# data[].attributes.headline
Environmental Impacts of Thar Coal Power Plant

# data[].attributes.subject
Environmental Impacts of Thar Coal Power Plant

# data[].attributes.body
The report's findings concerning Thar's pollution and health risks present an alarming scenario, emphasizing the need for more thorough environmental assessments. The imminent threat to public health, especially to the indigenous people, warrants immediate action. It also underscores regulatory agencies' failures to accurately assess and manage these risks. However, the critique hinges primarily on data validity and thoroughness; it could be strengthened by incorporating more perspectives such as economic considerations or the energy needs that these coal power projects address. Moreover, the interplay between climate change, local air quality, and public health, although hinted at, deserves more explicit discussion.

# data[].attributes.attachment_link.readable_text
KARACHI: "Coal energy is dirty energy. It is dirty as well as harmful energy that leads to health hazards, loss of livelihoods, further poverty, loss of lives, destruction of natural resources, loss of biodiversity and the massive displacement of indigenous people due to all these things," said Mohammad Ali Shah, chairman, Pakistan Fisherfolk Forum (PFF).

He was speaking during the launch of Air Pollution, Health and Toxic Impacts of the Proposed Coal Mining and Power Cluster in Thar, Pakistan, a study conducted by the Centre for Research on Energy and Clean Air (CREA), and conducted online via Zoom Meetings by the Alliance for Climate Justice and Clean Energy (ACJCE) on Friday.

"It is not that different from forced displacement. After all, how will the people carry on living at a place where their water sources have been compromised along with the polluting of the air they breathe, where the common grazing lands of their animals too have been encroached upon? But this is what is going on thanks to the coal power project in Tharparkar," he said, adding that in order to end the sufferings of the Thari people, the government should look towards adopting renewable energy projects while stopping the mining and import of coal for power generation.

The study looks at the consequences of mining and power production in Thar over an operating period of 30 years by examining coal blocks one, two and six, using the data provided by companies responsible for mining and power production.

Its findings show that Thar will be a major air pollutant and mercury and CO2 emission hotspot in South Asia, which is expected to be the cause of 29,000 air pollution-related deaths, 40,000 asthma emergency room visits, 19,906 new cases of asthma in children, 32,000 premature births etc.

Some 1,400kg of mercury per year is expected to be deposited from the nine coal plants that have been studied. And 320kg of this will be deposited in the immediate vicinity, a massive public health risk to the 100,000 indigenous people living in the project areas.

The report also indicates a range of failures by the environmental impact assessment (EIA) agencies.

There are errors and omissions in the data used in EIA reports of two coal power projects in block-II and one in block-VI as well as violations of the Sindh Ambient Air Quality Standards and guidelines of the World Health Organisation and the International Finance Corporation as they failed to take into account the mercury pollution, which is perhaps the most dangerous pollutant in coal power production.

"Since Pakistan is already suffering from air pollution levels that are among the highest in the world, the emissions induced by the coal mines and power plants of Thar will further reduce life expectancy in the country and increase the vulnerability of its citizens to the Covid-19 pandemic," said Lauri Myllyvirta, the lead analyst of CREA.

"One-fifth of the levels of mercury that will be emitted by the coal power plants would be deposited into land ecosystems in the region. Most of the deposition would take place onto cropland and increase the mercury concentrations in crops," he added.

"Given the actual incidences of legal non-compliance and misreporting involved in social and environmental impact assessments, land surveys, land acquisition and compensation and the monitoring processes adopted for development of Thar coal mines and power plants, what the study reveals is just a proverbial iceberg of misleading the public through data manoeuvring," said advocate Zubair Ahmad Abro of Alternative Law Collective, who has been fighting a legal battle for the communities adversely impacted by coal power projects in Thar.
Published in Dawn, May 30th, 2020

# data[].attributes.attachment_link.title
Study raises questions about environmental impact of Thar coal

# data[].attributes.attachment_link.description
KARACHI: "Coal energy is dirty energy. It is dirty as well as harmful energy that leads to health hazards, loss of...

# data[].attributes.body
This paper investigates climate change's impact on Pakistan, primarily floods' effects on agriculture. It uses remote sensing and mathematical models for quantification, but the study could benefit from more in-depth analysis and policy implications. Limited geographically, it could offer insights applicable to other regions. The utility and limitations of employed technology are not thoroughly examined, and the potential positive impacts of increased rainfall are overlooked. Despite its thoroughness in detailing physical effects, the study lacks depth in discussing social ramifications. The paper’s proposal to translate climate-induced losses into economic costs could have been explored further for comprehensive understanding.

# data[].attributes.attachment_link.readable_text
Introduction

There is increasing scientific evidence that human-induced climate change has caused severe environmental impacts and jeopardised global food security1,2,3. The frequency of floods and other extreme events has increased recently in South Asia and worldwide4 causing significant loss and damage, particularly in Pakistan5. Since the independence of Pakistan in 1947, the recurrence of the major flood is almost a decade or less, mostly due to heavy monsoon rainfall in July and August causing severe losses in terms of human lives, agriculture, infrastructure, property, and economy. Three major floods occurred in the last decade in 2010, 2011, and 2012, where the 2010 floods caused inundation of over 70,000 km ² and affected around 900,000 households6. The most recent' 2022 Pakistan floods' impacted approximately 33 million people, killing nearly 1500 people, and destroying critical infrastructure, agricultural land, and properties. In August 2022 Balochistan province of Pakistan received 590% more rainfall than normal while Sindh received 726% more rainfall than average for this month7. The World Weather Attribution group reports a 75% increase in heavy rainfall during the 60 days in the Indus River basin of Pakistan8.

The 2010, 2011, and 2022 floods in Pakistan affected approximately 55-60 million people with over 3500 deaths6,9,10. The floods in 2011 inundated over 21,000 km ² area, displaced 5.9 million people and damaged 1500 km of the road network, 382 km of railway tracks, 500 km ² of forests and over 16,000 km ² of agricultural land6. The 2012 floods inundated 13,157 km ² of the area in 22 districts of Pakistan damaging 2950 km ² of agricultural land, 1681 km of the road network, and 110 km of railway track9.

The post-disaster damages assessment is extremely important in the context of global warming causing more frequent extreme events. The loss and damages (L&D) assessment is key to post-disaster recovery and rehabilitation under the conference of parties (COP) commitments11. Frameworks of L&D assessments enable evidence-based policies to reduce the risk of disaster and its impacts on various sectors. Adaptation of the L&D mechanism in the agriculture sector (Fig. 1) can help in monitoring and evaluating the economic impacts of disasters and support the compensation mechanisms. The damages are partial or complete destruction of physical assets while production losses refer to declines in the value of agricultural production resulting from a disaster. The production losses not only cause deficits in the income of impacted communities but may also result in near-term food shortages in the region and it is likely to slow down the post-disaster recovery if not properly managed.

Satellite remote sensing is a powerful tool for assessing L&D caused by natural disasters such as floods, hurricanes, and earthquakes. Particularly for flood disaster, Synthetic Aperture Radar (SAR) satellites data can efficiently map flood extent12,13 and optical satellites can be used to detect differences in vegetation cover before and after a flood to assess the damage caused by flooding14,15. Researchers have developed mathematical models to estimate flood losses based on the physical processes in a river basin and stage-damage relationship for different land use features for economic loss estimation16. As such, a novel index Disaster Vegetation Damage Index (DVDI) was also developed to map the post-flood crop-specific damage that occurred soon after the flood event16. In earlier work on crop loss assessments from Earth Observation, a Cyber Service system (RF-CLASS) was designed to estimate crop losses for insurance decision-making17. Likewise, the temporal differences in the satellite-derived Normalized Difference Vegetation Index (NDVI) have been applied for depicting changes in vegetation conditions to determine the impacts of extreme climate events on tropical secondary forest succession18,19. Another study developed an integrated approach by combining the NDVI, Land Surface Temperature (LST), and satellite-based estimates of rainfall to characterize vegetation moisture stress in land covers including forest, shrubland, agriculture and grass20,21.

Building on earlier work on L&D assessment and accommodating the recent advances in satellite remote sensing, we developed an approach for evaluating crop-specific post-disaster production losses, in the severely affected Sindh province of Pakistan. The tools and methodologies developed in this study will support evidence-based policies for food security and resilient reconstruction. This will also contribute to standardise reporting on climate change-related losses.

Materials and methods

Description of the study area

The study area comprises the Sindh province of Pakistan (Fig. 2), with a total land area of ~ 14.1 million ha, of which ~ 35% (4.9 million ha) is agricultural land. Approximately one-fourth of the national economy comes from Sindh, of which 17% is contributed by the agriculture sector. The agricultural lands are irrigated by Indus Basin Irrigation System to grow various crops in the province. The major crops in the study area include cereal crops (wheat and rice), industrial crops (cotton and sugarcane), fruit crops (mango and guava), and horticultural crops (chilli, tomato, and sunflower). The climate of Sindh is Subtropical, with hot summers (May-August) and cold winters (December-January). Temperature ranges from 2 °C in winter to 46 °C in summer. Mean annual rainfall is about 150-180 mm but most of this amount falls during the monsoon season (July-September).

Location map of the study area and crop production zones in the Sindh Province of Pakistan, the maps were produced using the ArcGIS 10.7 ( www.esri.com).

Remote sensing and ground-based rainfall estimates

The estimates of incidental rainfall were derived from the Integrated Multi-satellitE Retrievals for GPM (IMERG), GPM_L3/IMERG_V06, which is based on the unified algorithm combining data to generate a multi-satellite precipitation product 22. The hourly rainfall product was used for spatially contiguous rainfall estimates as an alternative to scarcely distributed station data in the study area. The data were obtained and processed using the Google Earth Engine (GEE), a cloud computing platform, to derive daily estimates at a native spatial resolution of 0.1° (~ 1 km). The data was acquired from 1st August 2022 to 31st August 2022. Historic (1981-2010) and recent (August 2022) daily rainfall measurements from the ground stations (namely Mohenjo Daro, Sakran, Padidan, Larkana, Badin, Jacobabad, Nawabshah, and Rohri), in the study area, were acquired from Pakistan Meteorological Department (PMD). These data sets were used for relating the satellite-based rainfall estimates with ground observations. The daily rainfall estimates were also aggregated at the monthly interval to understand the spatial patterns of monthly accumulated rainfall during August 2022.

Flood extent mapping

Flood extent was mapped using pre- and post-event C-band Synthetic Aperture Radar (SAR) images from Sentinel-1B. The calibrated and ortho-corrected Level-1 Ground Range Detected (GRD) images at 10 m spatial resolution were obtained and processed using the 'COPERNICUS/S1_GRD' collection available on the GEE. Two sets of SAR images were acquired from, (1) May to July 2022, and (2) 22nd August to 3rd September 2022. Due to the specular reflectance of C-band signals, the backscatter from flooded areas or water bodies is significantly lower compared to other non-water areas, this enables rapid extraction of the flooded area from the SAR images23. Meticulous analysis of the pre-and post-flood images was performed to apply a parametric thresholding approach by splitting the histogram into the target and background classes to create binary maps indicating flooded and non-flooded areas24,25,26. Later, the binary images were processed to generate a flood extent map for subsequent analysis.

Delta NDVI analysis for changes in greenness and ﻿damage assessment

To assess the intensity and spatial patterns of the flood's impact on in-season crops, pre and post-flood images of Sentinel-2 were assessed to estimate the loss in greenness. The NDVI (Eq. 1), a frequently used indicator of green biomass27, was calculated using the reflectance wavebands corresponding to the Red and Near Infra-Red portion of the electromagnetic spectrum. Changes in the NDVI are related to photosynthesis and leaf cell structure which indicates a plant's vigour, greenness and productivity28

$$NDVI= \frac{{NIR}_{\sigma } - {Red}_{\sigma }}{{NIR}_{\sigma } +{ Red}_{\sigma }}$$

where, \({NIR}_{\sigma }\) denotes the NIR reflectance band and \({Red}_{\sigma }\) corresponds to the Red reflectance bands.

To analyze and understand the phenology patterns associated with crop development phases, the NDVI was derived from all the available satellite images over the study area. It was noted that greenness over the cropland rapidly increases during August indicating a critical crop development phase during this period. Therefore, to incorporate the phenological differences and to compensate for the noise in the data, maximum NDVI value composite images (22nd August-3rd September) were developed for 2021 and 2022. A delta NDVI image (Eq. 2) was derived from the pre and post-flood NDVI composite images.

$$Delta NDVI (Loss or Gain \left(\mathrm{\%}\right))= \frac{{NDVI}_{f} - {NDVI}_{n}}{{NDVI}_{n}} \times 100$$

where \({NDVI}_{f}\) and \({NDVI}_{n}\) represents post and pre-flood NDVI composite images, respectively.

This delta NDVI image measures the loss and damage to cropland biomass, where the negative values correspond to the intensity of damage to cropland greenness or biomass due to flood-water inundation or incidental rainfall, while positive values show normal conditions. The resultant difference map was divided into eight classes representing extreme damage (< − 0.50], very severe damage (− 0.5 to − 0.4], severe damage (− 0.4 to − 0.3] moderate damage (− 0.3 to − 0.2], slight damage (− 0.2 to − 0.1], very slight damage (− 0.1 to 0], near normal (0-0.1) and normal (> 0.1). The loss and damage map was masked by the cropland mask derived from the ESA's World Cover at 10 m resolution29. Later, to simplify the legend, the classes were lumped into three major classes representing severe loss (extreme damage and severe damage), mild loss (all other damage classes) and no loss (near normal and normal) for generating statistics at administrative levels. Then the percentage of loss or damage of cropland was aggregated at Tehsil and Districts level administrative boundaries for subsequent analysis. To distinguish the damage from continuous inundation and incidental rainfall, the loss and damage image was also masked by the flood extent map.

Other data sources

The cropland, non-cropland and other land use land cover masks were developed from the ESA WorldCover 10 m 2020 v100 '© ESA WorldCover project 2020/Contains modified Copernicus Sentinel data (2020) processed by ESA WorldCover consortium'. The dataset is produced with 11 classes using Sentinel-1 and Sentinel-2 data30.

The population density data were obtained from the standardized global population distribution at 1 km spatial resolution provided by the LandScan™ Global Population Distribution Dataset (ORNL)31. Other data sources and data used for this study include administrative boundaries, Agriculture sector data32, field-based damage reporting data by the Provincial Disaster Management Authority, Sindh (PDMA), and Pakistan Crop statistics: Pakistan Bureau of Statistics.

Analysis and aggregation of the data

Rigorous data analysis was performed to estimate and quantify loss and damages to cropland. The losses to agriculture and livestock were also converted to direct economic losses. For this, overlay analysis and zonal statistics of the flood extent map, NDVI loss and damage layer, incidental rainfall, and cropland masks were performed to map spatial extent and estimate area under flooded cropland, non-flooded cropland, agricultural damage due to incidental rain, severe and mild losses to the greenness of cropland. All the metrics were aggregated at district and tehsil (sub-district) boundaries to generate statistics for the administrative units. Percentage losses and damages were also calculated at the administrative units to understand the spatial spread of the flood's impacts across the province. The loss and damage to the greenness of cropland were tabulated to rank the tehsil boundaries according to the majority of pixels belonging to the severity of the loss. Furthermore, maps were produced to portray the spatial distribution of flood extent and rainfall at the country level and detailed analysis and mapping were performed at the district and tehsil levels. This analysis framework is based on combining data from multiple satellites and ground-based information to assess and understand flood-induced damage and loss to cropland and livestock, and overall economic losses. The analysis was performed using the GEE and R.

Results and discussion

Above-normal rainfall in July and August across Pakistan

The 22nd Session of the South Asian Climate Outlook Forum (SACOF-22) was held in April 2022. According to the "Consensus Statement on the Seasonal Forecast over South Asia for the 2022 Southwest Monsoon Season", the above-normal monsoon rainfall was projected in the South Asian region. An update of the consensus statement was also released in June 2022, reaffirming the extensive rainfall from July to September 2022. The national average rainfall in Pakistan for July 2022 was predominantly very high (+ 180%), with extremely high rains in Balochistan (+ 450%) and Sindh (+ 307%), the wettest for both in the last 62 years. The rainfall intensity was excessively increased in August 2022, the wettest ever August, with high above-average rainfall at the national level (+ 243%). Historically Sindh receives 150-180 mm of rainfall annually, which mostly comes in the monsoon season (July-September). Approximately six-fold rainfall was recorded in Balochistan (+ 590%) and Sindh received more than seven times the normal rainfall (+ 726%). The satellite-based rainfall estimates showed an extremely high intensity of monthly rainfall (~ 1000 mm) in the Sindh Province, nearly eight times its average rainfall in August (Fig. 1).

In August 2022, one of the most severe flash floods in the history of Pakistan was triggered due to above-normal monsoon rainfall in Balochistan, Sindh and southwest Punjab. The incidental and cascading rain-induced flooding started in July and both, rainfall intensity and flooding, progressively intensified in August which affected ~ 33 million people across the country. A sequence of flash floods started in July, and by the mid of August, one-third of the Sindh province was inundated by flood water. Moreover, the situation was further exacerbated by exceptionally high incidental rainfall (Fig. 4), for instance, 142 mm of rainfall was recorded in Naushahro Feroze District in a single day (11 August 2022), the highest monthly rainfall (1228 mm) in the province was recorded at the Padidan Town (Fig. 4) in the Naushahro Feroze District.

Flood water inundation

The flood extent mask for Pakistan (Fig. 4b) was derived from the Sentinel-1 SAR images. Detailed and aggregated flood maps were also produced for effective visualization and hotspot analysis along with population intensity maps. Nearly one-fifth (18%, 2.5 million ha) of the total land area of the province was waterlogged due to rain-induced flooding. District-level assessment of flood water inundation indicated four severely affected districts (Figs. 3, 4, 5) including Jacobabad, Larkana, Qambar Shahdad Kot, and Shikarpur, where the flooded area covered around half of the district (Figs. 4, 6). Due to the hill torrents in the Northeastern mountain ranges of Balochistan, the foothill areas in Balochistan and the north-western part of Sindh were severely affected by flash floods (Figs. 5, 6). The situation was exacerbated by the heavy rainfall in the affected areas which included Jacobabad, Kashmore, Larkana, and Shikarpur (Fig. 6). The district where the flood water inundated around one-fourth of the district included Kashmore (31.54%), Naushahro Feroze (27.05%), Matiari (24.57%), Dadu (23.82%), Badin (23.41%), and Khairpur (22.87%). Analysis of the flood extent map and cropland mask from the ESA WorldCover 10 m v100 showed that ~ 1.1 million ha of the cropland area was inundated in the Sindh Province.

Source: Pakistan Meteorological Department (PMD).

Station-based records of rainfall during August ( a) Monthly average rainfall across different weather stations in Sindh during August 2022 and historic average in August (1981-2010), ( b) daily rainfall patterns during August 2022 recorded in corresponding districts across Sindh.

(Source: GPM -IMERG satellite data), ( b) Fig. 1: Flood extent in Pakistan on 28 August 2022 based on Sentinel-satellite data (Source: Sentinel-1 satellite data, the maps were produced using the ArcGIS 10.7 ( www.esri.com).

( a) Rainfall estimates for August 2022 in Pakistan

Flood water inundation ( a) extent and patterns of flood-inundated areas in Jacobabad and Dera Murad Jamali on 28 August 2022 ( b) ground condition information.

A visual comparison of the rainfall intensity patterns (Fig. 4a) and flood extent map (Fig. 4b) indicates two distinct regions, North West of Sindh and North Eastern Balochistan, were severely affected by flood-inundated water (Fig. 5). These foothill regions lie in arid zones and are characterised by a flash floods and/or flood water inundation. The flood water inundated the foothill area and emerged as a 100 km inland water lake. Whereas central Sindh experienced the highest intensity of incidental rainfall, the amount of inundated water is comparatively less. It was also noted that the waterlogged area continued to expand through the increased water discharge at the Guddu barrage and rainwater coming through the western mountain region of Balochistan province. This caused flooding around the Indus River due to which mobility in most parts of the province became limited and access was obstructed.

Damage to cropland

Sindh's land area is ~ 14 million hectares of which ~ 35% (4.9 million ha) is used for agricultural purposes. Nationally, Sindh provides a significant proportion of summer crops including rice (42%), cotton (23%), and sugarcane (31%). The 2022 floods in Pakistan damaged the standing in-season crops, and huge quantities of grain in the storage, livestock, and infrastructure. The province is a production pocket of 14 Kharif season vegetables, 15 different fruits including major summer fruits, 5 different condiments and many cereal crops. This investigation did not estimate the specific crop type damages, nonetheless, an estimation of major crop losses and their spatial distribution was evaluated and discussed.

The mapping of flood water inundation and crop damage assessment showed that ~ 2.9 million ha (18% of Sindh's total area) was inundated and ~ 57% (2.8 million ha) of the cropland was affected (Fig. 7). The flood struck at a key phase of crop development-the initial stage of plant growth. Temporal patterns of NDVI were analysed to understand the crops' phenology patterns from June 2021 to 31st August 2022 (Fig. A1). The results indicated the critical crop development stage during August, where the NDVI values rise with a high rate of change, before reaching maturity or maximum seasonal growth (Fig. A1). A flat curve in August 2022 implied severe loss of crop greenness and damage (Fig. A1 due to flood water inundation and incidental rainfall (Fig. 3). Apart from the plant damage due to incidental rainfall at critical crop development phases, flood-induced water logging in cropland can also trigger abiotic stress in crops33 by reducing light availability34, depletion of oxygen35, and changing the chemical properties of soil36. These alterations in the environment can significantly impede crop growth, vigour and yield37,38,39.

Loss and damage to cropland based on the NDVI difference ( a) control or reference composite image, ( b) composite image acquired during a flood event, ( c) NDVI difference image indicating loss and damage to cropland. All the images were masked to cropland pixels. the maps were produced using the Google Earth Engine ( https://earthengine.google.com).

The delta NDVI maps were used to calculate the losses in greenness over the cropland. The results (Fig. 6c) were simplified into two classes indicating severe and moderate loss. It was noted that about ~ 36% of the cropland was severely affected while ~ 53% of the cropland was classified as moderately damaged. These losses included both the damages due to flood water inundation (one-third) and the remainder was directly damaged from torrential or incidental rainfall. The visual analysis of the NDVI changes (Fig. 6) along with rainfall and flood water inundation patterns suggested moderate damage to crops due to incidental rainfall but it was widely spread across the province. At the Tehsil level, the damage intensity ranges from ~ 90 to 50% (Fig. 8). According to the assessment, there were 50 Tehsils where the damage to the cropland was more than 50%. Nonetheless, it is important to discuss that the uncertainty in the NDVI-based analysis might prevail by changing the satellite images and composite period due to variation in crop development phases of the control image, emergence of herbaceous vegetation39, waterlogging tolerance of crops38, and death of the plants due to elongated flooded38. Moreover, in the mildly affected croplands, the production losses in yield could also vary with the duration of flooding and type and/or a variety of crops40,41.

Remote sensing-based vegetation indices have been used to derive indicators for crop development stages and impacts of flooding on crop growth conditions compared to pre-flood conditions42,43,44,45,46,47. Recently, a framework is developed for an integrated assessment of flood impacts on crop protection in the Yangtze River Basin39. However, this study investigated the post-flood damage at the end of the crop growing season by taking the difference in vegetation index between the normal year and flood-affected year47. Moreover, conventionally, flood impact studies neglect the effect of spatial-temporal variations and in-seasons crop damage assessment in severely flooded areas. This study developed the delta NDVI composite maps to determine the in-season crop loss by leveraging the power of GEE cloud computing and the availability of high temporal resolution of Sentinel-2 images.

Figure A2 shows rice, cotton, and sugarcane are the three major commercial crops cultivated throughout Sindh in the Summer season (Kharif crops). The distribution patterns of these primary crops in the province in very significant (Fig. A2). Interestingly, each of these crops is affected differently, for instance, the rice crop is mostly affected by the water logged in the north-western part. It is estimated that ~ 80% of the rice crop production (~ 1.9 million tons of rice) is lost due to flooding (Figs. 2, 6, 9, A2). The rice production zone was severely waterlogged due to the flooding which can extinguish plants by limiting light availability and oxygen supply. Table 1 summarises the expected loss in crop production at the district level. On the other hand, the sugarcane crop is predominantly cultivated in the northeastern districts along the Indus River. There was lesser evidence of flood water logging in the sugarcane zone, probably due to the better drainage mechanism of this side of the river and partially due to the well-grown plant of the sugarcane crop. However, the dispersed population and flooding could generate an expected loss of 61% (10.5 million tons) of the crop by the end of the crop-growing season. It was important to note that the cotton crop zone was the least inundated, nonetheless, the loss of cotton crop was significantly high due to the incidental rainfall. The hotspot of rainfall intensity was exactly over the cotton crop zone which could have severely affected the sensitive plants of the cotton crop. The total loss in cotton crop production is expected to be 88% (3.5 million bales) because of flooding and continuously exceptionally heavy rainfall. Considering the commodity prices of summer 202248, these three crops faced a direct loss of USD 1.30 billion (rice: USD 543 million, cotton: USD 485 million, sugarcane: USD 273 million).

Table 1 Expected production loss of rice, cotton and sugarcane crops in Sindh.

These estimates of production losses could be exacerbated while considering the abandoned or unattended agricultural fields due to dislocated and suffering population. It would be difficult for small farmers to immediately recover from loss which might trigger a household transition from on-farm to off-form work for livelihood49,50. Apart from the losses and damages that can be termed economic, the floods have caused more non-economic losses and damages that are difficult to assess in economic terms. These noneconomic losses may be more significant for developing countries for which such losses should become a central aspect of climate change policy. When land is lost or rendered unsuitable for agriculture the rich landowners may suffer greater losses in economic terms.

The rapid assessment loss estimates through this approach closely match with the detailed Post-Disaster Needs Assessment51 which reports cotton as the most affected crop followed by rice and sugarcane. It has been observed that rapid estimates of disaster losses for major events are more accurate than the small-scale local disaster loss events51. The true economic costs of climate change are difficult to quantify due to a lack of reliable data. The costs of climate change are often long-term and uncertain, making it difficult to accurately measure. The losses related to long-term impacts like reduction of soil productivity and indirect costs such as displacement and disruption to local economies may be difficult to quantify, while the intangible costs associated with loss and damage (such as emotional distress, loss of culture and traditional knowledge, etc.) cannot be measured.

Conclusion and recommendations

Numerous efforts are being made to reduce agriculture losses and damage to assets ahead of impending hazards by providing forecasts and early warning. However, the frequency of natural disasters has increased due to climate change and exacerbates food security issues across the globe, especially in developing economies. Therefore, apart from precise predictions of changing weather, e.g., floods, erratic and above-normal rainfall, and droughts; it is required to quickly evaluate the impacts of disasters to avoid their cascading effects. This study presented a multi-satellite/sensor-based framework to quantify the impacts of flooding, water logging and torrential/or incidental rainfall on in-season crops in the Sindh province of Pakistan. The province provides a significant portion of major crop production in the country including wheat (16%), rice (42%), cotton (23%), sugarcane (31%), vegetables and other horticulture crops.

It is equally important to translate climate-induced losses into the economic cost to quantify the benefits of the adaptation strategies. This can enable the implementation of resource allocation for a holistic climate change adaptation in public expenditure reporting. The information derived from this analytical framework can be incorporated into L&D assessment for informed decision-making not only during the catastrophe and rehabilitation of the affected people, but it can also help to timely plan for the economic losses and looming crisis of food security in the country. The framework could be extended and further developed to integrate economic losses of crop damage, loss of agriculture infrastructure and equipment and disruption in supplies and services. It is difficult to accurately attribute losses and damages to climate change due to the complexity of the climate and governance systems resulting in cumulative losses. Also, the costs of climate change are often long-term and uncertain, making it difficult to accurately measure.

References

1. Article Google Scholar

2. Thomas, V. & Lopez, R. Global increase in climate-related disasters. SSRN Electron. J. https://doi.org/10.2139/ssrn.2709331 (2015).

Article Google Scholar

3. Haq, M., Akhtar, M., Muhammad, S., Paras, S. & Rahmatullah, J. Techniques of Remote Sensing and GIS for flood monitoring and damage assessment: A case study of Sindh province, Pakistan. Egypt. J. Remote Sens. Sp. Sci. 15, 135-141 (2012).

Google Scholar

4. PMD. Government of Pakistan: Pakistan Meteorological Department-Pakistan's Monthly Climate Summary August, 2022 (2022).

5. Otto, F. E. L. et al. Climate Change Likely Increased Extreme Monsoon Rainfall, Flooding Highly Vulnerable Communities in Pakistan (2022).

6. Memon, A. A., Muhammad, S., Rahman, S. & Haq, M. Flood monitoring and damage assessment using water indices: A case study of Pakistan flood-2012. Egypt. J. Remote Sens. Sp. Sci. 18, 99-106 (2015).

Google Scholar

7. Qamer, F. M. et al. The 2022 Pakistan floods: Assessment of crop losses in Sindh Province using satellite data (2022). https://doi.org/10.53055/ICIMOD.1015.

8. Schäfer, L. & Künzel, V. Policy Brief. Steps Towards Closing the Loss&Damage Finance Gap. Recommendations for COP25 (2019). https://doi.org/10.13140/RG.2.2.30110.48964.

9. Article PubMed PubMed Central Google Scholar

10. Chakraborty, A., Srikanth, P., Murthy, C. S., Rao, P. V. N. & Chowdhury, S. Assessing lodging damage of jute crop due to super cyclone Amphan using multi-temporal Sentinel-1 and Sentinel-2 data over parts of West Bengal. India. Environ. Monit. Assess. 193, 464 (2021).

Article CAS PubMed Google Scholar

11. Huffman, G., Stocker, E., Bolvin, D., Nelkin, E. & Jackson, T. PM IMERG Final Precipitation L3 Half Hourly 0.1 degree x 0.1 degree V06 (2019). 10.5067/GPM/IMERG/3B-HH/06.

12. Chini, M. et al. SAR-based flood mapping, where we are and future challenges Luxembourg Institute of Science and Technology (LIST), Department of Environmental Research and Innovation ( ERIN ), Luxembourg , ( marco.chini@list.lu ) Vienna University of Technology. In Aust. Int. Geosci. Remote Sens. Symp. 884-886 (2021).

13. Zanaga, D. et al. ESA WorldCover 10 m 2020 v100 (2021). 10.5281/zenodo.5571936.

14. Sims, K., Reith, A., Bright, E., McKee, J. & Rose, A. LandScan Global 2021. In Population Density. Oak Ridge National Laboratory (2022). https://doi.org/10.48690/1527702.

15. JICA. Data Collection Survey on Agricultural Sector in Sindh Province in the Islamic Republic of Pakistan (Final Report) (2022). https://openjicareport.jica.go.jp/pdf/12368841.pdf.

16. Schmidhuber, J. & Tubiello, F. N. Global food security under climate change. Proc. Natl. Acad. Sci. 104, 19703-19708 (2007).

Article ADS CAS PubMed PubMed Central Google Scholar

17. Sun, L., Chen, S., Chao, L. & Sun, T. Effects of flooding on changes in Eh, pH and speciation of cadmium and lead in contaminated soil. Bull. Environ. Contam. Toxicol. 79, 514-518 (2007).

Article CAS PubMed Google Scholar

18. Article Google Scholar

19. Article Google Scholar

20. World Bank. Commodity Markets Outlook: A World Bank Report. World Bank Gr (2022). https://www.worldbank.org/en/research/commodity-markets.

Download references

Acknowledgements

This paper and material used are based upon the work supported under the SERVIR HKH program of ICIMOD. We thank the anonymous reviewers for their constructive comments and suggestions. The boundaries, names, and designations indicated on these maps do not imply the expression of any ICIMOD opinion concerning the legal status of any country, territory, city, area, their associated authorities, or demarcations of their frontiers or boundaries. The views expressed herein are solely those of the authors and do not necessarily reflect those of the organizations mentioned above.

Funding

The research was supported by the International Centre for Integrated Mountain Development (ICIMOD).

Author information

Author notes

These authors contributed equally: Faisal Mueen Qamer and Sawaid Abbas.

Authors and Affiliations

1. International Centre for Integrated Mountain Development (ICIMOD), Islamabad, Pakistan

Faisal Mueen Qamer, Abid Hussain, Sher Muhammad, Sravan Shrestha & Sunil Thapa

2. Smart Sensing for Climate and Development, Center for Geographical Information System, University of the Punjab, Lahore, Pakistan

Sawaid Abbas

3. Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong

Sawaid Abbas

4. Pakistan Agricultural Research Council (PARC), Islamabad, Pakistan

Bashir Ahmad, Muhammad Nawaz & Bilal Iqbal

5. Islamabad Policy Research Institute (IPRI), Islamabad, Pakistan

Aneel Salman

Contributions

F.M.Q., S.A.. and B.A. conceived, designed and wrote the paper. F.M.Q., and S.A. conducted the data analysis. A.H., A.S., S.M., M. N., S.S., B.I., and S. T. participated in processing, analysis, and discussion.

Corresponding authors

Correspondence to Faisal Mueen Qamer or Sawaid Abbas.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Reprints and Permissions

About this article

Cite this article

Qamer, F.M., Abbas, S., Ahmad, B. et al. A framework for multi-sensor satellite data to evaluate crop production losses: the case study of 2022 Pakistan floods. Sci Rep 13, 4240 (2023). https://doi.org/10.1038/s41598-023-30347-y
Download citation

Received:

Accepted:

Published:

DOI: https://doi.org/10.1038/s41598-023-30347-y

Get shareable link

# data[].attributes.attachment_link.title
A framework for multi-sensor satellite data to evaluate crop production losses: the case study of 2022 Pakistan floods - Scientific Reports

# data[].attributes.attachment_link.description
In August 2022, one of the most severe floods in the history of Pakistan was triggered due to the exceptionally high monsoon rainfall. It has affected ~ 33 million people across the country. The agricultural losses in the most productive Indus plains aggravated the risk of food insecurity in the country.

# data[].attributes.headline
Federal Initiatives in Reducing Emissions from Coal-Fired Power Plants

# data[].attributes.subject
Federal Initiatives in Reducing Emissions from Coal-Fired Power Plants

# data[].attributes.body
The article highlights the harmful effects of coal-fired power plants on the environment and human health and examines two federal efforts to reduce emissions. However, the critique lies in the lack of emphasis on the urgency and inadequacy of these efforts. The tax credit system for refined coal producers lacks proper oversight, leading to questionable emissions reduction claims. Additionally, the Carbon Capture and Storage (CCS) technology projects have largely failed, with significant financial overruns due to poor management decisions. More robust and ambitious solutions are needed to address the pressing climate crisis.

# data[].attributes.attachment_link.title
Federal Government Efforts to Reduce Emissions from Coal-Fired Power Plants

# data[].attributes.attachment_link.description
Coal-fired power plants release carbon dioxide, mercury, and other emissions that can harm human health. The Environmental Protection Agency (EPA) recently reported that emissions from power plants have increased from 2020 to 2021, reflecting growth in coal-fired power generation. Today's WatchBlog post looks at two of our recent reports on federal efforts to reduce emissions from coal-fired power plants.

# data[].attributes.headline
 The Impact of Coal-Based Power Plants and Mines on Public Health and Environment

# data[].attributes.subject
 The Impact of Coal-Based Power Plants and Mines on Public Health and Environment

# data[].attributes.body
The report effectively highlights Pakistan's alarming air pollution crisis, exacerbated by the expanding coal-based power generation capacity. It underscores the significant health implications of this unchecked pollution, showing the urgency of implementing stringent emission standards. However, the report could have benefited from a deeper exploration of political, societal, and economic factors contributing to the expansion of coal-based energy, and the barriers to renewable energy alternatives. Additionally, the proposed solutions could be more specific, considering the complexity of Pakistan's energy landscape. Nonetheless, it remains an important document in emphasizing the dire environmental and health consequences of Pakistan's current energy policies.

# data[].attributes.attachment_link.provider_name
Centre for Research on Energy and Clean Air

# data[].attributes.attachment_link.title
Air quality, health and toxics impacts of the proposed coal mining and power cluster in Thar, Pakistan – Centre for Research on Energy and Clean Air

# data[].attributes.attachment_link.description
A cluster of coal mines and power plants is proposed in the Thar region of Pakistan which will host 9 power plants with a total capacity of 3,700 megawatts (660 megawatt out of which has already been commissioned) and lignite coal mines. The report “Air quality, health and toxics impacts of the prop…

# data[].attributes.headline
Implications for Global Warming and Policy Recommendations for Emission Control

# data[].attributes.subject
Implications for Global Warming and Policy Recommendations for Emission Control

# data[].attributes.body
While insightful, the study critiqued herein lacks depth in addressing Pakistan's socio-economic realities driving its reliance on China-Pakistan Economic Corridor's (CPEC) coal-fired power plants. While the empirical evidence of rising CO2 emissions is alarming, the study's perspective feels limited, overlooking economic and infrastructural challenges, and potential socio-economic benefits. Its proposed solutions—transitioning to renewable energy sources, carbon capture, and tree plantation—while sound, oversimplify complexities and dismiss economic viability and political constraints. The study could benefit from a balanced, globally contextualized approach, embracing the intertwined nature of economic development and environmental sustainability. Clearer methodological exposition would enhance credibility and the inclusion of realistic mitigation measures would increase relevance.

# data[].attributes.attachment_link.readable_text
Pakistan is the seventh most vulnerable country by Global Climate Risk Index stands at the hit list of climatic hazards and to blame are anthropogenic activities. The emissions that transform our natural environment are concomitant to coal combustion in the ever growing power plants. The discharge of CO ₂ from these plants comes under the shadow of meeting the electricity demand of Pakistan's growing population (1.09% per year). It is also linked to swing the wheel of growth and development in the country (Arshad and Haidong, 2017). The efforts for energy generation are resulting in CO ₂ emissions that are posing far-reaching impacts. United Nations Framework Convention on Climate Change (UNFCCC) has identified that this accelerated emission level has been contributing directly to raise the global mean temperature of up to 2 °C annually (Zhang et al., 2014).

It is evident that Pakistan, over the past decades, contributed a low level of emission, compared to industrialized regional and world powers. By the year 2015, Pakistan contributed only 405 metric tons of greenhouse gas (mainly, CO ₂) emission in the open environment (Mir and Ijaz, 2016), which remains only 0.94% (135th global contributor) of the total global emission. Pakistan, as a signatory of the United Nations Climate Change Convention, is propelled to further reduce these emissions. Yet, on the path of prosperity and meeting the rising demand for electricity of its inhabitants has placed the country to commence Coal-Fired Power Plants (CFPPs) under China Pakistan Economic Corridor-CPEC (Hafeez, 2018).

Pakistan undersigned CPEC projects under 'one belt one road' initiative - the ever most significant foreign investment in the country, worth US$900 billion (Sehgal, 2018). Thus, CPEC stands as a model of regional cooperation in lieu of changing regional and international geopolitical coalitions for mutual interests (Abid and Ashfaq, 2015). CPEC brought electricity generation projects, amongst other e.g., transportation, fibre optics, dry ports etc. A major junk of electricity generation projects is based on (local and imported) coal with the worth of US$5.8 billion that has been executed in Baluchistan, Punjab and Sindh provinces to contribute 10,400 MW of electricity in the national grid (Ahmed, 2018; Husain and Arrfat, 2018; Rana, 2017). All such projects intend to meet the energy shortfall in the country i.e., to cover the energy deficit accounts to 6 GW.

Thus, CPEC energy generation projects, accounting up to 6% annual growth in energy, will cover the demand by injecting 10 GW to the national grid (IMF, 2017). These energy projects have an additive capacity of 4290 MW from local coal mines, whereas 5201 MW through imported coal by the year 2021 (GoP, 2013). Whereas, during the early harvest projects, these coal-fired power plants are expected to supply 7000 MW of electricity to the national grid by December 2020 (Husain and Arrfat, 2018). Thus, having met the national energy demand, CFPPs are considered to be the best game changer in the energy crisis in Pakistan (B. Khan, 2018; Mughal, 2017).

Contrarily, the energy projects under CPEC are fossil-fuel energy-based projects that use coal. Coal is already declared the major contributor of greenhouse gases, in general, and CO ₂ emissions, in particular. As coal-fired power plants are based on coal combustion, they chalk environmental concerns behind the reason that they have the potential to cause environmental degradation (Baloch, 2018), change atmospheric composition, enhance radiative forcing (IPCC, 2007), global warming, glacier melting, rise in sea level by approx. 7 m, rise in air temperature by 5.5 °C (Houghton et al., 2001), changes in the mountain cryosphere (Haeberli and Hohmann, 2008), glacier receding, glacial lakes outburst floods (GLOFs), numerous glacier lakes (Ashraf et al., 2017), degradation of agriculture, disturbance in water system (Tribune, 2017), and several non-reversible environmental costs associated to coal based power plants (Baloch, 2018). All such trends are higher than then the climatic variations in the past (Schimel et al., 2001). As a consequence, rectification to (IPCC) convention abides the countries to get rid of outdated technology (e.g., China already has closed the biggest CFPP in February 2017) and shift to clean energy sources (Malik, 2017).

The UNFCCC commits to stabilize CO ₂ emissions, before it becomes inevitable to shift to renewable energy sources and simultaneously keeping a systematic record of the emission trends. In this sense, UNFCCC obliges countries parties to develop their emission inventories (UNFCCC, 1992). In response, Pakistan developed its first emissions' inventory in 1994, second inventory in 2008, third in 2012 and (last) fourth in 2015. These inventories were compiled by Global Climate Impact Study Centre (GCISE) to fulfil the requirement of Intended Nationally Determined Contributions (INDCs). These are according to the obligations of COP-21 negotiations (Lin and Ahmad, 2017). These inventories calculated emissions from five sectors, namely; energy, agriculture, industrial processes, waste and land use change, and forestry (ADB, 2018; Mir and Ijaz, 2016). It is reported that in-total 405.06 Mt CO ₂ per year were released in 2015, corresponding to 1.35 °C rise in global mean temperature (GMT) (Table 1). There is non-existent of emission record afterwards, which poses concerns on the current and anticipated level of emissions in case of Pakistan (Aggarwal et al., 2017; Allen, 2018; Mir and Ijaz, 2016). It also poses disquiets as increased level of emissions have global and regional impacts on humans and beyond.

The coal-fired power plants in Pakistan are based on local abundant coal resources, estimated up to 185 billion tons, of which 95% coal is situated in the Thar coal fields (Sindh province) (GoP, 2004). So, to meet the energy shortages and lack of expensive technology to extract energy from renewable energy sources (e.g., solar, wind, tidal etc.) pulled Pakistan to install coal-fired power plants through CPEC. Initially, it was planned that all CFPPs are to be carried out through 'modern and up-to-date ultra-supercritical emission reducing as well as emission capturing technology' i.e., extensive electricity generation along with protective measure (E&T, 2017), baghouse filters or electrostatic precipitators (ESP) with removal efficiencies up to 99.9% or Low NOx Burner Technology (LNBT) with the efficiency of 40-60% (Lonsdale et al., 2012). However, none of CFPPs have used an advanced or ultra-supercritical technology to reduce carbon emissions, carbon capture and carbon sequestration to remove CO ₂ from the emissions (Siddiqui, 2018).

Furthermore, the plan of Carbon Capture and Storage (CCS) to reduce CO ₂ emissions between 50 and 80% (Viebahn et al., 2015) could not be attained. Also, the installation of environment protection equipment, i.e., dedusting, desulfurization, denitration and high-efficiency electrostatic precipitator and flue gas desulfurization facilities (CPEC-Portal, 2017a; 2017b; Khan, 2017; Xu et al., 2011), as planned before the execution of the plants, are seldom deployed. Likewise, other plans were also remained un-realized that had pledged to reduce pollutants through efficient usage of 6th world's largest carbon reserves and an increased energy capacity between 13 and 15%, more than China, India and USA altogether (DAWN, 2017a; E&T, 2017; IET, 2017). Furthermore, it was declared that this new technology will keep the emissions to its minimum level to mitigate environmental degradation (Power-China, 2017), which is coupled with 'no harm' to freshwater and marine lives (CPEC-Portal, 2017a). But, unprecedented carbon emissions are posing horrific environmental impacts (Munir and Khayyam, 2020; Siddiqui, 2018), besides badly damaging the (earlier) Pakistan international image as one of the lowest-carbon emitters (Shaikh and Tunio, 2017).

Along the way, air pollution and rising temperature in the country have amplified the complexity of CFPP operations and pledged controlled CO ₂ emissions. In view of no environmental impacts assessment and operationalisation of the CFPPs have already started posing a great concern for the fragile national and global environment. The local concerns on the amplified emissions are coupled with experts' view from think-tanks. Woodrow-Wilson Centre-Asia program has pointed out that pollutant gases (90% CO ₂) from CFPPs have the potential to damage air quality, destruction to farmland and excessive groundwater abstraction in the water scared region of Thar (also expected to run out of water by 2025) (Tribune, 2017). They are coupled with experts of Asian Development Bank concerning that 10 GW energy projects under CPEC are expected to increase CO ₂ emissions substantially and will affect efforts towards climate change mitigation (ADB, 2018). In the debate, the concerned federal institution (i.e., Ministry of Climate Change of Pakistan) has shown concerns of air quality degradation due to emissions from these plants (DAWN, 2017b). The thick layer of Smog (high concentration of Ozone) during summer 2018 and 2019 over in Punjab and Sindh provinces is a clear sign of air pollution due to emissions and ash disposal openly into the air. Thus, the absence of emission inventory after 2015 and meanwhile installation of such giant energy projects calls to record CO ₂ emission scenarios due to CFPPs and measurement of extent of air contamination that result in rise in global mean temperature (GMT). Secondly, this research study tires to forecasts emission scenario to plot rise in GMT till 2050 to sensitize the concerned national and global stakeholders, and actors to take prompt mitigative measures. Thus, the research questions this study tries to answer are:

1.
What is the level of CO ₂ emissions due to Coal-Fired Power Plants under CPEC funding?

2.
What is the level of projected rise in the temperature due to CO ₂ emissions of CFPPs?

# data[].attributes.attachment_link.title
Energy production and CO2 emissions: The case of coal fired power plants under China Pakistan economic corridor

# data[].attributes.attachment_link.description
Pakistan stands as the seventh most vulnerable country in the debate of climate change. The trail of changes occurring in the natural climate in the c...

# data[].attributes.headline
Environmental Impact of Coal Mining Challenges and Mitigation Strategies

# data[].attributes.subject
Environmental Impact of Coal Mining Challenges and Mitigation Strategies

# data[].attributes.body
The article comprehensively details the environmental impact of coal mining and burning, from land and water pollution to greenhouse gas emissions. It acknowledges the industry's mitigation efforts, such as scrubbers and adherence to environmental laws, but it does not emphasize their relative insufficiency. The need for a shift towards sustainable energy and socio-economic considerations for mining communities is also inadequately addressed. While informative about the ecological consequences of coal, the piece could better prompt decisive action towards greener energy alternatives.

# data[].attributes.attachment_link.readable_text
Coal is an abundant fuel source that is relatively inexpensive to produce and convert to useful energy. However, producing and using coal affects the environment.

Effects of coal mining

Surface mines (sometimes called strip mines) were the source of about 62% of the coal mined in the United States in 2021. These mining operations remove the soil and rock above coal deposits, or seams. The largest surface mines in the United States are in Wyoming's Powder River Basin, where coal deposits are close to the surface and are up to 70 feet thick.

Mountaintop removal and valley fill mining has affected large areas of the Appalachian Mountains in West Virginia and Kentucky. In this form of coal extraction, the tops of mountains are removed using explosives. This technique changes the landscape, and streams are sometimes covered with rock and dirt. The water draining from these filled valleys may contain pollutants that can harm aquatic wildlife downstream. Although mountaintop mining has existed since the 1970s, its use became more widespread and controversial beginning in the 1990s.

U.S. laws require that dust and water runoff from areas affected by coal mining operations must be controlled, and the area must be reclaimed close to its original condition.

Underground mines generally affect the landscape less than surface mines. However, the ground above mine tunnels can collapse, and acidic water can drain from abandoned underground mines.

Methane gas that occurs in coal deposits can explode if it concentrates in underground mines. This coalbed methane must be vented out of mines to make mines safer places to work. In 2020, methane emissions from coal mining and abandoned coal mines accounted for about 7% of total U.S. methane emissions and about 1% of total U.S. greenhouse gas emissions (based on global warming potential). Some mines capture and use or sell the coalbed methane extracted from mines.

Emissions from burning coal

Sulfur dioxide (SO₂), which contributes to acid rain and respiratory illnesses

Nitrogen oxides (NOx), which contribute to smog and respiratory illnesses

Particulates, which contribute to smog, haze, and respiratory illnesses and lung disease

Carbon dioxide (CO₂), which is the primary greenhouse gas produced from burning fossil fuels (coal, oil, and natural gas)

Mercury and other heavy metals, which have been linked to both neurological and developmental damage in humans and other animals

Fly ash and bottom ash, which are residues created when power plants burn coal

The U.S. Energy Information Administration estimates (as of October 2022) that in 2021, CO ₂ emissions from burning coal for energy accounted for about 20% of total U.S. energy-related CO ₂ emissions and for nearly 60% of total CO ₂ emissions from the electric power sector.

In the past, fly ash was released into the air through the smokestack, but laws now require that most emissions of fly ash be captured by pollution control devices. In the United States, fly ash and bottom ash are generally stored near power plants or placed in landfills. Pollution leaching from coal ash storage and landfills into groundwater and several large impoundments of coal ash that ruptured are environmental concerns.

Reducing the environmental effects of coal use

The Clean Air Act and The Clean Water Act require industries to reduce pollutants released into the air and water.

The coal industry has found several ways to reduce sulfur and other impurities from coal. The industry has also found more effective ways of cleaning coal after it is mined, and some coal consumers use low sulfur coal.

Power plants use flue gas desulfurization equipment, also known as scrubbers, to clean sulfur from the smoke before it leaves their smokestacks. In addition, the coal industry and the U.S. government have cooperated to develop technologies that can remove impurities from coal or that can make coal more energy efficient, which reduces the amount of coal that is burned per unit of useful energy produced.

Equipment intended mainly to reduce SO ₂, NOx, and particulate matter can also be used to reduce mercury emissions from some types of coal. Scientists are also working on new ways to reduce mercury emissions from coal-burning power plants.

Research is underway to address emissions of CO ₂ from coal combustion. One method is carbon capture, which separates CO ₂ from emissions sources and recovers it in a concentrated stream. The CO ₂ can then be injected underground for permanent storage, or sequestration.

Reuse and recycling can also reduce the environmental effects of coal production and use. Land that was previously used for coal mining can be reclaimed and used for airports, landfills, and golf courses. Waste products captured by scrubbers can be used to produce products such as cement and synthetic gypsum for wallboard.
Last updated: November 16, 2022

# data[].attributes.attachment_link.title
Coal and the environment - U.S. Energy Information Administration (EIA)

# data[].attributes.attachment_link.description
Environmental issues, effects, benefits, and impacts of producing and using coal for energy.

# data[].attributes.headline
A Comprehensive Strategy for Addressing Climate Change in Pakistan

# data[].attributes.subject
A Comprehensive Strategy for Addressing Climate Change in Pakistan

# data[].attributes.body
Pakistan, highly vulnerable to climate change impacts, needs urgent action from both government and individuals. The government should implement afforestation programs, devise waste management strategies, ban diesel vehicles in mountainous regions, switch to renewable energy, and prioritize climate change in development plans. Citizens can actively participate in climate advocacy, talk more about climate change, volunteer in related initiatives, reduce food waste, save energy, and share their climate stories. Though the impacts are severe, including flash floods, heatwaves, water scarcity, and displacement, proactive measures at various scales can mitigate the crisis and help cope with eco-anxiety.

# data[].attributes.attachment_link.title
A few ways to combat climate change in Pakistan

# data[].attributes.attachment_link.description
It is time to shun passivity and take an active part in climate advocacy.

# data[].attributes.headline
Review and Recommendations for Improvement on Pakistan's Energy Dynamics and Thar Coal Exploitation

# data[].attributes.subject
Review and Recommendations for Improvement on Pakistan's Energy Dynamics and Thar Coal Exploitation

# data[].attributes.body
The article discusses Pakistan's energy predicament and the potential of Thar coal. It explores the application of Circulating Fluidized Bed Combustion technology, presents a mathematical model for power generation and carbon emissions, and examines economic implications. The piece could benefit from exploring the technology's challenges, and the model doesn't account for real-world variables. The economic and environmental benefits of Thar coal are discussed, but the article lacks a comprehensive evaluation of carbon emissions' impact on climate change. The inclusion of a cost-benefit analysis accounting for social, environmental, and health implications would enrich the discussion.

# data[].attributes.body
This paper examines the viability of coal power in Pakistan, integrating statistical data and a SWOT-Delphi approach. It illuminates the energy needs, environmental challenges, and potential benefits of using indigenous coal resources. Despite its depth, the paper underexplores alternative renewable technologies and lacks a robust contextualization of Pakistan's specific socioeconomic and infrastructural aspects. Thus, while contributing to energy discourse, it lacks balance and specificity in its actionable strategies, underscoring the need for a more comprehensive look at Pakistan's energy future.

# data[].attributes.headline
Impact of coal quality on power plant and environment: assessment of physiochemical and ash composition of Thar coal from Pakistan

# data[].attributes.subject
Impact of coal quality on power plant and environment: assessment of physiochemical and ash composition of Thar coal from Pakistan

# data[].attributes.body
This study investigates the feasibility of utilizing Thar lignite coal, the world's seventh-largest reserve, for power generation in response to Pakistan's severe energy shortages. Characterizing 80 coal samples from Block II, the research highlights Thar coal's favorable properties, including a mean calorific value of 3030.0 kcal/kg and low-moderate sulfur content, making it a potential future fuel source. The report emphasizes the importance of advanced technologies, such as circulating fluidized bed combustors and clean coal technologies, to minimize environmental impacts associated with coal combustion. Overall, the study contributes valuable insights into leveraging local resources for sustainable energy solutions while addressing environmental concerns.

# data[].attributes.body
The reflective analysis emphasizes that human activities are the primary driving forces behind climate change. It highlights the significant impact of industrialization, deforestation, and fossil fuel combustion on the rise in greenhouse gas emissions, leading to fundamental changes in the Earth's climate system. The analysis underscores the urgent need for awareness and responsibility, calling for collective action to adopt sustainable practices, transition to renewable energy, and implement stringent environmental policies. It emphasizes the interconnectedness between human behavior and the delicate balance of the planet's ecosystems, reinforcing the imperative for a widespread commitment to mitigating the adverse effects of climate change and promoting harmonious coexistence with the environment.

# data[].attributes.attachment_link.title
Causes and Effects of Climate Change | National Geographic

# data[].attributes.headline
Exploitation of Thar coal field for power generation in Pakistan: A way forward to sustainable energy future

# data[].attributes.subject
Exploitation of Thar coal field for power generation in Pakistan: A way forward to sustainable energy future

# data[].attributes.body
The abstract presents a mathematical framework for estimating power production from the vast coal reserves in the Thar desert of southeast Pakistan. It highlights the region's significant coal capacity, positioning it as the largest coalfield in Asia. The paper projects an annual TWh energy production from Thar coal between 2020 and 2040, with a focus on achieving a 40% share of coal in the total energy mix by 2040. The findings suggest that Thar coal has the potential to generate 100,000 MW of power for the next 250 years, with specific energy production figures for 2020, 2032, and 2040. Importantly, the abstract claims negligible negative impacts on the environment. The long-term energy planning proposed is framed as a means to attract foreign investment and meet Pakistan's energy needs for sustainable development.

# data[].attributes.headline
Proximate analysis of Lakhra coal power plant and its health and environmental impact

# data[].attributes.subject
Proximate analysis of Lakhra coal power plant and its health and environmental impact

# data[].attributes.body
The report provides a insightful analysis of Pakistan's energy landscape, with a focus on the utilization of coal for electricity generation. Despite being rich in coal resources, the country currently contributes only 10% of its electricity to the national grid from coal-fired power plants, with major reliance on other sources such as hydropower, LNG, furnace oil, and natural gas. The report highlights the historical significance of Lakhra as the largest coal field, characterized by brown lignite coal with high ash and sulfur contents, posing environmental and health concerns. The study reveals a stark contrast between the properties of unwashed and washed coal, emphasizing the positive impact of washing on reducing ash, sulfur, and enhancing heating value. Importantly, the findings indicate that using washed coal from Lakhra is not only more environmentally friendly, with lower emissions of hazardous gases and particles, but also economically advantageous for electricity production, suggesting a potential shift towards more sustainable and cost-effective energy practices. This reflective report underscores the significance of adopting cleaner technologies and optimizing coal resources to meet energy needs while mitigating environmental and health risks.

# data[].attributes.attachment_link.title
Environmental impact study of Lakhra power project conducted

# data[].attributes.attachment_link.description
Assessment shows improvement in ambient air quality, increased socio-economic benefits to community.