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Natural wetlands are among the most important sources of methane; thus, these areas are important for better understanding long-term temporal variations in atmospheric methane concentration. During the last 60 years, wetlands have experienced extensive conversion and global impacts from climate warming, which makes the estimation of methane emission from wetlands highly uncertain. In this paper, we present a modeling framework, integrating CH4MODWETLAND, TOPMODEL and TEM models, to analyze the temporal and spatial variations in CH4 emissions from natural wetlands (including inland wetlands, coastal wetlands, lakes and rivers) in China. Our analysis revealed an increase of 25.5 %, averaging 0.52g m-2 per decade, in national CH4 fluxes from 1950 to 2010, which was mainly induced by climate warming. Higher rates of increasing CH4 fluxes occurred in northeastern, northern and northwestern China, associated with large temperature increases. However, decreases in precipitation due to climate warming o_set the increase in CH4 fluxes in these regions. The CH4 fluxes from the wetland on the Qinghai Tibetan Plateau exhibited a lower rate of increase, which was approximately 25% of that simulated in northeastern China. Although climate warming has accelerated CH4 fluxes, the total amount of national CH4 emissions decreased by approximately 2.35 Tg (1.91-2.81 Tg), i.e., from 4.50 Tg in the early 1950s to 2.15 Tg in the late 2000s, due to a large wetland loss of 17.0 million ha. Of this reduction, 0.26 Tg 0.24-0.28 Tg) was derived from lakes and rivers, 0.16 Tg (0.13-0.20 Tg) from coastal wetlands, and 1.92 Tg (1.54-2.33 Tg) from inland wetlands. Northeastern China had the largest contribution to this reduction, with a loss of 1.68 Tg. The CH4 emissions were reduced by more than half in most regions in China except for the Qinghai Tibetan Plateau, where only a 23.3% decrease in CH4 was observed. [ABSTRACT FROM AUTHOR]

Climate change is the dominant factor affecting the hydrological process, it is of great significance to simulate and predict its influence on water resources management, socio-economic activities, and sustainable development in the future. In this paper, the Xiying River Basin was taken as the study area, China Atmospheric Assimilation Driven Data Set (CMADS) and observation data from the Jiutiaoling station were used to simulate runoff of the SWAT model and calibrate and verify model parameters. On this basis, runoff change of the basin under the future climate scenario of CMIP6 was predicted. Our research shows that: (1) The contribution rates of climate change and human activities to runoff increase of the Xiying River are 89.17% and 10.83%, respectively. Climate change is the most important factor affecting runoff change of the Xiying River. (2) In these three different emission scenarios of SSP1-2.6, SSP2-4.5 and SSP5-8.5 in CMIP6 climate model, the average temperature increased by 0.61, 1.09 and 1.74 °C, respectively, in the Xiying River Basin from 2017 to 2050. Average precipitation increased by 14.36, 66.88, and 142.73 mm, respectively, and runoff increased by 15, 24, and 35 million m³, respectively. The effect of climate change on runoff will continue to deepen in the future. [ABSTRACT FROM AUTHOR]

Wetland loss and climate change are known to alter regional and global methane (CH4) budgets. Over the last six decades, an extensive area of marshland has been converted to cropland on the Sanjiang Plain in Northeast China, and a significant increase in air temperature has also been observed there, while the impacts on regional CH4 budgets remain uncertain. Through model simulation, we estimated the changes in CH4 emissions associated with the conversion of marshland to cropland and climate change in this area. Model simulations indicated a significant reduction of 1.1 Tgyr-1 from the 1950s to the 2000s in regional CH4 emissions. The cumulative reduction of CH4 from 1960 to 2009 was estimated to be ~ 36Tg relative to the 1950s, and marshland conversion and the climate contributed 86% and 14% of this change, respectively. Interannual variation in precipitation (linear trend with P > 0.2) contributed to yearly fluctuations in CH4 emissions, but the relatively lower amount of precipitation over the period 1960-2009 (47 mmyr-1 lower on average than in the 1950s) contributed ~91% of the reduction in the area-weighted CH4 flux. Global warming at a rate of 0.3 °C per decade (P < 0.001) has increased CH4 emissions significantly since the 1990s. Relative to the mean of the 1950s, the warming-induced increase in the CH4 flux has averaged 19 kg ha-1 yr-1 over the last two decades. For the RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 scenarios of the fifth IPCC assessment report (AR5), the CH4 flux is predicted to increase by 36 %, 52 %, 78% and 95 %, respectively, by the 2080s compared to 1961-1990 in response to climate warming and wetting. [ABSTRACT FROM AUTHOR]

The excessive carbon emissions not only intensify the global climate change, but also seriously restrict the sustainable development of social economy. However, improving industrial carbon emissions efficiency is the most directly effective way to reduce emissions. Therefore, accurate measurement and analysis of carbon emissions efficiency and evolution characteristics of China's industrial system is the basis for China to improve carbon emissions efficiency. Based on this, we adopted energy consumption method and input-output method to calculate and analyze the industrial carbon emissions efficiency and evolution characteristics of China from 2002 to 2015. The results show that (1) If carbon emissions from cement production are ignored and only energy-related carbon emissions are considered, the calculation results of carbon emissions efficiency of heavy industry will be overestimated about 30%. (2) Compared with 2002, China's industrial carbon emissions efficiency increased by about twice in 2015. Specifically, the optimization of carbon emissions efficiency in agriculture, construction, light industry and service industry is very obvious, which has increased by 5.65, 5.00, 4.69 and 4.68 times respectively; The optimization of carbon emissions efficiency in power sector, heavy industry, transportation and chemical industry was obvious, which increased by 2.55, 2.01, 1.86 and 1.47 times respectively; The carbon emissions efficiency of the fossil energy sector has decreased by 0.36 times. (3) The carbon emissions efficiency of various industries has significant differences. Among them, agriculture, service industry, light industry and construction industry are generally industries with higher carbon emissions efficiency, while power sector, fossil energy sector, transportation industry, chemical industry and heavy industry are generally industries with lower carbon emissions efficiency, especially power and fossil energy sectors. Based on these, this paper provides policy implications and scientific evidence for accurately improving carbon emissions efficiency from the perspective of carbon emissions efficiency. [ABSTRACT FROM AUTHOR]

Climate change is considered one of the major systemic risks facing the world in the 21st century. To address climate change, China has adopted a series of climate policies, but the uncertainty brought about by frequent climate policy issuance has increased pressure on enterprises, which may not be conducive to enterprises reducing emissions. This paper uses data on 1211 listed companies on the A-share market in China from 2012 to 2022 to study the impact of climate policy uncertainty on enterprise pollutant emissions. The research findings show that climate policy uncertainty increases corporate pollution emissions; climate policy uncertainty mainly generates negative impacts on enterprise environmental regulation, social responsibility, and R&D investment, thereby negatively affecting enterprise emissions reduction. Further heterogeneity analysis shows that climate policy uncertainty in China has a more significant impact on non-state-owned enterprises, technology-intensive enterprises, lightly polluting enterprises, and enterprises in western regions. These findings emphasize the importance of enterprise social responsibility, environmental regulation, and R&D investment in enterprise emissions reduction and provide policy implications for Chinese enterprises to optimize their energy-saving and emission reduction strategies in the face of climate policy uncertainty. • We investigate the correlation between uncertainty in climate policy and the corporate pollution emissions. • We utilized an extensive dataset comprising publicly listed Chinese firms spanning the period from 2012 to 2022. • Climate policy uncertainty negatively impacts corporate environmental regulation, social responsibility, and R&D investment. [ABSTRACT FROM AUTHOR]

The majority of the total greenhouse gas (GHG) emissions in China are energy-related. Thus, full understanding of energy-related GHG emissions is crucial for local governments to establish a baseline for tracking emission trends and developing mitigation strategies. In this paper, we present a survey-based GHG emission accounting method for sectoral energy consumption and apply it in Xiaolan, a typical town of Zhongshan. The method combines scope and sectoral analyses on the basis of local statistical approach, and pays more attention to data collection process. Scenarios of core findings in the study are list as below: (1) The energy-related GHG emissions of Xiaolan in 2010 was 2,072,444 tons of carbon dioxide equivalents (CO 2 e). Of this, 31.83% was Scope 1 emissions (direct emissions) and 68.17% was Scope 2 emissions (indirect emissions); (2) Emissions from “manufacturing”, “residents”, and “power, gas & water production and supply” made up 90.27%, among which, “manufacturing” represents the biggest emitting sector as 69.09%; (3) In 2010, the per capita GHG emissions was lower than that in most of the other Chinese cities, but higher than several Asian cities including Amman and Tokyo. Some strategic approaches to reduce GHG emissions were proposed: (1) save energy and improve energy efficiency; (2) optimize energy structure and develop low-carbon energy; (3) update manufacturing structure; (4) improve GHG emission management for the resident sector. Finally, we identified a number of key research issues to advance the town level GHG emission method for future research needs. This paper provides a useful method to understand and profile GHG emissions for towns. [ABSTRACT FROM AUTHOR]

Transportation industry accounts for the majority of air pollutant emission, which is one of the leading factors of climate change. Many vehicle emission models have been proposed focusing on emission factors to study the pollutant emission issue. However, little research has been done in China on emission models, though China is a major air pollutant-emitting country. This paper first introduces two emission models- MOBILE model and MOVES model, then proposes model selection methods including AIC (Akaike information criterion) and BIC (Bayesian information criterion) to compare and select the better model which could be applied in China. Experimental results show that the value of AIC and BIC for MOVES model is significantly lower than MOBILE model, which implies that MOVES model has better performance on real data fitness and prediction. Our experimental findings may be useful for future research on air pollutant emission modelling in China. [ABSTRACT FROM AUTHOR]

Abstract: The unprecedented resources and energy needed to support the high growth of urbanization with the emerging issues of environmental degradation and GHG emissions is increasingly dramatic in China. A series of national and local policies have been implemented for achieving the co-benefits of reducing emissions of greenhouse gas (GHG) and air pollution for China's sustainable development. In this paper, the achievement of climate change mitigation and air pollution reduction in different sectors through implementing policies is reviewed. This paper reports on the types of policy measures that have been introduced in two cases (i.e. Tiexi District of Shenyang and Baoshan District of Shanghai) to affect air quality and energy efficiency improvements, which are then collectively examined in terms of their impacts on GHG and air pollutant emissions. Recommendations are made for achieving co-benefits effectively through the integrated approach by comprehensively concentrating on the short and long-term environmental protection and energy conservation at local and national levels based on the analysis made in the paper. The limited coordination and lack of capacity in different government bodies may be the main barriers to the implementation of a co-benefits approach. Enhancing the cooperation and capacity building could overcome these obstacles. [Copyright &y& Elsevier]

Alleviating global climate change requires the development and adoption of green innovation. This study compares the impact of cooperative and independent green innovation on carbon reduction based on the panel data covering 252 cities in China from 2003 to 2019. We examine the heterogeneous impacts of cooperative green innovation across units, and explain the transmission mechanism. The two-way fixed effects model and interaction model are adopted. Results show that: (1) Cooperative green innovation can reduce carbon emissions more effectively than independent green innovation. A 1% increase in cooperative green patents (inventions) will reduce carbon emissions by 0.023% (0.037%), while independent green patents or inventions play a weak role. (2) For research and development (R&D) partners, firms' cooperative green innovation has a stronger positive effect on carbon reduction than research organizations. The carbon reduction effect of cooperative green innovation is better for listed firms and universities. (3) Mechanism analysis shows cooperative green innovation can reduce carbon emissions by improving the industrial structure and decreasing energy intensity. These effects are stronger when cities have more talent, funds and higher marketability. (4) We also find that listed firms' cooperative green inventions with a ten-year lag can still reduce carbon emissions effectively. Cooperative green innovation is conducive to carbon reduction among eastern and central cities of China. [Display omitted] • This paper explores the impact of green innovation on carbon reduction from the new perspective of cooperation. • Cooperative green innovation is more effective than independent green innovation in carbon reduction. • Cooperative green innovation of listed firms and universities is more conducive to carbon reduction. • Cooperative green innovation can optimize the industrial structure and decrease energy intensity for better carbon reduction. • Cooperative green innovation with more talent, funds and market has better carbon reduction effect. [ABSTRACT FROM AUTHOR]

The issue of climate change has become an increasing concern for the international community. At the same time, climate change and, particularly, global warming affects the amount of energy required in China and the structure of this demand, thereby influencing the amount of CO 2 (carbon dioxide) emissions produced. To investigate the possible influence of climate change on China's CO 2 emissions, this paper utilizes the degree-day method to calculate the heating degree days (HDD) and cooling degree days (CDD) in 29 provinces in China from 1995 to 2011. A series of appropriate econometric models are subsequently estimated to measure the impact of climate change on CO 2 emissions per capita. To enhance the explanatory power of the estimation results, several indicators, such as income per capita, industry structure, urbanization rate and population density, are incorporated in the estimation equations as control variables. The estimation results indicate that the feedback effect of climate change on China's carbon emissions is statistically significant but not large in magnitude. During the sample period between 1995 and 2011, approximately 1.687% of China's increased total CO 2 emissions could be attributed to climate change. Moreover, the impacts of climate change on different regions of China are notably different. For example, the influence of HDD on CO 2 emissions per capita are most significant in the middle and southern regions, while the impacts of CDD are most significant in the eastern and northern regions. However, there is no obvious evidence that climate change has affected CO 2 emissions in the western region. [ABSTRACT FROM AUTHOR]

At the Conference of the Parties held in Copenhagen in 2009 (COP15), the Chinese government announced its 2020 commitment to reduce the carbon intensity of the Chinese economy to 40–45% of its 2005 level. A number of analysts have criticised this target, indicating that these reductions can be achieved without the implementation of any active climate change policy. In this paper, we test this argument using a combined input–output based econometric projection approach and the World Input–Output Database (WIOD). Our results show that the projected carbon intensity for 2020 is likely to be 50% lower than the carbon intensity of 2005, without additional active climate change policy measures performed by the Chinese government. On top of it, our study indicates that the total volume of CO 2 emissions would be by 2020 seven times the volume of the year 2005. [ABSTRACT FROM AUTHOR]

China's climate has been warming since the 1950s, with surface air temperature increasing at a rate higher than the global average. Changes in climate have exerted substantial impacts on water resources, agriculture, ecosystems and human health. Attributing past changes to causes provides a scientific foundation for national and international climate policies. Here, we review recent progress in attributing the observed climate changes over past decades in China. Anthropogenic forcings, dominated by greenhouse gas emissions, are the main drivers for observed increases in mean and extreme temperatures. Evidence of the effect of anthropogenic forcings on precipitation is emerging. Human influence has increased the probability of extreme heat events, and has likely changed the occurrence probabilities for some heavy precipitation events. The way a specific attribution question is posed and the conditions under which the question is addressed present persistent challenges for appropriately communicating attribution results to non-specialists. [ABSTRACT FROM AUTHOR]

Abstract: In recent years, heavy metal pollution accidents were reported frequently in China. The atmospheric heavy metal pollution is drawing all aspects of attention. This paper summarizes the recent research results from our studies and previous studies in recent years in China. The level, temporal variation, seasonal variation and size distribution of the heavy metals of atmospheric Lead(Pb), Vanadium(V), Manganese(Mn), Nickel(Ni), Chromium(Cr), Cadmium(Cd), Copper(Cu), Zinc(Zn) and Arsenic(As) were characterized in China. The emission characteristics and sources of atmospheric heavy metals and As in China were reviewed. Coal burning, iron and steel industry and vehicle emission are important sources in China. Control policies and effects in China were reviewed including emission standards, ambient air quality standards, phase out of leaded gasoline and so on, and further works for atmospheric heavy metals control were suggested. The comprehensive heavy metals pollution control measures and suggestions were put forward based on the summarization of the development and experience of the atmospheric heavy metal pollution control abroad. [Copyright &y& Elsevier]

Abstract: The effects of black carbon (BC) aerosol on climate warming have been the study focus in the recent decade, and the reduction of BC is now expected to have significant near-term climate change mitigation. Large uncertainties of BC optical properties, however, still exist and seriously restrict the ability to quantify BC''s climate effects. In this study, advanced instrumentation (a three-wavelength photoacoustic soot spectrometer (PASS-3) and a single particle soot photometer (SP2)) were used to measure black carbon aerosol and analyze its optical properties in a mega-city in South China, Shenzhen, during the summer of 2011. The results indicated that the average BC mass concentration was 4.0 ± 3.1 μg m−3 during the campaign, accounting for ∼11% of the total PM2.5 mass concentration. The PM2.5 light absorption at 405, 532 and 781 nm was 37.1 ± 28.1, 25.4 ± 19.0 and 17.6 ± 12.9 Mm−1, respectively. The average absorption Angstrom exponent of PM2.5 in visual spectrum (AAE405–781 nm) was 1.1 ± 0.1 during the campaign, indicating that the light absorbing carbon mainly came from vehicular emissions, with little contributions from biomass burning emissions. The mass absorption efficiency (MAE) of BC at 532 nm ranged from 5.0 to 8.5 m2 g−1 during the campaign, with an average of 6.5 ± 0.5 m2 g−1, and showed an obvious diurnal pattern with high values in the daytime. The average percentage of internally mixed BC was 24.3 ± 7.9% during the campaign, showing significant positive correlation relationship with the MAE of BC. More quantitative data analysis indicated that the internally mixed BC would amplify MAE by about 7% during the campaign, which stands in accordance with the new finding of a very recent Science magazine paper (Cappa et al., 2012) that the BC absorption enhancement due to internal mixing in the real atmosphere is relatively low, in apparent contrast to theoretical model predictions. [Copyright &y& Elsevier]

Abstract: Urban building system assumes significant environmental and ecological implications in terms of a contribution of emissions of CO2 and other greenhouse gases. In order to understand the roles of urban building system in the global and regional climate changes, we set up an integrated model to analyze the carbon emissions of urban building system during its life cycle in this paper, which is called LCCE Model. The further analysis is made to examine the sources of CO2 emissions and the life cycle characteristics of typical architectural structures as masonry-concrete and steel-concrete. We first identified four major sources of CO2 emissions during the whole life cycle of urban building system, which are industrial process emissions, energy consumption emissions, fugitive emissions and land footprint emissions. Given an assumption of a building life cycle of 50years, we took urban residential buildings as an example and calculated CO2 emissions in the main five phases of an overall life cycle of a residential building system, including constructive materials preparation, building construction and reformation, building operation, building demolition as well as wastes treatment and recycling. A comparison was made to examine the differences of CO2 emissions among buildings with two typical architectural structures as masonry-concrete and steel-concrete. The results show that the latter produces less CO2 emission than the former per unit area. Specifically, the amount of CO2 emission is 329.61t for masonry-concrete buildings and 315.79t for steel-concrete buildings per 100m2. Most emissions come from energy consumption and land footprint, accounting for 78–83% and 13–20% of the total emissions respectively. According to our LCCE model, there is a great potential of reducing carbon emissions in urban building system. The key to reduce carbon emissions during the life cycle of urban buildings is directed to building wastes recycling, improvement of consumption patterns of energy and materials, preferential use of buildings with a moderate floor area ratio and effective utilization of natural energy and ecologically friendly building materials according to the characteristics of local urban development. [Copyright &y& Elsevier]

Abstract: As an important renewable energy, wind power has been paid more and more attentions in China recent years, in order to weaken the influence of climate change. We should know exactly the benefits wind power can produce, before government formulates relevant policies to accelerate its deployment. In this paper, we calculate the quantity of fossil energy saving and pollutant abatement in its life cycle, comparing with the baseline technology, i.e. 600MW coal-fired thermal power. Considering the damage cost of the pollutants, we can assess the benefits of development of wind power. By our model, we know that wind power can save 0.3839 kgce and avoid 0.203 yuan environmental cost when it generates 1 kWh electric quantity, comparing with coal-fired thermal power. [Copyright &y& Elsevier]

Abstract: Release of CO2 has caused significant climate change, and agricultural land use consitutes an important carbon source as well as principal carbon sinks. This paper, by examining carbon functions of main agricultural land in China, shows that in 2000-2008 the annual growth rate of carbon emission for arable land amounted to 2.47 percent, the average annual growth of carbon sinks for forest reached 3.19 percent, and the diminishing rate of carbon sink for grassland turned to be small but quite distinct. For arable land, higher carbon emissions are mainly located in its central provinces and major agricultural provinces, while higher carbon intensity in its eastern coastal provinces. Agricultural land of 9 provinces in China was found with net carbon emissions, primarily in the agricultural provinces and ecologically fragile urban areas, whereas the other 22 provinces with net carbon sinks. The EKC tests between carbon intensity of agricultural land and agricultural output per capita illustrate a significant inverted Ucurve relationship; as for agricultural output per capita, the inflection point of 9,615 RMB yuan was surpassed by 11 provinces, mainly in eastern China, developed cities and the northeast region. Finally, policy recommendations are proposed to reduce carbon emissions of agricultural land use across China. [Copyright &y& Elsevier]

Abstract: This paper reports findings of a recent field study that characterized the on-road emissions of individual diesel vehicles in and around Beijing, China during November and December of 2009. We successfully sampled 230 individual trucks on 4 major expressways around the city as well as 57 individual buses in the city using refined mobile chasing techniques and fast response instruments. Emission factors (EF) for carbon monoxide (CO), black carbon (BC) and particulate matter with diameters less than 0.5 μm (PM0.5) are derived from the measurements, which are consistent with the results from laboratory dynamometer tests. The PM0.5 number emission factor distributions demonstrate consistent bimodal modes with peaks around 10 nm and 80 nm, while the mass emission factor distributions demonstrate a unimodal maximum around 110 nm for a majority of the trucks. The BC emissions are shown to be highly correlated with the mass emission of particles with 100–250 nm diameters, which are in good agreement with the results from previous studies. A number of important policy implications are discussed based on the results from this study. First, we identified “heavy emitters” in the on-road fleet we encountered, finding that 5% of diesel trucks in this sample are responsible for 50% of total BC emissions, and 20% of the trucks are responsible for 50% CO and PM0.5 number emissions, 60% PM0.5 mass emissions and over 70% of BC emissions. This suggests that emissions control programs should include identifying and removing heavy emitters from the road or improving their emissions. Second, the BC and PM0.5 number emission factors of trucks registered in regions outside Beijing are significantly higher than those of Beijing-registered trucks, suggesting that improving engine and fuel standards in Beijing alone is not sufficient in reducing the traffic-related air pollution in Beijing. Third, the significantly lower emissions from Euro IV and CNG buses compared to the Euro II and Euro III buses support that introducing clean-burning buses is an effective way to reduce the overall vehicle emissions for the pollutants studied. Fourth, our refined chasing method demonstrates a cost-effective approach to characterize the emissions from a large number of on-road diesel vehicles. Further studies with large sample sizes are critical to constructing more accurate mobile emission inventories to represent the on-road vehicle population. [Copyright &y& Elsevier]

Abstract: This paper uses multivariate co-integration Granger causality tests to investigate the correlations between carbon dioxide emissions, energy consumption and economic growth in China. Some researchers have argued that the adoption of a reduction in carbon dioxide emissions and energy consumption as a long term policy goal will result in a closed-form relationship, to the detriment of the economy. Therefore, a perspective that can make allowances for the fact that the exclusive pursuit of economic growth will increase energy consumption and CO2 emissions is required; to the extent that such growth will have adverse effects with regard to global climate change. [ABSTRACT FROM AUTHOR]

Abstract: Monthly nitrogen isotopes of ammonium and nitrate in wet deposition in the city of Guangzhou, and the causes of their variability, are reported in this paper. Nitrate δ15N showed nearly constant values around zero in the dry season (October to April), but oscillating values from negative to positive in the rainy season (May to September). By contrast, ammonium δ15N displayed lower values during the rainy season than in the dry season. The rural area north of the city was considered as the prominent source of ammonium and nitrate in spring and early summer (May and June), as suggested by their concurrent negative isotopic trends and higher NH4 +/NO3 − ratios. From July to September, different dominating sources from the city, i.e., fossil fuel combustion for nitrate, and sewage and waste emission for ammonium, caused disparate δ15N trends of the two species, showing positive nitrate δ15N, but still negative ammonium δ15N. During the cool dry season, the high values of ammonium δ15N and concurrently low NH4 +/NO3 − ratios suggested the decrease in NH3 volatilization and relatively important thermogenic origin of ammonium, but the intermediate nitrate δ15N values around zero may be a result of a balanced emission of NOx from the city and the rural areas. The isotopic effects of chemical conversion of NOx to nitrate and washout of nitrate were ruled out as significant causes of nitrate δ15N variability, but ammonium washout, during which 15N is assumed to be preferentially removed, may partly contribute to the ammonium δ15N variability. [Copyright &y& Elsevier]

In this paper, we report the results and analysis of a recent field campaign in August 2007 investigating the impacts of emissions from transportation on air quality and community concentrations in Beijing, China. We conducted measurements in three different environments, on-road, roadside and ambient. The carbon monoxide, black carbon and ultrafine particle number emission factors for on-road light-duty vehicles are derived to be 95gkg−1-fuel, 0.3gkg−1-fuel and 1.8×1015 particleskg−1-fuel, respectively. The emission factors for on-road heavy-duty vehicles are 50gkg−1-fuel, 1.3gkg−1-fuel and 1.1×1016 particleskg−1-fuel, respectively. The carbon monoxide emission factors from this study agree with those derived from remote sensing and on-board vehicle emission testing systems in China. The on-road black carbon and particle number emission factors for Chinese vehicles are reported for the first time in the literature. Strong traffic impacts can be observed from the concentrations measured in these different environments. Most clear is a reflection of diesel truck traffic activity in black carbon concentrations. The comparison of the particle size distributions measured at the three environments suggests that the traffic is a major source of ultrafine particles. A four-day traffic control experiment conducted by the Beijing Government as a pilot to test the effectiveness of proposed controls was found to be effective in reducing extreme concentrations that occurred at both on-road and ambient environments. [Copyright &y& Elsevier]

In recent years, air pollution has caused more than 1 million deaths per year in China, making it a major focus of public health efforts. However, future climate change may exacerbate such human health impacts by increasing the frequency and duration of weather conditions that enhance air pollution exposure. Here, we use a combination of climate, air quality, and epidemiological models to assess future air pollution deaths in a changing climate under Representative Concentration Pathway 4.5 (RCP4.5). We find that, assuming pollution emissions and population are held constant at current levels, climate change would adversely affect future air quality for >85% of China's population (~55% of land area) by the middle of the century, and would increase by 3% and 4% the population-weighted average concentrations of fine particulate matter (PM2.5) and ozone, respectively. As a result, we estimate an additional 12,100 and 8,900 Chinese (95% confidence interval: 10,300 to 13,800 and 2,300 to 14,700, respectively) will die per year from PM2.5 and ozone exposure, respectively. The important underlying climate mechanisms are changes in extreme conditions such as atmospheric stagnation and heat waves (contributing 39% and 6%, respectively, to the increase in mortality). Additionally, greater vulnerability of China's aging population will further increase the estimated deaths from PM2.5 and ozone in 2050 by factors of 1 and 3, respectively. Our results indicate that climate change and more intense extremes are likely to increase the risk of severe pollution events in China. Managing air quality in China in a changing climate will thus become more challenging. [ABSTRACT FROM AUTHOR]

Objective: Bacterial canker of kiwifruit caused by Pseudomonas syringae pv. actinidiae (Psa) is a major threat to the kiwifruit industry throughout the world and accounts for substantial economic losses in China. The aim of the present study was to test and explore the possibility of using MaxEnt (maximum entropy models) to predict and analyze the future large-scale distribution of Psa in China. Method: Based on the current environmental factors, three future climate scenarios, which were suggested by the fifth IPCC report, and the current distribution sites of Psa, MaxEnt combined with ArcGIS was applied to predict the potential suitable areas and the changing trend of Psa in China. The jackknife test and correlation analysis were used to choose dominant climatic factors. The receiver operating characteristic curve (ROC) drawn by MaxEnt was used to evaluate the accuracy of the simulation. Result: The results showed that under current climatic conditions, the area from latitude 25° to 36°N and from longitude 101° to 122°E is the primary potential suitable area of Psa in China. The highly suitable area (with suitability between 66 and 100) was mainly concentrated in Northeast Sichuan, South Shaanxi, most of Chongqing, West Hubei and Southwest Gansu and occupied 4.94% of land in China. Under different future emission scenarios, both the areas and the centers of the suitable areas all showed differences compared with the current situation. Four climatic variables, i.e., maximum April temperature (19%), mean temperature of the coldest quarter (14%), precipitation in May (11.5%) and minimum temperature in October (10.8%), had the largest impact on the distribution of Psa. Conclusion: The MaxEnt model is potentially useful for forecasting the future adaptive distribution of Psa under climate change, and it provides important guidance for comprehensive management. [ABSTRACT FROM AUTHOR]

Climate change has gained widespread attention, and the rapid growth of the economy in China has generated a considerable amount of carbon emissions. Zhejiang Province was selected as a study area. First, the energy-related carbon emissions from 2000 to 2014 were accounted for, and then the Logarithmic Mean Divisia Index (LMDI) decomposition model was applied to analyse the driving factors underlying the carbon emissions. Finally, three scenarios (inertia, comparative decoupling and absolute decoupling) for 2020 and 2030 were simulated based on the low-carbon city and Human Impact Population Affluence Technology (IPAT) models. The results showed (1) carbon emissions increased by 1.66 times from 2000 to 2014, and trends of carbon emissions were used to divide the study period into three phases (rapid, medium growth and slow decrease phases, with annual growth rates of 12.60%, 4.77% and -1.24%, respectively); (2) the energy intensity effect from 2000-2011 inhibited carbon emissions but was exceeded by the economic output effect, which increased emissions, whereas the energy intensity effect from 2011-2014 outweighed the economic output effect; (3) the scenario analyses revealed that both the comparative and absolute decoupling scenarios would remain consistent with the carbon emissions boundaries in 2020 and 2030, but the comparative decoupling scenario was more reasonable for sustainable development. In addition, appropriate design of emission trading scheme could help to achieve the comparative decoupling by financial incentives. [ABSTRACT FROM AUTHOR]

The winter haze is a growing problem in North China, but the causes are not well understood. The chemistry version of theWeather Research and Forecasting model (WRF-Chem) was applied in North China to examine how PM2.5 concentrations change in response to changes in emissions (sulfur dioxide (SO2), black carbon (BC), organic carbon (OC), ammonia (NH3), and nitrogen oxides (NOx)), as well as meteorology (temperature, relative humidity (RH), and wind speeds) changes in winter. From 1960 to 2010, the dramatic changes in emissions lead to +260% increases in sulfate, +320% increases in nitrate, +300% increases in ammonium, +160% increases in BC, and +50% increases in OC. The responses of PM2.5 to individual emission species indicate that the simultaneous increases in SO2, NH3, and NOx emissions dominated the increases in PM2.5 concentrations. PM2.5 shows more notable increases in response to changes in SO2 and NH3 as compared to increases in response to changes in NOx emissions. In addition, OC also accounts for a large fraction in PM2.5 changes. These results provide some implications for haze pollution control. The responses of PM2.5 concentrations to temperature increases are dominated by changes in wind fields and mixing heights. PM2.5 shows relatively smaller changes in response to temperature increases and RH decreases compared to changes in response to changes in wind speed and aerosol feedbacks. From 1960 to 2010, aerosol feedbacks have been significantly enhanced due to higher aerosol loadings. The discussions in this study indicate that dramatic changes in emissions are the main cause of increasing haze events in North China, and long-term trends in atmospheric circulations may be another important cause since PM2.5 is shown to be substantially affected by wind speed and aerosol feedbacks. More studies are necessary to get a better understanding of the aerosol-circulation interactions. [ABSTRACT FROM AUTHOR]

Tropospheric ozone (O3) is a trace gas playing important roles in atmospheric chemistry, air quality and climate change. In contrast to North America and Europe, long-term measurements of surface O3 are very limited in China. We compile available O3 observations at Mt. Tai - the highest mountain over the North China Plain - during 2003-2015 and analyze the decadal change of O3 and its sources. A linear regression analysis shows that summertime O3 measured at Mt. Tai has increased significantly by 1.7 ppbv yr-1 for June and 2.1 ppbv yr-1 for the July-August average. The observed increase is supported by a global chemistry-climate model hindcast (GFDL-AM3) with O3 precursor emissions varying from year to year over 1980-2014. Analysis of satellite data indicates that the O3 increase was mainly due to the increased emissions of O3 precursors, in particular volatile organic compounds (VOCs). An important finding is that the emissions of nitrogen oxides (NOx) have diminished since 2011, but the increase of VOCs appears to have enhanced the ozone production efficiency and contributed to the observed O3 increase in central eastern China. We present evidence that controlling NOx alone, in the absence of VOC controls, is not sufficient to reduce regional O3 levels in North China in a short period. [ABSTRACT FROM AUTHOR]

Against a background of climate change, Macau is very exposed to sea level rise (SLR) because of its low elevation, small size, and ongoing land reclamation. Therefore, we evaluate sea level changes in Macau, both historical and, especially, possible future scenarios, aiming to provide knowledge and a framework to help accommodate and protect against future SLR. Sea level in Macau is now rising at an accelerated rate: 1.35 mm yr over 1925-2010 and jumping to 4.2 mm yr over 1970-2010, which outpaces the rise in global mean sea level. In addition, vertical land movement in Macau contributes little to local sea level change. In the future, the rate of SLR in Macau will be about 20% higher than the global average, as a consequence of a greater local warming tendency and strengthened northward winds. Specifically, the sea level is projected to rise 8-12, 22-51 and 35-118 cm by 2020, 2060 and 2100, respectively, depending on the emissions scenario and climate sensitivity. Under the +8.5 W m Representative Concentration Pathway (RCP8.5) scenario the increase in sea level by 2100 will reach 65-118 cm-double that under RCP2.6. Moreover, the SLR will accelerate under RCP6.0 and RCP8.5, while remaining at a moderate and steady rate under RCP4.5 and RCP2.6. The key source of uncertainty stems from the emissions scenario and climate sensitivity, among which the discrepancies in SLR are small during the first half of the 21st century but begin to diverge thereafter. [ABSTRACT FROM AUTHOR]

Historical temperature variability over China during the twentieth century and projected changes under three emission scenarios for the twenty-first century are evaluated on the basis of a multimodel ensemble of 20 GCMs from phase 5 of the Coupled Model Intercomparison Project (CMIP5) and two observational datasets. Changes relative to phase 3 of the Coupled Model Intercomparison Project (CMIP3) are assessed, and the performance of individual GCMs is also quantified. Compared with observations, GCMs have substantial cold biases over the Tibetan Plateau, especially in the cold season. The timing and location of these biases also correspond to the greatest disagreement among the individual models, indicating GCMs' limitations in reproducing climatic features in this complex terrain. The CMIP5 multimodel ensemble shows better agreement with observations than CMIP3 in terms of the temperature biases. Both CMIP3 and CMIP5 capture the climatic warming over the twentieth century. However, the magnitude of the annual mean temperature trends is underestimated. There is also limited agreement in the spatial and seasonal patterns of temperature trends over China. Based on six statistical measures, four individual models-the Max Planck Institute Earth System Model, low resolution (MPI-ESM-LR), Second Generation Canadian Earth System Model (CanESM2), Model for Interdisciplinary Research on Climate, Earth System Model (MIROC-ESM), and Community Climate System Model, version 4 (CCSM4)-best represent surface air temperature variability over China. The future temperature projections indicate that the representative concentration pathway (RCP) 8.5 and RCP 4.5 scenarios exhibit a gradual increase in annual temperature during the twenty-first century at a rate of 0.60° and 0.27°C (10 yr)−1, respectively. As the lowest-emission mitigation scenario, RCP 2.6 projects the lowest rate of temperature increase [0.10°C (10 yr)−1]. By the end of the twenty-first century, temperature is projected to increase by 1.7°-5.7°C, with larger warming over northern China and the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

Multi-decadal high resolution simulations over the CORDEX East Asia domain were performed with the regional climate model RegCM3 nested within the Flexible Global Ocean-Atmosphere-Land System model, Grid-point Version 2 (FGOALS-g2). Two sets of simulations were conducted at the resolution of 50 km, one for present day (1980-2005) and another for near-future climate (2015-40) under the Representative Concentration Pathways 8.5 (RCP8.5) scenario. Results show that RegCM3 adds value with respect to FGOALS-g2 in simulating the spatial patterns of summer total and extreme precipitation over China for present day climate. The major deficiency is that RegCM3 underestimates both total and extreme precipitation over the Yangtze River valley. The potential changes in total and extreme precipitation over China in summer under the RCP8.5 scenario were analyzed. Both RegCM3 and FGOALS-g2 results show that total and extreme precipitation tend to increase over northeastern China and the Tibetan Plateau, but tend to decrease over southeastern China. In both RegCM3 and FGOALS-g2, the change in extreme precipitation is weaker than that for total precipitation. RegCM3 projects much stronger amplitude of total and extreme precipitation changes and provides more regional-scale features than FGOALS-g2. A large uncertainty is found over the Yangtze River valley, where RegCM3 and FGOALS-g2 project opposite signs in terms of precipitation changes. The projected change of vertically integrated water vapor flux convergence generally follows the changes in total and extreme precipitation in both RegCM3 and FGOALS-g2, while the amplitude of change is stronger in RegCM3. Results suggest that the spatial pattern of projected precipitation changes may be more affected by the changes in water vapor flux convergence, rather than moisture content itself. [ABSTRACT FROM AUTHOR]

The Chinese Spring Festival is one of the most important traditional festivals in China. The peak transport in the Spring Festival season (spring travel rush) provides a unique opportunity for investigating the impact of human activity on air quality in the Chinese megacities. Emission sources are varied and fluctuate greatly before, during and after the Festival. Increased vehicular emissions during the "spring travel rush" before the 2009 Festival resulted in high level pollutants of NOx (270 µgm-3), CO (2572 µgm-3 black carbon (BC) (8.5 µgm -3and extremely low single scattering albedo of 0.76 in Shanghai, indicating strong, fresh combustion. Organics contributed most to PM2.5, followed by NO-3 , NH4+, and SO 42- . During the Chinese Lunar New Year's Eve and Day, widespread usage of fireworks caused heavy pollution of extremely high aerosol concentration, scattering coefficient, SO2 , and NOx. Due to the "spring travel rush" after the festival, anthropogenic emissions gradually climbed and mirrored corresponding increases in the aerosol components and gaseous pollutants. Secondary inorganic aerosol (SO42- , NO3- , and NH+4 ) accounted for a dominant fraction of 74% in PM2.5 due to an increase in human activity. There was a greater demand for energy as vast numbers of people using public transportation or driving their own vehicles returned home after the Festival. Factories and constructions sites were operating again. The potential source contribution function (PSCF) analysis illustrated the possible source areas for air pollutants of Shanghai. The effects of regional and long-range transport were both revealed. Five major sources, i.e. natural sources, vehicular emissions, burning of fireworks, industrial and metallurgical emissions, and coal burning were identified using the principle component analysis. The average visibility during the whole study period was less than 6 km. It had been estimated that 50% of the total light extinction was due to the high water vapor in the atmosphere. This study demonstrates that organic aerosol was the largest contributor to aerosol extinction at 47 %, followed by sulfate ammonium, nitrate ammonium, and EC at 22 %, 14 %, and 12 %, respectively. Our results indicated the dominant role of traffic-related aerosol species (i.e. organic aerosol, nitrate and EC) on the formation of air pollution, and suggested the importance of controlling vehicle numbers and emissions in mega-cities of China as its population and economy continue to grow. [ABSTRACT FROM AUTHOR]

Huabei, located between 32° N and 42° N, is part of eastern China and includes administratively the Beijing and Tianjin Municipalities, Hebei and Shanxi Provinces, and Inner-Mongolia Autonomous Region. Over the past decades, the region has experienced dramatic changes in air quality and climate, and has become a major focus of environmental research in China. Here we present a new inventory of air pollutant emissions in Huabei for the year 2003 developed as part of the project Influence of Pollution on Aerosols and Cloud Microphysics in North China (IPAC-NC). Our estimates are based on data from the statistical yearbooks of the state, provinces and local districts, including major sectors and activities of power generation, industrial energy consumption, industrial processing, civil energy consumption, crop straw burning, oil and solvent evaporation, manure, and motor vehicles. The emission factors are selected from a variety of literature and those from local measurements in China are used whenever available. The estimated total emissions in the Huabei administrative region in 2003 are 4.73 Tg SO2, 2.72 Tg NOx (in equivalent NO2), 1.77 Tg VOC, 24.14 Tg CO, 2.03 Tg NH3, 4.57 Tg PM10, 2.42 Tg PM2.5, 0.21 Tg EC, and 0.46 Tg OC. For model convenience, we consider a larger Huabei region with Shandong, Henan and Liaoning Provinces included in our inventory. The estimated total emissions in the larger Huabei region in 2003 are: 9.55 Tg SO2, 5.27 Tg NOx (in equivalent NO2), 3.82 Tg VOC, 46.59 Tg CO, 5.36 Tg NH3, 10.74 Tg PM10, 5.62 Tg PM2.5, 0.41 Tg EC, and 0.99 Tg OC. The estimated emission rates are projected into grid cells at a horizontal resolution of 0.1° latitude by 0.1° longitude. Our gridded emission inventory consists of area sources, which are classified into industrial, civil, traffic, and straw burning sectors, and large industrial point sources, which include 345 sets of power plants, iron and steel plants, cement plants, and chemical plants. The estimated regional NO2 emissions are about 2-3% (administrative Huabei region) or 5% (larger Huabei region) of the global anthropogenic NO2 emissions. We compare our inventory (IPAC-NC) with the global emission inventory EDGAR-CIRCE and the Asian emission inventory INTEXB. Except for a factor of 3 lower EC emission rate in comparison with INTEX-B, the biases of the total emissions of most primary air pollutants in Huabei estimated in our inventory, with respect to EDGAR-CIRCE and INTEX-B, generally range from -30% to +40 %. Large differences up to a factor of 2-3 for local emissions in some areas (e.g. Beijing and Tianjin) are found. It is recommended that the inventories based on the activity rates and emission factors for each specific year should be applied in future modeling work related to the changes in air quality and atmospheric chemistry over this region. [ABSTRACT FROM AUTHOR]

Probabilistic projection of climate change consists of formulating the climate change information in a probabilistic manner at either global or regional scale. This can produce useful results for studies of the impact of climate change impact and change mitigation. In the present study, a simple yet effective approach is proposed with the purpose of producing probabilistic results of climate change over China for the middle and end of the twenty-first century under the Special Report on Emissions Scenarios A1B (SRES A1B) emission scenario. Data from 28 coupled atmosphere-ocean general circulation models (AOGCMs) are used. The methodology consists of ranking the 28 models, based on their ability to simulate climate over China in terms of two model evaluation metrics. Different weights were then given to the models according to their performances in present-day climate. Results of the evaluation for the current climate show that five models that have relatively higher resolutions-namely, the Istituto Nazionale di Geofisica e Vulcanologia ECHAM4 (INGV ECHAM4), the third climate configuration of the Met Office Unified Model (UKMO HadCM3), the CSIRO Mark version 3.5 (Mk3.5), the NCAR Community Climate System Model, version 3 (CCSM3), and the Model for Interdisciplinary Research on Climate 3.2, high-resolution version [MIROC3.2 (hires)]-perform better than others over China. Their corresponding weights (normalized to 1) are 0.289, 0.096, 0.058, 0.048, and 0.044, respectively. Under the A1B scenario, surface air temperature is projected to increase significantly for both the middle and end of the twenty-first century, with larger magnitude over the north and in winter. There are also significant increases in rainfall in the twenty-first century under the A1B scenario, especially for the period 2070-99. As far as the interannual variability is concerned, the most striking feature is that there are high probabilities for the future intensification of interannual variability of precipitation over most of China in both winter and summer. For instance, over the Yangtze-Huai River basin (28°-35°N, 105°-120°E), there is a 60%% probability of increased interannual standard deviation of precipitation by 20%% in summer, which is much higher than that of the mean precipitation. In general there are small differences between weighted and unweighted projections, but the uncertainties in the projected changes are reduced to some extent after weighting. [ABSTRACT FROM AUTHOR]

In China, due to lack of countrywide monitoring and coarse emission inventory of black carbon (BC) in early years, there are large uncertainties as to the estimations of its loading, direct radiative forcing (DRF) and climate response. Here, we apply an up-to-date emission inventory of BC in 2006 to investigate its loading, optical depth (AOD) at 550 nm and DRF using the coupled Regional Climate Chemistry Modeling System (RegCCMS). A state of the art air quality model (WRF/Chem) is also used to access surface BC concentration. Simulated surface concentrations of BC from these two models were compared with observations, while the AOD was compared with the results both from the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model and from satellite and ground-based simulations. Results show that RegCCMS presented similar patterns and levels of annual mean-surface BC concentration to those of WRF/Chem. The regional distributions and monthly variations of RegCCMS BC were reproduced well in comparison to observations. Simulated pattern of AODs are consistent to but lower than those from satellite (Omi-0.25°) and AERONET simulations. Annual mean DRFs mainly distribute in the area with high BC loadings, with regional mean of 0.75 W m and predicted global mean of 0.343 W m. In general, the results are about 0.4-5 times for regional column burden, about 2 times as high for regional mean DRFs, about 1.3-1.8 times for global mean DRFs and about 3-4 times for AOD at 550 nm as compared to those in previous studies in China. These increasing DRFs of BC imply that its warming effect and climate response should be stronger and the DRF of total aerosols should be weaker (less negative). [ABSTRACT FROM AUTHOR]

essment of the potential CO emission reduction by development of non-grain-based ethanol in China is valuable for both setting up countermeasures against climate change and formulating bioethanol policies. Based on the land occupation property, feedstock classification and selection are conducted, identifying sweet sorghum, cassava, and sweet potato as plantation feedstocks cultivated from low-quality arable marginal land resources and molasses and agricultural straws as nonplantation feedstocks derived from agricultural by-products. The feedstock utilization degree, CO reduction coefficient of bioethanol, and assessment model of CO emission reduction potential of bioethanol are proposed and established to assess the potential CO emission reduction by development of non-grain-based bioethanol. The results show that China can obtain emission reduction potentials of 10.947 and 49.027 Mt CO with non-grain-based bioethanol in 2015 and 2030, which are much higher than the present capacity, calculated as 1.95 Mt. It is found that nonplantation feedstock can produce more bioethanol so as to obtain a higher potential than plantation feedstock in both 2015 and 2030. Another finding is that developing non-grain-based bioethanol can make only a limited contribution to China's greenhouse gas emission reduction. Moreover, this study reveals that the regions with low and very low potentials for emission reduction will dominate the spatial distribution in 2015, and regions with high and very high potentials will be the majority in 2030. [ABSTRACT FROM AUTHOR]

According to the IPCC's Fourth Assessment Report, global emissions of carbon dioxide have to be reduced by about 80 per cent by 2050 in order to stabilise the increase in global temperature at 2 to 2.4°C by 2100 compared with its pre-industrial level. An increase of only 2°C would bring about "acceptable" negative impacts on the eco-systems and the world economy. Without a reduction in CO2 emissions in China, however, it will be hard to achieve this goal. Currently, China is already responsible for about 50 per cent of the worldwide increase in CO2 emissions recorded over the past ten years. On the other hand, it is the industrialised countries that are mainly responsible for the greenhouse-gas emissions of earlier years. Taking the challenges of China's economic growth, its impact on future CO2 emissions and the development of China's climate policy into account, this article develops a new post- Kyoto regime based on cumulative per-capita emission rights. [ABSTRACT FROM AUTHOR]

The article discusses global efforts to confront the challenge of climate change. A conference in Stockholm in 1972 acknowledged the problem, and in 1997 the multinational Kyoto Protocol established goals for reducing emissions. Since Kyoto rapid economic growth in India, China, and other developing nations has made action on climate change more urgent. China and the U.S. combined account for 40% of the world's greenhouse emissions. Among nations disagreement still exists as to what level emissions should be capped at.

Global terrestrial ecosystems absorbed carbon at a rate of 1–4 Pg yr-1 during the 1980s and 1990s, offsetting 10–60 per cent of the fossil-fuel emissions. The regional patterns and causes of terrestrial carbon sources and sinks, however, remain uncertain. With increasing scientific and political interest in regional aspects of the global carbon cycle, there is a strong impetus to better understand the carbon balance of China. This is not only because China is the world’s most populous country and the largest emitter of fossil-fuel CO2 into the atmosphere, but also because it has experienced regionally distinct land-use histories and climate trends, which together control the carbon budget of its ecosystems. Here we analyse the current terrestrial carbon balance of China and its driving mechanisms during the 1980s and 1990s using three different methods: biomass and soil carbon inventories extrapolated by satellite greenness measurements, ecosystem models and atmospheric inversions. The three methods produce similar estimates of a net carbon sink in the range of 0.19–0.26 Pg carbon (PgC) per year, which is smaller than that in the conterminous United States but comparable to that in geographic Europe. We find that northeast China is a net source of CO2 to the atmosphere owing to overharvesting and degradation of forests. By contrast, southern China accounts for more than 65 per cent of the carbon sink, which can be attributed to regional climate change, large-scale plantation programmes active since the 1980s and shrub recovery. Shrub recovery is identified as the most uncertain factor contributing to the carbon sink. Our data and model results together indicate that China’s terrestrial ecosystems absorbed 28–37 per cent of its cumulated fossil carbon emissions during the 1980s and 1990s. [ABSTRACT FROM AUTHOR]

Climate change and farmland environmental pollution have put greater pressure on the sustainability of agricultural production. Based on the provincial panel data of mainland China from 1978 to 2018, climate variables such as precipitation, temperature, and sunshine hours are included into the input indicators, and agricultural non-point source pollution and carbon emissions are taken as undesirable outputs, the agricultural production efficiency (APE) under the dual constraints of climate change and the resource environment was estimated by the super slacks-based measure (SBM)-undesirable model. On the basis of the trajectory of the imbalanced spatiotemporal evolution of APE shown by Kernel density estimation and the standard deviational ellipse (SDE)–center of gravity (COG) transfer model, the spatial convergence model was used to test the convergence and differentiation characteristics of APE. Under the dual constraints, APE presents a "bimodal" distribution with a stable increase in fluctuation, but it is still at a generally low level and does not show polarization, among which the APE in the northeast region is the highest. The COG of APE tends to transfer towards the northeast, and the coverage of the SDE is shrinking, so the overall spatial pattern is characterized by a tendency of clustering towards the north in the north-south direction and a tendency of imbalance in the east-west direction. APE has significant spatial convergence, and there is a trend of "latecomer catching-up" in low-efficiency regions. The introduction of spatial correlation accelerates the convergence rate and shortens the convergence period. The convergence rate is the highest in the central and western regions, followed by that in the northeastern region, and the convergence rate is the lowest in the eastern region. In addition, the convergence rate in different time periods has a phase change. The process of improving the quality and efficiency of agricultural production requires enhancing the adaptability of climate change, balancing the carrying capacity of the resource environment, and strengthening inter-regional cooperation and linkage in the field of agriculture. [ABSTRACT FROM AUTHOR]