. It may need to be estimated with data included in a longer time series in the future.This article takes 38 resource-based cities in Western China from 2005 to 2016 as the research object, evaluates the static efficiency and dynamic efficiency of green transformation of each city by using the super-SBM model and the MI model of the DEA method and takes the two efficiency values as explained variables. We carry out Panel regression analysis by using the panel Tobit model with random effects and two-step system GMM method to comprehensively investigate the impact of different factors on the green transformation efficiency of resource-based cities in Western China. The main conclusions are as follows: first, the static efficiency of green transformation of resource-based cities in western China is generally low with uneven development. The regional green transformation needs to be further improved. Second, in the study area, the dynamic efficiency of green transformation of resource-based cities in western China shows an upward fluctuation and an accelerating trend. The overall development situation of green transformation is desirable. Third, the impact of TI and economic development level on the static efficiency of western resource-based cities' green transformation is significantly positive, while the impact of HC on static efficiency is significantly negative. It shows the necessity to strengthen the support for TI in the green transformation stage of western resource-based cities and improve the city's economic development. At the same time, the government needs to further explore the potential power of HC on the green transformation of resource-based cities. Fourth, the AIS, TI, ER, GDPP, and URB all have a significantly positive effect on the dynamic efficiency of green transformation, indicating that the improvement of the above factors will be conducive to the green transformation development of resource-based cities in western China in a long run.Based on the special background of the global spread of COVID-19 and the above research conclusions, this article holds that, in the short term, COVID-19 is likely to remain, so the government should combine economic recovery with green transformation and integrate the concept of green sustainable development into all aspects of policy formulation, industrial layout, and production and life. It is expected that the resource-based cities in Western China will smoothly pass through the green transition window period and epidemic period while the economy continues to grow. In the medium and long term, we need to plan ahead and make a long-term layout, summarize the experience and lessons brought by the outbreak of COVID-19, improve the resilience of western resource-based cities to cope with sudden disasters and ecological changes, make innovation the first driving force and green the internal vitality, so as to contribute to China's sustainable development. This article draws the following enlightenment: first, although the efficiency level of green transformation of resource-based cities in western China has been improving year by year, it is still uneven and unable to promote the overall green sustainable development in the western region. The government of resource-based cities in Western China should focus more on the difference in green transformation efficiency among cities, formulate targeted policies according to local conditions, and realize the comprehensive, harmonious, and sustainable development of humans and nature in the region. 1) Local governments should continue to optimize the industrial structure and develop the tertiary industry. Although the outbreak of COVID-19 has brought unprecedented pressure to the tourism service industry of resource-based cities in western China, it has fully stimulated the development demand and potential of the urban digital economy. The traditional way of trade is under great pressure. The advantages of digital and accurate modern commercial trade are becoming increasingly obvious. E-commerce online shopping has become a new form of trade with its high efficiency and point-to-point characteristics, In addition, online industries, such as online entertainment, online conference, and office, are also growing rapidly. Therefore, resource-based cities in western China should seize the advantages of geographical location and opportunities of the times, actively participate in the construction of the new industrial chain of “One Belt and One Road,” cultivate and strengthen characteristic industries, develop emerging industries, improve the proportion of the tertiary industry, and promote the AIS. 2) The government should increase investment in science and technology and improve the level and intensity of technology innovation, especially the R&D and application of green technologies. On March 2, 2020, when General Secretary Xi Jinping inspected the COVID-19 prevention and control research work in Beijing, he stressed that “human development cannot overcome major disasters and epidemics without scientific development and TI” Western resource-based cities should seize the opportunity brought by the epidemic to promote social and TI, vigorously develop green technology, promote the construction of new infrastructure, and speed up the transformation of old and new driving forces. 3) The government should set up ER policies according to local conditions, improve decision-making level, avoid “one size fits all.” The impact of the epidemic poses a severe threat to the ER of resource-based cities in western China. Therefore, in the post-epidemic era, it is necessary to explore a differentiated ER model that takes into account both ecological civilization and economic and social development, improves the flexibility, pertinence, and effectiveness of ER, and grasps the ecological red line. All law enforcement departments should properly implement their responsibilities. The government should establish and improve the supervision and supervision mechanism for the development of green transformation, improve the supervision, increase the illegal cost of enterprises, establish and improve the compensation mechanism for ER, and formulate policies according to local conditions in western resource-based cities to improve the local ecological environment, so as to accelerate the green transformation in the post epidemic era. 4) The government should continue to push forward the city's economic development and improve urban economic resilience. In the post epidemic era, on the basis of fully doing a good job in epidemic prevention and control, the governments of resource-based cities in the West should have an overall awareness, deal with the relationship between the government and the market, the relationship between capital and labor, the relationship between supply and demand and the difference in the GDPP between regions, support the development of micro, small and medium enterprises, and provide them with financial, technical, policy and other assistance, guard against financial risks, and improve economic resilience. 5) The government should continue to facilitate the urbanization process, strengthen the construction of new urbanization, and improve the livable degree of cities by realizing city low-carbon production. In the post epidemic era, the government of resource-based cities in Western China should focus on the people, promote employment and protect people's livelihood, implement the employment priority policy, promote employment through multiple channels, give priority to ensuring the employment of low-income groups, provide training and services for laid-off reemployment, coordinate urban and rural development, and ensure the normal progress of urbanization in resource-based cities. 6) It is worth mentioning that HC was not found positive in increasing the green transformation efficiency in this study. So in the future, the government should improve the talent introduction system to attract medium and high-end talents, adjust the current utilization mode of HC to fully tap their potential power, make HC play a full role in the post epidemic era, and drive resource-based cities in the west to realize green economic recovery.Second, with the experience of green transformation of resource-based cities in the central and eastern regions, such as Xuzhou and Zaozhuang, western cities should continue to support their dominant industries while expanding new economic growth points and accelerating the construction of public health, disaster prevention, and mitigation, comprehensive transportation and other projects to improve the green transformation efficiency in the post epidemic era.Finally, western resource-based cities should improve green production capacity and resource utilization efficiency to reduce resource investment and waste, accelerating the green transformation process of resource-based cities in western China, realizing the win-win situation of “mountains of gold and silver” and “clear waters and green mountains” in the near future, and contributing China's strength to the world's green recovery and sustainable development in the post-epidemic period.At present, resource-based cities in western China are in the window period of green transformation, the epidemic prevention and control period, and the construction period of the new development pattern of the national “double-cycle,” which is also a historical-critical period for the economic and social development of the western region and China. While keeping up with the characteristics of the times, this article uses the efficiency characteristics to investigate the green transformation achievements of western resource-based cities from static and dynamic perspectives, and regresses the key influencing factors, so as to provide a more targeted and enlightening basis for the improvement and development direction of green recovery and sustainable development in the post epidemic era. Therefore, compared with the existing literature, on the one hand, the perspective of this study is more comprehensive, scientific, and directional. On the other hand, this study further enriches the regional research system of green transformation of resource-based cities in China. In addition, in reality, the factors affecting the green transformation of resource-based cities in western China will be more complex. Therefore, it will be the focus of future research to continuously track and introduce new explanatory variables and conduct more microscopic studies based on different types of resource-based cities.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.JZ contributed to the motivation, the interpretation of the methods, the data analysis and results, and provided the draft versions and revised versions. SW provided the data results, the revised versions, and references. All authors contributed to the article and approved the submitted version.This research was funded by Research on Dual Incentive Model of Carbon Reduction and Emission Reduction Target, Government Competition and Urban Environmental Governance, which was the research and planning fund for humanities and social sciences of MOE (Ministry of Education in China). The grant number is 21YJA790086.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Correlations of the SMOG units to reference instruments also demonstrated strong associations (r2 = 0.87–95) and good accuracy (MAE of 2.5–3.0 μg m−3). The PM2.5 concentrations tracked by the SMOG units had a similar response time as those measured by collocated reference instruments. Overall, the study has shown that the SMOG units provide relevant information about ambient PM2.5 concentrations in an airshed impacted predominantly by biomass burning, provided that an adequate adjustment factor is applied.Biomass burning smoke is often a significant source of airborne fine particles in regional areas where air quality monitoring is scarce. Emerging sensor technology provides opportunities to monitor air quality on a much larger geographical scale with much finer spatial resolution. It can also engage communities in the conversation around local pollution sources. The SMoke Observation Gadget (SMOG), a unit with a Plantower dust sensor PMS3003, was designed as part of a school-based Science, Technology, Engineering and Mathematics (STEM) project looking at smoke impacts in regional areas of Victoria, Australia. A smoke-specific calibration curve between the SMOG units and a standard regulatory instrument was developed using an hourly data set collected during a peat fire. The calibration curve was applied to the SMOG units during all field-based validation measurements at several locations and during different seasons. The results showed strong associations between individual SMOG units for PM It is well understood that there are negative health impacts from exposures to biomass smoke ,7,8,9,10To capture the local movement of smoke associated with biomass burning events a dense spatial network of air quality monitors is needed ,16, whicThe challenges that earlier research studies identified related to the use of low-cost particulate matter (PM) sensors were the lack of consistency between individual sensors, under or over reporting in comparison to reference methods and the deterioration in their performance over time ,22. FeinWith this understanding, we have conducted a number of field monitoring campaigns across regional Victoria. We selected locations impacted by both residential woodsmoke and planned burn emissions to evaluate the utility of the Plantower PMS3003 ,46 for uWe present results from a range of validation monitoring tests that have been conducted using the sensor to demonstrate its utility for conducting biomass monitoring and to provide a better understanding of what can be interpreted from the data.2.5 compares against gravimetric mass measurements and reference instruments at three different locations and during different seasons.Develop a smoke-specific calibration curve for the low-cost sensor SMOG units developed in this study and test how the calibrated data set for PMAssess the suitability of low-cost particle sensors to detect ambient smoke events and provide insights into the spatial and temporal patterns of these events.Develop a school STEM curriculum focusing on the construction, deployment and analysis of data from low-cost particle sensors to assess biomass burning impacts on regional air quality where regulatory air quality monitoring is sparse.Objectives:2.5 dust sensor (model PMS3003) [1, PM2.5 and PM10 concentrations with a response time of 10 s. In this study, the raw standard PM2.5 output data from the PMS3003  were used.The SMoke Observation Gadget (SMOG) is a unit that comprises of a Plantower Laser PMPMS3003) ,46 and aPMS3003) ) shines The SMOG unit has both a particle and temperature/humidity sensor that are interfaced via a printed circuit board (PCB) to a microcontroller, a Raspberry Pi Model 3B (RPi). The RPi receives information from the sensors and logs the data at 5-min intervals to an internal micro-SD card and an external USB stick. The electronics are consolidated onto a single PCB that connects directly to the RPi. All components are housed in a waterproof enclosure (150 × 200 × 100 mm) to facilitate outdoor deployment. ® 200 S .The SMOG units were tested at various locations and in different seasons alongside a tapered element oscillating microbalance , an E-Sampler  and a FidasThe TEOM is an EPA-designated equivalent method used for real-time measurements of the mass concentrations of particles. Air is drawn through a filter resting on a microbalance at a known flow rate and the change in frequency of an oscillating microbalance relative to the blank filter weight determines the volumetric concentration of particulate matter in ambient air . The mea2.5. The E-samplers operate at a flow rate of 2 L/min and collect both continuous particle measurements at a 5 min interval by light-scattering and particle mass on pre-weighed 47 mm Fluoropore membrane filters with a 1 μm pore size . The scattering is converted into mass concentration using a gravimetric K-factor determined from the aerosol mass collected on a filter during sampling. Although the E-sampler is not an EPA-designated equivalent method, applying a gravimetric K-factor generated for the E-sampler during the measurement period ensures that accurate concentration measurements and good agreement with federal reference methods (FRM) and federal equivalent methods (FEM) are achieved.The E-sampler contains a diode laser that operates at a 670 nm wavelength and measures real-time particles through near-forward light-scattering. Accurate flow in the E-sampler is critical to ensure accurate size selection through the inlet for gravimetric calibration of PM® 200 S, a European equivalent reference method, is an optical aerosol spectrometer that continuously analyzes ambient particles present in the size range 180 nm–18 µm. It is equipped with a polychromatic LED light source and has a 90° scattering angle.The FidasThe TEOM, E-sampler and Fidas are all equipped with an aerosol drying system controlled by dynamic heating of the inlet to keep relative humidity of the intake air below 50%. In addition to removing water, heating the intake air has the undesired effect of evaporating volatile PM. The TEOM is the only instrument to control for this using a filter dynamics measurement system. Operational settings of the various types of particle instruments are provided in We used the data set collected during a peat fire event near Port Macquarie, NSW  to develop a smoke-specific calibration curve for the SMOG units. This event was chosen as it was a prolonged biomass burning particle pollution event that presented a wide range of particle concentrations. Two SMOG units were collocated alongside a standard regulatory method (FDMS-TEOM) between August and December 2019 to evaluate smoke impacts due to the nearby peat fires . The monA number of field-based measurements were conducted to test the suitability of the SMOG units to accurately detect and monitor biomass burning events in different locations and under different meteorological conditions .2.5 size-selective inlet and to the Fidas. In winter, one SMOG unit was collocated with an E-sampler fitted with a PM2.5 size-selective inlet and with the Fidas.Measurements were conducted on the rooftop of CSIRO laboratories at Aspendale, Victoria  located 30 km south of Melbourne and in close proximity (~50 m) to the Port Philip bay shoreline from 23 to 26 April 2018 (autumn) and between 25 June and 16 July 2018 (winter) . The are2.5 measurements using the low-cost sensor SMOG units were completed at fifteen locations in north-east Victoria between 1 May 2018 and 6 June 2018 and at six locations in north-east Victoria between November 2018 and June 2019  and unrealistic spikes or drops in temperature and PM2.5. The filtered data set was then aggregated to hourly averaged data using a 75% data capture.A data cleaning criterion was applied to the raw data output from the SMOG units to remove erroneous data due to errors in PM filter sizing  for the SMOG units was determined by using the method of Wallace et al. . LOD has2.5 under identical circumstances. The precision of the SMOG units was evaluated using Pearson’s Correlation Coefficient to understand the associations between SMOG units. We used the reduced major axis linear regression relationships in R to provide insight into the pattern and extent of agreement between SMOG units [The following parameters were used to assess the performance of the SMOG units. Precision refers to how well all sensors reproduce the measurement of PMOG units . A perfeOG units ,52. The OG units .2.5 measurements made by the SMOG units and the corresponding reference particle instrument (R package ‘BlandAltmanLeh’ version 0.3.1) [The performance of the SMOG units was evaluated by computing linear regression and correlation with a reference instrument  using Ordinary Least Squares (OLS) Linear Regression in R . This prn 0.3.1) . Bland-AAdditionally, the relative bias, mean absolute error (MAE), root mean square error (RMSE) and normalised root mean square error (NRMSE) were calculated for each hourly data set to measure data accuracy using R packages .The SMOG units were designed to support a student-based project. The STEM project combined science, mathematics, engineering, and digital technology to address the issue of the impact of ambient particles from biomass burning sources on local and regional air quality and to assess air quality sensors. The project aimed to forecast smoke movements in smoke impacted regions and engage the community through schools.The project was targeted at Grade 6–8 students and comprised of five lessons. The first three lessons were classroom based interactive presentations that taught students about air pollution and ambient particles, biomass burning and measurement techniques of ambient particles.Lesson 4 was a hands-on session when students worked in teams to build the SMOG. After building the SMOG unit the students undertook a monitoring campaign using the SMOG units. Ideally, the monitoring campaign captured a period of potential high particle concentrations in the air such as those that result from prescribed burning in autumn or from domestic wood smoke in winter. The students were encouraged to set up the SMOG units outside their home and monitor the ambient air over approximately a 4-to-6-week period. Once the monitoring campaign was finished, the students returned their units to school to process and analyse their collected data set as part of lesson 5.To evaluate the suitability of the SMOG units to capture and quantify smoke events, we assessed their performance against each other and against gravimetric mass measurements and reference instruments.2.5 concentrations.Previous studies have shown that the Plantower sensors correlated well with reference instruments, but they exhibited high biases ,42,43,452.5 measurements from a FDMS-TEOM during a period of smoke from peat fires near Port Macquarie (NSW) to develop a calibration curve for the SMOG units. Ambient hourly PM2.5 concentrations up to 1300 μg m−3 were measured during the sampling period between August–December 2019. We used hourly PM2.5 concentration of ~300 μg m−3, with a 3rd degree polynomial curve best fitted for PM2.5 concentrations exceeding 300 μg m−3. Previous studies have shown non-linear behaviour above concentrations as low as 25 μg m−3 [−3 [−3 [−3 [−3 [The data suggests that a linear relationship can be applied to correct the SMOG data up to an hourly PM5 μg m−3  and 40 μ m−3 [−3 , while o [−3 [−3 , 150 μg  [−3 [−3  and 200  [−3 [−3 . These d [−3 [−3 ,46,56.Our linear equations with zero and non-zero intercepts showed similar slopes (1.73 and 1.76) and no significant difference in RMSE. This was also observed by Delp and Singer  who used2.5 concentrations in the 0–600 μg m−3 range.A linear multivariate regression with additive terms for temperature and relative humidity was also developed for the SMOG PMA recent paper by Barkjohn et al.  develope2.5 measurements was calculated at 5.5 μg m−3, in agreement with the LOD of 6 µg m−3 reported by Barkjohn et al. [The LOD for PMn et al.  and Sayan et al.  but highn et al. ,34,58.There are several theories regarding the replacement of values below the LOD, either being censored or substituted with a constant value, such as half the LOD, the LOD divided by the square root of 2, or zero. Using either approach can have impacts on the analyses ,60. Depe2.5 concentrations for each measurement period and collocation of instruments are shown in 2.5 concentrations below LOD ranged from 32–89%. More than 90% of hourly PM2.5 concentrations remained below 25 μg m−3. Maximum hourly PM2.5 concentrations ranged from 32 to 220 μg m−3. As the maximum hourly PM2.5 concentration was measured at 220 μg m−3, we applied the linear calibration curve fitted through the origin to correct the hourly SMOG data for the field-based testing.During the rooftop test at Aspendale, 35–43% of data were below the LOD, while for the field-based measurements in Northeast Victoria the percentage of hourly PM2.5 concentrations. The summary of statistical metrics for the SMOG inter-comparisons is shown in Intercomparison of collocated SMOG units enabled us to assess whether the SMOG units are suitable for measuring the spatial variability in PM2 = 0.98, slope = 1.03, intercept = 0.41) and CCC value of 0.98 (−3 and agreement limits between −1.57 and 2.91 μg m−3). SMOG unit 3 did not perform as well with an under-reporting of ~20%, this was potentially due to drift in the sensor performance.Agreement between SMOG units 2 and 4 during the autumn measurements at Aspendale was very high  between two PMS3003 units.The rooftop tests conducted at CSIRO Aspendale and the collocated SMOG units at north-east Victoria have shown an overall good intra-precision between SMOG units. Previous studies have shown very high correlations between PMS3003 units. For example, Zheng et al.  reportedy et al.  showed h2.5 concentrations in a wide range of locations and conditions.The data suggest that the SMOG units are reliable over a range of concentrations, temperatures (5–50 °C), and RH values (11–91%) which suggests they can be deployed to assess the spatial variability of PMRegression analysis of the continuous measurements by light-scattering versus gravimetric mass measurements for the E-sampler and Fidas are provided in 2.5 concentrations compared to gravimetric mass measurements were observed in winter (May–June) at Alexandra. A similar trend was observed for the measurements with the Fidas and E-sampler. Lower ratios were observed in winter at both Aspendale and Alexandra when high concentrations of particle events were attributed to residential wood smoke. This trend is in agreement with the findings by Kelly et al. [Comparison of gravimetric mass measurements against averaged corrected SMOG data showed ratios varying between 0.69 and 1.48 (excluding time periods with less than 50% data capture and more than 90% of data below LOD). The corrected SMOG data measured at Rutherglen were within 10% of the gravimetric mass measurements. Most of the SMOG data measured during the summer at Alexandra were below the LOD, with averaged corrected SMOG data being lower than the gravimetric mass measurements. In April, corrected SMOG data was in good agreement with the gravimetric mass measurements, while higher PMy et al.  and Tryny et al.  who repo2.5 concentrations compared to gravimetric mass measurements, while the E-sampler under-reported PM2.5 concentrations compared to gravimetric mass measurements except for measurements completed in winter at Aspendale and Alexandra.The results in 2.5 concentrations has been attributed to the differences between the optical properties of the manufacturer’s factory calibration particles and wood smoke particles and can be adjusted using a site-specific or season-specific calibration factor. The data also shows that there is not a uniform response of the light-scattering instruments to the different particle sources. This will be further explored in Systematic discrepancies between light-scattering monitors and reference methods have been observed in previous research studies ,62,63. T2.5 concentrations measured with the calibrated SMOG units using gravimetrically corrected measurements from the collocated Fidas (Fidas_CF) and E-sampler. To check the accuracy of the SMOG units, we compared the hourly PM−3 with a larger bias observed at higher ambient PM2.5 concentrations , with an over-reporting compared to gravimetrically corrected Fidas data (slope of 1.43). Similarly to the E-sampler, the Bland-Altman plot , with an average slope of 0.80 and intercept of 0.68. The agreement between SMOG units and E-sampler was good . Performance of the SMOG unit against the Fidas was good, with a poorer performance for SMOG3 (possibly as a result of drift in sensor performance). Overall, the SMOG units over-reported by ~40% when using Fidas data corrected against gravimetric mass measurements.Correlations between SMOG units and E-sampler during the Aspendale autumn campaign were high  and the Fidas . However, the SMOG units over-reported PM2.5 concentrations, with agreement limits ranging from −15.6 to 15.0 μg m−3 for the E-sampler and from −9.9 to 19 μg m−3 for the Fidas.The set of measurements conducted at Aspendale in winter 2018 showed high correlations between the SMOG unit and the E-sampler  was observed between the two E-samplers and the two SMOG units at the location in Rutherglen, Victoria with slopes ranging between 0.88 and 0.96. The scatter plots between SMOG7 and E-samplers indicate a large scatter when PM2.5 concentrations were below 10 μg m−3 and an underestimation of PM2.5 when concentrations were above 15 μg m−3 . Bias and error values were within recommended performance metrics [Overall, the SMOG units exhibited a high correlation with reference instruments  were reported by Zheng for hourly PM2.5 measurements made with the Plantower PMS3003 sensor and an E-BAM reference instrument, with improved correlations when averaging times were increased to 6 h and 12 h [2 values of 0.58 for hourly PM2.5 measurements [2 of 0.83–0.92) between PMS units and FEMs were reported in studies where biomass burning was the dominant particle source [Observed correlations in this study were higher compared to other field-based studies using the Plantower sensor . Moderatand 12 h . Field-turements . Liu alse source ,29,45 as2.5 concentrations measured with the calibrated SMOG units compared with a reference instrument (E-sampler/Fidas) corrected against gravimetric mass measurements are shown in Time series plots of hourly PM2.5 trends of the collocated E-sampler and Fidas, indicating that the response time of the SMOG units is comparable to that of the E-sampler/Fidas and that peaks are temporally captured correctly.The time series plots show that the SMOG units closely follow the PM2.5 event on 27–28 June 2018 when the SMOG, Fidas and E-sampler were operational. Hourly PM2.5 concentrations remained above 25 μg m−3 for 15 h.At Aspendale in winter, we observed an elevated PM2.5 concentrations on 3 May 2018 and elevated PM2.5 concentrations between 8–10 May 2018. Elevated PM2.5 concentrations were measured at the other sampling sites during May 2018 and were either attributed to planned burns or stubble burns.In Rutherglen, we observed a short spike in PM2.5 peak events were identified: 1–8 February 2019, 7–20 March 2019 and 14–22 April 2019 . However, during winter, corrected SMOG PM2.5 concentrations were significantly higher compared to PM2.5 measurements made with the Fidas or E-sampler (bias of 5.9 to 13.3 μg m−3 and NRMSE of 94–132%).Results on the performance of the SMOG units during the identified smoke plume events are provided in Although Holder et al.  and DelpSeveral research studies have shown that a combined calibration curve is suitable ,28,29 whWhile we were able to investigate the effects of temperature and RH on the sensor performance other factors were not evaluated. One limitation of the study that could explain why the sensors responded differently between seasons is likely due to particle characteristics . Mehadi et al.  showed a1 than for PM2.5 for wood smoke particles.A larger scatter in the data was observed when comparing the SMOG data against the E-sampler data. This may be due to the different scattering angle between the E-sampler and Plantower sensor which affects the size range within which the oscillations are more pronounced  and/or tLike other educational programs using low-cost sensor technology , the SMO2.5 concentration ranges. This provided us with important data on the performance of the units under different meteorological conditions and in different locations with different biomass smoke sources.We were able to conduct a number of field-based monitoring campaigns where the SMOG units were tested over a wide range of environmental conditions  and PM2.5 monitoring, as precision between SMOG units when regularly maintained was very high.Based on the sensor performance when testing a number of units simultaneously we are confident that the SMOG units can be used to increase spatial coverage of PM2.5 concentrations in an airshed impacted predominantly by biomass burning, provided that an adequate adjustment factor is applied. This study suggests that a uniform adjustment factor applied to sensor data may not be appropriate across all PM sources and that a residential wood smoke adjustment factor may need to be applied to increase the accuracy of the sensor.The field-based measurements suggest that the Plantower PMS3003 dust sensor can provide relevant information about ambient PMThe study also highlighted that sensor accuracy and precision may vary depending on reference instruments used for comparison purposes.


Capsicum accessions held in genebanks and representing a frame of the global diversity of the genus. By combining single nucleotide polymorphisms (SNPs) based data and passport information, we investigated the genomic diversity and population structure of wild and domesticated peppers, tracing back to routes of evolution and providing a model of Capsicum annuum distribution, which reflects human trade and historical/cultural influences. Our results highlight west–east routes of expansion, shedding light on the links between South and Mesoamerica, Africa, and East/South Asia, the latter two constituting important diversification centers of pepper diversity. Finally, we outline a roadmap for genebank management and future direction for better exploitation of germplasm resources.This study provides a deep population genomic analysis of 10,000  Capsicum spp.) accessions from worldwide genebanks and investigated the recent history of this iconic staple. Genomic data detected up to 1,618 duplicate accessions within and between genebanks and showed that taxonomic ambiguity and misclassification often involve interspecific hybrids that are difficult to classify morphologically. We deeply interrogated the genetic diversity of the commonly consumed Capsicum annuum to investigate its history, finding that the kinds of peppers collected in broad regions across the globe overlap considerably. The method ReMIXTURE—using genetic data to quantify the similarity between the complement of peppers from a focal region and those from other regions—was developed to supplement traditional population genetic analyses. The results reflect a vision of pepper as a highly desirable and tradable cultural commodity, spreading rapidly throughout the globe along major maritime and terrestrial trade routes. Marker associations and possible selective sweeps affecting traits such as pungency were observed, and these traits were shown to be distributed nonuniformly across the globe, suggesting that human preferences exerted a primary influence over domesticated pepper genetic structure.Genebanks collect and preserve vast collections of plants and detailed passport information, with the aim of preserving genetic diversity for conservation and breeding. Genetic characterization of such collections has the potential to elucidate the genetic histories of important crops, use marker–trait associations to identify loci controlling traits of interest, search for loci undergoing selection, and contribute to genebank management by identifying taxonomic misassignments and duplicates. We conducted a genomic scan with genotyping by sequencing (GBS) derived single nucleotide polymorphisms (SNPs) of 10,038 pepper ( During the early 20th century, awareness of the increasing loss of genetic diversity in crops  first prCapsicum gene pool comprises domesticated and wild species with highly variable morphology and flavor and characterized by variable levels of pungency due to the presence of capsaicinoids that made peppers a staple cultural component in cuisines across the globe , of which C. annuum is globally the most cultivated. Historical records suggest that pepper was brought by Columbus from the New World to Europe and was thenceforth traded along most major maritime and overland trade routes. However, records are scattered, and controversies remain regarding the possibility of East/Southeast-Asian connections to the Americas independent of—and perhaps earlier than—the establishment of transatlantic trade routes by Europeans during the 16th century. The historical and archaeological records have not yet been synthesized with genetic data at a global scale, although the germplasm suitable for such a study is aptly represented among genebank collections. The full landscape of genomic diversity available in Capsicum PGRs has been only partially exploited, being applied to limited subsets , we estimated identity-by-state (IBS) proportions considering all pairwise combinations of accessions. We added a set of control replicates to the dataset  to discover what range of IBS proportions would be assigned to samples known to be identical replicates. A strongly bimodal distribution of IBS with one peak close to IBS = 0 was observed, with this peak containing all the “CM334” versus “CM334” comparisons. This allowed us to impose a cutoff value of IBS < 0.0001 for considering two accessions as potential duplicates . A total of 2,353 noncontrol accessions clustered in 735 groups , thus revealing that 1,618 accessions were genetic duplicates of other accessions, with the cardinality ranging from 2 (526 groups) to 246 accessions (1 group). The fraction of duplicated accessions differed among the genebanks that were sourced for the analyzed germplasm, as well as between taxa. On average, ∼75% of germplasm was found to be unique within genebanks, with a fraction of unique accessions ranging from 63.5% at the Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) to 80.4% at the Universitat Politècnica de València (UPV) . A consistent proportion of shared samples was found between World Vegetable Centre (WorldVeg) and IPK (23.1%), whereas only a few accessions . Overall, duplication occurred mostly within the Annuum clade  (Dataset S2). These differences presumably reflect variation in both the deduplication practices of genebanks and difficulty with which novel entry accessions can be checked against the current collection. This significant level of duplication should motivate the development of genetic prescreening protocols to be used in genebanks for documenting the potential duplicate samples upon first acquisition.The sharing and inconsistent documentation of germplasm often results in duplicates within and between genebanks that can be hard or impossible to identify and could affect population genomic analyses . To idenDataset S3). Members of clusters containing multiple species designations were assigned to the majority designation, if the majority assignment made up more than 80% of the cluster, after visual inspection of the principal component analysis (PCA) plots to assure the cluster did not fall within a region of broad overlap between multiple species. In total, 53 clusters included accessions from more than one species or undefined accessions. The largest part of species misassignment occurred within the Annuum clade and between the three C. baccatum groups, including the two botanical varieties and an undefined group. Rather than to misassignment, these outliers could be attributed to allele introgressions due to spontaneous crosses. While the levels of mis- and nonassignment of genebank taxa are expected to vary across taxonomic groups and to become more inaccurate at lower taxonomic levels, these results clearly demonstrate that genomics-based methods, integrated with passport information, should be considered the gold standard to correct any inaccuracy in species/subspecies assignment and duplicate detection.To correct and impute species assignments , hierarcCapsicum generally reflect their membership of true genetic demes  and PCA plot representations  were coherent with the main established complexes  holds the largest diversity, alongside being best represented in the collection . C. baccatum  is broadly separated from all other species groups. A significantly smaller degree of separation exists between C. chinense and C. frutescens accessions. C. chinense and C. frutescens are known for including the most pungent accessions, , and the small-fruited Tabasco (C. frutescens) types giving the eponymous name to the sauce.Species assignments in the genus ic demes A. Fittinic demes B , which are mostly sourced from the World Vegetable Center. While the frequency of accidental hybrids produced in a given genebank will vary with factors such as the multiplication techniques and the crossability between species, these higher heterozygosity levels do suggest the distinct possibility of recent, accidental crossings occurring in genebanks, leading to the creation of intermediate forms. However, many of them were marked as unclassified when they were collected, possibly resulting from natural or ancestral hybridization, and then maintaining a high rate of heterozygosity despite multiplication by selfing.A cluster of taxonomically unclassified samples appears to connect to um clade , resultium clade —which isC. baccatum accessions suggests a certain level of subspecies misassignment occurring within different repositories. C. pubescens and C. chacoense—both consumed to a small degree by humans—form distinct groups, and the data suggest that some wild individuals could arguably be collapsed into C. pubescens.Broad overlap among C. annuum caused its members to be modeled as highly admixed combinations of five source populations . Application of the same method to the 7,848 C. annuum accessions alone suggested the species could be represented as combinations of nine highly admixed K clusters, roughly reflecting geographical divergences . Evolutionary distances between clusters suggest the possible presence of more than one center of diversification . Using PCA plots to represent C. annuum population structure . In general terms, European samples dominate one end of a cline, the other end of which is dominated by Asian samples, while samples collected across the Americas are fairly widely distributed along the cline. A second deme is populated mostly by Mesoamerican samples, and (rare) samples intermediate between the small deme and the main cline are found in most regions. These observations are more consistent with a high degree of founding diversity coupled with an intricately reticulate population history, suggesting a model of pepper domestication in which a wide range of representatives of a significant natural diversity pool originating in Mesoamerica  were widely domesticated and frequently transported and intercrossed. We expand on this concept with further analysis described in Conclusion. Estimations of Tajima’s D show a consistent excess of rare alleles in C. annuum compared with other species  and also elevated Fst in most pairwise interspecific comparisons—both are compatible with a relatively stronger domestication bottleneck than other species, followed by population expansion and rapid dispersal to and between human cultures.The ADMIXTURE algorithm models individuals as the products of variable levels of admixture between a collection of K genetic source groups. The results of running ADMIXTURE on the whole collection suggest that this model has limited appropriateness for pepper at the intraspecific scale B. Indeedtructure  clearly C. annuum diversity as a proxy for the human forces that have shaped it, we examined morphological and genetic similarities and differences between the C. annuum peppers found in global regions. To dissect this complexity further, we sought to visualize the data so to reflect interregion sharing of peppers. The method ReMIXTURE  was developed to establish the so-called relative genotypic overlaps (RGOs) between a selection of regions, to which C. annuum accessions were assigned based on genebank passport data .Aiming to further leverage (regionA→regionB) measure provides an intuitive indication of the probability that a pepper accession chosen randomly from among the complement of pepper accessions in a focal region “A” will be genetically closer to a randomly chosen pepper accession in a target region “B” than it will belong to a randomly chosen pepper accession in any other region ((regionA→regionA)) can be understood as a proxy for uniqueness—the degree to which region A’s peppers cannot be well approximated by peppers from other regions. The RGOs—juxtaposed against the prevalence of certain phenotypes in certain regions—reflect several dominant themes that shaped the modern distribution of peppers. All in all, RGO tends to be higher between regions within the same continent, testifying to the influence of overland, riverine, and coastal trade .The ReMIXTURE’s RGOr region A. Or, st1, 4, 101, 5, 101). Transcontinental overlaps between American and Eurasian pepper groups are more complex to interpret. C. annuum is thought to have been originated in Mexico . Accordingly, pepper complements from regions in the eastern half of Eurasia have significant overlap with the South/Mesoamerican complement, most likely as a result of transatlantic trade during the 16th century : The peppers grown in these East Eurasian regions were primarily sourced—directly or indirectly—from the South/Mesoamerican diversity pool South America, while likely the origin of the wild peppers from which domesticated species arose, appears to have almost the entire domesticated 3). This series of connections explains the African peppers’ overlap with those of both South America (to which Portuguese traders enjoyed privileged access following the 1494 Treaty of Tordesillas) and East/Central Asia . The large proportion of the African complement that is unique may owe to gene flow as a consequence of germplasm exchange with the past trades    combinedC. annuum diversity, the former a possible consequence of sweet and blocky peppers popular in European cuisines, resulting in additional centers of diversification . The fact that South American diversity can be best represented as a combination of East/South/Southeast-Asian and of African pepper diversity (Ipomoea batatas) was introduced from the Americas to Oceania and then to East Asia in historic times (Lagenaria siceraria) followed the opposite route, being introduced from Africa to the Americas through Asia as early as 10,000 y ago . In addition, the high South America→East/South/Southeast Asia RGO  favors the more modern, post-Columbian routes, particularly the Portuguese, highlighting South America as a possible gate of distribution. This would explain the lack of a high similarly Mesoamerica→Europe RGO, as the Portuguese did not have any great interest in introducing pungent peppers to Europe, thus creating a cheaper alternative to the highly valued black pepper (Piper nigrum), which they imported from the Far East  and various elevated Europe→Asia/Asia→Europe RGOs . All these arguments collectively provided a perfectly parsimonious pathway for the regular transfer of peppers from America to Asia via the Atlantic route (1–3). The evidence does not rule out a Sino-American trade connection, but it does not require this scenario to explain East/South/Southeast-Asian pepper diversity.The high North→South America and Meso→South America RGOs suggest a primary route of expansion through Americas . Fruit pungency was primarily associated with a peak on the pepper chromosome P2 spanning 142 to 150 megabase pairs (Mbp)  contributes to the synthesis of valine (Genome-wide association studies (GWAS) detected several notable marker–trait associations for key traits under selection, several of which correspond to known quantitative trait loci (QTLs) and fall near genes with documented functions (rs (Mbp) A, fallinynthesis . Among cf valine , a vitalf valine B, a signSI Appendix, Fig. S13), were found strongly associated with markers on P12 in the vicinity of Protein EARLY FLOWERING 4 (ELF4)-like -like , whose Aed roles , includiIn addition, we found candidates for traits not yet fully explored in pepper. The number of pedicels per axil C, a traiGWAS highlights how a large factor in pepper’s initial appeal was certainly its pungency, suggesting putative regions for selection in correspondence of some primary traits that has driven the selection. By confirming established associations, we provide proof of the reliability of genebank records for discovering candidate genes. This suggests a key position of genebanks as a central repository of germplasm and related big data (genomics and phenomics) toward future gene discovery and crop improvement.C. annuum). Historians, archaeologists, and ethnobotanists have discussed evidence of many migration pathways including 1) longitudinal migration through the Americas, 2) three out-of-America pathways  through pre- or post-Columbian trans-Pacific trade routes, 3) overland migration throughout Eurasia, and 4) transatlantic slave trade connecting America, Europe and Africa. Our investigation using the ReMIXTURE method shows that the primary similarities between peppers collected in these regions accord with all these pathways, except for the direct Asia–America link, a hypothesis on which the analyses are somewhat equivocal. Mesoamerica, East/South/Southeast Asia, and Africa are all notable for large proportions of region-unique peppers indicating their status of diversification center. The broad overlapping clines that are formed by each region’s peppers suggests that crossing between locally favored varieties and new acquisitions have frequently occurred. As our GWAS and selection scan results confirm, a large factor in pepper’s initial appeal was certainly its pungency, especially in nontropical Europe where hot spices were rare and imported black pepper (Piper nigrum) could fetch demanding prices. This study shows how genomics applied to a horticultural crop can offer opportunities for PGR management and provide valuable insight on the conserved germplasm resources. In fact, genetic data stored in genebanks confirm that pepper, thanks to its flexible features  has been spread along with the very earliest intercontinental traders, being among the very earliest examples of a globally traded, mass-market, consumer-discretionary good.Our research represents a case study in the exploitation and in-depth analysis of genetic data from genebank collections to yield information on expansion routes of the most economically important pepper species  had an undetermined species status. Details of species, genebanks, and passport information provided by provider curators are reported in C. annuum cv. CM334 (originating from a unique seed batch provided by INRAE) was included in each library preparation . For complexity reduction, a two-enzyme protocol using PstI (CTGCAG) and MspI (CCGG) was used  or the Sbeadex maxi plant kit (LGC Genomics). DNA quantity and quality parameters were assessed using both spectrometry  and fluorometry  methods. Samples with 260/280 and 230/260 ratios ranging between 1.8 to 2.2 and 1.8 to 2.0, respectively, and with a less than twofold deviation between fluorimetric and spectrophotometric readings were subjected to genotyping-by-sequencing. As controls, the reference was used . DNA seqwas used . Size seSI Appendix, Table S8) were then aligned to reference genome sequence C. annuum CM334 version 1.6 available at http://peppergenome.snu.ac.kr . A 527,474 biallelic SNPs matrix was obtained with minimum QUAL ≥ 40; minimum read depth for homozygous call ≥ 2; minimum read depth for heterozygous calls ≥ 4. For downstream analysis, SNP sites were retained with minor allele count (mac ≥ 50), heterozygosity level (<5%), and missing data (20%). Imputation of missing genotype calls in the SNP matrix was done using the FILLIN algorithm implemented in TASSEL 5 (http://snpeff.sourceforge.net/). The commands were run in parallel to reduce computational time using GNU parallel  in an attempt to assess the degree to which models that imply some form of genetic structure were suitable to the data. We ran ADMIXTURE version 1.23  with the1)A matrix of counts 2)N random individuals from each region in R. N is a constant, chosen to be significantly smaller than the number of samples in the most sample-poor region.A subset of 3)For each sample In order to present the data in a way amenable to elucidating the exchange and sharing of pepper varieties among cultures, we developed the ReMIXTURE  method, a purely descriptive visualization method that asks, intuitively, for a series of nominated regions The global relative overlap matrix A bootstrapping procedure can be used to estimate CIs for the entries of C. annuum accessions, excluding those from Oceania which had very low sample numbers, using the IBS matrix calculated as described for the analysis of duplicated samples, with the following parameters: I = 2,000, N = 54 , m = 1,500, and P = 1,000. Details of the R . Before proceeding with the analysis, all data have been reviewed removing any inconsistencies  and outliers. This led to the establishment of a core set of 2,059 C. annuum accessions representing the variation of the whole species gene pool  and without any missing data for 21 phenotypic observations (Dataset S4).Phenotypic data for 21 qualitative/pseudoqualitative descriptors for plant, flower, and fruit trait categories recorded by each genebank during multiplication cycles following the International Plant Genetic Resources Institute (IPGRI)/Bioversity  protocolk-mer GWAS pipeline . The software was run with minimum read count threshold of 2 and keeping other parameters to default. The k-mers from all the samples were then compared to generate a k-mer presence/absence matrix which was further filtered with minor allele frequency (MAF) ≥ 0.02 and minor allele content (MAC) ≥40. The kinship matrices of relatedness between the samples were calculated based on the filtered k-mer matrix and using EMMA package (P value threshold was determined based on permutations of phenotype. For visualization of the results, the top 1 million k-mers for each trait were extracted from GWA study and mapped against the reference genome sequence C. annuum CM334 version 1.6, and positions of uniquely mapped k-mers were retrieved. The Manhattan plots for each trait were generated using qqman R package (In order to widen the genetic variants detected in GWAS such as major rearrangements, insertions, and deletions, reference-free GWA analysis was implemented using a pipeline . This pi package  with def package  for each package .Supplementary FileSupplementary FileSupplementary FileSupplementary FileSupplementary File