Greenhouse Gas And Air Pollution Interactions And Synergies Research Articles

Air Pollution and Mortality in India: Investigating the Nexus of Ambient and Household Pollution Across Life Stages.

Air pollution in India is a foremost environmental risk factor that affects human health. This study first investigates the geographical distribution of ambient and household air pollution (HAP) and then examines the associated mortality risk. Data on fine particulate matter (PM2.5) concentration has been extracted from the Greenhouse Gas Air Pollution Interactions and Synergies (GAINS) model. HAP, mortality and socio-demographic data were extracted from the National Family and Health Survey-5, India, 2019-2021. Regression models were applied to see the difference in age-group mortality by different pollution parameters. The districts with PM2.5 concentration above the National Ambient Air Quality Standard (NAAQS) level of 40μg/m3 show a higher risk of neonatal (OR-1.86, CI 1.418-2.433), postneonatal (OR-2.04, CI 1.399-2.971), child (OR-2.19, CI 0.999-4.803) and adult death (OR-1.13, CI 1.060-1.208). The absence of a separate kitchen shows a higher probability of neonatal (OR: 1.18, CI 1.074-1.306) and adult death (OR-1.06, CI 1.027-1.088). The interaction between PM2.5 levels above NAAQS and HAP leads toa substantial rise in mortality observed for neonatal (OR 1.19 CI 1.051-1.337), child (OR 1.17 CI 1.054-1.289), and adult (OR 1.13 CI 1.096-1.168) age groups. This study advocates that there is a strong positive association between ambient and HAP and mortality risk. PM2.5 pollution significantly contributes to the mortality risk in all age groups. Children are more vulnerable to HAP than adults. In India, policymakers should focus on reducing the anthropogenic PM2.5 emission at least to reach the NAAQS, which can substantially reduce disease burden and, more precisely, mortality.

Global scenarios of anthropogenic mercury emissions

Abstract. Anthropogenic mercury (Hg) emissions to the atmosphere are a long-lived hazard to human and environmental health. The UN Minamata Convention on Mercury is seeking to lower anthropogenic mercury emissions through a mix of policies from banning certain Hg uses to reducing unintentional Hg release from different activities. In addition to independent Hg policy, strategies to mitigate greenhouse gases, particulate matter (PM) and SO2 may also lower Hg emissions as a co-benefit. This study uses the Greenhouse Gas–Air Pollution Interactions and Synergies (GAINS) model to examine the effect of different clean air and climate policies on future global Hg emissions. The baseline scenario assumes current trends for energy use and Hg emissions as well as current legislation for clean air, mercury and climate policy. In addition, we explore the impact of the Minamata Convention, the co-benefits of climate and stringent air pollution policies, and maximum feasible reduction measures for Hg. Hg emission projections until 2050 show noticeable reductions in combustion sectors for all scenarios due to a decrease in global fossil fuel and traditional biomass use, leading to emission reductions of 33 % at baseline and up to 90 % when combining stringent climate controls and the most efficient Hg controls. Cement and non-ferrous metal emissions increase in all scenarios with current air pollution policy but could be reduced by up to 72 % and 46 %, respectively, in 2050 with stringent Hg-specific measures. Other emissions (including waste) are a significant source of uncertainty in this study, and their projections range between a 22 % increase and a 54 % decrease in 2050, depending on both climate and clean air policy. The largest absolute reduction potential for Hg abatement but also the largest uncertainties regarding absolute emissions lie in small-scale and artisanal gold production, where abatement measures could eliminate annual Hg emissions in the range of 601–1371 t (95 % confidence interval), although the uncertainties in the estimate are so high that they might eclipse reduction efforts in all other sectors. In total, 90 % of Hg emissions are covered by provisions of the Minamata Convention. Overall, the findings emphasize the necessity to implement targeted Hg control policies in addition to stringent climate, PM and SO2 policies to achieve significant reductions in Hg emissions.

Development of a greenhouse gas - air pollution interactions and synergies model for Korea (GAINS-Korea)

This study aimed to create Greenhouse Gas - Air Pollution Interactions and Synergies (GAINS)-Korea, an integrated model for evaluating climate and air quality policies in Korea, modeled after the international GAINS model. GAINS-Korea incorporates specific Korean data and enhances granularity for enabling local government-level analysis. The model includes source-receptor matrices used to simulate pollutant dispersion in Korea, generated through CAMx air quality modeling. GAINS-Korea's performance was evaluated by examining different scenarios for South Korea. The business as usual scenario projected emissions from 2010 to 2030, while the air quality scenario included policies to reduce air pollutants in line with air quality and greenhouse gas control plans. The maximum feasible reduction scenario incorporated more aggressive reduction technologies along with air quality measures. The developed model enabled the assessment of emission reduction effects by both greenhouse gas and air pollutant emission reduction policies across 17 local governments in Korea, including changes in PM2.5 (particulate matter less than 2.5 μm) concentration and associated benefits, such as reduced premature deaths. The model also provides a range of visualization tools for comparative analysis among different scenarios, making it a valuable resource for policy planning and evaluation, and supporting decision-making processes.

A tool for air pollution scenarios (TAPS v1.0) to enable global, long-term, and flexible study of climate and air quality policies

Abstract. Air pollution is a major sustainability challenge – and future anthropogenic precursor and greenhouse gas (GHG) emissions will greatly affect human well-being. While mitigating climate change can reduce air pollution both directly and indirectly, distinct policy levers can affect these two interconnected sustainability issues across a wide range of scenarios. We help to assess such issues by presenting a public Tool for Air Pollution Scenarios (TAPS) that can flexibly assess pollutant emissions from a variety of climate and air quality actions, through the tool's coupling with socioeconomic modeling of climate change mitigation. In this study, we develop and implement TAPS with three components: recent global and fuel-specific anthropogenic emissions inventories, scenarios of emitting activities to 2100 from the MIT Economic Projection and Policy Analysis (EPPA) model, and emissions intensity trends based on recent scenario data from the Greenhouse Gas–Air Pollution Interactions and Synergies (GAINS) model. An initial application shows that in scenarios with less climate and pollution policy ambition, near-term air quality improvements from existing policies are eclipsed by long-term emissions increases – particularly from industrial processes that combine sharp production growth with less stringent pollution controls in developing regions. Additional climate actions would substantially reduce air pollutant emissions related to fossil fuel (such as sulfur and nitrogen oxides), while further pollution controls would lead to larger reductions for ammonia and organic carbon (OC). Future applications of TAPS could explore diverse regional and global policies that affect these emissions, using pollutant emissions results to drive global atmospheric chemical transport models to study the scenarios' health impacts.

Emissions and spatial distribution of air pollutants from anthropogenic sources in Jakarta

This study aims to develop emission inventory and emission spatial distribution of NOX, CO, PM2.5, PM10, NMVOC, BC, and SO2 from anthropogenic sources in Jakarta from 2015 to 2030, using 2015 as a baseline year. The results from this study can be very important to improve the emission data for Jakarta and contribute to the global emission model. Emissions of these pollutants were calculated using GAINS (Greenhouse gas Air pollution INteractions and Synergies) model, considering implementation of emission standards for transport and stationary combustion sources as well as policies stimulating accelerated electrification of vehicle fleets and vehicle scrapping programs. The impact of current policies to emission reduction was also evaluated in this study. The total 2015 emissions of NOX, CO, PM2.5, PM10, NMVOC, BC and SO2 were estimated at around 53 Gg, 144 Gg, 4.6 Gg, 6 Gg, 48.6 Gg, 1.2 Gg, and 20 Gg, respectively. The biggest contribution for NOx, CO, BC and NMVOC emissions originated from road transportation sector which contributed about 57%, 93% and 75%, 96% respectively, while for SO2, industrial combustion contributed about 67%. Heavy duty vehicles contribute the most NOx and BC emissions in the transport sector, while motorcycles emit the most CO. PM2.5 and PM10 in Jakarta are mostly emitted from road transportation and industrial combustion sectors, which contributed around 43%–46% for each sector. Heavy duty vehicles were still the highest contributor of PM2.5 emission in the transport sector. Based on emission spatial distribution and the AERMOD dispersion model, the highest concentration of all pollutants was found in the central of Jakarta, where traffic activities are very busy. Policy implementation could effectively reduce pollution levels in Jakarta. The accelerated implementation of electric vehicles, stringent emission standards, and transport management measures like electronic road pricing could significantly contribute to the reduction of PM2.5, PM10 as well as BC.

Health and Economic Impact Assessment of Transport and Industry PM2.5 Control Policy in Guangdong Province

PM2.5 pollution-related diseases lead to additional medical expenses and the loss of working hours, thus affecting the macro-economy. To evaluate the health-related economic impacts of PM2.5, the Integrated Assessment Model of Climate, Economic, and Environment (ICEEH), combined with the Computable General Equilibrium (CGE) model, the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) model, and a health impact assessment module was constructed. The impact of different air pollution control strategies was analyzed in Guangdong Province by establishing a Without Control (WOC) scenario, an Air Control (AIC) scenario, and a Blue Sky (BLK) scenario. The results show that in the WOC scenario for 2035, the death rate for Guangdong Province is 71,690 persons/year and the loss of working hours is 0.67 h/person/year. In the AIC and BLK scenarios compared with WOC for 2035, the loss of working hours is reduced by 29.8% and 34.3%, and premature deaths are reduced by 33.0% and 37.5%, respectively; GDP would increase by 0.05% and 0.11%, respectively, through strict pollution control policies. Furthermore, improved labor force quality induced by better air conditions would promote the added value in labor-intensive industries, such as agriculture (0.233%), other manufacturing (0.172%), textiles (0.181%), food (0.176%), railways transport (0.137%), and services (0.129%). The added value in the waste (−0.073%), nature gas (−0.076%), and crude oil sectors (−0.072%) would decrease because of the increased investment installment in PM2.5 treatment equipment.

Interregional spillover effect of PM2.5 emissions on Northeast China through the national supply chain

The booming economy has worsened air pollution problems via energy-related production and consumption activities. Increasing cross-regional economic trading activities have also led to unexpected environmental externalities from PM2.5. To better understand the features of the interregional environmental impact of PM2.5 emissions, an integrated three-dimensional spillover effect assessment framework was proposed based on multiregional input–output analysis (MRIOA), the Greenhouse Gas-Air Pollution Interactions and Synergies (GAINS) model and the integrated exposure–response (IER) model. Taking Northeast China as a case study, we inventoried the sectoral PM2.5 emissions and additional PM2.5 emissions of supplying intermediate products/services to identify the direct PM2.5 spillover effect embodied in economic trade. Then, the demand-driven spillover effect was assessed via the PM2.5 emissions and flows driven by the final demand based on MRIOA at sectoral and regional levels. Finally, the PM2.5 spillover effect on public health in the target area was measured by the quantification of PM2.5-related mortality and economic loss based on the GAINS and IER models. The results showed that energy-related sectors like the petroleum and gas sector were among the prominent sectors influenced by the spillover effect of PM2.5. The spillover effect of increasing PM2.5 emissions in Northeast China was mainly caused by the final demand of developed areas such as Beijing, Tianjin, Shanghai, Zhejiang and Guangdong. The mortality, extra medical cost and labor loss in local areas have increased by 20–25% due to embodied PM2.5 emissions induced by non-Northeast China. The proposed three-dimensional spillover effect assessment framework could shed insight on the potential impacts of economic trade on local air quality and human health, thus shaping PM2.5 emission mitigation strategies from a cross-regional perspective.

Improving Human Health in China Through Alternative Energy.

In this study, we estimate the health benefits of more stringent alternative energy goals and the costs of reducing coal-fired power plant pollution in China projected in 2030. One of our two overarching alternative energy goals was to estimate the health benefits of complete elimination of coal energy, supplemented by natural gas and renewables. The second was a policy scenario similar to the U.S. 2013 Climate Action Plan (CAP), which played a pivotal role leading up to the 2015 Paris Climate Agreement. We used the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) model created by the International Institute for Applied Systems Analysis for our model simulations. We found that 17,137–24,220 premature deaths can be avoided if coal energy is completely replaced by alternative energy, and 8,693–9,281 premature deaths can be avoided if coal energy is replaced by alternatives in a CAP-like scenario. A CAP-like scenario using emission-controls in coal plants costs $11–18 per person. Reducing coal energy in China under a CAP-like scenario would free up $9.4 billion in the annual energy budget to spend on alternatives, whereas eliminating the cost of coal energy frees up $32 billion. This study's estimates show that more stringent alternative energy targets in China are worth the investment in terms of health.

Sectoral emissions contributions to anthropogenic aerosol scenarios over the Indian subcontinent and effects of mitigation on air quality, climate, and health

Over the last few decades, there have been substantial changes in sectoral anthropogenic emissions over India, modifying the region’s air quality and radiation budget. However, these sectoral contributions are still poorly understood. This study attempts to estimate the anthropogenic aerosols and SO2 emissions from different sectors over the Indian subcontinent and their implications for regional climate and human health using the RegCM4.4 regional climate model and the Greenhouse Gas-Air Pollution Interactions and Synergies (GAINS) global model. We consider current emissions as well as emissions with a mitigation scenario for the year 2030. The RegCM simulations with ECLIPSE v5a as emissions inventory for 2000 and 2015 show high SO2 emissions from the energy sector, substantially contributing to anthropogenic aerosol optical depth (AODanthro) and climate forcing. The residential and transport sectors’ imprint on climate forcing is increased in 2015 compared to 2000. Higher AODanthro (0.35-0.45) occurrence days substantially decrease under a mitigation scenario by 5-10% over the Indo-Gangetic Plain. In particular, over 5�megacities (Delhi, Kolkata, Mumbai, Chennai, and Bangalore) of India, the concentrations of black carbon, organic carbon, and particulate matter ≤2.5 µm in diameter (PM2.5) are substantially reduced under the mitigation scenario; however, SO2 is increased. The reduction of pollutants contributes to significantly reducing life expectancy loss in all cities. This study advocates the need for future emission control policies with a synergy between air quality and climate change.

Size-resolved particle number emissions in Beijing determined from measured particle size distributions

Abstract. The climate and air quality effects of aerosol particles depend on the number and size of the particles. In urban environments, a large fraction of aerosol particles originates from anthropogenic emissions. To evaluate the effects of different pollution sources on air quality, knowledge of size distributions of particle number emissions is needed. Here we introduce a novel method for determining size-resolved particle number emissions, based on measured particle size distributions. We apply our method to data measured in Beijing, China, to determine the number size distribution of emitted particles in a diameter range from 2 to 1000 nm. The observed particle number emissions are dominated by emissions of particles smaller than 30 nm. Our results suggest that traffic is the major source of particle number emissions with the highest emissions observed for particles around 10 nm during rush hours. At sizes below 6 nm, clustering of atmospheric vapors contributes to calculated emissions. The comparison between our calculated emissions and those estimated with an integrated assessment model GAINS (Greenhouse Gas and Air Pollution Interactions and Synergies) shows that our method yields clearly higher particle emissions at sizes below 60 nm, but at sizes above that the two methods agree well. Overall, our method is proven to be a useful tool for gaining new knowledge of the size distributions of particle number emissions in urban environments and for validating emission inventories and models. In the future, the method will be developed by modeling the transport of particles from different sources to obtain more accurate estimates of particle number emissions.

Development of the CREATE Inventory in Support of Integrated Climate and Air Quality Modeling for Asia

A bottom-up emissions inventory is one of the most important data sets needed to understand air quality (AQ) and climate change (CC). Several emission inventories have been developed for Asia, including Transport and Chemical Evolution over the Pacific (TRACE-P), Regional Emission Inventory in Asia (REAS), and Inter-Continental Chemical Transport Experiment (INTEX) and, while these have been used successfully for many international studies, they have limitations including restricted amounts of information on pollutant types and low levels of transparency with respect to the polluting sectors or fuel types involved. To address these shortcomings, we developed: (1) a base-year, bottom-up anthropogenic emissions inventory for Asia, using the most current parameters and international frameworks (i.e., the Greenhouse gas—Air pollution INteractions and Synergies (GAINS) model); and (2) a base-year, natural emissions inventory for biogenic and biomass burning. For (1), we focused mainly on China, South Korea, and Japan; however, we also covered emission inventories for other regions in Asia using data covering recent energy/industry statistics, emission factors, and control technology penetration. The emissions inventory (Comprehensive Regional Emissions inventory for Atmospheric Transport Experiment (CREATE)) covers 54 fuel classes, 201 subsectors, and 13 pollutants, namely SO2, NOx, CO, non-methane volatile organic compounds (NMVOC), NH3, OC, BC, PM10, PM2.5, CO2, CH4, N2O, and Hg. For the base-year natural emissions inventory, the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and BlueSky-Asia frameworks were used to estimate biogenic and biomass burning emissions, respectively. Since the CREATE emission inventory was designed/developed using international climate change/air quality (CC/AQ) assessment frameworks, such as GAINS, and has been fully connected with the most comprehensive emissions modeling systems—such as the US Environmental Protection Agency (EPA) Chemical Manufacturing Area Source (CMAS) system—it can be used to support various climate and AQ integrated modeling studies, both now and in the future.

Technical potentials and costs for reducing global anthropogenic methane emissions in the 2050 timeframe –results from the GAINS model

Methane is the second most important greenhouse gas after carbon dioxide contributing to human-made global warming. Keeping to the Paris Agreement of staying well below two degrees warming will require a concerted effort to curb methane emissions in addition to necessary decarbonization of the energy systems. The fastest way to achieve emission reductions in the 2050 timeframe is likely through implementation of various technical options. The focus of this study is to explore the technical abatement and cost pathways for reducing global methane emissions, breaking reductions down to regional and sector levels using the most recent version of IIASA’s Greenhouse gas and Air pollution Interactions and Synergies (GAINS) model. The diverse human activities that contribute to methane emissions make detailed information on potential global impacts of actions at the regional and sectoral levels particularly valuable for policy-makers. With a global annual inventory for 1990–2015 as starting point for projections, we produce a baseline emission scenario to 2050 against which future technical abatement potentials and costs are assessed at a country and sector/technology level. We find it technically feasible in year 2050 to remove 54 percent of global methane emissions below baseline, however, due to locked in capital in the short run, the cumulative removal potential over the period 2020–2050 is estimated at 38 percent below baseline. This leaves 7.7 Pg methane released globally between today and 2050 that will likely be difficult to remove through technical solutions. There are extensive technical opportunities at low costs to control emissions from waste and wastewater handling and from fossil fuel production and use. A considerably more limited technical abatement potential is found for agricultural emissions, in particular from extensive livestock rearing in developing countries. This calls for widespread implementation in the 2050 timeframe of institutional and behavioural options in addition to technical solutions.

Toward the 2-degree target: Evaluating co-benefits of road transportation in China

BackgroundCo-benefit assessments on health and economic impacts of climate change mitigation towards the 2-degree target are still largely insufficient in literature, especially from a sectoral perspective. ObjectivesThis study aims to (1) evaluate PM2.5 pollution-related health impacts on China's road transport sector at both national and provincial levels towards the 2-degree target by 2050; (2) uncover the contribution from the road transport sector compared with that of all sectors; (3) distinguish the contribution from climate change mitigation actions compared with air pollution control oriented actions in road transport sector; and (4) identify the heterogeneous influences at the provincial level. MethodsHealth and economic impacts are estimated using an integrated approach that combines the GAINS (Greenhouse Gas and Air Pollution Interactions and Synergies) model, the IMED/CGE (Integrated Model of Energy, Environment and Economy for Sustainable Development/computable general equilibrium) model and IMED/HEL (Health) model. Five scenarios are proposed based on climate change mitigation and stringency of air pollution control policy. ResultsIt is found that China's road transport sector could contribute to around 10.6% of total PM2.5 concentration reduction resulting from all sectors' participation in achieving the 2-degree target, equivalent to 10.8% of the monetized health benefits obtained from achieving the 2-degree target by all sectors. Populous provinces dependent on secondary industries would benefit more under the 2-degree target. Meanwhile, compared with the potential maximum benefits from air pollution control oriented measures in the road transport sector, such climate actions could bring noticeable synergies as well. Approximately climate change mitigation action alone can lead to 70% reduction of health impacts by applying air pollution control measures. ConclusionsThis research has implications for other emerging economies and those reluctant to engage in climate action and is deserving of further attention. The government should also realize the heterogeneity of road transport sector development in different provinces, and adopt a more flexible policy approach to take into account regional pollution levels and abatement options.

Applying Integrated Exposure-Response Functions to PM2.5 Pollution in India.

Fine particulate matter (PM2.5, diameter ≤2.5 μm) is implicated as the most health-damaging air pollutant. Large cohort studies of chronic exposure to PM2.5 and mortality risk are largely confined to areas with low to moderate ambient PM2.5 concentrations and posit log-linear exposure-response functions. However, levels of PM2.5 in developing countries such as India are typically much higher, causing unknown health effects. Integrated exposure-response functions for high PM2.5 exposures encompassing risk estimates from ambient air, secondhand smoke, and active smoking exposures have been posited. We apply these functions to estimate the future cause-specific mortality risks associated with population-weighted ambient PM2.5 exposures in India in 2030 using Greenhouse Gas-Air Pollution Interactions and Synergies (GAINS) model projections. The loss in statistical life expectancy (SLE) is calculated based on risk estimates and baseline mortality rates. Losses in SLE are aggregated and weighted using national age-adjusted, cause-specific mortality rates. 2030 PM2.5 pollution in India reaches an annual mean of 74 μg/m3, nearly eight times the corresponding World Health Organization air quality guideline. The national average loss in SLE is 32.5 months (95% Confidence Interval (CI): 29.7–35.2, regional range: 8.5–42.0), compared to an average of 53.7 months (95% CI: 46.3–61.1) using methods currently applied in GAINS. Results indicate wide regional variation in health impacts, and these methods may still underestimate the total health burden caused by PM2.5 exposures due to model assumptions on minimum age thresholds of pollution effects and a limited subset of health endpoints analyzed. Application of the revised exposure-response functions suggests that the most polluted areas in India will reap major health benefits only with substantial improvements in air quality.

Economic impacts from PM2.5 pollution-related health effects in China's road transport sector: A provincial-level analysis

Economic impact assessments of air pollution-related health effects from a sectoral perspective in China is still deficient. This study evaluates the PM2.5 pollution-related health impacts of the road transport sector on China's economy at both national and provincial levels in 2030 under various air mitigation technologies scenarios. Health impacts are estimated using an integrated approach that combines the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) model, a computable general equilibrium (CGE) model and a health model. Results show that at a national level, the road transport sector leads to 163.64 thousand deaths per year, increases the per capita risk of morbidity by 0.37% and accounts for 1.43 billion Yuan in health care expenditures. We estimate 442.90 billion Yuan of the value of statistical life loss and 2.09 h/capita of work time loss in 2015. Without additional control measures, air pollution related to the transport sector will cause 177.50 thousand deaths in 2030, a 0.40% per capita increase in the risk of morbidity, accounting for 4.12 billion Yuan in health care expenditures, 737.15 billion Yuan of statistical life loss and 2.23 h/capita of work time loss. Based on our model, implementing the most strict control strategy scenario would decrease mortality by 42.14%, morbidity risk by 42.14%, health care expenditures by 41.94%, statistical life loss by 26.22% and hours of work time loss by 42.65%, comparing with the no control measure scenario. In addition, PM2.5 pollution from the road transport sector will cause 0.68% GDP loss in 2030. At a provincial level, GDP losses in 14 out of 30 provinces far exceed the national rate. Henan (1.20%), Sichuan (1.07%), Chongqing (0.99%), Hubei (0.94%), and Shandong (0.90%) would experience the highest GDP loss in 2030. Implementing control strategies to reduce PM2.5 pollution in the road transport sector could bring positive benefits in half of the Chinese provinces especially in provinces that suffer greater health impacts from the road transport sector (such as Henan and Sichuan).

Emission Inventory of On-Road Transport in Bangkok Metropolitan Region (BMR) Development during 2007 to 2015 Using the GAINS Model

Bangkok Metropolitan Region (BMR), including the capital city and five adjacent provinces, constitutes one of the top 10 megacities experiencing serious traffic congestion in the world, leading to air quality problems with significant adverse human health risks. Previously, there have been many operations planned to influence the fuel consumption and emissions from the on-road transport sector in the BMR area. It is necessary to estimate emissions using detailed information in order to thoroughly understand the reason for changes in emission levels and their impact on air quality. This paper aims to determine the successful implementation of energy and air pollution control policies in Thailand through an investigation of the emissions inventory of on-road transport in BMR, including ozone precursors (CO, NOX, Non-methane volatile organic compounds (NMVOCs) ), greenhouse gases (CO2, CH4, N2O), acidic substances (SO2 and NH3), and particulate matters (PM2.5, PM10, Black Carbon (BC), Organic Carbon (OC)) during the period from 2007 to 2015, using the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) model based on the country-specific activity data together with the emission factor from the GAINS-Asia database. This study found that the amount of exhaust emissions over the BMR area in the year 2015 (and the trend during the period from 2007 to 2015) is approximately 139 kt of CO (−7.9%), 103 kt of NOX (−4.1%), 19.9 kt of NMVOC (−6.7%), 15 kt of CO2 (+1.6%), 8.6 kt of CH4 (+6.8%), 0.59 kt of N2O (+1.3%), 0.87 kt of SO2 (−25.8%), 1.1 kt of NH3 (+7.8%), 4.9 kt of PM2.5 (−5.5%), 5.1 kt of PM10 (−7.9%), 3.1 kt of BC (−2.5%), and 1.4 kt of OC (−7.7%). The change in emissions in each pollutant is a result of the more stringent control of fuel and engine standards, the shift in the fuel type used, and the effects of controlling some emissions. Light duty car gasoline fuel is identified as a major contributor of CO, NH3, N2O, and NMVOC, whereas trucks are the greatest emitters of NOX, SO2, and particulate matter. This study suggests that the most powerful implementation plan for the continuous, significant reduction of ozone precursor, SO2, and particulate matter emissions is the more stringent enforcement of fuel and vehicle standard levels, especially concerning light duty vehicles.

Mitigating ammonia emission from agriculture reduces PM2.5 pollution in the Hai River Basin in China

The Hai River Basin (HRB), one of the most populated areas in China, is experiencing high NH3 emissions, mostly from agricultural sources, and suffering from strongly enhanced PM2.5 concentrations in all urban areas. Further population growth and urbanization projected until 2030 may exacerbate this situation. Here, the NUFER (NUtrient flows in Food chains, Environment and Resources use) and GAINS (Greenhouse gas – Air pollution Interactions and Synergies) models have been coupled for the first time to understand possible changes of agricultural NH3 emission between 2012 and 2030 and their impacts on ambient PM2.5 concentrations, and to explore options to improve this situation. Results show that agricultural ammonia emissions in the HRB were 1179kt NH3 in 2012, 45% of which was from the hotspots at or near conurbation areas, including Beijing-Tianjin, Tangshan-Qinhuangdao, Shijiazhuang-Baoding, Dezhou, Handan-Liaocheng, and Xinxiang. Without intervention, agricultural ammonia emissions will further increase by 33% by 2030. The impacts of several scenarios were tested with respect to air pollution. Compared to the business-as-usual scenario, a scenario of improved technology and management combined with human diet optimization could greatly reduce emission (by 60%), and lead to 22–43% and 9–24% decrease of the secondary inorganic aerosols and PM2.5 concentrations, respectively, in the hotspots of NH3 emissions. Our results further confirmed that ammonia control is needed for air pollution abatement strategies (SO2, NOx and primary PM reduction) to be effective in terms of PM2.5.

Comparison of emissions inventories of anthropogenic air pollutants and greenhouse gases in China

Abstract. Anthropogenic air pollutant emissions have been increasing rapidly in China, leading to worsening air quality. Modelers use emissions inventories to represent the temporal and spatial distribution of these emissions needed to estimate their impacts on regional and global air quality. However, large uncertainties exist in emissions estimates. Thus, assessing differences in these inventories is essential for the better understanding of air pollution over China. We compare five different emissions inventories estimating emissions of carbon dioxide (CO2), carbon monoxide (CO), nitrogen oxides (NOx), sulfur dioxide (SO2), and particulate matter with an aerodynamic diameter of 10 µm or less (PM10) from China. The emissions inventories analyzed in this paper include the Regional Emission inventory in ASia v2.1 (REAS), the Multi-resolution Emission Inventory for China (MEIC), the Emission Database for Global Atmospheric Research v4.2 (EDGAR), the inventory by Yu Zhao (ZHAO), and the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS). We focus on the period between 2000 and 2008, during which Chinese economic activities more than doubled. In addition to national totals, we also analyzed emissions from four source sectors (industry, transport, power, and residential) and within seven regions in China (East, North, Northeast, Central, Southwest, Northwest, and South) and found that large disagreements exist among the five inventories at disaggregated levels. These disagreements lead to differences of 67 µg m−3, 15 ppbv, and 470 ppbv for monthly mean PM10, O3, and CO, respectively, in modeled regional concentrations in China. We also find that all the inventory emissions estimates create a volatile organic compound (VOC)-limited environment and MEIC emissions lead to much lower O3 mixing ratio in East and Central China compared to the simulations using REAS and EDGAR estimates, due to their low VOC emissions. Our results illustrate that a better understanding of Chinese emissions at more disaggregated levels is essential for finding effective mitigation measures for reducing national and regional air pollution in China.

Economic Impacts from PM2.5 Pollution-Related Health Effects: A Case Study in Shanghai.

PM2.5 pollution-related diseases cause additional medical expenses and work time loss, leading to macroeconomic impact in high PM2.5 concentration areas. Previous economic impact assessments of air pollution focused on benefits from environmental regulations while ignoring climate policies. In this study, we examine the health and economic impacts from PM2.5 pollution under various air pollution control strategies and climate policies scenarios in the megacity of Shanghai. The estimation adopts an integrated model combining a Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) model, exposure-response functions (ERFs), and a computable general equilibrium (CGE) model. The results show that without control measures, Shanghai's mortality caused by PM2.5 pollution are estimated to be 192 400 cases in 2030 and the work time loss to be 72.1 h/cap annually. The corresponding GDP values and welfare losses would be approximately 2.26% and 3.14%, respectively. With an estimated control cost of 0.76% of local GDP, Shanghai would gain approximately 1.01% of local GDP through local air pollution control measures and climate policies. Furthermore, the application of multiregional integrated control strategies in neighboring provinces would be the most effective in reducing PM2.5 concentration in Shanghai, leading to only 0.34% of GDP loss. At the sectoral level, labor-intensive sectors suffer more output loss from PM2.5 pollution. Sectors with the highest control costs include power generation, iron and steel, and transport. The results indicate that the combination of multiregional integrated air pollution control strategies and climate policies would be cost-beneficial for Shanghai.

Valuation of Public Goods: The Case of Emissions from Livestock Holdings in the Czech Republic

Designed paper is focused on the analysis of public goods in the form of greenhouse gas emissions in livestock production in Czechia. The main aim of the paper is to quantify the amount and valuation of greenhouse gas emissions produced in beef cattle breed (dairy and meat), pig breed, and poultry breed (meat and eggs). The partial aim of this paper is to compare greenhouse gas emissions production across sectors of livestock production and to evaluate a development of volume, value and share of emissions as a form of public goods. The methodology is based on the conceptual model MITERRA-Europe (The model was developed to assess the effects and interactions of policies and measures in agriculture on N losses and P balances at a regional level in EU-27), which is partly based on the CAPRI (Common Agricultural Policy Regionalised Impact) and the GAINS (Greenhouse Gas and Air Pollution Interactions and Synergies) models using the tools for quantification of the emission factors indicators defined by the IPCC (Intergovernmental Panel for Climate Change) organizations. Part of the solution is to determine the value of public goods quantified through a European platform for carbon emissions trading with its futures contract based on the EU Allowances. The result of this paper is quantified emission value of public goods in livestock production in Czechia and their appreciation in the period 2000-2014. In the final consequence is quantified the proportion of the value of public goods in the total production of the analyzed livestock sector.