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Chemical oxygen demand (COD) is widely used as an organic pollution indicator in wastewater treatment plants. Large amounts of organic matter are removed during treatment processes to meet environmental standards, and consequently, substantial greenhouse gases (GHGs) such as methane (CH4) are released. However, the COD indicator covers a great amount of refractory organic matter that is not a pollutant and could be a potential carbon sink. Here, we collected and analysed COD data from 86 worldwide municipal wastewater treatment plants (WWTPs) and applied a model published by the Intergovernmental Panel on Climate Change to estimate the emission of CH4 due to recalcitrant organic compound processing in China’s municipal wastewater treatment systems Our results showed that the average contribution of refractory COD to total COD removal was 55% in 86 WWTPs. The amount of CH4 released from the treatment of recalcitrant organic matter in 2018 could have been as high as 38.22 million tons of carbon dioxide equivalent, which amounts to the annual carbon sequestered by China’s wetlands. This suggests that the use of COD as an indicator for organic pollution is undue and needs to be revised to reduce the emission of GHG. In fact, leaving nontoxic recalcitrant organic matter in the wastewater may create a significant carbon sink and will save energy during the treatment process, aiming at carbon neutrality in the wastewater treatment industry.

In 2020, China promised to achieve carbon peaking by 2030 and carbon neutrality by 2060, and these targets are famous as “Goal 3060” in China. Chinese resource-based cities are concerned about the realization of Goal 3060 to practice national action against environmental change. In this paper, this study evaluates the impact of population, economic growth, energy intensity, industrial structure, fixed asset investment, and urbanization level on carbon emissions in Chinese cities. To do so, the paper divides 36 Chinese cities into four types (growing city, mature city, recessionary city, and regenerative city) from 2003 to 2017 by factor investigation according to the diverse development stages. The extended STIRPAT model is used to assess the impact of various factors on CO2 emissions in the Yellow River basin and diverse city levels. The panel regression analysis was conducted for the basin as a whole and cities at different development stages through a fixed-effects model and a linear regression model with Driscoll-Kraay standard errors. The results show that (1) the total carbon emissions in the Yellow River basin continued to climb during the study period. However, the growth rate slowed down significantly after 2012. In addition, there are differences in the total carbon emissions and growth rate of different cities. (2) Population, real GDP, energy intensity, industrial structure, and fixed asset investment all have a significant positive impact on carbon emissions in the overall basin except the urbanization level which has a significant negative influence on carbon emissions. (3) There is heterogeneity in the influencing factors of carbon emissions in resource-based cities at various development stages. Based on these results, corresponding policies are proposed for different types of cities to help resource-based cities achieve the 3060 dual carbon goal.

Greenhouse gas (GHG) emissions related to human activities have significantly caused climate change since the Industrial Revolution. China aims to achieve its carbon emission peak before 2030 and carbon neutrality before 2060. Accordingly, this paper reviews and discusses technical strategies to achieve the "dual carbon" targets in China's metal mines. First, global carbon emissions and emission intensities from metal mining industries are analyzed. The metal mining status and carbon emissions in China are then examined. Furthermore, advanced technologies for carbon mitigation and carbon sequestration in metal mines are reviewed. Finally, a technical roadmap for achieving carbon neutrality in China's metal mines is proposed. Findings show that some international mining giants have already achieved their carbon reduction targets and planned to achieve carbon neutrality by 2050. Moreover, improving mining efficiency by developing advanced technologies and replacing fossil fuel with renewable energy are two key approaches in reducing GHG emissions. Green mines can significantly benefit from the carbon neutrality process for metal mines through the carbon absorption of reclamation vegetations. Geothermal energy extraction from operating and abandoned metal mines is a promising technology for providing clean energy and contributing to the carbon neutrality target of China's metal mines. Carbon sequestration in mine backfills and tailings through mineral carbonation has the potential to permanently and safely store carbon dioxide, which can eventually make the metal mining industry carbon neutral or even carbon negative.

China’s recently announced directive on tackling climate change, namely, to reach carbon peak by 2030 and to achieve carbon neutrality by 2060, has led to an unprecedented nationwide response among the academia and industry. Under such a directive, a rapid increase in the grid penetration rate of solar in the near future can be fully anticipated. Although solar radiation is an atmospheric process, its utilization, as to produce electricity, has hitherto been handled by engineers. In that, it is thought important to bridge the two fields, atmospheric sciences and solar engineering, for the common good of carbon neutrality. In this überreview, all major aspects pertaining to solar resource assessment and forecasting are discussed in brief. Given the size of the topic at hand, instead of presenting technical details, which would be overly lengthy and repetitive, the overarching goal of this review is to comprehensively compile a catalog of some recent, and some not so recent, review papers, so that the interested readers can explore the details on their own.

In a monopolistically competitive model with production externalities, where individuals voluntarily provide offsets which compensate for degradation of environmental quality caused by their income earning activities, this paper examines how an increase in the population size affects the equilibrium levels of environmental quality, offsets, and net contributions. Whether labor supply is institutionally constrained or not, as the population size increases, environmental quality decreases and converges to zero. However, since offsets increase and converge to the degradation rate of environmental quality, the carbon neutrality theorem holds: net contributions are zero. These results are independent of the specification of the utility function.

Carbon neutrality lays out a grand blueprint for carbon emission reduction and climate governance in China. How to reduce energy consumption is the key to achieving this goal. The economic development and energy consumption show a very large gap at the provincial level, and this paper divides China into six regions (North, Northeast, East, Mid-South, Southwest, and Northwest) and analyzes the dynamic changes and reveals the driving factors that have affected CO2 emission changes from 1997 to 2017. Then, the driving forces including energy intensity, energy structure, energy efficiency, economic activity, and population scale were discussed employing the logarithmic mean Divisia index (LMDI) based on provincial panel data. The results show that CO2 emissions from energy consumption show an upward trend, from 4145 Mt in 1997 to 13,250 Mt in 2017, with an annual average growth rate of 1.06%; coal consumption is the main source of CO2 emission. The regions with the highest proportion of CO2 emissions are the East and North, which account for 50% of total emissions. China’s CO2 emissions from energy consumption, coal consumption, and output have shown significant spatial autocorrelation at the provincial scale. According to coal consumption, energy consumption CO2 emissions are divided into three stages: phase I (1997–2002), the increase in CO2 emissions in six regions was attributed to significant and positive impacts of energy intensity, economic activity, and population scale, the effects of which exceeded those of the energy structure and energy efficiency; phase II (2003–2012), the economic activity effect on CO2 emissions was highest in the East region, followed by the North and Mid-South regions; phase III (2013–2017), the East, Mid-South, and Southwest regions of China were dominated by the positive effects of energy intensity, economic activity, and population scale. The major driver of CO2 emissions is economic activity; the energy efficiency effect is an important inhibitory factor. Regional economic development and energy consumption in China are unbalanced; we conclude that differentiated emission reduction measures should be of particular concern for policymakers.

Recently, China has declared its national objective of becoming carbon neutral by 2060. Hence, mitigating carbon dioxide emissions has become an important agenda of the Chinese government. Against this backdrop, this paper aims to evaluate the effectiveness of pursuing expansionary fiscal and monetary policies on China’s carbon dioxide emission figures by using annual frequency data from 1980 to 2018. Accordingly, this study considers the levels of government expenditure and broad money supply as fiscal and monetary policy instruments, respectively. Besides accounting for structural break concerns in the data, the findings from the empirical analysis reveal that there are long-run associations between carbon dioxide emissions, economic growth, and fiscal and monetary expansion in China. Moreover, the results also show that in both the short- and long-run expansionary fiscal policy trigger higher carbon dioxide emissions while expansionary monetary policy inhibits the carbon dioxide emission figures of China. Furthermore, the results invalidate the existence of the Environmental Kuznets Curve hypothesis since the relationship between China's economic growth and carbon dioxide emissions is evidenced to portray an N-shape. In line with these findings, it is recommended that China achieve environmentally sustainable economic growth by aligning the national fiscal and monetary policies with the 2060 carbon-neutrality objective.

In order to limit global warming to 2 °C, countries have adopted carbon capture and storage (CCS) technologies to reduce greenhouse gas emission. However, it is currently facing challenges such as controversial investment costs, unclear policies, and reduction of new energy power generation costs. In particular, some CCS projects are at a standstill. To promote the development of CCS projects in different countries, this paper reviews and compares energy conservation and emission reduction policies and different national goals. From a policy perspective, CCS-driven policies are analyzed. Based on this, corresponding policy recommendations are put forward, in order to promote the healthy development of global CCS technology and deal with climate issues more effectively. With less than 10 years away from the short-term goal, promoting the development and application of CCS projects requires scientific research from universities, enterprises and governments in order to attain zero or negative CO2 emission. On the basis of focusing on the development of CCS technology, according to the actual situation of each country, the appropriate application of CCS engineering should focus on the development of science and technology, rather than a unified requirement around the world., Carbon Neutrality, 1 (1)

With the national goal of "carbon peak by 2030 and carbon neutral by 2060 in China", studies on carbon prices of China's Emissions Trading System (ETS) pilots have shown growing interest in the related fields. Carbon price fluctuations reflect the scarcity of carbon resources, and accurate prediction can improve carbon asset management capabilities. Therefore, in order to clarify the dynamics of carbon markets and assign carbon emissions allocation rationally, we propose a hybrid feature-driven forecasting model with the framework of decomposition-reconstruction-prediction-ensemble. In this paper, the non-stationary, nonlinear and chaotic characteristics of carbon prices in China's ETS pilots have been verified, and then the prediction model is built based on the tested features. Firstly, the original carbon price series are decomposed by Variational Mode Decomposition (VMD), and then reconstructed by Sample Entropy (SE). Next, Extreme Learning Machine (ELM) optimized by Particle Swarm Optimization (PSO) is conducted to predict the subsequences. Lastly, the forecasting series of every subseries are summed to obtain the final results. The empirical results based on carbon prices of China's ETS pilots proved that the proposed model performs more efficiently than the current benchmark models. As carbon prices are expected to increase across all ETS during the post-COVID-19 recovery stage, the new prediction model will be useful for improving the guiding principles of the existing government policies including the likely introductions of Border Carbon Adjustment (BCA) in the EU and the US, and governing the large global public companies to deliver their "net zero" commitments.

Technologies evolve under the impact of several factors starting from the progress of science and innovation. Usually driven by market forces, the evolution is slow. With regard to energy, the time unit is roughly a century. Concerns about climate change add a new element: political decisions. The EU committed itself at the end of 2019 to achieving carbon neutrality by 2050, mainly through the implementation of wind and solar energies. A comparison between past data and forecasts related to the change sets the difficulties clearly in evidence. The paper discusses the requirements for the European Green Deal to be successful.